The impact of entrepreneurial alertness 

on the performance of youth-owned 

enterprises in South Africa 

 

 

 

Mafadi Eliot Mahamotse 

 

Supervisor: Dr Jabulile Msimango-Galawe 

 

 

 

A research report submitted to the Faculty of Commerce, Law and Management, 

University of the Witwatersrand, in partial fulfilment of the requirement for the 

degree of Master of Management in Entrepreneurship and New Venture Creation 

 

 

 

 

Johannesburg, 2020 

 



i 
 

ABSTRACT 

The South African government, in an attempt to remedy the high unemployment rate, 

has introduced policies and bodies to curb the unemployment rate, especially amongst 

the youth. This effort on the part of the government has shortcomings, as the South 

African GEM Report (2016/2017) depicts an alarming picture on the rate of business 

continuation in South Africa.  The inabilities of youth to identify business opportunities, 

creativity and innovation are reasons stated in the GEM Report to be contributors to 

business discontinuation amongst youth owners. 

It is critical for government to develop cognitive skills amongst the youth in South Africa, 

since that the problem of business discontinuation is associated with cognitive 

capabilities. Entrepreneurial alertness is considered as an important cognitive skill that 

has the potential to improve enterprise performance when it is measured by scanning 

and search, association and connection and evaluation and judgement 

Data was collected from youth entrepreneurs in all provinces in South Africa, using a 

self-administered questionnaire and a sample size of 126 was attained. In the analysis 

of the data, factor analysis was utilised to reduce some variables and the variables 

converged into two entrepreneurial alertness dimensions, which are scanning and 

search and evaluation and judgement. However, scanning and search proved 

insignificant when regression tests were done. 

The findings of the study showed that entrepreneurial alertness tested with evaluation 

and judgement positively impacts youth-owned enterprise performance in South Africa 

and this impact is significant. Consequently, no evidence was found to prove that 

alertness tested with scanning and search has a relationship with enterprise 

performance. The study recommended that there is a need for an entrepreneurial 

alertness model that can expand alertness dimensions. 

 

Key words: Youth entrepreneurs, entrepreneurial alertness, opportunity recognition, 

Enterprise performance 

  



ii 
 

DECLARATION 

 

 

 

I, Mafadi Eliot Mahamotse, declare that this research report is my own work except as 

indicated in the references and acknowledgements. It is submitted in partial fulfilment of 

the requirements for the degree of Master of Management in Entrepreneurship and New 

Venture Creation at the University of the Witwatersrand, Johannesburg. It has not been 

submitted before for any degree or examination in this or any other university. 

 

Name:____________________________________Signature:__________________________ 

 

Signed at …………………………………………………… 

 

On the …………………………….. day of ………………………… 20….. 

 

 

 

 

 

 

 

 

 

 

 

 



iii 
 

DEDICATION 

 

 

This work is dedicated to my late grand-grand-mother (Linah-Nkoti Mahamotse) who 

invested in my educational foundation. My undergraduate studies would have never 

been possible without her. “Robala ka kgotso Lenkoe”. 

 

To my father (Eliot Nkoehatse Mahamotse), for encouraging and instilling the need and 

importance of education to me and my siblings. I still remembers his words “Thuto 

pele, monate ha o fele” (in direct translation, this meant Education first, entertainment 

is endless) has played an important role in my life. “Ee Lenkoe”. 

 

To my brothers (Mike Mahamotse and Jerry Mahamotse), my sister (Ntobineng 

Mahamotse), and the entire Mahamotse family. Thank you all for your love and no 

words can express my love to you. 

 

To my fiancé (Yvonne Mariri), thank you for your support and understanding when I 

sometimes only came home in the morning, swallowed by syndicate rooms. Thank you. 

  

To my kids (Rethabile and Karabelo). I pray that the tears felt during the time of this 

work, can deeply nourishes the tree that shall bear fruits for you, my kids (Rethabile and 

Karabelo). PAPA HAS FINALLY MADE IT. 

 



iv 
 

ACKNOWLEDGEMENTS 

 

First, I would like to thank my supervisor, Dr Jabulile Msimango-Galawe, who was 

always there when I needed her guidance and advice. Her guidance and positive 

criticism have forged my academic character and contributed directly to the quality of 

my work. Your professionalism and the speed you always took to respond to my work 

was amazing - as if you never slept. “Thank you Doc” 

 

Secondly, my gratitude goes to Ms Meisie Moya; for your support during course work. 

The day you refused to let me quit when I felt like nothing was making sense; you 

actually injected courage into me from that day to this end. 

 

Thirdly, my former colleagues at the College in Vanderbijlpark; you always let me in for 

your help and opinions. I knew I had a home in you and it would have not been possible 

without you. 

 

Thank you, my training colleagues at the National Youth Development Agency (NYDA); 

for your help in distributing the questionnaires in different provinces. Practically without 

you, I could have not done this study, especially due to time constraints but with your 

help, I have managed to distribute my questionnaire to different provinces. 

 

Lastly, my former MMENVC students with whom we sometimes did night vigils in the 

syndicate rooms. Your advice has never fallen on death ears. Especially my research 

buddy (Tshegofatso Eister), with whom we always left campus in the morning hours 

pushing. Your support was amazing and I thank you so much. 

 

 

 

  



v 
 

TABLE OF CONTENTS 

 

 

ABSTRACT ..................................................................................................................... i 

DECLARATION .............................................................................................................. ii 

DEDICATION ................................................................................................................. iii 

ACKNOWLEDGEMENTS .............................................................................................. iv 

LIST OF TABLES ........................................................................................................... x 

LIST OF FIGURES......................................................................................................... xi 

CHAPTER 1: INTRODUCTION................................................................................... 1 

1.1 Purpose of the study ................................................................................................. 1 

1.2 Context of the study .................................................................................................. 1 

1.3 Problem statement .................................................................................................... 5 

1.4 Research objective ................................................................................................... 6 

1.5 Resesrch questions .................................................................................................. 6 

1.6 Contribution of the study ........................................................................................... 6 

1.6.1 Theoritical contributions ........................................................................................ 7 

1.6.2 Practical contributions ........................................................................................... 8 

1.7 Delimitations of the study .......................................................................................... 8 

1.8 Conceptual definition of terms ................................................................................... 9 

1.9 Assumptions ............................................................................................................10 



vi 
 

CHAPTER 2: LITERATURE REVIEW ...................................................................... 11 

2.1 Introduction ..............................................................................................................11 

2.2 Background discussion ............................................................................................11 

2.3 Theoretical foundation .............................................................................................12 

2.4 Entrepreneurial alertness and enterprise performance .............................................14 

2.5 Enterprise performance ...........................................................................................15 

2.6 Entrepreneurial alertness .........................................................................................17 

2.6.1 Scanning and search ............................................................................................19 

2.6.2 Association and connection ..................................................................................19 

2.6.3 Evaluation and Judgement ...................................................................................20 

2.7 Conceptual framework .............................................................................................21 

2.8 Summary of the chapter ...........................................................................................21 

CHAPTER 3: RESEARCH METHODOLOGY........................................................... 23 

3.1 Introduction ..............................................................................................................23 

3.2 Research design ......................................................................................................23 

3.3 Data collection and sampling ...................................................................................25 

3.3.1 Population ............................................................................................................25 

3.3.2 Sampling method .................................................................................................25 

3.3.3 Sampling frame ....................................................................................................26 

3.3.4 Sample size..........................................................................................................27 

3.4 The research instrument ..........................................................................................27 

3.5 Data analysis ...........................................................................................................30 



vii 
 

3.5.1 Descriptive statistics .............................................................................................30 

3.5.2 Exploratory factor analysis: validity .......................................................................30 

3.5.3 Cronbach’s alpha: Reliability ................................................................................31 

3.6 Correlation analysis .................................................................................................31 

3.7 Multiple regression ...................................................................................................32 

3.8 Ethical considerations ..............................................................................................32 

3.9 Summary of the chapter ...........................................................................................33 

CHAPTER 4: PRESENTATION OF RESULTS ........................................................ 34 

4.1 Introduction ..............................................................................................................34 

4.2 Data screening.........................................................................................................34 

4.3 Demographic profile of respondents ........................................................................34 

4.3.1 Gender and race ..................................................................................................34 

4.3.2 Age group ............................................................................................................35 

4.3.3 Education .............................................................................................................35 

4.3.4 Enterprise Industry ...............................................................................................36 

4.3.5 Age of Business ...................................................................................................37 

4.3.6 Number of employees ..........................................................................................38 

4.4 Descriptive statistics ................................................................................................38 

4.4.1 Responses on the Scanning and search ..............................................................38 

4.4.2 Responses on Association and connection ..........................................................39 

4.4.3 Response on Evaluation and judgement ..............................................................39 

4.4.4 Responses on Enterprise Performance ................................................................40 

4.5 Measurement scale .................................................................................................40 

4.5.1 Validity of factors ..................................................................................................41 



viii 
 

4.5.2 Reliability of the measurement scale ....................................................................46 

4.6 Correlational results .................................................................................................49 

4.7 Multiple Regression Assumption Testing .................................................................50 

4.7.1 Multicollinearity diagnosis .....................................................................................50 

4.7.2 Normality ..............................................................................................................51 

4.7.3 Linearity ...............................................................................................................51 

4.7.4 Outliers .................................................................................................................51 

4.8 Hypotheses testing results .......................................................................................52 

4.8.1 Result for hypothesis 1 .........................................................................................54 

4.8.2 Results for hypothesis 2 .......................................................................................55 

4.8.3 Results for hypothesis 3 .......................................................................................55 

4.9 Summary of results ..................................................................................................55 

CHAPTER 5: DISCUSSION OF THE RESULTS ...................................................... 57 

5.1 Introduction ..............................................................................................................57 

5.2 Demographic profile of respondents ........................................................................57 

5.2.1 Gender and race ..................................................................................................57 

5.2.2 Age ......................................................................................................................58 

5.2.3 Education .............................................................................................................58 

5.2.4 Enterprise Industry ...............................................................................................59 

