EFFECT OF BUSINESS COACHING ON GROWTH AND PERFORMANCE AND THE MODERATING ROLE OF COMPETITIVE ADVANTAGE IN SMALL MEDIUM ENTERPRISES IN MALAYSIA

AZIZAN OSMAN

ASIA e UNIVERSITY 2022

EFFECT OF BUSINESS COACHING ON GROWTH AND PERFORMANCE AND THE MODERATING ROLE OF COMPETITIVE ADVANTAGE IN SMALL MEDIUM ENTERPRISES IN MALAYSIA

AZIZAN OSMAN

A Thesis Submitted to Asia e University in Fulfilment of the Requirements for the Doctor of Philosophy (Business Administration) July 2022

ABSTRACT

High-impact growth is vital to the survival and sustainability of all small and medium enterprises (SMEs). Unfortunately, most SMEs' leaders do not invest sufficient time and resources in building employee competencies and assuring their organisations' high-impact growth. In Malaysia, an inadequacy of business coaching in the nation's SMEs necessitates more research into the effects of business coaching on the highimpact growth of SMEs. This study aimed to examine the effects of motivation, productivity, job satisfaction, innovation, and business model innovation on the growth and performance of SMEs in Malaysia and the moderating role of competitive advantage. A positivist philosophical approach was employed to investigate the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs. Besides, this study adopted a causal research design. A survey questionnaire was utilised to collect data from respondents, while structural equation modelling was employed to analyse the data. According to the study's findings, motivation, productivity, innovation, and improved business model innovations positively and significantly influence the growth and performance of Malaysian SMEs. The study's findings also revealed that comparative advantage has a positive and significant influence on Malaysian SMEs' growth and performance. The findings of this study enlighten SME leaders in Malaysia and other stakeholders on the value of business coaching on the growth and performance and the key role of competitive advantage in Malaysian SMEs. The findings also have critical implications for business coaching among SMEs. The study posits that Malaysian SME leaders should promote motivation, productivity, job satisfaction, innovation, and improved business model innovations in their businesses to realise improved growth and performance. Keywords: Business coaching, small and medium-sized enterprise (SME), high-impact growth

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APPROVAL

This is to certify that this thesis conforms to acceptable standards of scholarly presentation and is fully adequate, in quality and scope, for the fulfilment of the requirements for the degree of Doctor of Philosophy (Business Administration). The student has been supervised by: Assoc. Prof. Dr. Wan Sabri Wan Hussin. The thesis has been examined and endorsed by:

Professor Dr. AAA Position University Examiner 1

Professor Dr. AAA Position University Examiner 1

Professor Dr. AAA Position University Examiner 1

This thesis was submitted to Asia e University and is accepted as fulfilment of the requirements for the degree of Doctor of Philosophy (Business Administration).

……………………………… Professor Ts. Dr. Titik Khawa Abdul Rahman Asia e University Dean, School of Graduate Studies [Date]

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DECLARATION

I hereby declare that the thesis submitted in fulfilment of the PhD degree is my own work and that all contributions from any other persons or sources are properly and duly cited. I further declare that the material has not been submitted either in whole or in part for a degree at this or any other university. In making this declaration, I understand and acknowledge any breaches in this declaration constitute academic misconduct, which may result in my expulsion from the programme and/or exclusion from the award of the degree.

Name: Azizan Osman

Signature of Candidate:

Date: 1 July 2022

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Copyright by Asia e University

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ACKNOWLEDGEMENTS

I wish to thank Allah for giving me the grace and strength to complete my thesis. I want to dedicate my thesis and present my sincere thankfulness to my late supervisor, Associate Professor Dr Wan Sabri Wan Hussin, who passed away recently, for his great role in my life and his numerous advice during my PhD journey. I offer my heartfelt gratitude to him, who persistently and meticulously led and corrected my work. I will be ever grateful for his assistance. I would also like to thank Asia e-University, notably the School of Graduate Studies, for supporting me during course work and allowing me to complete my thesis professionally. I also thank my peers for their assistance in refining my PhD thesis.

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TABLE OF CONTENTS ABSTRACT APPROVAL DECLARATION ACKNOWLEDGEMENTS TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS CHAPTER 1

INTRODUCTION Introduction 1.1.1 Background of the Study 1.1.2 Brief Perspective on SMEs in Malaysia 1.1.3 SMEs Growth and Performance Problem Statement Research Aim and Objectives 1.3.1 Justification of the Research Objectives Research Question Rationale of the Study Significance of the Study Scope of the Study Structure of the Thesis Summary

CHAPTER 2

LITERATURE REVIEW Introduction Review of the Relevant Theories Underlying Theories 2.3.1 Biggs' Presage-Process-Product Model 2.3.2 Resource-Based View (RBV) Theory 2.3.3 The GROW Model 2.3.4 The CLEAR Model Business Coaching Small and Medium-Sized Enterprises (SMEs) Firm Growth Conceptualisations SMEs with Rapid Growth Development Requirements of SMEs Growth and Performance of SMEs Business Development as a Structural Factor SMEs Market Growth Influence of Business Coaching on the Growth and Performance of SMEs Empirical Review 2.13.1 Effect of Motivation on Growth and Performance of SMEs 2.13.2 Effect of Coaching Improved Productivity on Growth and Performance of SMEs

ii iii iv vi vii x xi xii 1 1 1 3 9 11 16 16 18 19 25 25 26 27 29 29 29 34 34 37 45 52 54 60 61 64 69 74 77 82 87 89 89 96 vii

2.13.3 Effect of Job Satisfaction on Growth and Performance of SMEs 2.13.4 Effect of Innovation on Growth and Performance of SMEs 2.13.5 Impact of Improved Business Model Innovation on Growth and Performance of SMEs 2.13.6 Moderating Role of Competitive Advantage on HighImpact SME Growth Conceptual Framework 2.14.1 Explanation of the Conceptual Framework Research Gaps Summary of the Literature Review CHAPTER 3

RESEARCH METHODOLOGY Introduction Research Paradigm Research Methodology Method Outline Research Onion Research Philosophy Justification of the Pragmatic Philosophy Research Approach Justification of the Deductive Approach Research Design Justification of the Descriptive Design Data Collection Method Justification of the Primary Data Collection Method Research Method Sampling Method and Sample Size Data Analysis Method Justification of the Quantitative Data Analysis Method Data Screening 3.18.1 Outliers Investigation 3.18.2 Test of Normality 3.18.3 Multicollinearity 3.18.4 Validity and Reliability Structural Equation Modelling (SEM) 3.19.1 PLS-SEM vs CB-SEM Comparison 3.19.2 The Algorithm of PLS-SEM 3.19.3 Evaluation of Measurement Model 3.19.4 The Evaluation of the Structural Model Ethical Considerations Summary Capability of the Researcher

CHAPTER 4

RESEARCH FINDINGS Introduction Demographic Characterisation of the Respondents 4.2.1 Response Rate

101 105 112 120 128 130 130 132 133 133 133 134 136 136 137 142 142 144 144 146 146 148 148 150 150 151 151 155 156 159 159 163 164 170 171 174 175 176 177 178 178 178 178 viii

4.2.2 Age 4.2.3 Highest Level of Education Test of Normality Outlier Detection Test of Linearity Multicollinearity Reliability and Validity Model Fit Assessment Testing Hypotheses Summary CHAPTER 5

DISCUSSION AND CONCLUSIONS Introduction Discussion of the Results 5.2.1 Effect of Motivation on Growth and Performance of SMEs 5.2.2 Effect of Improved Productivity on Growth and Performance of SMEs 5.2.3 Effect of Job Satisfaction on Growth and Performance of SMEs 5.2.4 Effect of Innovation on Growth and Performance of SMEs 5.2.5 Effect of Improved Business Model Innovation on Growth and Performance of SMEs 5.2.6 Moderating Role of Competitive Advantage on HighImpact SME Growth Summary Conclusions Implications for Practitioners Limitations Recommendations for Further Research

REFERENCES APPENDICES Appendix A: Timeframe Appendix B: Informed Consent Form Appendix C: Email Invitation for Recruitment Appendix D: Email Questionnaire

179 180 180 182 183 184 188 190 195 197 198 198 198 200 206 210 212 220 224 229 231 233 235 235 236 314 314 316 319 320

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LIST OF TABLES

Table

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Table 2.1: Definition of the variables

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Table 2.2: Summary of the research gaps

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Table 4.1: Normality test

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Table 4.2: Outlier detection test

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Table 4.3: Test of linearity

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Table 4.4: Multicollinearity test results

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Table 4.5: Test results for reliability and validity

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Table 4.6: Discriminant validity - Henseler criterion (HTMT)

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Table 4.7: Test of R Square

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Table 4.8: Model fit indices

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Table 4.9: Path coefficients

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Table 4.10: The summary of the findings

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LIST OF FIGURES

Figure

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Figure 1.1: Percentages of SMEs in Malaysia by 2020

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Figure 1.2: Percentages of total SMEs

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Figure 1.3: Structure of the study

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Figure 2.1: Biggs' Presage-Process-Product model

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Figure 2.2: Whitmore's GROW Model

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Figure 2.3: Conceptual framework

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Figure 4.1: Respondents’ gender

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Figure 4.2: Respondents’ age

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Figure 4.3: Respondents’ highest level of education

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Figure 4.4: The structural model

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LIST OF ABBREVIATIONS

3P

Presage-Process-Product

ADF

Asymptotic Distribution Free

AMOS

Analysis of a moment structures

AVE

Average variance extracted

BMI

Business model innovation

CB-SEM

Covariance-based structural equation modelling

CEOs

Chief Executive Officers

CFA

Confirmatory factor analysis

CLEAR

Contracting, Listening, Exploration, Action, Review

d_G

Geodesic distance

d_ULS

Squared Euclidean distance

EFA

Exploratory factor analysis

EM

Expectation maximisation

EQS

Equation modelling software

ERG

Existence-Relationship-Growth

GDP

Gross domestic product

GoF

Goodness of fit

GROW

Goal, Reality, Options, Will

HTMT

Heterotrait-monotrait ratio

IMF

International Monetary Fund

KMO

Kaiser-Mayer-Olkin

LISREL

Linear structural relations

MAR

Missing at random

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MCAR

Missing completely at random

MFP

Multi-factor productivity

MI

Multiple imputations

MNAR

Missing not at random

MVA

Missing value analysis

NFI

Normed Fit Index

OECD

Organisation for Economic Co-operation and Development

PLS

Partial least squares

PLS-SEM

Partial least squares structural equation modelling

RBV

Resource-based view

RMSR

Root means square residual

SAS

Statistical Analysis System

SEM

Structural equation modelling

SMEs

Small and medium-sized enterprises

SPSS

Statistical Package for the Social Sciences

SRMR

Standardised root means square residual

VIF

Variance inflation factors

VRIN

Valuable, rare, inimitable, non-substitutable

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CHAPTER 1 INTRODUCTION

Introduction This chapter evaluates the study's background and outlines the problem statement, research aims and objectives, research hypotheses, study rationale, the study scope, and a summary of the thesis structure.

1.1.1 Background of the Study Small and medium-sized enterprises (SMEs) and the economic development of a nation are dependent on growth. The SME sector is the engine that drives the economy (Eggers, 2020). In addition, SMEs are critical to economic growth, particularly for developing nations such as Malaysia, which seek to be innovationdriven (Hanifah et al., 2019). Thus, the expansion of SMEs is significant because it influences the economy. Bayraktar and Algan (2019, p. 56) noted that SMEs constitute most of the global business sector. Consequently, governments must prioritise growth and expansion. The authors highlighted that SMEs are crucial economic drivers as they promote innovation, employment, poverty alleviation, the creation of jobs, and economic growth. Research by the World Trade Organisation revealed that SMEs account for 90% of the company population and 60 to 70% of worldwide job prospects (World Trading Organisation, 2016). The research disclosed that SMEs contribute 55% of the gross domestic product (GDP) in emerging economies. The World Trade Organisation highlighted that SMEs are potential global traders. As a result, SME growth is crucial not only for a nation but also for the global economy as a whole. Consideration of SMEs is crucial since they play critical social and economic

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responsibilities (Bayraktar & Algan, 2019, p. 56). Furthermore, the growth of SMEs depends on innovation and ingenuity (Halim et al., 2019, p. 16). Thus, SMEs must be innovative and expand their competence to increase their economic competitiveness. In fact, Erdin and Ozkaya (2020) stressed that SMEs contribute to the socioeconomic growth of a nation by providing more flexible options than other economic sectors. They further argued that SMEs are crucial for the economy since they contribute greatly to deploying new technologies, hence producing disruptive innovation in the market. Chen et al. (2017, p. 140) asserted that disruptive innovation has become vital for the growth and development of SMEs. The authors emphasised that SMEs may not experience development owing to technological disruption and a lack of innovation. Disruptive innovation does not result in superior products but rather facilitates the sustainable expansion of SMEs. A strong probability exists that SMEs which implement disruptive innovation will experience growth and obtain a market edge. Kumar et al. (2019, p. 334) suggested that management training is essential for SMEs to fulfil their company objectives. As a matter of fact, SMEs concentrate on profit maximisation and revenue expansion (Hughes et al., 2018). Chen et al. (2017, p. 145) concurred that SMEs should prioritise profit maximisation to secure their continued existence. Profit reflects the corporate expansion and organisational performance. The authors also asserted that SMEs might increase their profits by employing forward-looking strategies that emphasise new product creation and improvement. Product enhancement increases organisational success (Sivakumar & Feng, 2019, p. 27), boosts client reaction, and ultimately contributes to growth. Therefore, SMEs should continuously make product enhancements by conceptualising consumer perceptions and formulating relevant tactics in order to promote sustainable growth.

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Byrne et al. (2016) suggested that small and medium-sized business management greatly impacts their overall success. Likewise, M'zungu et al. (2017) concurred that brand management impacts SME performance. Positive management fosters inventiveness and originality, influencing an organisation's operational and strategic views. Organisational performance is driven by effective management. Child et al. (2017) observed that SME owners are required to handle numerous company facets, including operations, branding, marketing, business administration, and personnel management. These facets significantly impact the overall success of SMEs. Thus, SME owners must conduct regular appropriate training and coaching to enhance company management (Sung et al., 2016). Training is essential for increasing SME owners' passion for coaching and training sessions, which relates directly to their mediocre performance or failure (Pham & Nguyen, 2017). Employees lack the skills, knowledge, competencies, and capacities necessary to perform their job duties effectively or to operate according to SMEs' expectations due to the lack of enthusiasm of SME owners for staff training or coaching. The lack of passion exhibited by SME owners has had a detrimental effect not only on individual employee performance but also on the overall performance of SMEs. These two categories of performance can be associated with the success of SMEs based on the efficacy of their owners in managing important business operations (Bin Atan et al., 2015). Business owners must provide necessary training and mentoring to their employees.

1.1.2 Brief Perspective on SMEs in Malaysia The International Monetary Fund (IMF) placed Malaysia's economy sixth in South-East Asia and 39th worldwide (Kamaruddin & Shamsudin, 2021). SMEs in 3

Malaysia are vital to the nation's economic progress. Hence, Malaysian SMEs have made substantial contributions to employment, revenue, and economic growth. According to Bank Negara Malaysia (Central Bank of Malaysia), there are three definitions of SME in Malaysia (WeCorporate, 2021). For instance, SMEs can be categorised by yearly sales volume, personnel count, and paid-in capital. Malaysian SMEs have been defined by three institutions: the Central Bank of Malaysia, Lembaga Hasil Dalam Negeri (the Malaysian tax office), and the Malaysian Ministry of Human Resources. According to The Central Bank of Malaysia, SMEs may be further divided into two categories: manufacturing and services and other sectors. Micro firms in the manufacturing sector must have yearly sales of less than RM300,000 or employ less than five people. Besides, the number of employees in SMEs must range from five to 75, or full-time employees must be between 75 and 200. These SMEs contribute around RM521.7 billion to the nation's GDP. In addition, Malaysian SMEs account for about 66.2% of all job possibilities. As reported by SME Corporation Malaysia (2020), SMEs may be identified based on yearly revenue, staff headcount, and paid-in capital. WeCorporate (2021) reaffirmed the Central Bank of Malaysia's definition of SMEs, which specifies that SMEs in the manufacturing sector are firms with annual sales of less than RM50 million or less than 200 full-time workers. The annual sales of service-sector SMEs should not exceed RM20 million, nor should the number of full-time workers exceed 75. Additionally, the Malaysian Tax Authority or Lembaga Hasil Dalam Negeri (Malaysia Tax Return Agency) defines an SME as a firm with a paid-up capital of RM2.5 million or less and a relationship to a firm with a paid-up capital of more than RM2.5 million. The Malaysian Ministry of Human Resources classified SMEs in terms of their workforce by stipulating that micro firms must have less than 75 employees. For small businesses,

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the number of employees should range between 76 and 200, while employees for medium-sized businesses should be less than 200.

Profile of Malaysian SMEs In 2020, a total of 1,151,339 SMEs were present in Malaysia, constituting 97.2% of all business enterprises (SME Corporation Malaysia, 2021). The figures suggest that the number of SMEs in Malaysia has expanded by 4.9% annually since 2015. Notably, more than 80% of all SMEs are located in the services industry, which has steadily and continuously witnessed growth. In 2020, 85.5% of all small and medium-sized businesses, or 984,643, operated in the service industry. The percentage of SMEs in the construction industry climbed to 7.4%, or 85,637 businesses. Approximately 5.1% of small and medium-sized businesses, or 58,439 businesses, were involved in manufacturing. The proportion of SMEs in the agriculture industry was 1.7% or 19,130 businesses. In the mining and quarrying industry, there were 3,490 SMEs or 0.3%. The percentage of SMEs in the services, construction, manufacturing, agricultural, mining, and quarrying industries is depicted in Figure 1.1 below.

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Source: SME Corporation Malaysia (2021)

Figure 1.1: Percentages of SMEs in Malaysia by 2020

Percentage of Total SMEs Microenterprises in Malaysia accounted for 78.4% in 2020, which comprised 903,174 micro-enterprises (SME Corporation Malaysia, 2021). In the last few years, the SME industry in Malaysia has witnessed considerable growth. From 2015 to 2020, there was an increase of 209,504 micro-enterprises, with an annual growth rate of 5.4%. For instance, SMEs in the mining and quarrying industry exhibited the highest growth with 6.6%, followed by SMEs in agriculture (5.6%) and construction (5.6%) industries. Additionally, SMEs in the manufacturing industry grew by 5.0%, followed by the service industry (0.9%).

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Source: SME Corporation Malaysia (2021)

Figure 1.2: Percentages of total SMEs by Industry

Topimin and Hashim (2021, p.8) stated that Malaysian enterprises are classified as micro, small, medium, and big. According to SME Corp (2017), 920,624 businesses existed in Malaysia in 2016. Of the total amount, 693,670 were microbusinesses, followed by 192,783 small businesses, 20,612 medium enterprises, and 13,559 big businesses. Therefore, micro and small enterprises in Malaysia account for 75.4% + 20.9% = 96.3% of all firms in Malaysia. These figures suggest that almost all Malaysian businesses are SMEs, highlighting their importance to the country's economic growth. Chuah and Thurusamry (2021) described that Malaysian SMEs are characterised by the number of workers or yearly sales volume. The authors defined SMEs as companies with less than five full-time workers or annual revenue of less than RM300,000. In addition, the authors defined SMEs as organisations with between five and 75 workers or an annual sales turnover between RM300,000 and RM15 million. The authors further classified small firms as organisations with between five and 30 workers or yearly revenues between RM300,000 and RM3 million. According 7

to SME Corp (2017), 89.2% of Malaysian SMEs specialise in the service business, notably wholesale and retail commerce, while the remaining 20.4% specialise in the food and beverage services business. Topimin and Hashim (2021) stressed that SMEs in Malaysia have been crucial in creating employment possibilities for the public. SMEs offered 66.2% of job possibilities, increased the nation's production levels, contributed significantly to the nation's economic development, and increased the country's GDP from 37% to 38.3% from 2015 to 2018. Al Mamun et al. (2018, p. 1) estimated that the value created by SMEs in Malaysia would reach RM120 billion by 2020. In addition, SMEs represent a substantial source of revenue production (Rozmi et al., 2020, p. 208) and account for 65.3% of total employment (Al Mamun et al., 2018, p. 1). Hence, small and mediumsized businesses contribute considerably by producing jobs, enhancing living conditions, and raising a nation's GDP. Her et al. (2020) highlighted that Malaysian SMEs account for 38.3% of the nation's GDP and 66% of job possibilities. Malaysian SMEs are essential to the nation's economy as its driving force (Her et al., 2020, p. 271). According to Mahidin (2020), the SMEs' GDP increased by 5.8% in 2019, amounting to RM586.9 billion. Moreover, the SME employment rate increased by 3% in 2019, indicating that SME employment has increased significantly from the previous fiscal year. In order to accomplish the Shared Prosperity Vision 2030, the government has focused on the expansion of SMEs (Allegra et al., 2015). Ijirshar et al. (2015) argued that the Malaysian government had implemented several efforts to stimulate the growth of SMEs because SMEs constitute the economy's backbone. For instance, the Malaysian government has begun to offer training programmes to enhance the sustainability and growth of SMEs.

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According to Topimin and Hashim (2021), the majority of Malaysian businesses are SMEs. Despite their importance to the nation's economy, they are susceptible to and influenced by changes in the business climate. The authors also mentioned that the Malaysian government should utilise business coaching to assist Malaysian SMEs in achieving firm growth and increased performance to secure their survival. Mohamad et al. (2021) stated that the Malaysian government is discussing the efficiency of business programmes in promoting the growth and survival of SMEs.

1.1.3 SMEs Growth and Performance Cicea et al. (2019) highlighted that SMEs' development and success might be characterised by their value creation. The rise in the value of assets inside an SME is a metric for measuring value addition. The authors noted that the growth and performance of SMEs may be assessed through production efficiency, productivity, revenue, market share, and costs. Arguably, the growth and performance of SMEs may be characterised by a gain in efficiency, production level, productivity, revenue, market share, and a decrease in operating expenses. Gopang et al. (2017) added that additional performance indicators for SMEs include target achievement, customer satisfaction, employee satisfaction, production quality, product diversification, reputation, marketing innovation, product innovation, profitability, client count, and organisational innovation. The authors also argued that SMEs might achieve development and success by employing organisational, human, and physical assets. Utilising these assets enables SMEs to attain outstanding performance. Intriguingly, other studies found that the internal environment, organisational strategy, and organisational features also impact SME success. An organisation's strategy should be distinctive and focused on attaining its goals and objectives.

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In addition, SME development and performance are also influenced by social responsibility. Choongo (2017) asserted that social responsibility provides businesses with a competitive edge. The adoption of corporate social activities boosts the exposure of SMEs and enables firms to communicate with numerous stakeholders. For instance, communications with SME stakeholders increase customer loyalty and draw consumers. Customer retention supports growth, encouraging more customers to purchase the company's services and products. The purchase of a company's services and products raises revenue, hence supporting growth in revenue. A rise in a company's revenue enhances its earnings and profitability, fostering growth and performance. Peitsch (2020) identified the stages of SME development, including idea, development, launch, survival, growth, expansion, and scaling. Idea. The idea refers to the thought of beginning a business. Entrepreneurs bore business ideas and envision the operation of the business. Entrepreneurs further research the intended business idea. Development. In this stage, the entrepreneurs conduct market validation, ensuring that the intended business idea has an existing market. Furthermore, entrepreneurs ensure that the intended product or service solves a market problem. The proof of concept and prototyping are deployed at this stage. The proof of concept demonstrates the viability of a business idea by undertaking a pilot study. Thus, the pilot study is used to determine the feasibility of a project. Prototyping involves experimenting with the business idea in the actual market. Businesses utilise prototyping to capture the effect of the business idea on users. Launch. After the development stage, businesses obtain feedback from consumers on the effectiveness of the desired product or service. The feedback allows

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businesses to refine their products or services to fulfil consumers' desires. After product or service refinement, the business starts its business operations. Survival. Businesses establish a business plan intended to promote the growth and success of the business. Businesses also develop appropriate business models to increase revenues. Growth. In this stage, SMEs experience growth due to the high demand for their products and services. For example, SMEs experience growth as they meet their customers' demands. Expansion. Expansion occurs when SMEs identify the factors inhibiting their growth. Therefore, they rectify these factors by changing their business models to adapt to the consumers' needs. Maturity. When SMEs experience growth and slump, they experience maturity. Businesses experience maturity when they achieve success despite different market situations [prevailing conditions].

Problem Statement Inadequate performance has been a persistent worry that has negatively impacted the overall growth of Malaysian SMEs. Most Malaysian SMEs lack the knowledge and skills necessary to realise their market potential. According to NezCacho Utrilla et al. (2015), business coaching equips workers with the necessary abilities to work in a dynamic company environment. Due to the increasing expansion of Malaysian SMEs, securing sustainable company growth is essential for SMEs. The Malaysian government launched the Eleventh Malaysia Plan for 2016-2020 in 2015 to promote economic growth and sustainability. The government declared that it was facing economic growth difficulties and needed to pursue the National Transformation

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Policy to achieve a developed country status by 2020 (Razak, 2015). Notably, 98.5% of firms in Malaysia are SMEs, while their economic contribution to the country's GDP is merely 36% (The World Bank, 2016). Moreover, Malaysian SMEs have not proven noteworthy success since they have not accomplished the anticipated influence on economic development (Her et al., 2020, p. 272). Kaur highlighted that Malaysian SMEs have underperformed in recent years, hence, narrowing the productivity gap. The author mentioned that the COVID-19 pandemic had revealed the productivity gap of SMEs and their underperformance in production and productivity levels. Furthermore, the success of SMEs is essential for the creation of job opportunities and economic growth enhancement in local areas (Mahidin, 2020). Training and mentoring are crucial to the success of SMEs (Hamidi et al., 2018). In order to achieve exponential growth and contribute to a country's economic development, SME owners must prioritise product innovation, training, and mentoring. In contrast, if SMEs fail to receive mentorship and coaching, their performance will suffer. Hamidi et al. (2018) observed that Malaysian SMEs fail to coach their employees, which has a negative impact on the sustainability and growth of the company. Adnan et al. (2015) proposed that the SMEs and the Malaysian government provide training seminars to employees in SMEs to equip them for potential industry transformations. The author additionally discovered that training aids the exponential expansion of SME businesses. Training and mentoring are essential for Malaysian small and medium-sized businesses since they strengthen their dynamic skills. The failure of many SMEs to attain the appropriate performance level in recent years has had a negative effect on the Malaysian economy (Wahab et al., 2016). Due to poor company performance and a shifting business climate, SME failures have

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occurred (Eniola & Entebang, 2016). In addition, disruptive innovation has prompted a paradigm change among Malaysian SMEs that struggled to sustain the appropriate performance level while employing successful business strategies and providing highquality goods and services (Arshada et al., 2016). Numerous efforts have been adopted by SMEs' in an effort to improve their overall performance (Lei et al., 2018). Recent studies have determined that deficiencies in a variety of areas, such as skillsets, understanding of work procedures, capabilities, competencies, morale or job motivation, job satisfaction, and stress management, are the primary causes of SMEs' failure to attain performance criteria (Lara & Salas-Vallina, 2017). These concerns are related to poor training and mentoring of SME staff. Business coaching is essential for assuring SMEs' success and preventing failure since it motivates employees by boosting their abilities and confidence (Affendy et al., 2015). Khan and Anuar (2018) observed that the majority of small and medium-sized businesses do not have the required infrastructure and resources to provide staff coaching and training, leading to a negative impact on the growth of SMEs. Hence, SME personnel must be trained as per their job functions, current developments within the sector, market trends, and the skill needs of SME owners (Satiman et al., 2015). Sessions of SME training and mentoring have positively impacted overall performance and progressed employees' careers (Poon et al., 2018). Mustapa and Mohamad (2021) revealed that despite accounting for 60 to 70% of jobs in most of the Organisation for Economic Co-operation and Development (OECD) nations, only around half of SMEs survive for longer than five years. Notably, the study found that SMEs invest less in training and business coaching and rely more on external recruiting to promote organisational competency. Furthermore, the majority of SMEs' profitability, survival,

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and development are challenged. Existing and emerging SMEs, and those with sluggish or rapid growth, confront this difficulty (Ajuna et al., 2018). Nevertheless, Malaysia has not completely harnessed the advantages of SME coaching and training, implying that the government has not fully tapped the economic potential of SMEs' significant influence on the economy (Zakaria et al., 2016a). The primary objective of the Malaysian government is to facilitate SMEs' exponential growth (Razak, 2015, 11:30). Therefore, the government may address the difficulties by ensuring that SME employees receive proper training and coaching. According to Chuah and Thurusamry (2021), the implementation of big data poses significant obstacles for Malaysian SMEs. Due to a lack of business coaching in terms of big data use, SMEs are unable to improve operations, customer service, and marketing efforts. The lack of use of big data restricts small and medium-sized businesses' understanding of client views and preferences. The authors further highlighted that SMEs need coaching to be educated on the importance of business coaching. Lack of knowledge of consumers' opinions and preferences is bad for firms since it limits sales, resulting in sluggish growth and poor performance (Awang et al., 2019). According to Pertuz and Pérez (2020), the majority of Malaysian SMEs have leadership issues. The majority of SME leaders lack good staff management, administrative management, and resource management abilities. The authors highlighted that personnel management is a necessary skill for Chief Executive Officers (CEOs) of SMEs. Nonetheless, Wahid et al. (2018) voiced concern that most SMEs fail to see the need to motivate all firm personnel to work collaboratively to achieve business goals and objectives. In addition, the authors concluded that the majority of SME CEOs in Malaysia lack administrative management abilities. The majority of leaders possess the necessary administrative, accounting, and tax abilities.

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Typically, most executives of SMEs do not employ specialists for these duties. Notwithstanding, employing specialists to carry out their responsibilities and encourage growth and enhance organisational performance is essential. For example, resource management is required during the production process. A firm should hire the right employee who can accurately estimate the number of consumers who need its products or services. The waste of resources is caused by excessive corporate output due to the inability of existing employees to identify accurate estimations. Regarding the present study, as per the researcher's knowledge, no studies have been undertaken to identify the technique and art of business coaching or how business coaching influences the performance and growth of SMEs in Malaysia. Mustapa and Mohamad (2021) investigated the Malaysian government's business assistance and support for small and medium-sized businesses by undertaking a case study during the COVID-19 pandemic crisis. The analysis was limited to the Malaysian government's assistance to SMEs during the COVID-19 outbreak. The research did not investigate how business coaching influences the rapid expansion of SMEs. Mohamad et al. (2021) explored contributions, difficulties, and obstacles that affected Malaysian SMEs. The study could not identify the causes of the difficulties faced by SMEs, leaving a research deficit in this area. Topimin and Hashim (2021) undertook research to identify the impact of the Malaysian government's support on SMEs during the COVID-19 crisis. Their study evaluated the influence of government support during the pandemic. Unfortunately, it failed to identify the elements that impede SMEs' highimpact development and performance. Chuah and Thurusamry (2021) explored the obstacles faced by SMEs in implementing big data. The study focused solely on big data, how it should be managed, and how it impacts SMEs' performance. Therefore, the study's findings are

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inapplicable to a study examining the impact of implementing business coaching in non-SMEs. According to the researcher's understanding, there is a dearth of empirical findings, resulting in a scarcity of empirical explanations regarding the influence of business coaching on SMEs' growth and performance in Malaysia. In order to fill this gap, the researcher undertook the present study to assess the technique and art of business coaching and its influence on the performance and growth of Malaysian SMEs.

Research Aim and Objectives The overall aim of the present study was to establish the significance of business coaching for SMEs in Malaysia to achieve high-impact growth.

1.3.1 Justification of the Research Objectives Kaur (2019) stated that business coaching increases employee motivation and job satisfaction. The author suggested that business coaching motivates people to realise their personal and organisational potential by enhancing their skills and knowledge. Employee motivation increases job happiness and performance. Shoraj and Llaci (2015) highlighted that employee success is dependent on employee motivation and company mentoring. The authors further stated that employee motivation is a crucial predictor of corporate performance. Employee motivation helps employees to work towards accomplishing the organisation's goals and objectives. Business coaching contributes to employee motivation, greater work performance, and enhanced job performance, leading to increased business growth. Furthermore, employee motivation enhances work engagement and job satisfaction (Tsvangirai & Chinyamurindi, 2019, p. 1). Weideman and Hofmeyr

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(2020) defined employee engagement as the cognitive, emotive, and behavioural vigour of employees. They suggested that employee engagement results in increased staff productivity and dedication. Employee happiness leads to increased productivity and dedication, contributing to corporate expansion (Raziq & Maulabakhsh, 2015). Thus, one might argue that business coaching increases employee pleasure, thereby boosting staff productivity. Employee commitment encourages employees to strive towards accomplishing the organisation's goals, purposes, and visions. This commitment eventually supports corporate success, resulting in increased enterprise growth. Business coaching enhances staff competencies (Idris & Abu Bakar, 2020). Hanafi and Ibrahim (2018) stated that business coaching enhances employees' innovative skills. Thedieck et al. (2013) defined creative employee behaviour as the development, appraisal, realisation, and implementation of novel ideas connected to organisational objectives. For instance, employees might design inventive techniques to search for new technologies that support the fulfilment of organisational goals. Hence, building new routes leads to the achievement of those goals, employing new work practices, and developing better business models. According to Gavin (2020), business coaches may advise people on innovation since innovation supports organisational growth. Training in innovation supports long-term success. Business counselling fosters strategic thinking, allowing workers to generate growth that promotes innovations (Rosha & Lace, 2015). Ovans (2015) described business models as organisational blueprints for maximising a company's profitability. They identified the primary components of business models as firms' goods, marketing methods, corporate costs, and predicted profit. Business coaching increases employee innovation and strategic thinking (Rosha

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& Lace, 2015). Business coaching potentially assists individuals in developing their strategic thinking abilities in relation to company concepts. Employees might provide innovative concepts for the new company's products, hence, boosting marketing techniques, minimising expenditures, and maximising predicted profits. Therefore, business coaching encourages the creation of improved company models. The study's specific objectives are as follows: 1.

To examine the effect of motivation from coaching on the high-impact growth and performance of SMEs.

2.

To study the effect of improved productivity from coaching on the high-impact growth and performance of SMEs.

3.

To evaluate the effect of job satisfaction on the high-impact growth and performance of SMEs.

4.

To assess the effect of innovation on the high-impact growth and performance of SMEs.

5.

To examine the effect of improved business model innovation on the highimpact growth and performance of SMEs.

6.

To test the moderating role of competitive advantage in promoting the growth and performance of Malaysian SMEs.

Research Question The study's central research question is as follows: What is the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia? The objective of the present study is to address the research questions listed below: 18

1.

What is the effect of motivation from coaching on the high-impact growth and performance of SMEs?

2.

What is the effect of productivity from coaching on the high-impact growth and performance of SMEs?

3.

What is the effect of job satisfaction on the high-impact growth and performance of SMEs?

4.

What is the effect of innovation on the high-impact growth and performance of SMEs?

5.

What is the effect of improved business model innovation on the high-impact growth and performance of SMEs?

6.

What is the moderating role of competitive advantage in promoting the growth and performance of Malaysian SMEs?

Rationale of the Study The primary goal of the study was to investigate the significance of business coaching in the high-impact growth of SMEs in Malaysia. As reported by the World Bank (2016), 98.5% of Malaysian businesses are SMEs. Nevertheless, their economic contribution to the country's GDP is merely 36%. Thaker et al. (2016) discovered that SMEs had prioritised earnings, business strategies, value propositions, and business models, which has resulted in their closure in certain cases. According to Hamidi et al. (2018), most SMEs do not coach or train their employees, despite the fact that coaching and training are critical for SME success. Most SMEs have also overlooked employee performance in favour of profit. The neglect of employee performance and owner effectiveness has hampered these organisations' abilities to reap the benefits of their

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innovative business products, services, models, and strategies (Hussain & Raghavan, 2017). Usman et al. (2015) contended that organisations fail to prioritise coaching and training despite their relevance to overall performance. According to Poon et al. (2018), overlooking training and coaching has resulted in Malaysian SMEs struggling to improve employee and overall performance. Employees are unable to gain the skills, information, or competencies that would probably increase their performance in accordance with their organisations' expectations and standards without coaching and training (Satiman et al., 2015). The absence of coaching and training in enterprises has hampered Malaysian SMEs' overall performance and their contribution to GDP and the nation's economy (Kadir et al., 2018). As a result, Malaysia's economy has shrunk. Besides, inadequate training and coaching have forced SME owners to struggle with adequately managing different business processes, leading Malaysian SMEs to be unable to achieve the intended development or growth. The Malaysian economy has been continuously weakening since 2014. Despite a rise in national GDP to 5.74 % in 2017, it fell to 4.33% in 2018. Furthermore, the average economic growth rate since 2014 has been around 5%. (The Malaysian Administrative Modernisation and Management Planning Unit, n.d.). Economic development could have been rapid if SMEs had performed better. Nevertheless, while accounting for 98.5 % of all Malaysian businesses, SMEs account for merely 36% of the country's GDP (Shamsuddin et al., 2017). This insufficient growth has had a negative impact on the national government's development, infrastructure, nationbuilding, and welfare initiatives. With the onslaught of the COVID-19 crisis, the issue of the business coaching programmes in Malaysian SMEs has become more critical. The crisis revealed that

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business survival is important, especially during pandemics. Studies further revealed that business coaching enhances business survival. Based on the studies mentioned above, this study explores the effect of business coaching on the performance and highimpact growth of SMEs. The current study concentrated on RichWorks International, which assists businesses in accelerating their success (RichWorks International, 2021). The organisation provides coaching and training services and is Malaysia's leading seminar organiser. It offers coaching and training services to SME owners, managers, and employees. RichWorks International's training and coaching services are designed to assist SME employees and organisations in acquiring the knowledge, skills, capabilities, and competencies necessary to achieve organisational success. RichWorks International provides mentoring programmes with the primary purpose of guiding businesses and ensuring their remarkable success. The preceding discussion presents a clear path for SME growth and the relevance of business coaching in achieving sustainable growth, especially in the Malaysian SME context. The relevant literature indicates that business coaching results in employee motivation, improved employee productivity, employee job satisfaction, enhanced business model development, and business growth. The studies further asserted that most businesses in Malaysia are SMEs as they comprise 98.5% of the business establishments in the country. Furthermore, the studies discussed earlier found that Malaysian SMEs have experienced considerable growth in the last years, especially from 2015 to 2020. Arguably, when SMEs comprise 98.5% of the business establishments in a country, they significantly impact a country's economy due to their contribution to employment and productivity.

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Additionally, SMEs must achieve enhanced growth and performance to contribute to the country's economy. Nevertheless, the studies also noted that if SMEs do not undergo a business coaching process, it might derail their growth and performance, which have devastating effects on the national economy. As a result, the current researcher was inspired to undertake this study and investigate the effects of business coaching on growth and performance and the moderating function of competitive advantage in Malaysian SMEs. According to the findings, it is evident that SMEs in Malaysia face substantial challenges in business growth owing to a lack of employee training and coaching. This situation has resulted in a decrease in the growth of SMEs, and numerous SMEs have closed. This issue has exacerbated the nation's economy. The study's findings are anticipated to enlighten SMEs about the need for coaching and to train their employees to achieve business growth. The primary aim of the study is to investigate the significance of business coaching for the rapid expansion of Malaysian SMEs. This disdain for employee performance and owner effectiveness has impacted the capacity of these organisations to obtain the expected advantages from their creative business models, products, services, and initiatives (Hussain & Raghavan, 2017). Usman et al. (2015) suggested that firms disregard training and coaching despite its significance to overall success. Poon et al. (2018) reported that Malaysian SMEs have struggled to improve both their overall and employee performance due to a disdain for training and coaching. Without training and coaching, employees are unable to gain relevant skills, information, or talents that would likely improve their performance in accordance with their organisations' expectations and standards (Satiman et al., 2015). The absence of training and mentoring in enterprises has negatively impacted the overall performance of SMEs in Malaysia, and their

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contribution to the country's economy and GDP (Kadir et al., 2018), causing the Malaysian economy to contract. Malaysian SMEs are unable to achieve the intended growth or development due to a lack of proper training and coaching. As stated previously, Malaysia's economy has been continuously contracting since 2014, although the national GDP increased to 5.74% in 2017. Unfortunately, the GDP fell to 4.33% in 2018. In addition, the average economic growth rate has been merely 5% since 2014 (The Malaysian Administrative Modernisation and Management Planning Unit, n.d.). The economic growth rate might have been greater if SMEs had functioned effectively. Nevertheless, while accounting for 98.5% of all Malaysian enterprises, SMEs contribute only 36% of the country's GDP (Shamsuddin et al., 2017). This insufficient growth has had a negative impact on government-sponsored development, infrastructure, nation-building, and welfare initiatives. Consequently, with the onset of the COVID-19 crisis, the topic of business coaching courses in Malaysian SMEs has become more critical. The crisis emphasised the significance of corporate survival, particularly during pandemics. Research also demonstrated that business coaching improves firm survival. Based on the previous research, this study investigates the influence of business coaching on the performance and high-impact growth of SMEs. This research focused on RichWorks International. RichWorks International assists businesses in achieving success (RichWorks International, 2021). The organisation provides training and coaching services and is Malaysia's prominent seminar organiser. It primarily provides training and coaching services to the owners, managers, and employees of SMEs. RichWorks International's training and coaching services are intended to assist SME people and organisations develop the skills, information, competencies, and capabilities necessary to achieve organisational

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performance. RichWorks International's major objective is to help businesses and assure remarkable success by providing mentoring courses. The preceding debate provides clear direction about SME growth and the significance of business coaching in achieving sustainable growth, especially in the Malaysian SMEs context. The relevant research demonstrates that business coaching results in employee motivation, higher employee productivity, employee work satisfaction, and the creation of improved company models. Further research demonstrates that business coaching results in better business growth. As stated in the earlier studies, approximately 98.5% of the country's commercial entities are SMEs. In addition, the research covered in the study's context revealed that Malaysian SMEs had witnessed significant growth in recent years, particularly from 2015 to 2020. When SMEs account for 98.5% of all business establishments in a country, they arguably have a major influence on the economy owing to their contribution to employment and production. In order to contribute to the nation's economy, SME growth and performance must be improved. Nevertheless, the research also found that if SMEs do not receive business coaching, their development and performance might be disrupted, which would have disastrous implications on the national economy. Therefore, the present study's researcher was inspired to conduct this study and uncover the benefits of business coaching on development and performance and the moderating function of competitive advantage in Malaysian SMEs. According to the discussion above, evidently, a lack of training and coaching for their employees poses a substantial obstacle to the commercial success of Malaysian SMEs, leading to a reduction in the growth and closure of many SMEs and worsening the country's economic situation.

