University of Ghana  http://ugspace.ug.edu.gh
 
 
UNIVERSITY OF GHANA 
COLLEGE OF HUMANITIES 
 
 
PSYCHOLOGICAL CAPITAL AND ACHIEVEMENT MOTIVATION AS 
PREDICTORS OF WORK ENGAGEMENT AMONG MICRO AND 
SMALL-SCALE ENTREPRENEURS 
 
 
BY 
EMMANUEL NKANSAH ANOKYE 
(10338317) 
 
 
THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, 
LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE 
AWARD OF MPHIL. INDUSTRIAL AND ORGANISATIONAL 
PSYCHOLOGY DEGREE 
 
 
DEPARTMENT OF PSYCHOLOGY 
 
 
JULY, 2018 
 
 
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PSYCAP, ACHIEVEMENT MOTIVATION AND WORK ENGAGEMENT  
 
DECLARATION 
This is to confirm that this thesis is the final product and a true reflection of a research conducted 
by Emmanuel Nkansah Anokye in pursuant to an award of MPhil. Degree in Industrial and 
Organisational Psychology at the Department of Psychology, University of Ghana. This thesis was 
supervised by Dr Maxwell Asumeng and Dr Kwaku Oppong Asante. This thesis has not been 
presented in whole or in part and the ideas of other persons used in this study have been duly 
acknowledged. 
 
………………………………     Date: ......./10/2018 
Emmanuel Nkansah Anokye 
(Student) 
 
This thesis has been submitted for examination with the approval of: 
………………………………     Date: ......./10/2018 
Dr Maxwell Asumeng 
(Principal Supervisor) 
 
………………………………     Date: ......./10/2018 
Dr Kwaku Oppong Asante 
(Co-supervisor) 
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DEDICATION 
 
To my parents and siblings for their prayers, motivation and unwavering support. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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ACKNOWLEDGEMENT 
My supervisors, Dr Maxwell Asumeng and Dr Kwaku Oppong Asante have been of tremendous 
help with their guidance, timely responses, patience and contributions towards my thesis. I am 
very thankful for the support I received from them. 
I would like to appreciate Mrs Opoku Ntiamoah, Annabella Owusua Agyemang, Joana Bekoe, 
Stephanie Bosompem and Emmanuel Adjetey for the help you offered during various stages of 
this research. 
Finally, to the participants of this study, I thank you for your acceptance and willingness to be part 
of my study. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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TABLE OF CONTENTS 
DECLARATION.......................................................................................................................................... i 
DEDICATION............................................................................................................................................. ii 
ACKNOWLEDGEMENTS ...................................................................................................................... iii 
TABLE OF CONTENTS .......................................................................................................................... iv 
ABSTRACT .............................................................................................................................................. viii 
LIST OF TABLES ...................................................................................................................................... x 
LIST OF FIGURES ................................................................................................................................... xi 
LIST OF ABBREVIATIONS .................................................................................................................. xii 
CHAPTER ONE ......................................................................................................................................... 1 
INTRODUCTION ....................................................................................................................................... 1 
1.1 Background to the study ........................................................................................................ 1 
1.2 Statement of the problem ...................................................................................................... 1 
1.3 Aim and objectives of the study ............................................................................................ 6 
1.4 Relevance of the study .......................................................................................................... 7 
1.5 Outline of the thesis ............................................................................................................... 7 
CHAPTER TWO ........................................................................................................................................ 9 
LITERATURE REVIEW .......................................................................................................................... 9 
2.1 Introduction ........................................................................................................................... 9 
2.2 Theoretical Framework ......................................................................................................... 9 
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2.2.1 Job Demands-Resources Theory ........................................................................................ 9 
2.2.2 Expectancy-Value Model of Achievement Motivation ................................................... 13 
2.3 Psychological Capital: A general overview ........................................................................ 14 
2.3.1 Resilience ......................................................................................................................... 16 
2.3.2 Optimism .......................................................................................................................... 16 
2.3.3 Hope ................................................................................................................................. 17 
2.3.4 Self-efficacy ..................................................................................................................... 17 
2.4 Achievement motivation: A general overview .................................................................... 18 
2.5 Work engagement: A general overview .............................................................................. 19 
2.6 Micro and small-scale enterprises in Ghana: A general overview ...................................... 21 
2.7 Review of related studies .................................................................................................... 23 
2.7.1 Psychological capital and achievement motivation. ........................................................ 24 
2.7.2 Psychological capital and work engagement ................................................................... 28 
2.7.3 Achievement motivation and work engagement .............................................................. 35 
2.7.4 Demographics and work engagement .............................................................................. 37 
2.8 Rationale for the present study ............................................................................................ 39 
2.9 Statement of Hypotheses ..................................................................................................... 40 
2.9.1 Conceptual model ............................................................................................................. 42 
2.9.2 Operational definition of terms ........................................................................................ 43 
2.10 Conclusion ......................................................................................................................... 43 
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CHAPTER THREE .................................................................................................................................. 44 
METHODOLOGY ................................................................................................................................... 44 
3.1 Introduction ......................................................................................................................... 44 
3.2 Design.................................................................................................................................. 44 
3.3 Population............................................................................................................................ 44 
3.4 Sample and sampling technique .......................................................................................... 45 
3.5 Measures.............................................................................................................................. 46 
3.5.1 Demographic variables ..................................................................................................... 46 
3.5.2 Psychological capital ........................................................................................................ 46 
3.5.3 Achievement Motivation .................................................................................................. 47 
3.5.4 Work Engagement ............................................................................................................ 47 
3.6 Procedure ............................................................................................................................. 48 
3.7 Ethical considerations ......................................................................................................... 50 
3.8 Data analysis ....................................................................................................................... 50 
3.9 Conclusion ........................................................................................................................... 52 
CHAPTER FOUR ..................................................................................................................................... 53 
RESULTS .................................................................................................................................................. 53 
4.1 Introduction ......................................................................................................................... 53 
4.2 Demographic characteristics of participants ....................................................................... 54 
4.3 Preliminary Analysis ........................................................................................................... 55 
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4.4 Intercorrelations Matrix for Study Variables ...................................................................... 57 
4.5 Predictors of work engagement ........................................................................................... 59 
4.6 Subscales of psychological capital as predictors of work engagement. .............................. 60 
4.7 Gender and age group differences on work engagement .................................................... 62 
4.8 Summary of findings ........................................................................................................... 63 
4.9 Summary of the observed relationship between psychological capital, the subscales of it 
and work engagement................................................................................................................ 64 
4.10 Conclusion ......................................................................................................................... 65 
CHAPTER FIVE ............................................................................................................................ 66 
DISCUSSION, RECOMMENDATION AND CONCLUSION ....................................................... 66 
5.1 Introduction ......................................................................................................................... 66 
5.2 Psychological capital, achievement motivation and work engagement. ............................. 66 
5.3 The dimensions of psychological capital and work engagement. ....................................... 71 
5.4 Age, gender and work engagement ..................................................................................... 74 
5.5 Implications for work engagement ...................................................................................... 76 
5.6 Limitations of the study....................................................................................................... 78 
5.7 Recommendations for future research................................................................................. 79 
5.8 Conclusion ........................................................................................................................... 80 
REFERENCES .......................................................................................................................................... 82 
APPENDICE ........................................................................................................................................... 104 
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ABSTRACT 
 
The study examined how psychological capital and achievement motivation predict work 
engagement among micro and small-scale entrepreneurs in Accra. One hundred and seventy-one 
(171) micro and small-scale entrepreneurs operating small IT firms, beauty parlour, food 
businesses, wood businesses, construction and plumbing, retail shops, event planning and 
decorations, management consulting firms, fashion businesses, poultry farming, cold stores, auto 
mechanic businesses, shoemaking businesses, pub businesses among others were purposively 
sampled from various locations in Accra. Participants fell between the ages of 24-64 years. The 
number of male participants stood at 104 (60.8%) and females were 67 (39.2%). A high proportion 
of the participants (78.4%) had been in business operation from 1 to 5 years, Majority of the 
participants (97.7%) had from 1 to 10 employees of study of the participants, while 4 (2.3%) 
participants had employees numbering between 11 and 30.  
A cross-sectional design was adopted where respondents were administered a set of 
questionnaires measuring psychological capital (self-efficacy, hope, resilience and optimism), 
achievement motivation and work engagement. Standard hierarchical regression and independent 
t-test were used to analyse the data. The results showed that work engagement had a significant 
positive relationship with psychological capital and its sub-dimensions but no significant 
relationship was observed with achievement motivation. Psychological capital predicted work 
engagement but self-efficacy predicted work engagement more than the other dimensions of 
psychological capital. Additionally, no significant difference existed between male and females; 
young and old entrepreneurs on work engagement. Based on the findings, there is the need for the 
design and implementation of interventions that offer support systems to help entrepreneurs in the 
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micro and small-scale business sector of Ghana to develop their psychological capital as a way of 
improving their work engagement. 
 
 
 
 
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LIST OF TABLES 
Table 1: Socio-demographic characteristics of participants………………...................... 56 
 
Table 2: Summary of means, standard deviations, skewness, kurtosis and alphas of the main    
                study variables…………………………………………………………………58 
 
Table 3: Inter-correlation matrix of main study variables.……………………………….59 
 
Table 4: Results of a simple linear regression analysis for psychological capital as a predictor    
             of work engagement……..……………..……………………………………….60 
 
Table 5: Results of hierarchical multiple regression analysis for the dimensions of psychological   
              capital as predictors of work engagement… ………………………………….61 
 
Table 6: Summary of the Independent t-test comparing gender and age group differences on work   
              engagement………………………………………………………………………62 
 
 
 
 
 
 
 
 
 
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LIST OF FIGURES 
 
Figure 1: Model showing hypothesized relationships between the predictor variables and the   
               the criterion in the study…………………………………………………………  44 
 
Figure 2: Model of the observed relationship between the psychological capital, its subscales and   
               work engagement….………………………………………………………………64 
 
 
 
 
 
 
 
 
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LIST OF ABBREVIATIONS 
 
ASSI    Association of Small Scale-Industries 
GBA    Ghana Beauticians Association  
GDP    Gross Domestic Product 
JD-R    Job Demands-Resources 
MSE    Micro and Small-Scale Enterprises 
NBSSI    National Board for Small-Scale Industries 
NEIP    National Entrepreneurship and Innovation Plan 
NVTI    National Vocational Training Institute. 
Psycap    Psychological capital 
1D1F    One District One Factory 
 
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CHAPTER ONE 
INTRODUCTION 
1.1 Background to the study 
In line with the development aspirations of many developing countries, the strategic growth of 
Ghana’s informal sector is very critical. Compared to some emerging Asian economies such as 
India, China and Thailand that were behind Ghana in terms of GDP per capita in 1960, these 
countries are now far ahead of Ghana in terms of economic development (World Bank, 2018). 
Among the many factors that their successes can be attributed to their investment in micro and 
small-scale businesses and entrepreneurship (Dugguh, 2014). Globally, micro and small-scale 
enterprises (MSEs) are recognised as a springboard for a viable economic development (Oppong, 
Owiredu, & Churchill, 2014). In India for example, micro and small-scale enterprises are among 
the biggest employment providers and the survival of that sector is of vital importance to the people 
(Tripathi, Tripathi, & Dedhia, 2016). Evidence from Ghana (Agyapong, 2010), Pakistan (Ali, 
Rashid, & Khan, 2014), Nigeria (Ajuwon, Ikhide, Akotey, & Ajuwon, 2018; Ayanda & Adeyemi, 
2011), Ethiopia (Ageba & Amha, 2018), some least developed countries across Africa, Asia and 
the Middle East (Maksimov, Wang, & Luo, 2017) suggest that micro and small-scale enterprises 
contribute to poverty alleviation thus, helping to achieve the United Nations’ (UN) sustainable 
development goal of  no poverty. With the vision of growing Ghana beyond aid and 
industrialization through the One District One Factory (1D1F) policy initiative, entrepreneurs have 
been seen as the main driver of the successes of these two initiatives (Baafi, 2017).  
 
Despite the huge potential of the micro and small-scale enterprises in helping to eradicate poverty 
and create employment, in Ghana, this sector has been criticized for their lack of innovativeness 
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and creativity (Agyapong, 2010). Regardless of this, a strong evidence exists to support the notion 
that work engagement has a positive impact on the creativity and innovation of employers and 
employees (Bakker, 2017; Lisbona, Palaci, Salanova, & Frese, 2018). Work engagement is 
characterised by the worker’s level of vigour, dedication and absorption (Schaufeli, Salanova, 
Gonzalez-Roma, & Bakker, 2002). This concept has received significant attention in the recent 
years and the findings from some studies have shown that work engagement can positively 
influence the profit margins, client satisfaction and job performance (Bakker, Albrecht, & Leiter, 
2011). Thus, highly engaged employers and employees may be more open to explore new business 
opportunities, be of good physical and mental health which are more likely to predict job 
performance and lastly, they may be able to build and sustain a good social network than workers 
with low levels of engagement (Gorgievski & Bakker, 2010).  
 
According to Lockwood (2007), work engagement is deemed as the business advantage associated 
with organisational success. Engaged workers are full of energy, self-efficacious and have the 
ability to influence events that affect their lives (Bakker, 2009). Employers and business leaders 
are coming to the agreement that the human resource holds the unique competitive advantage 
(Burke & El-Kot, 2010). Talents and motivations of workers need to be developed if businesses 
want to achieve a peak in their performance (Leiter & Bakker, 2010). In an attempt to improve 
business performance, the focus has been on positive organisational behaviour concepts and 
positive emotions such as optimism, trust and work engagement (Bakker & Schaufeli, 2008). 
Among these positive organisational behaviour concepts and positive emotions, work engagement 
emerges as the most prominent positive organisational concept (Leiter & Bakker, 2010).  
 