5.2.5 Age of business and number of employees ..........................................................59 

5.3 Outcomes of hypotheses .........................................................................................59 

5.3.1 Hypothesis 1 ........................................................................................................60 

5.3.2 Hypothesis 2 ........................................................................................................61 

5.3.3 Hypothesis 3 ........................................................................................................62 



ix 
 

5.4 Conclusion ...............................................................................................................63 

CHAPTER 6: CONCLUSIONS, IMPLICATIONS AND RECOMMENDATIONS ....... 65 

6.1 Introduction ..............................................................................................................65 

6.2 Conclusions of the study ..........................................................................................65 

6.2.1 Summary of key findings ......................................................................................68 

6.2.2 New conceptual framework ..................................................................................69 

6.3 Implications and recommendation............................................................................70 

6.3.1 Theoretical implications ........................................................................................70 

6.3.2 Practical implications ............................................................................................70 

6.4 Limitations ...............................................................................................................70 

6.5 Suggestions for future research ...............................................................................71 

REFERENCES .............................................................................................................. 72 

APPENDIX A: QUESTIONNAIRE COVER LETTER .................................................... 81 

APPENDIX B: RESEARCH INSTRUMENT .................................................................. 82 

SECTION A: Demographics ..................................................................................................82 

SECTION B: Entrepreneurial Alertness .................................................................................83 

SECTION C: Enterprise Performance....................................................................................84 

APPENDIX C: ETHICS CLEARANCE CERTIFICATE ................................................. 85 

APPENDIX D: CONSISTENCY MATRIX ...................................................................... 86 

APPENDIX E: ADDITIONAL RESULTS ....................................................................... 87 



x 
 

LIST OF TABLES 

Table 1.1: Definition of terms ..................................................................................................... 9 

Table 2.1: Two types of performance measure .........................................................................17 

Table 2.2: Developing views of alertness ..................................................................................18 

Table 3.1: Research instrument summary .................................................................................29 

Table 4.1: Gender and Race Cross-tabulation ..........................................................................35 

Table 4.2: Age Group ................................................................................................................35 

Table 4.3: Industry of your enterprise ........................................................................................37 

Table 4.4: Number of Employees ..............................................................................................38 

Table 4.5: Descriptive Statistics: Scanning and search .............................................................39 

Table 4.6: Descriptive Statistics: Association and connection ...................................................39 

Table 4.7: Descriptive Statistics: Evaluation and judgement......................................................40 

Table 4.8: Descriptive Statistics: Enterprise Performance .........................................................40 

Table 4.9: KMO and Bartlett's Test: Independent Variable ........................................................42 

Table 4.10: Total Variance Explained: Independent Variable ....................................................42 

Table 4.11: Pattern Matrixa ........................................................................................................43 

Table 4.12: KMO and Bartlett's Test: Dependent Variable ........................................................45 

Table 4.13: Total Variance Explained: Dependent Variable.......................................................45 

Table 4.14: Factor Matrixa .........................................................................................................46 

Table 4.15: Summary of Construct Reliability Results ...............................................................47 

Table 4.16: Inter-Item Correlation Matrix (Scanning and search) ..............................................47 



xi 
 

Table 4.17: Inter-Item Correlation Matrix (Evaluation and judgement) .......................................48 

Table 4.18: Inter-Item Correlation Matrix ...................................................................................49 

Table 4.19: Correlations ............................................................................................................50 

Table 4.20: Model Summaryb ....................................................................................................53 

Table 4.21: ANOVAa .................................................................................................................53 

Table 4.22: Coefficientsa ...........................................................................................................54 

Table 4.23: Summary of hypotheses results .............................................................................56 

 

LIST OF FIGURES 

Figure 2.1: Conceptual framework ............................................................................................21 

Figure 4.1: Highest Education Completed .................................................................................36 

Figure 4.2: Length of time enterprise paid salaries ....................................................................38 

Figure 4.3: Outliers ...................................................................................................................52 

Figure 6.1: New conceptual framework .....................................................................................69 



1 
 

CHAPTER 1: INTRODUCTION 

The chapter begins with the purpose of the study, followed by the context of the study, 

then, the problem statement, highlighting the objectives and research questions of the 

study, contributions of the study, the chapter ends with delimitation, conceptual 

definitions of terms and finally, with assumptions. 

1.1 Purpose of the study 

The purpose of the study was to investigate the impact of entrepreneurial alertness 

tested by Scanning and search; Association and connection, and Evaluation and 

judgement, towards performance of youth-owned enterprises in South Africa.  

1.2 Context of the study 

Globally, there is an increase in the number of young people conceiving ground-

breaking innovations and turning them into multi-billion dollar businesses (Whitten, 

2015). Whitten (2015) further states that this has revamped the youth and provides the 

understanding that youth participation in economy through entrepreneurship is undoubly 

impacful. There is understanding that youth are centre of concertration for study globally 

and that is equivalent to paying attention to the topology of the social landscape as a 

whole (Durham, 2000 in Majola, 2017). Studies further suggest that there is a growing 

number of young people that are resorting to entrepreneurship as a solution to their 

social problems, based on a high unemployment rate (Musengi-Ajulu, 2010; Seabela & 

Fatoki, 2014). Seabela and Fatoki (2014) further state that university degrees and 

diplomas are no longer holding the promise of jobs for young South Africans as a large 

number battle to find employment. 

 

Studies conducted by Youth Business International, International Labour Organisation 

(ILO) and Global Entrepreneurship Monitor (GEM) on youth entrepreneuship, provides a 

couple of reasons on the importance of entrepreneurship amongst the youth and they 

are;  



2 
 

Youth entrepreneurship is a choice to create employment; Young entrepreneurs are 

more likely to create employment for other fellow youths; Young entrepreneurs are 

particularly sensitive to new economic opportunities and trends; Young people are 

active in economic participation; Young people are more innovative and creative and 

often create new forms of independent work; Young people who are self-employed 

have higher life satisfaction; Entrepreneurship offers youth an opportunity to build 

sustainable livelihoods and a chance to integrate themselves into society; and 

Entrepreneurial experience help youth to develop new skills that can be applied to 

other challenges in life (Kew, Herrington, Litovsky, & Gale, 2013, p. 12) 

 

Despite the importance of entrepreneurship amongst youth in South Africa, the GEM 

(2016/2017) Report depicts an alarming picture on entrepreneurial participation (Global 

Entrepreneurship Monitor, 2016/2017). According to StatsSA (2019), young people in 

South Africa, between the ages of 18 to 35, constitute almost a third of the overall 

population, but with a lower occurrence of entrepreneurial activity (Global 

Entrepreneurship Monitor, 2016/2017; Musengi-Ajulu, 2010).  

 

The unemployment rate in South Africa was recorded at 29, 1% in the third quarter of 

the year 2019 (Smit, 2019). The youth between the age of 15 – 34 unemployment rate 

was approximately 40.4% in the third quarter of 2019 for both male and female, and 

translated to approximately four in every ten young people in South Africa that do not 

have a job (StatsSA, 2019). From unemployment statistics, it is evident that 

approximate 8,3 million young people are not economically active, and according to 

StatsSA (2019), this inactive group is referred to as “Not in employment, education and 

training” (NEET). These numbers increase every year and encompass young people 

who are discouraged from entering into the labour market (StatsSA, 2019). According to 

the National Development Plan 2030 (National Planning Commision, 2019), young 

people who have failed to secure formal employment by the age of 24 are unlikely to 

ever be formally employed, hence the ultimate solution for youth employment is 

entrepreneurship (Whitten, 2015). Entrepreneurship has been adopted globally as a 



3 
 

meaningful strategy to facilitate economic participation amongst young people 

(Musengi-Ajulu, 2010; Nafukho & Muyia, 2010). 

 

The European Commission has highlighted the importance of all stakeholders taking 

part in imparting an entrepreneurial mind-set in the society and the South African 

Government, like other countries, takes the development of small, medium, micro 

enterprises (SMMEs) amongst youth as an important agenda to pursue (European 

Commission, 2012; Majola, 2017). Youth enterprises receive financial and non-financial 

support from government through the establishment of the National Youth Development 

Agency (NYDA) (Nieman & Nieuwenheuizen, 2009). According to Nieman and 

Nieuwenheuizen (2009), the objective of this agency is to stimulate an entrepreneurial 

mindset, facilitate business funding and forge market linkages to younth aged 18 to 35 

in South Africa (Nieman & Nieuwenheuizen, 2009; National Youth Development 

Agency, 2018).  

 

On the other hand, South Africa’s Department of Trade and Industry (DTI), through its 

endeavours to faciliate the country’s economic growth, wealth and job creation, has 

made the various establishment of institutions and  frameworks for supporting SMMEs. 

These institutions include the Small Enterprise Development Agecy (SEDA), Small 

Enterprise Finance Agency (SEFA), National Empowerment Funds (NEF) and 

frameworks, such as National Youth Economic Empowerment Strategy and 

Impementation Framework (NYEESIF) for 2009-2019 (DTI, 2009). The objective of all 

this frameworks and agencies are to improve the quality and quantity of youth 

entrepreneurship and technical knowledge, reduce poverty and uneployment amongst 

young people (DTI, 2009; Nieman & Nieuwenheuizen, 2009; Gwija, Ersia-Eke, & Lwu, 

2014). 

 

According to Beeka and Rimmington (2011), this suggests that entrepreneurship is one 

of numerous solutions to reduce youth and graduate unemployment in South Africa. 

However, the South African GEM Report (2016/2017) paints an alarming picture on the 

sustainability of small businesses in South Africa. According to the report, 67% of 



4 
 

businesses in 2016/2017 have closed down due to non-profitability. GEM suggest that 

this non-profitability is associated with a lack of business skills; poor ideas that are not 

marketable (miscalculation of opportunities); lack of access to market; lack of affordable 

and efficient support structures and infrastructure (transport, electricity, etc). The GEM 

Report (2016/2017) further states that non-profitability is associated with the fact that 

many entrepreneurs in South Africa are active in a saturated market that has high levels 

of competition, which in turn, threatens the stability of their businesses (Global 

Entrepreneurship Monitor, 2016/2017). 