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The study's outcomes are anticipated to enlighten SMEs on the significance of training and coaching for achieving company success.

Significance of the Study The current study's findings are expected to contribute to the Malaysian SME industry significantly. Practitioners. The findings of this study enlighten SME leaders on the significance of coaching and training and their impact on business growth. Hence, SME leaders may utilise the study's recommendations to develop suitable strategies for implementing training and coaching in their businesses in order to boost business growth. Scholars and Researchers. The findings of this study are significant for academics and scholars. This study, in particular, acts as a reference and guide for researchers undertaking a study on a topic relevant to the significance of coaching and training for SME growth. This study's findings also contribute to the current literature on the impact of coaching and training on SME growth. Policymakers. The findings of the study are also useful to policymakers, including the government. The findings may be used by the government to design relevant policies that improve SME employees' training and coaching. This study will also be valuable to Malaysian legislators in drafting appropriate laws to promote training and coaching in SMEs.

Scope of the Study The purpose of this study was to explore the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs

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in Malaysia. It analysed the effect of business coaching on business model innovation, employee motivation, innovation, productivity, job satisfaction, and the moderating role of competitive advantage. The study's target population was SMEs in Malaysia. A quantitative approach was employed in the study, which was conducted from April to November 2021.

Structure of the Thesis This thesis is organised according to the structure outlined in Figure 1.3 below.

chapter 1: introduction chapter 2: literature review chapter 3: research methodology chapter 4: findings chapter 5: discussion and conclusion

Figure 1.3: Structure of the study

This study was carried out in accordance with academic norms and research procedures. The introduction, literature review, research methodology, findings and discussion, and conclusion and recommendations comprise the five chapters of the thesis. By analysing relevant prior research, Chapter 2 highlights the background information and theoretical underpinnings relevant to the roles of coaching and

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training in boosting the performance of Malaysian SMEs. The researcher concentrated on scholarly textbooks and peer-reviewed articles. The review aided the researcher in critically discussing the findings of the primary data analysis. The methodological framework for data collection and analysis is described in Chapter 3. The following methodologies were utilised by the researcher: pragmatic philosophy, a deductive approach, descriptive design, primary data collecting, a survey, and quantitative data analysis. The researcher gathered the primary data required for the study from 245 RichWorks International clients in Malaysia. The findings of the primary data analysis are presented in Chapter 4. In order to appropriately analyse the primary data, the researcher employed quantitative data analysis methodologies (regression, descriptive, inferential, and correlation analysis). Moreover, the findings are discussed in the context of the background data and theoretical underpinnings. In Chapter 5, the researcher summarises the key findings and suggests strategies for Malaysian SMEs to improve their development and performance through effective coaching and training. Lastly, the researcher discusses how the study's scope may be expanded in the future.

Summary This chapter has reviewed the study's background related to the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia. Researchers asserted that business coaching is imperative to realise SMEs' growth and performance. The studies further revealed that Malaysian SMEs experience poor growth and performance due to a lack of business coaching. The studies also showed that business coaching results in employee

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motivation, productivity, job satisfaction, innovation, and the development of enhanced business models.

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CHAPTER 2 LITERATURE REVIEW

Introduction This chapter examines the existing research on the impact of business coaching on the high-impact growth of SMEs. The chapter begins with a theoretical overview, evaluating how underlying ideas are relevant and related to the current study. The chapter then explores the independent variables (training and coaching, organisational resources, organisational performance, improved work performance, business models, and competitive advantage) and the dependent variable of SME growth, how they are associated, and how numerous researchers have researched them. The chapter subsequently discusses the research gap before developing a conceptual framework. The researcher used an integrative literature approach to critique and synthesise research while also generating knowledge on the topic of interest.

Review of the Relevant Theories Clayton Alderfer introduced Existence-Relationship-Growth (ERG) Theory in 1969 (Caulton, 2012). The ERG theory is an expansion of Maslow's theory of the hierarchy of human needs. According to Alderfer, needs may be divided into three different categories instead of five. The three categories are existence, psychological and safety requirements, and relatedness needs. Existence requirements are comparable to Maslow's categories of safety and physiological needs (Caulton, 2012). Comparable to Maslow's belongingness and esteem requirements, relatedness needs entail interpersonal interactions. Maslow's esteem and self-actualisation needs are tied

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to the achievement of an individual's potential, which is associated with growth requirements (Caulton, 2012). Alderfer (1969) suggested that when an individual is consistently incapable of fulfilling their higher-level requirements, their lower-level needs become the primary motivators. In simple words, the ERG theory varies from the hierarchy of needs as it proposes that lower-level wants do not have to be entirely met before higher-level needs may be fulfilled (Ahmad et al., 2021). Alderfer (1969) further asserted that humans are driven by advancing and retreating between these levels (Ahmad et al., 2021). According to Ahmad et al. (2021), when relatedness satisfaction declines, existence desires are likely to rise, and development desires tend to reduce (backward movement). In contrast, as relatedness satisfaction improves, growth desires tend to increase while existence desires decrease (forward movement). Douglas McGregor proposed Theory X and Theory Y, which comprise two distinct assumption sets pertaining to manager-employee interactions (Ahmad et al., 2021). The primary premise of Theory X is that workers detest and tend to avert employment. Hence, these types of individuals must be constantly regulated and intimidated with punishment to achieve the intended goals. On the contrary, Theory Y presumes that employees may exercise self-direction and self-control provided they are devoted to their employment (Ahmad et al., 2021). McGregor emphasised that Theory Y is regarded as more legitimate and includes higher job participation, autonomy, and responsibility. As a result, Theory Y increases employee motivation (Ahmad et al., 2021). Frederick Herzberg's (1959) two-factor theory of motivation is strongly associated with Maslow's hierarchy of human needs theory. The components of Herzberg's two-factor theory of motivation are separated into two categories,

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motivators and hygiene (Caulton, 2012). Herzberg (1959) stressed that some intrinsic characteristics would directly drive employees and promote contentment. These variables are referred to as motivators by Herzberg since they symbolise the urge for self-actualisation and growth. The motivators include personal views and internal sensations, such as accomplishment, experience, the job itself, responsibility, changing status through promotion, and the chance for development and progress. Nevertheless, the hygiene variables leading to extrinsic satisfaction and discontent might include factors such as supervision, interpersonal interactions, management, recognition, business policy and administration, advancement, salary and perks, status, job security, and physical working conditions (Ahmad et al., 2021). Thus, as per the two-factor theory, the most crucial predictors of employee happiness might be intrinsic variables because employees are driven to acquire happiness. Individuals will be unsatisfied if the institution fails to supply motivational elements, as discontent is produced by hygiene aspects. The absence of hygienic elements contributes to occupational discontent, but their presence motivates employees. In simple words, discontent develops when hygienic factors are not reached. Nonetheless, they do not encourage employees (Ahmad et al., 2021). Consequently, the consequence of the motivator-hygiene hypothesis includes extrinsic considerations such as compensation, perks, and safety that will refrain employees from being actively unhappy. Unfortunately, these extrinsic considerations will not inspire them to invest further effort towards improved performance. In contrast, managers must focus on altering internal elements, such as responsibility, autonomy, recognition, opportunity, skills, and careers, in order to drive employees (Caulton, 2012).

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Alternatively, Herzberg's motivation theory is also questioned in certain respects. The distinctions between contentment and discontentment are not clarified by theory (Caulton, 2012). The results of these two components, known as "motivators" and "hygiene," vary for different populations. Any element that contributes to discontent may lead to satisfaction in different circumstances or nations. Besides, this distinction is difficult to implement since individuals have diverse requirements and expectations. As reported by researchers with an opposing viewpoint, the amount of pleasure cannot be predicted solely based on motivation or cleanliness (Ahmad et al., 2021). People's needs are suggested to be categorised into three psychological categories (Caulton, 2012). According to this view, the three fundamental wants are affiliation, achievement, and power. First, the demand for affiliation indicates a desire to form social ties with other individuals. Secondly, the urge for achievement is the drive to assume responsibility, establish challenging goals, and obtain performance evaluations. The third component, namely the urge for power, is the need to dominate one's surroundings and exert influence over others (Ahmad et al., 2021). This idea has served as the foundation for several empirical and experimental studies. As stated in the idea, when one of these wants is strong in an individual, the want has the ability to inspire conduct, leading to its fulfilment. Therefore, managers should strive to determine whether and to what extent their workers have these requirements and the amount to which their tasks might be designed to meet them (Ahmad et al., 2021). Tolman introduced the Expectation Theory in the 1930s. This idea implies that expectations motivate human action. According to the idea, a human selects to act in a particular manner in order to receive the desired reward. The individual is motivated to choose conduct based on their expectation of the outcome of that activity (Ahmad

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et al., 2021). For example, if employees require more compensation to meet their demands, they are promised that they will be compensated with a higher amount of money if they put in the extra effort. In subsequent years, Victor Vroom utilised the notions of behavioural research (Caulton, 2012). The Explanation of Expectations is a process theory of motivation and work satisfaction. The theory outlines expectations in which a person's effort is governed by the anticipated outcomes and the perceived worth of those consequences (Ahmad et al., 2021). In simple words, the idea of expectation relies on human perception and conduct. Furthermore, necessities exist independent of an individual's desires. Nevertheless, values are subjective and based on the individual's internal standards. It implies that, although everybody has the same fundamental requirements, the value of those needs varies according to individual standards (Caulton, 2012). As stated in the Expectancy Theory, a close connection exists between effort, performance, and the benefits that result from efforts and performances. They are driven when they feel that great effort will result in a good performance, which will result in the desired reward (Ahmad et al., 2021). According to the Goal Setting Theory created by Locke and Latham, goal setting is an important aspect of work satisfaction. The goal-setting theory highlights the significance of precise objectives for achieving motivation and fulfilment. In the goal-setting process, individuals aspire to attain objectives to satisfy their desires and emotions (Caulton, 2012). Among the conclusions of goal setting theory is that clear and challenging goals need better performance. Another conclusion highlights that goal setting would be most successful if an efficient feedback system existed.

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Consequently, rather than administering punishment, a manager should evaluate the reasons why targets are met or failed to be achieved (Caulton, 2012).

Underlying Theories The present section discusses the two theories that are pertinent to the current study, namely Biggs' Presage-Process-Product (3P) model of learning and the Goal, Reality, Options, Will (GROW) model.

2.3.1 Biggs' Presage-Process-Product Model Biggs (1996) created the Presage-Process-Product (3P) model to assist learners in improving their theory learning skills. According to Biggs (1996), learning is a dynamic process that involves both educators and learners. He suggested that employee coaching and mentoring are the primary indicators of corporate success, and they are impacted by them. Biggs (1996) emphasised that learners must go through the learning process in order to enhance their performance. He stressed that in order to maximise the learning process, learners must comprehend how to learn effectively, and teachers must establish a suitable atmosphere to promote the learning process. Biggs (1996) established the 3P model of learning, which includes the presage, process, and production stages. The presage stage occurs before the learning process, the process stage occurs throughout the learning process, and the product stage occurs at the end of the learning period. Biggs' model is depicted in Figure 2.1.

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Source: Biggs (1996)

Figure 2.1: Biggs' Presage-Process-Product model

According to the 3P paradigm, learners exhibit learning-related qualities during the presage stage (Biggs, 1996, p. 186). He emphasised that the presage stage is separated into two parts: student and teacher presage. The possessed knowledge that students have before beginning coaching and training sessions is referred to as student presage. It also includes their talents, linguistic proficiency, and expectations following the coaching sessions. According to Kamarudin et al. (2020, p. 293), learners approach learning based on their past experiences. Kanashiro et al. (2020) acknowledged that presage elements are important in determining students' learning techniques. Students' personalities before learning impact their learning method too. Biggs (1996) defined teacher presage as the structure established by teachers, including learning content, to assist students' learning. He also observed that teachers' presage generates a suitable environment for learners, motivating them to learn and internalise the subject. As a result, if learners have already come across a topic, they may simply engage with the topic. Kanashiro et al. (2020) corroborated 35

Biggs' 3P model by claiming that instructors' presage contains academic and professional abilities that may be utilised to communicate their message to learners successfully. The second stage is referred to as the process. According to Biggs (1996), the process stage includes how coaches approach the work of instructing learners. Coaches assist, mentor, teach, and support learners in understanding the learning material at this stage. Kanashiro et al. (2020) emphasised that the process stage is mostly determined by the motivations of coaches and their approach to the learning task. A coach should concentrate on the students and the ways to influence their knowledge. Biggs (1996) discovered that the process stage necessitates pedagogical interventions. At this level, learning takes two forms, which are surface learning and deep learning. Surface learning occurs when teachers read the material without delving into the depths of the content. They achieve the learning objectives without requiring extensive processing of the learning contents. In deep learning, coaches guarantee that meaningful interpretation is developed and that learners are assisted in connecting knowledge. The production stage is the final stage. The student's learning outcomes are determined at this step (Biggs, 1996), which is dependent on their diverse approaches to learning. Students can grasp the application and integration of the learning content and also apply it to achieve economic and social goals, in addition to studying the required materials (Kamarudin et al., 2020). The study also discovered that when students get hands-on experience with what they learnt during the coaching sessions, they learn more effectively. According to Biggs' 3P model, SMEs may utilise the model to coach their staff on the skills necessary to achieve high-impact company growth. For example, SMEs

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might use organisational resources and innovative skills to establish dynamic capabilities that assure a competitive market edge for the firm. As a result, this model was pertinent to the current study since it verifies the impact of staff coaching on business growth. The model was appropriate since it assisted in establishing the relationship between business coaching and the high-impact growth of SMEs in the Malaysian context. The implementation of this theory illustrates how Malaysian SMEs can successfully sustain high-impact growth.

2.3.2 Resource-Based View (RBV) Theory The topic of strategic management is organised around a central research question that gauges why certain companies consistently outperform others. This question indicates that there will be permanent performance gaps across businesses in some instances, which cannot be analysed or explained using conventional economic theories of performance. As stated in these conventional economic ideas, disparities in business performance should be infrequent and certainly not sustained (Newbert, 2014). When these ideas exist, the anti-competitive collusive or monopolistic behaviour of corporations is used to legitimise their existence. In the realm of strategic management, the resource-based view (RBV) has emerged as one of the numerous significant reasons for enduring company performance variations (Newbert, 2014). By analysing enterprises from the resource side as opposed to the product side, it can be argued that the RBV takes a more introspective position on the success or failure of businesses (Safari & Saleh, 2020). In attempting to explain the extent to which an organisation may be able to maintain a competitive advantage, the theory uses the firm's resources as its unit of study (Safari & Saleh, 2020).

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According to the RBV theory, firms are profit-maximising entities controlled by boundedly rational managers functioning in discrete markets that are fairly predictable and tend to incline towards equilibrium (Newbert, 2014). The RBV theory also acknowledges that information on the future value of a resource is dispersed asymmetrically. If the firm's management is able to evaluate the future worth of a resource more accurately than their competitors, or if they are just lucky, this information offers their businesses ex-ante sources of sustainable competitive advantage (Newbert, 2014). In other words, the invention and execution of isolating mechanisms have the capability to acquire a sustainable competitive advantage. The RBV theory is premised on two key assumptions: (1) resources are dispersed heterogeneously among enterprises, and (2) productive resources cannot be moved without cost from one firm to another, such that heterogeneity may persist (Newbert, 2014). These assumptions constitute the axioms of RBV. Two basic arguments may be derived from these premises. First, valuable and scarce resources might create a competitive edge. Valuable resources are crucial to efficiency and organisational success because they enable the organisation to exploit opportunities and counteract environmental challenges. For instance, rare resources are often available in short supply and not distributed evenly across the firm's existing and prospective competitors. Second, when such resources are simultaneously non-imitable and nonsubstitutable, they may become sources of enduring competitive advantages (Safari & Saleh, 2020). Inimitability refers to the degree to which it is difficult for other companies to replicate a company's resources. According to Barney (1991), social complexity may be a contributing factor. Involvement of other factors, such as causal ambiguity and particular historical conditions surrounding the resource's production

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or acquisition, is possible. Non-substitutability of resources denotes that a resource cannot be easily substituted for another in order to conceive and execute similar strategies as effectively or efficiently as the original resource (Newbert, 2014). These resources are referred to as VRIN resources. The term 'VRIN' represents valuable, rare, inimitable, and non-substitutable. Hence, these resources are more likely to provide a durable competitive advantage (Barney, 1991). Currently, resources are defined as tangible and intangible assets organisations utilise to develop and implement plans (Safari & Saleh, 2020). The strategic and economic importance of tangible and intangible assets varies. In general, resources are valuable when organisations are able to plan and implement strategies that decrease their net expenses and increase their net revenues beyond a value that would otherwise be possible. Researchers may also evaluate the worth of the resources based on their capacity to enable enterprises to design and implement plans that are tailored according to the firm's operating market (Safari & Saleh, 2020). The firm's financial capital, such as debt capital, equity capital, leverage potential, and retained earnings, are examples of physical resources. Physical capital may also comprise the machinery, technology, equipment, and buildings that a company possesses. Traditional intangible resources consist of a company's human capital, which consists of the training, judgments, intellects, relationships, experiences, and insights of each management and employee. Organisational capital consists of the characteristics of groups of employees affiliated with a company, such as its culture, formal reporting structure, and reputation in the marketplace (Newbert, 2014). The RBV of the organisation has become one of the most popular theoretical frameworks in management literature. The RBV focuses on the firm's competitive advantages derived from its exclusive collection of resources (Owusu & Ismail, 2018).

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Understanding the causes of organisations' ongoing competitive advantage has become a prominent study topic in strategic management. The majority of the research has been structured under a single organising framework (Nagano, 2020). Most research on sources of persistent competitive advantage has focused on identifying a firm's opportunities and threats, characterising its strengths and weaknesses, or analysing how the components are matched to determine organisational strategies (Owusu & Ismail, 2018). There is little question that this technique has been extremely beneficial in elucidating human understanding of the effect of a company's environment on its growth (Chumphong et al., 2020). According to the RBV approach, analysing an organisation's internal strengths and weaknesses is predicated on two key premises. First, companies may be seen as collections of productive resources, and each organisation owns a unique collection of these resources (Safari & Saleh, 2020). This premise is the resource heterogeneity assumption of the contribution of the RBV and entrepreneurial orientation to small firm growth. Second, this strategy posits that a portion of these resources is either prohibitively expensive to duplicate or have an inelastic supply. The second premise is also known as the resource immobility assumption. The most notable attribute of the RBV is its concentration on the firm's internal forces. Recent interest in the importance of company resources as the cornerstone of business strategy has increased. The increasing interest reflects a certain level of frustration with the equilibrium-based, static framework of industrial organisation economics, where the emphasis was previously on the relationship between strategy and the external environment (Nagano, 2020). Numerous advancements on several strategic levels have led to what has been dubbed a resources-based perspective. The RBV essentially describes a company in

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terms of the resources it possesses. Penrose (1959) emphasised that a company is not only a unit but also a collection of resources. The term resource is frequently restricted to traits that increase the firm's efficiency and effectiveness (Chumphong et al., 2020). Thus, resources must be able to create profits or prevent losses. The availability of generic resources will nullify the firm's competitive edge. For a company to attain high-performance levels and sustainable competitive advantage, it must acquire diverse, difficult-to-create, substitute, and imitate resources. Picturing a small company seizing an opportunity and making a substantial impact on the market without expanding is difficult. According to Garnsey et al. (2006), early growth has both internal (learning effects) and external benefits (market position). In this regard, the expansion of a firm appears to be an essential indication of the entrepreneurial conduct of small businesses (Chumphong et al., 2020). In the subject of strategic research, the expansion of businesses has become a crucial concern. Davidsson et al. (2002) highlighted the conditions under which the study of growth successfully adds to the understanding of the entrepreneurial process. As reported by some scholars, equating entrepreneurship with the development of a new business is a simplification of the topic of entrepreneurship since it does not fully represent its contemporary definitions. The author believes that academics in this subject should view the growth of a company as an integral aspect of the entrepreneurial process. Regarding the process of growth in small firms, Owusu and Ismail (2018) found that the process is the consequence of a combination of three fundamental components. The three components are the qualities of the entrepreneur, the features of the small business, and the development plans of the firm. These three factors do not mutually exclude one another, and they all impact the growth of small businesses.

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Analysing the elements of firm growth is relevant when examining the strategy of small businesses and, in particular, the strategic decisions that might affect growth. Owusu and Ismail (2018) believed that an entrepreneurial company is one that "engages in product market innovation, pursues relatively hazardous projects, and is the first to come up with proactive advances, beating out competitors." A nonentrepreneurial company is a company that innovates very little, is extremely riskaverse, and imitates its competitors' movements rather than setting the pace. In an empirical study, Owusu and Ismail (2018) devised a measuring tool to capture the dimensions of firm growth. This measurement tool has had an impact on later studies. Despite the use of the same measuring tool, multiple terms are employed to describe the same dimensions. Moreover, there is limited agreement on the type of dimension involved (Chumphong et al., 2020). Although multiple interpretations of the measuring instrument have been proposed, the drawback does not prevent the tool from being viable for assessing the essential elements of entrepreneurial orientation. M'zungu et al.'s (2017) point of view is supported by many researchers, who highlighted that organisations, not only people, may exhibit entrepreneurial behaviour. In addition, they maintain the relevance of risk-taking, inventiveness, and initiative as entrepreneurial characteristics (Owusu & Ismail, 2018). In most instances, the utilisation of a single resource does not enable a company to design and implement an effective strategy but rather the utilisation of a collection of such resources. In fact, it may be extremely challenging to comprehend how various resources interact to enable a strategy to attain competitive success (Newbert, 2014). Consequently, finding the primary origins of these unique competitive advantages is a challenging endeavour. The advantages that might be derived from identifying the origins of the competitive advantages include the fact that it prevents rivals from

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discovering the sources of the greater performance and duplicating these valuable resource networks (Safari & Saleh, 2020). Maintaining competitive differentiation is crucial for an organisation. Indeed, a company that possesses a significant collection of resources does not necessarily exhibit consistent excellent performance (Newbert, 2014). If its competitors possess similar resources and employ them to create and implement identical plans, these resources will not guarantee a sustainable competitive advantage (Safari & Saleh, 2020). Therefore, possessing valuable bundle resources is a required but insufficient condition for organisations to achieve excellent performance. Organisations must identify some isolation techniques to safeguard the resources from being copied or replaced (Safari & Saleh, 2020). Improving the performance of enterprises in the external environment is central to the definition of the discipline of strategic management, although the connection between strategic management and organisational performance is rather hazy (Newbert, 2014). Business strategy includes both strategising (associated with market power) and economising (associated with efficiency) and suggests that performance can be a function of strategising and economising. Economising, which comprises efficiency analysis, involving governance costs and production costs, and comparative economic organisation, is the most crucial element in determining performance because every organisation require economising to survive and thrive (Safari & Saleh, 2020). While the distinction between strategy and growth is essential, viewing these two parts of company strategy as intrinsically complementary may be more productive. This view is evident when strategising is framed in providing 'perceived value' for target consumers and when economising is framed in the 'delivered costs' involved with developing and delivering growth (Safari & Saleh, 2020). This potential frontier,

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which precludes the realisation of 'bliss', may be identified by benchmarking to identify best-in-class rivals at the top, middle, and bottom of the market (Safari & Saleh, 2020). The majority of firms will be located within the frontier, and it is a crucial objective of strategic management to push their organisation closer to the frontier through programmes such as comprehensive quality management and the reengineering of business processes (Newbert, 2014). The notion needs a detailed study of the relationship between cost drivers and growth and the continued willingness of senior management to shift expenditures from lower-value-creating to higher-valuecreating activities. Incremental innovation shifts the frontier of possibilities proportionally and enables the majority of industry incumbents to employ, occasionally taking the lead and occasionally having to play catch-up. Nevertheless, radical innovation alters the border of possibilities in a discontinuous manner (Newbert, 2014). Radical innovation includes new technological solutions, such as the use of the Internet, new ways of organising, such as diverse forms of outsourcing, and introducing new business models, such as shifting from selling products to providing subscription services to generate revenue. These changes are frequently presented by new entrants to a sector and are typically exceedingly challenging for established corporations to react to due to different types of strategic inertia (Newbert, 2014). As with the previously stated models, several frameworks have been founded based on organisational performance. The inputs are the external world, and outputs might be described as both organisational performance and individual growth, a feature not available in other models. The outcomes comprise two major categories: organisational members' behaviour (individual cognitions and on-the-job conduct) and the work environment (Safari & Saleh, 2020). The work environment may consist of

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components that can be classified as streams: organising arrangements (goals, strategies, structure, and systems), social factors (culture, networks, and individual characteristics), technology such as equipment, machinery, job design, and physical settings (Safari & Saleh, 2020).

2.3.3 The GROW Model The GROW model by Whitmore (1992) first emerged in the 1980s. He believes that the GROW model contributes significantly to coaching in personal development. He went on to suggest that coaches should utilise the GROW model to create a systematic training roadmap for their personnel. He also envisioned the GROW model as a behavioural coaching model. According to the author, the model additionally implies that the coach is an active participant throughout training and impacts trainee behaviour, resulting in collective performance (Whitmore, 2009). The GROW model is summarised in Figure 2.2.

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Source: Whitmore (1992)

Figure 2.2: Whitmore's GROW model

Coaching is conceptualised as a partnership between a client and coach in a thought-provoking and creative process that incorporates various behavioural strategies to inspire and maximise the client's personal and professional potential (Greif et al., 2022). Coaching is a collaborative, solution-oriented, results-oriented, and methodical process in which the coach helps the coachee improve professional performance, self-directed learning, life experience, and personal development (Greif et al., 2022). By originating from the arena of athletics in the 1960s, coaching became popular in the business field in the 1970s and 1980s and in a number of contexts by the 1990s. Coaching takes several forms and is utilised in a variety of contexts, affording the potential to establish a collaborative relationship that develops a pleasant learning environment, supports participants, and results in greater end satisfaction 46

(Augestad et al., 2020). Coaching in education may be considered an opportunity to promote educators' professional and personal growth. It benefits from a humanistic coachee-centred viewpoint based on the concepts of encouraging positive change and self-actualisation in this setting (Lai & Palmer, 2019). Coaching in education has been utilised through a number of approaches as a beneficial method for professional development and generating interest. Models generally include a pre-conference, an observation of practice, and a post-conference structure with self-reflection and feedback procedures that are helpful for continual instructional development (Lai & Palmer, 2019). Coaching is an effective technique to enhance educators' learning and provides chances for educators' personal and professional development (Greif et al., 2022). In business education, peer coaching is a prevalent technique since educators frequently share their curriculum goals and methods. Due to a common context and shared knowledge, educators researching and applying instructional approaches is an excellent strategy to assist the adoption of teaching tactics (Lai & Palmer, 2019). The GROW coaching paradigm, first established by Graham Alexandre in the 1980s and popularised by Sir John Whitmore in the 1990s, is a standard coaching approach. Since the model was first established in the 1980s, it has been continually utilised and enhanced in a range of sectors. It remains one of the most prominent and widely used models, with over half of coaching practitioners employing it (Lai & Palmer, 2019). The GROW model provides coaches with a structure and series of questions to use in their work with coachees. With its emphasis on objectives, it is an appropriate approach to professional development in education (Augestad et al., 2020; Greif et al., 2022).

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The GROW model, which is enabled by a series of questions aimed at enhancing the coachee's awareness and sense of responsibility, draws on the coachee's personal thought processes to bring to light the objectives they aspire to accomplish, the hurdles to these objectives, the action course they will employ to accomplish their goals, and the behaviours they will change to achieve their goal. The GROW model is based on Roger's Theory of the way of being, with its belief in human beings' "constructive tendency" adopting a humanistic approach to capacity building and prioritising empathy to assist changes in motivation, attitudes, and dispositions, which are well-suited to the educational setting (Lai & Palmer, 2019). The GROW model supports self-efficacy as a driver of learning and progress in order to create the unique performance-producing behaviours that are important to human's control over behaviour, motivation, and social environment (Lai & Palmer, 2019; Augestad et al., 2020). These distinctive components and processes of the GROW may be employed in a variety of contexts, such as the job of the coach, independent of a position, is that of feedback giver and process facilitator, moving the coachee back and forth through the model's phases and the sequence of inquiry. In the GROW model, the coach uses questioning to help the coachee clarify their objectives and improve their awareness of present realities to assist them in assessing their present situation. Besides, the coach assists the coachee in identifying and evaluating available alternatives and encourages and supports them in determining the course of action they intend to pursue (Greif et al., 2022). The process of quantifying the efficacy of professional development efforts can be challenging (Greif et al., 2022). Nevertheless, it is vital to focus on the impact of programmes aimed at assisting coaches' professional growth in maximising their capacity to promote learning. The implementation of knowledge and skills in SMEs is

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crucial to their effectiveness since the managers' or instructors' discourse and concepts of learning to influence the growth results (Lai & Palmer, 2019). The research suggests that coaching can play a crucial role in boosting the chance that newly acquired abilities will be used in the business (Lai & Palmer, 2019; Augestad et al., 2020; Greif et al., 2022) The GROW model highlights the need to follow a certain sequence in order to attain greater performance. Goal, Reality, Opinion, and Way Forward are the stages in the sequence. Whitmore (1992) argued that in the first stage, goal, organisations should have a clear and quantifiable objective that they plan to attain by the end of the training session. The establishment of a defined and quantifiable goal will provide consistency for the company. Whitmore (1992) also recommended that businesses develop objectives that are explicit, quantifiable, achievable, reasonable, and time-bound. Organisational leaders should establish the goals to ensure that they may compare their accomplishments to their initial aims. The four stages of the GROW model are described in further detail below: What is a Goal? In this stage, the coachee outlines their annual goals, overarching goals, and their goals for the business coaching session (Stout-Rostron et al., 2014). In this stage, the coachees should ask themselves several questions, including the following: 1.

What would I like to achieve by the end of the business coaching session?

2.

Where would I like to be at the end of this session?

3.

What is the most important thing that I would like to benefit from this business coaching session? What is Existence? In this stage, the business coach helps the coachees to

explain the reality of their businesses by inviting them to share their business stories 49

and how this reality relates to the business goals. The sharing session helps the coachees to become aware of the current situation in the organisation (Stout-Rostron et al., 2014, p. 98). Whitmore (1992) suggested that the following questions should be asked to establish the reality: 1.

Which actions have been taken so far?

2.

What have the effects been of taking those actions?

3.

Were there any internal obstacles to implementing those actions?

4.

Were any internal blocks faced during their implementation?

5.

Which assumptions are limiting the thinking? Answering these questions allows the coachees to become more aware of the

current situation and the outcomes of the coaching. According to Kamarudin et al. (2020, p. 295), employees must be aware of the origin of their difficulties in order to design viable alternatives to resolve the issues they face. What are the Options? Various courses of action to be adopted should be identified at this point in case of a planned desirable change. According to StoutRostron et al. (2014, p. 98), options refer to the action plans and strategies that are supposed to be taken by the coachees. Coachees should have as many courses of action available as possible to decide on the most suitable one. Various solutions should be considered based on their primary benefits and drawbacks in accomplishing the intended aim. What should be Done? Stout-Rostron et al. (2014) stated that this stage requires clients to note what they will do differently after undergoing the business coaching sessions. The business coaches can ask the following questions to the coachees: 1.

What will you do? 50

2.

When is the management system going to take this action?

3.

Does the system think that taking this action will help you achieve your goal?

4.

Which obstacles do they think they might encounter?

5.

Which support does the system need in taking this action?

6.

When is this support needed?

7.

Are there any other considerations? According to Whitmore (2009), the way forward specifies the actions to be

undertaken, when they will be undertaken, who will take the actions, and the willingness to do so. These questions are critical for charting a course and allocating roles to various personnel within the organisation, who will then carry out the planned activities to accomplish the intended goals. There are various supporters of the GROW model. As stated in Abdulla (2018), the GROW model is required for designing a coaching session. The author went on to suggest that the GROW model is crucial because it assists in analysing the effect of the company's actions in order to accomplish the intended goal. If the activities do not fulfil the organisational goals, Abdulla (2018) suggested that remedial measures be implemented to guarantee optimal corporate performance. The GROW model suggests that coaching has an impact on organisational performance. As a result, this model is applicable to the current study, which sought to analyse the impact of business coaching on high-impact growth in SMEs. The theory offers a paradigm for how SMEs might utilise coaching to influence their staff in order to achieve high-impact growth. The theory was not only applicable but also useful to the current study since it provided a lens that may be utilised to help the conceptualisation of business coaching in the context of Malaysian SMEs.

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2.3.4 The CLEAR Model Hawkins (2011) developed the CLEAR model to explain the process used to help a client to develop an issue. The term 'CLEAR' is an acronym that stands for Contracting, Listening, Exploration, Action, and Review. The CLEAR model emphasises that a great need exists for coaching in businesses in the present time to promote the growth of employees. The model suggests that managers should intervene in business processes to achieve maximum workplace potential. The model also suggests that employees are critical in achieving the organisation's objectives and goals. Therefore, employees should be committed to the company's goals, unlike complying with directives given by the organisation's managers. The CLEAR model aims to help individuals to achieve transformational changes. The model further emphasises that reviewing the business coaching session is essential because it encourages feedback from the coaches. Contracting. In the contracting stage, the client begins the discussion by explaining their desired outcomes and establishing ground rules with the business coach. According to Hawkins (2011), contracting issues, such as the time available for conducting the coaching sessions, are determined at this stage. Stout-Rostron et al. (2014, p. 104) recommended that business coaches ask their clients questions, such as what the clients would like to be coached about, what helps them to learn, and what impedes the learning process. These questions are crucial to the coach because the answers help them to determine the direction of the coaching sessions. The questions asked at this stage further help the business coach to determine the desired outcomes, including the client's intended outcomes and the shared desired outcomes. The contracting stage also helps to avoid confusion and misunderstanding during the business coaching process because the entire desired outcomes are determined here.

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Listening. According to Stout-Rostron et al. (2014), listening is a critical part of business coaching because the coachees will start understanding the coach, thus, generating personal insight. The authors provided several guidelines to be used by coachees during the business coaching sessions. First, coachees should spend 75% of a business coaching session listening to the business coach and only 25% speaking. Second, coachees should concentrate on the context of the message communicated by the business coach. Stout-Rostron et al. (2014) further recommended that coachees should assess the coach's non-verbal signals, including gestures, facial expressions, and body language. Non-verbal signals help the coachees to understand the content of the message from the coach. Exploration. In this stage, the business coach assists the coachees in understanding how a particular situation will have a personal impact on them. The business coach also challenges the coachees to think through all of the available possibilities that they can utilise to resolve the situation in the future. The business coach can use the exploration stage to help coachees to understand their assumptions about people's behaviour and the implications of these assumptions (Stout-Rostron et al., 2014). Action. The business coach helps the coachees to determine their next step and choose the best and most appropriate action for their business in this stage (StoutRostron et al., 2014). The coachee decides the next business steps to take on their own, depending on their personal insights gained from the business coaching sessions. Stout-Rostron et al. (2014) stated that coachees could ask themselves the following questions to decide on the best indicator of change: What can be done? Is there any alternative action? How will these action steps help to achieve the business goals and objectives (Stout-Rostron et al., 2014)?

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Review. In the review stage, the business coach ends the business coaching session by justifying the areas covered during the session, the decisions made by the coachees, and the value-added to them. The business coach also encourages feedback from the coachees regarding the benefits and drawbacks of participating in the business coaching process (Stout-Rostron et al., 2014). This feedback helps the business coach to identify the weaknesses and strengths of the business coaching programme to make the necessary changes in the future.

Business Coaching Business coaching refers to the process of business coaches guiding business owners in running their businesses successfully to improve their business performance (Blackman et al., 2016, p. 460). Business coaching also assists business owners in clarifying their business visions and determining how the visions match with their personal goals (The Alternative Board, 2015). Notably, The Alternative Board (2015) further defined business coaching as the process used by business coaches to take a business from its current state to the state the business owner wishes to attain. Business coaching creates sustainable change in the organisation by generating changes and transformations in the organisational culture (Klopper & Coller-Peter, 2018). Business coaching represents a relationship between coaches and coachees, where coaches bring their experience of previous business performance and coach the organisational owners and employees on achieving business success (Idris & Abu Bakar, 2020). According to Idris and Abu Bakar (2020), business coaching improves poor organisational performance and improves employees' individual competencies to promote business success. Henderson (2020) stated that business coaches are experts who assist entrepreneurs, professionals, and influencers in strategically achieving their

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business goals and objectives. The author emphasised that business coaches are necessary due to the changing business environment, which is complex, uncertain, and competitive. Therefore, businesses must vitally undergo business coaching to acquire knowledge on how to achieve a clear vision. Business coaching helps business leaders to identify critical steps to be undertaken in their businesses. A business coach helps business leaders to make better and more informed decisions concerning their businesses. According to Henderson (2020), business coaches offer business leaders appropriate growth plans, business strategies, implementation strategies, support, guidance, and personalised advice to accelerate the growth of their business and capitalise on their revenue. For example, business coaches identify business issues and subsequently address them by changing the business operations. Business coaches also discover business situations that would be extremely challenging for the business owner to discover (Henderson, 2020). Business coaches help business owners to evaluate the current business situations and to improve their knowledge to attain business success. Business coaches also assist business owners in unlocking selfimposed limitations, thus helping businesses to achieve their potential. Most business owners usually limit their potential by defining easily achievable business goals. Therefore, business coaches help owners to redefine these goals to achieve their actual potential. Stout-Rostron et al. (2014) asserted that business coaching helps business owners to learn from their past experiences and create the necessary wisdom for improving business performance. According to the authors, business coaches support and educate senior executives, business leaders, and managers (Stout-Rostron et al., 2014). The main objective of business coaching is to ensure that a business achieves

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its long-term goals by managing human resources, projects, communication, and conflicts effectively and efficiently. Interestingly, the same authors noted that business coaches help their clients to balance their work and personal lives besides managing stress (Stout-Rostron et al., 2014). Business coaches evidently not only focus on business perspectives but also on the well-being of their clients. The authors also emphasised that business coaches play a critical role in helping their clients become aware of their contributive roles in achieving business success and in enhancing their roles to become sustainable and measurable (Stout-Rostron et al., 2014). From the extensive assertions mentioned above, it is evident that business coaching offers the requisite knowledge, support, motivation, and skills to business leaders to improve their businesses. Business coaches further offer valuable strategies required to take businesses from one level to the next level. Thus, business coaching has an influence on employees and the performance of the organisation. Business coaching is arguably critical in SMEs as it offers leaders the required strategies to enhance business growth and maximise profit in the dynamic business environment. Noteworthily, a major difference exists between coaching and mentoring. Business coaches assist business owners in planning goals and objectives and hold them accountable for promoting their achievements. Moreover, business mentors focus on advising business owners (The Alternative Board, 2015). On the other hand, according to Stout-Rostron et al. (2014, p. 16), mentoring involves conversations with clients. During mentoring, the business mentor provides advice and expertise to help clients. In contrast, coaching involves developing question frameworks that assist clients in developing appropriate strategies for creating solutions to specific business issues. Furthermore, business coaching helps business owners and organisational leaders establish better organisational goals, achieve those goals fasters, make better

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organisational decisions, and improve relationships with employees (Stout-Rostron et al., 2014). Notion (n.d.) stated that business coaching differs from business training. First, training only focuses on what business owners should undertake to improve business performance, but it does not promote accountability. Business coaches engage business owners in the process of achieving business success. Moreover, business coaching helps business owners to discover their actual business potential. Business coaching can take two forms, namely face-to-face or virtual meetings between the business coach and the client (Joseph, 2016). Business coaching equips enterprise employees with the relevant skills required to improve enterprise performance and productivity (Grover & Furnham, 2016). Blackman et al. (2016) outlined the benefits of business coaching, including identifying issues affecting business performance, recommending business growth solutions, sharing business knowledge expertise, and creating owner accountability. The authors reiterated that business coaching is highly effective compared to other forms of training and development as it is grounded in the business owner's workplace. In addition, Kandasamy et al. (2015) stated that training and coaching are essential for boosting the performance of SME employees because the performance impacts the entire performance of the organisation. Al Mamun et al. (2016) observed that training may assist SME employees in acquiring the skillsets, knowledge, capabilities, and competencies required to achieve performance requirements and expectations of enterprises. The authors stated that training for small and mediumsized businesses is essential since training provides more knowledge about firm development in general. Therefore, employees of SMEs are able to run their businesses effectively and efficiently, contributing to the expansion of SMEs when they receive

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this training. During training, entrepreneurs of SMEs share ideas and experiences with other trainees, which stimulates the growth of SMEs. Coaching improves employee performance since it satisfies their particular requirements and tackles their skill shortcomings (El Achi & Sleilati, 2016, p. 138). Coaching assists employees in enhancing their performance by boosting their morale, confidence, and self-esteem and lowering work-related stress and worries. Cicea et al. (2019, p. 1615) concurred that the training of SME personnel is vital since it contributes to the growth of the business. Coaching increases the self-awareness of employees, which motivates them to perform at their best in the workplace. The authors also noticed that training enhances SME performance. According to Motilewa et al. (2017), SME owners and entrepreneurs may obtain business-enhancing skill sets, competencies, capacities, and knowledge through training and mentoring. Wang et al. (2015) highlighted that SME owners must manage several company elements on their own, unlike the heads of multinational firms or large-scale enterprises. Notably, SME owners must also guarantee that their staff receive proper training and coaching to enhance the successful operation of their businesses. Coaching enables SME owners to efficiently manage company activities such as business administration, branding and marketing, operations management, and personnel management (Brinkley & Le Roux, 2018). Ideally, the performance of SMEs is dependent on each of the business operations (Ludwig & Owen-Boger, 2017). In conclusion, SME owners may improve the performance of their businesses by assuring that the employees are taught and coached, enhancing their knowledge, skill sets, and competencies. Mentoring and training have a substantial impact on the overall performance and output of employees (Hamidi et al., 2018). Al Mamun et al. (2018) observed that

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over the past decade, employees' job duties and responsibilities have tuned increasingly complicated. Consequently, training is essential for adjusting to the changing business environment and gaining new skills. Rosyadi et al. (2020, p. 1) stated that workers must be taught with a plan tailored to their actual requirements, which would increase their capabilities and contribute to the growth and performance of the organisation. Businesses also provide sophisticated on-the-job training to improve the quality and quantity of employee performance (Rahim et al., 2015). Coaching inspires people, hence, enhancing their productivity. Growth and profitability are also enhanced by employee productivity. The management of SMEs can assess employee success following training to anticipate business success. Grant and Gerrard (2019) claimed that coaching assists employees in defining the organisation's goals and in working to achieve them. In addition, Rosyadi et al. (2020, p. 5) emphasised that continuous staff training is necessary for the sustainability of an organisation. Continuous training allows employees to retain more of their acquired information and abilities. Training has a significant impact on employee performance. According to Noori et al. (2017), the fundamental purpose of training programmes is to facilitate the acquisition of information, skillsets, and competencies by employees, which not only increases the quantity and quality of their performance but also enables them to fulfil performance requirements and anticipations. Individual performance development is vital since it adds directly to the overall success of the organisation (Noori et al., 2017). Likewise, coaching enhances worker performance, which has a positive impact on overall performance. Minzlaff (2018) deduced that coaching modifies workers' troublesome behaviours, hence enhancing their performance. The author observed that coaching offers a methodology that optimises organisational performance. Importantly,

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individuals may learn management and leadership abilities or attributes through effective coaching and other talents (Haruna & Marthandan, 2017). This link significantly impacts workers' job satisfaction, morale, and motivation hence, enhancing their performance and output. Through staff training and mentoring, SMEs may realise organisational growth (Saat & Talib, 2015). Finally, the literature has suggested that business coaching leads to improved business performance (Dobrea & Maiorescu, 2015; Núñez-Cacho Utrilla et al., 2015). Dobrea and Maiorescu (2015) noted that business coaching increases the effectiveness of interactions in the workplace, which results in improved organisational performance. Business coaching increases business owners' knowledge and the skills required to promote the long-term success of the business.