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Studies in Ghana suggest that entrepreneurs face a number of challenges which include financial 
and human resource related challenges, inadequate government policies to protect local businesses, 
competition from international firms, low research and development capability levels, inadequate 
use of technology and others (Asare, 2014; Bamfo, 2013; Robson & Obeng, 2008). These lack of 
resources have made the process of founding and growing a business a difficult one (Adomako, 
Danso, Uddin, & Damoah, 2016) and can also lead to feelings of failure and disappointment 
(Mauno, Kinnunen, & Ruokolainen, 2007). Thus, potentially affecting the entrepreneur’s work 
engagement. Several studies point out that psychological capital which comprises of hope, 
efficacy, resilience and optimism serve as a personal resource in driving work engagement (Kotzé, 
2017; Líbano, Llorens, & Salanova, 2012; Robyn & Mitonga-Monga, 2017; Schaufeli & Salanova, 
2011; Simons & Buitendach, 2013; Smith, 2007).  
 
Optimism, in particular, compels the entrepreneur to persist in their goal pursuit in a challenging 
environment (Adomako et al., 2016). In most developing countries, the sad reality is that although 
there is an increase in entrepreneurial activities, the same cannot be said of its rate of success 
(Gindling & Newhouse, 2014). The past few years may have arguably been the most difficult years 
for businesses in Ghana due to the energy crisis. A study carried out by the Institute of Statistical 
Social and Economic Research (ISSER), in 2014 indicated that Ghana’s economy was losing an 
amount of between US$320 million and US$924 million annually. An impact assessment of small 
and micro businesses indicated a daily loss of $2.2 million. The particular interest in this study is 
placed on entrepreneurs in small and micro businesses who are faced with financial and human 
resource related challenges, inadequate government policies to protect local businesses, 
competition from international firms, low research and development capability levels, inadequate 
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use of technology and others (Asare, 2014; Bamfo, 2013). These challenges are likely to impact 
on the level of growth and development of their entrepreneurial activities and also test the 
resilience of the micro and small-scale entrepreneurs. (Asare, 2014). Bullough and Renko (2013) 
are of the view that entrepreneurs need to possess some qualities. The first has to do with his or 
her capabilities to do the tasks necessary to be a successful entrepreneur and the second is the 
ability to withstand and overcome the challenges of the economy and business environment. 
Entrepreneurs provide an insight into how some personal cognitive characteristics come in handy 
as resources needed by them to navigate the rough environment of the informal sector (Renko, 
Bullough, & Saeed, 2016). In this regard, the Ghanaian micro and small-scale entrepreneur is no 
exception. 
  
1.2 Statement of the problem 
Globally, work engagement has received an appreciable amount of research attention within the 
last decade (Agyemang & Ofei, 2013). However, a little research attention has been given to work 
engagement of personnel in the Ghanaian informal private sector and especially, for those 
operating micro and small-scale businesses. Studies done within the Ghanaian context have mostly 
focused on the contributions, barriers and growth of the micro and small-scale business 
environment (Abebrese, 2015; Agyapong, 2010; Akugri, Bagah, & Wulifan, 2015; Boateng, 
Boateng, & Bampoe, 2014; Robson & Obeng, 2008) 
 
Furthermore, to the best of the knowledge of the researcher through literature searches done, it was 
found that, globally, a few numbers of research have been carried out to study the influences of 
demographic factors such as age or gender on work engagement. These few studies are not 
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conclusive of their findings. Some findings point to the direction that demographic factors such as 
age or gender has a significant impact on work engagement (Banihani & Syed, 2017; Schaufeli, 
Salanova, Gonzalez-Roma, & Bakker, 2002; Ugwu, 2013) other findings suggest otherwise 
(Ayangeawam, Tertindi, & Tyokyaa, 2014; Koyuncu, Burke, & Fiksenbaum, 2007). One paper 
done within the Ghanaian context (Robson & Obeng, 2008) found that neither age nor sex was a 
barrier to entrepreneurship and not work engagement.  
 
Despite the positive growth of the number of entrepreneurs in sub-Saharan Africa, the business 
environment presents a number of challenges for entrepreneurs (Fal, 2014). Within the Ghanaian 
context, the informal business environment is faced with demands of financial restraints, lack of 
appropriate technology and market regulations on microenterprise development (Abor & Quartey, 
2010; Forkuoh & Li, 2015; Doe & Asamoah, 2014). While emphasis has been placed on finding 
solutions to the factors stated above, “business success through work engagement is also closely 
tied to specific psychological attributes, which affect behaviours such as business leadership, 
financial discipline, networking, resource management, and building relationships with employees 
and customers” (Baluku, Kikooma, & Kibanja, 2016; p. 28). According to Schaufeli, Bakker and 
van Rhenen (2009), changes in job demands can affect work engagement negatively. Within this 
framework, Simons and Buitendach, 2013 argue that the role of psychological capital is 
instrumental in an organisation’s quest for long-term survival and excellence by serving as a 
safeguard against the adverse effects of the job demands. Investigations on the constituents of 
psychological capital, such as self-efficacy and optimism, has been shown to play significant roles 
in entrepreneurial behaviour and achievement (Hmieleski & Baron, 2016; Mcgee, Peterson, 
Mueller, & Sequeira, 2009). Additionally, psychological capital has been shown to influence 
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organisational commitment, job enrichment and job demands among workers in South Africa 
(Kanengoni & Buitendach, 2015). The influence of psychological capital on work engagement 
within micro and small-scale business space has received a limited attention. We are not aware of 
how psychological capital and achievement motivation influence work engagement of micro and 
small-scale entrepreneurs in Ghana.  This study, therefore, is conducted to explore how 
psychological capital and achievement motivation influence work engagement of micro and small-
scale entrepreneurs in Ghana.  
 
1.3 Aim and objectives of the study 
The general aim of the study would be to investigate the relationships that exist between  
psychological capital, achievement motivation and job engagement among entrepreneurs in the 
informal sector and to determine the predictive powers of psychological capital and achievement 
motivation on job engagement. The specific objectives are as follows: 
1. To examine the relationship between achievement motivation, psychological capital 
and the experience of job engagement among micro and small-scale entrepreneurs. 
 
2. To find out which of the four dimensions of psychological capital (resilience, hope, 
optimism and self-efficacy) would significantly predict job engagement. 
 
3. To find out if work engagement of micro and small-scale entrepreneurs varies with age 
and gender. 
 
 
 
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1.4 Relevance of the study 
This study will provide empirical evidence to micro and small-scale entrepreneurs on how 
psychological capital and achievement motivation individually and collectively lead to work 
engagement among them. It will also provide insight into how resilience, self-efficacy, hope 
and optimism which are the sub-dimensions of psychological capital each contribute towards 
enhancing the work engagement of these entrepreneurs. The findings from this study will 
enable policymakers and business leaders within the informal sector and those operating micro 
and small-scale businesses to design interventions that will engender both the individual and 
combined effects of these factors. It is also envisaged that the findings study will help fill the 
gap in the scientific literature regarding the exact relationships that exist among psychological 
capital, achievement motivation and work engagement. It is hoped that the study will also be 
of benefit to researchers and persons who wish to understand the behaviour patterns of micro 
and small-scale entrepreneurs with regards to psychological capital and work engagement.  
 
1.5 Outline of the thesis 
Chapter 1: Introduction 
The background of the study, statement of the problem, aims as well as the relevance of the 
research were discussed in this chapter. 
 
      Chapter 2: Literature Review 
The chapter begins with the theoretical framework that guides the study. Since this study has 
a strong focus on work engagement, and how psychological capital and achievement 
motivation may be able to predict it, relevant studies pertaining to these variables and how they 
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may be associated are reviewed. From the identified gaps in the literature, six hypotheses are 
formulated and the conceptual framework for this study is designed. The operational definition 
of the key terms of this research is given under this chapter as well. 
 
Chapter 3: Methodology 
The research approach adopted for this study is described in this chapter. The justification for 
using quantitative design is provided. Information on the research setting, instruments, 
procedure for data collection and ethical considerations are covered in this chapter. 
 
Chapter 4: Results 
Under this chapter, the descriptive statistics of the demographic characteristics of participants, 
preliminary data analysis and inferential analysis are conducted based on the data collected. 
The formulated hypotheses are tested using the appropriate statistical method. 
 
Chapter 5: Discussion. 
The general discussions of this research results are carried out in this chapter. These 
discussions are done taking into consideration relevant literature and the Ghanaian context. 
This chapter further highlights the contribution of this thesis, the limitations of it and 
recommendations for future research endeavours. The chapter ends with a general conclusion 
of the study. 
 
 
 
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CHAPTER TWO 
LITERATURE REVIEW 
2.1 Introduction 
This chapter encompasses a theoretical framework containing theories that explain the concepts 
under investigation and also includes a detailed review of studies related to this present one and 
their findings. This chapter provides a theoretical background on work engagement, psychological 
capital and achievement motivation behaviour, as well as academic research vital and related to 
the present study. Expected outcomes in the study are stated in the form of hypotheses supported 
with a conceptual model and operational definitions of key terms used. 
 
2.2 Theoretical Framework 
The concentration of research efforts on work engagement, psychological capital and achievement 
motivation has led to the building of a considerable amount of theories that explain these 
phenomena. For this current study, three relevant theories: Job Demands-Resources Theory and 
Expectancy-Value Model were reviewed and they serve as the framework within which the 
findings of the study are explained. 
 
2.2.1 Job Demands-Resources Theory    
The Job Demands-Resources theory (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) provides 
a theoretical background for the proposed study. The JD-R theory offers us the opportunity to 
understand, explain and make predictions about employee work engagement and job performance 
(Bakker & Demerouti, 2014).  
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The JD-R theory has been a key and one of the most important theories for explaining employees’ 
work engagement, psychological capital and burnout. This model was originally developed to 
explain the concept of burnout experienced by workers due to stress. Maslach and Leiter (2008) 
are of the opinion that work engagement lies at the positive end of the spectrum whereas burnout 
lies at the negative end.  
 
This theory is built on two propositions. The first proposition is the job demands and job resources 
aspect of every working environment. To explain this proposition better, the authors of this theory 
state that irrespective of the organisations in which employees work, they would be faced with two 
variables: job demands and job resources. Job demands are “those physical, social or 
organisational aspects of the job that require sustained physical or mental effort and therefore 
associated with certain physiological and psychological cost” Demerouti et al. (2001; p. 501).  
Some of these demands may include poor work environment and work overload. Job demands 
may not always be negative, they turn into hindrance when meeting those demands require a 
sustained greater effort from the employee (Bakker & Demerouti, 2014). 
 
Job resources are, “the physical, psychological, social or organisational aspects of the job that are 
functional in achieving work goals, reducing job demands and the associated physiological and 
psychological costs and lastly, stimulating the personal growth and development of the employee” 
(Demerouti et al., 2001; p.501). “Job resources are not only necessary to deal with job demands, 
but they are also important in their own right” (Bakker & Demerouti, 2014; p. 9). The job resources 
affect the psychological condition of the individual which subsequently affects their level of work 
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engagement. Job resources serve as a health-promoting factor which keeps people healthy even 
after they face high degrees of workload (Demerouti et al., 2001).  
 
The second proposition of this theory is that job demands and job resources initiate two fairly 
independent processes. The first is the health impairment process and the second is the 
motivational process. The health impairment process according to Schaufeli and Bakker (2004),  
links job demands with health problems as a result of burnout and this process offers a cognitive-
emotional basis for understanding how workers perform under stress. This process concerns itself 
with the preservation of performance stability under tough conditions which require the 
mobilization and management of mental efforts (Schaufeli & Bakker, 2004). The motivational 
process of this theory states that job resources act as either intrinsic or extrinsic motivator. 
Schaufeli and Bakker, 2004 asserted intrinsic motivators foster employees’ growth, learning and 
development while extrinsic motivators become helpful in attaining work goals. Furthermore, as 
an extrinsic motivator, job resources nurture an individual’s readiness to commit their efforts and 
skills to the work at hand.  
 
Generally, job demands are the most important factors that lead to exhaustion and health complains 
whereas job resources, generally, serve as the most important predictor of work engagement 
(Bakker, Hakanen, Demerouti, & Xanthopoulou, 2007). Bakker and Demerouti (2014) explain the 
reason for this unique effect by asserting that, job demands basically cost effort and takes a toll on 
the energies of the workers whereas job resources acts to buffer the negative consequences of the 
job demands and that employees who have many job resources available can deal better with their 
regular job demands.  
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Another important aspect of this theory is the addition of personal resources into the original model 
developed by Demerouti et al. (2001). These are positive self-evaluations of an individual with 
regards to their abilities to regulate and influence their environments positively (Hobfoll, Johnson, 
Ennis, & Jackson, 2003). In a compelling manner, it has been shown that such personal resources 
predict motivation, goal-setting,  job and life satisfaction, performance, career ambition and other 
desirable outcomes (Bakker & Demerouti, 2008). Several researchers have explored the 
relationship between personal resources and work engagement. For example, Xanthopoulou, 
Bakker, Demerouti and Schaufeli (2007) investigated the influence of some personal resources 
such as self-efficacy and optimism on work engagement. The outcome revealed that engaged 
workers possess high self-efficacy levels. Furthermore, engaged workers have the propensity to 
be optimistic and believe they can meet their needs by involving themselves in tasks in the 
organisation. Shire and Talib Bin Bon (2015) studied the relationship between personal resources 
and the affective commitment of employees. Van den Heuvel, Demerouti and Schaufeli (2010) 
also explored the mitigating impact of personal resources of employees during organisational 
change processes.  
 
Limitation of this extension is that only few evidence points to the interaction between personal 
resources and job demands (Bakker & Demerouti, 2014). It is evident that engaged workers 
possess personal resources, such as optimism, self-efficacy,  resilience and an active coping style, 
which enable them to successfully navigate their work environment (Bakker & Demerouti, 2008). 
This theory has been used in studies involving work engagement (Bargagliotti, 2012; Karatepe & 
Olugbade, 2009) and absence duration and frequency (Bakker, Demerouti, de Boer, & Schaufeli, 
2003). A positive relationship has been found to exist between job resources and work engagement 
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(Bakker et al., 2007). Psychological capital has been found to be a positive resource in fostering 
work engagement among employees (Avey, Luthans, & Jensen, 2009). 
 