 

It is evident that, despite the governmnet support provided to youth enterprises, such 

has not yielded the intented results, compared to literature on entrepreneurship 

discountinuation (Galawe, 2017). The study of Fatoki and Oni (2015) has stated that the 

inability to identify business opportunities, creativity and innovation are reasons for 

youth-owned enterprises fail or discountinue. Opportunity identification represents one 

of the most distictive and fundamental entrepreneurial behaviours. According to Fatoki 

and Oni (2015), entrepreneurial alertness helps to drive the process of opportunity 

identification. Alert entrepreneurs are likely to become competetive, creative and 

innovative and perform better than non-alert entrepreneurs.  

 

There is growing interest in the literature to investigate the entrepreneurial alertness as 

a construct rather than as variable under opportunity recognition literature. A study of 

Tang et al. (2012) has managed to make a significant contribution in the literature by 

exploring entrepreneurial alertness variables (scanning & search, association & 

connection and evaluation & judgement). The study conducted by Fatoki et al. (2015) 

has tested entrepreneurial alertness variables on enterprise performance of immigrants. 

However, the study was looking at innovation as the only determinant of enterprise 

performance. 

 

Following from the context and current state of youth entrepreneurs in South Africa, this 

study investigated the impact of Entrepreneurial Alertness (EA) and its dimensions, 

such as scanning and search; association and connections; and evaluation and 



5 
 

judgement on the performance of youth-owned  enterprises. The central questions 

asked in this study, is what impact does EA have on the enterprise performance? 

1.3 Problem statement 

Youth unemployment is a serious global problem, which seems to be much worse in 

South Africa, than in other countries as the youth constituted 63.4% of the unemployed 

population in the first quarter of 2019 (StatsSA, 2019). Youth are regarded as an 

unattractive labour force because of their inexperience and lack of knowledge and 

therefore participation in the labour market is difficult (Seabela & Fatoki, 2014). 

Moreover, the university degrees and diplomas are no longer holding the promise of 

jobs for young South Africans as large numbers of youth still battle to find jobs (Seabela 

& Fatoki, 2014). 

 

The notion of youth inexperience seems to be apparent in enterprise development, 

judging from the high level of failures or business discontinuations, despites efforts by 

government to provide assistance to youth-owned enterprises. This means that the 

government needs to find more ways to make entrepreneurship attractive to the South 

African youth and possibly include market opportunities. The identification of young 

people who already have their own enterprises and attempt to provide financial 

assistance to them is already taking place through agencies such as NYDA, however, 

the problem of business sustainability still persist (Majola, 2017). This therefore calls for 

a cognitive approach in looking at the individual’s intelligence and creativity to be alert to 

entrepreneurial knowledge. 

 

Recent scholars have continued to advance arguments that alertness involves a 

proactive stance, based on a number of cognitive capacities and processes, such as 

prior knowledge and experience, pattern recognition, information processing skills, and 

social interactions (Ardichvili, Cardozo, & Ray, 2003; Baron & Ensley, 2006; 

Shane,2000). McMullen and Shepherd (2006) state that alertness is never 

entrepreneurial unless it involves judgement and a move in the direction of taking an 

action. “To act on the possibility that one has identified an opportunity that is worth 



6 
 

pursuing” is at the heart of being an entrepreneur (McMullen & Shepherd, 2006, p. 132). 

The notion of McMullen and Shepherd (2006) linking the entrepreneur with alertness 

skills is central as the motivation of the study is to investigate the impact of 

entrepreneurial alertness on enterprise performance. 

1.4 Research objective 

The objective of the study is to investigate the impact of entrepreneurial alertness 

towards performance of youth-owned enterprises in South Africa.  

1.5 Resesrch questions 

What impact does entrepreneurial alertness have on the performance of youth-owned 

enterprises? 

Entrepreneurial alertness, in this study, includes three dimensions and the research 

questions are sub-divided accordingly, as stated below; 

- To what extant does scanning and search as dimension of EA impact enterprise 

performance? 

- To what extent does associstion and connection as dimension of EA impact 

enterprise perfomance? 

- To what extent does evaluation and judgement as dimension of EA impact 

enterprise performance? 

1.6 Contribution of the study 

In a country such as Malaysia, the study on opportunity recognition has been advanced 

(Sambasivan, Abdul, & Yusop, 2009; Khin, 2018; Lim & Xavier, 2015), where 

entrepreneurial alertness is mentioned as a variable and antecedent of opportunity 

recognition literature. From the study of Tang et al. (2012), improving on the literature of 

Kirzner (1979) on the entrepreneurial alertness, it is evident that entrepreneurial 

alertness is one of the cognitve skills that depends on the entrepreners’ intelligence. In 

the social cognitive theory perspective, the level of alertness can be imparted by 



7 
 

actively being involved in behaviour, action and experiential learning (Lumpkin & 

Lichtenstein, 2005). 

 

There are fewer studies concentrating on factors contributing to the variable of 

entrepreneurial alertness and how this variable in turn, affects dimensions of enterprise 

performance. Dutta and Crossan (2005) state that learning processes such as intuiting, 

interpreting, and institutionalising can have an impact on scanning and search, 

association and connection, and evaluation and judgement of entrepreneurial 

opprtunity. These views of Dutta and Crossan (2005) lack empirical evidence. 

 

This work addresses gaps in the literature of South African entrepreneurship, especially 

on entrepreneurial alertness. Much work has been conducted on entrepreneurship 

opportunity recognition, wherein entrepreneurial alertness serves as an antecedent of 

opportunity recognition. The high rate of failure of youth-owned enterprises at the rate of 

50% (Governder, 2019) has motivated the study and the contribution to the body of 

literature is to investigate cognitive skills embedded into entrepreneurial alertness to 

impact enterprise performance. This study explores dimensions of entrepreneurial 

alertness (scanning and search, association and connection and evaluation and 

judgement) towards enterprise performance.  The focus on performance is the focus on 

all dimensions of performance, which is different to what Fatoki and Oni (2015) have 

done in their study as they only looked at increase on sales as the variable testing 

performance.  The work of Wiklund (1999) suggests that performance measures should 

include both growth and financial measures. 

1.6.1 Theoritical contributions 

First, while previous studies indicate that alertness is an important determinant of 

entrepreneurial opportunity (Baron, 2006; Gaglio & Katz, 2001; Fatoki & Oni, 2015; 

Tang et al., 2012), theoritical specification and empirical examiniation of how alertness 

drives enterprise performance remains incomplete. This research addresses that gap in 

the entrepreneurship literature, by hypothesising dimensions of alertness on enterprise 

performance and creating the conceptual framework. This study argues how alertness, 



8 
 

as a cognitive entrepreneurial skill, influences enterprise performance, is predicted on 

the propensity of the young entrepreneurs to act, exploit opportunities, creativity and 

innovation (McMullen & Shepherd, 2006). 

 

Second, the study contributes to literature by providing information on the extent that 

each of the alertness dimensions impact performance. Studies such as Ardichvili et al. 

(2003); Kirzner (1979); Gaglio et al. (2001) provide enough evidence on the relationship 

between alertness and performance, but do not concentrate on alertness dimensions 

individually towards enterprise performance. 

1.6.2 Practical contributions 

This work also contributes to policy makers and entrepreneurial education providers, 

such as TVET Colleges and Development Finance Institutions (DFIs), to concentrate 

more in enhancing entrepreneurial alertness as a cognitive skill rather than just 

providing funding to youth enterprises. 

1.7 Delimitations of the study 

The study of entrepreneurial alertness assumes the coverage of entrepreneurial 

opportunity recognition and its antecedents, such as prior knowledge and social 

networks and entrepreneurial alertness. This study takes a different angle and tests 

entrepreneurial alertness as an independent construct with its own variables towards 

dependent variable enterprise performance. 

 

Secondly, the study of enterprise performance or business performance attempts to 

cover all five dimensions of performance. However, this study only looked at 

performance referring to business growth and financial performance. 

The study focused on youth-entrepreneurs in South Africa and because of time 

constraints, the data was collected in Gauteng, Limpopo, Free State, Kwa Zulu Natal 

and Northern Cape provinces only. It was impractical to collect data in all nine 

provinces. 

  



9 
 

1.8 Conceptual definition of terms 

Table 1.1: Definition of terms 

Terminology Definition 

Youth Youth refers to young people between the age of 18 and 35, as 

promulgated on the National Youth Development Agency Act (Act 

54 of 2008) (Gazette No. 31780, 2009) 

Entrepreneurship “Entrepreneurship is the recognition of an opportunity to create 

value, and the process of acting on this opportunity, whether or 

not it involves the formation of a new entity. While concepts such 

as ‘innovation’ and ‘risk-taking’ in particular are usually 

associated with entrepreneurship, they are not necessary to 

define the term” (Schoof, 2006, p. 12) 

Youth 

entrepreneurship 

“youth entrepreneurship involves the development of 

entrepreneurial attitude, skills and opportunities for young people 

between the age of 18 to 35, from the middle school though 

young adulthood” (Majola, 2017, p. 11) 

 

Alertness Alertness is defined as ”a process and perspective that helps 

some individuals to be more aware of changes, shifts, 

opportunities and overlooked possibilities” (Kirzner, 1979, p. 48) 

Performance According to Maltz (2003, cited in Rylková, 2015), organisational 

performance measurement should include five main dimensions, 

namely (Majola, 2017, p. 11):  

1. Financial (with indicators such as sales, profits and return 

on investment); 

2. Market and customer (with indicators such as customer 

satisfaction, retention, and service quality); 

3. Process (with indicators such as evaluation of the length 

and quality of processes); 

4. Staff development (with indicators such as employees’ 



10 
 

options, their motivation, and the capacity of information 

system); and 

5. Standards for the future (with indicators such as the depth 

and quality of strategic planning, forecasting and preparing 

for unexpected changes in the external environment, the 

possibility of joint ventures and strategic alliances, and 

investing in new market development). 

Source: (Majola, 2017) 

1.9 Assumptions 

- Those young entrepreneurs understood their business growth patterns. 

- That the respondents read the questionnaire properly. 