Small and Medium-Sized Enterprises (SMEs) As stated previously, SMEs represent the majority of all businesses globally. The definition of an SME is critical for access to funding and assistance programmes designed expressly for small businesses. While definitions of what makes an SME might differ, they always focus on a firm's potential to create jobs, with staff count being a typical measurement. Nonetheless, categorising SMEs according to their employee count varies. For example, Kim et al. (2017) classified small enterprises as those with fewer than 200 workers. Highfill et al. (2020) recently asserted that businesses with 100 to 499 people could be classified as medium-sized. The European Commission agreed to use worker headcount as a criterion for business size, classifying SMEs as organisations with between ten and 250 people (Highfill et al., 2020). The European Commission also established four classifications for the number of individuals employed in non-agricultural businesses. For instance,

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micro firms have fewer than five employees. Small firms have between five and 20 employees, medium-sized firms comprise between 20 and 200 employees, while large firms with 200 or more employees (Highfill et al., 2020). Numerous aspects influence the growth of SMEs. In spite of staff size, it is widely recognised that all businesses, whether for-profit or not-for-profit, operate on a similar fundamental tenet, namely to produce, sell, or impart products and services in response to client demands and requirements (Kim et al., 2017). Nevertheless, a complex combination of elements, including the growth stage, shareholder influence, product or service offering, consumer demand, global reach, staff competence, and capacity to adapt to change, all combine to affect desired performance levels (Stoffers et al., 2020). While criteria for goods and services production vary by industry and are influenced by critical characteristics including age, asset base, yearly sales, and ownership type, SME growth may be assessed fairly in terms of sales, profit, market share, or earnings per share (Kim et al., 2017). The sections that follow provide an overview and conceptualisation of the stages of business growth.

Firm Growth Conceptualisations Most organisations proceed through phases of growth in various degrees of overlap, trajectory, or regression, beginning with birth and survival, expanding, professionalising with formal structures and processes, then consolidating efforts, and eventually bureaucratising (Merkle, 2020). With several conflicting factors impacting activity and strategic direction, expansion throughout the complete spectrum is not always a linear process. Expansion can take as little as three years in several situations and as long as ten years in others to transition goods and services from idea to

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commercialisation (Merkle, 2020). Hillary (2017) argued that SME development within a certain environment of influencing variables is a predictor of entrepreneurial activities. Huggins et al. (2017) noted that a variety of factors contribute to the formation and growth of new firms, including entrepreneur qualities, organisational structure, present environment, and measures done to establish and encourage company longevity. Huggins et al. (2017) also emphasised the need to evaluate competitiveness, company differentiators, customer choice and market demand for products and services, and total revenue minus expenses. Additionally, company demographics, including age, size, and industry, provide another dimension to the performance by affecting growth, profitability, risk tolerance, internal control, and hence performance (Yang et al., 2018). Entrepreneurial managers who grasp the internal and external dynamics that necessitate strong leadership, good company structures, system controls, management focus, and incentive systems are better equipped to survive and create sustainable firms in volatile circumstances (Yang et al., 2018). Firms continuously change through numerous stages of growth, influenced by both internal and external influences. During the start-up period of growth, an entrepreneur and possibly one or two individuals are responsible for the organisation's direction, strategy, vision, and operations management (Merkle, 2020). Tortorella et al. (2020) argued that organisations' growth paths are not always linear and are influenced by factors such as customer base, product capacity and delivery, and available capital. As markets undergo expansion, additional resources are required. With the responsibility of managing the resources comes the responsibility for effectively managing people. As a result, firms that have efficient procedures to govern the activities of individuals

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involved in the creation of goods and services have a better chance of survival and growth (Bongomin et al., 2017). While aversion to bureaucracy can result in flexible and rapid responses to client requests, as SMEs become large, issues such as lax controls or non-existent processes can derail a business (Merkle, 2020). Additionally, re-occurring challenges in SME growth are a result of ineffective managerial practices in the marketing, accounting, inventory control, and cash flow domains (Bongomin et al., 2017). Nevertheless, growth has a cost. Lee et al. (2021) discovered that while high-growth organisations had a greater array of resources and capacities at their disposal, they lacked the dexterity to respond swiftly to market pressures in a similar way as moderate-growth enterprises. Hands-on entrepreneurial approaches may be relevant during the initial growth stages when tight controls must be retained and resources are stretched thin. Nonetheless, growth usually requires a high external focus, the establishment and implementation of procedures and processes, and an increased focus on long-term strategies as prerequisites for running an organisation efficiently and profitably (Lee et al., 2021). Management competencies and good leadership are necessary components for organisations to retain a flexible attitude to market dynamics as they increase in size. Neneh and Van (2017) hypothesised that prior entrepreneurial experience, in combination with present environmental variables, predicts entrepreneurial inclinations and firm growth. Notwithstanding, the business size is not determined by environmental unpredictability or complexity but instead by entrepreneurs' ideals and motivations (Neneh & Van, 2017). Akpan et al. (2022) asserted that entrepreneurs encounter additional issues related to competitive pressures and resource management

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when enterprises develop in size. Firm growth is accomplished through individuals. Unlike before the industrial revolution, when employees were given orders to comply, individuals nowadays are supposed to be self-conscious, aware of their strengths and shortcomings, and self-motivated (Akpan et al., 2022). Therefore, executives who come from technical backgrounds must first learn how to manage and delegate successfully and subsequently assess performance. Developing a self-awareness that would aid leaders' professional development and serve as a springboard for dealing with employee motivation and transformation is critical in SME growth (Fraser & Schwind, 2017). For growth to be effective, the production of products and services must be directed by individuals who are competent and motivated to behave, act, and collaborate in order to fulfil the organisation's vision and objectives. In order to develop connections, firms have to manage organisational politics and convey a clear vision to their employees to maintain development (Evans et al., 2021).

SMEs with Rapid Growth Researchers initially became aware of fast-growing enterprises about three decades ago. Carland et al. (2018) argued that entrepreneurial enterprises are distinguished from small firms by their commitment to creative, strategic activities aimed at growth and profitability. According to D'Angelo and Presutti (2019), few small enterprises are capable of achieving rapid development on a constant basis and sustaining rapid development. The attempt to categorise fast-growth firms results in divergent interpretations of business trajectory, such as compound sales growth from a revenue base and, elsewhere, a growth rate of more than 40% per year on revenue (D'Angelo & Presutti, 2019). Exposito and Sanchis-Llopis (2018) concluded that

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rather than high growth occurring consistently across businesses, it is multidimensional, with characteristics such as firm age, size, and environment playing a role in achieving growth. Klongthong et al. (2020) cautioned that employing performance satisfaction as a measure is not supported by data, while founder-reported metrics of growth and company volume are viable constructs for measuring success. Younger, high-growth businesses typically require considerable investment in resources and infrastructure to expand. Significant aspects leading to rapid growth involve creative goods, distinctive selling talents, product quality, high-profile leadership, regional expansion plans, and ongoing investment in increasing the product variety through expansion into new markets (Exposito & Sanchis-Llopis, 2018). Additionally, other factors that contribute to rapid growth include strategic management, tight company control, effective leadership, and early-stage human development (Na-Nan et al., 2017). According to De Massis et al. (2018), effective businesses maintain a laser-like focus on objectives and meticulously manage financial projections and cash flow. The primary issue for the majority of high-growth enterprises is acquiring financial capital, with high-technology initiatives appearing to be an exception (Exposito & Sanchis-Llopis, 2018). Numerous entrepreneurs finance their companies using personal savings or loans from friends and family. An archive study concerning social resources of service sector enterprises in the form of affiliations and network connections supported the expansion. On the other hand, other organisations have access to government funding or are sufficiently developed in their growth phase to participate in capital raising (Exposito & Sanchis-Llopis, 2018). Nevertheless, investors face concerns about the experience of entrepreneurs and their abilities to

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handle significant quantities of cash successfully while developing enterprises rapidly (Carland et al., 2018). Carland et al. (2021) discovered that organisations engaged in creative, disruptive technologies benefited from processes and structures that helped underlie and drive growth. Based on prior research, the aversion of certain entrepreneurs to embracing systems and procedures hampered development. In contrast, entrepreneurs who took a more managerial approach in their companies were more likely to succeed. High-growth businesses were more inclined to invest in infrastructure to support and automate systems and processes as a method to sustain expansion (Abdissa et al., 2021). Having the right employees is crucial for achieving a sustainable growth trajectory, but inadequately competent resources are a substantial impediment. As stated in prior studies, Zhan et al. (2018) mentioned that growth barriers might include the following: increased competitiveness, particularly during economic downturns, geographic expansion without adequate planning or management controls, and inadequate management. On the other hand, the authors were unable to establish a meaningful association between processes or interactions that could contribute to business growth. Entrepreneurs who are willing to address their shortcomings, accept feedback, and be receptive to learning tend to scale up operations successfully and attain company development (Zhan et al., 2018). The incentives of entrepreneurs to focus on end goals and the flexibility to adapt capacity to market forces by situating near consumers are also critical for development. Along with a lack of ambition to achieve, it has been suggested that growth inhibitors might originate from gender difficulties, a need for security, and the personality traits of entrepreneurs (Zhan et al., 2018). Even though budding

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entrepreneurs with strong social networks also demonstrated a high level of selfefficacy and were more motivated to succeed, not all founders desire rapid growth. Several founders actively resist investment offers. The opposition of founders to expansion may be motivated by a desire to retain a certain lifestyle over shareholder involvement (Zhan et al., 2018). Over the last three decades, it appears as though the understanding of entrepreneurial qualities has remained stable. Entrepreneurs were once defined as founders and managers of their own businesses with the goal of achieving profit and attaining growth (Zhan et al., 2018). Despite the fact that entrepreneurs are more likely than non-founders to achieve faster growth rates, several entrepreneurs manufacture goods by disregarding marketing requirements, customer demand, or production costs. Hence, these entrepreneurs fail to establish businesses to commercialise their ideas (Abdissa et al., 2021). Serious entrepreneurs usually start and build firms in response to market needs that may be met through the provision of products and services (Abdissa et al., 2021). Nevertheless, the differences between inventors and entrepreneurs get blurred when entrepreneurs with inventive orientations who work in high-technology organisations have a high demand for accomplishment, a desire for autonomy, and an openness to experience (Carland et al., 2018). Nonetheless, entrepreneurs showed considerably stronger self-efficacy and sensed greater control over adversity and accomplishing results than nonentrepreneurs. Entrepreneurship is frequently recognised for its benefits, which include decision-making, freedom, and independence (Exposito & Sanchis-Llopis, 2018). Entrepreneurs' motivations for new enterprises might range from discontent with their existing employment or circumstances to a desire to be independent (Bandura, 1992), all of which fuel their desires to strike out on their own (Corman et

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al., 1988). Motives for starting a business might include a desire to innovate, wealth creation, self-realisation, financial success, the difficulty of running the business, and independence, all of which are likely similar to why individuals choose careers (Exposito & Sanchis-Llopis, 2018). Nonetheless, independence places small company owners under psychological and financial strain. Entrepreneurs' demand for independence is highly connected to their willingness to take risks in order to generate future revenue (Na-Nan et al., 2017). Moreover, SME managers with higher education, skill, ability to secure higherpaying work, and a sense of self-worth in the market, especially in high-technology fields, seem to be unconcerned about the risks associated with starting a business. Additionally, self-belief can influence motivation and behaviour, with highly educated SME managers having a greater chance of success and access to financial borrowing (Abdissa et al., 2021). Furthermore, self-efficacy is closely associated with goal accomplishment demands, implying that it has a direct influence on performance. Entrepreneurs with internal or stable characterisations who made substantial sales to the degree of activity were far more likely than entrepreneurs with external or stable characteristics to dedicate considerable time to business creation (Srimulyani & Hermanto, 2021). Successful SME managers appear to be defined by their capacity to redefine profit drivers in conjunction with their abilities to respond to market dynamics, such as reconfiguring product offers, modifying ways of distribution, and reducing administrative costs (Mawson & Brown, 2017). Notwithstanding, entrepreneurs with a clear vision and mission, as well as the capacity to distribute resources and train employees on how to attain shared goals, are said to bear the ultimate responsibility for firm success, with success or failure relying on their entrepreneurial personality

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(Mawson & Brown, 2017). While numerous entrepreneurs appear to have distinct qualities, such as achievement requirements and a risk-taking proclivity, advancement through phases of personal and business growth can occur asynchronously (Mawson & Brown, 2017). A high need for personal participation and control might impair the willingness of entrepreneurs to delegate and work collaboratively with workers, impairing their capacity to attract and keep qualified talent over time (Mawson & Brown, 2017). Entrepreneurs in challenging circumstances frequently exhibit features of high achievement orientation due to the isolation associated with SME ownership, resulting in job stress and physical symptoms to the degree of coronary heart disease (Abdissa et al., 2021). While contextual factors had an indirect effect on initiatives, certain talents and drive were direct predictors of business development. Entrepreneurs with high levels of energy, creativity, and imagination may excessively pursue ideas and exhibit destructive tendencies at the cost of seeking guidance from workers about the realities of the situation (Abdissa et al., 2021). While entrepreneurs can be charming, motivating, and innovative, they can also exhibit narcissistic tendencies such as emotional isolation and mistrust, with little consideration for employee or stakeholder concerns (Na-Nan et al., 2017). Additionally, entrepreneurial characteristics, behaviours, and beliefs influence the financial performance of a business (Na-Nan et al., 2017).

Development Requirements of SMEs Globalisation, competitiveness, and economic instability have escalated to the point where entrepreneurs are increasingly looking for novel and quick methods to innovate and adopt constant changes. Due to time limitations and a need for ready-to-

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use frameworks, processes, and appropriate responses to business imperatives, numerous entrepreneurs are unwilling to invest energy in acquiring information that will not be immediately beneficial for their firms. Traditionally, training has taken the form of university degrees. Nevertheless, entrepreneurs are not always ready or able to take time off to attend classes for an extended length of time. According to McKenzie (2017), SME managers seeking commercial expansion regard business schools as being confined to teaching theories and case studies about huge organisations. Although the theories and case studies provide vital information, the knowledge has little relation to SMEs in the real-world and day-to-day problems. Academic and scientific programmes are being discarded in favour of short, relevant learning experiences led by practical professionals (McKenzie, 2017). Formal education may impart certain business skills and process management strategies. Nevertheless, it does not always address problem-solving abilities in the context of entrepreneurs adopting alternative management styles capable of efficiently achieving end results (McKenzie, 2017). On the other hand, managing company development becomes challenging when entrepreneurs lack expertise in business or operating a business. Rather than wanting knowledge transmission, entrepreneurs desire to learn how to think at a higher level and conceptualise their enterprises (Na-Nan et al., 2017). After assessing entrepreneurs, it is clear that the most critical areas of learning for entrepreneurs were financial decision-making, growth, business value, and resources. According to Na-Nan et al. (2017), early-stage entrepreneurs sought guidance on company planning and implementation, strategy, marketing, and growth planning. Additionally, SME managers require specialised, readily transferrable abilities relevant to the current operational business environment. Providing entrepreneurs with the option to bring their challenges to the facilitator in a generalised

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approach enables them to benefit from a collective conversation where they tend to generate insight and, therefore, adopt solutions in their own setting (Na-Nan et al., 2017). Short-term external management training focused on the financial return to company performance contributed to business survival in a cross-sectional follow-up study of small and medium manufacturing enterprises (Burlea-Schiopoiu & Mihai, 2019). When offered the opportunity to study, entrepreneurs favoured relevant, handson programmes and broad-ranging disciplines such as commercialising goods and services, financing and funding, marketing, and company growth techniques (BurleaSchiopoiu & Mihai, 2019). After completing a management development programme, business managers might be satisfied with the programme. Besides that, the learning can be translated into improved customer service and external relations and image (Burlea-Schiopoiu & Mihai, 2019). Thus, evolutionary learning from experienced individuals, such as external directors, is more helpful than theoretical training. Entrepreneurs' learning requirements vary according to the internal and external elements they confront on a daily basis and the stage of growth of their organisations. Entrepreneurs are active in all aspects of the firm throughout the startup period, including vision, strategy, direction setting, and operational management (D'Angelo & Presutti, 2019). Entrepreneurs at this stage seek practical guidance and ideas on company planning and implementation, strategy, marketing, and expansion planning. D'Angelo and Presutti (2019) argued that entrepreneurs might exert substantial influence throughout the early phases of firm development by networking with informed stakeholders, suppliers, and business people. Besides, owing to the isolation associated with overcoming daily obstacles, learning circles with other

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entrepreneurs in similar situations may provide excellent learning opportunities that are not accessible in theoretical courses (D'Angelo & Presutti, 2019). The managers of SMEs may be unable to address the high workload and instead attempt to maintain tight control over all business aspects. As a result, they must adapt to delegating and trusting employees. Therefore, learning must include strategic management and prioritisation of staff development (D'Angelo & Presutti, 2019). Entrepreneurs might profit from programmes that combine training and business coaching, in which peers from non-competing organisations attend training together and subsequently work one-on-one with a business coach (Ofili, 2018). Additionally, entrepreneurs might enrol in training programmes to increase their selfawareness, pursue personal objectives, impact change, or acquire a highly effective leadership style (Ofili, 2018). The managers of SMEs valued engagement with peers and favoured programmes presented in round-table, half-day forms by working professionals. Ofili (2018) stated that effectiveness-based programmes tend to be more successful when training is accompanied by business coaching. Entrepreneurs frequently encounter subordinates who tell them what they want to hear rather than what they need to hear. Alternatively, Cuéllar-Molina et al. (2019) denoted that leaders can appear to be confident in their own competence and talent that they do not have sufficient emotional intelligence necessary to cultivate connections and hence seek advice from other individuals. The authors stated that entrepreneurs' cognitive processes and thinking patterns around perceived or actual failures could either weaken or strengthen their capacity to remain concentrated on activities despite situational challenges. Entrepreneurs may lead firms into very profitable undertakings by transforming themselves through self-development and personal awareness into a

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state of analysing their environment and arriving at innovative solutions (CuéllarMolina et al., 2019). Leaders that are behaviourally aware identify their faults, learn from their mistakes, rectify their acts, and modify company operations appropriately participate in what is referred to as double-loop learning or developing competencies through self-help learning (Cuéllar-Molina et al., 2019). Not all entrepreneurs benefit from a sometimes occasionally overlooked component of growth management, namely honest and objective performance feedback. When combined with the loneliness inherent in the job, isolation may result in entrepreneurs committing strategic business mistakes, being oblivious of operational challenges, exhibiting selfish or authoritarian behaviours, and experiencing worry and stress that manifests as health problems (Cuéllar-Molina et al., 2019). While some entrepreneurs take frequent vacations, meditate, and connect with family and friends to cope with many pressures, only a few entrepreneurs seek psychiatric counselling. Nonetheless, when economic and organisational demands rise, some entrepreneurs look for mentors with experience in their particular business or profession for sponsorship, advocacy, performance advice, or as sounding boards (Cuéllar-Molina et al., 2019). Lately, entrepreneurs in SMEs have engaged business coaches for several reasons, including the loneliness associated with senior positions, the immensity of constantly making choices, and the stress placed on family life and health by such roles (Molina et al., 2019). Entrepreneurs receive assistance from business coaches who demonstrate comprehension and give criticism, which is crucial for entrepreneurs to keep ahead of competing demands. Additionally, skilled business coaches equip entrepreneurs with the skills necessary to manage and operate their businesses efficiently (Molina et al., 2019).

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Business coaching is most effective when preparation and planning are properly implemented, with clear definitions of responsibilities and role expectations at the start, followed by developmental assistance at regular intervals. Thus, a suitable fit between an entrepreneur and a business coach in terms of necessary ability and experience is critical. Training can also guarantee that each party knows the nature of the relationship and its expectations (Widhaningrat, 2021). While business coaches working with entrepreneurs might help alleviate entrepreneurs' lack of expertise, identifying competent individuals with the necessary background and skills to impart information can be challenging (Widhaningrat, 2021). Nonetheless, entrepreneurs' maturity, self-reliance on business coaching and SME growth, and determination to build their businesses may eventually exceed the need for coaches or mentors (Widhaningrat, 2021).

Growth and Performance of SMEs The expansion of SMEs is one of the most studied issues in empirical research on SMEs. It is typically impacted by financial reasons, non-financial factors, and technology (Tong & Serrasqueiro, 2020). The financial criteria involve profitability, insufficient liquidity, high gearing, and return on investment, whereas the nonfinancial aspects are assessed by sales and market share. Tong and Serrasqueiro (2020) have stated that the rise of SMEs has a positive effect on national economies. In addition, they noted that the enhanced efficiency of SMEs also contributes to economic growth since efficient SMEs may grow and survive in the market. Moreover, as reported by the authors, growth factors may be divided into external, firm-specific, and founder-specific aspects. Twesige and Gasheja (2019) concluded that SMEs must attain a sustainable growth rate to have a competitive edge in the market. The authors

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also asserted that SME growth might be assessed by a rise in assets, an increase in retained earnings, and steady, sustainable growth. The authors also emphasised that incentives, including government tax rebates, lessen the responsibility of SMEs, leading to increased growth. As a result, nations should implement numerous incentives to boost the growth and sustainability of SMEs. Salder et al. (2020) hypothesised that staff knowledge and learning contribute to the growth of SMEs. The authors observed that employees contribute value to key capabilities after learning necessary information and training, propelling the SME to the next level. In order to achieve the desired growth, they also noted that SMEs must complete a process. Growth is a natural and important process for all organisations. Profitability and product advantages dominate the growth trajectory of businesses. Consequently, SMEs are willing to raise profitability and develop product benefits in order to promote sustainable growth. Salder et al. (2020) determined that the characteristics of SME growth include assets, strategies, characteristics, and the environment. The assets comprise human capital, tacit knowledge, and finances, whereas the strategies include process, product, and personnel development. Additionally, the features include the business structure and scale. On the other hand, the environment relates to the market and industry of the business. The growth paradigm is critical to the survival of SMEs. Tehseen et al. (2019) claimed that an SME's growth is contingent on its strategic and ethical competencies. Strategic and ethical competencies affect business performance, therefore assisting SMEs in developing their network competency. The competencies help small businesses access essential business resources, such as skills, knowledge, and technology. Therefore, network capabilities are essential for achieving corporate success. Tehseen et al. (2019) also emphasised that entrepreneurial skills are

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crucial in determining the success of SMEs. These competencies encompass personal, learning, ethical, opportunity, and strategic competencies. The competencies are crucial abilities that SMEs should utilise to achieve growth. Tehseen et al. (2019) recommended that firms in Malaysia use network competence to achieve success. In addition, they maintained that talents are unnecessary for corporate expansion. According to Possumah and Appiah (2018), institutional support, particularly in leadership, promotes SME growth. The authors outlined that institutional support refers to how organisations care for the welfare of their personnel. Businesses flourish when their people are optimised. They recommended that institutional assistance is intended to strengthen the organisation's dynamic capacities. It should be applied with strategic plans to fulfil the organisation's objectives. The corporate expansion enables organisations to expand their growth pattern and profit margins, consequently improving business advantages. According to Ipinnaiye et al. (2016), training and innovation are crucial growth drivers for SMEs. The authors also stated that training fosters the growth of SMEs because it encourages the investment in human capital, which is a valuable resource for organisations. Therefore, Malaysian SMEs may train and advise their staff in accordance with their business growth strategies. El Shoubaki et al. (2020) argued that human capital is essential for SME growth. The authors discovered that employees must be motivated to perform properly, which ultimately leads to the success of the organisation. Abilities, skills, and knowledge are examples of human capital traits. El Shoubaki et al. (2020) advised small and medium-sized businesses to invest in human capital to achieve company success. Human capital is mostly accumulated through education and training. According to Wang et al. (2020), SME growth is a stimulus indicator since it is utilised to monitor operational circumstances. The writers also emphasised that corporate

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growth is assessed by sustainable development, dynamic capacities, and a company's future development. Ullah (2020) argued that access to capital is essential for the success of SMEs. Moscalu et al. (2020) concurred that the growth of SMEs needs financial assistance. A scarcity of research exists on the impact of business coaching on the growth of SMEs in the nation despite the fact that several studies have examined SMEs in the Malaysian setting (Ripain et al., 2017; Mustafa et al., 2020; Rozmi et al., 2020). This gap must be addressed to establish the influence of business coaching on the rapid expansion of Malaysian SMEs. Thus, one of the study's purposes is to explore the effect of business coaching on the growth of high-impact SMEs in Malaysia. Distinguishing between SMEs and large businesses and their distribution is a decent estimate of the actual shape of the distribution of the company size within the economy, but it is still a matter of controversy (Growiec et al., 2008; Luttmer, 2010). The confusion surrounding the topic suggests that a limited number of major enterprises co-exist alongside a high number of small firms (Segarra & Teruel, 2012). Nevertheless, the fact that small businesses dominate the commercial scene by sheer numerical weight is not the only factor that has contributed to an increase in research concentrating only on SMEs. The reasons for distinguishing between SMEs and large corporations are summarised by examining both the theoretical and empirical causes of growth and performance discrepancies.

Business Development as a Structural Factor The realisation that SMEs are not scaled-down replicas of major enterprises is the primary argument for recognising them as distinct research objects (Mawson & Brown, 2017). Clearly, organisations do not keep their structures when undergoing

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expansion. Hannan and Freedman (1977) compared the growth of a mouse to that of a home. The mouse must undergo significant structural adaptations to preserve its structural integrity as it matures. It cannot keep the same ratio of weight to skeletal structure as it matures (Yeboah, 2021). Similar structural inequalities are also visible in the predominant financial arrangements employed by SMEs, where agency fees hinder access to long-term debt and equity financing, hence increasing their reliance on internally produced finance. As per the transaction cost economic theory, the firm's expansion is constrained by "the governance cost limitations of the internal organisation" (Mawson & Brown, 2017). Therefore, when businesses expand, organisational, coordination and communication issues occur as a result of management limitations on control and direction, necessitating structural reform (Yeboah, 2021). Size has been long regarded as one of the most significant contingency factors in studies of company performance and growth. The larger organisations often have greater resource slack, better specialisation and expertise, a larger market share, greater brand recognition, and greater economies of scale and breadth, which translate to greater efficiency, lower costs and stronger net income growth (Yeboah, 2021). Large firms are highly complicated, which leads to more bureaucracy and slower information-processing systems. In contrast, SMEs possess more organisational structure flexibility, faster decision-making and responsiveness to their external condition, higher entrepreneurial drive, motivation, risk-seeking behaviour, and persistence; management proximity to customers and the shop floor, and higher ability to react to qualitative changes in market demand, adjustable production technologies, flexible specialisation, and stronger capability to absorb demand fluctuations. The liability of smallness alludes to the disadvantages associated with small size, which

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are often tied to resource constraints and legal challenges (Mawson & Brown, 2017). Small businesses have human resources and financial drawbacks but possess behavioural advantages (Mawson & Brown, 2017). The diminishing relevance of scale economies makes small businesses more competitive with the development of the economy based on knowledge as they are more adaptable and possess more knowledge-based assets (van Stel et al., 2014). The statement corroborates with the views in resource-based theory that persistent competitive advantage is the outcome of bundles of both tangible and intangible resources (Yeboah, 2021). Besides, SMEs may hold intangible resources with the highest strategic potential for creating lasting competitive advantages, although SMEs are at a disadvantage in relation to physical resources (Mawson & Brown, 2017). Physical resource-constrained SMEs would highly depend on intangible resource acquisition, development, exploitation, and leveraging. Conversely, these firms would have to directly compete on price with highly efficient large firms, which would severely impact their performance prospects (Yeboah, 2021). An industry's minimum efficient scale and expansion are a necessity for existence, and the relative growth rate demonstrated by firms has proved to be a significant differentiator between large and small businesses (Mawson & Brown, 2017). The firm size distribution in an industry will be skewed, and the degree of skewness will increase with time iff the growth rates of the firms are random (Yeboah, 2021). The heavily skewed upper tail often indicates that fewer huge businesses would cohabit with a considerably bigger and rising number of smaller firms. Academics studied the veracity of the idea that business size has no predictive association with future growth to test the random growth hypothesis because the growth rate can be independent of the firm size. The majority of the data imply that the random growth

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hypothesis does not apply to small enterprises, as they regularly expand faster than bigger firms on average (Mawson & Brown, 2017). One of the initial explanations for this anomaly was hypothesised that the law of proportionate impact only applies to enterprises operating over a minimum efficient scale in an industry (Yeboah, 2021). Consequently, small enterprises operating below the minimum efficient scale of the sector would need to expand swiftly to secure their long-term existence. A recent study revealed that expansion and survival go hand-inhand for small businesses since growth appears to ameliorate the relative cost disadvantages suffered by small businesses (Mawson & Brown, 2017). In addition, the small-firm survival disadvantage emerges as a result of particular sector features, such as the relative relevance of sunk costs, industry development, scale economies, and capital intensity (Yeboah, 2021). According to Yeboah (2021), small enterprises are extremely likely to operate at the minimum efficient scale in the service sector. In stark contrast to the manufacturing industry, the authors subsequently discovered evidence that Gibrat's law applies to service sectors (Dutch hospitality industry) characterised by fewer sunk costs and scale economies. Small businesses in these industries are not required to develop rapidly to assure their survival. As recommended by the industrial organisation perspective, this advantage appears to highlight the relevance of industry selection, particularly for small and medium-sized businesses, as a factor in firm success (Yeboah, 2021). It is vital to highlight that the average growth rate variance of small enterprises is greater than large ones over time, although expansion improves the survival chances of small organisations, and small firms appear to expand quicker than big firms on average (Mawson & Brown, 2017). Therefore, rapid expansion is more irregular and

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less likely to be sustained in small businesses (Coad, 2007). Small businesses with strong growth in a year are statistically more likely to suffer low growth in the following year than bigger enterprises with less volatility (Yeboah, 2021). The age of the firm influences the relationship between firm size and growth, which ties directly to the preceding statement regarding the relationship between growth and survival. For instance, smaller organisations less than five years old have substantially greater growth compared to older small businesses on average (Lawless, 2014). The combination of greater mortality and start-up rates among SMEs suggests that they are younger than their bigger counterparts on average, rendering them prone to "the liability of newness" (Mawson & Brown, 2017). The risk associated with novelty is attributable to three factors. The first factor points out that new SMEs have limited resources, which hinders their capability to capitalise on development possibilities (Yeboah, 2021). Secondly, legitimacy (which is a social assessment of acceptance, appropriateness, and attractiveness) and network links are formed through time, suggesting that new enterprises lack both of the resources, which restricts their access to other resources required for survival and growth (Lampadarios et al., 2017). Lastly, young companies lack formalised routines and roles, giving them the initial flexibility to seize possibilities, especially in areas that are constantly changing or evolving. Nevertheless, the lack of structure eventually leads to ambiguity and confusion, which hinders the functioning of the company (Lampadarios et al., 2017). It is crucial for emerging enterprises with limited resources to adopt fundamental structural characteristics while establishing more formalised organisational positions. Formalised organisational positions minimise task uncertainty, enhance individual attention, learning, and decision making, reduce coordination costs and boost

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productivity (Mawson & Brown, 2017). Devoid of finances, legitimacies, social links, and formalisation of roles, new small businesses differ significantly from their bigger, more established counterparts. Moreover, research suggests that a disproportionate percentage of the turbulence or high growth variation among small businesses is attributable to a small number of enterprising SMEs experiencing very fast development (known as gazelles) (Mawson & Brown, 2017). The majority of small and medium-sized businesses (also known as subsistence or lifestyle businesses) (Lampadarios et al., 2017) do not grow much in real terms, particularly when accounting for inflation (Yeboah, 2021). The larger growth variation among SMEs may be enlightened by the positive relationship between growth ambition and actual growth (Yeboah, 2021). This result is consistent with the behavioural theory, which asserts that firm growth is exactly proportional to the desired level of firm size (Lampadarios et al., 2017). Most small businesses do not develop because they intentionally do not wish to expand as larger business entities. Evolving into larger business organisations would entail experiencing the negative effects of control loss and increased bureaucracy related to growing staff numbers. There is a limit to expansion because of the governance cost disabilities of the internal organisation or the "decreasing returns to the entrepreneur functions," with several entrepreneurs opting to stay independent SME owners instead of becoming managers in huge organisations (Mawson & Brown, 2017).

SMEs Market Growth The tendency of small enterprises to primarily service niche markets or "interstices" in an attempt to avoid competition with larger firms that do not view the smaller niches as economically viable may also contribute to their modest growth

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aspirations (Yeboah, 2021). In oligopolistic markets, product differentiation according to quality, design, customer service, or location allows SMEs to achieve small individual market shares (Yeboah, 2021). Small and medium-sized businesses have greater development potential in labour-intensive industries or when they are capable of filling gaps with specialised products that are not offered by mass manufacturers. Large corporations are not capable of exploiting all specialised opportunities in growing markets that are available to SMEs (Yeboah, 2021). It may be necessary for the SME to remain relatively small, which may hinder its development prospects due to the size of these niches compared to the general market, the specialised nature of the unique service or product, and the structure and resources required to offer it. In conclusion, a persuasive argument has been made for why small and large businesses should be classified as separate study objects (Yeboah, 2021). The primary arguments are based on the structural and behavioural distinctions revealed in the reviewed theories and empirical research on business performance and growth. This thesis focuses solely on SMEs to identify the prominent themes and constructions in the academic literature on SME development and performance (Yeboah, 2021). In the context of the current market and business, a strategy can be a collection of plans, policies, and objectives that define the firm's scope and method for navigating complicated competitive situations and adapting to dynamic market conditions (Safi et al., 2022). The market determines the firm's strategies and resources and focuses on technical and product development (Kristinae et al., 2020). The desired result of a strategy is in alignment with its associated environmental limitation and the attainment of sustained competitive performance (Shala et al., 2018). In accordance with the "contingency viewpoint," a company may develop the most effective strategy by aligning its organisational methods with the speed of its environmental settings

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(Kristinae et al., 2020). The organisational approaches are as follows: establishing a position in an industry and shielding it against the competitive forces by predicting and responding to changes in the forces (Porter, 1980), concentrating on its own capabilities and resources to leverage them against the competitors' resources, choosing several important processes, and having guidance through the processes (Shala et al., 2018). Nevertheless, organisations might pursue strategy development in a variety of ways (Kristinae et al., 2020). Analysis and execution of a strategy might be distinct tasks performed by various individuals and units in big organisations. Nonetheless, in small organisations, these activities are performed by a single individual. In dynamic global business and market contexts, the firm's strategy is no more a question of determining a fixed set of actions (Brown, 1990; Sim & Teoh, 2011). The strategies of the firm must be timely updated and kept in dynamic equilibrium as the external and internal circumstances change (Safi et al., 2022). Strategic breakthroughs can be identified and replicated by other businesses, which drives businesses to focus more on their competitive edge (Kristinae et al., 2020). Consequently, the ownership of strategic assets (for example, creative skills) is crucial, as losing control might result in subpar value generation and copying by rivals (Shala et al., 2018). It can be emphasised that "a corporation acquires a competitive advantage by doing its tasks more cheaply or more effectively than its rivals." Competitive advantage is described as a distinguishing factor that places a company in a favourable position relative to its rivals and derives from various actions within and outside the company (Shala et al., 2018). A corporation has a sustained competitive advantage when adopting a value-creating strategy that is not concurrently being applied by present or future competitors and when others are unable to replicate

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[its] advantages. Safi et al. (2022) highlighted that competitive advantage could direct the company to continue pursuing innovative processes and technologies to fulfil the needs of consumers and obtain a competitive advantage over rivals. The authors examined the strategy-related (for example, learning and market orientations) and competition-related (for example, industry concentration and entry barriers) attributes of small and medium-sized businesses. They discovered that strategy-driven firms improve innovative performance while competition-driven firms have substantial influences on innovative activities (Kristinae et al., 2020). Research studies on multiple determinants of innovation (for example, the impact of firm-specific characteristics and the effect of external environments) emphasised the importance of structural factors, which are particularly applicable to large organisations (Shala et al., 2018), while an increasing number of studies have examined the impact of strategic variables such as flexibility, learning, and customer proximity (Safi et al., 2022). By achieving a better fit with its environment, the firm's strategic direction becomes the continual integration and reconfiguration of its skills and competencies. The phenomenon of globalisation has intensified competitiveness, and the innovation lifecycle timeline is now shorter compared to the past owing to the need for market competitiveness, making it more challenging for small innovative businesses (Safi et al., 2022). The capacity to maintain a balance among a collection of internal and external competing components in a manner that promotes improved company performance can be a crucial element of effective strategic management (Shala et al., 2018). From a strategic choice viewpoint, the strategic orientation of top management contributes to the firm's dynamic interactions with its surroundings instead of merely responding to them. In order to achieve strategic alignment, a company must align its

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resources (for example, financial, physical, organisational, and human), capabilities (for instance, process and skill), and competencies with the shifting opportunities and dangers in its environment (Shala et al., 2018). The "strategic fit" of a business necessitates internal coherence with its overall operations (Porter, 1980) and dynamically governs its relationship with its surroundings (Safi et al., 2022). The coherence emphasises the "dynamic fit" or interaction between the organisation and its environment and the contrasts between the logical and impromptu parts of strategic management. A company has the option of adopting a variety of strategic stances and orientations at the enterprise level (Safi et al., 2022). First, in the competitive position, Porter (1980, 1985) views an enterprise embracing a competitive position as a cost leadership leading to the aggressive pursuit of a lowest cost position producer, which seems to be low industry-wide, a differentiation leading to the development of distinctive capability perceived to be unique by customers and industry-wide, and a focus leading to a concentration of strength by a specific niche or segment by targeting specific customers. The remaining strategies include the blue ocean strategy, which leads to the creation of new market space, the elimination of competition, and the creation and capture of new demand, as opposed to the red ocean strategy, which leads a company to contend in an existing or oversaturated market by investing more in research and product development, and marketing (Safi et al., 2022). By implying different management strategic orientations, the business-level typology tends to view an organisation as a complete and integrated system in a dynamic process and interaction with its environment (such as an adaptive cycle). At the same time, organisational effectiveness is heavily dependent on top management's conceptions of environmental factors and their choices to acclimate to these conditions

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(Shala et al., 2018). There are four distinct archetypal strategic orientations, prospector, defender, analyst, and reactor, which have been practically and theoretically examined (Shala et al., 2018). First, the prospector acts in a dynamic environment, consistently hunts for new market possibilities, possesses adaptable technologies and structures, creates novel processes, goods, and services, and instigates changes and uncertainty to enrage competitors. Second, the defender functions in a stable environment, concentrate on constrained product-market domains, seldom modifies structures, processes, and technologies, and prioritises enhancing efficiency and defending market shares. Thirdly, the analyser performs either pro-actively or reactively, integrating decentralisation and centralisation features based on environmental conditions and efficiency-and-innovation ratios. Lastly, the reactor provides stable processes, products, and services but is unable to effectively respond to competitive and changes in the environment because of its inherent inconsistency and instability, which is inherently unstable, has a non-viable strategy, and rarely results in satisfactory performance. The defender and prospector defender live at opposing extremes of the strategic spectrum, with the analyst in the middle in the majority of contexts. Nevertheless, past research investigations have shown inconsistent findings (Safi et al., 2022).

Influence of Business Coaching on the Growth and Performance of SMEs This section aims to review literature related to the effect of business coaching on the growth and performance of SMEs. Business coaching boosts company performance. Furthermore, training improves management capacity and speeds up

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SME growth (Possumah & Appiah, 2018). According to Ipinnaiye et al. (2016), a crucial determinant of SME growth is training, and employee motivation greatly adds to productivity, which boosts SME growth. As a result, it may be claimed that business coaching increases employee motivation, which promotes SME growth. As stated in Chen et al. (2021), business model innovation significantly and positively impact the growth of SMEs. Roša and Lace (2021) noted that business coaching facilitates selfdirected learning among SME employees, triggering knowledge creation and business transformation. The knowledge created during business coaching sessions provides innovative capabilities for SMEs, which drive growth and performance. Furthermore, training has a good impact on employee job performance, resulting in increased business growth (Djastuti et al., 2020). As reported by Djastuti et al. (2020), training leads to job satisfaction and has a positive and direct influence on employee performance. Subsequently, enhanced employee performance leads to increased business growth. They also discovered that organisations invest in training to strengthen their competitive edge. Training also promotes creativity since it increases employee knowledge, which can then be utilised to create new products in organisations. Product innovation has an impact on business performance (Ipinnaiye et al., 2016). The distinct effects of training have a good impact on SME growth. Undeniably, training leads to increased employee engagement, productivity, work satisfaction, creativity, business model innovation, and competitive advantage. Thus, the literature has assumed a direct relationship between business coaching and highimpact SME growth.