In applying the JD-R theory to this study, Ghanaian entrepreneurs are faced with some constraints 
that impede the progress of their firms (Abebrese, 2015). These constraints come in the form of 
financial and human resource related challenges, inadequate government policy to protect local 
businesses, competition from international firms, low research and development capability levels, 
inadequate use of technology and others (Asare, 2014; Bamfo, 2013).  It can be argued that the 
psychological capital of the entrepreneur would provide him or her with resources in the form of 
positive psychological attributes (resilience, hope, optimism and self- efficacy) which would 
enable the entrepreneur to sustain and expand their businesses even in the unfavourable 
environment within which they operate.  
 
2.2.2 Expectancy-Value Model of Achievement Motivation  
Expectancies and values are assumed to directly affect performance, tenacity and the choice of the 
task. According to this theory, task-specific beliefs such as perceptions of the competence, 
perceptions of the difficulty of the tasks and the individual’s goals and self-schema influence the 
expectancies and values of the individual. These social cognitive variables are also influenced by 
the individual’s perception of other people’s attitudes and expectations of them. Expectancies for 
success is the individual’s beliefs about how well they will do on upcoming tasks either in the 
immediate or long-term future. The model is on personal or efficacy expectations. According to 
this theory, four components of task values have been identified thus: attainment value, intrinsic 
value, utility value and cost.  
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Attainment value is the personal importance of doing a task well and the opportunity to confirm 
or disconfirm important aspects of one’s personality. Intrinsic value is the enjoyment the individual 
gets from performing the activity. Finally, Utility value is determined by how well the task relates 
to current and future goals such as career goals. Lastly, the cost is defined in terms of negative 
aspects of engaging in a task such as anxiety, fear of both failure and success as well as the amount 
of effort needed to succeed. This suggests that the value attached to an individual’s expectation 
has an influence on the number of resources and energy spent on it to see to its realization. This 
theory has been used in studies involving achievement domains relating to the academic 
performance of children in schools (Eccles, 2000), However, it is relevant to this study because 
entrepreneurs also set for themselves goals to which they strive to achieve. 
 
In applying this theory to this study, entrepreneurs’ motivation for success and their future 
expectations would be seen in the value they put in their choice of the venture, the persistence of 
efforts and the self-belief they have towards successfully achieving their goals. The combination 
of the Job Demand Resource theory and the Expectancy-Value model of achievement motivation 
would offer a sound theoretical framework for the study of work engagement among Ghanaian 
entrepreneurs taking into consideration that when personal resources in the form of psychological 
capital and the needed drive to succeed are present, the entrepreneur is better positioned to stay 
engaged in the line of work despite the presence of other demands. 
 
2.3 Psychological Capital: A general overview 
Psychological capital is a combination of four positive psychological resources, specifically, 
optimism, self-efficacy, resilience and hope. It relates to one’s positive outlook on a situation and 
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the likelihood of success based on perseverance (Luthans, Avolio, Avey, & Norman, 2007). Unlike 
other personality traits, psychological capital is a state characteristic and remains flexible. This 
makes it possible for it to be developed or improved (Luthans, Youssef, & Avolio, 2007). 
Psychological capital is considered as a significant merged construct that can help in addressing 
organisational matters which concerns the employees (Simons & Buitendach, 2013). This concept 
is rooted in the principles of positive organisational behaviour (Luthans et al., 2007). Luthans 
(2002a, p. 59), defines this positive organisational behaviour as, “the study and application of 
positively-oriented human resource strengths and psychological resource capacities that can be 
measured, developed, and effectively managed for performance improvement in today’s 
workplace.”  
 
According to Luthans, Avolio, Walumbwa and Li (2005), at the individual level, psychological 
capital has an impact on fueling the growth and performance of workers. At the organisational 
level, psychological capital may provide control, increase in profit and competitive advantage 
through enriched worker performance. Larson and Luthans (2006), speak of the added potential 
that psychological capital may have on workers’ levels of job satisfaction and organisational 
commitment. They further stress that psychological capital impacts significantly on human and 
social capitals of workers. Psychological capital has been found to have a significant influence on 
work performance, work happiness and subjective well-being (Choi & Lee, 2014) and on 
employee creativity (Sweetman, Luthans, Avey, & Luthans, 2011).  
The psychological capital subscales (dimensions) of resilience, optimism, hope and self-efficacy 
would be discussed briefly. 
 
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2.3.1 Resilience 
Resilience is defined by Luthans (2002, p.702) as the “positive psychological capacity to bounce 
back from adversity, uncertainty, conflict, failure, or even positive change, progress and increased 
responsibility.” Studies in Clinical Psychology give the indication that highly resilient individuals 
are effective in handling diverse experiences in life including making changes and developing 
under various hostile environments (Luthans et al., 2005). In view of this, resilient people bounce 
back to life after experiencing a stressful event such as failure. Luthans et al. (2005) found a 
significant positive relationship between Chinese workers experiencing major changes in their 
workplace and their work performance as a result of their resilience even as they faced such 
turbulent moments.  
 
In the uncertain environment that entrepreneurs operate in, resilient entrepreneurs, who show a 
high degree of tolerance for ambiguity and respond appropriately to change, may be better 
prepared to succeed (Ayala & Manzano, 2014). According to Madichie and Hinson (2013), the 
majority of Ghanaian entrepreneurs are known to have fought against all odds to achieve and 
maintain their success in business despite the difficulties facing the sector. Resilience, in particular, 
has an impact on the firm’s entry, growth and survival (Abebrese, 2015). Resilience has a positive 
link with workplace performance (Luthans, Avolio, Avey & Norman, 2007).  
 
2.3.2 Optimism 
“To the optimist, setbacks are not necessarily seen as failures but as challenges and opportunities 
that can be improved on for success” (Luthans et al., 2005, p. 257). Optimism has a positive impact 
on physical and psychological health. The resulting impact of it is seen in academic, athletic, 
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political and occupational successes (Luthans, 2002a). Optimism is a force that motivates and 
shapes self-assurance in the probability of positive outcomes in the present and future events 
(Luthans et al., 2007). Entrepreneurs predominantly have a higher tendency to experience 
optimism and they are more inclined to expect positive outcomes from situations which are not 
really reasonable (Hmieleski & Baron, 2016).  
 
2.3.3 Hope 
According to Snyder (2002), hope is the belief in oneself to set goals, figure out how to attain those 
goals and motivating oneself to accomplish them. Snyder (2002) further explains that hope consists 
of the individual’s willpower and way power. Willpower is one’s action or fortitude to accomplish 
goals and way power is an individual’s ability to create other paths and plans in order to accomplish 
a goal in the face of difficulties. According to Luthans et al. (2007), hope is a state of motivation 
that pushes individuals towards achieving a goal and altering the path that leads to the goal when 
it becomes necessary. Hope has played a substantial role and has proven its impact in the 
workplace (Simons & Buitendach, 2013) For instance, Youssef and Luthans (2007) identified that 
it had a positive influence on work happiness, organisational commitment, and employee 
satisfaction. Again, researchers found that hope influences job performance (Peterson, Walumbwa, 
Byron & Myrowitz, 2009). 
 
2.3.4 Self-efficacy  
Self-efficacy refers to the belief an individual has concerning his or her abilities to organise and 
carry out an action required to bring desired results (Bandura, 1997). Stajkovic and Luthans (1998) 
go a step further to explain that self-efficacy is a belief an individual holds with regards to his or 
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her ability in shaping their cognitive resources, energies, and another line of activities essential to 
carry out a definite task in a specific situation. With reference to Çavuş and Gökçen (2015), self-
efficacy is an inner drive that direct people to effectively execute different tasks and roles in their 
life and that it can have both positive and negative influence on motivation. Self-efficacy has been 
found to correlate significantly with business creation and success (Bullough, Myatt, & Renko, 
2014), socialising and retaining new workers (Bauer, Bodner, Erdogan, Truxillo & Tucker, 2007) 
and also organisational commitment (Harris & Cameron, 2005). Self-efficacy is needed in 
evaluating a person’s competence and the real force one needs to exert to get the essential resources 
needed to execute the occupational opportunities available (Mcgee et al., 2009). 
                     
2.4 Achievement motivation: A general overview 
Traditionally, achievement motivation has been seen as a disposition that drives an individual to 
face challenges in the interest of gaining success and excellence. This attitude compels an 
individual to set challenging goals, strive for performance, work out risks, face uncertainties and 
bear ambiguous situations, solve problems creatively and assume responsibility for the 
consequences of his or her behaviour (McClelland, 1961 as cited in Deshpandé, Grinstein, Kim, 
& Ofek, 2013). Achievement motivation behaviour is described as that behaviour in which the 
ultimate goal is to develop or demonstrate to others or to oneself high ability and to avoid showing 
characteristics of low ability (Nicholls, 1984). Achievement motivation theory suggests that people 
who expect to achieve success are more highly motivated by the need to achieve and less motivated 
by fear of failure (Hsu, Chen, Yu, & Lou, 2010). Additionally, in achievement motivation, the 
need strength is more substantial than the need satisfaction and individuals high in achievement 
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motivation are mostly aspiring and are focused on achieving high-performance standards (Van 
Den Broeck, Vansteenkiste, De Witte, & Lens, 2008).  
 
Rauch and Frese (2007) identified that the need for achievement and risk taking are some of the 
specific characteristics entrepreneurs need in order to thrive in their roles. According to 
McClelland as cited in Rauch and Frese (2007), this disposition is linked to business success.  In 
this regard, achievement motivation behaviour is based on reaching success, achieving aspiration 
in life and also the extent to which an entrepreneur pursues challenging goals (Ogunleye & Osekita, 
2016). Dr Paa Kwesi Nduom, an accomplished entrepreneur is reported by the Ghana News 
Agency urging fellow entrepreneurs to take risks, expect failures and rejection in their bid to 
succeed (Ghana News Agency, 2015).  
 
2.5 Work engagement: A general overview 
Kahn (1990) in his seminal paper on work engagement described that when people are engaged in 
their work, they employ and express their selves physically, cognitively and emotionally in 
performing their work roles. These three components namely: vigour, dedication and absorption 
correspond to the physical, emotional and cognitive aspects of work engagement (Geldenhuys, 
Łaba, & Venter, 2014). It is worth noting that work engagement has become an essential factor in 
achieving business growth (Ravikumar, 2013). This concept is characterised by the worker’s level 
of vigour, dedication and absorption (Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002). To 
throw more light on this, Shimazu and Schaufeli (2008), explain that vigour is associated with high 
levels of energy and mental resilience; dedication is associated with feelings of enthusiasm, pride 
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and a sense of significance with one’s work; absorption is regarded as being cheerfully immersed 
in one’s work.  
 
Work engagement as a behaviour is a manifestation of a particular mental state that produces 
positive outcomes both at the personal growth and development level as well as performance 
quality (Bakker, Schaufeli, Leiter, & Taris, 2008). In the light of this, engaged workers are full of 
energy, self-efficacious and have the ability to influence events that affect their lives (Bakker, 
2009), in addition, they put in more efforts into their job because they identify with it (Bakker et 
al., 2008). Organisations seeking to be on top need workers who are connected to their work 
psychologically and show high levels of proactiveness and willingness towards high performance 
 
Lu, Xie, and Guo (2018) throw in an interesting view that points to the fact that, besides work 
engagement being an individual level phenomenon, it has also been found to have a contagious 
and trickling-down effect from supervisors to subordinates and even among employees. In this 
regard, work engagement may transmit from entrepreneurs to their employees or apprentices. They 
defended their position from three angles. Firstly, the leader's work engagement sends a positive 
signal that compels their followers to develop an optimistic view of the future, secondly, the vigour 
and absorption exhibited by leaders reflect resourcefulness of the work environment. This gives 
an indication to the subordinates that there are adequate resources available to accomplish 
organisational goals. Lastly, the positive emotions, such as enthusiasm, pleasure, and joy engaged 
leaders experience in their work tend to be emulated by employees or subordinates. They further 
asserted that the absorption, dedication and vigour of the leader are likely to create positive 
affective experiences in their employees. 
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Christian, Garza and Slaughter (2011) draw a clear distinction between work engagement and 
other job attitudes such as job satisfaction, organisational commitment and job involvement moves 
further to discuss how work engagement serves as a precursor to certain work behaviours such as 
improved task performance. They emphasized that this improvement in task performance reflects 
how well an individual executes the duties and the intensity and persistence with which they pursue 
their job.  
 
Despite all the good consequences of work engagement, Halbesleben, Harveyand Bolino (2009), 
exposes us to the dark side of it. They are of the view that work engagement has a potentially 
negative effect on work-life balance. This is because engaged workers are more likely to take on 
extra roles and devote more resources to their job than other facets of their lives. Nonetheless, in 
the words of  Sonnentag (2011; p. 34), “Luckily, the sun seems to shine much stronger on the 
positive implications of work engagement.” 
 
2.6 Micro and small-scale enterprises in Ghana: A general overview 
For years, entrepreneurs in the informal sector were seen to be conducting menial businesses for 
survival (Adom, 2014). However, with the turn of the millennium, this perception has gradually 
changed and entrepreneurs are gaining more recognition (Adom & Williams, 2012). Van Praag 
and Versloot (2007) define entrepreneurs as “self-employed or the owner-manager of an 
incorporated business” (p. 353). 
In Ghana, the National Board for Small-scale Industries describes MSEs as those enterprises 
employing 29 or fewer workers. Specifically, micro enterprises employ between 1 to 5 people and 
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have fixed assets not exceeding USD 10,000 excluding land and building. Small enterprises 
employ between 6 and 29 people and have fixed assets not exceeding USD 100,000 excluding land 
and building (Oppong et al., 2014). 
 
Micro and small-scale enterprises (MSEs) hold the potential for a sustainable economic 
development (Oppong et al., 2014) and they are considered as seeds for big businesses (Abor & 
Quartey, 2010). Again, a chunk of micro and small-scale enterprises make up the manufacturing 
sector of Ghana (Ministry of Trade and Industry, 2011). Behind the establishment of small firms 
are entrepreneurs who are motivated to satisfy a target market by bringing up a product that meets 
their needs (Agyapong, 2010). In Japan, South Korea, and India among other countries, the 
important role of micro and small enterprises have been displayed through the substantial 
contribution to the Gross Domestic Products (GDP), earnings on export and reducing the 
unemployment rate (Oppong et al., 2014). 
 