- Those young entrepreneurs were the real owners of the enterprises. 

  



11 
 

CHAPTER 2: LITERATURE REVIEW 

2.1 Introduction 

This section’s objective is to review the current literature. The study will first provide a 

background discussion on the literature, followed by the theoretical foundation, 

entrepreneurial alertness and enterprise performance, and lastly, it provides the 

conceptual framework. 

2.2 Background discussion 

A young person who can be classified as youth in South Africa is between the age of 18 

and 35 (National Youth Development Agency, 2018). A young person can be called a 

youth entrepreneur when he/she opens up a new enterprise and takes all the risks 

associated with the financial and social responsibility of the enterprise, plus daily 

operations (Xie & Lv, 2016). Entrepreneurship plays an important role into the economy 

and society (Rezvani, Lashgari, & Farsi, 2018). When entrepreneurs spot opportunities 

and take action to exploit them, they drive the process of market production and fulfils 

social and economic needs (Valliere, 2013). Tili and Tengeh (2017) state that the ability 

to identify entrepreneurial opportuties is considered as a core attribute in 

entrepreneurship literature. 

 

The debate whether opportunities are or can be recocognised, dicovered or created is 

on-going (Venkataraman, 1997; Shane, 2000; Klein, 2008). It is therefore not well 

known why some people are able to dicover opportunities and others do not (Rezvani et 

al., 2018). Kirzner (1979) has argued that the difference in individuals in identification of 

opportunities can only attributed by entreprenerial alertness, therefore many scholars 

argue that alertness is an antecendant of opportunity recognition (Baron, 2006b; Tang 

et al., 2012; Valliere, 2013). This means, for opportunitites to be first recognised, youth 

in South Africa must first be alerted (Fatoki, 2011a). 

 



12 
 

Valliere (2013) argues that alertness itself is based on the schemata  that must be 

activated, especially if such shemata are based on attributes for value creation. This 

activivation of schemata can be archived for example, by exposure to education, 

knowledge, skills or prior information (Baron, 2004a). Baron (2006) adds that alertness 

to new opprotunities is also by vatue of pattern recognition, with also supports the 

notion that patterns requires prior knowledge. Other than being exposed to prior 

information, Baron( 2006) mentions that entrepreneurial alertness is based on cognitve 

capacity with its ability to realise similarities that are meaningful. Alertness depends in 

part on whether entrepreneurs are able to exploits opportunities when once identified 

which is the result of their developed entrepreneurial capacities (Short, Ketchen, Shook, 

& Ireland, 2010). 

 

The relationship between entrepreneurial alertness and performance can be defined in 

the context of existing incentives in which the entreprenurs can obtain entrepreneurial 

opportunities that should boost innovative performance (McCaffrey, 2014). There is a 

growing body of literature that advocates that enterprise performance can be linked to 

growth and innovation as a result of the alert individual (Ardichvili et al, 2003; Tang et al, 

2012).  This is supported by Fatoki (2011a) that the enterprise‘s innovative activities and 

competitiveness can be enhanced by entrepreneurial alertness. Valliere (2011) adds 

that innovation and growth in youth entrepreneurship is the results of entrepreneurial 

processes where opportunities are spotted, planning conducted, execution of 

opportunities takes place and lastly, revenue is generated. 

2.3 Theoretical foundation 

Cognitive theory is the theory in psychology that attempts to explain human behaviour 

by understanding the thinking process. In order to analyse and understand the 

entrepreneur’s decisions and behaviours that lead to the success of the enterprise, it is 

crucial to understand youth cognitive processes and how they use prior knowledge 

(experience) in the success of their businesses (Urban, 2012; Baron, 2004). Cognitive 

theory postulates that everything that individuals do depends on mental process, 

meaning information is categorised and analysed within internal structures that 



13 
 

individuals develop during their life experience (Baron, 2006; Palich & Bagby, 1995; 

Rosch, 1978). Mitchell et al. (2002, p. 97) define entrepreneurial cognition as the 

knowledge structures that people use to make assessment, judgements or decisions 

involving opportunity evaluations and venture creation and growth. Baron (2004, 2006) 

emphasises the importance of considering the framework with the objective to promote 

entrepreneurial awareness, since it guides individuals to be alert to specific information.  

 

This framework emphasises knowledge development and provides four reasons: First, 

cognitive theory does not rely on inheritance or stability principles, but is based on the 

principles that individuals are able to develop their cognitive framework through 

significant experiences that they transform into knowledge (Baron, 2006b). Second, the 

cognitive approach asks questions such as “how do entrepreneurs think and perform 

certain activities (Mitchell, et al., 2002). The cognitive perspective describes the 

entrepreneur’s mind-set. Third, according to the cognitive perspective, every 

entrepreneur possesses a mental framework that is developed throughout life 

experience and is able to use these cognitive frameworks to make sense of the 

environment (Dutta & Crossan, 2005). Last, the cognitive perspective is used in 

opportunity recognition and regard opportunity recognition as the most important 

competency that must be developed before other technical competencies (Kuratko, 

2003; Pittaway & Cope, 2007). 

 

Entrepreneurial alertness is dependent on the cognitive skills and intellectual capacity of 

the individuals, coupled with prior knowledge (Lim & Xavier, 2015). Youth entrepreneurs 

are able to produce innovative and creative solutions in addressing the customer’s 

problems and that can be translated into improved business performance (Lim & Xavier, 

2015). Therefore, this theory provides the understanding that cognitive skills play a vital 

role in the overall competencies needed by youth entrepreneurs and that influences the 

performance of their businesses. 

 

The focus of this study is on the contribution of entrepreneurial alertness towards the 

success of youth owned-enterprises, rather than entrepreneurial alertness as an 



14 
 

antecedent of opportunity recognition as most literature focuses on (Venkataraman, 

1997; Tang et al 2012; Ardichvili, Cardozo, & Ray, 2003; Shane & Venkataraman, 2000; 

Shane, 2000). 

2.4 Entrepreneurial alertness and enterprise performance 

In entrepreneurial opportunity literature, alertness has been identified as a vital 

entrepreneurial characteristic that is defined as the “ability to notice without search 

opportunities that have been overlooked by others” (Kirzner, 1979, p. 48). It is therefore, 

suggested that entrepreneurial alertness reflects an entrepreneurial ability to recognise 

an opportunity ahead of others (Gaglio & Katz, 2001) and such can be translated into 

financial gain (Tang et al., 2012). According to Tang et al. (2012), the major coverage 

point is that alert entrepreneurs have greater capabilities to recognise profitable 

opprtunities. Linking alertness to enterprise performance through opportunity 

recognition, requires that entrepreneurs take action for opportunities to yield commercial 

maturity (McMullen & Shepherd, 2006). Shane et al. (2003) also add that the 

appropriateness of opportunities is positively related to venture performance, meaning 

its only called a good opportrunity if it has a direct impact on enterprise performance. 

Adomako et al. (2018) allude that existing literature linking alertness and performance 

lacks theorisation of the entrepreneurial action machanism connecting entrepreneurial 

alertness to performance. 

 

The study by Tang et al. (2012) however, links alertness to performance throungh 

innovation. According to Fatoki and Oni (2015a), a firm’s innovative activities and 

competitive actions are enhanced by entrepreneurial alertness and that can lead to 

positive firm’s performance. Amato et al. (2017), in extending the work of Shane, 

Kolvereid, and Westheas (1991), also support the notion that alertness is positively 

related to the firm’s innovatioveness. It is also imperative to note that identifying and 

selecting the most appropriate and potentially profitable opportunities for new or existing 

business is the most important activity carried out by enterpreneurs (Amato, Baron, 

Barbieri, Belanger, & Pierro, 2017).  

 



15 
 

Entrepreneurs with high levels of entrepreneurial alertness can accurately locate 

resources when confronted with a changing market environment (Xie & Lv, 2016). 

Adaptation to a new environment becomes easier, and therefore ensures the survival of 

enterprises and the improvement of enterprise peformance (Gaglio & Katz, 2001). 

Adding to this notion, Roundy and partners (2018) state that facing environmental 

disruptions, alert decision makers will be more likely to engage in a strategic decision 

change compared to less alert individuals. However, these authors acknowledge the 

lack of empirical evidence susbstantiating environmental adoption to enterprise 

performance (Roundy, Harrison, Khavul, Perez-Nordtvedt, & McGee, 2018). 

 

Entrepreneurs with high levels of alertness also are more skillful in discovering new 

opportunities through social networks (Ardichvili et al., 2003). For example, young 

entrepreneurs in fashion can use social networks to optain new key partners important 

to their value chain and in return, such opportunities can be trasnlated into financial 

growth. Individuals with high levels of entrpreneurial alertness make efforts to expand 

and establish new social networks (Xie & Lv, 2016). Social networks provide information 

and resources and this enhances the performance of enterprises through the integration 

and utilisation of information and resources (Xie & Lv, 2016; Ardichvili, Cardozo, & Ray, 

2003). 

 

On this note,  entrepreneurial alertness linkage to enterprise performance can be 

conceptualised as a cognitive resource that affords entrepreneurs a first hand 

opportunity ahead of others and who are then able to take action towards such 

opportunity (Adomako, Danso, Boso, & Narteh, 2018). The ownership of cognitive 

resources by entrepreneurs might not on itself be translated to business performance; 

its effect is likely to be determined by entrepreneurs’ ability to exploit an opportunity 

ahead of others (Teece, 2012). 

2.5 Enterprise performance 

According to Gavrea et al. (2011), organisational performance can be conceptualised as 

a set of financial and non-financial indicators that offer information on the degree of 



16 
 

achievement of objectives and results. Gavrea and partners (2011) further state that 

performance may be illustrated by using a causal model that describes how current 

actions may affect future results. Performance may be understood differently depending 

on the person involved in the assessment of the organisational performance (e.g., 

performance can be understood differently from a person within the organisation 

compared to one from outside (Majola, 2017). 

 

Performance of any enterprise has a big impact on a country’s economy. Enterprises 

are a significant source of employment and are often used to determine the economic, 

social, and political progress of a country (Gavrea, Lllies, & Stegerean, 2011). Through 

performance, the organisation can determine in the best way, whether it is growing and 

progressing, hence amount of management’s time is invested in investigating 

performance indicators (Gavrea et al, 2011). 