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Empirical Review This section examines the independent variables and their relationships with the dependent variables of the current study. Subsequently, it examines past empirical literature that is pertinent to the study and then notes the gaps that need to be filled.

2.13.1 Effect of Motivation on Growth and Performance of SMEs Employee motivation arises when workers are ready to put in additional effort to achieve the organisational objectives. Employee motivation implies the efforts undertaken by employees to attain organisational goals (De Sousa Sabbagha et al., 2018). According to So et al. (2018), employee motivation impacts organisational performance since they strive hard to achieve the desired goals. The authors additionally stated that employee motivation impacts employee performance, which improves organisational growth. According to Matloob et al. (2021), employee motivation happens when an organisation enables its people to perform effectively and increases the organisation's performance. Employee motivation is critical in organisations, and businesses must guarantee that their staff are motivated in order to be competitive (Pârjoleanu, 2020). Besides, Pârjoleanu (2020) stated that training employees help them learn new skills, which improves organisational commitment and employee retention. Staff motivation also improves employee efficacy, which leads to increased organisational sustainability and performance. Firms that prioritise employee motivation experience greater performance and company success. Yusoff et al. (2018) undertook extensive research to investigate the impact of sustainable growth on Malaysian SMEs. As stated by the authors, employee retention and satisfaction are critical in SMEs. They suggested that SMEs improve human capital by assuring staff retention since it fosters employee motivation, which leads to

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growth. As reported in the study, skill development might help with employee retention and motivation. As a result, SME personnel may enrol in training courses to improve their abilities, therefore contributing to the high-impact growth of SMEs. Authors such as Yusoff et al. (2018) stressed that SMEs should prioritise employee motivation to encourage long-term commitment. According to Okolocha (2020), employee motivation leads to work satisfaction and organisational commitment, hence resulting in SME growth. The author highlighted that Malaysian SMEs lack trained staff as a result of poor employee training. The limitations demonstrate the critical importance of worker training in achieving improved corporate performance and longterm success. Ismail et al. (2018) investigated Malaysian SMEs' alignment. Their research discovered that SME training for workers increases creativity, which increases motivation since they feel highly capable. The motivation allows workers to put their training abilities to use in the workplace. The effective use of skills promotes company performance, which leads to organisational growth. According to Ghani et al. (2019), motivated employees perform effectively, can tackle complicated tasks, and achieve self-efficacy. Essentially, organisations with engaged workers tend to achieve higher levels of performance and also a commercial success. Łukasik (2017) investigated the impact of training on employee motivation in SMEs and discovered that human resources are crucial in organisations for achieving key skills. The author emphasised that the essence of employee training is to gain a competitive advantage, and employee motivation inspires employees to perform better and be more efficient. Matloob et al. (2021) investigated the impact of employee motivation in SMEs. They proposed that employee motivation drives people to enhance their performance in order to meet organisational goals and objectives.

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Attained organisational goals result in business growth. Human resource management methods, such as constant learning, drive employee motivation. This knowledge is obtained through training, which encourages individuals to give their utmost, hence increasing job participation. Job participation boosts employee enthusiasm and productivity, which in turn boosts business growth (Mikkelsen & Olsen, 2019). Additionally, job involvement increases job satisfaction, which contributes to organisational growth. The relation shows that people are appreciated in an organisation and that the core abilities contribute to organisational effectiveness. As a result, SMEs which invest in business coaching are more likely to gain from employee motivation, resulting in the high-impact growth of SMEs. Vlacsekova and Mura (2017) undertook research to identify how motivating tools improve employee satisfaction in SMEs. They discovered that employee motivation has a favourable and considerable influence on employee satisfaction, promoting business growth. Park et al. (2019) emphasised that employee satisfaction leads to staff retention, which, in turn, leads to increased productivity. Increased productivity benefits an organisation tremendously. The authors stated that staff motivation minimises employee turnover, which leads to employee commitment and organisational effectiveness. According to the research stated above, employee motivation

significantly

and

positively

influence

employee

performance.

Consequently, organisations must guarantee that they have a strong and good relationship with their employees in order to fulfil the achievement of organisational goals. Many scholars and authors have suggested theories on the topic of financial motivation and its function in improving employee performance in any firm. Despite the substantial research on the topic, several of these models are

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commonly employed and accepted by leaders in present organisations. The process of motivation can lead to occupational satisfaction. The unclear link between motivation and work satisfaction can be exemplified by the motivational theories (Łukasik, 2017). According to Freitas and Duarte (2017), two types of motivational theories exist, namely content theories and process theories. As reported by Freitas and Duarte (2017), content theories of motivation are particularly important for job satisfaction and assume a direct relationship between job satisfaction and improved performance, while process theories investigate the relationship between motivation, job satisfaction, and performance in greater detail. In the existence, relatedness, and growth theory, there are three fundamental human wants. Existence, relatedness, and development are prerequisites for an employee's enhanced performance (Łukasik, 2017). Maslow (1943) proposes that human wants can be categorised into five groups, and these groups can be placed in order of significance. These five groups include physiological, security, possession, self-esteem, and self-actualisation requirements. Maslow (1943) stated that a person's primary motivation is to meet their physiological demands. As long as employees are dissatisfied, they will only be motivated to meet their needs (Freitas & Duarte, 2017). When physiological requirements are met, they cease to be key motivators and the individual "moves up" the hierarchy to meet security needs (Freitas & Duarte, 2017). This process continues until all needs for self-actualisation are met. Maslow (1943) also asserted that the reasoning is simple and straightforward. For instance, employees who are too unwell or too hungry to work would be unable to make sound decisions. Process theories primarily concentrate on why individuals choose specific behavioural choices to achieve their needs and how they measure their satisfaction after attaining

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their goals. In contrast, content theories emphasise the factors inside people that govern their behaviour (Łukasik, 2017). Psychologists have discovered through observations that need to motivate human behaviour. When an individual has a need, a drive condition is induced. A drive is described as a lack of orientation. The motivation of the individual is goal-oriented. Therefore, a goal is defined as something believed to fulfil a need. After attaining a goal, a person's need may be satisfied, partially satisfied, or unsatisfied. For example, the demand for tough work may motivate an individual to pursue the objective of securing a challenging job. A person's behaviour in relevant future situations is influenced by the level of satisfaction derived from achieving a goal (Łukasik, 2017). People prefer to repeat actions they connect with happiness while avoiding the actions they link with dissatisfaction. Incentives might not be solely monetary. Due to the fact that each individual's views are unique, what constitutes a reward and its relative worth, or valence, will vary greatly between individuals. Imagine a suitcase stuffed with one hundred dollar cash. The majority of Americans would view this suitcase as an incredibly valuable prize. Nevertheless, an exceedingly affluent individual could value a few weeks of vacation more compared to a relatively small quantity of money (Łukasik, 2017). An example of positive reinforcement or motivation is a prize. Money and motivation are two additional types of reinforcement that managers may employ to get the desired results. Money is the most obvious method a company can reward its employees (Burlea-Schiopoiu & Mihai, 2019). The dispute around the extent to which money may motivate humans dates back to the beginning of the human relations movement. Human relations advocates argued that the social needs of an individual

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were of the utmost significance, in contrast to the scientific management notion that monetary incentives would always boost motivation. Behavioural scientists who invested a substantial amount of effort in researching the expectation theory support the scientific management viewpoint. It has been discovered that, in some situations, compensation leads to increased performance (Burlea-Schiopoiu & Mihai, 2019). First, the individual must place a high value on monetary compensation (Mulolli et al., 2020). The second need is that the individual must anticipate that performance and pay are linked. Thus, if they work more, they will receive pay increases. Clearly, it is preferable for employees to see a direct relationship between compensation and performance. Money is a proven motivation in the majority of circumstances, but it is not the only motivator (Łukasik, 2017). Handayani (2018) studied the impact of training on employee motivation. The author discovered that training improves workability by providing employees with assistance in achieving organisational success. Handayani (2018, p. 25) continued to explain that training helps individuals develop necessary abilities, allowing them to execute their tasks better and contributing to their organisational success. Miah and Hafit (2020) undertook an in-depth study on Malaysian SMEs to assess how employee training improves their creativity. The authors discovered that non-creative workers reported increased inventiveness following training. They came to the conclusion that training would have a substantial and positive influence on Malaysian SMEs. According to Ikem (2019), training increases employee enthusiasm and boosts SME performance. The author suggested that staff training is required owing to the constantly changing corporate environment and rising market competitiveness. Due to the growing diversity in the workforce, employee training is essential. Training also

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aids in increasing customer value and improving SME performance (Burlea-Schiopoiu & Mihai, 2019). Mulolli et al. (2020, p. 522) stressed that employee motivation is crucial for organisational growth since employees are the most precious company assets as they lead to corporate success. The authors highlighted that employee motivation is influenced by factors including high-quality skills and performance. High-quality skills are obtained through business coaching and training, resulting in the high-impact growth of SMEs. As stated by Haruna and Marthandan (2017), employee motivation results in high job engagement and boosts SME employee productivity. The authors additionally concurred with the findings of previous research about employee motivation, reducing staff turnover, and improving development potential for SMEs. Employee motivation also improves the firm's potential to achieve a competitive edge. Some studies (Haruna & Marthandan, 2017; Miah & Hafit, 2020) have improved the competencies of SME employees. Nevertheless, research on the effectiveness of business coaching on the high-impact development in SMEs is insufficient. The present study aims to fill another research gap by investigating how business coaching influences the high-impact growth of SMEs in Malaysia. The current researcher deduced from the studies mentioned earlier that when employees receive business coaching, they develop new skills and increase their capabilities, resulting in enhanced business performance, which, in turn, results in sustainable growth. Thus, the researcher concluded that available literature supports the importance of employee motivation in the high-impact growth of SMEs. The data also support Biggs' 3P model. As a result, the researcher developed and aimed to test the following hypothesis:

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H1: Employee motivation has a significant positive effect on the high-impact growth of SMEs.

2.13.2 Effect of Coaching Improved Productivity on Growth and Performance of SMEs Productivity is a critical factor in the growth of a company (Ismail, 2018, p. 246). According to Okolocha (2020, p. 53), productivity in Malaysian SMEs is a crucial element contributing to the growth of SMEs. Ensuring a skilled workforce through educating and training employees about the SME's aims and objectives increases productivity. The author also mentioned that staff retention has a role in productivity. As a result, he encouraged managers to devote special attention to staff training, emphasising that the essential treatments for minimising employee turnover are implemented. These policies ensure SMEs' productivity and high-impact growth. Park et al. (2019, p. 1) suggested that workers have a major impact on the firm's production. The authors contended that employee training assists the organisation in attracting high-performing employees. Such employees contribute to the ongoing growth of the company, resulting in a competitive advantage. Amah and Oyetuunde (2020) observed that SMEs that improve their employees' well-being boost their productivity, hence improving the high-impact growth of the company. The authors also further believed that SMEs increase employee productivity by providing an environment in which the employees may develop their skills. Coaching and training can help employees acquire these skills. Thus, SME employees must participate in development programmes in order to raise their productivity, affecting the growth of SMEs. Unfortunately, there has been little

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study on the effects of business coaching on Malaysian SMEs' high-impact growth. Undoubtedly, more study is required to fill this specific literature gap. Ballestar et al. (2020) stressed that knowledge has a substantial influence on the productivity of SMEs. The authors also recommended that SMEs improve their growth and productivity by implementing training in the workplace. Training facilitates the flow of knowledge within the organisation, resulting in improved business growth and firm performance. Palanimally et al. (2020) carried out research to identify the factors that influence SMEs' growth in Malaysia. They discovered that Malaysian SMEs' strong productivity compensated for high failure rates and affected their market competitiveness. Productivity has had an impact on the growth performance of SMEs. The study showed that productivity has a major impact on the growth of these organisations. According to Mahmod et al. (2018), SMEs fail due to a lack of productivity. They emphasised that SMEs must be productive in order to achieve growth. Iqbal et al. (2019, p. 235) highlighted that employee productivity is critical to the success of SMEs and is one of the primary factors influencing training programmes. Their research revealed that training programmes assist employees in creating high-quality output, increasing firm revenues. The findings of several studies highlighted that employee productivity impacts organisational commitment, which leads to higher organisational performance (Mamun & Hasan, 2017; Berberoglu, 2018; Diamantidis & Chatzoglou, 2019). It may be suggested that productivity is a necessity for SMEs' high-impact growth. Diamantidis and Chatzoglou (2019) reported that training encourages employees to be productive and proactive. They continued by stating that productivity improves employee performance since employees will fulfil the firm's performance standards, resulting in corporate development. Okolocha (2020, p. 53) concurred that

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productivity is important in a business because it influences financial performance as increased productivity leads to increased financial performance. Nure et al. (2020, p. 1) demonstrated that increasing staff productivity helps SMEs enhance their performance. The authors also stated that employees' job quality affects their productivity and also their work dedication. The increase in productivity and commitment to their job corresponds to enhanced economic performance for SMEs, resulting in high-impact growth for SMEs. According to Pasnicu (2017), training programmes are critical for SMEs since they boost employee productivity and contribute to greater creativity and innovation in the firm. Improved creativity and innovation lead to greater economic performance for SMEs. The author also stated that training is beneficial to businesses since it adds to employees' career growth, providing a quality workforce, which eventually results in productivity. Furthermore, greater productivity leads to significant SME growth. As a result, SMEs should invest in training to increase efficiency and achieve high-impact growth. Ismail (2018) studied labour productivity in Malaysian SMEs. The author also discovered that investing in intellectual capital is critical in business since it leads to higher labour quality and improves productivity, which, in turn, leads to SME growth. According to the study, human capital activities such as coaching and training have a beneficial impact on the production and profit of firms. In addition, the author suggested that staff who have received training can sustain and adapt to new technologies. The ability to embrace and utilise new technologies allows them to be more creative and imaginative, enhancing the firm's production and development. Ismail (2018) observed that training aids in the creation of information, vision, and knowledge. Information is crucial when conducting business operations as it enables organisational goals and objectives to be realised. Vision promotes knowledge

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development and innovation, both of which contribute to organisational growth (Ismail, 2018, p. 246). According to Jones and Corral de Zubielqui (2017), increased efficiency leads to increased sales growth and the sustainability of SMEs. Furthermore, the authors believed that innovation has a positive influence on company productivity, hence improving organisational growth. Teh and Kee (2019) performed a study on Malaysian SMEs' readiness to face the fourth industrial revolution. They discovered that increasing SMEs' productivity increases their efficacy and income. Increased income has a positive and significant influence on business growth. The authors came to the conclusion that SMEs' productivity should be monitored on a regular basis to ensure sustainable company growth. Rusly et al. (2017) reported that employee motivation helps to boost company productivity, which improves overall business performance and contributes to corporate growth. These arguments suggest that productivity is essential for achieving corporate growth. AlManei et al. (2017) asserted that productivity is critical in boosting corporate growth. They believed that SMEs might increase productivity by teaching their employees certain lean principles that apply to SMEs. The knowledge of lean principles would encourage employees to work hard and strive to accomplish these values, allowing the achievement of organisational objectives and goals, which leads to business growth. According to Suminar et al. (2020), entrepreneurship training improves SME productivity. The authors also stated that human resources quality in SMEs is a critical factor in their growth. They contended that SMEs gain productivity by going through transformational processes that provide value to the business. Entrepreneurship training programmes are one of these transformative processes that

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are expected to boost the productivity of SME management and staff. The SME's revenue increases and its high-impact business growth accelerates. Majid et al. (2021, p. 1) reported that productivity boosts SMEs' efficiency levels and business growth. They stated that SMEs might attain high levels of productivity by routinely undertaking management and entrepreneurial training programmes. These programmes aid in the improvement of organisational performance and the expansion of businesses. According to Haseeb et al. (2019, p. 4), productivity improves the effectiveness, efficiency, and development of SMEs. Surya et al. (2021) stressed that human resource competencies, such as staff training, are important predictors of SMEs' growth and productivity. They discovered that productivity increases the economic capacity of businesses and has a beneficial impact on the growth of SMEs. In addition, the authors observed that training boosts the production of SMEs. As stated in the studies cited above, productivity is a crucial resource in SMEs since it significantly improves organisational performance, which contributes to business growth. Igwe et al. (2018) reported that training the labour force is a critical strategy to enhance the productivity of SMEs. They discovered that a good company environment promotes productivity. Hence, if employees work in such an atmosphere, they may attain high productivity, which boosts corporate growth. Moreover, increased productivity leads to higher project quality, which contributes to the expansion of SMEs (Motta, 2020, p. 1). According to research, productivity has a significant and positive impact on the high-impact growth of SMEs. The current study was able to establish that business coaching may be used in SMEs to increase productivity and, subsequently, high-impact SME growth. Thus, the researcher formulated and attempted to test the following hypothesis:

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H2: Improved productivity has a significant positive effect on the high-impact growth of SMEs.

2.13.3 Effect of Job Satisfaction on Growth and Performance of SMEs Employees' emotions in the workplace are referred to as job satisfaction (Mira et al., 2019, p. 773). Abbasi et al. (2020) investigated the role of job satisfaction as a mediating effect in Malaysian SMEs. They discovered that job satisfaction improves employee work performance, which causes them to exhibit enthusiasm for their work, thus helping them to achieve the goals that have been set in their organisation. Satisfied employees will ensure they perform optimally to achieve the organisational objectives (Inayat & Khan, 2021). Furthermore, satisfied employees are often productive, avoid absenteeism, and be more committed and punctual. In contrast to dissatisfied employees, satisfied employees are committed to the environment, leading to organisational commitment, job satisfaction, and the achievement of organisational goals. Her et al. (2020) outlined several factors that lead to employee satisfaction, namely good relationships between employees and their coworkers, attractive pay scales, employee involvement in organisational policymaking, and job security. The accomplishment of organisational goals promotes SME growth. Okololocha (2020, p. 53) discovered that work satisfaction boosts organisational commitment and improves performance, consequently impacting SME growth. According to Ibrahim et al. (2018), training and development are important variables in SMEs that contribute to work satisfaction. They contended that individuals might improve their communication abilities during training and then apply the skills in their job. The improvement in communication skills makes employees feel more at

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ease with their coworkers, which leads to greater job performance and, as a result, SME growth. Lei et al. (2018) reported that job satisfaction promotes employee retention and has a beneficial influence on business success. Coaching and mentoring programmes boost employee motivation and work satisfaction (Lei et al., 2018, p. 3). As per the authors, such programmes reduce personnel turnover and boost organisational performance. Organisational effectiveness contributes to better organisational performance, which leads to better company performance and growth. As stated in the study, coaching and mentoring programmes are critical for assuring corporate success since they help employees learn new job skills, hence increasing their effectiveness. The findings of the studies mentioned above revealed that job satisfaction has a positive influence on the growth of SMEs. Nevertheless, there is little research on the effectiveness of business coaching and its influence on the high-impact growth of SMEs in Malaysia. The gap shows the requirement for more research to identify the impact of business coaching on the high-impact growth of SMEs in Malaysia. Ling et al. (2019) investigated how job satisfaction impacts organisational commitment in Malaysian SMEs. They discovered that organisational commitment is significantly and positively affected by job satisfaction. Additionally, organisational commitment contributes to organisational success and increases the business performance of SMEs. When an employee is more loyal and productive in the workplace, the employee's behaviour is referred to as organisational commitment. Employees' organisational commitment speeds the attainment of organisational goals and objectives, resulting in high-impact SME growth. Visvanathan et al. (2018, p. 248) concurred that job satisfaction is the most important factor of company productivity.

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They also determined that coaching is critical in achieving organisational goals, aiding in the improvement of the organisation and contributing to business growth. Besides that, the authors determined that one of the conditions that contribute to job satisfaction is the provision of assistance, such as coaching and training. According to Krishnan (2020), organisations should recognise the aspects that impact job satisfaction in order to support the organisation's objectives. The author further emphasised that happy workers are successful employees who contribute to the success of the organisation. As a result, SMEs are more likely to experience greater business growth and performance if they prioritise job satisfaction. According to Dyczkowska and Dyczkowski (2018), job satisfaction increases efficient communication inside the organisation, which fosters collaboration. Teamwork promotes positive work relationships and partnerships, which aid in organisational growth (Vu, 2020). Ibrahim et al. (2018) agreed that the work environment improves job satisfaction in SMEs. The authors also concurred that work satisfaction is also employed as a key performance indicator for SME growth. According to Lai et al. (2017), SMEs with high job satisfaction outperform SMEs with poor job satisfaction in terms of financial performance. The authors also stated that SMEs should implement strong human resources policies and procedures to achieve high levels of employee dedication that contribute to high-impact business growth. As stated in Lai et al. (2017), employees who are satisfied with their jobs are more likely to use their talents and abilities to accomplish organisational growth, which leads to company success. As a result, SMEs will enjoy exponential business growth if their employees are satisfied with their jobs. Employee

experiences

significantly

and

positively

influence

work

satisfaction (Nanjundeswaraswamy et al., 2020, p. 13). Employees that have positive

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experiences in the organisation will demonstrate organisational commitment, resulting in company success. Smolarek and Sukowski (2020, p. 182) found that job satisfaction increased organisational efficiency. The authors also stated that improved organisational efficiency should be measurable by all businesses in order to improve the growth of a business. Work engagement is influenced positively by job satisfaction (Ali et al., 2018). As reported in the study, management coaching improves managerial competency and fosters positive job engagement. Abbasi et al. (2020) denoted that job satisfaction minimises workplace deviance and motivates employees to strive towards the firm's visions, resulting in the growth of a business. Positive work engagement results in employees having a positive attitude at work, which promotes organisational performance and contributes to business growth. Employee efficiency promotes total organisational efficiency due to employees' job satisfaction. The finding suggests that employee satisfaction is an important resource for organisational efficiency, which leads to business growth. According to the studies stated above, job satisfaction contributes to employee motivation, which leads to organisational commitment. Organisational commitment leads to organisational success, which leads to high-impact expansion of SMEs, which improves a firm's performance to a higher level. A large number of studies have found that job satisfaction has a major beneficial impact on the performance and growth of SMEs (Dyczkowska & Dyczkowski, 2018; Mira et al., 2019; Abbasi et al., 2020). Unfortunately, a scarcity of research exists on the impact of job satisfaction on Malaysian SMEs. In order to fill this gap in the literature, further research is required. As a result, the researcher established and attempted to test the following hypothesis: H3: Job satisfaction has a significant positive effect on the high-impact growth of SMEs.

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2.13.4 Effect of Innovation on Growth and Performance of SMEs The introduction of new goods and services into the market in order to obtain a competitive edge is referred to as innovation. Alam et al. (2016) investigated the influence of innovation on the growth of Malaysian SMEs. As reported by the authors, there are numerous types of innovation in SMEs, including product innovation and process innovation. Product innovation comprises improving a current product to achieve greater market performance. In contrast, process innovation entails developing new and improved product delivery systems. Wahab et al. (2020, p. 263) agreed that innovation positively affects SMEs. It is an important accelerator for SME growth since it enables SMEs to reach their full potential. The authors continued to highlight that innovation helps SMEs improve their performance and gain a competitive advantage in the market. Innovation also increases the value of assets while also enhancing organisational performance. Finally, organisational success leads to the high-impact growth of SMEs. Innovation significantly improves business growth and organisational competition (Ibrahim et al., 2018, p. 161). According to the authors, innovations improve a company's potential to expand its organisational capacities while retaining performance growth. Innovation fosters the growth and sustainability of SMEs. Expósito and Sanchis-Llopis (2019) discovered that innovation also enhances company performance and raises its survival rate. They emphasised that innovation is critical in SMEs since it affects the firm's financial and operational aspects, enhancing overall performance. An enterprise's business and financial performance are both improved through innovation. In addition, it also improves the efficacy and effectiveness

of operating procedures

in

SMEs.

The studies

mentioned

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above showed that SMEs should employ new techniques in order to attain long-term sustainability. Singh and Hanafi (2020) evaluated the impact of innovation capacity on Malaysian SMEs' performance. They observed that organisations' performance, business growth, and sustainability are all affected by innovation. The authors also stated that staff training boosts innovation, which is essential for driving business growth. In order to achieve greater business growth, SMEs should manage innovation. Mustafa and Yaakub (2018) agreed that a significantly positive relationship exists between innovation and SME success. They also stated that SMEs' adoption of innovation leads to dynamic capabilities, resulting in improved market capabilities. The authors also discovered that SMEs should embrace innovation since it improves corporate performance and business value. As a result, organisations should embrace innovation in order to obtain a competitive edge. Rahim et al. (2019) reported that Malaysian SMEs fail due to a lack of adoption of innovative techniques. They emphasised the importance of innovation in ensuring sustainability and creating competitive advantages. The authors stated that SMEs must critically understand their business environment and develop appropriate innovations in order to capitalise on market risks. Additionally, Islam and Wahab (2021) discovered that SMEs should apply strategic innovation methods that are focused on their core company strategy in order to achieve long-term business success. Furthermore, the authors observed that strategic innovation techniques assist organisations in achieving long-term success, hence improving SMEs' high-impact business growth. According to Rahim et al. (2015), innovation assists SMEs in maximising their growth. In order to obtain a competitive edge and boost organisational success, SMEs should explore product and process innovation and other

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types of innovation. Organisations must embrace innovation to sustain the efficacy of their organisational processes. As a result, innovation could boost SMEs' high-impact growth. Chong et al. (2019) investigated the impact of Malaysian SMEs' innovation on internationalisation and the balanced scorecard. Their findings suggested that innovation boosts organisations' chances of internationalising, hence enhancing their competitive advantage. The authors further stated that success in international marketplaces requires innovation. The authors examined knowledge, trust, commitment, and opportunity development in relation to the balanced scorecard and discovered that the factors had a positive influence on innovation. Additionally, Ha et al. (2018, p. 242) asserted that organisations should strive for innovative performance, which alludes to the outcomes of a firm's creative behaviours. Thus, firms must develop and apply innovative behaviours in order to attain organisational growth. Nevertheless, according to Bodlaj et al. (2020), SME development is not only dependent on technological innovation. The authors recommended that SMEs concentrate on organisational innovations in order to attain long-term growth and performance. They came to the conclusion that organisations should concentrate on technological and non-technological innovations in order to sustain the performance of the business. Musneh et al. (2021) studied the strategic significance of innovation in Malaysian SMEs. They discovered that strategic innovation is critical to the success of SMEs. Rather than concentrating solely on research and development, they argued that SMEs should support innovation in order to accomplish sustainable development objectives and also continue to motivate and increase employees' potential. Besides, the authors stated that one of the most crucial core competencies

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for successful businesses is innovation. Beynon et al. (2019, p. 3) proposed that governments should implement policies to foster innovative activities in SMEs since they are critical to SME growth. The authors noted that SMEs should define appropriate innovation intentions, such as innovative practices that the business should perform in order to fulfil organisational goals and objectives. The authors' findings suggest that innovation serves a strategic role in improving organisational performance. According to Saridakis et al. (2019), among the three categories of SME innovation are goods, product, and service innovations. Goods innovation refers to enhancing goods to suit customer expectations, product innovation pertains to new product introduction or the enhancement of current products, and service innovation is the introduction and modification of new services. The authors reported that the innovations boost the chances of SMEs internationalising and acquiring a competitive edge. The competitive advantage would boost business growth and organisational performance. Likewise, Mawson and Brown (2017) investigated the role of open innovation in the growth of SMEs. They revealed that open innovation is a critical driver in SME growth. They further argued that SMEs should not be bound by resources but could instead embrace open innovation by utilising external resources and competencies, which would result in optimal SME growth and performance. Their study also showed that most SMEs are utilising open innovation, gaining competitiveness, and enhancing business growth. In SMEs, innovation drives productivity and sales (Gherghina et al., 2020, p. 4). Moreover, Gherghina et al. (2020) proposed that SMEs must innovate by undertaking a study based on consumer needs and producing innovative products that satisfy customer wants.

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Roša and Lace (2021) suggested that business coaching encourages a company to build its innovation capability, which promotes growth and enhanced performance. The authors further argued that business coaching transforms SME leaders as it enables them to discover their potential, thus enhancing their realisation of new opportunities in the market. This realisation creates the need to develop innovative competencies, which result in innovation. Furthermore, the authors asserted that business coaching leads to purposive knowledge inflows and outflows that result in the innovation of new technologies and other forms of open innovation. Knowledge inflow is a core contributor to innovation in organisations (Kraus et al., 2020). Business coaches enable SME leaders to assimilate knowledge, and these leaders use the knowledge to develop innovative capabilities. The development of innovative capabilities promotes enhanced growth and performance of SMEs. Knowledge accelerates SMEs' innovation. Wang et al. (2021) proposed that effective business coaching should be oriented towards behavioural coaching as it stimulates SME employees' internal self-regulation. The stimulation promotes work satisfaction, leading to the development of innovative capabilities among employees. The study also indicated that business coaching should be integrative by combining various frameworks aimed at improving outcomes. Feyertag and Roschk (2021) asserted that organisational innovation drives longevity and growth. Innovation allows SMEs to improve their business processes and culture. Therefore, SMEs that promote innovation are able to achieve market excellence, thus improving their performance. Fontes and Russo (2021) agreed that innovation would change the way SMEs conduct business in the upcoming years. Thus, when SMEs change the way they do business through innovation, they promote business growth and performance. Jarosz (2021) noted that innovation in firms is

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indispensable as it allows firms to raise their expectations of employee performance. Higher expectations of employee performance motivate employees to work harder to achieve the company goals and objectives. Motivating employees to achieve organisational goals improves the firm's performance and promotes business growth. According to Adam and Alarifi (2021), innovation is also critical in organisations as it allows employees to achieve their job-related goals. The authors stressed that innovation is critical for any SME that wants to survive in the market. Innovation promotes SME performance as it results in an improvement in products and processes, making them more competitive and profitable than the current ones. Innovation in SMEs entails innovating new business strategies that help the firm to grow, adapt, and succeed in a volatile business environment (Gomes de Carvalho et al., 2021). Additionally, Gomes de Carvalho et al. (2021) noted that innovation is essential in firms as it allows them to be creative and encourages collaboration, thus promoting enhanced performance. Innovation promotes continuous development in organisations, reducing their losses and improving their business performance. Innovation also promotes enhanced productivity in SMEs. Authors such as Saunila (2020) confirmed that innovation creates productivity. An increase in productivity increases the goods and services produced by SMEs, resulting in increased growth and performance. Issau et al. (2021) argued that innovation leads to an improvement in sales and the enhancement of customer relationships. The enhancement of customer relationships is vital because customers require products and services to be constantly improved. This constant improvement leads to customer loyalty, which increases the sales of a business. An increase in sales translates into growth and enhanced performance for SMEs (Kiyabo & Isaga, 2020). Therefore, it can be argued that business coaching provides SME leaders with ideas on how to

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enhance their innovative capabilities and the enhancement results in business growth and performance. Albats et al. (2021) asserted that a major advantage of innovation in SMEs is cost reduction. Innovation allows firms to improve their business efficacy by finding simpler methods of conducting their business operations, which results in reduced costs. Cost reduction led to improved profitability and increased business growth due to increased profit margins. Pierre and Fernandez (2018) reiterated that innovation in SMEs helps to reduce waste and costs. The authors stated that business innovation allows operational efficiency to be streamlined, which eliminates production inefficiencies, further reducing waste and costs. Interestingly, the authors also noted that innovation improves employee relations. Employees are stimulated by innovation (Drosos et al., 2021), which cultivates pride and enthusiasm among them, motivating them to work towards achieving organisational goals and objectives. Therefore, innovation in organisations reduces staff attrition because employees are motivated to work with innovative and exciting products and services. The reduction of staff attrition boosts productivity, improving business growth and enhancing the firm's financial performance. According to Abdilahi et al. (2017), innovation in SMEs results in the implementation of new practices, markets, and products, which allow SMEs to improve their sustainability, growth, and performance. The authors also noted that innovation results in an increase in sales volume, which leads to improved business growth. As stated in the findings of the studies mentioned above, innovation has a significant impact on the high-impact growth of SMEs. Increased innovation will lead to increased growth and productivity for SMEs. As a result, investment in technological, non-technological, and open innovation is crucial for achieving the

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necessary level of growth. The current study supports the relevance of innovation in the growth of SMEs. Thus, the researcher developed and sought to test the following hypothesis: H4: Innovation has a significant positive effect on the high-impact growth of SMEs.

2.13.5 Impact of Improved Business Model Innovation on Growth and Performance of SMEs Chen et al. (2021) stated that the structure and tactics used by an organisation to produce value from customers are described as business models. According to them, SMEs should develop their business models to fulfil the demands of their clients. The authors also indicated that SMEs that use business models outperform SMEs that do not use these models. Cosenz and Bivona (2021) reported that business model innovation is a vital component for SMEs to thrive and exceed customer expectations. The authors also suggested that SMEs investigate various business model development methods in order to create unique business models. According to them, business model innovations boost business sustainability and competitive advantage. In order to develop their businesses, SMEs adopt business innovation model paths (Heikkilä et al., 2018). Besides, Heikkilä et al. (2018) observed that firms produce business model innovation by changing the primary components of their business model in order to enhance company performance and achieve business development. Arif et al. (2019) found that the quality of business models determines SME growth. They further stated that business model innovation outperforms process innovation. Process innovation affects company processes, whereas business model innovation changes business models, the foundation of the firm. Business model

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innovations have an impact on long-term organisational performance, which leads to SME growth. The authors came to the conclusion that business model innovation is positively associated with high-impact growth in SMEs. Business models are SMEs' blueprints for expanding their business and making a profit (Peric et al., 2017). These blueprints explain the products or services that the SME should sell, the target market, and forecasted expenses. Therefore, when an SME is able to project these factors, it can determine whether it will make a profit or loss. Business model innovations refer to innovations or advancements to existing business models (Schiuma & Lerro, 2017). The advancement and innovation of business models in SMEs could result in increased profitability, thereby improving SME growth and performance. A business model further synthesises and integrates all of the strategic, economic, and managerial aspects of an organisation (Vaska et al., 2021). The integration of these aspects guarantees organisations' uniqueness and value enhancement, which promote value creation and sustainability. The SMEs that create value grow faster and have enhanced access to capital markets (Chilembo, 2021). Access to capital markets is a major ingredient of SME growth, as SMEs gain visibility to investors, which promotes their growth. Growth enables an SME to improve its products and services, which, in turn, improve its performance. Business models focus on the value proposition of an organisation (Ilyas & Osiyevskyy, in press). Besides, Ilyas and Osiyevskyy (in press) explained that businesses should adopt sustainable business models to realise corporate sustainability. They further explained that the adoption of sustainable business models has significant and positive implications for a firm's sustainable value proposition. The implementation of a sustainable value proposition increases firms' financial performance and promotes growth. Business coaching arguably improves the

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sustainable capabilities of firms by coaching them on the mechanisms and advantages of implementing sustainable business models. As a result of the adoption of sustainable business models, SMEs experience a positive impact on their value proposition and financial performance. Biloshapka and Osiyevskyy (2018) reiterated that business models promote value creation and value capture. Furthermore, business models enhance proper market positioning, allowing firms to offer value propositions to their customers. Value propositions allow companies to provide value to their customers through buying their products. Value propositions refer to a company's general marketing strategies (Bailetti et al., 2020). A company's value proposition informs consumers about the brand, the operations of the company, and the reasons why the consumers should purchase its products and services. Thus, business coaching allows SMEs to explain to consumers why their business will add more value than other SMEs. In sum, business coaching enables SMEs to develop innovative products that offer value propositions. In addition, business models explain the fundamental questions required to propel business growth, including the issues that the business intends to solve, how it intends to solve the issues, and the forecasted growth in a particular market (Climent & Haftor, 2021). Andreini et al. (2021) asserted that business model innovation refers to the development of new and unique concepts in the products and services of businesses that promote value creation. Hence, these concepts are supposed to catapult the organisation towards enhanced financial viability. Value creation in SMEs results in business growth (Matarazzo et al., 2021) and promotes a sustainable advantage. By developing products and services that are unique, SMEs create value-creating competitiveness in the market.

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Ghinoi and Toma (2021) asserted that business model innovation drives competitive advantage as it allows organisations to change their value proposition. Adjusting the value proposition changes the organisation's operating model, adding significant value for customers. This enhancement of the value proposition creates competitiveness in the market. Latifi et al. (2021) stated that most SMEs do not achieve their expected growth after adopting such innovations, although business model innovation results in improved firm performance. Business model innovation includes a complete change of critical components of SMEs' business models. Thus, SMEs should adopt and implement suitable business model innovations that are not risky, uncertain, or ambiguous. Moreover, business model innovation significantly impacts organisational capabilities, revenue growth, and efficiency growth (Loon & Quan, 2020). Mihalache and Volberda (2021) critically noted that business model innovation does not automatically translate to improved firm performance. Nevertheless, business model innovation is triggered by mediating and moderating factors, such as business coaching. Business coaching triggers SME managers to make strategic business model innovation decisions that lead to improved performance of the organisation. Several approaches to business model innovation exist, namely the reinventor, adapter, maverick, and adventurer approaches (Lang, 2020). The reinventor approach can be utilised when an SME wants to reinvent its customer value proposition. The SME realigns its proposition and develops a new superior offering. The adapter approach is deployed when an SME is seeking to experiment with a new product or service using the appropriate business model. Contrarily, the maverick approach is used when an SME seeks to revolutionise the industry by creating a competitive advantage. Lastly, the adventurer approach is employed when an SME wants to perform optimally in new

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markets. These business model approaches are aimed at driving business growth. Therefore, their deployment in SMEs will drive growth and performance. Business model innovation helps firms continuously seek out areas of improvement (Bhatti et al., 2021). This continuous search for improvement in firms' business model innovations allows them to deploy models that promote growth and development. Bhatti et al. (2021) added that business model innovation depends on the firm's knowledge absorptive capacity. García-Villaverde et al. (2018) outlined that absorptive knowledge capacity refers to the capability to learn through knowledge assimilation. As stated in Klopper and Coller-Peter (2018), business coaching results in the assimilation of new knowledge that increases the awareness of the coaches. Thus, business coaching in SMEs could increase the knowledge absorptive capacity among employees, hence promoting the growth and enhanced performance of the firm. Employees could use this knowledge to develop business model innovation, resulting in further SME growth and improved performance. Furthermore, business model innovation promotes organisational agility (AlTaweel & Al-Hawary, 2021), which refers to a firm's ability to develop and utilise its knowledge base (Walter, 2021). Organisational agility can be classified into various categories, namely agility capabilities, agility dimensions, agility enablers, and agility drivers. Business coaching is an agility driver as it allows organisations to develop and utilise their knowledge base. Business coaching improves a firm's knowledge base as employees are coached on how to retain and attract competitiveness and promote superior business performance. Organisational agility enables firms to respond to the dynamic and swiftly transforming business environment (Mrugalska & Ahmed, 2021). Business coaching arguably enables firms to strive to achieve their organisational goals and improve their performance. Business coaches have a

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significant positive role to play in coaching business model innovation. Andersen et al. (2018) stated that business coaches promote business model innovation competencies. The authors further stated that business model innovation coaching might occur in various styles, such as guidance, teaching, and consulting. Business model coaching entails facilitating coachees to collaborate in their workplace, innovate and develop the organisation's business model, and pitch business model solutions. Business model innovation promotes firm growth and competitiveness as it is new in the industry (Kraus et al., 2020). New products in the market promote competitiveness, allowing the firm to realise growth. Business models also describe the execution of innovations. The planning of the executions allows SMEs to lead new ways of value creation for customers, thus promoting SME growth. Anwar (2018) evaluated the influence of business model innovation on SME performance. According to the author, business model innovation is a key driver of SME growth. He also stated that business model innovation leads to improved organisational performance and, consequently, a competitive advantage. According to Anwar (2018), firms that have adopted business model innovation have higher firm performance than SMEs that use business models. Business model innovation boosts a company's profitability by allowing it to pursue new business possibilities (Anwar, 2018, p. 7). The author stressed that business model innovation improves company sustainability, allowing the company to achieve a competitive edge. The achievement of competitive advantage adds to SMEs' increased value generation, which boosts their growth. Moreover, SMEs could create business models that go beyond product and process innovation through business model innovation (Hock-Doepgen et al., 2020), providing these firms with a major competitive edge. As stated in the study, three essential components of business model innovation are value creation, value

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proposition, and value capture. Value creation is obtained by selling services rather than items. The value proposition is gained by being more service-oriented instead of product-oriented, and value capture are achieved by improving a firm's overall innovativeness and internal agility. Bouwman et al. (2019) reported that business model innovation increases SME performance. Additionally, Husin et al. (2021) concurred that business model innovation helps SMEs reach their objectives. Nevertheless, they also noted that in order to achieve a successful implementation, SMEs need have appropriate knowledge and comprehend business model innovation. As stated by the authors, business model innovation increases income for SMEs while also increasing growth and sustainable performance. Gatautis (2017) highlighted that business model innovation highlights the firm's value generation, what the company provides to its clients, and its financial development. The author discovered that SMEs must implement business model innovation in order to achieve company development since innovation gives value to customers. The author also revealed that organisations should embrace business model innovation not only to obtain a competitive edge but also to capitalise on the market's dynamic nature. Business model innovation must be undertaken on a regular basis, and SMEs should use systematic techniques to accomplish the implementation (Pucihar et al., 2019). According to Pucihar et al. (2019), business model innovation leads to increased sales and profit. As a result, SMEs that embrace business model innovation is more likely to experience high-impact growth. Miroshnychenko et al. (2020) reported that business model innovation has a key influence on value generation in SMEs. They also stated that organisations that use business model innovation have a larger possibility of strategic flexibility than SMEs that do not use business model innovation. Strategically adaptable firms can

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readily deal with external problems. They are highly sustainable, which boosts their growth. Besides, SMEs that use business model innovation possess dynamic capabilities that allow them to achieve a competitive edge. A competitive edge improves both sustainability and growth. Müller et al. (2018) stated that SMEs that implement business model innovation add additional tasks that go beyond market offers. They pointed out that the responsibilities help SMEs to enter new markets and attain organisational success, which leads to organisational growth. According to Bashir and Farooq (2019), business model innovation has a strong association with an organisation's expertise. They further asserted that such innovation includes capabilities and assets, cost and revenue architecture, and value proposition. Their research revealed that redesigning an SME's capabilities allows it to emphasise its core skills and provide value to consumers, resulting in sustainable growth. Due to the market's fast technological developments, SMEs should undertake business

model

innovation

(Rezazadeh,

2017).