Annually, out of about 250,000 young people that enter the Ghanaian labour market, only about 
5,000 representing 2% are absorbed by the formal sector (Otoo, Osei-Boateng, & Asafu-Adjaye, 
2009). The remaining larger proportion finds their way into the informal sector. Abor and Quartey 
(2010), asserts that MSEs have an important role to play in stimulating economic growth, 
generating employment and contributing to poverty alleviation This statement is valid considering 
the fact that entrepreneurs through job creation provide employment, reduce poverty and 
contribute to the overall economic development of the nation (Bamfo, 2013).  
 
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Nonetheless, with successive Ghanaian governments having to accept the important role of micro 
and small-scale enterprises in poverty reduction, a number of institutions such as National 
Vocational Training Institutions (NVTI), Gratis foundation and Rural Enterprise Project (REP) 
have been set up and assigned to promote the growth of this sector. (Tetteh & Frempong, 2007). 
More recently, the National Entrepreneurial and Innovation Plan (NEIP) has also been rolled out. 
With specific reference to the Rural Enterprise Project, the overall objective of the project was to 
build competitive small and micro enterprises in the rural areas backed with good sustainable 
support services (Rural enterprise project, 2011). 
 
The development of the informal sector which is the niche of entrepreneurs has been met with a 
number of challenges (Asare, 2014). Among these are financial and human resource related 
challenges, inadequate government policy to protect local businesses, competition from 
international firms, low research and development capability levels, inadequate use of technology 
and others (Asare, 2014; Bamfo, 2013). Despite these general challenges facing the sector, some 
entrepreneurs have risen above these challenges and made name for themselves in their respective 
ventures.  
 
2.7 Review of related studies 
The key argument in this study is that, based on Job demand-resources theory and Expectancy-
value theory of achievement motivation, there is an association between psychological capital, 
achievement motivation and work engagement. In view of this, this section reviews some studies 
that have focused on the areas of achievement motivation, psychological capital and work 
engagement. 
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A number of studies have been done on the impact of psychological capital on work engagement. 
These studies were mostly focused on the formal work environment with little emphasis on the 
informal sector. However, the literature on the impact of psychological capital on achievement 
motivation and the joint impact of achievement motivation and psychological capital on work 
engagement within the informal sector appear to be scanty. Research evidence so far has indicated 
a strong consistency in the fact that one main predictor of work engagement is personal resources 
of which psychological capital is hugely involved. What has not been so clearly demonstrated is 
how the different dimensions of psychological capital and achievement motivation predict work 
engagement.  The first part of this review focuses on psychological capital and achievement 
motivation.  This would be followed by related studies on psychological capital and work 
engagement; achievement motivation and work engagement and finally, gender and age 
differences and work engagement.  
 
2.7.1 Psychological capital and achievement motivation. 
As described by Luthans, Avey, Avolio and Peterson, (2010), the concept of psychological capital 
suggests that the common link running through the four dimensions is a motivational propensity 
to accomplish goals and succeed. “Taken together, the four resources synergistically interacting to 
form the core construct of psychological capital can be expected to lead to higher performance 
based on their abilities to reinforce greater effort from individuals, promoting the generation of 
multiple solutions to problems, positive expectations about results leading to higher levels of 
motivation, and positive responses to setbacks. In other words, there may be a motivational 
propensity found in psychological capital for goal accomplishment and success” (p. 49). 
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Motivations may be the spark that transforms a latent intention into real action (Carsrud & 
Brännback, 2011).  
 
A few studies have tried to study the relationship between psychological capital and achievement 
motivation. One of such studies was done by Hmieleski and Carr (2008), who found that 
psychological capital of entrepreneurs could account for a significant amount of variance in new 
venture performance than financial capital, social capital and human capital. The authors further 
did a mean comparison of the psychological capital of first-time entrepreneurs and those who had 
started multiple businesses. It was shown that the entrepreneurs with multiple businesses scored 
higher on psychological capital than first-time entrepreneurs. In a similar study from  Uganda, 
Baluku, Kikooma, and Kibanja, (2016) found that start-up capital and psychological capital 
together predicted entrepreneurial success significantly; however, the psychological capital was 
found to be a  better predictor. In a further observation, it was revealed that optimism which is a 
dimension of psychological capital moderated the relationship between entrepreneurial success 
and start-up capital significantly.  
 
Psychological capital has not only been studied within organisational environment., Datu, King 
and Valdez, (2016) explored its impact within an academic context. The primary objective of that 
study was to examine the relationship between psychological capital, academic motivation, 
academic engagement, and academic achievement using both cross-sectional (Study 1) and 
longitudinal (Study 2) approaches. Study 1 revealed that psychological capital was associated with 
higher motivation. Study 2 showed that psychological capital was a predictor of motivation, 
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academic engagement and academic achievement. The authors discussed the adaptive function 
that psychological capital may play an in facilitating student success. 
 
The relationship between the subscales (dimensions) of psychological capital and achievement 
motivation has been explored in some studies. The impact of resilience on achievement motivation 
has been studied by  Magnano, Craparo and Paolillo (2016). They examined the roles that 
emotional intelligence and resilience played in the achievement motivation of the workers. The 
study which was carried out in a sample of 488 Italian workers from diverse backgrounds both 
within the formal and informal sectors revealed that resilience mediated the relationship between 
emotional intelligence and achievement motivation. To this, they concluded that resilient people 
are able to cope with stressful work environments and are able to make adjustments to achieve 
organisational goals. 
 
Ayala and Manzano (2014), in a related study, which employed a 5-year longitudinal study of 650 
entrepreneurs in the Spanish tourism sector found that resilience could account for entrepreneurial 
success. This study was further confirmed by Bullough, Myatt and Renko (2014) when they 
surveyed a sample of 163 Afghan professionals. Results from the survey using regression analysis 
showed that resilience positively influenced the intent of starting a business. They concluded that 
resilience plays a major role in entrepreneurial intentions even in dangerous environments. 
Bullough and Renko (2013), did not only find that resilience could play an important role in 
motivating entrepreneurial intentions The contribution of self-efficacy was found to be significant. 
These findings were revealed after conducting a study on a sample of 400 entrepreneurs, aspiring 
entrepreneurs and non-entrepreneurs in Afghanistan and also among a sample of 100 MBA 
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students in America. In sports, It has been shown that resilience is positively associated with sports 
achievement (Nezhad & Besharat, 2010). The authors discussed that high levels of resilience help 
the individual stay afloat during unfavourable experiences. 
 
There is evidence to suggest that there is a relationship between an individual’s level of self-
efficacy and achievement motivation. Earlier, Bandura (2012), was of the view that self-efficacy 
affects the motivation and competence of students to enter the challenging process of starting their 
own businesses. This opinion by Bandura was confirmed by Pihie and Bagheri (2013) who found 
that students’ self-efficacy had the most significant and positive impact on their intention to 
become entrepreneurs. The authors discussed that self-efficacy has an effect on one’s self-
regulation, the ability to set goals and accomplish them.  
 
Still considering the impact of self-efficacy on achievement motivation behaviour, Liñán, Santos 
and Fernández (2011) discussed the influence of individual perception on entrepreneurial 
intentions. The individual perception was assessed based on the individual’s level of self-efficacy, 
knowledge of a role model and low-risk perception. Self-efficacy, knowledge of a role model were 
found to be the most important antecedent to entrepreneurial intentions. Furthermore, Gurnani 
(2014), examined how self-efficacy could affect the innovative behaviour of women entrepreneurs. 
The result indicated that women with high self-efficacy scored higher on entrepreneurial 
innovative behaviour than women with low self-efficacy.  
 
Przepiorka (2017) sought to understand the relationship between hope, goal commitment and 
entrepreneurial success. Pearson correlation results indicated that hope was positively related to 
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entrepreneurial success and goal commitment. The author highlighted the relevance of hope, 
motivation, goal commitment, and action as decisive factors in achieving goals. Similarly, hope 
was identified as being able to significantly predict achievement motivation among urban 
adolescent. This is according to a study done by Kenny, Walsh-Blair, Blustein, Bempechat, and 
Seltzer (2010). 
 
 Although many studies suggest that there is a positive relationship between psychological capital 
and achievement motivation,  Hmieleski and Baron (2016) hold a contrary opinion. They identified 
a negative relationship between the optimism levels of entrepreneurs and the performance of their 
firms. The authors defended their position that highly optimistic individuals often hold high 
expectations that appear to be unrealistic, suffer from overconfidence, and play down on warning 
signs that can seriously interfere with their decision making and judgment.  
 
2.7.2 Psychological capital and work engagement 
Highly motivated and engaged employees are critical to the success of organisations and 
enterprises (Bakker & Demerouti, 2008). Studies relating to how psychological capital influences 
work engagement has mostly focused on the formal organisations such as call centres in South 
Africa (Pillay, Buitendach, & Kanengoni, 2014; Simons and Buitendach 2013), consortium of HR 
practitioners in South Africa (Plessis & Barkhuizen, 2012), pharmaceutical companies, petroleum 
companies, a chocolate factory, a food processing facility, an auto assembly plant, a corporate 
leasing company, a telecommunication provider, an information technology company, a public 
university and a private university all within Egypt (Burke & El-Kot, 2010), hospitality industry 
in Nigeria has also received some attention (Karatepe & Karadas, 2015; Karatepe and Olugbade 
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2009), school teachers in Italy (Simbula, Guglielmi, & Schaufeli, 2011), Information Technology 
company in India (Sihag & Sarikwal, 2014), among nurses in India (Chaudhary, Bidlan, & Darolia, 
2015).  
 
Some studies have concentrated on the total impact of psychological capital whereas some isolated 
its dimensions and studied its associations with work engagement. When Simons and Buitendach 
(2013), set out to explore the relationship between psychological capital, work engagement and 
organisational commitment in 106 South African call centre employees using a cross-sectional 
survey design, they found a significant positive relationship between psychological capital and 
work engagement. In a similar study within the same South African context, Robyn and Mitonga-
Monga (2017), investigated the effects of psychological capital and work engagement in relation 
to employees’ commitment. The sample comprised 81 employees within a manufacturing 
organisation. Their findings indicated that psychological capital had a significant positive 
relationship with work engagement. Further hierarchical regression analysis showed psychological 
capital moderated the relationship between work engagement and organisational commitment. 
They concluded by saying that employees who are high in the psychological capital show greater 
attachment to their organisation, more engaged and their attrition rate is lower than their colleagues 
with low psychological capital. 
 
According to Kotzé (2017), psychological capital can be developed as a personal resource to 
enhance work outcomes, such as work engagement. Her study was done with a section of workers 
drawn from several organisations in South Africa. This study supported the assertion that 
psychological capital has a positive influence on work engagement and went further to discuss 
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how employees’ personal resources can be developed in order to enhance work engagement. In 
the same vein, Smith (2007) found that psychological capital was positively related to work 
engagement. Smith’s study looked at how the socialization of newcomers into an organisation 
could lead to the provision of job resources that create psychological capital, leading to positive 
outcomes for employees in their level of work engagement. In another related study, Sihag and 
Sarikwal (2014), examined the role of psychological capital in enhancing the level of employee's 
engagement of middle level IT professionals. They found a positive relationship between 
psychological capital and work engagement.  
 
Costantini et al. (2017), examined the degree at which any development in the psychological 
capital, as a personal resource, could lead to an improvement in work engagement among a section 
of public sector employees. They asserted that organisations need enthusiastic and devoted 
workers to augment the superiority of their services and products constantly. Results of their study 
showed that there is a positive relationship between psychological capital and work engagement. 
In addition, when they compared the pre-test and post-test results, it was revealed that the 
intervention step to increase psychological capital considerably improved both psychological 
capital and work engagement. This points to the fact that an enhancement in the psychological 
capital is likely to predict an increase in work engagement.   
 
As stated in the introduction, Maslach and Leiter (2008) are of the view that work engagement is 
the opposite of burnout. In light of this, Herbert (2011) set out to find the relationship between 
psychological capital and burnout. His study revealed a significant negative relationship between 
psychological capital and burnout. They argued that workers with higher levels of psychological 
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capital would experience fewer feelings of exhaustion, both physically and emotionally. They 
would also experience fewer feelings of fatigue and frustration in their line of duty and their 
interactions with clients. In another study, which also sought to find the relationship between 
psychological capital and burnout, Rehman, Qingren, Latif and Iqbal (2017), found a negative 
relationship between psychological capital and burnout.  
 
On the other hand, De Waal and Pienaar (2013) came out with contrary findings when they 
attempted to conceptualise and examine the causal relationship between psychological capital and 
work engagement using longitudinal survey and a crossed-lagged study design. Their studies did 
not find a significant influence of psychological capital on work engagement.  This study was 
restricted to participants working in a specific unit of a chemical facility. However, they 
established that work engagement can facilitate the mobilisation of job and personal resources. 
They argued that the relationship between work engagement and psychological capital gets 
stronger with time, in the sense that grasping difficult tasks may add directly to improving one’s 
psychological capital. This has been confirmed in a study done by Bakker, Demerouti and Sanz-
Vergel (2014).  
 
The studies reviewed so far takes into consideration the global impact of psychological capital on 
work engagement. However, some studies took into consideration the dimensions (subscales) of 
psychological capital (hope, optimism, self-efficacy and resilience)   and examined its relationship 
with work engagement. For example, Rodoplu Şahin, Çubuk, and Uslu (2014) found that the 
dimensions (subscales) of psychological capital positively correlated with work engagement 
distinctively. A number of empirical studies involving resilience and work engagement report of 
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a significant positive association between the two variables. One of such studies was carried out 
by  Ayangeawam, Tertindi and Tyokyaa (2014). They studied the association between resilience 
and work engagement. Their study was carried out in a General Hospital and Federal Medical 
Centre in Makurdi metropolis. Two hundred and two medical personnel were involved in this 
study. The Statistical results using Pearson Product Moment Correlation Coefficient indicated that 
a positive relationship existed between resilience and work engagement. The authors went on to 
discuss that highly resilient individuals are attractive to potential employers and that this type of 
attribute, in part, may account for an overall increase in work engagement.  
 