 

The 1980s and 1990s mark the years where the realisation that the identification of 

organisational objectives is more complex than initially considered. According to Gavrea 

et al. (2011), amongst the organisational objectives lies the enterprise performance. 

Gavrea et al. (2011) further explain that managers began to understand that an 

organisation is successful if it accomplishes its goals (effectiveness) using a minimum of 

resources (efficiency). There are several performance indicators researcher use to 

measure performance, and profit often used Gavrea et al (2011). 

 

However, according to Lim and Xavier (2015), growth together with profitability are the 

most frequently used performance dimensions, while Rylkova (2015), cited in Majola 

(2017), states that performance measurement should include five main dimensions. In 

addition, he alluded that these dimensions are; Finance, profit and Return on 

investment (ROI); Marketing and customers; Processes; Staff development and 

Standard for the future. 

 

Wiklund (2006), cited in Galawe (2017), argues that performance can be measured 

using two dimensions, which are growth and financial performance. Wiklund (2006) 



17 
 

states that both dimensions are sought to be used simultaneously, in order to provide a 

richer description of firm performance that when each is used independently. 

 

Table 2.1: Two types of performance measure  

Growth Financial performance 

- Sales (volume) 

- Employment  

- Assets  

- Market share  

- Office space  

- Growth rate compared to competitors 

o Sales  

o Market value  

- Revenue (Rands)  

- Profitability  

- Gross Margin  

- Cash flow  

- FP Compared to competitors 

o Profits  

o Cash flow  

Source: (Wiklund, 2006; Galawe, 2017) 

 

This paper, therefore, argues that enterprise performance can be influenced by 

entrepreneurial alertness. Borrowing from Cognitive Theory, we further posit that 

innovation is the bigger performance driver as the theory advocates the possession of 

cognitive skills embedded in the individual person. 

2.6 Entrepreneurial alertness 

Several scholars agree that entrepreneurs are individuals who are more alert in the 

identification and discovery of opportunities than others (Shane & Venkataraman, 2000; 

Schumpeter, 1934; Kirzner, 1979). Alertness has been central in the context of 

opportunities in the recent developing entrepreneurship research (Tang et al., 2012). In 

an environment where opportunities frequently arise, remaining alert is profitable, 

Venter, et al. (2017) explain the situation by saying that the development process 

begins when entrepreneurial alertness exceeds a threshold level. This gives people the 

incentives to search for and be alert to entrepreneurial opportunities and this creates 

more entrepreneurial alertness (Eckhardt & Shane, 2003). 

 

The literature on entrepreneurial alertness was developed by Kirzner in 1973 to provide 

an explanation of entrepreneurial process. Alertness is defined as a process and 

perspective that helps some individuals to be more aware of changes, shifts, 



18 
 

opportunities and overlooked possibilities (Kirzner, 1979, p. 48). Kirzner (1973) further 

classified individuals who are more alert as having an “antenna” that allows recognition 

of gaps with limited clues, while Kaish and Gilad (1991) refer to the individual having 

alertness as one who possesses unique preparedness and consistently scans the 

environment to discover hidden opportunities. Kirzner (1985) further posit that non-alert 

individuals will fail to identify opportunities because they may not seek out pertinent 

information and misjudge the market environment. Alertness is described as a 

continuous state of being “on call” (Aviram, 2010). 

 

Work done by McMullen and Shepherd (2006) cited in Tang and partners (2012) argues 

that alertness involves a proactive stance, based on a number of cognitive capacities 

and processes such as prior knowledge and experience, pattern recognition, 

information processing skills and social interactions (Ardichvili, Cardozo, & Ray, 2003; 

Baron, 2006b; Gaglio & Katz, 2001; Shane, 2000). McMullen and Shepherd (2006) 

provide the summary of developing views of alertness as thus; 

 

 

Table 2.2: Developing views of alertness  

 Early Kirzner Later Kirzner Recent Development 

Role of markets Disequilibrium gaps to 

be identified 

Adjustments of 

opportunities to fit the 

market 

Opportunities emerge 

from macro changes 

Role of knowledge 

and pre-existing 

conditions 

Helpful to the extent 

that it triggers the 

“Aha” moment 

Prior knowledge can be 

expanded to further 

pursue opportunities 

Prior knowledge and 

information processing 

inform observations 

and feasibility 

assessment 

Alert scanning and 

search 

Passive; a unique 

preparedness 

Passive and active; pursue 

specific opportunities 

Cognitive capacity (e.g. 

creativity, intelligence) 

and personal fit 

Alert association and 

scanning 

Lying dormant waiting 

to be identified 

Still lying dormant but 

room for creativity and 

further development 

Initial insight heightens 

sensitivity and can 

produce further search 

and processing 

Alert evaluation and 

judgement 

Largely unaddressed, 

assumed that 

entrepreneurs would 

act on opportunities 

Evaluations of 

opportunities can evolve 

over time 

Combining beliefs/ 

insights and desires for 

a judgement on venture 

prospects: distinction 

between first-and-third- 

person opportunities 

Source: (McMullen & Shepherd, 2006; Baron, 2006; Tang, Kacmar, & Busenitz, 2012) 



19 
 

From the views of McMullen and Shepherd (2006) in Table 2.1, alertness can be 

conceptualised in three dimensions: Scanning and search, association and connection, 

and evaluation and judgement (Tang, Kacmar, & Busenitz, 2012). In order for this study 

to achieve its objectives, these dimensions are explored in the context of its impact 

towards enterprise performance. 

2.6.1 Scanning and search 

Scanning and search allows entrepreneurs to be determined and progressive in their 

efforts to investigate new ideas. This dimension involves prior knowledge, awareness 

and sensitivity to new opportunities (Lim & Xavier, 2015). Scanning and search will 

enable the entrepreneurs to examine new ideas in a progressive manner as in the 

process, they increase the entrepreneur’s domain-relevant information (Tang et al 

,2012). Scanning and search also refers to continuous scanning of the environment to 

identify information or changes that are overlooked or unnoticed by other individuals 

(Fatoki, 2011a; Urban, 2019) 

 

The scanning and search dimension helps in the formulation of a cognitive framework 

(i.e. prototypes and schemas that reflect an individual’s knowledge and beliefs about the 

external world); such frameworks represent the increasing experience, learning, and 

knowledge (Tang et al., 2012). The stock of knowledge and information for 

entrepreneurs provides them with the competitive advantage and in turn, can boost 

business performance. This study therefore hypothesises, that; 

 

H1: Scanning and search as dimension of Entrepreneurial Alertness (EA) has a 

positive impact on enterprise performance 

2.6.2 Association and connection 

Association and connection dimension involves putting together scatted pieces of 

information and reassembling them into comprehensible alternatives (Lim & Xavier, 

2015). This dimension focuses on the availability of new information, creativity and 

making extensions in logic. It accounts for how new information is applied or extended 



20 
 

(Tang et al., 2012). Tang and partners (2012) adds that association and connection is 

all about connecting dots to creating new alternative information. 

 

Once dots are connected, individuals may need to re-assess the environment to further 

clarify the picture or to explore the usefulness of the newly connected information (Tang 

et al, 2012). Individuals are unlikely to go from scanning and search to making an on-

the-spot judgment about the potentiality of the new connections, rather, the newly 

gathered information has to be interpreted and perhaps considered for more 

assessment in order to be certain of its potentiality (Tang et al., 2012). Young 

entrepreneurs who have various options on the information are considered to be 

advanced on information, therefore we hypothesis that; 

 

H2: Associations and connection as dimension of Entrepreneurial Alertness 

(EA) has a positive impact on enterprise performance 

2.6.3 Evaluation and Judgement  

This dimension is based on the predictions of potentiality of new information and the 

effects of business opportunity (Tang et al., 2012). When evaluation and judgement is 

conducted correctly, this can streamline the collection and interpretation of new and 

relevant information ensuring that information is correctly processed while 

simultaneously disregarding extraneous or useless information and knowledge (Cox, 

2016). Relevant knowledge and information directly contributes to one’s ability to 

identify opportunities and aids in the development of the opportunities (Baron, 2006b; 

Shane, 2000). 

 

Judgement is necessarily associated with the evaluation of new information in the 

context of its usefulness and value for the creation of new opportunities (Cox, 2016). 

Effective judgement can distinguish between information capable of yielding new 

innovative solution in the form of opportunities that are perceived as novel (Valliere, 

2013).  This dimension further enables individuals to distinguish between what is 

profitable and non-profitable, and high-value versus low-value opportunities (Tang et al 



21 
 

2012). Lim and Xavier (2015) refer to this dimension as decisions to be made on the 

effect of business opportunity and profit potentials. Profitability is one of the dimensions 

of business performance and therefore, we hypothesises that; 

 

H3: Evaluation and judgement as dimension of Entrepreneurial Alertness (EA) 

has a positive impact on enterprise performance. 

 

2.7 Conceptual framework 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
 
Figure 2.1: Conceptual framework  

 

Source: (Rezvani et al, 2018; Adomako et al, 2018; Fatoki & Oni, 2015a; Roundy et al, 

2018; Tang et al, 2012) 

2.8 Summary of the chapter 

This chapter put forth the theory that underpins the study and connected the constructs 

and its variables. The construct, entrepreneurial alertness (EA) has the following 

 

 
Entrepreneurial 

alertness 

Scanning and 

search 

Association and 

connection 

Evaluation and 

judgement 

Youth-owned 

enterprise 

performance 

H1 

H2 

H3 



22 
 

variables; scanning and search, association and connection and lastly, evaluation and 

judgement. Then, entrepreneurial alertness has a positive impact on the enterprise 

performance construct. Hypotheses were proposed and a conceptual framework 

created to provide the picture. In the following chapter, the research methodology is 

outlined. 

  



23 
 

CHAPTER 3: RESEARCH METHODOLOGY 

3.1 Introduction 

The aim of this section was to describe in detail, the research methodology that was 

used and to address the research and hypotheses put forward for this study. The 

section includes the research design, data collection and sampling, the research 

instruments, data analysis, ethical consideration and summary of the chapter. 