Additionally, Rezazadeh

(2017) explained that business model innovations enable organisations to compete while also creating value for their shareholders and stakeholders. Asemokha et al. (2019) highlighted that business model innovation emerges when firms update their business operations in order to remain successful and grow. As reported by the authors, businesses that use business model innovation techniques can weather any business climate and assure sustained business growth. Their research indicates a relationship between innovative business models and high-impact growth in SMEs. Business model innovation is an opportunity recognition source (Guo et al., 2017). Recognising opportunities is critical in SMEs since it allows them to obtain a competitive edge and enhance their performance. As a result, SMEs' ability to recognise opportunities is a critical aspect of their success. Guo et al. (2017) reported

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that SMEs should design effective business models that utilise and recognise existing possibilities that result in SME performance. Sadiku-Dushi et al. (2019) agreed that SMEs should identify prospects for improved performance and long-term growth. Environmental and market changes should drive continuous business model innovation (Silva et al., 2020, p. 596). As stated in Silva et al. (2020), a successful business model innovation must include revenue components to secure the firm's financial success. The authors also mentioned that it should include agile approaches that pursue customer development strategies. Clauss et al. (2019, p. 2) acknowledged that business model innovations must generate and restructure new business activities. The authors also demonstrated that business model improvements help SMEs expand and succeed. Nevertheless, they stressed that in order to secure SME growth, business model innovations must be handled successfully and efficiently. Business model innovation is critical for boosting a company's sustainability, which assures its growth and competitiveness (Horvath et al., 2019, p. 64). As a result, in order to gain long-term competitive advantage and growth, an organisation must undertake business model innovations. Moreover, previous studies have not attempted to assess the influence of business model innovation on the high-impact development of Malaysian SMEs. Academics should conduct a study to explore the relationship between business model innovation and SMEs' high-impact growth. Therefore, the researcher developed and sought to test the following hypothesis: H5: Business model innovation has a significant positive influence on the highimpact growth of SMEs. 2.13.6 Moderating Role of Competitive Advantage on High-Impact SME Growth

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English and Hoffmann (2018) highlighted that the influence of competitive advantage on SME growth had gained significant academic interest in the last 20 years. Competitive advantage refers to a company's distinct capabilities that offer it an edge over other companies in the market. The way businesses offer their services and goods to the market for consideration by consumers is crucial since the market is a source of competition. Rua et al. (2018) reported that SMEs are continually influenced by possible risks, making them sensitive to business sustainability and competitiveness. The authors proposed that in order to be competitive, businesses must have distinctive talents. Competitive advantages foster an innovative culture in SMEs, allowing them to develop the competencies needed to respond to market challenges and opportunities (Kiyabo & Isaga, 2019). The innovations also give clients more options, ensuring that SMEs increase their performance. English and Hoffmann (2018) emphasised that innovation provides organisations with a competitive edge and guarantees continuous expansion. A firm's competitive edge can be influenced by both external and internal variables. As a result, businesses should identify and pursue the most relevant activities and important core capabilities that will help them obtain a competitive edge. Matloob et al. (2021) observed that employee motivation develops when an organisation enables its people to perform effectively and enhance the performance of the organisation. Organisations must guarantee that their personnel are motivated in order to maintain competitiveness (Parjoleanu, 2020). Additionally, staff training assists employees in acquiring new abilities, which increases employee retention and organisational engagement (Parjoleanu, 2020). Staff motivation also increases employee effectiveness, which contributes to the sustainability and success of an organisation. Essentially, companies that maintain employee motivation see increased productivity and expansion. Employees of SMEs may participate in training courses

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to improve their abilities, thereby contributing to the rapid expansion of SMEs. Authors such as Yusoff et al. (2018) emphasised that SMEs must ensure staff motivation since it inspires long-term commitment. Prior research has focused on the role that competitive advantage plays in the rapid expansion of Malaysian SMEs. How market orientation and innovation affect competitive advantage in Malaysian SMEs was examined by Udriyah et al. (2019). According to their findings, market orientation is important in recognising consumers' wants and designing the enterprise's products and services to match those needs. Udriyah et al. (2019) asserted that fulfilling customer needs enhance business performance and growth. They also mentioned that SMEs might boost their innovativeness by using innovative approaches, including labour skills, employee engagement, and managerial competencies. Moreover, Okolocha (2020) emphasised that employee motivation adds to work satisfaction and organisational dedication, which contribute to the success of SMEs. The author added that SMEs in Malaysia lack trained personnel due to insufficient employee training. The lack of trained employees demonstrates the necessity for employee training to achieve improved business performance and sustained growth. Furthermore, marketing orientation leads to market innovation, which adds to organisational success by establishing a competitive advantage (Adi & Adawiyah, 2018). Marketing innovation assists businesses in developing top-tier products for their consumers based on their demands, ultimately increasing customer satisfaction and business growth. Employee coaching may assist in strengthening these abilities, which will improve the firm's commercial performance and help it acquire a competitive edge. Innovation leads to a unique and sought-after idea that offers SMEs the chance to attain superior performance in the market, providing them with a further

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opportunity to achieve a competitive advantage. As a result, market orientation and innovation provide superior results, assuring SMEs' high-impact growth. According to Yatim et al. (2019), management talents give SMEs a competitive advantage. They also stated that SMEs must have the suitable infrastructure and business facilities to improve company performance. Firm performance improves competitive advantage, resulting in SMEs experiencing high-impact growth. The authors proposed that the government may be a valuable source of benefits for SMEs by providing them with the essential necessities for success. For example, the government should provide SMEs with access to energy, water, and other services. Furthermore, the authors stated that the government might offer SMEs consulting services to help them achieve improved market performance and a competitive edge. Haseeb et al. (2019) reported that technological and social advancements are an important source of competitive advantage for SMEs. They stated that the longterm performance of SMEs is important in a competitive setting. As stated by the authors, a proper decision-making framework is crucial for defining the strategic decisions that SMEs must undertake to maintain a competitive edge. In order to enhance low business performance and assure optimal performance, SMEs should use new technology. The authors also suggested a strong and positive relationship between technology and competitive advantage. A competitive edge boosts corporate performance and assures expansion. According to Aziz and Samad (2016), distinctive goods are significant sources of competitive advantage in SMEs. In addition, they emphasised that in order to be competitive in the market, SMEs should participate in creative activities on a continuous basis. Nevertheless, the researchers argued that youthful enterprises are more competitive in the market due to their proactiveness, aggressiveness, and

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adaptability. Competitive advantage enables businesses to apply novel methods that increase efficiency and effectiveness in order to achieve maximum growth. As stated in the studies above, a competitive edge is critical for SMEs since it translates into increased business performance. Ismail and Alam (2019) investigated how innovation affected Malaysian SMEs' competitive advantage. They stated that innovation enables businesses to fulfil all of their customers' changing requirements. As customers seek items that meet their changing demands, they require diverse and one-of-a-kind offerings. Firms should consequently develop distinctive goods and services to attain superior performance, which translates to high-impact development for SMEs. The authors further asserted that innovation helps organisations accomplish their goals, such as greater sales and profitability. According to Ismail and Alam (2019, p. 78), companies acquire a competitive edge in the market when they provide more value to their consumers than their competitors. The competitive edge will lead to even better performance, boosting SME growth. Kumar et al. (2019) stressed that organisational innovation provides firms with a competitive edge. The authors also stated that a company's competitiveness would suffer if it does not participate in innovation and entrepreneurship. As a result, SMEs should embrace entrepreneurial orientation and knowledge advancement to achieve a competitive advantage. They also proposed that SMEs should engage in organisational learning and knowledge dissemination since they contribute positively to organisational performance and competitive advantage (Kumar et al., 2019). According to Khurram et al. (2019), SMEs with a sustained competitive advantage rely on human, social, and financial resources. Human capital refers to what a company understands and the distinctive capabilities that allow it to acquire a

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competitive edge in the market. Social capital dictates the firm's clients. On the other hand, financial capital implies a firm's financial resources that contribute to its everyday operations. They discovered that these three forms of capital had a positive impact on an enterprise's competitive edge (Khurram et al., 2019). Lee et al. (2016) revealed that knowledge management might be used to obtain a competitive advantage. As per the authors, practical knowledge is utilised to establish core competencies that assist firms in enhancing their performance and achieving a competitive advantage. Knowledge management is created by analysing existing knowledge and comparing it to what is required. In order to obtain a sustained competitive advantage, more steps are necessary to incorporate the knowledge. According to the studies described above, competitive advantage has a significant influence on organisational performance and business growth. The sources of competitive advantage in Malaysian SMEs were examined by Al Mamun et al. (2018). They stated that entrepreneurial talents are the essential competencies that secure firms' competitive advantages. Entrepreneurial competencies are defined by a firm's resource capabilities. As per the findings of this study, competitive advantage significantly impacts the firm's performance and overall growth. As reported by the authors, competitive advantages help SMEs create crucial capacities for increased and sustainable high-impact growth. Their findings also suggested that SMEs perform better when they have a competitive edge. Al-Juoori et al. (2021) argued that organisational learning positively and significantly impacts SMEs' performance. The authors further argued that organisational learning is essential as it promotes organisational survival. Organisational learning refers to the process where employees in an organisation create knowledge, retain it, and subsequently transfer it within the organisation,

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resulting in knowledge assimilation within the organisation (Antunes & Pinheiro, 2020). Thus, it can be argued that business coaching contributes to organisational learning as SMEs' staff gain knowledge related to the market and business strategies that can aid in the process of increasing their effectiveness and efficiency. Furthermore, business coaching allows firms to learn to employ business strategies that result in long-term success. Tukamuhabwa et al. (2021) suggested that SMEs aiming to gain a competitive advantage should undertake business coaching programmes, such as programmes that promote continuous development for their staff. Continuous staff development in an SME will ensure that the company responds proactively to market changes, thus promoting its competitiveness. Additionally, continuous knowledge in an SME will allow the firms to create specific competencies, thereby enhancing sustained competitiveness. According to Antunes and Pinheiro (2020), competitive advantages have several attributes, including cost structure, quality product offerings, customer services, and branding. Firms that take advantage of these attributes will realise competitive advantages. Business coaches help SME owners to realise their business strengths and mitigate existing weaknesses to promote business success (Ofili, 2018). Business coaches further help SME owners to establish a clear path for their business and promote business improvement. Business improvement results in the development of new products and services that ensure customer satisfaction, thus enhancing competitiveness. Therefore, the deployment of these competitive advantage attributes in SMEs allows them to become competitive as they become more productive and offer higher-quality goods and services than their competitors. These factors enhance SMEs' productivity, allowing them to generate more sales than their competitors in the

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market. This rivalry promotes competitiveness among SMEs, thereby promoting growth and performance. Basten and Haamann (2018) argued that businesses gain competitiveness when they produce services and products that are both different from and superior to those of their rivals. Offering differentiated products and services allows these firms to acquire differential advantages, leading to greater profit margins than their rivals. Prasanna et al. (2021) posited that SMEs could gain competitiveness by differentiating themselves from the common market offerings. The differentiation allows SMEs to increase their market value. Consequently, business coaching is arguably consequential for SMEs because it is a significant determiner of their performance. Competitive strategies allow SMEs to shift their economic resources from less productive areas to more productive areas to promote efficacy (Castaneda et al., 2018). Business coaches notably train SMEs to improve the efficacy of their economic resources to operate more effectively. The efficacy of economic resources in SMEs reduces firms' chances of becoming economically vulnerable. This reduction of economic vulnerability promotes growth and competition, thereby improving firms' performance (Noy & Yonson, 2018). According to Woźniak et al. (2019), SMEs have much potential for utilising appropriate growth strategies. They argued that the utilisation of such strategies promotes SMEs' growth and enhances their performance as they implement strategic entrepreneurship (Woźniak et al., 2019). Business coaching promotes strategic entrepreneurship as it helps SME owners to leverage available entrepreneurial opportunities to promote competitiveness. Ardley and Naikar (2021) opined that SMEs could realise long-term growth by adopting product and process improvement, which

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results in the development of meaningful products, thus attracting new customers and retaining current ones. Furthermore, customer retention increases the firms' sales and growth. Innovation and product improvement are the key competitive strategy that ensures that a firm remains competitive in the market. The application of growth measures in SMEs promotes competitive advantages (Kiyabo & Isaga, 2019). Vătămănescu et al. (2019) noted that the implementation of innovation strategies and new technologies in SMEs drives competitive advantages. When SMEs embrace new technologies, new opportunities arise that their competitors may not have, allowing them to gain competitiveness in the market. As per the assertions mentioned in the literature, the researcher developed and sought to test the following hypotheses: H6: Competitive advantage moderates the relationship between motivation and high-impact growth of SMEs. H7: Competitive advantage moderates the relationship between improved productivity and high-impact growth of SMEs. H8: Competitive advantage moderates the relationship between job satisfaction and high-impact growth of SMEs. H9: Competitive advantage moderates the relationship between innovation and high-impact growth of SMEs. H10: Competitive advantage moderates the relationship between improved business model innovation and high-impact growth of SMEs.

Conceptual Framework Kovács-Kószó (2020) defined a conceptual framework as the model that is used to explain the relationships between independent and dependent variables in order

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to answer research questions. A conceptual framework is intended to provide the proper context for an investigation, the issue being studied, and any potential solutions (Kovács-Kószó, 2020). The formulation of research questions and hypotheses was the main emphasis of the current study. A conceptual framework employs images to explain the key ideas under investigation and the relationships between the variables. According to Kivunja and Kuyini (2017, p. 47), a conceptual framework is the researcher's conceptualisation of the entire study endeavour. The conceptual framework aids in identifying the variables to be measured in order to identify any causal relationships between the study's variables. The conceptual framework of the current study is illustrated in Figure 2.3 below.

Independent Variables

Dependent Variable

Employee Motivation Productivity Job Satisfaction

High-Impact SME Growth

Innovation Business Model Innovation

Moderating Variable Competitive Advantage Source: Researcher (2021)

Figure 2.3: Conceptual framework

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2.14.1 Explanation of the Conceptual Framework The dependent variable in this study, which is reliant on business coaching, was the overall high-impact growth of SMEs. It comprises employee motivation, productivity, job satisfaction, innovation, and business model innovation as independent variables. Competitive advantage was the moderating variable. All of these variables might lead to the high-impact growth of SMEs. The study's variables are defined in Table 2.1.

Table 2.1: Definition of the variables Independent Variables Employee motivation

Productivity Job satisfaction Innovation

Business model innovation Competitive advantage

Dependent Variable High-impact SME growth

Definition The efforts made by a firm to achieve its organisational goals (De Sousa Sabbagha et al., 2018). The amount of work accomplished by employees (Ismail, 2018, p. 246). The employees' feelings in the workplace (Mira et al., 2019). The introduction of new goods and services in the market to gain a competitive advantage (Alam et al., 2016). A company's structure and methods are used to generate value from consumers (Chen et al., 2021). Unique capabilities that give a firm an advantage over other firms in the market (English & Hoffmann, 2018). Definition The optimal performance of SMEs, guided by the enterprise's goals, objectives, and strategies (Tong & Serrasqueiro, 2020).

Research Gaps The literature review revealed notable research gaps. Table 2.2 summarises the knowledge gaps.

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Table 2.2: Summary of the research gaps Authors Title Ismail et al. Aligning (2018) Malaysian SMEs with the Megatrends: The roles of Highperformance work practices (HPWPs) and employee creativity in enhancing Malaysian SME performance Mahmod et A conceptual al. (2018) framework of enterprise risk management (ERM) practices among SMEs in Malaysia

Methodology Descriptive research

Findings Highperformance work practices, such as employee creativity, enhance SME performance.

Research Gap The study focused on employee growth and how it promotes SME performance. The study did not examine other factors that promote SME performance.

Descriptive research

The adoption of enterprise risk management practices positively and significantly impact SMEs in Malaysia.

Influence of Descriptive employeeresearch focused corporate social responsibility and employer brand on turnover intention

An unskilled and uneducated workforce constrains the productivity and growth of SMEs in Malaysia.

Palanimally Factors that Descriptive et al. (2020) influence the research growth performance of SMEs in Malaysia

The study discovered that asset management, productivity, and cash flow affect the growth of SMEs.

The study only focused on enterprise risk management and its effect on SME growth. It failed to examine other factors that determine SME growth. The study concentrated on how an unqualified workforce hinders SME growth. The study failed to examine other factors that hinder SME growth. The study did not examine the role of business coaching and its effect on SME growth.

Okolocha (2020)

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Authors Title Methodology Yusoff et al. Sustainable Descriptive (2018) growth in research SMEs: A review from the Malaysian perspective

Findings Sustainability significantly and positively affects SME growth.

Research Gap The study focused on sustainability and SME growth, but it overlooked other factors that affect SME growth. Therefore, the study's findings cannot be generalised.

Source: The reviewed empirical studies (2021)

Summary of the Literature Review The literature study reported in this chapter shows that SME performance is one of the most studied topics by researchers. The study discovered a positive and significant relationship between business

coaching

and (employee motivation,

productivity, job satisfaction, innovation, business model innovation, competitive advantage) and the high-impact growth of SMEs. Nevertheless, the researcher discovered several gaps in the literature, which are presented in Table 2.2. The study aimed to address these research gaps. Chapter 3 below presents the research methodology.

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CHAPTER 3 RESEARCH METHODOLOGY

Introduction The methodology adopted in the current study is described in this chapter. The sections that follow discuss the study paradigm, methodology, outline, philosophy, research design, data collection, data analysis, and ethical considerations.

Research Paradigm The researcher's viewpoint and views are described in a research paradigm (Kivunja & Kuyini, 2017, p. 26). It is the lens through which academics interpret their common views. Kivunja and Kuyini (2017) described many research paradigms, such as positivism and interpretivism. The determination of causalities between research variables is emphasised under a positivist paradigm. According to Park et al. (2020, p. 5), a positivist research paradigm assists researchers in determining functional relationships between causal and explanatory factors. The independent variables are explanatory factors, whereas the dependent variables are outcomes. The authors emphasised that a positivist research paradigm aids in the generation of explanatory explanations, leading to the development of control over the phenomenon being studied.

The

researcher

employed

a

positivist

research

paradigm

to

emphasise explanation and prediction. The researcher also employed positivism to test hypotheses and establish causal relationships between independent and dependent variables. In summary, as the researcher investigated these causal relationships, a positivist research paradigm was appropriate for the current study.

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Maula and Stam (2019) stated that a quantitative research methodology is utilised when a researcher aims to develop numerical measurements. The measures were utilised to collect data and identify any causal relationships between the independent variables (employee motivation, productivity, job satisfaction, innovation, business model innovation, and competitive advantage) and the dependent variable (high-impact SME growth). According to Powell (2019), a quantitative research methodology measures data objectively and quantitatively. Researchers may assess the objectivity of the findings. Thus, the researcher employed a quantitative research methodology to evaluate the existence of a significant relationship between these factors and to test the hypotheses. Furthermore, the quantitative research method was utilised to gather data on the impacts of employee motivation, productivity, job satisfaction, innovation, business model innovation, and competitive advantage on the high-impact growth in Malaysian SMEs.

Research Methodology According to Smith (2020), a research methodology outlines a precise and systematic process for collecting and evaluating data or information required to analyse a research topic. Researchers must examine the research philosophy, research strategy, research design, data collecting technique, research method, and data analysis method, among diverse elements of the methodological framework (McPhail & Lourie, 2017). The findings are heavily reliant on identifying the best components for the methodological framework (Newman & Gough, 2020). While selecting relevant components, researchers should evaluate the nature of the study and its requirements (Clarke & Visser, 2019). This decision is critical since minor errors in appropriate

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methodological aspects can drastically influence the findings, compromising the study's credibility (Ahmed et al., 2016). This chapter outlines the methodological approach utilised for data collection and analysis in order to analyse the role of coaching and training in improving Malaysian SMEs' performance in the context of RichWorks International's coaching and training services. The chapter specifically examines why certain methodological framework components were chosen, and the remaining were omitted. The three general strategies utilised to guide mixed-methods research are as follows: 1.

Sequential – When the researcher strives to expound on or expand findings from one method with another

2.

Concurrent – The researcher can converge qualitative and quantitative data to offer a detailed analysis of the research problem

3.

Transformative – The researcher can utilise a theoretical lens as an integrated and holistic viewpoint within the design, including qualitative and quantitative methods The lens serves as a framework for the study's topic of interest, data collection

techniques, and predicted findings or changes. The strategy can be implemented sequentially or concurrently (Creswell, 2003, p. 16). The increased interest in mixed-methods research is evident in the number of publications, journals, and books devoted to mixed-methods methodologies (Creswell, 2003, p. 208). The disadvantages of utilising a mixed-methods design are timeconsuming and the need for experience in both qualitative and qualitative methodologies. Thus, the researcher adopted a quantitative methodology to analyse the impact of presenting a developmental viewpoint (through knowledge, inquiry, and assessment) to SMEs in RichWorks' business development post-secondary 135

programmes. Besides, the researcher used a transformational strategy. The strategy is led by the application of a certain theoretical perspective, which is the constructive development theory in this study. The quantitative and qualitative data were gathered simultaneously.

Method Outline Alavi et al. (2018) highlighted that describing a method entails delineating the methodological framework to provide a roadmap for leading a study on its desired course. Bairagi and Munot (2019) stated that the primary feature of a method outline is to offer the researcher a precise and methodical approach for examining the research topic and fulfilling the objectives. Hence, a method outline assists the researcher in selecting the methodological framework components by taking into account the study's requirements, nature, and aims (Leatherdale, 2019). The researcher aimed to examine the relationship between business coaching and the high-impact growth of SMEs in the context of RichWorks International's coaching and training services in the current study.

Research Onion The research onion, created by Saunders et al. (2019), is a framework that outlines the steps that researchers must take in order to identify the best methodological framework (Zawacki-Richter et al., 2020). Cuervo-Cazurra et al. (2017) stated that the framework's name is self-explanatory, with the layers of an onion representing the methodological framework's components. Every layer of the research onion is structured in accordance with its significance or utility within the overall methodological framework (Daniel et al., 2018). The most important elements are at

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the centre of the research onion, while the layers of lower value are towards the edges (Tobi & Kampen, 2018). The approach assists researchers in selecting the most appropriate methodological framework components by taking into account the study's purpose, objectives, and needs (Dwigo & Dwigo-Barosz, 2018). Mohajan (2018) stated that numerous researchers struggle to choose the most appropriate elements for the methodological framework. The research onion can assist researchers in overcoming this challenge. Thus, the current researcher employed a research onion to identify the most appropriate methodological framework elements.

Research Philosophy Zangirolami-Raimundo et al. (2018) described research philosophy as a set of beliefs, values, traditions, traditions, and other characteristics that govern information selection and analysis. The research philosophy is the outermost layer of the research onion since it is substantially less prevalent in the research methodology (Ørngreen & Levinsen, 2017). Nevertheless, the features of the research philosophy are critical since they have a significant impact on information selection and analysis and, consequently, on the final results (Wiek & Lang, 2016). Thus, researchers should choose the appropriate philosophy for their study based on its goals, objectives, nature, and requirements. Pragmatism, interpretivism, and positivism are the most prominent research philosophies. According to Greenfield and Greener (2016), among the most common errors that researchers commit is choosing a single point of view for their analysis. Papachristodoulou et al. (2017) suggested that a single point of view considerably decreases the study's quality and lessens its scope. Pragmatic research philosophy can assist researchers in overcoming this issue. Its core principle is that no single ideology,

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perspective, or viewpoint can thoroughly analyse a research topic (Mohajan, 2018). Researchers who employ this concept should utilise diverse views (Bryman, 2016). The method allows researchers to examine their issues from several perspectives, hence improving the study's quality (Myers, 2019). This aspect is the most crucial aspect of the pragmatic research philosophy. Nonetheless, unlike positivism, this philosophy neither emphasises actual facts nor urges researchers to concentrate on human elements such as interpretivism, which are the primary drawbacks of the pragmatic research philosophy. As stated by Apuke (2017), a positivist research philosophy requires researchers to emphasise factual data gathered from experiments and observations. Chidlow et al. (2015) stated that positivist researchers must evaluate data from previous observations, experiments, and studies that have already been validated for validity and credibility (Ørngreen & Levinsen, 2017). This action is crucial because researchers frequently employ data with unverified reliability, accuracy, and validity, lowering the research's quality despite undertaking an extensive study (Bailey & Burch, 2018). Notwithstanding, researchers that employ a positivist philosophy do not have to deal with these concerns because the data's reliability, credibility, and validity have already been evaluated (Kingsley et al., 2017), which is the philosophy's major strength. Rahi (2017) stressed that the interpretivist research philosophy demands researchers to emphasise the human aspect of the study issue. Fuller et al. (2016) stated that researchers utilising this philosophy must differentiate social factors from human elements in the study. Therefore, unlike positivist researchers who objectively assess a research topic, interpretivist researchers must subjectively analyse in order to concentrate on how humans view the world (Hamilton et al., 2017). The research

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practice and methodology employed in a study are typically impacted by the research paradigm and philosophy. Research philosophy is a set of beliefs and hypotheses concerning knowledge evolution (Bailey & Burch, 2018). The research philosophy consists of ontological assumptions (assumptions about the nature of reality), epistemological assumptions (researchers' views on how knowledge must be acquired and what constitutes knowledge), and axiological considerations (the influence of ethics and values in the research). These components determine the methodological selection, research strategy, and data collection techniques (Bailey & Burch, 2018). The research paradigm can be used to differentiate the research philosophy (Ørngreen & Levinsen, 2017). A research paradigm is a framework that drives the conduct of research. It reflects the researcher's philosophy and beliefs about the universe and the nature of knowledge (Bryman, 2016). Thus, the research paradigm reflects the researcher's ontological (beliefs about reality) and epistemological (theory of getting information) attitude and guides the researcher's activities when performing an investigation. According to the findings of this study, this quantitative research is grounded on positivism. Positivists believe in an independent external world, things can be comprehended and described through rational observation, and quantitative methods, including surveys, experiments, and statistical analysis, may be used to gather information (Bailey & Burch, 2018). The ontological perspective of research examines the link between the researchers and reality. The ontological assumptions of research influence how the researcher perceives the universe and investigates the things being studied. The primary question in ontological assumptions involves whether an objective reality exists outside of social entities or phenomena or if social entities or phenomena may and must be understood as social constructions generated by social

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actors' perceptions and actions (Bryman, 2015). In short, social phenomena possess external facts beyond the influence and control of social actors and should be studied objectively. Alternatively, social phenomena are a product of social interaction and must be studied subjectively, with social actors as participants involved. The ontological position of positivism is realism. Hence, from the positivist perspective, an absolute reality independent of social actors exists. This explanation is in contrast to the ontological viewpoint of relativism, which asserts that reality is individually produced and subjective, varying from individual to individual (Bailey & Burch, 2018). This study employed a positivist ontological approach. It asserts that an objective universe exists that can be explored independently of the researcher (Ørngreen & Levinsen, 2017). In order to achieve this goal, the study concentrated on determining factors impacting SME growth. As each nation's business activities are unique, the study required an understanding of the effects of numerous elements and the moderation that influences these interactions to acquire a deeper understanding of these aspects in the Malaysian SMEs context. The epistemological perspective of research is concerned with the assumptions about what constitutes knowledge and how knowledge is generated, gained, and disseminated to the general public (Buckley et al., 2017). The epistemological perspective in research is often separated into positivistic and interpretative epistemologies (Ørngreen & Levinsen, 2017). Positivist epistemology is motivated by objectivism. A positivist researcher believes in an independent and unbiased method of collecting information about the studied phenomenon. The positivist method of knowledge acquisition entails the systematic collection of data based on literature and a theoretical framework, followed by rigorous analysis to offer a trustworthy and

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accurate explanation of the correlations between the variables under consideration (Ørngreen & Levinsen, 2017). In a positivist method, the researcher's goal is to produce information supported by empirical evidence derived from scientific inquiry. This method is distinct from interpretative epistemology that is driven by subjectivism based on real-world facts. From an interpretative epistemology standpoint, researchers contend that knowledge is generated through interactions between awareness and the real world (Ørngreen & Levinsen, 2017). Thus, researchers must experience and engage in the real world in order to obtain information. According to interpretative epistemology, the researcher is an integral component of the research process and generates knowledge through interactions with study participants (Buckley et al., 2017). Consequently, knowledge and meaningful reality are formed through continuous interaction between the participants and the researcher and subsequently developed and communicated within a social context, disclosing the social forces and structures influencing the hidden real world (Ørngreen & Levinsen, 2017). In this research, a positivist stance has been chosen. Accordingly, the researcher seeks to gain information on the elements that affect the financial decisionmaking of SMEs through a systematic research approach underpinned by an established theoretical framework (Ørngreen & Levinsen, 2017). Thus, the researcher must retain objectivity and independence while confirming the expanded theoretical framework based on the study's accepted theory and when testing hypotheses through empirical hypothesis testing.

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Justification of the Pragmatic Philosophy The researcher employed a pragmatic research approach in this study. This approach enabled the researcher to examine the role of coaching and training in improving Malaysian SMEs' performance in the context of RichWorks International's coaching and training services from many viewpoints. The decision has critical ramifications. First, the researcher examined the research topic from several angles by applying numerous views. The approach also improved the study's quality. The researcher dismissed positivism since it emphasises largely factual data from experiments, observations, and previous studies and drastically lowers the researchers' role, requiring them to operate as data collectors and interpreters. Interpretivism was also dismissed since its focus is on the human factor. Moreover, as the philosophy encourages researchers to analyse the research topic subjectively, it is better suited for studies that use a secondary data collection technique and qualitative data analysis. Nevertheless, the researcher obtained primary data through questionnaires and applied a quantitative data analysis approach in the current study. Thus, the researcher chose the pragmatic research philosophy.

Research Approach This section describes the research method and methodologies, followed by a discussion of the epistemology and general research design utilised in the current study. According to Delen and Zolbanin (2018), a research methodology refers to the method that researchers employ to undertake their research, from the development of broad assumptions through the precise procedures of data collecting and analysis to findings interpretation. Easterby-Smith et al. (2015) stressed that the research approach is important within the research onion. Researchers must evaluate the study's

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goals and objectives and the nature of the study. Among the most prevalent tactics are inductive and deductive approaches. Quinlan et al. (2015) stated that deductive researchers must leverage existing models, frameworks, and theories relevant to the research topic. According to Buckley et al. (2017), this strategy assists researchers in considering the use of current theoretical frameworks, models, and tools for analysing their findings. The approach is critical because it enables researchers to examine their findings' accuracy, reliability, and validity (Walliman, 2018) and also their assumptions, beliefs, and hypotheses, utilising established theoretical models, frameworks, and tools (Gray, 2019). This approach improves the accuracy, quality, credibility, and reliability of the research. Nonetheless, the deductive method fails to support certain analytical tools, nor does it help researchers to construct their own analytical tools, models, or frameworks depending on the specific features of their subject (Sekaran & Bougie, 2016). Regardless of the context in which previous theoretical frameworks and models were established or the study's nature, researchers using this approach must accept such frameworks and models. The limitation may negatively impact the quality and scope of these studies, rendering it the major limitation. Ghauri et al. (2020) argued that, contrary to the deductive approach, the inductive approach enables researchers to investigate new and novel approaches, models, and tools for analysing the findings. According to Bezzina and Saunders (2014), researchers who utilise the inductive approach must construct their analytical framework based on the study's needs, nature, purposes, and objectives. Thus, the distinction between the deductive and inductive approaches is as follows: The deductive method supports current models, frameworks, and tools, while the inductive

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approach enables researchers to develop new models, frameworks, and tools depending on the needs of the research (Eriksson & Kovalainen, 2016). The approach enables researchers to create more relevant and appropriate models, tools, and frameworks for their aims (Hair et al., 2015). Nevertheless, researchers are not always sure about the accuracy, validity, or credibility of their models, frameworks, and instruments, which can have a negative impact on the outcomes. Additionally, the approach does not assist researchers in determining the accuracy, credibility, validity, or relevance of their assumptions and hypotheses.

Justification of the Deductive Approach The current study's researcher adopted a deductive research approach, which aided in considering existing models, theoretical frameworks, and tools for evaluating the primary data analysis findings. The researcher also examined the reliability and validity of the hypotheses using this approach. The deductive technique has significant implications for this study as it assisted the researcher in improving the accuracy, credibility, validity, or relevance of the study.

Research Design Golichenko (2016) highlighted that a research design is an overarching approach that researchers employ to integrate the various study components logically. According to Bell et al. (2018), a research design serves as a road map for data collection, analysis, and interpretation. A research design assists researchers in analysing the research problem, background information, and other study aspects, such as the study's goals and objectives (Daniel & Harland, 2018). Three of the most often utilised research designs are descriptive, exploratory, and explanatory. As stated by

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Ngozwana (2018), the primary objective of descriptive research is the correlation of the findings. Researchers utilising a descriptive design must correlate the primary and secondary data analysis findings to the objectives of their study. Taylor et al. (2016) stated that one of the most typical issues that researchers face is the study's coherence. Researchers, in particular, frequently struggle to maintain alignment among a study's results, aims, and objectives, which has a negative impact on its quality (Antwi & Hamza, 2015). Thus, the descriptive research design is critical because it enables researchers to correlate findings with their aims. Nevertheless, as the whole emphasis is on coherence, it makes effective analysis of the research problem, background information, or topic difficult (Lynch & Mannion, 2016). Instead of assisting researchers in improving the studies' quality or scope, this narrow focus dramatically diminishes both. According to Thomson and McLeod (2015), when the research problem has not been examined, researchers often adopt an explanatory design. Explanatory research designs require researchers to focus not solely on the issue statement or study challenge but also on operational definitions and other important features (Saunders & Bezzina, 2015). Moreover, instead of choosing an issue, statement or unsolved research issue at random, researchers must choose topics that are currently important and require analysis (Krishnaswamy et al., 2006). Therefore, researchers who utilise this design must identify and analyse the research problem in light of background information, distinct views, and diverse ideologies. This criterion assists researchers in developing a framework that will allow future academics to undertake comparative research, the primary strength of this design. Nonetheless, this strategy overlooks coherence, which greatly affects the quality of related studies.

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Snyder (2019) highlighted that an exploratory research design is acceptable when the number of studies is insufficient or adequate information about the research topic is lacking. Murshed and Zhang (2016) highlighted that exploratory research typically serves as a theoretical framework for future researchers studying comparable subjects premised on the provided theoretical or hypothetical information. Researchers who utilise the approach must examine the components contributing to the research problem (King & Mackey, 2016). The biggest limitation of this design is that studies utilising it are frequently unstructured due to a lack of information on the research problem (Basias & Pollalis, 2018).

Justification of the Descriptive Design The researcher employed a descriptive research strategy in this study, which assisted in relating the findings to the aims. This decision had a significant impact in assisting the researcher in overcoming coherence issues, thus improving the study's quality. The researcher disregarded an explanatory study strategy since it would concentrate on the problem statement and background information and would not aid in resolving coherence-related issues.

Data Collection Method According to Flick (2015), the data gathering method is the innermost layer of the study onion. Kumar (2019) stated that the major goal of a data collection method is to ease the information gathering required to analyse the research topic. Researchers analyse the data to determine the goal, objectives, research problem, and research questions, rendering the component essential (Fletcher, 2017). The most prevalent data collecting methods are primary and secondary data collection. Primary data collection

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necessitates researchers gathering first-hand information, namely information obtained directly from the individuals being studied or stakeholders involved (Taherdoost, 2016). Clark et al. (2017) highlighted that primary data collection methods, including interviews, surveys, experiments, and observation, could be utilised by researchers. Researchers that use this method acquire highly accurate, credible, and reliable data directly from the individuals modelled in the study or related stakeholders (Bentahar & Cameron, 2015). The strategy for data collection assists researchers in overcoming challenges regarding relevance that are typical in secondary data collection, which is one of the fundamental strengths of primary data collection (Kingsley et al., 2017). Nevertheless, data obtained in the method include significant bias, which, if not analysed or eliminated, can have a negative impact on a study's outcomes, findings, and quality (Chidlow et al., 2015). Researchers must obtain secondary data from a variety of secondary sources, including peer-reviewed studies, industry reports, trustworthy media articles, yearly reports, websites, and government reports (Bailey & Burch, 2018; Smith, 2020). According to Myers (2019), the major advantage of secondary data collection is that researchers will not have to be concerned about the data's quality, reliability, credibility, or validity because previous scholars have already examined such qualities. Thus, researchers frequently employ secondary data collection to acquire reliable and credible data in order to improve their research quality (Bryman, 2016). Additionally, contrary to primary data, which contains considerable bias, secondary data are not related to bias issues since any biases were already identified and corrected by previous researchers before publication (Greenfield & Greener, 2016). The major limitation of secondary data collecting is that researchers must

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devote considerable amounts of energy, time, and other resources to locating pertinent information (Wiek & Lang, 2016), which may be due to the fact that secondary data studies have been undertaken in many contexts. Hence, finding studies similar to each other, even for studies that share a research topic, is difficult.

Justification of the Primary Data Collection Method The researcher used primary data collection in this study, which allowed data to be collected directly from Malaysian SME owners. The researcher surveyed 245 Malaysian SMEs and entrepreneurs. This approach had a significant impact on the study since it enabled the researcher to acquire relevant, accurate, credible, and reliable primary data directly from Malaysian SME owners. Furthermore, this approach aided in the analysis of the issue and improved the study's quality.

Research Method The mixed-methods strategy was chosen by the researcher for this study. Mixed methods research is a relatively recent research methodology in the social and human sciences. It began in 1959 when Campbell and Fiske employed a multi-method matrix to investigate the validity of psychological traits. They employed a variety of data gathering methods, such as interviews, observations, and integrated surveys. One of the reasons for using mixed methods research is because biases in one method can be neutralised or cancelled by biases in another. Triangulating data sources allows the pursuit of convergence between qualitative and quantitative methodologies. According to Cuervo-Cazurra et al. (2017), a research method refers to the procedures, strategies, plans, and tactics that researchers utilise to obtain the necessary information. Zangirolami-Raimundo et al. (2018) stated that research methodologies

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assist a researcher in gathering data for analysing the research issue and uncovering new relevant information. Among the most frequent research methods include surveys, interviews, experiments, secondary data analysis, archival study, and observation. Surveys are commonly used by researchers to collect information from a pre-set sample of respondents (Ørngreen & Levinsen, 2017). Typically, survey questions are closed, and respondents only need to choose their preferable responses (Dwigo & Dwigo-Barosz, 2018). The most crucial strength of the survey method is that it allows researchers to collect data from a large number of respondents in a short amount of time (Daniel et al., 2018). Closed questions have a major limitation as they do not allow respondents to complete questions narratively or offer specific replies that differ from the options provided (Zawacki-Richter et al., 2020). Contrarily, interviews are a research method that enables researchers to comprehend and explore participants' thoughts and perspectives through a set of openended questions that they may respond to thoroughly and comprehensively (O'Brien & Pipkin, 2017). The merit of the interview method is that respondents can openly share their thoughts on the questions without being confined to a limited selection of replies, as in a survey (Leatherdale, 2019). One significant limitation is that this technique is time-consuming, and researchers frequently encounter accessibility issues, preventing them from collecting information from a large sample of respondents. The researcher utilised a survey in this study and obtained primary data from 245 Malaysian SMEs using the survey approach. As the questions were close-ended, respondents did not have to spend much time answering the survey, enabling them more inclined to participate. The survey was sent through Google Forms links by the researcher. This approach aided in the collection of accurate, credible, and reliable data

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directly from Malaysian SMEs' owners. Google Forms was used to distribute semistructured questionnaires.

Sampling Method and Sample Size Clark et al. (2017) stated that statistical sampling, survey technique, and quality assurance are the procedures and criteria by which researchers choose a subset of the total population to ascertain its qualities. Due to the massive size of a population, it is impossible to analyse every individual. Hence, researchers frequently evaluate a subset, presuming that it is reflective of the entire population (Bairagi & Munot, 2019). Sampling assists researchers in selecting such subsets to gather data. The researcher used random sampling in this study. Therefore, all of RichWorks International's clients' employees had the possibility of being chosen for data collection. The researcher used this sampling method to develop a subgroup of 245 Malaysian SMEs. The researcher identified 245 SMEs who had received business coaching from RichWorks International. This subset was utilised to gather the information needed to analyse the role of coaching and training in improving the performance of Malaysian SMEs performance in the context of RichWorks International's coaching and training services.

Data Analysis Method The data analysis method is determined by the nature of the data and the method of collection. Contradictorily, quantitative analysis is commonly used by researchers to analyse numerical or statistical data (Ahmed et al., 2016). The method enables researchers not only to analyse but also to understand the data. Statistical techniques such as correlation analysis, regression analysis, and descriptive analysis

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can be used to interpret statistical data. Researchers typically utilise qualitative data analysis to examine descriptive, non-numerical, and non-statistical material (Newman & Gough, 2020). The methodology enables researchers to analyse their data precisely using a variety of methodologies, including thematic and content analyses. The structural relationships between the research variables were established using structural equation modelling (SEM) in this study.

Justification of the Quantitative Data Analysis Method The researcher in this study employed quantitative data analysis to acquire numerical information through surveys. The decision had a crucial implication as the quantitative analysis helped in analysing and interpreting the primary data. The researcher used statistical techniques to interpret the data, such as descriptive analysis, model fit analysis, and correlation analysis.