In related research which was aimed at studying the relationship between resilience and work 
engagement, Villavicencio-Ayub, Jurado-Cárdenas and Valencia-Cruz (2014), identified a 
positive relationship between work engagement and resilience. They also made an assertion similar 
to that of Ayangeawam, Tertindi and Tyokyaa (2014) that resilience favours the emergence of 
work engagement. They further added that an organisation composed of resilient workers is better 
positioned to overcome, analyse, and react appropriately to the demands of the environment, 
giving rise to superior performance. 
 
With regards to self-efficacy and work engagement, Líbano, Llorens and Salanova (2012), found 
that self-efficacy had a significant positive relationship to work engagement. This study was 
carried out on 386 university staff in Spain. Based on these findings, they discussed that people 
with higher levels of self-efficacy perceive more job resources than demands and they experience 
more work engagement than people with lower levels of self-efficacy. In a similar study involving 
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Principals in Norwegian schools, Federici and Skaalvik (2012) found that self-efficacy was 
negatively related to burnout.   
 
Xanthopoulou, Bakker, Demerouti and Schaufeli (2009) provided empirical evidence of the 
positive relationship between personal resources (self-efficacy and optimism) and work 
engagement across time. Their results suggested that employees who are self-efficacious and 
optimistic are most likely to experience high levels of work engagement. The main purpose of 
their longitudinal study was to investigate long-term relationships between job resources, personal 
resources, and work engagement. They hypothesized that job resources, personal resources, and 
work engagement are reciprocal. Simbula et al. (2011), also identified a similar pattern of 
reciprocity in the interactions among self-efficacy, job resources and work engagement. This is 
after they had conducted a three-wave longitudinal study on 104 Italian school teachers. This study 
was specifically aimed at testing how job resources, self-efficacy and work engagement are related 
over time. 
 
Following an assertion made by Bakker and Demerouti (2008) that employees high in hope are 
more engaged in their work since they have more goal-oriented strategies and are motivated for 
goal achievement, Karatepe (2014) found evidence to support that assertion using data gathered 
from full time hotel frontline employees and their managers in a Romania. The findings from that 
study showed that there was a positive relation between hope and work engagement. The author, 
in conclusion, argued that when such employees with high levels of hope encounter difficulties 
that impede them to reach their goals, they take advantage of alternative paths to achieve their 
goals. In Malaysia, a study conducted by Othman and Nasurdin (2011) on the work engagement 
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of Nurses found that hope and resilience were positively related to work engagement. They 
affirmed that in order to promote high work engagement within the nursing profession, nurses need 
to possess a greater amount of psychological capital. The growing interest in employee resilience 
and work engagement led Cooke, Cooper, Bartram, Wang and Mei (2016) to study this 
phenomenon within the Chinese banking sector. The study investigated the relationship that exists 
among employees’ resilience and their level of work engagement. The sample size for this study 
was 2040.  Results of the study showed that resilience had a positive impact on work engagement.  
 
The impact of psychological capital on work engagement within the hospitality industry has 
received some attention. The competitive hospitality industry requires that their service delivery 
is on point and meets the satisfaction of customers (Karatepe & Karadas, 2015). An engaged 
workforce, then, appears critical to developing and maintaining high-quality customer service 
relationships (Thompson, Lemmon, & Walter, 2015). In the Nigerian hospitality industry, 
Karatepe and Olugbade (2009) came to the realisation that self-efficacy increased the level of 
employees feelings of being engaged at work. This was based on a study they conducted on 130 
hotel managers. They concluded this by saying that employees with high levels of self-efficacy 
become more immersed in their works.  Paek, Schuckert, Kim and Lee (2015) found that 
psychological capital has very strong effects on both work engagement and employee morale. 
Specifically, front-line employees with high psychological capital are more engaged with their 
work and more likely to display job satisfaction and affective organisational commitment. This 
study was done in Seoul, Korea involving 312 front-line staff working in some top performing 
hotels.  
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According to Lockwood (2007), work engagement is deemed as the business initiative associated 
with organisational success. Work engagement contributes to the success of an enterprise. This is 
confirmed by Gorgievski and Bakker (2010). They stated that, through work engagement, new 
business opportunities are explored and it can lead to employees’ physical and mental wellbeing 
which can predict job performance. Lastly, highly engaged workers may be able to build and 
sustain a good social network than workers with low levels of engagement. Avey, Luthans, Smith 
and Palmer (2010) also discuss how psychological capital influences employees’ wellbeing over 
time and how that also affects their level of work engagement.  
 
According to  Rich, Lepine and Crawford (2010), work engagement can account for the job 
performance of an employee. Bakker (2008) established that there is a positive association between 
work engagement and performance. Bakker and Demerouti (2008; p.215) provided the following 
reasons for this relationship: “Engaged employees (1) often experience positive emotions, 
including happiness, joy, and enthusiasm; (2) experience better health; (3) create their own job and 
personal resources; and (4) transfer their engagement to others.”  
 
2.7.3 Achievement motivation and work engagement 
A few studies directly study the impact of achievement motivation on work engagement. One of 
such study was carried out by Akhtar, Boustani, Tsivrikos and Chamorro-Premuzic (2015). Their 
study which was aimed at identifying individual differences in work engagement revealed that 
individuals with high achievement motives are highly engaged in their work.  
 
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Although a little direct evidence on the relationship between achievement motivation and work 
engagement exists, it is reasonable to expect a positive association between these variables and 
also between achievement motivation and other outcomes of work engagement such as job 
performance, creativity, organisational citizenship behaviour and others. For example, Lăzăroiu 
(2015), stressed that the attitudes and motivations of employees have a tremendous effect on their 
workplace conduct and performance. Deshpandé et al. (2013), studied the role of the founder’s 
achievement motivation on an entrepreneurial firm’s performance in America and Japan. Their 
study showed that the achievement motivation of the founder positively influenced the choice to 
adopt an orientation that is based on the customer in both Japan and the USA and that this 
orientation is related to improved performance across the two countries. A negative correlation 
was found between Taiwanese nurses’ achievement motivation and occupational burnout. Thus by 
inference, a positive correlation exists between their achievement motivation and work 
engagement. This finding was made possible through a study done by Hsu et al. (2010).  
 
As it has been stated earlier, people with achievement motives are creative in solving problems. 
Ahmetoglu, Harding, Akhtar and Chamorro-Premuzic (2015) found a significant association 
between employees’ creativity and their work engagement. However, these associations were 
nonsignificant after the variance of demographic variables had been accounted for. They went to 
suggest the need for other demographic and personality variables in work engagement researches. 
 
Khan, Breitenecker and Schwarz (2015), studied how a team with a diverse need for achievement 
did in terms of their performance. The study findings revealed that the diversity in need for 
achievement motivation had a negative impact on the team’s effectiveness and efficiency. They 
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discussed that due to the varying levels of need for achievement, team members were likely to 
attribute different levels of importance to the same task. Moreover, the differences in need for 
achievement resulted in differently perceived expectancies which led to the delays and wastage of 
resources. This ultimately led to low team performance. Anra and Yamin (2017), concede to the 
fact that the performances of lecturers are an important part of the quality of a University’s 
educational programme. In a survey conducted among University lecturers, they established that 
there was a direct effect on their achievement motivation in their work performance. They 
concluded that a healthy competition with their colleagues would foster their professional growth. 
Moreover, this healthy competition will be a factor in the future development of the individual.   
 
2.7.4 Demographics and work engagement 
In confirming the measure for work engagement,  Schaufeli et al. (2002) found that there was a 
weak positive relationship with age. In terms of gender, differences have been found in some 
populations. In Belgian, German, Finnish and Norwegian samples, men scored slightly higher than 
women. However, in Dutch and South African samples, women scored slightly higher than men.  
In Nigeria, a validation of the measure for work engagement showed that showed that it was only 
gender that showed a significant difference in response to work engagement scale. Age showed no 
significant difference (Ugwu, 2013) 
 
In a similar manner, Shukla, Adhikari, and Singh (2015) found that the work engagement level did 
not differ significantly across different age groups. It was however found that female employees 
in the organisation were more engaged in their jobs compared to their male counterparts. They 
argued that usually females are seen to be more composed and responsible hence being more 
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engaged in their work. This survey was conducted in a sample of 90 employees of an e-commerce 
company in India.  To study whether the concept of work engagement is gendered, Banihani, Lewis 
and Syed (2013) included gender in the concept of work engagement. Based on a review of the 
literature associated with work engagement and gendered organisations, they found that work 
engagement is gendered and it is easier for males to show higher levels of work engagement than 
females. In a follow up to gain more insight into this phenomenon of the gendered nature of work 
engagement, Banihani and Syed (2017) conducted a qualitative study on private sector firms in 
Jordan. The aim of their research was to investigate how different women’s experiences and 
perspectives of work engagement are, as compared to men. It has shown that the psychological 
conditions present in work engagement are gendered, in that women do not have the same 
opportunities to experience these dimensions of absorption, dedication and vigour as men do. A 
criticism of this study is that the religious and political regime in Jordan can explain why women 
experience low levels of work engagement.  
 
In contrast to research findings that identified a relationship between work engagement and gender, 
Koyuncu, Burke and Fiksenbaum (2007) found that gender was unrelated to levels of work 
engagement. These findings were the results of a study done on a sample of professionals and 
managers in Turkish banks. Ravikumar (2013), in a study seeking to understand the work 
engagement of employees in micro, small and medium enterprises in India found no significant 
relationship between gender and work engagement. To support this finding, Ayangeawam et al. 
(2014) undertook a study which sought to find if gender differences existed in work engagement 
levels. It was revealed in the study that there was no gender difference with regards to work 
engagement. The authors discussed that men and women show the similar or almost the same level 
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of work engagement. They further stated that this finding was interesting as it goes a long way to 
account for why there is the need to eliminate gender discrimination in the workplace since both 
sexes score almost the same in terms of work engagement. This line of reasoning was also 
empirically supported by Adil and Kamal (2016) who found no gender difference in work 
engagement of University staff in Pakistan. These discrepancies in the outcomes demonstrate the 
call for more investigations on the matter of gender and work engagement.  
 
2.8 Rationale for the present study 
Based on the review of related studies, it is evident that research on psychological capital and work 
engagement have been limited to formal organisational settings. Even in Ghana, the informal 
sector, specifically the micro and small-scale business environment remain largely ignored in 
studies on organisational behaviour. This is rather unfortunate as this sector is the bedrock of the 
country’s economy and a majority of the citizens work in this sector (Ghana Statistical Service, 
2012). There is a paucity of literature with regards to the psychological capital and work 
engagement of employers. Studies on psychological capital and work engagement have mostly 
been focused on employees. However, as Seligman (2011) argues, a leader's work engagement 
conveys positive information and leads followers to develop a positive expectancy in the future. 
An entrepreneur’s sense of work engagement may transmit to their employees. Hence there is the 
need to focus on the work engagement of these business owners and develop interventions to spur 
their growth. This study will, therefore, focus on entrepreneurs in micro and small-scale 
businesses. This sample was chosen to draw the attention of researchers to the behaviour patterns 
of micro and small-scale business owners in this sector and also to enable future researchers to 
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make a better generalisation based on both sectors since Ghana’s economy is controlled by both 
the formal and informal sectors.  
 
This situation creates a significant gap in the literature regarding the exact relationships that exist 
between psychological capital and achievement motivation as well as psychological capital and its 
relationship with work engagement. There is also the lack of evidence regarding the role of the 
different dimensions of psychological capital and achievement motivation in predicting work 
engagement in the informal sector; specifically, micro and small-scale enterprises.  
This study will, therefore, expand the literature by filling the gaps regarding the relationships 
between psychological capital, achievement motivation, demographic factors (age and gender) and 
work engagement. Another reason is to analyse the comparative powers of the dimensions of 
psychological capital in predicting work engagement. This will give entrepreneurs, policymakers 
and other bodies such as the National Board for Small-scale industries (NBSSI) that a better chance 
at developing interventions that would enhance the psychological capital and consequently the 
work engagement of entrepreneurs within that space. 
 
2.9 Statement of Hypotheses 
1. There would be a positive and significant relationship between psychological capital and 
work engagement of entrepreneurs. 
 
2. There would be a significant positive relationship between achievement motivation and 
work engagement. 
 
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3. Psychological capital would better predict work engagement more than achievement 
motivation. 
 
4. Self-efficacy will significantly account for more variance in work engagement than the 
other dimensions of hope, resilience and optimism in the psychological capital. 
 
5. Younger entrepreneurs would experience higher levels of work engagement than older 
entrepreneurs. 
 
6. Female entrepreneurs would experience higher levels of work engagement than male 
entrepreneurs. 
 
 
 
 
 
 
 
 
 
 
 
 
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2.9.1 Conceptual model 
                                                                                                                                   
                 IV 1 
 
Achievement 
 motivation 
 
   
 
Work Engagement 
    Psychological capital  
 Hope  
  P  s y  c  h  o l oS  eg  li fc -a e l f  cf ia c pa  ic t ya   l                                                                                                      DV 
  
Resilience 
 
     Optimism 
                   
                   IV 2 
Figure 1. Model showing hypothesized relationships between the predictor variables and the 
criterion in the study 
 
The model above (Figure 1) was developed based on the relationships predicted. It is expected that 
a significant positive relationship will exist among psychological capital, achievement motivation 
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and work engagement. In addition, it is expected that resilience would account for more variance 
in the psychological capital.   
2.9.2 Operational definition of terms 
 
Entrepreneur: an owner of a micro or small-scale enterprise. 
Micro and small-scale enterprise: A private business venture with employee size ranging from 
1-29. 
Psychological capital: An individual’s positive outlook on a situation based on the level of hope, 
self-efficacy, resilience and optimism. 
Work engagement: An individual’s level of vigour, absorption and dedication to the line of duty. 
Achievement motivation: An individual’s drive to achieve excellence in the line of duty. 
 