3.2 Research design 

This study is quantitative in nature. Quantitative research is a positivist method and is 

based on numerical data on which the researcher relies (Taylor & Medina, 2011). In 

quantitative methods, the data is presented by numbers and hence several statistical 

analyses can be applied which are quantitative in nature (Greenstein, 2003 cited in 

Gunda, 2013). Quantitative is ideal for this research because it is a statistically based 

study and the data is analysed in numerical form and this research measures youth-

owned enterprise performance against entrepreneurial alertness (alert scanning and 

search, alert association and connection and evaluation and judgement). A positivist 

research paradigm is appropriate for this study because the research takes on an 

objective focus (Creswell & Creswell, 2017). 

 

A quantitative research methodology brings out the relationship of the variables of this 

research making use of numerical data. It is a multivariate study consisting of more than 

two variables (Daniel, 2016), in this case, four variables. The dependent variable is 

enterprise performance whilst the independent variables are scanning and searching, 

association and connection and evaluation and judgement.  The independent variables 

are used as elements in the entrepreneurial alertness as a cognitive competency a 

person must have. 

 

The assumption is that quantitative methodology allows for a large sample size and the 

researcher’s involvement is limited therefore preventing bias (Cooper & Schindler, 



24 
 

2008). Ontologically the researcher assumes that the external reality is comprised of 

facts that are “law-like” and provide structure or a theoretical framework to this reality 

(Eisner, 1981). Methodological and ontological assumptions in an empirical-analytical 

inquiry are characterised by the researcher’s detached or objective review from the 

setting under study (Eisner, 1981; Smith, 1983).  The empirical results of this study 

contribute to literature on what impact cognitive skills, such as entrepreneurial alertness, 

has on enterprise performance. 

 

This research is conducted for the purpose of partial fulfilment of a Master of 

Management degree. The degree is made out of course work and a mini-dissertation 

that must be fulfilled within a period of a year, therefore has a time constraint, hence a 

cross-sectional quantitative research was used. Cross-sectional research methodology 

captures a “moment in time” (Cooper & Schindler, 2008). Online, self-administrated 

questionnaires were distributed using social media platforms, such as WhatsApp, twitter 

and Instagram to all youth-owned entrepreneurs, in order to collect primary data. 

 

The advantage of using cross-sectional quantitative data, collected by distributing an 

online link, created using Qualtrics Software, is that it was easy to share the link and to 

code the collected data for transfer to SPSS system, where analysis of data was 

conducted 

 

A survey questionnaire however, is limiting in the fact that: 

- There is no contact with the respondents hence no chance of further explanation 

of a question or requirements 

- Responding and finishing the survey is absolutely at the discretion of the 

respondents 

- There is a chance of the research being disregarded as spam due to many 

surveys circling the web. 



25 
 

3.3 Data collection and sampling 

In order to collect primary data, a link providing access to the questionnaire was 

distributed to youth entrepreneurs using different social media platforms, and was not 

limited to SMSs and emails. Simple random sampling was used to identify the sample. 

This procedure was used to “select a sample of n objects strictly by chance, the 

selection of one member does not influence the selection of any other member, each 

member of population is equally likely to be chosen, and every possible sample of a 

given size N,  has the same chance of selection” (Newbold, Carlson, & Thorne, 2013, p. 

3). 

3.3.1 Population 

A population is defined as people or unit of analysis that possess the characteristics on 

which one wishes to focus their research (Bhattacherjee, 2012). According to Newbold 

et al. (2013), a complete set of all items that interest an investigator is considered a 

population, and its size (n) can be very large or even infinite (∞). The units of analysis 

for this study was South Africans between the ages of 18 and 35 years who are self-

employed or running their own enterprises. The areas to be used predominantly was 

Gauteng, Limpopo, Free State, KwaZulu Natal and Northern Cape provinces. Due to 

time constraints, it was not possible to collect data from individual business owners from 

all nine provinces. It is not the interest of this study to focus on geographic type (i.e. 

urban or rural). 

3.3.2 Sampling method 

Newbold et al. (2013) define a sample as a practical portion or subset of a population 

with the size of the sample given as “N”. Sampling involves ensuring that the 

questionnaire is administered to the targeted populations (Slavec & Drnovsek, 2012). 

Although there is no specification about the size of a sample, there are two 

recommendations to be considered, first, the sample of subjects should be large 

(Slavec & Drnovsek, 2012), and second, as the number of items increase, the number 

of respondents should increase (Slavec & Drnovsek, 2012). 



26 
 

 

The sample was derived from youth entrepreneurs between the ages of 18 and 35 

years, who own businesses in South Africa and belonged to specific youth 

organisations or forum that had national representation. These forums have helped the 

researcher  to reach youth entrepreneurs from provinces such as; Gauteng, Limpopo, 

Free State, KwaZulu Natal and Northern Cape cost-effectively and with fewer 

complications.  

 

Sampling random is used to identify the sample. This procedure is used to “select a 

sample of an object from a population in such a way that each member of the 

population is chosen strictly by chance. The selection of one member does not influence 

the selection of any other member, each member of the population is equally likely to be 

chosen, and every possible sample of a given size, n, has the same chance of 

selection” (Newbold, Carlson, & Thorne, 2013). 

3.3.3 Sampling frame 

The study’s sampling frame was designed in a way that would produce general 

representation of the sample from the following provinces; Gauteng, Limpopo, Free 

State, KwaZulu Natal and Northern Cape in South Africa. The sample frame was youth 

between the ages of 18 and 35 years who own business in various industries and keeps 

records of their businesses, in order to understand their business performance. This 

youth must have social media accounts (WhatsApp, Facebook, Twitter and Instagram). 

 

A few social media group accounts were identified with mass number of youth 

entrepreneurs, such as Facebook: AFASA Youth – National, Facebook: Local 

Government Youth Development Forum, Facebook: Independent Thinkers of South 

Africa, Facebook: Youth Entrepreneurship Campaign, Facebook: Sedibeng Youth 

Chamber of Commerce & Industry – SYCCI, Facebook: ICT SMME Chamber, Twitter: 

@djsbu, Twitter: @VusiThembekwayo and Twitter: @NYDARSA. 

 



27 
 

This approach assisted the researcher  to reach respondents from all nine province in s 

limited period. In order to avoid exclusion of youth entrepreneurs that were not 

members of the mentioned Facebook pages and following either @djsbu and 

@VusiThembekwayo, I also posted the link to the survey on my personal Facebook, 

twitter and Instagram walls. 

3.3.4 Sample size 

There is not clear indication as, how many participants had accessed the survey 

especially from Facebook, twitter and Instagram, the platforms holds many potential 

respondents, however as for WhatsApp messages sent, there is approximate 1500 

messages sent. A total of 129 of the responses were viable, 7 did not consent and 

considered unusable, and 11 had missing data. Therefore, the analysis is based on a 

sample size of 126 with 3 outliers that were removed. 

 

There are specific requirements as to how big the sample size should be to perform 

certain statistical tests and statistical analysis. Because factor analysis and multiple 

regression analysis were used, it was necessary to consider the minimum sample sizes 

required in order to perform such statistical procedures. 

 

There are no clear theories on how to determine the optimal sample size for both factor 

and multiple analysis, thus the different views in literature are just rules of thumb. 

However, the general agreement in factor analysis, is that the higher the commonalities, 

the lower the required sample size (Field, 2013).  

3.4 The research instrument 

The research instrument that was used for this study was a self-administered online 

questionnaire. Self-administered online questionnaire is the most advantageous method 

as it “permits for easy geographical reach” (Galawe, 2017). Cooper and Schindler 

(2014) further states more advantages of using online survey such as, fixed and low 

cost, data can be collected from large samples and it is easy to administer. The online 



28 
 

survey was suitable for this study for the purpose of reaching large sample easily and 

cost effectively (Wiklund, 2006; Cooper & Schindler, 2008). 

 

The research instrument contained multi-item scales to measure the independent and 

dependent variables. Multi-item scale type questions are often used in social science 

researches due to subjective and difficulties to measure variables, sometimes difficult to 

just measure with a single question (Galawe, 2017; Zikmund, 2003). The questions 

testing independent variables are based on a 7-point Likert scale: 1 = strongly disagree 

– 7 = strongly agree, while questions testing dependent variables are based on 5-point 

satisfactory scale: where, 1= very dissatisfied – 5=very satisfied. Another study by Yang 

(2008) created a business performance scale that contained eight items and used a 

seven-point Likert scale. The four indicators of growth were: sales growth, employment 

growth, sales growth compared to competitors, and market share compared to 

competitors. The three financial performance indicators were gross profit, return on 

sales (ROA), and return on investment (ROI). The final indicator was one of overall 

performance/ success to business performance adapted from Lumpkin and Dess 

(1996).  The work of Wiklund (1999) suggests that performance measures should 

include both growth and financial measures and therefore it was an objective of this 

study to factor in both growth and financial dimensions to make sense of the dependent 

variable. 

 

All of the questions of the research instrument are forced questions in an effort to try to 

avoid receiving incomplete questionnaires. In order to measure the impact of 

entrepreneurial alertness to youth-owned enterprises, three variables of the alertness 

construct was tested. Scales from previous studies were used to obtain some level of 

reliability and such scales had excellent Cronbach Alpha. The Table 3.1 provides 

summarised different sections of the research instrument: 

 

 

 



29 
 

Table 3.1: Research instrument summary 

Section Description Source of question 
Type of 

questions 
Comments 

SECTION A: 

Demographic 

This section collected 

demographic information 

of the respondents such 

as gender, age, race, level 

of education, industry, 

length of time in business 

and lastly number of 

employees. 

Adapted from Majola 

(2017) 

Multiple 

choice 

 Gender and race is important to determine the 

representatives. According to Netshitenzhe (2013) 

woman are amonst the previously disadvantaged and 

continue to be sidelined in business.  