Data Screening The necessity of pilot studies was emphasised in the previous chapter as a crucial step in the development of a credible instrument, which in turn meets the study's desired objectives. A pilot test was undertaken before the collection of fullscale data for the present study. The pilot study sought to investigate the critical requirements for instrument validation, including the wording of the questions, sequencing, layout, acquaintance with participants, response rate, questionnaire completion time, and analytic procedure (Hair et al., 2017). Moreover, it attempted to assess the degree of content validity and dependability in order to verify that the instructions, questions, and scale of questions were easy to comprehend (Hair et al., 2020). Before the instrument was disseminated, the questions' phrasing, sequencing,

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and layout establishing the 'facial validity' requirement were checked by emailing a small number of survey instruments to employees working in higher education institutions. As the instrument's questions were extensively used in literature, relatively few adjustments were provided by the pilot study respondents, ensuring the face validity's correctness. The pilot test was carried out by sending instruments as email attachments to randomly chosen respondents from higher education institutions. The pilot research participants were not asked to take part in the final study as it may impact their subsequent behaviour (Hair et al., 2017). Choosing a minimal sample size for the pilot test is consistent with the research, which suggests that the pilot study sample size should be typically small, such as between ten and 30 respondents or a maximum of 100 respondents (Hair et al., 2017). By the cut-off date, survey instruments had been gathered. Three responses were disqualified owing to a high amount of missing data. Consequently, the response rate for the pilot research was 85%. The pilot test found that respondents need an average of 15 to 20 minutes to answer the questionnaire. After content validity, the subsequent step in the instrument purification process is reliability (Cronbach's), which assures that measures are errorfree and hence provide consistent findings (Hair et al., 2017). Besides, exploratory factor analysis (EFA) was undertaken to validate that the results support the scale used for this study. The overall piloting instrument dependability was more than 80%, which is above the suggested level of 0.70 (Hair et al., 2017). Individual construct reliability varies between 0.691% and 0.795%. The EFA found that Kaiser-MayerOlkin (KMO) statistics, a measure of sample adequacy, were greater than the minimum required value of 0.60 for the majority of the constructs (Hair et al., 2017). Furthermore, the significance of Bartlett's test of sphericity across every construct

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suggests that the correlation between the measuring items was greater than 0.3 and appropriate for EFA. The overall variance recovered by construct questions was more than 0.60 (Hair et al., 2017). The majority of marketing and social science research is based on questionnaires (Hair et al., 2020). Additionally, it is quite uncommon to acquire comprehensive data when surveys are administered manually (Hair et al., 2020). According to Klain (2007), missing data is a commonly prevalent issue in data analysis. In survey research, the issue of missing data (incomplete data) occurs when respondents in the targeted sample fail to address one or more instrument items. Missing data generates several difficulties for statistical analysis techniques. For example, diminishing sample size caused by missing data reduces statistical power, suggesting that generalisations derived from computed estimates may be prejudiced (Hair et al., 2020). Hair et al. (2020) alerted about similar issues with missing data in multivariate analysis. They stated that, from a practical standpoint, if missing data remedies are not implemented correctly, then observations with missing values are omitted. Thus, a reduction in a sample produces an inadequate sample for comprehensive analysis. From a substantive standpoint, empirical findings extracted from data containing nonrandom missing data could be biased and lack validity. Hair et al. (2020) proposed four stages to overcome the severe difficulties of missing data: 1) analyse the kind of missing data, 2) investigate the degree of missing data, 3) assess the randomness of missing data, and 4) implement the remedies (Hair et al., 2020). In contrast, the missing data are divided into ignorable and non-ignorable categories (Hair et al., 2020). Research suggests that ignorable types of missing data can be incorporated into research survey instruments and do not necessitate treatment.

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In contrast, not-ignorable missing data are either the result of researcher procedural variables, such as mistakes during data entry or failure to include all entries, or the consequence of respondents' reluctance to address several survey questions (Hair et al., 2020). The researcher did not include any items on the survey instrument that respondents were permitted to leave blank in the current study. Therefore there was no likelihood of ignorable missing data occurrences. Nevertheless, a possibility exists for the non-ignorable missing data being absent owing to the factors mentioned above. Hair et al. (2020) proposed determining the patterns of missing data first, followed by the amount of missing data present in each individual variable, individual instance, and total dataset, for the management of non-ignorable missing data. Tabachnick and Fidell (2007) placed greater focus on the patterns than on the degree of missing data occurrences based on the significance of the patterns and frequency of their occurrences. Three different patterns exist for missing data: missing completely at random (MCAR), missing at random or often referred to as ignorable (MAR), and missing not at random or not ignorable (MNAR) (Hair et al., 2020). Tabachnick and Fidell (2007) noted that treating MNAR may provide biased findings, while MCAR may be treated with any mechanism, and the results are generalisable (Hair et al., 2020). In the current study, missing value analysis (MVA) was used to determine the patterns and degree (frequency) of missing data within each item and variable (encompassing many items to measure a similar idea) (Hair et al., 2020). The findings of the expectation maximisation (EM) approach demonstrated that Little's MCAR test was inconsequential at both the item and variable levels. Little's MCAR result was

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statistically insignificant, indicating that patterns of missing values were totally random (Hair et al., 2020). Hair et al. (2020) recommended that within random patterns, missing data levels of less than 10% may often be overlooked, but levels of 20 to 30% frequently require correction. Similar recommendations suggest that the absence of 5% or less of data in random patterns is regarded to be minimal, and approximately every treatment gives comparable outcomes (Hair et al., 2020). Thus, based on the consensus of the researchers and the lesser quantity of missing data in the present study, it may be ignored or resolved using any existing imputation technique. The mean substitution approach was used in this study, which is one of several imputation approaches described by Hair et al. (2020), including hot or cold deck imputation, case substitution, mean substitution, and regression imputation. It is the most widely used or accepted approach for MCAR and normally distributed data. The estimated mean can be the most effective single substitution for any missing value (Hair et al., 2020).

3.18.1 Outliers Investigation According to Kline (2005), an outlier is a case with an extreme value on one variable (a univariate outlier) or a strange combination of scores for two or more variables (a multivariate outlier). Observation(s) vary from others due to their high or low ratings (Hair et al., 2020). As per researchers, outliers can cause data nonnormality and incorrect statistical inferences (Kline, 2005). Incorrect data entry, failure to specify codes for missing values that can be treated as real data, entering an observation which is not a component of the population from which the sample is derived, and including observation from the population when the distribution for the variable in the population has more extreme values than the normal distribution are all

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reasons for the presence of outliers in a dataset, according to researchers (Hair et al., 2020). Kline (2005) classified two forms of outliers, namely univariate outliers, which represent an extreme value on a single variable, and multivariate outliers, which represent an unusual combination of high values in two or more variables. The topic of "extreme values" and their tolerance is not specifically characterised in the literature. Nevertheless, several commonly acknowledged rules of thumb indicate that a case is an outlier among univariate outliers. For instance, the standard score for small sample sizes (80 or less) is 2.5 or higher, but the standard score for big sample sizes is up to 4. A value higher than 3.0 for standard deviations from the mean is considered an outlier (Hair et al., 2020). In the present study, items were aggregated to represent a single variable to find univariate outliers. Using the descriptive statistics feature of Statistical Package for the Social Sciences (SPSS) software, the data value for each observation was transformed into a standardised score, sometimes termed a z-score (Hair et al., 2020). The findings suggest that this data set has few univariate outliers.

3.18.2 Test of Normality Hair et al. (2020) stated that the assumption of normality is viewed as fundamental in multivariate analysis. The assumption is that the data distribution in every item and in all linear combinations of items is normal and referred to as normality (Hair et al., 2020). The resulting statistical tests are erroneous if the deviation from the normal distribution is high enough because normality is required to use the F and t statistics. In addition, the authors noted that a violation of normality in the multivariate analysis might result in underestimating fit indices and standardised residuals of estimates (Hair et al., 2020). Normalcy assumptions can be verified at the

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univariate and multivariate levels (score distribution at the item level) (distribution of scores within a combination of two or more than two items). Hair et al. (2006, p. 80) stated that a variable or item that meets multivariate normalcy also meets univariate normality, although not always the case. The presence of univariate normality does not guarantee the occurrence of multivariate normality. Assessing the degree of non-normality relies on two assumptions: 1) the form of the violating distribution and 2) the size of the sample (Hair et al., 2006, p.80). Tabachnick and Fidell (2007, p. 79) asserted the possibility of determining the shape of a normal distribution using graphical or statistical approaches. Within the graphical technique of inspection, normalcy is determined by examining the histogram of the variable with a symmetrical, bell-shaped curve and a greater frequency of scores in the centre than on the peaks (Hair et al., 2020). The Q-Q plot (also termed the normal probability plot) is a second graphical approach for determining normality that is regarded to be the simplest way (Hair et al., 2020). The Q-Q plot is a graph that compares observed and predicted values. If the points within a Q-Q plot are crowded around a straight line, then the variable is normally distributed (Hair et al., 2020). Skewness and kurtosis are other approaches used to determine the distribution shape (Hair et al., 2020). In contrast to the normal distribution, skewness describes the distribution symmetry, whereas kurtosis describes the 'peakedness' or 'flatness' of the distribution (Field, 2006; Hair et al., 2020). Hair et al. (2020) highlighted that positive skewness indicates a distribution displaced to the left and tapers to the right, while negative skewness indicates the opposite. The recommended value of skewness for the normal distribution is zero, corresponding to a symmetric shape (Hair et al., 2020). The kurtosis in which the distribution is taller or more peaked than average is named 'leptokurtic.' In contrast, the distribution that is flat is labelled 'platykurtic' (Hair et al.,

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2006, p. 80). Moreover, a negative kurtosis value implies a flatter distribution, whereas a positive kurtosis value shows a distribution with peaks (Hair et al., 2020). Hair et al. (2020) outlined homoscedasticity as the assumption of normalcy associated with the premise that the dependent variable(s) have the same variance regardless of the number of independent variables(s). Homoscedasticity is the similarity between the variability of scores for one variable and all other variables. In multiple regressions, the assumption of equal variance across variables is a prerequisite (Hair et al., 2020). Heteroscedasticity is another term for the failure of homoscedasticity within the multivariate analysis and can provide a significant challenge (Hair et al., 2020). Heteroscedasticity is induced by either the existence of non-normality in the independent variable(s) or an increase in measurement error at a certain level (Hair et al., 2020). In data-grouping analyses, homoscedasticity is referred to as homogeneity of variance. Levene's test for equal variance is the most typical approach for evaluating homoscedasticity (Hair et al., 2020). The analysis findings revealed that all variables in this study fell within the typical range of skewness and kurtosis (Hair et al., 2020). Nevertheless, the values for skewness and kurtosis are negative and positive. Negative or positive skewness and kurtosis do not indicate an issue unless they fall beyond the typical range. Besides, negative or positive values of skewness and kurtosis indicate the nature of the examined underlying concept. For instance, the negative skewed score of construct perceived usefulness indicates that more respondents in the sample agree with the acceptance owing to usefulness than disapprove (Hair et al., 2020). Besides the sample size, the degree of normalcy is also dependent on the sample variance. A higher sample size mitigates the detrimental consequences of nonnormality (Hair et al., 2020). In addition, a small sample size (less than 50 instances)

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has a greater impact on normalcy than a large sample size (more than 200 cases). With a manageable sample size of the current investigation, the existence of minimal nonnormal univariate distribution may be avoided (Hair et al., 2020).

3.18.3 Multicollinearity Multicollinearity is the issue associated with the correlation matrix when three or more independent variables are substantially linked (0.90 or greater) to one another (Li et al., 2018). Higher levels of multicollinearity reduce the unique variation described by each independent variable (β-value) and increase the proportion of shared prediction (Li et al., 2018). In simpler words, the existence of multicollinearity restricts the magnitude of the regression coefficient (R) and makes it challenging to comprehend the contribution of each independent variable (Li et al., 2018). In order to improve prediction, it is proposed that one of the highly associated variables be eliminated after a thorough examination (Li et al., 2018). Two of the many methods for determining the degree of multicollinearity are particularly prevalent, namely examining the bivariate and multivariate correlation matrices and computing the variance inflation factors (VIF) and tolerance impact (Li et al., 2018). According to earlier research, the tolerance effect implies that the variability represented by the independent variable is unique (not explained by any other independent variable), while the VIF implies the reverse. The higher VIF (greater than 10) and lower tolerance (less than 0.1) indicate multicollinearity (Li et al., 2018).

3.18.4 Validity and Reliability After reviewing the descriptive characteristics of respondents' demographic data, investigating the manner in which respondents responded to survey questions or

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items connected to the conceptual framework's stated notions is crucial. Examining the survey questionnaire, also termed an evaluation of psychometric characteristics, necessitates an acceptable level of reliability and validity for the measurements (Hair et al., 2020). The term reliability is generally used for two main purposes, namely determining the correlation between the same respondent's score on the same measurement item at two points in time, also known as test-retest reliability (Purwanto & Sudargini, 2021) and assessing the consistency between a number of measurement items measuring a single variable, also known as the split-half method (Afthanorhan et al., 2020). In general, scale reliability permits the precision and consistency of measurements. It eliminates the bias (error-free) associated with the repeatability of measuring devices over a range of samples and time horizons. Cronbach's coefficient technique was chosen for this study from the various statistical approaches for measuring reliability, including Cronbach's coefficient and test-retest (Purwanto & Sudargini, 2021). Cronbach's (inter-item consistency reliability) was chosen because it is more straightforward to compute and widely acknowledged in academic research (Afthanorhan et al., 2020). In general, the minimum acceptable Cronbach's coefficient value is 0.70 (70%). Nevertheless, 0.60 (60%) is also acceptable (Afthanorhan et al., 2020). Despite its popularity and ease of computation, Cronbach's test is inflated by the number of items. It assumes that an increase in the number of items would lead to increases in overall reliability. Hair et al. (2020) stated that the item-to-total correlation (the correlation between the item and the scale's total score) and the interitem correlation might also be used to measure a scale's reliability or internal consistency (the correlation among items). Item-to-total correlation should be at least

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0.50 (50%), and inter-item correlation should be at least 0.30 (30%) (Purwanto & Sudargini, 2021). The findings show that items in all constructs are significantly associated. Cronbach's was also more than the suggested value of 0.6 (Purwanto & Sudargini, 2021), with the exception of constructs. As indicated, the items with lower squared-multiple correlations (SMC) or lower corrected item-total correlation should be deleted to enhance the β-value (Hair et al., 2020). Following the recommendations, items in the construct were required to be deleted to increase the β-value. Nevertheless, they were retained for additional research utilising the EFA technique of convergent validity (Hair et al., 2020). The validity of the measuring scale guarantees that the instrument's results accurately reflect the idea of interest (Hair et al., 2020). A validity test should be able to corroborate already-known notions (Purwanto & Sudargini, 2021). Content and construct validities are the two most popular types of validity tests utilised in social science and business research to determine the quality of an instrument. In contrast, content validity, also termed face validity, is a qualitative evaluation of the link between items and the related concept based on ratings by experts, judges and pre-tests with multiple subpopulations (Afthanorhan et al., 2020). The first step in developing the association between a concept and the measuring items should be to demonstrate the construct's content validity. According to Hair et al. (2020), if a measuring scale lacks content validity, it cannot have construct validity regardless of the results of statistical analysis. In the present study, the researcher gathered items from the literature on information systems using a rigorous analytical procedure to establish content validity (Afthanorhan et al., 2020). The researcher subsequently asked faculty members who were knowledgeable

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about the issue to evaluate the measuring items and indicate whether the items appeared to be logically valid (Hair et al., 2020). As the items related to the constructs were broadly acknowledged in the literature, the experts proposed and implemented minor typographical changes into the final questionnaire. Construct validity refers to the extent to which a group of items measures what it was designed to measure. It is known as an instrument's external validity and is quantified by examining the correlation between a set of theoretically supported measurement items (Hair et al., 2020). The degree to which a set of measuring items is devoid of systematic or non-random error in the context of generalisation is referred to as construct validity (Hair et al., 2020). Similarly, Hair et al. (2020) asserted that construct validity presents evidence that acts as the foundation for intended score interpretation. Construct validity may be assessed using three methods: convergent, discriminant, and nomological validities (Afthanorhan et al., 2020). The researcher's aim at this stage was to assess the general validity of the survey instrument. Hence, only convergent validity was calculated to establish the degree to which measuring items from a similar concept were associated. In the next chapter, the discriminant and nomological validity are determined and elaborated. The convergent validity, sometimes referred to as criterion validity (Afthanorhan et al., 2020), emphasises that measuring items of a certain concept should converge or have a large proportion of variance in common (Hair et al., 2020). In short, it measures the correlation between elements of the same concept (Afthanorhan et al., 2020). For greater convergent validity, the item-to-total correlation is recommended to be above 0.50 (50%) and the inter-item correlation to be above 0.30 (Hair et al., 2020; Afthanorhan et al., 2020). In addition, correlation (r) = 0.10 to 0.29 is a minor correlation, r = 0.30 to 0.49 is a medium correlation, and r =

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0.50 to 1.00 is a high correlation. By utilising the partial least squares structural equation modelling (PLS-SEM) reliability test, a correlation was estimated in the current study. Except for SEM, the inter-item correlation for all constructs was between moderate and high. Until this point in the study, items with correlations below the minimum threshold were maintained for further examination through EFA (Hair et al., 2020).

Structural Equation Modelling (SEM) The introduction of SEM with latent variables altered the character of research in a variety of fields. Since pioneering works on maximum likelihood factor analysis and subsequent applications to the estimation of structural equation systems, SEM has established itself as a fundamental approach for empirical research. The approach has been widely employed in management, marketing, and psychology (Hair et al., 2017). Currently, two broad methods of SEM exist, namely covariance-based structural equation modelling (CB-SEM) implemented in the analysis of a moment structures (AMOS), linear structural relations (LISREL), and equation modelling software (EQS), and variance-based structural equation modelling also, termed partial least squares (PLS) (Hair et al., 2017). The CB-SEM is focused on estimating model parameters. Hence, the theoretical covariance matrix indicated by the set of structural equations is as similar to the empirical covariance matrix visible within the fitted model as feasible. When fitting with maximum likelihood, a number of assumptions must be met. For instance, the observed indicators have a multivariate normal distribution, and the sample size is appropriate. If the assumptions are not met, PLS-SEM (Hair et al., 2017) may be an appropriate alternative for researchers. Contrasting to CB-SEM, PLS-SEM analysis

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does not need the fulfilment of any distributional assumptions and is capable of providing strong and accurate fits for relatively small sample sizes (Hair et al., 2017).

3.19.1 PLS-SEM vs CB-SEM Comparison Gefen et al. (2000) pointed out that the CB-SEM technique varies in numerous ways from the PLS-SEM approach. These techniques differ in their assessments of their aims, the underlying statistical assumptions, and the characteristics of the fit statistics they provide (Hair et al., 2017). The CB-SEM commonly employs a maximum likelihood function to minimise the variation between the sample covariance and the theoretical model's projected covariance. In comparison, the PLSSEM method seeks to minimise the variance of all dependent variables rather than attempting to explain the covariance (Hair et al., 2017). Rigdon et al. (2017) conducted a comparative analysis using CB-SEM and PLS-SEM for the purpose of modelling customer satisfaction data. The authors compared the two estimate approaches containing several latent variables as a baseline for the analysis. This simulation was used to assess each method's ability to predict the inner model coefficients and indicator loadings accurately. Their findings indicated that PLS-SEM estimations are typically more accurate and precise than CB-SEM estimates (Rigdon et al., 2017). Afthanorhan et al. (2020) undertook a similar analysis, including Monte Carlo simulations. They examined the influence of various design parameters on the accuracy of route prediction using PLS-SEM and CB-SEM. The following parameters influenced the design, namely the estimating technique (PLS-SEM vs AMOS), sample size, the number of measurement items per construct, and correlations across independent constructs. Their findings indicated that the PLS-SEM yielded better

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accurate regression coefficient estimations when sample sizes were less and measurements per latent variable were fewer than four (Afthanorhan et al., 2020). The CB-SEM estimates failed more frequently when sample sizes were fewer than 100 and data distribution was severe. Only two measurements were available for each latent variable. Generally, the shortcomings of PLS-SEM outweigh covariance-based and SEM positives, and vice versa (Afthanorhan et al., 2020). The current study is motivated by the previously described benefits of PLS-SEM. The growing body of PLS-SEM research in management and marketing has also affected the choice to utilise PLS-SEM. It works with considerably smaller and much larger samples than CB-SEM. This study explores the influence of small and large samples to assist researchers in coping with missing data challenges caused by small sample sizes (Rigdon et al., 2017). In general, PLS-SEM can be a viable substitute for CB-SEM when the following features are present. For example, the phenomenon under investigation is novel, necessitating the development of novel measuring methods. The structural equation model is sophisticated, containing a high number of latent and indicator variables (Hair et al., 2017). The relationships between latent variables and indicators must be modelled in a variety of ways (Hair et al., 2017). The sample size, independence, or normal distribution criteria are not fulfilled, and prediction takes precedence over parameter estimation. Regardless of how flexible PLS-SEM is, CB-SEM is a highly established technique with well-documented goodness of fit (GoF) measures and higher parameter accuracy. Thus, CB-SEM is usually accepted for rigorous model validation purposes (Afthanorhan et al., 2020). Although technique comparisons demonstrate superior behaviour of PLS-SEM due to

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its distribution-free nature, CB-SEM can employ alternate distribution-free approaches, such as Asymptotic Distribution Free (ADF) model fitting (Hair et al., 2017). Both systems have distinct advantages and disadvantages, making them suitable for different contexts. Therefore, researchers should undertake a thorough analysis of the study's design and sample characteristics before deciding on either technique (Hair et al., 2017). Occasionally, using both PLS-SEM and CB-SEM is also feasible, and the findings are frequently quite comparable. Comprehensive data are necessary, and where data are insufficient, modifications must be made to the data set, either by removing or imputation of values. On the other hand, incomplete or missing data is a frequent occurrence in structural equation issues. Therefore, researchers must be aware of the best accessible alternatives for resolving data gaps in their study. Although experiments and surveys are tightly controlled, missing data problems are unavoidable and can negatively influence data interpretations or models developed from the data (Hair et al., 2017). Additionally, such issues might result in an erroneous assessment of variability (variance and standard deviation) (Hair et al., 2017). Previously conducted studies examined the efficacy of statistical approaches for missing data handling in CB-SEM (Afthanorhan et al., 2020). Nevertheless, neither CB-SEM nor PLS-SEM have been documented to employ computational intelligence methods of data imputation to estimate missing data for SEM (Afthanorhan et al., 2020). The majority of the literature on partial data in SEM has been on CB-SEM (Hair et al., 2017). A dearth of literature exists on component-based SEM (Hair et al., 2017). Rezaei and Valaei (2018) showed how the maximum livelihood technique in CB-SEM addresses the missing data problem. Unfortunately, the machine learning process is impractical unless the data set comprises only several different missing data

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patterns (Rigdon et al., 2017). A high level of technical competence is necessary for the application of machine learning, especially when the data is inadequate. At least two CB-SEM tools (such as AMOS) provide machine learning estimates with missing data (Afthanorhan et al., 2020). Strategies for dealing with missing data in the general multivariate situation include assessing the performance of approaches for dealing with missing data in CB-SEM programmes using Monte Carlo simulation. Both studies were critical of pairwise deletion and the listwise deletion methods, highlighting skewed and inefficient estimates and an increased likelihood of producing indefinite sample covariance matrices, but offered no alternative (Trichtinger, 2021). Zhang et al. (2021) investigated five strategies for calculating the CB-SEM when missing data was present in varying degrees. These approaches included pairwise deletion and the listwise deletion methods, mean substitution, hot-deck imputation, and comparable response imputation. Similar observations were identified, and values were copied to fill in the gaps. They concentrated on deletion and imputation approaches, claiming that the maximum likelihood method was inapplicable in a wide variety of scenarios. Rigdon et al. (2017) conducted simulation research using a structural model with a design that included two sample sizes and different levels of missing data. Assuming that data were randomly absent, the collection of instances containing values for all variables was a random subsample of the original population. Little et al. (2014) empirically showed that listwise deletion produced unbiased estimators for all parameters. On the other hand, the pairwise deletion means substitution and hot-deck imputation resulted in significant bias in the structural and measurement model parameters. Brown's (1990) findings corroborated previous prior regression model studies (Little et al., 2014). Due to the loss of examples, the listwise

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deletion technique produced the greatest standard errors and a lower overall model fit. Brown's (1990) study concluded that the appropriateness of listwise deletion should be judged by the original sample size and the quantity of data lost as a result of its application. His work cast doubt on the use of mean substitution and hot-deck imputation in CB-SEM, claiming that they performed worse than comparable pattern imputation approaches. Brown (1990) continued by mentioning that there were several alternative ways that looked to be promising for coping with missing data in CB-SEM, most notably the use of the expectation-maximisation algorithm. Hair et al. (2017) conducted a simulation analysis to bolster their claim for resolving missing values in CB-SEM using the Full Information Maximum Likelihood technique. As a co-author of AMOS, the widely used CB-SEM programme, the authors were instrumental in including this approach into the package. Hair et al. (2017) suggested that it is unnecessary to impute values for missing data or to estimate population moments prior to fitting models using machine learning. In conclusion, it can be claimed that estimation with partial data is viable and should be favoured over pairwise deletion or listwise deletion when only pairwise deletion or listwise deletion is available. Moreover, when working with missing data, the SEM approach is utilised collaboratively with CB-SEM, applying statistical techniques that are not covered by AMOS. An actual imputation approach, such as multiple imputations (MI), would allow the missing data to be replaced. Researchers might subsequently utilise the imputed data sets to conduct the processes they desire in their preferred statistical programmes (such as Statistical Analysis System (SAS) or SPSS). Additionally, they discovered that mean substitution produced skewed results, which impacted the structural model's conclusions (Hair et al., 2017). Although Monte Carlo studies have been utilised in the past to assess

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missing data approaches, the merits of highly contemporary and theoretically sound computational intelligence methods for managing missing data for SEM applications have not been investigated. The performance of the approaches utilised in this study is examined using PLS-SEM in terms of their capacity to generate values close to the good values while dealing with two forms of missing data (Hair et al., 2017). The PLS-SEM technique is a variance-based technique for data screening and structural model validation (Becker et al., 2018). There has been a continuous growth in the number of published studies utilising PLS-SEM in some business areas (Hair et al., 2022). Since 1987, more than 20 studies utilising PLS-SEM have been published in five peer-reviewed marketing journals, with most of them published in the last six years. The PLS-SEM technique is the dominant approach for estimating the different national customer satisfaction index models and for marketing success factor analyses (Hair et al., 2017). Becker et al. (2018) claimed that PLS-SEM was better suited to explaining the complex relationship. This method might be chosen over a CB-SEM since the study's objective was theory creation rather than theory testing. Thus, PLS-SEM can be used for data analysis when the study model includes both reflecting and formative dimensions with a modest sample size (Hair et al., 2017). Becker et al. (2018) provided evidence of the growing popularity of PLS-SEM among marketing researchers. Numerous researchers have stated that the objectives of their studies align with the inherent capabilities of PLS-SEM. Afthanorhan et al. (2020) asserted that PLS-SEM is capable of successfully testing and verifying exploratory models. They employed a PLS-SEM model to predict behaviours. Hajipour (2010) used PLS-SEM to examine the correlations between three dimensions of new product market entrance strategy (order, positioning, and size) and

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four variables of performance (competitive position, customer satisfaction, and profitability). They highlighted that PLS-SEM is capable of handling both reflecting and formative measurement methods. Many research forecasted market performance using a PLS-SEM due to the sample size of the study, claiming that PLS-SEM is highly resilient than CB-SEM with small sample sizes (Hair et al., 2022). Utilising a PLS-SEM model to examine behaviours that account for the high number of variables and complicated correlations present is advisable (Hair et al., 2022). Based on the above highlights concerning the breadth and relevance of PLS-SEM for business and management, the use of PLSSEM as the focal point for the current examination of missing data is justified. These applications fall under three broad business and management disciplines: marketing, strategic management, and information systems. The PLS-SEM technique was selected for this study as the approach has been shown to be particularly beneficial during the early creation and assessment phases of theory development (Afthanorhan et al., 2020).

3.19.2 The Algorithm of PLS-SEM A preparation step, an iterative main procedure, and a final phase make up the PLS-SEM method. All variables are normalised in the first phase to ensure that the findings can be easily comprehended, and the main operation may employ simpler computations (Becker et al., 2018). There are two steps in the primary operation. The outside approximation is the initial stage, which estimates all latent variables as weighted aggregates of manifest variables. This estimation is accomplished in the first iteration by assigning equal weights to each block of indicators (Hair et al., 2017).

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For each of the examples, latent variable scores are produced using these weights. After iterations are undertaken, more suitable weights are calculated based on empirical data and proxies for all latent variables produced in the previous stage. Ordinary least squares regression is used to compute the weights. The second stage lies within approximation. Approximation develops proxies for each endogenous latent variable based on its connection with other latent variables (Becker et al., 2018). Ordinary least squares regression is applied one more time. As for the following iteration of this combination of inside and outside approximations, the outcomes of this regression are new latent variable proxies (Hair et al., 2017). For example, when the preceding iteration did not result in a significant improvement in the latent variable estimates, the algorithm converges. Factor loadings, regression coefficients, and validation measures are generated in the last step of the procedure. The user may obtain weights for all formative indicators, loadings for all reflective indicators, and coefficients (standardised regression coefficients) for all latent variable routes using the procedure (Becker et al., 2018). The evaluation of model structures is based on a number of factors. A systematic application of the various criteria is undertaken in two steps: (1) the measurement model assessment and (2) the structural model assessment. Reflective and formative measurement models have been separated to examine the measurement models (Hair et al., 2017).

3.19.3 Evaluation of Measurement Model Models of Reflective Measurement Evaluation A latent variable's unidimensionality refers to the fact that each of its measurement items relates to it better than any other latent variable (Becker et al., 2018). An EFA can be used to examine a latent variable's unidimensionality. The goal

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of EFA is to identify if the measuring items are convergent with the related constructs (factors). If the loading coefficient is greater than 0.6, the item loading is regarded as high. Contrarily, if the coefficient is less than 0.4, the item loading is considered low (Hair et al., 2017). Cronbach's alpha and composite reliability are two conventional criteria for evaluating internal consistency dependability (Henseler, 2010). As Cronbach's alpha implies that all indicators are equally trustworthy, the internal consistency reliability of latent variables in PLS-SEM is frequently underestimated (Hair et al., 2017). Contrarily, composite reliability considers the fact that indicators have various loadings (Hair et al., 2017). An internal consistency reliability value of greater than 0.7 in the early phases of research, and greater than 0.8 in later stages, is deemed excellent. Nevertheless, a value of less than 0.6 suggests a weak contribution to the construct (Hair et al., 2017). The amount of variation explained by the associated latent variable is measured by indicator reliability (Hair et al., 2017). In order to measure the reliability of each indicator, the researcher can track the loadings of reflective indicators. In general, a latent variable is thought to explain at least 50% of the variation in each indicator (Hair et al., 2017). As a result, indicator loadings should be more than 0.7 and substantially different from zero, at least at the 0.05 level (Chin, 2010). The degree to which individual items load onto their specified concept is known as convergent validity. The average variance extracted (AVE) developed by Fornell and Larcker is a widely used criterion for convergent validity (Hair et al., 2017). A significant convergent validity score of at least 0.5 proposes that a latent variable can explain at least half of the variation of its indicators on average (Hair et al., 2017).

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Finally, discriminant validity refers to how different various concept measurements are from one another. Two metrics of discriminant validity are typically utilised in PLS-SEM. Cross loadings are calculated by associating the component scores of each latent variable with each of the indicator variables for the first measure (Hair et al., 2017). Suppose each indicator's loading is greater for its assigned build than for any component score of the other constructs, and each construct loads the most with its allocated items. In that case, it may be determined that the construct indicators are not interchangeable. The Fornell-Larcker criteria state that a latent variable must share more variation than any other latent variable with its assigned indicators (Hair et al., 2017). As a result, the AVE of each latent variable should be larger than the greatest squared correlation of the latent variable with any other latent variable (Hair et al., 2017). Validation of formative measurement models necessitates a diverse methodology than that of reflecting measurement models. Henseler (2010) proposed evaluating the validity of formative conceptions on two levels, namely indicator validity and construct validity. In order to determine the indicator level, the researcher should use bootstrapping or jackknifing to track the significance of the indicator weights (Hair et al., 2017). A significance level of at least 0.05 indicates that an indicator is significant to the creation of the formative index and has sufficient validity. Furthermore, the VIF should be calculated to determine the degree of multicollinearity among the formative indicators (Hair et al., 2017). The VIF shows how much the variance of the indicator may be explained by other indicators in the same construct. Multicollinearity is not a concern if the value is less than the usually recognised threshold of 10 (Hair et al., 2017).

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A test for nomological validity might be the initial step in determining the construct level. In this situation, nomological validity indicates that the formative concept performs as predicted inside a net of hypotheses (Hair et al., 2017). The links between the formative construct and the remaining model constructs (which have been adequately discussed in previous studies) should be solid and substantial. If the correlations between formative and all other constructs are less than 0.7, the construct stands apart from the others (Hair et al., 2017).

3.19.4 The Evaluation of the Structural Model The structural model can be examined when the measurement model has been properly validated. The coefficient of multiple determinations (R2) for every endogenous component is the first and most crucial criterion for evaluating the PLSSEM. Besides, R2 is a measure of a latent variable's explained variance in relation to its overall variance. It is well-acknowledged that R2 values of 0.6, 0.3, and 0.2 in PLSSEM path models are described as considerable, moderate, and weak, respectively (Hair et al., 2017). The examination of the regression coefficients between the verified latent variables is the subsequent stage in evaluating the structural model. The regression coefficient algebraic signs, magnitudes, and significances should all be checked by the researcher (Hair et al., 2017). The associated research hypotheses are not supported by paths whose signals are opposite to the theoretically hypothesised relationship. The size of a regression coefficient reveals how strong the association between two latent variables is. In order to account for a substantial influence inside the model, some scholars proposed that regression coefficients should be greater than 0.1 (Hair et al., 2017). Path coefficients should also be statistically significant at the 0.05 level (Hair

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et al., 2017). Resampling approaches such as bootstrapping are commonly employed to establish the significance (Hair et al., 2017). Finally, another aspect of the structural model is to evaluate its capacity to make predictions. The Stone-Q2 Geisser's statistic, which may be calculated via blindfolding techniques, is utilised to assess the predictive significance of the structural model (Hair et al., 2017). Only once the model has been verified the findings obtained by the PLS-SEM method can be interpreted. As a result, the structural model's hypotheses may be classified as either verified or rejected. Subsequently, the researcher can address the relevant research questions, deduce the findings, and draw implications for theory and practice (Hair et al., 2017). Finally, it is possible to determine the necessity for in-depth future studies (Hair et al., 2017).

Ethical Considerations Clark-Kazak (2017) proposed that in a study involving human subjects, researchers should address ethical issues. Since the current study included human participants, the researcher took ethical factors into account. The notion of informed consent was the first ethical concern. The researcher explained the study's goal to the participants and how the data will be utilised. The researcher also reminded participants that their participation in the study was entirely optional and that they may opt out at any time, either verbally or in writing. Besides that, the researcher assured the participants that their withdrawal from the study would have no effect on them in any manner. While conducting this study, the researcher attempted to adhere to the ethical standards of academic research. The researcher acquired the permission of Malaysian SME owners before distributing the questionnaire.

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Before the participants agreed to take part in the data collection process, the researcher outlined the study's aim and purpose, including information and data storage. The survey was only distributed to the owners and executives who agreed to participate. Additionally, the researcher verified that no private and personal questions or identifying questions were included in the survey. Responses were safeguarded in accordance with the Data Protection Act. The collected data were only utilised for this study. Lastly, in order to avoid plagiarism, the researcher has given proper acknowledgement to the academics whose works were referred to complete the study through in-text citations and a reference list.

Summary This chapter has established the methodological framework and components that the researcher utilised to analyse the function of coaching and training in boosting Malaysian SMEs' performance in the context of RichWorks International's coaching and training services. Moreover, the chapter also discussed why several methodological framework components were chosen while others were rejected, resulting in the following methodology: a pragmatic research philosophy, a deductive research approach, a descriptive research design, primary data collection through a survey, and quantitative data analysis. The chapter also discussed the potential implications of the study's methodological framework. The discussion of PLS-SEM, which has grown more popular in various domains, has been addressed in this chapter. A discussion concerning the differences between PLS-SEM and covariance-based methods to SEM has also been undertaken. The PLS-SEM method is described in detail, and a framework for empirical research using PLS-SEM is supplied. The chapter also included a summary of works that used PLS-SEM in a variety of settings.

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Finally, the final section reviewed past research that provided examples of the ways to deal with missing SEM data.

Capability of the Researcher The aptitude and credentials of the researcher have a significant impact on the quality and efficacy of academic research. The researcher's qualifications and capability are important aspects because the amount to which the researcher may use his or her competencies or abilities determines the efficient completion of the various phases or procedures linked with the study. The researcher must have the necessary competencies or capacities to conduct the research. In the specific setting of my academic research, I utilised my diverse abilities and competencies to complete my research successfully. For example, as one of RichWorks International's Master Business Coaches, I have almost ten years of expertise in the field. As a result, I have an in-depth understanding of how the concerned organisation provides training and coaching services and its critical attributes. These advantages positioned me in the greatest situation possible to conduct the study discussed here. Along with the understanding of the company under evaluation, I also have the necessary experience and competencies to undertake this academic study. For example, my past expertise in performing academic research has really aided me in finishing my research project and thesis successfully. In particular, I believe that my data analysis abilities, which I have refined in previous research, assisted me in efficiently collecting and analysing the data essential for the successful completion of this particular research. To summarise, I also acknowledge that I have the sufficient skills, knowledge, competencies, and capacities required to complete this academic study successfully.

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CHAPTER 4 RESEARCH FINDINGS

Introduction This chapter outlines a summary of the study's findings as per the results of the data analysis. The present study aimed to analyse the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia. The results of normality analysis, outlier detection, reliability, and validity were discussed in this chapter. The researcher employed SEM to analyse the structural relationships in the present study.

Demographic Characterisation of the Respondents 4.2.1 Response Rate The researcher selected and contacted more than 430 respondents to participate in the study. After checking the responses, 361 completed datasets were chosen to be analysed. Figure 4.1 shows the response rate according to gender.

Gender Male

Female

42% 58%

Figure 4.1: Respondents' gender 178

The results presented in Figure 4.1 reveals that male respondents accounted for the highest proportion of respondents with 58%. On the other hand, female respondents accounted for 43%. These results indicated that more men had undergone business coaching in Malaysian SMEs than women.

4.2.2 Age The respondents' age is displayed in Figure 4.2 below.

Age 18-25 years

26-35 years

36-45 years

46-55 years

Above 55 years

3% 3% 18%

36%

40%

Figure 4.2: Respondents' age

The results presented in Figure 4.2 indicate that most of the study's respondents, or 40%, were aged between 36 to 45 years old, followed by respondents aged from 26 to 35 years old (36%). Additionally, 18% of the study's respondents were aged 46 to 55 years old. The remaining respondents were from 18 to 25 years old (3%) and above 55 years old (3%) age groups.

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4.2.3 Highest Level of Education

Highest Level of Education Skills Certificate / Certificates/ Another Matriculation / Foundation / A-Level /STPM Certificate 16 Diploma 79 Bachelor’s Degree 139

Master’sDegree 35 PhD Degree 7 10%

2%

24% 0%

41%

23%

Figure 4.3: Respondents' highest level of education

The pie chart in Figure 4.3 illustrates that 24% of the study's respondents possessed a skills certificate/ certificates/ other forms of qualifications. Besides, 23% of the study's respondents have a PhD degree, followed by 21.9% of respondents who had a diploma. Another 10% of respondents held a master's degree.

Test of Normality Kurtosis and skewness statistics have been utilised to undertake the normalcy test of data distribution. This study utilised SPSS version 24.0 for Windows to conduct these tests. First, the most commonly employed kurtosis and skewness test critical values are between -2.58 to +2.58 (Hair Jr et al., 2020). The kurtosis test validates the data's normal distribution, whereas the skewness test describes the distribution's balance (Hair et al., 2020). The kurtosis and skewness tests revealed that all variables in this investigation were normally distributed (Refer to Table 4.1). 180

Table 4.1: Normality test

Motivation1 Motivation2 Motivation3 Motivation4 Motivation5 Productivity1 Productivity2 Productivity3 Productivity4 Productivity5 Job_Satisfaction1 Job_Satisfaction2 Job_Satisfaction3 Job_Satisfaction4 Job_Satisfaction5 Innovation1 Innovation2 Innovation3 Innovation4 Innovation5 Business_Innovation 1 Business_Innovation 2 Business_Innovation 3 Business_Innovation 4 Business_Innovation 5 Comp_Advantage1 Comp_Advantage2 Compe_Advantage3 Comp_Advantage4 Comp_Advantage5 High_Imp_Growt1 High_Imp_Growt2 High_Imp_Growt3 High_Imp_Growt4 High_Imp_Growt5

No.

Missing

Mean

Median

Standard Deviation

Excess Kurtosis

Skewness

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

3.387 2.499 2.473 2.224 2.333 3.092 3.185 3.042 2.521 3.146 3.569 3.787 3.86 3.882 4.011 3.947 3.577 3.725 3.616 3.818 2.487

4 2 2 2 2 3 3 3 2 3 4 4 4 4 4 4 4 4 4 4 2

0.783 1.089 0.98 0.69 0.709 0.99 0.938 0.926 0.842 1.021 1.279 0.907 0.871 0.939 0.889 0.86 1.211 1.03 1.131 1.146 0.835

0.195 0.07 0.071 4.389 2.256 -0.895 -0.585 -0.805 -0.59 -0.682 -1.083 0.396 0.628 0.553 0.708 0.441 -0.565 0.103 -0.571 -0.046 -0.214

-0.764 0.847 0.406 1.828 1.552 -0.013 -0.417 0.341 0.047 -0.169 -0.38 -0.697 -0.796 -0.842 -0.888 -0.773 -0.362 -0.587 -0.372 -0.501 1.169

29

0

3.3

3

0.811

-0.598

-0.284

30

0

2.583

3

0.893

-0.58

0.069

31

0

2.852

3

0.928

-0.678

-0.42

32

0

3.339

4

1.007

-0.548

-0.471

33 34 35 36 37 38 39 40 41 42

0 0 0 0 0 0 0 0 0 0

3.426 3.16 3.695 3.434 3.473 1.709 2.611 2.975 2.44 2.493

4 3 4 4 4 1 2 3 2 2

0.826 0.99 0.681 0.975 0.945 1.132 1.03 0.801 0.778 0.773

-0.037 -0.489 0.112 -0.266 -0.283 0.473 -0.668 0.202 1.531 0.23

-0.602 -0.22 -0.329 -0.596 -0.533 1.37 0.341 -0.086 1.421 1.011

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Outlier Detection In the multivariate studies, the Mahalanobis distance is used to determine the distance between two points (Leys et al., 2018). Variables are represented by axes drawn at right angles to each other in normal Euclidean space. The distance between any two points may be measured (Leys et al., 2018). The Mahalanobis distance equals the Euclidean distance for uncorrelated variables. Nevertheless, when two or more variables are linked, the axes are no longer at right angles, making ruler measurements impossible. Furthermore, if there are more than three variables, the researcher will be unable to plot them in conventional 3D space (Leys et al., 2018). As it measures distances between locations, including correlated points for several variables, the Mahalanobis distance addresses this measurement challenge. Multivariate outliers arise as a mixture of scores on two or more factors, and multivariate approaches can compensate for the bivariate outliers' flaws (Leys et al., 2018). Hair et al. (2020) stated that multivariate outliers might be discovered using Mahalanobis D2 measurement. The approach can measure the distance of each in multidimensional space. Outliers can be identified by this test if the D2/df (degree of freedom) value surpasses 2.5 in small samples (80 or fewer observations) and 3 or 4 in large samples (Hair et al., 2020). As per Hair et al. (2010), the present study used a graphical tool called a box plot to locate univariate outliers and Mahalanobis D2 measurement to find multivariate outliers and establish their influence on the study's objectives. As a consequence, the Mahalanobis distance test identified three univariate outliers (indicated with an asterisk) (Refer to Table 4.2). As a result, three outliers were left out of this study.