2.10 Conclusion 
Drawing upon job demands-resources theory and expectancy-value model of achievement 
motivation, this chapter reviewed relevant studies that had been done with respect to the variables 
of interest in this study. Six hypotheses were formulated to help address some of the identified 
gaps in the literature.  
The methodological approach employed in conducting this study would be discussed in the next 
chapter. 
 
 
 
 
 
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CHAPTER THREE 
METHODOLOGY 
3.1 Introduction 
In this chapter, an explanation of the research methodology is presented. A description of the 
study design, population, sample and sampling methods are provided. The research instruments 
and their psychometric properties are also discussed. Data collection procedure and the analysis 
of data are further highlighted in this chapter. 
 
3.2 Design  
A quantitative cross-sectional research design was used for this study. Using this form of research 
design, information was gathered from a sizeable number of participants at only a point in time 
using a set of instruments with pre-set questions with fixed responses at one point in time 
(Creswell, 2012) and also due to the fact that the collected data were analysed statistically (Aliaga 
& Gunderson, 2000). Additionally, this method was chosen because the study was carried out 
mainly to investigate associations between the variables of interest and the strengths of those 
associations. 
 
3.3 Population 
The study was targeted at the micro and small-scale entrepreneurs operating within Accra, the 
capital of Ghana. The city is dominated by workers in the private informal sector (Bentsi-Enchill, 
Cudjoe, Sepah, Anarfi, & Gaisie, 2013). This gives the indication that the informal business 
landscape might be very competitive with many entrepreneurs offering the same or similar kind of 
service thus fighting to win an appreciable customer base. Moreover, many other informal 
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businesses may have started but could not be sustained over the years thus making this setting 
appropriate for studying the interaction between psychological capital and achievement motivation 
and how it leads to engagement among these entrepreneurs. According to Budlender (2015), the 
majority of people in the region work within the wholesale and retail space and about 10% of the 
population work in food-related services.  
 
3.4 Sample and sampling technique 
A total of 171 micro and small-scale entrepreneurs were used for this study. Even though a total 
of 200 questionnaires were distributed, 174 were retrieved. Upon further examination of the 
returned questionnaires, three (3) of them were removed from the data due to uncompleted 
responses. This resulted in 171 valid questionnaires for analysis. This represents a response rate of 
85.50%. The sample size of 171 was considered appropriate for regression analysis. This is based 
on the formula proposed by Tabachnick and Fidell (2007) for the determination of a minimum 
sample size, N>50+8M, where M is the number of predictor variables and N is the sample size. 
The present study has two main independent variable, achievement motivation and psychological 
capital and from the above formula, a sample size of 66 should be the minimum. Based on the 
above deductions, a sample size of 171 was deemed adequate for the study.  
The sample size of 171 was obtained using the convenient sampling technique whereby micro and 
small-scale entrepreneurs who were willing to take part in the study were sampled. The study 
further employed the purposive sampling technique. This was done to ensure that only 
entrepreneurs aged 46 and above were captured.  
 
 
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3.5 Measures 
The measures used in this study were standardized instruments with acceptable reliabilities.  
 
3.5.1 Demographic variables 
This section of the questionnaire sought to gather information on the participants’ ages, gender, 
marital status, nature of the business, number of employees and job tenure.  
 
3.5.2 Psychological capital 
Psychological capital questionnaire (PCQ-24) developed by Luthans, Avolio and Avey (2007) was 
used to measure psychological capital. The psychological capital questionnaire is a 24-item 
instrument with a 6-point Likert-style response format ranging from “strongly disagree” (1) to 
“strongly agree” (6). This questionnaire consists of 4 subscales measuring hope, self-efficacy 
resilience and optimism. Each subscale has 6 items measuring it. Some of the items measuring 
each subscale include, “I can think of many ways to reach my current work goals”, “I feel confident 
analysing a long-term problem to find a solution”, “I usually manage difficulties one way or 
another at work” and “when things are uncertain for me at work, I usually expect the best” 
respectively. PCQ-24 has a good measure of internal consistency and it has been used across a 
number of populations (Dawkins, Martin, Scott, & Sanderson, 2013).  
 
 Monico, Pais, Dos Santos and Santos (2014), report of an overall internal consistency of .91 with 
the subscales of self-efficacy, hope, resilience and optimism having Cronbach alphas of .84, .82, 
.74, and .66 respectively when used in a sample of Portuguese workers. Avey, Hughes, Norman 
and Luthans (2008) and Avey, Luthans and Jensen (2009) report a Cronbach’s alpha of .92 when 
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the PCQ-24 was administered to a primarily white or Caucasian working adults in the USA. When 
it was used in a South African sample, Görgens-Ekermans and Herbert (2013) reported a reliability 
coefficient of .85 whiles Simons and Buitendach (2013) reported a reliability coefficient of .91.  
The instrument was piloted and yielded a reliability of .76. The scale yielded a reliability of .94 
with the subscales of self-efficacy, hope, resilience and optimism having reliability coefficients of 
.85, .88, .73 and .62 respectively. Items 13, 20 and 23 which are negatively worded in the scale 
were reversed and scored 
 
3.5.3 Achievement Motivation 
Achievement motivation was measured using the 14 item Ray-Lynn Achievement Motivation 
Scale developed by Ray (1979). This scale would measure an individual’s drive for personal 
achievement and the tendency to evaluate performance against some standard of excellence (e.g. 
Do you get restless and annoyed when you feel you are wasting time?). Ratings on this scale are 
as follows: No (1), Not certain (2) and, Yes (3). Its Cronbach alpha in a Turkish sample is reported 
to be .70 (Ozbilir, Day, & Catano, 2015). When sampled in South Africa, an internal reliability 
score of .72 was realised (Ray, 1979). The instrument yielded a Cronbach alpha of .80 when it was 
piloted for this study. It yielded a reliability coefficient of .70 after the main study. Seven 
negatively worded items; 1, 2, 7, 11, 12, 13 and 14 were reversed and scored. 
 
3.5.4 Work Engagement 
The work engagement of entrepreneurs was assessed with the 17-item Utrecht Work Engagement 
Scale (UWES) developed by Schaufeli et al. (2002). This is a self-report questionnaire with 17 
items scored on a seven-point Likert scale ranging from 0 = never to 6 = every day. The scale 
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comes with three subscales, namely, vigour (6 items), dedication (5 items) and absorption (6 
items). Some statements on this scale are, “At my job, I feel strong and vigorous” (vigour), “I am 
enthusiastic about my job” (dedication) and “I am immersed in my work” (absorption). A 
reliability coefficient of 0.95 has been reported when used on a South African Sample (Simons & 
Buitendach, 2013). Burke and El‐Kot (2010), report of reliability coefficients of the subscales 
ranging from 0.72 to 0.88 when sampled on an Egyptian population of managers. After piloting, a 
reliability coefficient of .69 was achieved. At the end of the main study, a reliability of coefficient 
of .79 was realized. 
 
3.6 Procedure 
Ethical approval was sought from the Ethics Committee for Humanities (ECH) of the University 
of Ghana before data collection commenced. After approval had been given, the researcher visited 
the study sites for familiarization and recruitment of participants for the study. For each of the 
study sites that were visited, two assistants, who are indigenes of that locality were involved. These 
assistants were people known personally by the researcher or based on recommendations of others. 
Their involvement helped gain the acceptance of the populace and also helped the researcher with 
easy navigation of the study sites. These familiarization exercises were conducted on different 
days aside from the days for the actual data collection. The introductory letter from the Psychology 
Department of the University of Ghana the researcher’s school ID card was shown to potential 
participants to indicate the authenticity of the research.  The telephone numbers of entrepreneurs 
operating micro and small-scale businesses who accepted to be part of the study were taken so that 
any further communication concerning the actual day for data collection could be made to them 
and also to get them to confirm their participation in the study. The researcher prepared a digital 
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version of the questionnaire using google documents for entrepreneurs who preferred to respond 
to it via the internet. Some of the micro and small-scale businesses operated by these entrepreneurs 
included, IT firms, beauty parlour, food businesses, wood businesses, construction and plumbing, 
retail shops, event planning and decorations, management consulting firms, fashion businesses, 
poultry farming, cold stores, auto mechanic businesses, shoemaking businesses, pub businesses 
among others. 
 
The researcher stated the purpose of the study and provision was made for participants to express 
their consent. Participants who agreed and consented to be part of the study appended their 
signatures and proceed to complete the questionnaire. Instructions were stated at the beginning of 
each section of the questionnaire. However, the researcher was available to give clarification if the 
need arose. If a participant was unable to complete and hand over the questionnaire to the 
researcher due to some other pressing demands on his or her part, the said participant was directed 
to put the completed questionnaire in a sealed envelope which the researcher provided them. This 
was to ensure the confidentiality of their responses. The assistant living within their locality was 
informed to check up on the participant after a week and pick up the questionnaire if it had been 
completed. After completion, the questionnaires were taken, scored, coded and statistically 
analysed. Only completed questionnaires retrieved from participants were analysed. 
The main study was preceded by a pilot study which aimed at establishing the reliability of the 
instruments designed for data collection. This process was needed due to the fact that even though 
these instruments have good reliability values, the Ghanaian cultural context and the population 
under study could affect the responses and consequently the reliability of the instruments.  
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3.7 Ethical considerations 
The ethical considerations that were emphasized in this study were informed consent, freedom to 
withdraw, confidentiality and privacy. All participants were provided with the relevant information 
regarding the research. This comprised the aim or purpose of the research for which their help or 
assistance was being sought. They were also provided with information on the potential harm if 
any that may arise from their participation in the research as well as the benefits of the research. 
They were informed that they were not going to directly benefit from the research but that the 
findings from the research could potentially influence policy decision thus benefiting the micro 
and small-scale business environment as a whole. It was only after this information had been 
provided to them that they were asked to sign the consent form to participate in the study.  
 
Participants were permitted to withdraw at any point in the study even though they had consented 
to it. One other very vital issue in terms of ethics that was highlighted in the study was anonymity 
and privacy of participants’ identity as well as their responses. Participants were given total 
assurance of the secrecy of whatever information they were providing to the researcher and his 
team. For this reason, participants were not required to provide their names or any information that 
could be linked to their identities. 
 
3.8 Data analysis 
The data collection instruments were inspected for completeness and the data was entered into 
Microsoft Excel 2013 spreadsheet and then introduced into the Statistical Package for the Social 
Sciences version 23 (IBM SPSS) for data analysis. Prior to proceeding with statistical analyses, 
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hypothesis testing assumptions, including normality and homoscedasticity, were performed. The 
analyses techniques that were used to analyse each hypothesis are described below.  
 
For hypotheses 1 and 2, Pearson Product Moment Correlation Coefficient (Pearson r) was used to 
examine possible significant positive relationships among psychological capital, achievement 
motivation and work engagement of micro and small-scale entrepreneurs. 
 
The third hypothesis stated that “Psychological capital would account for more variance in work 
engagement than achievement motivation.” Standard multiple regression was used to test this 
hypothesis. The intention of this hypothesis is to study the power of each of the independent 
variable in predicting work engagement. 
 
Hypothesis 4 was that “Self-efficacy will significantly account for the most variance in work 
engagement than the other dimensions of hope, self-efficacy, resilience and optimism in the 
psychological capital.” This hypothesis was tested to investigate the extent of variance in the 
dependent variable accounted for by dimensions of psychological capital. In addition, through this 
analysis, the comparative predictive power of each of the variables would be identified. This 
hypothesis was tested using the standard multiple regression. 
 
Hypothesis 5 sought to investigate how work engagement is affected by age. The entrepreneurs 
were divided into two groups based on their ages. Participants with ages ranging from 24 to 44 
were classified as younger entrepreneurs whereas older entrepreneurs were participants with ages 
ranging from 45 to 64. This was tested using the independent t-test. 
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The last hypothesis was that “Female entrepreneurs would experience higher levels of work 
engagement than male entrepreneurs” This was also tested using the independent simple t-test 
because the difference between female and male entrepreneurs in terms of work engagement was 
the focus of the analysis. 
 
3.9 Conclusion 
This chapter focused on the methodology for the study. The research design, population, sampling, 
data collection instruments, research procedure and ethical considerations guiding this study have 
been discussed. The mode of data analysis was also presented. The next chapter focuses on the 
data analyses and the testing of hypotheses. 
 
 
 
 
 
 
 
 
 
 
 
 
 
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CHAPTER FOUR 
RESULTS 
4.1 Introduction 
The study was conducted purposely to investigate the relationship among psychological capital, 
achievement motivation and work engagement of micro and small-scale entrepreneurs in Accra, 
the capital of Ghana. In this chapter, information gathered from participants is analysed to establish 
valid and reliable results that could explain the relationship between psychological capital and 
achievement motivation in predicting work engagement. The comparative strengths of the 
subscales of psychological capital in predicting work engagement are also examined. Finally, 
gender and age group differences on work engagement are studied. 
 
 
 
 
 
 
 
 
 
 
 
 
 
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4.2 Demographic characteristics of participants 
Table 1. 
 Socio-demographic characteristics of participants (n=171) 
Variable Frequency Percentage (%) 
Gender   
 Male 104 60.80 
 Female   67 39.20 
Age   
 24-44 136 79.50 
 45-64   35 20.50 
Tenure   
 1-5 years 134 78.40 
 6-10 years   29 17.00 
 11-15 years    7   4.00 
 16-20 years    1     .60 
Number of employees   
 1-10 167 97.70 
 11-29    4   2.30 
Marital status   
 Married 84 49.1 
 Single 76 44.7 
 Divorced   8   4.7 
 Separated   3   1.8 
 
Table 1 above captures the demographic characteristics of the study participants. It demonstrated 
that the participants fell between the ages of 24-64 years. The number of male participants stood 
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at 104 (60.8%) and females were 67 (39.2%). A high proportion of the participants (78.4%) had 
been in business operation from 1 to 5 years, 17% had from 6 to 10 years work experience, 4% 
had from 11-15 years of work experience and only .6% being in business from 16 to 20 years, 
Majority of the participants (97.7%) had from 1 to 10 employees of study of the participants, while 
4 (2.3%) participants had employees numbering between 11 and 30. Again, almost half of the 
participants (49.1%) were married with only 1.8% separated.  
 