 There is strong correlation between age and education 

level amongst youth entrepreneurs in South Africa 

(GEM, 2016/2017) 

 Age of business and number of employee also have 

correlations (GEM, 2016/2017) 

SECTION B: 

Entrepreneurial 

alertness 

This section collected 

information of three 

dimensions: 

(1) Scanning and search 

(2) Association and 

connection 

(3) Evaluation and 

judgement 

Adapted from (Tang 

et al., 2012; Tang, 

Tan et al., 2008) 

7 Point 

Likert scale 

 Study of Tang et al. (2012) developed 13 questions to 

test the alertness scale and the study demonstrated 

appropriate dimensionality and strong reliability. 

 Scanning and search had 6 questions, Association and 

judgement had 3 questions and Evaluation and 

judgement  had 4 questions 

SECTION C: 

Enterprise 

performance 

This section collects data 

on the business 

performance, which 

operationalized as growth, 

profitability and ability to 

self-fund. 

(Covin & Slevin, 

1989) 

5-Point 

Satisfactory 

scale 

 Each of these financial performance criteria were 

assessed; sales level, sales growth rate, cash flow, 

return on shareholders’ equity, gross profit, net profit 

from operations, and profit to sales ratio return on 

investment, and ability to fund business growth from 

profit (Fatoki, 2011a). 

Source: Primary data



30 
 

3.5 Data analysis 

Data was collected using a Qualtrics generated questionnaire and was exported to 

SPSS for data analysis. Once data was imported into SPSS and coded, the data was 

cleaned and all errors removed. The errors in the data could be contributed by missing 

values. 

3.5.1 Descriptive statistics 

Newbold et al. (2013) define descriptive statistics as graphical and numerical 

procedures that are used to summarise and process data. The demographic data of the 

sample and data collected are presented in tables and graphs in Chapter 4 and 

interpreted in Chapter 5. 

3.5.2 Exploratory factor analysis: validity 

Validity focuses on whether the research accomplishes accurately an explanation of the 

concept that the researcher is measuring, the extent to which the conclusions of the 

study are supported by its design. It is folded into two; internal and external validity 

 

Internal validity is concerned with the results of the study, if they are acceptable 

because of the sample selection, data recording, or analysis (Handley, 2001). Internal 

validity states that the outcomes of the data might be skewed, based on how or where 

the survey is distributed, for example, if the survey is distributed online only. For the 

research design to be termed internal valid, it must isolate the effects of the variables 

used in the research such that they can be measured separately (Handley, 2001). 

 

External validity is also known as generalisability. External validity measures if the 

outcomes of the study would be the same in a different environment with a different 

subject (Handley, 2001). It is advisable to use a research instrument that has been used 

several times, with the same or similar outcomes, as this increases its validity. 



31 
 

3.5.3 Cronbach’s alpha: Reliability 

Reliability is the consistency of the research instrument whether it can yield a certain 

results when the object being measured is the same (Leedy & Omrod, 2005).  Factors 

affecting reliability include the lack of understanding of the research questions (Leedy & 

Omrod, 2005). Tavakol and Dennick (2011) outline the relationship between validity and 

reliability as thus; 

- Validity is concerned with the extent to which an instrument measures what it is 

intended to measure; 

- Reliability is concerned with the ability of an instrument to measure consistently; 

- The reliability of an instrument is closely associated with its validity; 

- An instrument cannot be valid unless it is reliable, however, 

- The reliability of an instrument does not depend on its validity. 

 

It is possible to measure effectively the reliability of a research instrument using 

Cronbach’s alpha. Cronbach’s Alpha was developed by Lee Cronbach in 1951, to 

measure internal consistency of a test or scale (Tavakol & Dennick, 2011). The 

acceptable values of alpha range from 0.70 to 0.95. A low alpha measurement could be 

because of poor interrelatedness between items, heterogeneous constructs or too few 

questions (Tavakol & Dennick, 2011). 

3.6 Correlation analysis 

Correlation analysis is used to evaluate the relationship between two variables; it 

generally tests the direction and strength of the relationship (Newbold et al., 2013). It 

looked at the relationships of the dependent variables (Enterprise Performance) and 

each of the independent variables (Alert scanning and search, Alert association and 

connection and Evaluation and judgement) and the independent variables against each 

other. This is done to look out for cases of multicollinearity. 



32 
 

3.7 Multiple regression 

The multiple regression model determines the effect of several independent variables 

individually and concurrently on the dependent variables, using the least squares 

principles (Newbold, Carlson, & Thorne, 2013). There is a process to follow when 

developing the multiple regression model: first, develop the model specifically by 

determining the model variables and model form; second, study the least squares 

process and analyse the variability to identify the effects of each predictor variable; 

third, examine the estimation, confidence intervals, and hypothesis testing (Newbold et 

al., 2013). 

3.8 Ethical considerations 

Ethics are described as behavioural norms or standards that guide moral choices 

related to our relationships with others (Cooper & Schindler, 2008). Cooper and 

Schindler (2008) further states that as in business, research must strive to be ethical to 

ensure that research activities do not lead to adverse consequences to anyone and also 

that participants do not suffer embarrassment, loss of privacy, discomfort or pain.  In 

order for research to be ethically, researcher must (Cooper & Schindler, 2008, p. 90): 

- Give participants an option to agree or disagree to participate in the research. 

- Be honest about the purpose, benefit and confidentiality of the research. 

- Demonstrate integrity during the research process 

- Guarantee the right to privacy and ensure the protection of participants. 

 

The researcher took the following steps to adhere to ethical considerations in this study; 

- The University of Witwatersrand’s Ethical Committee issued out official ethical 

certificate as the first go-head procedure. 

- The cover page detailing the purpose and benefits where attached to 

questionnaire. For the questionnaires send via WhatsApp, such cover was send 

as first slide then followed by link to the questionnaire. 

- The first question on the questionnaire was a consent option that was set to “Exit 

the participation” if participants choice “no” to consent. This option has ensured 



33 
 

that participants are not forced to participate in the study and that participation if 

completely voluntarily. 

- No personal information has been asked on the questionnaire in order to keep 

responses strictly anonymous. 

- The results of the survey will be destroyed after the research report is published 

3.9 Summary of the chapter  

This chapter focused on the research methodology that included philosophy and 

paradigms. The study was a quantitative and was presented in numbers hence several 

statistical analysis were applied. The SPSS V25 software system was used for 

descriptive and exploratory factor analysis from the data collected using self-

administered questionnaire.  

 

Youth between the ages of 18 – 35 operating businesses in South Africa took part in the 

study. Because the study has used online survey the random sampling was adopted 

with could not be quantified, but has achieved 147 usable observations. The survey was 

distributed amongst different social media groups with number of youth enterprise 

owners. 

 

Data was screened and cleaned to ensure integrity and quality of data is not 

compromised. Incomplete responses and responses containing outliers were removed. 

The reliability and validity of the measurements scales were tested and it was found that 

they are reliable and valid. 

 

The study further performed correlation analysis and multiple regression to establish the 

factor structure I order to determine the degree and form of the relationship between 

Independent variables and Dependent variables and lastly to test hypothesis of the 

study. 

 

  



34 
 

CHAPTER 4: PRESENTATION OF RESULTS 

4.1 Introduction 

The objective of this chapter is to present the results and interpretation. The chapter 

begins with demographic results of the participants, followed by descriptive analysis of 

the participants, reliability of the measuring scale, explorative factor analysis, 

hierarchical multiple regression, and then lastly, testing of hypotheses.  

4.2 Data screening 

The survey was sent through social media (WhatsApp, Facebook, twitter and 

Instagram); it also included email. The survey managed to attract 147 respondents in 

total, seven respondents never consent to participate, 11 contained much missing data 

and therefore were regarded as invalid. There were three outliers found in the data and 

removed. The results are thus analysed from 126 respondents. 

4.3 Demographic profile of respondents 

This section presents the demographic information of the respondents and includes 

gender with race, age group, enterprise industry, age of business and lastly, number of 

employees. 

4.3.1 Gender and race 

Sample characteristics results reveal that more males (52.4%) than females (47.6%) 

were sampled overall. Most of the respondents were African at the total number of 120, 

followed by Coloured at the total number of three, then whites and Indian by one 

respondent respectively. Table 4.1 illustrates how the sample is distributed according to 

gender and race combined. 

 

 

 

 



35 
 

Table 4.1: Gender and Race Cross-tabulation 

 
Race 

Total African Coloured Indian White Other 

Gender Male Count 62 2 1 0 1 66 

% within Race 51.7% 66.7% 100.0% 0.0% 100.0% 52.4% 

Female Count 58 1 0 1 0 60 

% within Race 48.3% 33.3% 0.0% 100.0% 0.0% 47.6% 

Total Count 120 3 1 1 1 126 

% within Race 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 

Source: Primary data 

4.3.2 Age group 

Table 4.2 shows that most respondents (45.2%) were in the 25-29 age group, followed 

by the 30-35 age group (44.4%) and lastly 18-23 age group (10.3%). According to GEM 

Global Report 2016/2017, there is relatively lower entrepreneurial occurrence amongst 

18 – 24 years cohort, and relatively higher occurrence amongst 25 – 34 years cohort 

(Global Entrepreneurship Monitor, 2016/2017). GEM further states that the higher the 

age, the more the decline in entrepreneurial participation.  

 

Table 4.2: Age Group  
 Frequency Percent Valid Percent Cumulative Percent 

Valid 18 - 23 13 10.3 10.3 10.3 

25 - 29 57 45.2 45.2 55.6 

30 - 35 56 44.4 44.4 100.0 

Total 126 100.0 100.0  

Source: Primary data 

4.3.3 Education 

The majority of the respondents (47.6%) had tertiary education, that is, a total number 

of 60, followed by those who had completed secondary education (matriculated) at 

38.9% which is total number of 49, followed by 10 and seven respondents who have not 

completed secondary education and those who hold post-graduate qualifications, 

respectively. This sample was largely distributed using WhatsApp that needed 



36 
 

understanding of how to access the link directly from the WhatsApp. Figure 4.1 

illustrates the education percentage distribution on the respondents. 