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Table 4.2: Outlier detection test Mahalanobis' Distance 29.93548 30.02735 39.93745

Probability 0.00000 0.00000 0.00000

Test of Linearity The direct connection between variables is referred to as linearity. Multivariate approaches such as multiple regression, logistic regression, factor analysis, and SEM are based on co-relational measures of association, but linearity is an implicit assumption in all of them (Moosavi & Ghassabian, 2018). Therefore, evaluating the linear relationship between variables is crucial because non-linear effects cannot be represented by the correlation value (Moosavi & Ghassabian, 2018). Pearson's correlations or a scatter plot can be used to calculate linearity in statistics (Hair et al., 2020). The linearity test was used in this investigation, which was undertaken with SPSS software. The results show that all independent variables have a substantial and positive correlation with the dependent variable, with considerable linearity (p-value < 0.05) (Refer to Table. 4.3). The findings also reveal that the p-values for divergence from linearity are more than 0.05, indicating that the associations are linear.

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Table 4.3: Test of linearity

Motivation

Between (Combined) Groups Linearity Deviation from Linearity Productivity Between (Combined) Groups Linearity Deviation from Linearity Job Between (Combined) Satisfaction Groups Linearity Deviation from Linearity Innovation Between (Combined) Groups Linearity Deviation from Linearity Business Between (Combined) Innovation Groups Linearity Deviation from Linearity High Between (Combined) Impact Groups Linearity Growth Deviation from Linearity Competitive Between (Combined) Advantage Groups Linearity Deviation from Linearity

Sum of Mean df F Squares Square 23.343 23 3.377 10.259 34.564 21 88.723 299.720

0.000 0.000

56.555

23

.755

2.396

0.300

60.646 62.462

34 44

3.556 47.892

9.711 299.071

0.000 0.000

66.756

34

.712

2.291

0.090

16.698 12.339

45 1

2.525 23.759

7.150 257.092

0.000 0.000

32.833

44

.519

1.470

0.710

47.049 10.144

34 1

3.736 10.120

13.734 401.192

0.000 0.000

34.834

21

.542

1.993

0.102

14.645 44.423

23 1

3.385 94.523

9.889 275.870

0.000 0.000

55.245

32

.540

1.577

0.132

50.648 52.342

29 25

2.525 34.479

401.192 1.993

0.000 0.000

34.434

1

.519

9.889

0.303

13.616 90.779

22 34

19.736 34.525

265.660 321.192

0.000 0.000

22.837

1

90.779

1.955

0.302

Sig.

Multicollinearity Multicollinearity can occur when two or more independent variables have a significant association (Li et al., 2018). As a result, measurement is required to describe how each independent variable is influenced by the set of other independent 184

variables (Hair et al., 2017). The VIF and tolerance value are two methods for determining multicollinearity. The VIF was used to test for multicollinearity among variables. In order to prevent a multicollinearity problem, the VIF value of each construct should be less than 5. In ideal circumstances, the VIF should be less than 10 (Hair et al., 2017). If an independent variable has a strong linear connection with other variables, the VIF demonstrates it. If the VIF value is more than 10, the variables have a major issue (Hair et al., 2017). Furthermore, if the tolerance value is less than 0.1, it indicates an issue (Li et al., 2018). As a result, SPSS that provides collinearity diagnostics employed by VIF and tolerance value was utilised to investigate multicollinearity in this study. As per the study's findings, the VIF value of all variables was less than 10, and the no tolerance value was less than 0.1. Hence, the VIF and tolerance were utilised to assess multicollinearity. There is a problem with multicollinearity if the VIF value is more than 4.0 or the tolerance is less than 0.2. Nevertheless, if the value of VIF is less than 10, it is acceptable (Li et al., 2018). The researcher does not have to be concerned about multicollinearity in this study (Refer to Table 4.4).

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Table 4.4: Multicollinearity test results Factor Business_Innovation1 Business_Innovation2 Business_Innovation3 Business_Innovation4 Business_Innovation5 Competitive_Advantage1 Competitive_Advantage1 * Business_Innovation1 Competitive_Advantage1 * Business_Innovation2 Competitive_Advantage1 * Business_Innovation3 Competitive_Advantage1 * Business_Innovation4 Competitive_Advantage1 * Business_Innovation5 Competitive_Advantage1 * Innovation1 Competitive_Advantage1 * Innovation2 Competitive_Advantage1 * Innovation3 Competitive_Advantage1 * Innovation4 Competitive_Advantage1 * Innovation5 Competitive_Advantage1 * Job_Satisfaction1 Competitive_Advantage1 * Job_Satisfaction2 Competitive_Advantage1 * Job_Satisfaction3 Competitive_Advantage1 * Job_Satisfaction4 Competitive_Advantage1 * Job_Satisfaction5 Competitive_Advantage1 * Motivation2 Competitive_Advantage1 * Motivation3 Competitive_Advantage1 * Motivation4 Competitive_Advantage1 * Motivation5 Competitive_Advantage1 * Productivity1 Competitive_Advantage1 * Productivity2 Competitive_Advantage1 * Productivity3 Competitive_Advantage1 * Productivity4 Competitive_Advantage1 * Productivity5 Competitive_Advantage3 Competitive_Advantage3 * Business_Innovation1 Competitive_Advantage3 * Business_Innovation2 Competitive_Advantage3 * Business_Innovation3 Competitive_Advantage3 * Business_Innovation4 Competitive_Advantage3 * Business_Innovation5 Competitive_Advantage3 * Innovation1 Competitive_Advantage3 * Innovation2 Competitive_Advantage3 * Innovation3 Competitive_Advantage3 * Innovation4 Competitive_Advantage3 * Innovation5 Competitive_Advantage3 * Job_Satisfaction1 Competitive_Advantage3 * Job_Satisfaction2

VIF 1.042 1.230 1.240 1.148 1.224 1.081 1.235 1.370 1.344 1.200 1.422 1.249 2.263 2.081 1.584 1.427 1.361 1.868 1.911 1.680 1.307 3.583 1.293 3.079 2.335 2.539 1.453 1.606 1.573 1.402 1.062 1.269 1.714 1.554 1.256 1.547 1.311 2.565 1.913 2.208 1.663 1.189 1.594 186

Factor Competitive_Advantage3 * Job_Satisfaction3 Competitive_Advantage3 * Job_Satisfaction4 Competitive_Advantage3 * Job_Satisfaction5 Competitive_Advantage3 * Motivation2 Competitive_Advantage3 * Motivation3 Competitive_Advantage3 * Motivation4 Competitive_Advantage3 * Motivation5 Competitive_Advantage3 * Productivity1 Competitive_Advantage3 * Productivity2 Competitive_Advantage3 * Productivity3 Competitive_Advantage3 * Productivity4 Competitive_Advantage3 * Productivity5 Competitive_Advantage5 Competitive_Advantage5 * Business_Innovation1 Competitive_Advantage5 * Business_Innovation2 Competitive_Advantage5 * Business_Innovation3 Competitive_Advantage5 * Business_Innovation4 Competitive_Advantage5 * Business_Innovation5 Competitive_Advantage5 * Innovation1 Competitive_Advantage5 * Innovation2 Competitive_Advantage5 * Innovation3 Competitive_Advantage5 * Innovation4 Competitive_Advantage5 * Innovation5 Competitive_Advantage5 * Job_Satisfaction1 Competitive_Advantage5 * Job_Satisfaction2 Competitive_Advantage5 * Job_Satisfaction3 Competitive_Advantage5 * Job_Satisfaction4 Competitive_Advantage5 * Job_Satisfaction5 Competitive_Advantage5 * Motivation2 Competitive_Advantage5 * Motivation3 Competitive_Advantage5 * Motivation4 Competitive_Advantage5 * Motivation5 Competitive_Advantage5 * Productivity1 Competitive_Advantage5 * Productivity2 Competitive_Advantage5 * Productivity3 Competitive_Advantage5 * Productivity4 Competitive_Advantage5 * Productivity5 High_Imp_Growt1 High_Imp_Growt2 High_Imp_Growt4 High_Imp_Growt5 Innovation1 Innovation2 Innovation3 Innovation4

VIF 1.432 1.677 1.192 2.984 1.156 2.558 2.039 2.596 1.718 1.690 1.364 1.520 1.022 1.095 1.196 1.269 1.156 1.308 1.204 2.013 1.769 1.443 1.521 1.096 1.568 1.366 1.556 1.133 2.915 1.171 2.632 1.688 3.072 1.898 1.370 1.467 1.471 1.111 1.203 1.475 1.580 1.126 1.980 1.590 1.621 187

Factor Innovation5 Job_Satisfaction1 Job_Satisfaction2 Job_Satisfaction3 Job_Satisfaction4 Job_Satisfaction5 Motivation2 Motivation3 Motivation4 Motivation5 Productivity1 Productivity2 Productivity3 Productivity4 Productivity5

VIF 1.449 1.056 1.442 1.350 1.499 1.159 2.727 1.002 2.484 1.988 2.515 1.626 1.512 1.360 1.356

Reliability and Validity Confirmatory factor analysis (CFA) was used in Smart PLS to determine the measurement's reliability and validity (Hair et al., 2020). The CFA has a cut-off score of 0.60 (Hair et al., 2020), while other studies contend that the value should be no less than 0.70 (Hair et al., 2020). The researcher maintained the components with a value of 0.60 for additional study in order to determine the complete influence on all indicators. As suggested, each construct has a Cronbach's alpha value of more than 0.60, indicating internal consistency (Hair et al., 2020). Additionally, the composite dependability ratings are above the 0.70 cut-off point (Hair et al., 2020). As per researchers' suggestion, composite reliability is considered to be a more rigorous evaluation of reliability (Hair et al., 2020). Each construct's AVE was more than 0.5 (Bagozzi et al., 1988), hence, establishing convergent validity. The cut-off values for Dijkstra-Henseler (Rho A) coefficients were all greater than 0.7, providing more evidence for composite reliability (Hair et al., 2013). The reliability and validity tests are summarised in Table 4.5.

188

Table 4.5: Test results for reliability and validity Cronbach's Alpha Employee Motivation Business Model Innovation CA*BMI CA*Innov CA*JS CA*PR CA*EM Competitive Advantage High-Impact SME Growth Innovation Job Satisfaction Productivity

rho_A

Average Composite Variance Reliability Extracted (AVE) 0.787 0.575

0.686

0.996

0.754

0.899

0.759

0.697

0.749 0.854 0.727 0.874 0.854 0.843 0.655 0.751 0.758 0.868

1.000 1.000 1.000 1.000 1.000 0.741 0.879 0.772 0.783 0.741

0.710 0.803 0.765 0.773 0.778 0.674 0.794 0.718 0.838 0.757

0.591 0.554 0.584 0.561 0.535 0.415 0.596 0.609 0.514 0.594

In order to measure the discriminant validity, the present study used the heterotrait-monotrait ratio (HTMT) of correlations, an alternative approach to the examination of cross-loadings and Fornell-Larcker criteria as per the multi-trait multimethod matrix (Henseler et al., 2015). Henseler and colleagues argued that the cut-off value of HTMT must be below 0.9 (Refer to Table 4.6).

Table 4.6: Discriminant validity - Henseler criterion (HTMT) Employee Business Competitive High- Innovation Job Motivation Model Advantage Impact Satisfaction Innovation SME Growth

Employee Motivation Business Model Innovation Competitive Advantage High-Impact SME Growth Innovation Job Satisfaction

0.759 0.041

0.630

0.011

0.211

0.644

0.004

0.114

0.079

0.704

0.052 0.052

0.076 0.073

0.231 0.013

0.271 0.227

0.556 0.256

0.717 189

Model Fit Assessment The structural model can be examined once the measurement model is validated satisfactorily. Validating the structural model enables systematic evaluation of whether the structural model's hypotheses are corroborated by the data (Urbach & Ahlemann, 2010). The coefficient of determination (R squared) and path coefficients can be utilised to assess the structural model in PLS. The first critical criterion for assessing the structural model is to identify the coefficient of determination (R2) of each endogenous latent variable, which quantifies the connection between the explained variance of a latent variable and its overall variance. A value of R square of 0.67 is regarded as strong, 0.333 is considered ordinary, and 0.19 and below are considered poor. The path coefficient value, which forecasts the strength of the association between two latent variables, is the second criterion for evaluating the structural model. The researcher should assess the path coefficients, algebraic sign, size, and significance of two latent variables while examining their connection. In order to account for a particular effect inside the model and to be significant at the 0.05 level of significance, path coefficients must surpass 0.100 (Huber et al., 2007). Table 4.7 shows the adjusted R-squared score (confidence interval biascorrected) of employability that helps in understanding the amount of explained variance of employability and independent variables (Hair et al., 2020). The final model improved the predictability and R2 (0.705). All the control variables were insignificant in the model. Researchers who studied PLS indicated that the inclusion of control variables significantly reduces the effect, irrespective of significance (Hair et al., 2017).

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Table 4.7: Test of R Square R Square R Square Adjusted High-Impact SME Growth 0.705 0.707

These fit measurements should be more precisely defined and described in the PLS-SEM literature. At the moment, the majority of readers do not have an idea concerning what fit measurements are, the definition, or the calculation method for fit measurements. For the approximate fit indices, standardised root means square residual (SRMR) and the Normed Fit Index (NFI), a researcher may directly examine the results of a PLS-SEM model estimation (for instance, the results report) and the values of these criteria above a specified threshold (Hair et al., 2020). The inference statistics for the precise fit measures d_ULS and d_G were considered. As a result, the researcher conducted the bootstrapping procedure and configured Smart PLS (Hair et al., 2020). Smart PLS performs the typical bootstrapping approach in the first round to obtain the inference statistics for the model parameters (Hair et al., 2020). Subsequently, Smart PLS adapts the Bollen-Stine bootstrapping approach outlined in Dijkstra and Henseler in the second round to calculate confidence intervals for the d_ULS, d_G, and SRMR criteria (Hair et al., 2020). While the root means square residual (RMSR) represents the mean absolute value of the covariance residuals, the SRMR is calculated by translating both the sample and projected covariance matrices into correlation matrices. The literature on PLS-SEM should include a more detailed explanation of how and where the covariance matrix is created in PLS-SEM (Hair et al., 2020). The SRMR is explained as the difference between the observed and implied correlation matrix in the model. Therefore, SRMR enables the average size of actual and expected correlation differences to be utilised as an absolute measure of the

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(model) fit requirement (Hair et al., 2020). Any value of less than 0.10 or less than 0.08 is regarded to be a good match (Hair et al., 2020). Henseler et al. (2014) explained the SRMR as a metric of model GoF for PLS-SEM that may be used to avoid model misspecification. Additionally, Smart PLS calculates the SRMR criterion's bootstrapbased inference statistics. The exact model fit is used to interpret the SRMR bootstrap confidence interval results (Hair et al., 2020). The precise model fit procedure assesses the statistical (bootstrap-based) inference of the gap between the empirical covariance matrix and the composite factor model's indicated covariance matrix (Hair et al., 2020). The literature on PLS-SEM should include a more detailed explanation of how and where the covariance matrix is created in PLS-SEM (Hair et al., 2020). Dijkstra and Henseler (2015) define d_ULS (such as the squared Euclidean distance) and d_G (such as the geodesic distance) as two distinct methods for computing this disagreement. The bootstrap procedure calculates confidence intervals for the disparity values. The d_G criteria are based on eigenvalue calculations using PLS-SEM. Nevertheless, the issue remains as to how these eigenvalues differ from CB-SEM. The values of d_ULS and d_G are meaningless in and of themselves (Hair et al., 2020). Only the bootstrap results of the exact model fit measures enable the findings to be interpreted. More precisely, the d_ULS and d_G interpretation are considerably different from the "standard" bootstrap findings because the d_ULS and d_G (and SRMR) confidence intervals are calculated using the customised BollenStine bootstrapping process rather than the "regular" bootstrapping procedure (Hair et al., 2020). When comparing the original values of the precise fit criteria to the confidence interval generated from the sampling distribution, confidence intervals must contain the initial value (Hair et al., 2020). Thus, the confidence interval's upper limit should

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be greater than the initial value of the precise d_ULS and d_G fit requirements to show that the model is "well fitted." In short, a model fits well if the discrepancy between the proposed and actual correlation matrices is minimal that it can be attributed completely to sampling error. The difference between the model's inferred correlation matrix and the empirical correlation matrix should be insignificant (p > 0.05). In contrast, if the divergence is substantial, there is no evidence of model fit (Hair et al., 2020). The normed fit index was introduced by Bentler and Bonett as one of the first fit measures in the SEM literature (Hair et al., 2020). It calculates the Chi2 value of the suggested model and contrasts it with a meaningful benchmark. As the suggested model's Chi2 value does not provide sufficient information to establish model fit, the NFI compares it to the null model's Chi2 value. Nonetheless, the literature fails to explain why the PLS-SEM Chi2 value varies from the CB-SEM Chi2 value (Hair et al., 2020). Therefore, the NFI is defined as 1 minus the proposed model's Chi2 value divided by the null model's Chi2 value. Consequently, the NFI produces values between 0 and 1 (Hair et al., 2020). The NFI is a measure of incremental fit. Therefore, a significant drawback is that model complexity is not penalised. The high parameters in the model indicate greater (and hence highly accurate) the NFI results (Hair et al., 2020). The NFI value that is closest to 1 indicates a better match. Additionally, NFI values greater than 0.9 often show a satisfactory fit (Hair et al., 2020). The nearer the NFI to 1, the greater the fit. The NFI value in the current study is 0.923, which is above 0.9, and represents an acceptable fit. The RMSR is a measure of the mean absolute value of the covariance residuals. In contrast, the SRMR is calculated by converting both the sample and predicted covariance matrices into correlation matrices (Hair et al., 2029). Smart PLS also

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includes SRMR criteria bootstrap-based inference statistics. The accurate model fit illustrates additional information on interpreting SRMR bootstrap confidence interval findings (Hair et al., 2029). The SRMR denotes the difference between the observed and model inferred correlation matrices (Hair et al., 2029). The SRMR is introduced by Henseler et al. (2014) as a goodness of fit metric for PLS-SEM that may be used to avoid model misspecification. Consequently, evaluating the average size of the differences between actual and predicted correlations as an absolute measure of the (model) fit criteria is possible. A value less than 0.10 is considered a good fit. The result of SEM analysis in this study shows SRMR equals 0.082, which is acceptable (Hair et al., 2020). The model fit indices are exhibited in Table 4.8.

Table 4.8: Model fit indices SRMR d_ULS d_G Chi-Square NFI

Saturated Model 0.082 0.595 0.918 17.034 0.923

Estimated Model 0.082 0.595 0.918 17.034 0.923

In the next step, the hypotheses generated from this study were tested by examining the structural model through Smart PLS software (Refer to Table 4.9). Initially, the researcher tested the estimated model with all competencies included. Bentler and Bonett's normed fit index was one of the earliest fit metrics presented in the SEM literature (2014). It computes the proposed model's Chi-squared value and evaluates it to a useful benchmark. As the suggested model's Chi-squared value does not give enough information to measure model fit, the NFI uses the Chi-squared value from the null model as a yardstick. Nevertheless, the literature fails to explain why the

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PLS-SEM Chi-squared value varies from the CB-SEM. Figure 4.4 shows the structural model.

Figure 4.4: The structural model

Testing Hypotheses Subsequently, the impacts of PLS-SEM bootstrapping on the model were investigated. Along with their values, the relevance of the route coefficients was determined. Values typically vary from -1 to +1. The analysis of the 500 Initiation Project Records is shown in Table 4.9.

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Table 4.9: Path coefficients

Employee Motivation → High-Impact SME Growth Business Model Innovation → HighImpact SME Growth CA*BMI → High-Impact SME Growth CA*Innovation → High-Impact SME Growth CA*JS → High-Impact SME Growth CA*PR → High-Impact SME Growth CA*EM → High-Impact SME Growth Innovation →High-Impact SME Growth Job Satisfaction → High-Impact SME Growth Productivity → High-Impact SME Growth

Original Sample (O)

Sample Mean (M)

0.547

0.629

0.054

0.005

0.161

0.082

0.046

0.019

0.138

0.121

0.141

0.133

0.589

0.572

0.090

0.032

0.143 0.586 0.132

0.149 0.501 0.142

0.134 0.082 0.137

0.309 0.029 0.337

0.132

0.110

0.085

0.019

0.151

0.142

0.044

0.101

0.013

0.014

0.059

0.031

Standard p-values Deviation

*Note: CA - Competitive Advantage / BMI - Business Model Innovation / JS- Job Satisfaction / PRProductivity / EM - Employee Motivation

The results indicated that employee motivation significantly affect high-impact SME growth (β = 0.547, p-value = 0.005). Thus, the first hypothesis is supported. Business model innovation is also significantly influence high-impact SME growth (β = 0.161, p-value = 0.019). Interestingly, job satisfaction was shown not to have a significant influence on high-impact SME growth (β = 0.151, p-value = 0.101). Finally, the influence of productivity on high-impact SME growth was also significant (p-value = 0.031). Remarkably, the results show that comparative advantage moderates the influences of innovation (β = 0.589, p-value = 0.032) and productivity on high-impact SME growth (β = 0.586, p-value = 0.029). Nevertheless, as reported in the findings of this study, the comparative advantage does not moderate the effects of business model innovation, employee innovation, and job satisfaction on high-impact SME growth. The findings are summarised in Table 4.10. 196

Table 4.10: The summary of the findings Hypothesis H1: Employee motivation has a significant positive effect on the highimpact growth of SMEs.

Result Accepted

H2: Productivity has a significant positive effect on the high-impact growth of SMEs. H3: Job satisfaction has a significant positive influence on the highimpact growth of SMEs. H4: Innovation has a significant positive influence on the high-impact growth of SMEs. H5: Improved business model innovation has a significant positive influence on the high-impact growth of SMEs.

Accepted

H6: Competitive advantage moderates the relationship between motivation and high-impact growth of SMEs. H7: Competitive advantage moderates the relationship between improved productivity and high-impact growth of SMEs. H8: Competitive advantage moderates the relationship between job satisfaction and high-impact growth of SMEs. H9: Competitive advantage moderates the relationship between innovation and high-impact growth of SMEs.

Rejected

H10: Competitive advantage moderates the relationship between improved business model innovation and high-impact growth of SMEs.

Rejected Accepted Accepted

Accepted Rejected Accepted Rejected

Summary Chapter 4 presents the findings of the study. The primary study objective was to analyse the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia. The researcher employed SEM to analyse the structural relationships in the study. The test of normality, outlier detection, the test of linearity, reliability, validity, and assessment of the model was presented. Finally, the path analysis in Smart PLS was undertaken to test the research hypotheses. The next chapter discusses the results and conclusion.

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CHAPTER 5 DISCUSSION AND CONCLUSIONS

Introduction This present chapter offers the thesis summary, the study's conclusion, and recommendations according to the research findings regarding the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia.

Discussion of the Results Economic growth in numerous Southeast Asian nations increased by an average of 4.6% between 2018 and 2019. In Malaysia, SMEs have the ability to promote the country's economic growth. Additionally, if these commercial initiatives are promoted and enhanced, the Malaysian economy will increase. The potential of SMEs to boost the country's economic growth indicates that developing SMEs will account for a significant portion of Malaysia's overall GDP. Unfortunately, SMEs continue to suffer a fundamental difficulty due to the lack of access to formal financial institutions, particularly capital loans from banks. Thus, the features of SME management remain incompatible with maximising advantages, owing to a variety of regulatory issues that continue to necessitate complicated processes and regulations. In the framework of macroregional growth, economic assistance for firms, particularly SMEs, must be directed at developing business productivity and competitiveness in local, national, and global markets. As a result, it necessitates improved knowledge, effective management, and the development of human resource capabilities. A critical component of an economic enterprise's longevity is its capacity

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to interpret its strategic environment and remain competitive. Economists believe that achieving rapid economic growth, as measured by GDP, is critical for balancing social, environmental, and economic development on a continuous basis. In the local and regional growth context, relational assets are critical for bolstering the capabilities of corporate institutions, network systems, and business collaboration as a unified system. Malaysia's march towards industrialisation and urban modernisation has benefited from crucial economic sectors, such as wholesale commerce, retail, automobile, tourism, construction services, the processing sector, educational services, and information and communication. These sectors demonstrate that the Malaysian macroeconomic growth is largely stable but has been unable to stimulate the growth of SMEs in terms of business innovation and sustained job absorption. A variety of factors influence this condition, including a slow process for developing SMEs, insufficient innovation and utilisation of technology to support SMEs' development, insufficient aid for business capital and access to formal financial services to assist the increase in the production, a diversified economic enterprise base, and product marketing systems which have not been optimal and sustainable, and insufficient government policy support. The results showed that employee motivation significantly influence highimpact SME growth (β = 0.547, p-value = 0.005). Business model innovation has a significant effect on high-impact SME growth (β = 0.161, p-value = 0.019). Notably, job satisfaction was shown to have no statistically significant impact on high-impact SME growth (β = 0.151, p-value = 0.101). Nevertheless, productivity also significantly affects high-impact SME growth (p-value = 0.031). Surprisingly, the results indicate that comparative advantage mitigates the effects of innovation (β = 0.589, p-value =

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0.032) and productivity on high-impact SME growth (β = 0.586, p-value = 0.029). Hence, as per the findings of this study, the comparative advantage does not appear to mitigate the benefits of business model innovation, employee innovation, and job satisfaction on high-impact SME growth. The research findings will be elaborated below:

5.2.1 Effect of Motivation on Growth and Performance of SMEs Employee motivation refers to employees' efforts to advance organisational aims (De Sousa Sabbagha et al., 2018). According to the findings in this study, employee motivation has a substantial influence on high-impact SME growth (β = 0.547, p-value = 0.005). This finding corroborates the findings of So et al. (2018). They discovered that employee motivation has an effect on organisational performance because people strive diligently to accomplish organisational goals. Additionally, the authors highlighted that employee motivation has an effect on staff performance, which benefits organisational growth. Matloob et al. (2021) highlighted that employee motivation develops when an organisation enables its employees to perform effectively and increase organisational performance. A few empirical studies have examined the relationship between motivation for expansion and the subsequent growth of Malaysian SMEs. The central principle of motivational theories argues that psychology is the motivation that influences individual behaviour and, hence, the individual amount of effort (Kondalkar, 2020). The review of the literature revealed that few researchers had examined the influence of motivation on revenue, employment, and export growth individually. This divergence is critical for business leaders and public policymakers. For instance, although business leaders are primarily focused on revenue growth, public

200

policymakers are concerned with employment growth. International expansion is becoming an increasingly realistic development strategy for SMEs as a result of the revolutions in communication, transportation, finance, and the homogeneity of markets (Matloob et al., 2021). Motivation is characterised as a function of an individual's personality and environment. Besides, differences in an individual's personality are suggested to impact an individual's job motivation significantly. According to Łukasik (2017), managers hold the responsibility to effectively inspire individuals and influence their behaviour in order to increase organisational efficiency. Therefore, these managers must have an awareness of what drives employees and the ways to motivate employees. Furthermore, motivation is explained as purposeful and directed. The term 'intentional' refers to a personal decision and diligence of action. On the other hand, 'directed' implies the presence of an influential force aiming at reaching a certain objective. Thus, an individual who is motivated is continually aware of the desired outcome and directs his or her efforts towards achieving the outcome (Kondalkar, 2020). Organising human resources into action to achieve the desired outcomes necessitates the use of physical, financial, and human resources (Freitas & Duarte, 2017). Through incentives, human resources may be exploited to their maximum capacity, which could be accomplished through fostering work ethics among personnel (Kondalkar, 2020). Such action will aid a firm in achieving optimal resource usage. The level of an employee or subordinate does not solely depend on the individual's qualifications or talents. Rather, the individual's motivation enhances their degree of productivity. The gap between a subordinate's ability and willingness must be narrowed down in order to maximise job performance, hence enhancing the

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subordinate's level of performance. The improvement in subordinates' performance levels will lead to an increase in production, a decrease in operating expenses, and an improvement in overall efficiency. As stated by Łukasik (2017), motivation is a crucial aspect that contributes to employee happiness. Employee happiness may be accomplished by considering and formulating an incentive scheme for the employees' benefit and could begin with the workforce stability and retaining employee retention rate. A manager should take the necessary procedures to cultivate a pleasant, amicable environment in a business. Stability in the workforce may be attained through motivation. From the perspective of a business's reputation and goodwill, the stability of its personnel is critical. Employees will only remain loyal to the company if they have a sense of engagement in the management. The talents and productivity of employees will constantly benefit both employers and employees (Łukasik, 2017). For instance, a high employee retention rate will result in a positive public image on the market, which will attract skilled and competent employees. According to the adage "Old is gold," the older the individuals, the greater their experience and their ability to adapt to the business, which may be advantageous to the organisation. Motivation does not simply act in a downward way. In the current context, when the workforce is highly informed, conscious, educated, and goal-oriented, the function of motivation expands beyond the confines of the management hierarchy. In addition to a superior encouraging a subordinate, support and encouragement to a colleague, and timely useful ideas even to a superior foster rapport at all levels in the workplace (Łukasik, 2017). Moreover, if workers are self-motivated, acknowledging their self-motivation helps them feel valued and desired. On the one hand, motivation relates to the desire and attempts to satisfy a need or objective. In fact, satisfaction

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implies the happiness experienced when a need is met. Contradictorily, inspiration causes a shift in one's way of thinking. On the other side, manipulation involves obtaining predefined behaviour from others. Motivation is a crucial aspect of capability, which is described as the ability of individuals, institutions, and communities to execute functions, solve issues, and establish and attain goals. Motivation is the mixture of an individual's desire and drive and effort focused on reaching a goal. It is the reason for an activity to be undertaken. Motivation may be internal, such as emotions of satisfaction and accomplishment, or extrinsic, such as rewards, punishments, and goal attainment (Łukasik, 2017). For example, incentives and incentive systems are essential for developing employees' capacities and turning them into improved performance (Łukasik, 2017). Not everyone is driven by the same motivation, and their motives may vary over time. Different degrees of motivation exist, including individual, organisational, and social. Individuals are motivated by their own wants and moral convictions. Individual motivations can be "internal" or "intrinsic" (activated from the inside), for instance, hobbies or volunteering in the community. In contrast, individual motivations may be external or extrinsic (active from the outside), which are cultivated from the outside (Pârjoleanu, 2020). The fact that individuals prefer to identify with others and feel a sense of belonging to groups is the source of social motives. Individuals are dependent on others. As a result, they are loyal to the organisations to which they belong. Formal and informal norms regulate social relationships (Pârjoleanu, 2020). First, people, groups, and organisations prefer to believe that they are treated fairly in comparison to their peers or rivals. The second element is the establishment of criteria and authorities that promote fair conduct and prevent unfair deals (Łukasik, 2017). The third

203

phenomenon is known as social pressure. It may be acceptance or condemnation from bosses, colleagues, or people for whom the individual feels responsible. Historically, motivational tactics including pay, supplemental benefits, intangible rewards, recognition, and punishments have been employed to promote employee performance. Motivators can be either positive or negative (Pârjoleanu, 2020). Reducing disincentives or perverse incentives that encourage undesirable behaviour is frequently more necessary than creating new incentives (Pogozhina et al., 2020). Incentive systems exist within organisations, particularly in their structure, regulations, human resource management, possibilities, internal advantages, rewards, and punishments. Despite being based on perception or fact, organisational incentive systems have a substantial impact on the performance of employees, resulting in organisational success. In fact, the most ubiquitous structural incentives and motivations potentially exist at the society level, such as security, the rule of law, investment climate, public service salaries, and legislation, facilitating civic involvement (Pogozhina et al., 2020). General organisation incentives that influence employee motivation, compensation, wages, and efficiency pay direct monetary benefits, such as a pension, sickness, health, and life insurance, allowances (clothes, housing), subsidies, and profit-sharing. Examples of indirect financial advantages include subsidised food, clothes, housing, and transportation. Amenities, infrastructure, occupational health, recreational facilities, safety, school access, transportation, and work environment or conditions are all elements of a quality of life index (Pogozhina et al., 2020). Internationalisation and the overall growth of SMEs appear to be inextricably linked (Hasim et al., 2018). While earlier research has concentrated on international orientation and motivation in isolation, less attention has been given to the combined

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effect on performance. A possible explanation for this seeming scarcity of studies is the temporal separation of motivation, international orientation, and subsequent performance, which makes data gathering laborious and time-consuming. Pogozhina et al. (2020) believed that motivational characteristics might have an indirect effect on behaviour through other processes. Their belief is especially true when studying a firm's growth. Growth is a process of change that cannot be adequately analysed by focusing solely on a single moment in time. Therefore, understanding how successful employee motivation affects future growth and motivation is important. While several motivation dimensions have been studied independently in the past, research into their relationship and relative relevance to performance is non-existent. Longitudinally, investigating these characteristics and their interrelationships in an SME environment is critical as SMEs account for most of the enterprises and produce most of the new jobs in Malaysia (Ramdan et al., 2022). A deeper knowledge of the growth factors is critical for both business practitioners and public policymakers. Employee motivation is critical in organisations. Pârjoleanu (2020) stressed that businesses must ensure employee motivation in order to remain competitive. Additionally, Pârjoleanu (2020) highlighted that training employees help them develop new abilities, which improves employee retention and organisational dedication. Staff motivation also increases employee effectiveness, contributing to the sustainability and success of the organisation. Essentially, businesses that foster employee motivation experience an increase in performance and revenue growth. Lukasik (2017) examined the impact of training on employee motivation in small and medium-sized businesses. The author concluded that human capital is crucial for organisations to achieve key competencies. The author also emphasised that the purpose of employee training is to obtain a competitive advantage. Besides,

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Lukasik (2017) stressed that employee motivation affects employees' performance and efficiency. Matloob et al. (2021) examined the influence of employee motivation in small and medium-sized businesses. They asserted that employee motivation encourages employees to enhance their performance to contribute to the achievement of organisational goals and objectives. The accomplishment of organisational objectives results in corporate growth. Employee motivation is bolstered by human resource management techniques that include ongoing education. This knowledge is gained through training, which motivates individuals to perform at their best, hence increasing workplace engagement. Employee engagement boosts motivation and productivity, which benefits corporate growth (Mikkelsen & Olsen, 2019). Work participation results in job satisfaction, which results in organisational growth. This finding demonstrates that when an organisation values its people, their core abilities contribute to the organisation's performance. As a result, SMEs that engage in business coaching are likely to profit from increased employee motivation, resulting in rapid development for SMEs.

5.2.2 Effect of Improved Productivity on Growth and Performance of SMEs The results show that productivity significantly positively affects the highimpact growth of SMEs. Therefore, increased productivity is achieved by having trained staff and educating employees about the SME's aims and objectives. Moreover, Okolocha (2020) argues that staff retention affects productivity. As a result, he urged managers to pay special attention to staff training, ensuring that managers implement the required measures to reduce employee turnover. The methods ensure the productivity and impact growth of SMEs.

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In economics, physical productivity is described as the amount of output produced by a unit of input over a unit of time (Filipenko, 2021). The normal calculation produces output per unit of time. Physical productivity gains result in an increase in the value of labour, which raises remuneration. Thus, employers must emphasise education and on-the-job training. Experience and knowledge aid human capital development and increase productivity (Filipenko, 2021). In economics, productivity refers to the output per unit of input that could be labour, capital, or any other resource (Filipenko, 2021). It is often stated as a ratio of GDP to hours worked in the economy (Filipenko, 2021). Labour productivity can be categorised further by sector in order to research trends in technological advancement, pay levels, and labour growth (Sobolev, 2020). Profitability and shareholder return of businesses are inextricably connected to developing productivity. At the corporate level, productivity is a measure of an organisation's manufacturing efficiency. Productivity is determined by comparing the number of units produced to the number of employee work hours or by comparing net sales with employee labour hours. Therefore, the ability of Malaysian SMEs to enhance their level of outcome is almost entirely dependent on their capability to increase production per worker. Productivity growth is used by economists to model an economy's productive potential and estimate capacity utilisation rates (Filipenko, 2021). Subsequently, this information is utilised to anticipate business cycles and forecast future GDP growth rates. Additionally, capacity and utilisation figures are utilised to forecast demand and inflationary pressures. The forecast is calculated by dividing GDP by the total number of hours worked in the economy. Productivity in the workplace refers to the amount of "work" completed during a specified time. Economic development and

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competitiveness are mostly determined by productivity. Thus, increases in the quantity of capital accessible to human resources, the experience and education of the workforce (labour composition), and technological advancements all contribute to labour productivity growth. Moreover, productivity is often stated as a ratio of GDP to hours worked in the economy. Labour productivity may be further categorised by sector in order to study trends in labour growth, pay levels, and technological advancement. Profitability and shareholder return of businesses are inextricably connected to developing productivity. At the corporate level, productivity is a measure of an organisation's manufacturing efficiency. It is determined by comparing the number of units produced to the number of employee work hours or by comparing net sales to employee labour hours (de la Fuente-Mella et al., 2020). When productivity growth is insufficient, potential advances in wages, living standards, and corporate profits are constrained. Economists utilise productivity growth to simulate an economy's productive potential and estimate its capacity utilisation rates. This information is subsequently utilised to estimate business cycles and forecasts future GDP growth rates. As witnessed lately, gains in productivity may occur during both booms and recessions. Hence, considering the economic backdrop when assessing productivity data is necessary. Numerous factors influence a nation's GDP, such as investments in equipment and plant, innovation, supply chain logistics improvements, education, enterprise, and competition. Total factor productivity measures the proportion of an economy's growth which cannot be attributed to labour and capital accumulation. Total factor productivity is defined as the contribution of managerial, technical, strategic, and financial innovations to economic growth. This economic performance metric, also known as multi-factor productivity (MFP), compares the number of goods

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and services produced to the number of combined inputs used to produce those goods and services. Inputs include labour, energy, capital, materials, and purchased services. When productivity growth is inadequate, potential gains in wages, corporate profits, and living standards are hampered. Savings must finance investment in an economy. Therefore, investment is proportionate to savings. Low savings rates might result in lower investment rates and lower labour productivity, and real wage growth rates. Park et al. (2019) suggested that workers have a large impact on the firm's production. The authors stated that employee training enables businesses to recruit and retain high-performing employees. These employees contribute to the business's continual growth, resulting in the business gaining its competitive advantage. Amah and Oyetuunde (2020) observed that SMEs that invest in their employees' well-being boost organisations' productivity, hence, increasing their high-impact development. The authors asserted that SMEs increase staff productivity by providing an atmosphere conducive to employee growth. Coaching and training can help improve these personnel's talents. Thus, SME employees should participate in development programmes to boost their productivity, which would positively affect the growth of SMEs. Nevertheless, studies on the influence of business coaching on the high-impact growth of Malaysian SMEs are lacking. As a result, further study is necessary to address this particular gap in the literature. Ballestar et al. (2020) revealed that knowledge has a considerable influence on the productivity of small and medium-sized businesses. Besides, the authors indicated that SMEs could boost productivity and development by adopting training within the organisation. Training facilitates information transfer with the organisation, resulting in enhanced performance and company success.

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5.2.3 Effect of Job Satisfaction on Growth and Performance of SMEs According to the results of this study, job satisfaction was discovered not to have a statistically significant effect on the high-impact SME growth (β = 0.151, pvalue = 0.101). Job satisfaction is a term that refers to employees' sentiments about their jobs (Mira et al., 2019, p. 773). Abbasi et al. (2020) performed a study on the mediating influence of work satisfaction in Malaysian SMEs. They discovered that job satisfaction improves employees' performance, which results in increased excitement for their work, subsequently assisting them in meeting established goals. Satisfied personnel will guarantee that they perform maximally in order to accomplish the organisation's goals (Inayat & Khan, 2021). Additionally, satisfied employees will be highly productive, reduce absenteeism, and demonstrate increased commitment and punctuality. In comparison to unsatisfied workers, contented employees are environmentally conscious, which results in organisational commitment, job satisfaction, and accomplishment of organisational goals. Hee et al. (2020) identified several elements that contribute to employee happiness, including positive relations between employees and colleagues, competitive pay scales, employee participation in organisational decisions, and job security. Job satisfaction is critical because it is shown to have a positive and reciprocal link with life satisfaction. Besides, job satisfaction also has an effect on personal, social, and professional life (Unanue et al., 2017). Individuals often experience varying degrees of pleasure with various parts of their jobs. The determinants of motivation, performance and job satisfaction are identified as work-related variables (the work context, task activities or content, and job objectives), individual characteristics (individual abilities, knowledge, and skills) and rewards (Unanue et al., 2017). This

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model considers organisational functioning, task and job characteristics, physical working circumstances, career issues, social and relationship issues, and compensation packages and personnel policies. The expectation theory presents a procedure that reflects individual variances in job motivation, as opposed to offering precise advice for the factors that inspire employees. Expectancy theory offers principles for increasing employee motivation by identifying an individual's effort-to-performance and performance-to-reward expectations (Ahmad et al., 2021). Thus, employees are paid if they exert more effort and do better in their jobs. When there are disparities between expected and real remuneration, employees become dissatisfied. In other words, discontent may emerge if employees receive less than they had anticipated or feel that they have been treated unfairly (Ahmad et al., 2021). Managers must instil the belief that great effort yields valuable benefits in their staff (Ahmad et al., 2021). In his research on work and motivation, Vroom, V.H. (1964) noted that job satisfaction is comprised of seven factors, namely salary, supervisor, coworkers, working environment, job content, advancement, and organisational self. This research has been utilised by social scientists for decades (Ahmad et al., 2021). In addition, Porter and Lawler expanded the Vroom expectancy model in the late 1960s by creating the Porter-Lawler Expectancy Model. Although the Porter-Lawler model is premised on the Vroom model, the former model was more complicated. The Porter-Lawler model suggests that more effort does not necessarily result in higher performance since individuals may lack the essential ability to attain high levels of performance or have an inadequate understanding of how to accomplish vital activities (Ahmad et al., 2021). Smith et al. (1969) established the Cornell Model by arguing that work satisfaction is how an individual feels about various aspects of his or her profession.