4.3 Preliminary Analysis 
Table 2 
Summary of Means, Standard Deviations, Skewness, Kurtosis and Alphas of the main Study 
Variables 
 Mean SD Min Max Skewness Kurtosis Cronbach 
Alpha 
Psychological 112.16 17.52 58.00 135.00 -1.29 1.64 .94 
capital 
Self-Efficacy 30.22 5.16 13.00 36.00 -1.60 2.58 .85 
Hope 28.25 5.75 14.00 36.00   -.71 -.30 .88 
Resilience 27.16 4.90 15.00 35.00   -.62  .03 .73 
Optimism 26.53 4.75 14.00 33.00 -1.17  .41 .62 
Achievement 34.43 4.54 22.00 42.00   -.38 -.84 .70 
motivation 
Work 77.83 8.11 58.00 95.00   -.38  .04 .79 
engagement 
 
In conducting the preliminary analysis, the reliability analysis, descriptive statistics, tests of 
normality and assumptions of collinearity were computed for the study variables. The Variance 
Inflation Factor (VIF) according to Field (2009) should not be more than 10 and from the first 
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standard regression analysis, the largest VIF was 1.004 which is less than 10 as suggested by Field 
(2009). Also, the Tolerance values according to Field (2009) should not be less than .2 which was 
also met considering the fact that the least Tolerance value, .999, is greater than .2. In the second 
standard regression analysis done, the largest VIF observed among the subscales of psychological 
capital was 3.831 and the least Tolerance value was .261.  The VIF and Tolerance values, therefore, 
reveal that the predictors are not highly correlated. This makes it useful for regression analysis. 
The assumption of normality was also examined and the analysis revealed that the distribution was 
normal, a prerequisite for doing parametric analyses. The skewness and kurtosis of the main 
variables fell within -3 and 3. According to Garson (2012), both skewness and kurtosis should 
range from +2 to -2. He further suggested that some authors use the more stringent range of +1 to 
-1 while others use the more lenient range of +3 to -3 (Garson, 2012). 
 
 
 
 
 
 
 
 
 
 
 
 
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4.4 Intercorrelations Matrix for Study Variables 
Table 3 
Inter-correlation matrix of main Study Variables 
 Variable 1 2 3 4 5 6 7 
1 Work Eng. 1       
2 Psycap .661** 1      
3 Efficacy .700** .831** 1     
4 Hope .658** .900** .709** 1    
5 Resilience .606** .912** .640** .807** 1   
6 Optimism .258** .757** .460** .506** .661** 1  
7 Achievement .037 .026 .074 .058 .025 .083 1 
Mot. 
Note: ** p < .01 Psycap= Psychological capital; Achievement Mot=Achievement motivation and 
Work Eng = Work engagement  
 
The Inter-correlation matrix which indicates the relationships among the study variables were 
analysed using the Pearson Product Moment Correlation Coefficients and the results are presented 
in Table 3 above. The sub-dimensions of psychological capital (Hope, Self-efficacy, Resilience 
and Optimism) were included in this analysis. From the results obtained, there is a strong 
significant positive relationship between psychological capital and work engagement (r = .661, p 
< .01). The analysis also revealed a strong significant positive relationship between the dimensions 
of psychological capital and work engagement. Furthermore, it was observed that self-efficacy, 
resilience, hope and optimism individually had a strong correlation with the composite 
psychological capital. Though a high correlation was observed between the psychological capital 
dimensions of hope and resilience (r = .807, p < .01), no multicollinearity was identified when it 
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was subjected to a variance inflation factor test.  No significant correlation was identified between 
achievement motivation and work engagement  (r = .037, p > .05) as well as between psychological 
capital and achievement motivation (r = .026, p > .05). 
Based on the identification of a strong significant relationship between psychological capital and 
work engagement, hypothesis 1 which stated that there would be a significant positive relationship 
between psychological capital and work engagement was confirmed.  However, hypothesis 2 
which stated that there would be a significant positive relationship between achievement 
motivation and work engagement was not supported. 
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4.5 Predictors of work engagement 
Pearson Product Moment Correlation Coefficient test revealed that there was no significant 
correlation between achievement motivation and work engagement, hence a simple linear 
regression analysis was conducted to determine the variance in work engagement that could be 
accounted for by psychological capital.  
Table 4:  
Results of a simple linear regression analysis for psychological capital as a predictor of work 
engagement. 
Variable          B        SE              Β 
Constant      43.485      3.302  
Psychological capital          .306        .027           .661*** 
***p < .001 
The results, in Table 4 above, showed a significant regression model (F = 131.41; p < .001), and 
accounted for 43.70% of the variance in work engagement (R2 = .437, Adjusted R2 = .434). 
Psychological capital (β =.661; p < .001), significantly predicted work engagement. This finding 
suggests that micro and small-scale entrepreneurs in this study who reported greater scores of 
psychological capital were more likely to be engaged in their work. This result goes to confirm 
hypothesis 3 which stated that, psychological capital would account for more variance in work 
engagement than achievement motivation. 
 
 
 
 
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4.6 Subscales of psychological capital as predictors of work engagement. 
Table 5: 
Results of hierarchical multiple regression analyses for the dimensions of psychological capital 
as predictors of work engagement 
Variable     B SE β 
Step 1    
Self-efficacy 1.100   .086 .700*** 
Step 2    
Self-efficacy .738  .116 .469*** 
Hope .458  .104 .325*** 
Step 3    
Self-efficacy .710 .118 .452*** 
Hope .331 .137 .235* 
Resilience .211 .148 .127 
Step 4    
Self-efficacy .756 .113 .481*** 
Hope .278 .132 .197* 
Resilience .531 .161 .321*** 
Optimism -.469 .114 -.275*** 
For step 1, R2 = .490, adjusted R2 = .487; for step 2, R2 = 542, adjusted R2 = .537, ΔR2 = .052; for 
step 3, R2 = 548, adjusted R2 = .540, ΔR2 = .006; for step 4, R2 = 590, adjusted R2 = .580, ΔR2 = 
.042; *p < .05; ***p < .001 
Hierarchical multiple regression was conducted to determine the unique significant contribution 
of each subscale (dimension) of psychological capital towards work engagement. The four 
subscales (self-efficacy, resilience, hope and optimism) were entered as predictors in steps 1, 2, 3 
and 4 respectively and work engagement as the criterion variable into the fitted regression model. 
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The results, as presented in Table 5 above, revealed a significant regression model (F = 162.23; p 
< .001; R2 = .490, Adjusted R2 = .487,) for step 1, self-efficacy accounted for 49.00% of the 
variance in work engagement. In step 2, (F = 99.51; p < .001, ΔR2 = .052) was significant. Hope 
contributed an additional 5.2% in the variance of work engagement. In the third step, the regression 
model was significant (F = 67.43; p < .001, ΔR2 = .006). Resilience contributed an additional 6% 
to the variance in work engagement. At the final stage, optimism contributed an additional 4.2% 
to the variance in work engagement.  
 
The entire model was significant when all the four dimensions were included (F = 59.63; p < .001, 
R2 = .590, adjusted R2=.580) Self-efficacy (β = .481; p < .001), hope (β = .197; p < .036), resilience 
(β = .321; p < .001) and optimism (β = -.275; p < .001) uniquely and significantly predicted work 
engagement. These findings suggest that entrepreneurs who reported higher scores of self-efficacy, 
hope, resilience and optimism had more likelihood of experiencing engagement in their work, as 
summarily expressed in Table 5 above. Comparatively, self-efficacy had the most power in 
predicting work engagement than the other subscales. The fourth hypothesis which stated that self-
efficacy will significantly account for more variance in work engagement than the other 
dimensions of hope, resilience and optimism in the psychological capital was confirmed based on 
this results. 
 
 
 
 
 
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4.7 Gender and age group differences on work engagement 
Table 6 
Summary of the Independent t-test comparing gender and age group differences in work  
engagement 
Variable N  Mean   SD  t Sig 
Socio-demographic        
Gender        
 
Male 104 77.07  7.93  -1.54 .266 
 
 Female  67 79.01  8.32   
Age group        
 24-44 136 77.97  7.94  .44 .480 
 
 45-60 35 77.29  8.87   
 
 As shown in Table 6 above, the results of an independent sample t-test that compared the 
differences in the mean score of work engagement according to gender indicated that female 
entrepreneurs (M = 79.01, SD = 8.32) would be more likely to experience work engagement than 
their male counterparts (M = 77.07, SD = 7.92). This difference was, however, not strong enough 
to yield any statistical significance [t (169) = -1.54, p > 0.05].   
 
In terms of age groups mean score on work engagement, younger entrepreneurs with ages ranging 
from 24 to 44 years (M =77.97, SD = 7.94) would be more likely to feel engaged with their work 
than their older counterparts aged 45 and above (M =77.29, SD = 8.87). However, this difference 
did not yield any statistical significance [t (169) = .44, p > 0.05]. Thus hypotheses 5 and 6, which 
sought to find the age differences in work engagement and gender differences in work engagement 
respectively were not supported. 
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4.8 Summary of findings 
After taking the gathered data through the appropriate statistical tests, the following findings were 
observed: 
1.  Psychological capital had a significant positive relationship with work engagement.  
2. Achievement motivation had no significant relationship with work engagement. 
3. It was further observed that psychological capital was a better predictor of work 
engagement than achievement motivation.   
4. The self-efficacy dimension of psychological capital was the best predictor of work 
engagement than the other dimensions of resilience, optimism and hope. 
5.  Finally, there was no significant difference in the level of work engagement of micro and 
small-scale entrepreneurs in terms of gender and age groups 
 
 
 
 
 
 
 
 
 
 
 
 
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                                                                     β = .661*** 
 
        Psychological capital            
Self-efficacy               β = .481*** 
  
             
Resilience              β = .321*** 
 Work engagement 
           β = -.275***                                 
Optimism 
 
    β = .197*                                                                   
Hope 
                                                                                                  
                                                                              DV 
IV   
 Figure 2 
Model of the observed relationship between the psychological capital, its subscales and work 
engagement. 
  
4.9 Summary of the observed relationship between psychological capital, the subscales of it 
and work engagement.                                                                                        
The proposed model predicted that psychological capital and achievement motivation would 
significantly predict work engagement (see Figure 1). However, the data analysis revealed that it 
was only psychological capital that contributed significantly to predicting work engagement. 
Achievement motivation made no significant contribution and was therefore taken out of the 
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model. All the dimensions of psychological capital made significant contributions in predicting 
work engagement. Therefore, Figure 2 presents the model that emerged from the data analysis. 
Since there was no significant difference between gender and age of entrepreneurs in their work 
engagement, the observed model (Figure 2) applies to both male and female entrepreneurs 
irrespective of their age. 
 
4.10 Conclusion 
The stated study hypotheses were analysed using the appropriate statistical methods. Out of the 
five hypotheses stated, three were confirmed. Based on the outcome of the data analysis, the 
proposed research model was revised to reflect the significant relationships among the study 
variables. A multiple hierarchical regression showed that all the subscales of psychological capital 
contributed significantly to the variance in work engagement. A discussion of the findings is 
carried out in the next chapter. 
 
 
 
 
 
 
 
 
 
 
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CHAPTER FIVE 
 
DISCUSSION, RECOMMENDATION AND CONCLUSION 
 
5.1 Introduction 
The study was conducted to explore how both psychological capital and achievement motivation 
predict work engagement of entrepreneurs running micro and small-scale businesses within Accra.  
The psychological capital was identified to be an important predictor of work engagement. When 
the four dimensions were considered individually, all of them significantly predicted work 
engagement. Comparatively, self-efficacy emerged as the best predictor. Furthermore, no gender 
and age group differences were found in the work engagement. Contrary to what was expected, 
achievement motivation had no significant relationship with either work engagement or 
psychological capital. Practical implications of the findings, limitations and recommendations for 
future research are discussed.  
 
5.2 Psychological capital, achievement motivation and work engagement. 
 
This research showed a significant strong positive relationship between psychological capital and 
work engagement. This outcome is similar with research evidence in the existing literature that put 
forward that the psychological capital of workers has an impact on their level of work engagement 
(Costantini et al., 2017; Kotzé, 2017; Robyn & Mitonga-Monga, 2017; Sihag & Sarikwal, 2014; 
Simons & Buitendach, 2013). Additionally, the observation made in this study that psychological 
capital of entrepreneurs will predict work engagement is consistent with a number of studies in the 
literature (Avey et al., 2010; Bakker et al., 2014; Cooke et al., 2016; Othman & Nasurdin, 2011; 
Paek et al., 2015) However, this is contrary to the observation made by De Waal and Pienaar 
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(2013). They observed that there was no significant relationship between psychological capital and 
work engagement. The evidence from this study reveals that increasing entrepreneur’s level of 
psychological capital comes with increasing level of work engagement. What this means for micro 
and small-scale businesses is that the more the job creators and business owners possess these 
positive psychological resources, the more likely it becomes that they may approach their 
businesses with vigour, dedication and absorption. This could also mean a significant decrease in 
negative physiological problems such as fatigue, headaches and insomnia that have been linked to 
burnout (Herbert, 2011; Rehman et al., 2017). 
 
The confirmation of this hypothesis, first, supports the explanations offered by the Job-Demands 
Resources theory which explains that personal resources which are individual’s positive self-
evaluations are able to predict good work outcomes. This position is affirmed by Bakker and 
Demerouti (2008) who advance that personal resources comprising of the dimensions of 
psychological capital help workers to navigate challenging work environments. Ghanaian micro 
and small-scale entrepreneurs are faced with a myriad of demands such as rising cost of production, 
providing fair compensation to the employees, competition from other businesses running similar 
products among others which can potentially affect their performance, innovative behaviours and 
way they think about their job. The idea of job resources being relevant in fostering dedication to 
task especially when the demands imposed by the job are high as advanced by Bakker and 
Demerouti (2014) further supports the findings.  
 