 

 

Figure 4.1: Highest Education Completed  

Source: Primary data 

4.3.4 Enterprise Industry 

The majority of respondents (34.1%) have chosen “Other”, followed by 19.8% of the 

respondents who are in the manufacturing sector, followed by 14.3% of the respondents 

in wholesale and retail trade, repair of motor vehicles, motor cycles and personal and 

household goods, hotels and restaurants.  The major contributors to the number is 

mainly wholesale and retail, as suggested by the GEM Report (Global Entrepreneurship 

Monitor, 2016/2017). According to GEM, wholesale and retail requires fewer skills and 

lower capital requirements and therefore attracts a lot of entrepreneurial activities 

(Global Entrepreneurship Monitor, 2016/2017). There is also relatively good 

participation at 12.7% in community, social and personal services from the respondents. 

Industries such as agriculture, hunting, forestry, fishing, electricity, gas, water supply, 

financial inter-mediation, insurance, real estate, business services, transport, storage, 

accommodation and construction share between one to six respondents. Table 4.3 

illustrates industrial domination from respondents. 



37 
 

Table 4.3: Industry of your enterprise  

 Frequency Percent 

Valid 

Percent 

Cumulative 

Percent 

V
a

lid
 

Agriculture, hunting, forestry and fishing 3 2.4 2.4 2.4 

Manufacturing 25 19.8 19.8 22.2 

Electricity, gas and water supply 1 .8 .8 23.0 

Construction 12 9.5 9.5 32.5 

Wholesale and retail trade, repair of motor vehicles, motor 

cycles and personal and households goods, hotels and 

restaurants 

18 14.3 14.3 46.8 

Transport, storage and accommodation 2 1.6 1.6 48.4 

Financial inter-mediation, insurance, real estate and business 

services 

6 4.8 4.8 53.2 

Community, social and personal services 16 12.7 12.7 65.9 

Other 43 34.1 34.1 100.0 

Total 126 100.0 100.0  

Source: Primary data 

4.3.5 Age of Business 

Most of the youth-owned enterprises have been paying salaries for between three 

months and 3.5 years (56.35%), while 26.96% have been paying salaries for more than 

3.5 years. Lastly, 16.67% have been paying salaries for less than three months. 

Salaries paid also include salaries paid to the owners of the businesses, either formally 

paid or informally paid. Figure 4.2 illustrates the salary statistics. 

 



38 
 

Figure 4.2: Length of time enterprise paid salaries  

Source: Primary data 

4.3.6 Number of employees 

The majority of enterprises (93.7%) had a size of 1-10 employees, followed by 4.8% of 

enterprises that had 11-50 employees and finally, followed by only 1.6% of enterprises 

that had more than 50 employees. According to the GEM report, there is a significant 

correlation between the duration of the business and the number of employees the 

particular enterprise afford to have (Global Entrepreneurship Monitor, 2016/2017). Table 

4.4 illustrates the number of employees enterprises have including the owners. 

 

Table 4.4: Number of Employees  

 Frequency Percent Valid Percent Cumulative Percent 

Valid 1 - 10 118 93.7 93.7 93.7 

11 - 50 6 4.8 4.8 98.4 

More than 50 2 1.6 1.6 100.0 

Total 126 100.0 100.0  

Source: Primary data 

4.4 Descriptive statistics 

The descriptive statistics provide the results of the main constructs and the focus is on 

showing the means, confidence interval, median, skewness and kurtosis. The results of 

scanning and search, association and connection as well as evaluation and judgement, 

including the dependent variable, business performance, are presented in the following 

tables; 

4.4.1 Responses on the Scanning and search 

Six questions were asked to measure the impact scanning and search has on the 

enterprise performance. Table 4.5 provides the results of participation oneach question 

and no missing results were reported on each question. The majority of respondents 

(mean=6.25) have responded positively on the question number 6. “I am always actively 

looking for new information”. 



39 
 

Table 4.5: Descriptive Statistics: Scanning and search  

 
N Minimum Maximum Mean 

Std. 

Deviation 

Skewness Kurtosis 

Statistic Std. Error Statistic Std. Error 

SS_1 126 1 7 6.01 1.149 -2.074 .216 5.758 .428 

SS_2 126 1 7 6.05 1.344 -2.641 .216 7.432 .428 

SS_3 126 1 7 5.58 1.472 -1.490 .216 2.065 .428 

SS_4 126 1 7 6.21 1.143 -2.131 .216 5.449 .428 

SS_5 126 2 7 5.79 1.177 -1.158 .216 1.087 .428 

SS_6 126 3 7 6.25 .885 -1.650 .216 3.422 .428 

Valid N 

(listwise) 

126 
        

Source: Primary data 

4.4.2 Responses on Association and connection 

Three questions were asked in order to evaluate the impact of association and 

connection to enterprise performance. The majority of respondents (mean=6.00) have 

responded positively to question number 2 “I am good at ‘connecting dots’”. Table 4.6 

provides the results and no missing value is reported in any of the question asked. 

 

Table 4.6: Descriptive Statistics: Association and connection  

 
N Minimum Maximum Mean 

Std. 

Deviation 

Skewness Kurtosis 

Statistic Std. Error Statistic Std. Error 

AC_1 126 1 7 5.02 1.513 -.972 .216 .294 .428 

AC_2 126 2 7 6.00 .980 -1.193 .216 2.063 .428 

AC_3 126 1 7 5.34 1.303 -1.033 .216 .816 .428 

Valid N 

(listwise) 

126 
        

Source: Primary data 

4.4.3 Response on Evaluation and judgement  

Four questions were asked in order to evaluate the impact of evaluation and judgement 

to enterprise performance. The majority of respondents (Mean= 6.02) have responded 

positively on question number 1 “I have a gut feeling for potential”.  Table 4.7 provides 

the results and no missing value is reported in any of the questions asked. 

 



40 
 

Table 4.7: Descriptive Statistics: Evaluation and judgement 

 
N Minimum Maximum Mean 

Std. 

Deviation 

Skewness Kurtosis 

Statistic Std. Error Statistic Std. Error 

JE_1 126 1 7 6.02 1.039 -2.266 .216 8.051 .428 

JE_2 126 1 7 5.92 1.177 -1.847 .216 4.121 .428 

JE_3 126 2 7 5.67 1.289 -1.397 .216 1.758 .428 

JE_4 126 2 7 5.94 1.049 -1.394 .216 2.674 .428 

Valid N 

(listwise) 

126 
        

Sources: Primary data 

4.4.4 Responses on Enterprise Performance 

Nine questions were asked in order to evaluate Enterprise performance. The majority of 

respondents (Mean=3.73) have responded positively to question number 1 “Sales 

level”. Table 4.8 provides the results and no missing value is reported.  

 

Table 4.8: Descriptive Statistics: Enterprise Performance  

 
N 

 

Minimum 

 

Maximum 

 

Mean 

 

Std. 

Deviation 

Skewness Kurtosis 

Statistic Std. Error Statistic Std. Error 

EP_1 126 1 7 3.73 1.183 .600 .216 .525 .428 

EP_2 126 1 7 3.68 1.360 .692 .216 .287 .428 

EP_3 126 1 7 3.58 1.556 .872 .216 .356 .428 

EP_4 126 1 7 3.55 1.532 .730 .216 .108 .428 

EP_5 126 1 7 3.67 1.470 .719 .216 .418 .428 

EP_6 126 1 7 3.62 1.419 .787 .216 .606 .428 

EP_7 126 1 7 3.72 1.429 .904 .216 .506 .428 

EP_8 126 1 7 3.60 1.449 .754 .216 .376 .428 

EP_9 126 1 7 3.82 1.455 .434 .216 -.133 .428 

Valid N 

(listwise) 

126 
        

Source: Primary data 

4.5 Measurement scale 

The dependent variable, business performance, was measured using a 5-point 

satisfaction scale with nine indicators of testing business performance. Where 1= Very 

dissatisfied and 5= very satisfied. Entrepreneurial alertness is measured using three 



41 
 

antecedents, scanning and search, association and connection and evaluation and 

judgement.  Entrepreneurial alertness dimensions (Scanning and search, Association 

and connection, as well as Evaluation and judgement) were all measured using a 7-

point Likert scale. 

4.5.1 Validity of factors 

Exploratory factor analysis was conducted to assess the validity of the scale for 

enterprise performance and entrepreneurial alertness constructs. The extraction method 

used was Principle components analysis (PCA) with KMO and scree plot. The pattern 

matrix was preferred over structure matrix for the purpose of easy of interpretation 

(Slater, 2019).  The primary role of factor analysis is to determine the underlying 

structure among the variables in order to explain the pattern of correlations amongst the 

variables (Leech, Barrett, & Morgan, 2015). The scale had been developed by Tang et 

al. (2012) and the purpose of this section is not to create a new scale but rather to 

confirm the reliability of the the existing theoritical scales in the context of this study. 

4.5.1.1 Entrepreneurial alertness dimensions (IV) 

Entrepreneurial Alertness dimensions (Scanning and search, Association and 

connection and Evaluation and judgement) are independent variables in this study. The 

sufficiency of 13 items designed to measure alertness, were examined using the Kaiser-

Meyer-Olkin (KMO) measure and Bartlett’s test of Sphericity.  According to Grande 

(2015). the KMO value must be above 0.50, but the most acceptable is 0.60 and 

Bartlett’s test of Sphericity must be significant at p<0.001. Table 4.9 provides results on 

KMO 0.809, Bartlett’s Test of Sphericity= sig. 0.000 and BTS= 313,205, indicating that 

the data were appropriate for the purpose of factor analysis. Statistically, this means 

that there exists a relationship between the variables, even though some variables 

shows weak relationships, but can be included in factor analysis. 

 

 

 

 



42 
 

Table 4.9: KMO and Bartlett's Test: Independent Variable 
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .809 

Bartlett's Test of Sphericity Approx. Chi-Square 313.205 

df 28 

 Sig. .000 

Source: Primary data 

 

The eigenvalue summary table, Table 4.10, shows components divided among factors 

that had strong loadings. After some items showed double (cross loading) and others 

with no loadings, three components were reduced to only two components. The 

components had Eigenvalues greater than 1.0, which is a common criteri