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This emotion stems from the employee's impression of a disparity between reasonable and fair outcomes. The idea of the reference frame relates to the criteria employed during evaluation. These standards are the result of employee experiences and expectations (Ahmad et al., 2021). Job satisfaction is projected to be a more powerful motivator of job success than any other reward. Previous studies have demonstrated that job happiness and motivation have a bigger impact on job performance than any other incentive. Consequently, employees and management must collaborate to create, design, and implement incentive programmes. The present study's findings confirmed that job motivation and job satisfaction had a beneficial effect on job performance. Nevertheless, despite the results of the current research, in essence, effective job performance is a result of employee motivation and job happiness. Therefore, job satisfaction and motivation could be effectively implemented when human motivational needs and psychological feelings or behaviours are taken into account. Additionally, placement should be based on discipline, interest, and experience in order to introduce the appropriate incentives for the required performance towards organisational growth.

5.2.4 Effect of Innovation on Growth and Performance of SMEs Innovation is the process of introducing new services and products to the market in an effort to obtain a competitive edge. Consistent with the results of this study, Alam et al. (2016) investigated the influence of innovation on the growth of Malaysian SMEs. The authors believed that SMEs innovate in a variety of ways, including process innovation and product innovation. While product innovation

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requires improving a current product in order to increase market performance, process innovation entails developing new and improved methods for delivering products. Innovation is crucial to the role of the enterprise in contemporary society, which is the main activity that involves the whole firm and conditions its behaviour to facilitate value creation, competitive advantage, and business performance (Whitacre et al., 2019). Innovation can have many connotations in various fields. Innovation is indefinable because of its intricacy and interacting processes of demand-and-supplyside customer factors and research and development outputs (Mowery & Rosenberg, 1979; Mole & Worrall, 2001; Samara et al., 2012). Among the first contributions to the classical innovation literature is Schumpeter's (1939) microeconomic perspective on innovation, which includes business ideas. Schumpeter (1934, 1993) has also utilised the phrase "creative destruction" to outline the process of reinvention and creation in which the old is continuously destroyed, and the new is created. Innovation can be defined as the firm's ability to identify, acquire, and implement ideas and tasks that emerge in various forms (distributing channels, internal cultures, management and administrative systems, marketing methods-segments, and processes, products and services) in a manner that is novel and superior (Whitacre et al., 2019). It may be a wholly new invention, an enhancement of an available product or system, or a novel application of a previously developed innovation. Innovation can also be associated with the establishment of new enterprises within an existing firm or the revitalisation of continuing businesses that have grown stagnant or require change (Rondi et al., 2019). "Innovation manifests itself in many different ways, and it is very hazardous to predict, both its timing and its consequences", which may be thought of as incremental innovation (using available technology to reduce uncertainty and increase competitive advantage within the present industry and market) or radical

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innovation (seek new technology, high uncertainty, and dramatic change within the new or current industry and market). Radical innovation requires a new market to yield fruit (Rondi et al., 2019) and has the potential to alter product category, industry, and market drastically. Other forms of innovation are dependent on qualities associated with competence enhancement in opposition to competence degrading and technical as opposed to administrative (Rondi et al., 2019). Innovative capability is regarded on several levels and from a wide viewpoint, based on a firm's strategy and market state, which is connected to the organisation's potential to adapt accordingly to environmental changes. It enables a business to adapt to competition and attain commercial success (Guan & Ma, 2003). Innovative capability is compatible with the resource-based perspective in describing how a company obtains a competitive advantage by channelling resources, skills, and competencies into innovation (Hult et al., 2004; Martinez-Roman et al., 2011). Successful innovation necessitates "exploration capabilities," or the capacity of a business to glean ideas and knowledge from many sources (Whitacre et al., 2019). Systematic innovation could result in the observation of various sources of innovative opportunities within and outside of a company, which is critical for determining the unprecedented (such as unanticipated potential), incongruity (such as opportunity between reality and behaviour), industry and market restructures, demographics (for instance, shift in perception and population), process need, and localised, embedded, and research-based knowledge (Rondi et al., 2019). In addition to implicit knowledge, tacit knowledge is a crucial source of innovation. Tacit knowledge is an unspoken form of knowledge (for example, hunches, inspirations, ingrained habits, observations, or other forms of awareness) that is commonly not written down or codified and provides an organisation with a distinct advantage over competitors in comparison to explicit

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knowledge that is absorbed intellectually or taught in training sessions (Whitacre et al., 2019). Examining the literature on innovation reveals two primary study streams, namely research on the effect of organisational cultures, processes, and individuals on innovation and research on the diffusion of innovation across organisations and sectors (Rondi et al., 2019). In the first stream, the company's internal culture plays a crucial role in fostering creativity and providing employees with ample room to make errors, hence, increasing possibilities for serendipity and meaningful learning (Whitacre et al., 2019). Well-established innovation culture and process inside the organisation is a crucial component in determining the rate of invention generation and commercialisation (Klingler-Vidra, 2019). Consequently, organisational innovation is "not just an important means of producing value (for the business in the market), but also of capturing it" (Arshad et al., 2018). Multiple external and internal variables inspire and influence innovation in businesses, particularly small and medium-sized businesses (Klingler-Vidra, 2019). The identification of these factors and forces provides businesses with a deeper knowledge of their innovation potential. The classic literature on innovation has tackled the topic from three different theoretical schools. The three distinct theoretical views are described below. First, the innovation system is viewed through the lens of the original notion of industrial districts or industry clusters. The first view contends that industrial districts comprise several elements, including hereditary business traditions, unique infrastructure, competencies and skills, and trading systems (Arshad et al., 2018). The industries can be embedded in specific regions. The resource compositions in these regions and localities are critical to the development of firms and the location (akin to the modern concept of the innovation system and innovation

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cluster), where geographical proximity and social networks play crucial roles in the dissemination and implementation of innovations (Whitacre et al., 2019). Entrepreneurs are "creative destructors" capable of drastically altering the preferences of their customers as a result of their inventive ideas and thoughts that create new standards. When one takes a firm-level perspective, evidently, enterprises are continually working to generate "new combinations" of resources and skills and improving existing talents and competencies or imitating rivals. This procedure can lead to creative destruction (Arshad et al., 2018), producing organisational and market disruption, which, if effective, may lead to profits and competitive advantage (Whitacre et al., 2019). Firms should be able to continually grow and refresh their configurations of human, informational, intellectual, financial, technological, and other resources (participate in a continuous cycle of internal creative destruction) (Arshad et al., 2018). This continual change compels businesses to reconsider their present structures or face extinction at the hands of rivals. Lastly, according to the technology-push or market-pull perspective, the rate and direction of innovation inside an organisation can be determined by technologypush premised on scientific and technological advancements and by market-pull based on unmet consumer and market demands (Whitacre et al., 2019). In order to effectively serve existing or new markets, businesses are required to develop new and change processes and models or new goods and services (Klingler-Vidra, 2019). These ways are two ways in which innovation may vary. Technology-push is defined as radical innovation (destructive with new improvement) with the commercialisation of technological capacity and expertise. In addition, the market pull is defined as incremental innovation (a replacement with improved enhancement) driven by the demand or requirement of people or groups representing various market clients

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(Klingler-Vidra, 2019). Another viewpoint is that technology-push is significant in the early stages of the product life cycle. On the other hand, the market pull is prominent in the latter stages of product dissemination (Abernathy & Utterback, 1978; Pavitt, 1984). Currently, the SMEs are facing a change from technology-push to market-pull as a result of an improvement in client intelligence and complexity, which dictates market needs rather than technological needs. Firms that create goods and services in reaction to market-pull rather than technology-push have greater success in satisfying client needs, resulting in innovative success for responsive producers and manufacturers (Arshad et al., 2018). Wahab et al. (2020) concurred that innovation benefits SMEs. It plays a key role in SME growth by assisting SMEs in attaining their full potential. Additionally, the authors observed that innovation enables SMEs to boost their performance and achieve a competitive edge in the market. Innovation revitalises the value of assets, thus, improving both their worth and the success of the organisation. Finally, organisational success results in the rapid expansion of SMEs. Innovation significantly improves organisational competitiveness and company growth (Ibrahim et al., 2018). The authors argued that innovations enable an organisation to expand its organisational capacities while sustaining performance growth. Therefore, innovation contributes to the growth and sustainability of SMEs. Expósito and Sanchis-Llopis (2019) highlighted that innovation boosts chances of survival and enterprise success. They emphasised the importance of innovation in SMEs since it affects the operational and financial components of the business, ultimately boosting its performance. Innovation enhances an organisation's operational and financial success. Additionally, it improves the efficacy and effectiveness of SME

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operating procedures. The studies mentioned above indicate that SMEs should pursue innovative initiatives in order to attain long-term sustainability. Innovativeness is a critical component of growth plans since it enables the organisation to access new markets, expand its existing market share, and maintain a competitive advantage and business performance (Bedi, 2019). Companies have started to appreciate the need for innovation as a result of continually changing technology and the competitive global market, which are swiftly diminishing the value offered by old goods and services. Thus, innovation is a critical component of corporate strategies for a variety of reasons, involving the use of highly productive production methods, greater market performance, the pursuit of a positive customer reputation, and, as a consequence, the achievement of a sustainable competitive edge (Bedi, 2019). Over the last two decades, innovativeness has become a popular field of study for scholars attempting to define, categorise, and examine its performance implications, owing to its practical usefulness. Innovations offer organisations a strategic perspective for overcoming obstacles on their path to achieving a sustained competitive advantage (Arshad et al., 2018). The phrase innovation might also refer not solely to goods and processes but also to marketing and organisation (Bedi, 2019). Domi et al. (2019) defined innovation in terms of new goods, new techniques of production, new sources of supply, the exploitation of new markets, and new organisational structures. It is the process of endowing something with new, enhanced capabilities or utility, which comprise an innovation in products, processes, marketing, and organisations. Innovations in products and processes are inextricably linked to the notion of technological advancement. Product innovation refers to the introduction of new or substantially improved goods and services in their characteristics or possible

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uses, such as considerable improvements in technical specifications, component and material requirements, fully integrated software, user-friendliness, or other functional properties (Domi et al., 2019). Product innovations might be premised on new knowledge or technologies, innovative applications or combinations of previously known knowledge or technologies (Domi et al., 2019). The term product refers to both tangible products and intangible services. Product innovation is a challenging process that is accelerated by advances in technology, changing consumer requirements, shorter product life cycles, and growing global competition. It must include important contact both within the organisation and between the firm, its customers, and suppliers to succeed (Ibrahim et al., 2018). The introduction of a new or significantly enhanced production or distribution technology is known as process innovation, including physical changes to processes, equipment, and software. Process innovations can be used to lower unit costs of manufacturing or delivery, enhance product quality, or create or supply new or considerably better goods (Ibrahim et al., 2018). Thus, it is often believed that the introduction of new commodities has a clear, positive impact on employment development and income. In contrast, process innovation may have a more ambiguous effect because of its cost-cutting nature (Klingler-Vidra, 2019). Therefore, successful innovative SME growth requires the incorporation of scientific and technological potential and market prospects within a business.

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5.2.5 Effect of Improved Business Model Innovation on Growth and Performance of SMEs As reported in the findings, business model innovation has a substantial effect on high-impact SME growth (β = 0.161, p-value = 0.019). Consistently, Chen et al. (2021) suggested that SMEs should develop their business strategies to serve their clients better. Additionally, the authors indicated that SMEs that adopt business models outperform other businesses that fail to adopt the models. According to Cosenz and Bivona (2021), business model innovation is a vital component of the survival of SMEs and the ability to match customer expectations. The authors stated that SMEs should experiment with various business model creation methodologies in order to create unique business models. They stated that business model innovations increase a company's sustainability and enable it to maintain a competitive edge. Heikkilä et al. (2018) stressed that SMEs must adopt business innovation model routes in order to develop their company. They also stated that organisations innovate their business models by adjusting key components of their business model to increase their performance and achieve growth. Arif et al. (2019) found that the quality of innovative business models determines the growth of SMEs (Cosenz & Bivona, 2021). They emphasised that business model innovation generates larger returns than process innovation since process innovation modifies company processes. In contrast, business model innovation modifies business models, which are the primary components of a business (Cosenz & Bivona, 2021). Business model innovations have an effect on an organisation's long-term success, which results in SME growth. The authors concluded that innovation in business models is positively related to the rapid expansion of SMEs.

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The government and the related agencies should attempt to boost innovation in order to increase their regional competitive advantage. Consequently, the regional environment can either encourage or discourage firm-level innovation (Peric et al., 2017). The framework of innovative business clarifies why certain regions have an environment conducive to innovation, as there is a link between individual and regional firm-level innovation. Strong elements of local entrepreneurship, close interaction and collaboration between many companies, and relevant externalities are associated with a specialised labour market. The combination of innovation levels and business synergies can generate a potent endogenous stimulus for economic growth (Heikkilä et al., 2018). The local labour market is an essential information source and expertise because individuals who migrate from one location to another share tacit knowledge and best practices throughout the region. The innovative environment may be described in three different ways: management structure to decrease transaction costs under uncertainty (microanalytical perspective), the organisation to exchange learning and information (cognitive dimension), and organisation strategy structure (Cosenz & Bivona, 2021). This paradigm allows countries to build policy interventions to change areas into an inventive milieu (Heikkilä et al., 2018). There are two pathways to an innovative milieu, namely regionalised integration policy and regionalised innovation policy. Bigger enterprises can dominate innovation in the innovative without milieu area (regional integration policy), but smaller firms can be more inventive in the innovative and milieu region (innovative milieu). Nevertheless, there is a correlation between individual and regional firm-level inventions (Peric et al., 2017). In emerging economies, the qualities of an embedded innovation system can assist a firm in leveraging local and global knowledge and technology, which are better

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diffused throughout the local economy, resulting in an increase in the number of businesses engaging in technological upgrading and economic development and growth (Heikkilä et al., 2018). Since the early 1990s, the notion of a business innovation system has served as the theoretical framework for technology and science policy. Since the 1990s, the emphasis switched from a single corporation to a network of participants (innovation network) and from a university and research funding and technology programme to a holistic perspective that integrated these distinct organisations (Heikkilä et al., 2018). The inventive performance of a nation is dependent on the interactions between many entities and agencies, which can result in a collective system for developing and implementing technology and knowledge (Peric et al., 2017). It is critical to comprehend the new notion of a national innovation system in political and historical contexts with an instrumental purpose for economic achievements and policymakers rather than as a scientific theory drawn from the original ideas of industrial districts (Vaska et al., 2021). For instance, when the local economy is liberated to generate new market possibilities, the national innovation system can support the rapid expansion of technology and innovative breakthroughs. Local governments create assistance programmes, infrastructure, and legal and regulatory frameworks. The number of public-private sector collaborations is growing (Peric et al., 2017). It should also be noted that the new emphasis usually starts with the allotment of limited and scarce resources to the creation, distribution, and use of new resources, with the goal of producing, disseminating, and applying technology and knowledge to new processes, products, and services within national boundaries (Vaska et al., 2021).

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The connections and exchanges between these players are crucial to the formation of the national innovation system (Vaska et al., 2021). For instance, the difficulty in SMEs is that cross-stakeholder contact is restricted to bilateral discussions. This situation necessitates the orchestration of the innovation agenda in order to facilitate effective interaction between all major players, resulting in a flourishing innovation system. Nonetheless, there is a dearth of empirical studies and research papers documenting the nature of these driving factors in the business model (Cosenz & Bivona, 2021). The rising importance of the national innovation system is attributable to the improved knowledge of innovation processes, which points to new potential in innovation growth performance and new options for developing innovation policy for organisations, particularly small and medium-sized businesses (Vaska et al., 2021). As a response to the criticism of the classic linear innovation model and as a method for national research and development efforts, the modern interactive innovation model was created. In comparison to the bottom-up interactive innovation model, the classic linear innovation model is research-based, technocratic, and sequential. In contrast, the current interactive approach is more adaptable to traditional SMEs and the learning-based economy (Peric et al., 2017). Moreover, it should be recognised that the dynamics of industrial transformation have an effect on industry clusters and, by extension, the national innovation system. At the level of industrial sectors, there has been a tendency towards establishing a national innovation system with industry clusters comprised of players from all stages of the value chain. The globalisation phenomenon has substantial effects on the local system (Schiuma & Lerro, 2017). The objective of the free zone model and industrial cluster techniques is to implement the cluster idea in the computer industry (assembly line,

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outbound supply, and incoming component) and the car industry (auto parts manufacturers, assemblers, and suppliers). Nevertheless, this industry and sectorbased cluster method could provide a static bias (set borders and configured players in relation to current production processes and goods). They could not be able to catch instances in which industrial boundaries are muddling (Schiuma & Lerro, 2017). The combination

of

the introduction

of new

regulations, the

emergence

of

novel technologies, the entry of new competitors, and the modification of market rules can change the structure of industries and the potential for advancement and sustained competitive advantage for businesses and organisations within these industries (Cosenz & Bivona, 2021). Therefore, since business models are SMEs' blueprints for expansion and profitability, it can be argued that the innovative plans detail the items or services the SME should sell, as well as the target market and anticipated costs. As a result, when an SME is able to forecast these variables, it can predict whether or not it will generate a profit. Hence, business model innovations relate to new or improved business models (Schiuma & Lerro, 2017). Business model development and innovation in SMEs may result in higher profitability, hence, enhancing SME growth and performance. A business model further synthesises and combines all of an organisation's strategic, economic, and managerial facets (Vaska et al., 2021).

5.2.6 Moderating Role of Competitive Advantage on High-Impact SME Growth The results indicate that competitive advantage moderates the effects of innovation and productivity on high-impact SME growth. Nonetheless, the comparative advantage does not appear to moderate the benefits of business model

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innovation, employee innovation, and job satisfaction on the high-impact SME growth, according to the findings of this study. Numerous researchers have studied the moderating effect of competitive advantage by recognising the significance of SMEs to economic growth or their ability to provide employment opportunities (Garcés-Ayerbe et al., 2012; Klingler-Vidra, 2019). As reported by a number of academics, the capacity of SMEs to produce distinctive goods and to be adaptable to adopting new technologies is the most important factor in determining whether or not they will achieve the production of distinctive goods (Saeidi et al., 2019). It indicates that SMEs should engage in innovation to acquire a competitive edge in the marketplace. According to the findings of other studies, the small size of the enterprises hindered the continuation of innovative activities. Lack of internal funding, poor management abilities, lack of labour skills, lack of expertise, and lack of market access are obstacles to innovation for small businesses (Garcés-Ayerbe et al., 2012). Previous research on innovation and competitive advantage has been mostly on exporting and internationalising SMEs. These studies were conducted at mediumsized businesses and large-sized businesses, which have the financial means and infrastructure necessary to support innovation activities. Despite their expanding importance, little empirical research (Avermaete et al., 2003; Bayarçelik et al., 2014) have examined the innovation-competitive advantage link in small enterprises. In Malaysia, research on the impact of innovation on competitive advantage has been done in the hotel and timber industries (Saeidi et al., 2019). It is a well-known fact that SME businesses generate billions in the Malaysian GDP. The result of this research indicates that enterprises are more likely to innovate and hence, provide even greater competitive advantages. Thus, highly successful companies are more proactive,

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adaptable, and aggressive in innovating (Saeidi et al., 2019). According to these empirical investigations, the moderating influence of company age on the innovationcompetitiveness connection yields contradictory results. Rua et al. (2018) observed that SMEs are continually exposed to possible challenges,

which

makes

them

sensitive

to

business

sustainability

and

competitiveness. The authors also stated that organisations must cultivate distinctive competencies to attain competitiveness. Furthermore, SMEs with competitive advantages foster an innovative culture, enabling them to develop the ability to adapt to market challenges and opportunities (Kiyabo & Isaga, 2019). The innovative culture offers clients additional options to select from, hence, improving the success of SMEs. English and Hoffmann (2018) noted that innovation provides organisations with a competitive edge and supports their continuous expansion. External and internal variables might impact a company's competitive edge. Therefore, businesses should identify the activities and core skills that will aid them in establishing a competitive edge and subsequently pursue them. Udriyah et al. (2019) undertook a study to assess how market orientation and innovation influence Malaysian SMEs' competitive advantage. Their research highlighted that market orientation plays a vital role in detecting consumers' wants and adapting an organisation's goods and services to satisfy those needs. Udriyah et al. (2019) highlighted that fulfilling customers' needs by providing goods and services as per their desire boosts corporate performance and growth. The authors also emphasised that SMEs might increase their innovativeness through the development of creative tactics, such as labour skills and management capabilities. In addition to generating a competitive advantage, marketing orientation results in market innovation, which contributes to the success of the organisation (Adi & Adawiyah, 2018). Innovation in

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marketing enables companies to offer superior goods to their consumers based on their demands, ultimately boosting customers' happiness and business success. The coaching of employees can improve commercial performance in a firm and help it acquire a competitive edge by enhancing these talents. Innovation generates a novel and marketable concept that affords SMEs the potential to achieve superior market performance, hence enhancing their competitive edge. Thus, market orientation and innovation result in improved performance, guaranteeing the expansion of SMEs with a significant influence. According to Yatim et al. (2019), managerial talents confer a competitive edge for SMEs. As reported by the authors, managers guarantee that SMEs have the appropriate infrastructure and business facilities to boost company performance. Besides, SMEs experience robust development as a consequence of an increase in their performance relative to their competitors, hence enhancing their competitive advantage. The authors claimed that the government could be a beneficial source of advantages for SMEs by providing them with the fundamental necessities for success. The government should offer access to energy, water, and other services for small and medium-sized businesses. In addition, the authors observed that the government could provide consulting services to SMEs. The service can assist them in achieving improved market performance and a competitive edge. Haseeb et al. (2019) stated that social and technological advancements are a good source of competitive advantage for SMEs. They argued that in a competitive context, the sustained success of SMEs is essential. Furthermore, the authors argued that a suitable decision-making framework is essential for defining the strategic decisions that SMEs must undertake in order to maintain a competitive edge. Small and medium-sized businesses should utilise new technologies

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to enhance their subpar company performance and assure optimal performance. The authors also revealed that technology and competitive advantage have a substantial and beneficial link. A competitive advantage enhances the performance of a firm and assures its expansion. Aziz and Samad (2016) noted that distinctive goods are significant sources of competitive advantages for SMEs. They asserted that SMEs must consistently participate in innovative activities to gain market competitiveness. Nevertheless, according to the study, new companies tend to be competitive in the market due to their aggressiveness, proactivity, and adaptability. A competitive edge enables businesses to develop distinctive tactics that increase their efficacy and efficiency in order to achieve optimal growth. According to the findings mentioned above, a competitive edge is vital for small and medium-sized businesses since it corresponds to enhanced company success. Ismail and Alam (2019) analysed the effect of innovation on the competitive advantage of Malaysian SMEs. They asserted that innovation enables businesses to fulfil all of the constantly changing wants of customers. As consumers seek to satisfy their ever-changing wants, they require different and one-of-a-kind items. Therefore, businesses should develop distinctive goods and services to attain better performance, which will result in high-impact growth for SMEs. The authors further claimed that innovation assists businesses in achieving their objectives, profitability, and sales growth. Ismail and Alam (2019) have argued that enterprises acquire a competitive edge in the market when they produce greater consumer value than their competitors. The achievement of the competitive edge will contribute further to the firm's exceptional performance, hence fostering SME expansion. According to Kumar et al. (2019), organisational innovation provides businesses with a competitive edge.

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By taking the above discussion into consideration, as stated earlier, the objective of the present study was to investigate the moderating influence of competitive advantage on the innovation-competitiveness growth in the context of Malaysian SMEs. Research on the role of the moderator (firm age) in such a relationship has never been conducted in the SME context. Moreover, research on the influence of innovation on competitive advantage has also never been conducted in the SME context. Thus, this study aimed to address the resulting research gaps. This study's findings may assist policymakers in allocating funding to the proper target groups to secure future investment returns.

Summary This chapter presented a summary of findings as per the results of the data analysis. The present study aims to analyse the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia. In order to assist in answering the research question, this study developed and tested the following hypotheses: H1: Motivation has a significant positive effect on the high-impact growth of SMEs. H2: Productivity has a significant positive effect on the high-impact growth of SMEs. H3: Job satisfaction has a significant positive influence on the high-impact growth of SMEs. H4: Innovation has a significant positive influence on the high-impact growth of SMEs.

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H5: Improved business model innovation has a significant positive influence on the high-impact growth of SMEs. H6: Competitive advantage moderates the relationship between motivation and high-impact growth of SMEs. H7: Competitive advantage moderates the relationship between improved productivity and high-impact growth of SMEs. H8: Competitive advantage moderates the relationship between job satisfaction and high-impact growth of SMEs. H9: Competitive advantage moderates the relationship between innovation and high-impact growth of SMEs. H10: Competitive advantage moderates the relationship between improved business model innovation and high-impact growth of SMEs.

The present study's findings showed that employee motivation has a substantial influence on high-impact SME growth. Additionally, business model innovation has a substantial effect on the high-impact SME growth. Notably, job satisfaction was found not to have a statistically significant effect on the high-impact SME growth. Productivity also had a significant effect on high-impact SME growth. Surprisingly, the results indicate that comparative advantage mitigates the effects of innovation and productivity on high-impact SME growth. Nonetheless, as per the findings of the present study, the comparative advantage does not appear to mitigate the benefits of business model innovation, employee innovation, and job satisfaction on the highimpact SME growth.

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Conclusions Inadequate performance has been a persistent concern that has a negative impact on the overall growth of Malaysian SMEs. The majority of Malaysian SMEs lack the knowledge and skills necessary to achieve their market potential. Company coaching educates employees with the necessary abilities for a dynamic business environment accordingly. Due to the fast expansion of SMEs in Malaysia, it is essential for them to secure sustainable company growth. The Malaysian government declared that it was facing economic growth issues. Hence, the government proceeded to undertake the National Transformation Policy in order to become a developed nation by 2020. Notably, the majority of Malaysian firms are SMEs, although their economic contribution to the national GDP remains low. In addition, Malaysian SME performance has not been noteworthy since they have not had the anticipated effect on economic development. The results indicated that employee motivation significantly affects highimpact SME growth. Therefore, the first hypothesis is supported. Business model innovation also significantly influences the high-impact SME growth. Interestingly, job satisfaction was shown not to have a significant influence on the high-impact SME growth. Finally, the influence of productivity on the high impact of SME growth was also significant. Remarkably, the results show that comparative advantage moderates the influences of innovation and productivity on the high-impact SME growth. Nevertheless, according to the findings of this study, the comparative advantage does not moderate the effects of business model innovation, employee innovation, and job satisfaction on the high-impact SME growth. In recent years, Malaysian SMEs have underperformed, hence narrowing the productivity gap. The current investigation addressed the productivity gap and

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underperformance of SMEs in terms of production and growth. The success of SMEs is essential for the creation of job opportunities and the enhancement of economic growth in local areas. According to the results of the present study, coaching and training are essential to the success of SMEs. In contrast, their performance will suffer if SMEs do not receive mentorship and coaching. Malaysian SMEs need to provide coaches to their employees, which negatively impacts the growth and sustainability of the firms. The Malaysian government and SMEs must provide training seminars to SME personnel in order to prepare training aids to help the exponential expansion of SME businesses. Training and mentoring are essential for Malaysian SMEs since they boost their dynamic skills. Nonetheless, in recent years, many SMEs have failed to attain the expected level of performance, sometimes leading to their closure, which has had a negative influence on the Malaysian economy. Due to poor economic performance and a changing business climate, many SMEs have closed their doors. In addition, disruptive innovation has resulted in a paradigm change among Malaysian SMEs. In fact, Malaysian SMEs have struggled to sustain the appropriate level of performance while employing successful business strategies and providing high-quality products and services. This study has determined that deficiencies in a variety of areas, such as skillsets, understanding of work procedures, capabilities, competencies, morale or job motivation, job satisfaction, and stress management, are the primary causes of SMEs' failure to reach performance criteria. These problems are a result of the poor training and mentoring of SME personnel. Business coaching is essential for assuring SME growth and reducing the risk of failure since it motivates employees by increasing their ability and confidence.

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Implications for Practitioners Based on the study's objectives, this study proposed the following recommendations: 1.

Malaysian SME owners should undergo business coaching programmes to improve the growth and performance of their firms.

2.

The Malaysian government should encourage SME owners regarding the benefits of attending business coaching programmes.

3.

Since SMEs are critical to the growth and success of the Malaysian economy, this study recommends that the government should consider public-private partnerships with coaching companies in Malaysia to promote SME growth. The findings of the study found that business coaching positively impacts

motivation, productivity, job satisfaction, innovation, and improved business models. These impacts on SMEs promote a competitive advantage, which results in highimpact growth and improved performance. The conclusion of the thesis provides a summary of the study's findings and a discussion of the principal contributions to the theoretical body and practice. The contributions of the present study are quadruple. First, evidence is offered regarding the use of intangible resources for SMEs with limited physical and idle resources in establishing a sustained competitive edge. Second, the findings contribute to resource-based theory, the social capital theory, dynamic capabilities perspective, and network literature by illustrating the mechanisms and conditions under which networks, innovation breadth, and business model design translate into a competitive advantage, as demonstrated in enhanced SME performance. As a result, this thesis accounts for some of the intermediary business processes that convert resources and skills into firm performance. Innovation breadth is defined as a mechanism that 233

translates network performance gains. On the other hand, business model design is highlighted as the key to unlocking the performance gains of innovation breadth. Thirdly, according to evolutionary growth theory, SMEs' function as economic actors is constrained by the restricted range of routines they have learned, and the creation of new routines consumes prolonged time, besides being expensive and dangerous for SMEs. Similarly, the resource-based theory asserts that the low administrative capability of SMEs restricts their strategic diversity. The conclusions of this study make it very evident that SMEs must concentrate their innovation, network, and business model design efforts on maximising performance. It is recommended that SMEs focus on developing network connections that encourage innovation, restrict the scope of their innovations implemented in a particular year, and prioritise originality and efficiency in business model designs. The innovation breadth construct, which is central to the research models of the final three studies composing this dissertation, is a unique notion and a significant methodological contribution to innovation studies. Fourth, network and social capital theories are corroborated by validating the relationship between innovation breadth, networks, and SME performance using a longitudinal design. The understanding of the relationship is limited due to the abundance of cross-sectional studies in the field. Evolutionary economics is additionally strengthened by the fact that innovation benefits are ephemeral and that SMEs must innovate continuously to maintain high-performance levels. The contribution to SME policy is a better understanding of the significance of networks and business model design techniques among SME economic growth agents. This thesis identifies the processes and conditions under which innovation breadth, networks, and business model design transform into performance, which would

234

improve policy imperatives. The practice will benefit because SME owners would be able to allocate their limited resources more effectively to maximise performance.

Limitations The researcher experienced limitations when choosing a suitable sample size to participate in the study. Nevertheless, the researcher overcame this limitation by selecting all the participants that have participated in business coaching programmes by RichWorks International.

Recommendations for Further Research Future research on the benefits of training on the high-impact SME growth should be conducted. Further research should also be conducted on the impact of business coaching on SMEs in the context of other countries. The impact of business coaching on SMEs may be different in different countries.

235

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APPENDICES Appendix A: Timeframe

Table A1 outlines the timeline that I followed to conduct this study: Table A1: Timeline Major stages or activities May– July– June 2021

Selection of research topic

✓

Discussion

✓

September November– January– March– August –October December February April 2022 2021 2021 2021 2022

✓

Desk research

✓

Identification of respondents

✓

Population and sampling Instrument development

✓

✓

✓

✓ ✓

✓

Fieldwork

✓

Data computation

✓

✓

Data analysis

✓

✓

Writing and documentation

✓

✓

Final project submission

✓

✓

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14th October 2021 To whom it may concern: RE: REQUEST TO FILL IN THE QUESTIONNAIRE You have been invited to participate in this study because you are an SME business owner in Malaysia, and you have participated in business coaching programs by RichWorks International Sdn Bhd. Before you agree to participate in this study, please read the attached consent form. After you have read the consent form and agreed to participate in this study, please select one of the options below. I have read and understood the information on both documents, and I consent to participate in this study: Yes

No

Concerning privacy and confidentiality, you will NOT BE asked to fill in your name or the name of your SME. All of the questionnaires will be destroyed after recording the data. This questionnaire will take approximately 15–20 minutes to complete. The questionnaire contains six sections (A–G): section A contains demographic information; section B contains general information; and sections C–G contain information concerning employee motivation, improved productivity, job satisfaction, employee motivation, and enhanced business models, respectively. Kindly answer all of the questions to the best of your knowledge. Doing so will help me to develop findings that will help to answer my research questions. Kindly tick or fill in the blank spaces with the most suitable answer or response. Furthermore, kindly fill and return the questionnaire by 25th September 2021. If you have any questions regarding the questionnaire, please get in touch with me using the details provided below. Thank you very much for your time and cooperation.

Yours sincerely, Azizan Bin Osman [email protected]

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Appendix B: Informed Consent Form

Asia e-University Faculty of Business and Economics E-mail: [email protected] Website: https://aeu.edu.my

Thesis Title: Effect of Business Coaching on Growth and Performance and the Moderating Role of Competitive Advantage in Small Medium Enterprises in Malaysia

Researcher: Datuk Wira Dr Haji Azizan Osman Thesis Supervisor: Assoc. Prof. Dr. Wan Sabri Wan Hussin Email: FILL HERE

The researcher is a graduate student at the School of Graduate Studies, Asia eUniversity, Malaysia. The researcher conducted this study in partial fulfilment of the Degree of Doctor of Philosophy (Business Administration). The researcher’s supervisor is Assoc. Prof. Dr. Wan Sabri Wan Hussin. You will be left with a copy of this consent form for your reference. This will help you to refer to any details that are not clear. However, if you find any information that is not here, please feel free to ask me via my email. Kindly take your time to read the information below.

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Research Purpose This study’s purpose is to determine the effect of business coaching on growth and performance and the moderating role of competitive advantage in SMEs in Malaysia.

Role as a Participant Your role as a participant will include answering the questions on a day that you will mutually agree with the researcher. The researcher will ask you to provide honest answers to the questions asked, such as your experiences with business coaching with RichWorks international Sdn Bhd and whether it has impacted your SME’s growth and performance.

Benefits of Participating in the Study By participating in this study, you will benefit from the study’s results, which will inform you whether business coaching affects the growth and performance of your SME.

Potential Risk There are no potential risks from participating in this study.

Confidentiality The researcher will ensure your confidentiality by not using any identifiable information. This means that your personal information will not be included in the study. The researcher will also ensure your confidentiality by using the information you provide only for the purpose of this study.

Withdrawal from the Study You can withdraw anytime from this survey, either orally or in writing, and your withdrawal will not affect you in any way. If you withdraw from the study prior to the process of data analysis, the researcher will destroy the data collected, and your consent form will also be destroyed. 317

Access to Research Findings The researcher will send you a summary of the study findings via email.

Data Storage The researcher will store the research data in a password-protected cabinet for 5 years from 2021. After this period, the researcher will destroy all of the research data.

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Appendix C: Email Invitation for Recruitment

Study Title: Effect of Business Coaching on Growth and Performance and the Moderating Role of Competitive Advantage in Small Medium Enterprises in Malaysia

Dear study participant, My name is Azizan Osman, and I am a student studying the Degree of Doctor of Philosophy (Business Administration) at Asia e-University. I am conducting research on “Effect of Business Coaching on Growth and Performance and the Moderating Role of Competitive Advantage in Small Medium Enterprises in Malaysia.” I would like to understand your experiences of business coaching by RichWorks International Sdn Bhd and how it has affected growth and performance in your SME. This study has been approved by the Asia e-University Research Ethics Board. I will present this study’s findings to Asia e-University as part of the fulfillment of the Degree of Doctor of Philosophy (Business Administration). Please click the following link to participate in the survey: https://freeonlinesurveys.com/s/bLBmCJck In case you have any questions or concerns, please let me know.

Kind regards, Azizan Osman Researcher/Student

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Appendix D: Email Questionnaire

Section A: Demographic Information Kindly tick or fill in the blank spaces with the most suitable answer or response: 1. What is your gender? Male

Female

2. What is your age bracket? 18–25

26–35

36–45

46–55

Above 55

3. What is your education level? High school

Diploma

Bachelor’s degree

Master’s degree

PhD

Section B: General Information 4. Are you aware of the term “business coaching”? Yes

No

5. If you answered yes to the question above, have you or your employees ever attended a business coaching program? Yes

No

6. How often do you or your employees attend business coaching programs? 6 months

12 months

18 months

7. How would you rate the effectiveness of business coaching at your SME? Excellent

Good

Poor

8. Does business coaching lead to the growth and performance of SMEs? Yes

No

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Section C: Motivation 9. Indicate your level of agreement with the following statements about business coaching and motivation by putting a tick [√] to indicate the level to which you agree. Please rate the extent to which you agree/disagree with the following statements (1 = Strongly Disagree (SD), 2 = Disagree (D), 3 = Undecided (U), 4 = Agree (A), and 5 = Strongly Agree (SA)): Level of Agreement with No.

Statement

Statement

SSD DD JU 1 1

2

3

SA SSA 4

5

Business coaching improves my leadership skills, which gives me confidence.

2

Business coaching programmes equip me with the relevant marketing skills; therefore, I can gain tact, increasing my motivation to achieve business success.

3

Business

coaching

helps

me

improve

employee management. 4

Business coaching enhances strategic clarity.

5

Business coaching raises awareness of the importance of employee management.

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Section D: Productivity 10. Indicate your level of agreement with the following statements about business coaching and productivity by putting a tick [√] to indicate the level to which you agree. Please rate the extent to which you agree/disagree with the following statements (1 = Strongly Disagree (SD), 2= Disagree (D), 3= Undecided (U), 4= Agree (A), and 5= Strongly Agree (SA)): Level of Agreement with No.

Statement

Statement

SSD DD JU 1 1

2

3

SA SSA 4

5

Business coaching lessons increase my work productivity.

2

I enhance my skills due to business coaching programs.

3

I deliver quality work after undergoing business coaching.

4

Business

coaching

enhances

finance,

accounting, and tax management skills. 5

Business coaching helps me to complete workrelated tasks in a short timeframe.

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Section E: Job Satisfaction 11. Indicate your level of agreement with the following statements about business coaching and job satisfaction by putting a tick [√] to indicate the level to which you agree. Please rate the extent to which you agree/disagree with the following statements (1 = Strongly Disagree (SD), 2 = Disagree (D), 3 = Undecided (U), 4 = Agree (A), and 5 = Strongly Agree (SA)): Level of Agreement with No.

Statement

Statement

SSD DD JU 1 1

Business coaching gives me job satisfaction.

2

After attending business coaching sessions, I

2

3

SA SSA 4

5

am usually absent from work. 3

Business coaching makes me unhappy with my job.

4

I feel satisfied after undergoing business coaching programs.

5

Business coaching reduces employee turnover in my business.

323

Section F: Innovation 12. Indicate your level of agreement with the following statements about business coaching and innovation by putting a tick [√] to indicate the level to which you agree. Please rate the extent to which you agree/disagree with the following statements (1 = Strongly Disagree (SD), 2 = Disagree (D), 3 = Undecided (U), 4 = Agree (A), and 5 = Strongly Agree (SA)): Level of Agreement with No.

Statement

Statement

SSD DD JU 1 1

2

3

SA SSA 4

5

Business coaching helps me to contribute innovative ideas that enhance the growth and performance of my business.

2

My SME has modified products and services after attending business coaching sessions.

3

I do not create new ideas after undergoing business coaching training.

4

Innovation

positively

and

significantly

contributes to SME growth. 5

I have developed actionable ideas that have contributed to business growth.

324

Section G: Improved Business Models 13. Indicate your level of agreement with the following statements about business coaching and enhanced business models by putting a tick [√] to indicate the level to which you agree. Please rate the extent to which you agree/disagree with the following statements: (1 = Strongly Disagree (SD), 2 = Disagree (D), 3 = Undecided (U), 4 = Agree (A), and 5 = Strongly Agree (SA)): Level of Agreement with No.

Statement

Statement

SSD DD JU 1 1

2

3

SA SSA 4

5

Business coaching has helped my business to develop enhanced business models.

2

I have built a better marketing strategy after a business coaching session.

3

Business coaching helped me to develop appropriate plans to enhance the business’s product and customer base.

4

After attending business coaching sessions, I created a sales model that increased my firm’s revenue.

5

My customers are satisfied with my business’s improvement in business and services.

325

Section H: Growth and Performance 14. Indicate your level of agreement with the following statements about growth and performance by putting a tick [√] to indicate the level to which you agree. Please rate the extent to which you agree/disagree with the following statements: (1 = Strongly Disagree (SD), 2 = Disagree (D), 3 = Undecided (U), 4 = Agree (A), and 5 = Strongly Agree (SA)): Level of Agreement with No.

Statement

Statement

SSD DD JU 1 1

2

3

SA SSA 4

5

My business has experienced sales growth after attending business coaching programs.

2

My business has experienced tremendous financial

performance

due

to

business

coaching. 3

Business coaching programs have helped me attract new employees.

4

My SME has experienced growth in total return of assets after business coaching.

5

My SME has improved its total returns on investments.

Thank you for taking the time to fill in this questionnaire!

326