Secondly, as rightly asserted by Sweetman, Luthans, Avey and Luthans (2011), psychological 
capital of personnel has the ability to influence their level of creativity. In the creative process, 
they devote all their faculties to the task at hand. Bearing this in mind, the Ghanaian micro and 
small-scale entrepreneur fall on their psychological capital to generate innovative ideas to keep 
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them in competition with other well established and bigger brands. They show confidence in taking 
up challenges to come out with the innovative products which later is refined to become 
masterpieces through their constant practices. For example, most local auto mechanics have found 
ways of improvising small parts of car engines and other parts of machines which are difficult to 
obtain from the original manufacturers. Instead of letting this difficulty affect their work 
engagement and eventually their job performance, they take some risk to alter some parts to fit 
into the model they want to achieve. These improvised accessories arise as a result of the difficulty 
in obtaining an original part at a reasonable price. Many of these micro and small-scale 
entrepreneurs adopt innovative ways to beat the high cost involved in their line of production.  
 
Thirdly, psychological capital is able to influence work engagement through the happiness and 
satisfaction it generates in the entrepreneurs as they go about their business. Although the cultural 
narrative is gradually changing, the Ghanaian society gives much recognition to white collar jobs. 
Thus, entrepreneurs operating micro and small businesses are often seen to be performing jobs that 
are menial and not lucrative enough. This false perception can prevent some people from starting 
a small business venture. Nonetheless, individuals with the interest and passion to grow their 
careers in entrepreneurship are likely to remain and begin with small and micro businesses and 
with the right mechanisms in place such small businesses would see growth. Psychological capital 
acts as a buffer against the negative label associated with running micro and small businesses. 
Luthans et al. (2007) explain how hope, in particular, has a positive effect on work happiness, 
satisfaction and commitment. In this regard, hope plays a role in ensuring that the entrepreneur is 
persistent and changes the path when it becomes necessary especially when the job demands 
become greater. In this regard, no matter the amount of social ridicule and other operational 
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challenges they may encounter, their positive psychological resources hold them together and 
lowers the tendency for business attrition to occur. This might account for the reason why despite 
the huge money and resources small businesses were losing due to the recent energy crisis, they 
found alternative means of keeping their work together without crumbling. As rightly admitted by 
Çavuş and Gökçen (2015), psychological capital of the individual adds to the sustainable 
competitive advantage of their business.  
 
Another observation is that most of these entrepreneurs’ sources of livelihood may only be derived 
from these small and micro businesses they operate. They may not have the luxury of having 
multiple streams of income and so they invest all their resources into the running of the business. 
Though starting a business and staying relevant in the industry is difficult, they rely on their 
psychological capital to overcome any storm. Due to the essential role the business plays in their 
lives, they find all means to keep it going. They know the implications of losing the business. 
Another observation is that besides apprentices and other employees may also have this as their 
only source of livelihood. This development puts more pressure on the business owner to do 
everything possible to get the business going successfully. 
 
Contrary to the research expectation, achievement motivation could not make any significant 
contribution to work engagement. This is in contrast to previous studies that have found 
achievement motivation of personnel to influence their level of work engagement (Akhtar, 
Boustani, Tsivrikos & Chamorro-Premuzic, 2015; Hsu, Chen, Yu & Lou, 2010). A reason that 
could account for this study outcome is that the Ghanaian micro and small-scale entrepreneurs are 
not extremely ambitious to take on tasks that they know to be beyond their ability and capacity. 
They are fully aware of the demands of their environment in which their psychological capital is 
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helping them to stay afloat. They would rather strive to keep their small business and a stable 
customer base than to increase it and lose touch with its operations and customers.  
The expectancy-value theory of achievement motivation further supports the claims being made 
from these results. The entrepreneur's input into their businesses and subsequent positive 
expectations are influenced by how they perceive their competencies in the face of the operational 
challenges and difficulties. Based on their personal belief of their strengths and the situation at 
hand, most of them are not eager to develop their micro and small businesses beyond their level 
of perceived competencies.  They fear that any attempt to further expand their businesses would 
rather bring it down. This belief stems from the fact that it is difficult to secure financial resources 
to expand and sustain a business, thus, an entrepreneur will rather prefer to self-finance the 
operations of the small business rather than expand it and later face challenges in getting financial 
and other resources to support its growth.  
 
The interesting view held by Çavuş and Gökçen (2015) that self-efficacy can have a negative 
influence on motivation has been validated in this study. The confidence of these entrepreneurs 
becomes self-limiting.  This development compels them to take on tasks that they perceive is 
within their ability and that which they can manage with their own resources. It is a common thing 
to see especially among entrepreneurs in food businesses. Instead of opening up their businesses 
to accommodate the growing number of customers, they appear to be satisfied serving the same 
number of people daily. This sad development prevents them from increasing their profit margins 
and expanding their businesses to employ other persons. Similar observations can be made from 
other micro and small-scale entrepreneurs who operate their businesses from the comfort of their 
homes.  
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5.3 The dimensions of psychological capital and work engagement. 
In this study, all the four sub-dimensions of psychological capital predicted work engagement. 
This finding is consistent with the evidence provided by Alessandri et al. (2015); Federici and 
Skaalvik (2012); Karatepe and Olugbade (2009); Skaalvik and Skaalvik (2016); Consiglio, 
Borgogni, Di Tecco and Schaufeli (2016); Lu, Xie, and Guo (2018) which suggest that an 
individual’s self-efficacy, optimism, resilience and hope had a significant influence on how well 
they were engaged in a work.  Additionally, the finding in this study is partially supported by the 
evidence presented by Herbert (2011). He found both self-efficacy and optimism as the only 
significant predictors of work engagement. Entrepreneurs with high levels of self-efficacy are 
willing to invest their effort in accomplishing their work goals. This is further supported by 
Luthans et al. (2007). They are of the understanding that individuals with high self-efficacy set 
higher goals for themselves, stay motivated to achieve those goals and they are adaptive to changes 
in their environment as they pursue their set goals. They remain engaged in their work and are less 
likely to experience burnout.  
 
Even though all the dimensions predicted work engagement, self-efficacy emerged as the best 
predictor. In this regard, the micro and small-scale entrepreneurs sampled for my study believe in 
their skills and abilities to effectively manage the processes involved in the running of their 
enterprises.  They have met challenges in the discharge of their work duties and have been able to 
overcome them. This has built their confidence to face other likely challenges that might come 
their way. Nothing stops them from dedicating and absorbing themselves to the sustenance and 
growth of their small ventures. Before most of them started their small and micro businesses, they 
underwent some training and apprenticeship. Through their period of apprenticeship, they might 
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have observed their supervisor face some of the challenges peculiar to their industry. They might 
have picked some knowledge on how to solve some of these issues when they are faced with it. 
This practical training most of them acquired did not only equip them with the skills but also some 
positive psychological attributes of their supervisors might have trickled down on them.  
 
Secondly, it does appear that among the study participants used, self-efficacy is the central attribute 
that holds the other dimensions together. It appears so because self-efficacy has been found to 
predict entrepreneurial intentions even in dangerous zones such as Afghanistan (Bullough et al., 
2014). It requires one’s self-efficacy to be in action before all the other dimensions of 
psychological capital come into force. The Ghanaian micro and small-scale entrepreneur does not 
only rely on his or her abilities and skills to stay engaged at work. They are very much aware of 
how disruptive the informal sector can be. In the process of drawing business growth targets, 
optimism and hope come into play. The entrepreneur is aware of certain unforeseen and 
unpredictable bad events that can disrupt the business flow. They think of alternative ways of 
reaching their target. All of this is factored into the profit and growth projections.  
 
In addition to self-efficacy, the resilience of the Ghanaian entrepreneur is worth discussing. 
Although their enterprises go through different difficult phases, they do not give up. Resilience 
helps them to keep their focus on the business goal.  In the central business district of Accra, some 
of these business owners have had their offices and shops razed by fire. Despite this, they picked 
themselves up and continued the business in temporary locations. They live the adage that says, 
“that which does not kill you makes you stronger.” Entrepreneurs appear to understand the risk 
part of their business and they know how to bounce back from such negative events. Resilient 
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entrepreneurs are able to hold their head above the water and are motivated to work harder and 
reclaim all the losses made. The resiliency of the Ghanaian entrepreneur is very necessary 
considering the unstable foreign exchange rate, the high cost of doing business and other 
challenges they face. Being resilient helps them to keep their eyes on the goal and still remain 
dedicated to their work irrespective of the number of times they face adverse situations. 
 
Finally, hope and optimism also predicted the work engagement of micro and small-scale 
entrepreneurs. Entrepreneurs with relatively high optimism have a general affirmative expectation 
on the future aftermath. This explains why they pursue a career in entrepreneurship especially 
within Ghana when they know the risks and challenges involved.  They are likely to have observed 
or heard of how other people who started doing business the small way have been able to establish 
bigger entrepreneurial firms. This positive expectation of the future helps them to keep their focus 
on the goal. They simply believe that despite all the difficulties they will encounter, things are 
going to work out for them in the end. With them having this in mind, they pursue their job with a 
picture of their future in mind. According to Hmieleski and Baron (2016), optimism fosters good 
physical and psychological well-being among entrepreneurs because of their tendency to focus on 
positive information. By extension, good physical and psychological well-being will lead to being 
more dedicated, absorbed and invigorated to their business ventures. Just like self-efficacy, these 
other dimensions may have been developed in some of these micro and small-scale entrepreneurs 
through their period of apprenticeship or training. 
 
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5.4 Age, gender and work engagement 
It was predicted that younger entrepreneurs would experience higher work engagement than older 
entrepreneurs and also, female entrepreneurs would experience higher levels of work engagement 
than their male colleagues. However, when we look at these characteristics of the entrepreneur, 
neither gender nor age differences had a substantial influence on work engagement.  When the 
data was further investigated, it was revealed that younger entrepreneurs had a slightly higher 
mean score than older entrepreneurs in terms of work engagement. Females also reported a higher 
mean score than males on work engagement. Even though these two hypotheses were not 
supported, the findings can be explained in light of some factors within the Ghanaian economic 
context.  
 
Although the informal business environment in Ghana is confronted with many challenges, there 
is no hindrance to its entry with respect to the age and gender of an individual. To further buttress 
this point, Robson and Obeng (2008) concede that in Ghana, age and gender do not impose any 
barrier to business. With the introduction of entrepreneurship as an academic discipline being 
propagated and studied in some tertiary institutions, people are coming to terms with its potential 
in addressing a range of economic and social issues. Business start-up competitions among 
students and the youth are being rolled up every now and then. Some students are operating micro 
and small-scale businesses such as delivery services, food services, IT support services among 
others. Moreover, there is a strong movement of youth towards the informal sector. Hitherto, jobs 
that were seen as menial such as baking, shoemaking, make up artistry, barbering, home and office 
cleaning and others have now been occupied by most young educated people. The introduction of 
these young people has come with the necessary vibrancy and innovations. Due to this widespread 
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acceptance and attractiveness of entrepreneurship, people who are involved in such businesses are 
not stigmatised irrespective of their socio-economic status. Their services and products are boldly 
advertised on the social media and other convenient spaces. 
 
Again, the general business environment in Ghana is not heavily segregated along age and gender 
lines. Both genders are exposed to the same conditions unlike what pertains in countries like Jordan 
where women do not enjoy the same psychological conditions at work as males (Banihani et al., 
2013). Once an individual is of the acceptable age to engage in labour work and is operating a 
decent business, they are likely to attract the right market.  Gradually, the interface between 
gender-specific informal businesses is fading. For example, beauty salons which used to be the 
preserve of females are gradually assuming a universal work domain with both men and women 
venturing into it. These findings confirm the suggestions made by Ravikumar (2013) and 
Ayangeawam et al. (2014). However, this is contrary to the position held by Shukla et al. (2015) 
that women are more composed and responsible than men, hence being more engaged in their 
work. Our findings suggest that male entrepreneurs are equally composed and responsible as their 
female counterparts. Both genders pull the necessary resources at their disposal to make their 
businesses profitable. It must be emphasised that there are efforts to encourage more women to 
enter into entrepreneurship. A policy paper from the Ministry of trade and industry encourages the 
need for women in micro and small-scale enterprises to receive incentive support to enhance their 
business (Ministry of Trade and Industry, 2011).  
 
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5.5 Implications for work engagement  
The findings of this research go to reinforce the importance of personal resources in promoting 
positive work outcomes as postulated by the job demands-resources theory. This study has proven 
how applicable the job demands-resources theory is in explaining how personal resources of which 
a person’s psychological capital forms part may nurture work engagement in the Ghanaian context. 
Previous evidence that supported the theory largely came from other geographical and work 
contexts. Indeed, this study brings evidence from Ghana and more specifically, within the micro 
and small-scale business space. 
  
Given the importance of the micro and small-scale enterprises in the growth of the country, the 
findings from this research bring on board some practical contributions towards the improvement 
of the psychological capital of entrepreneurs as a way of increasing their levels of work 
engagement. So far, all interventions aimed at improving work performance, profitability and work 
engagement of entrepreneurs have been tangible. According to Tetteh and Frempong, (2007), 
examples of such interventions include the provision of technology and assistance in accessing 
financial support. Interventions aimed at developing the psychological personal resources have not 
been forthcoming.  
 
This study showed how psychological capital could predict the work engagement of entrepreneurs. 
Hence there is an urgent need for the design and implementation of interventions that offer support 
systems to help entrepreneurs in the micro and small-scale business sector of Ghana to develop 
their psychological capital. The National Board for Small Scale Industries, The National 
Vocational and Training institutions and other agencies and trade union groups that champion the 
cause of micro and small-scale enterprises as part of the stimulus packages they give to these 
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entrepreneurs can introduce modules that would broaden the scope of the personal psychological 
resources at the disposal of these entrepreneurs. Over the years, attention has been on the provision 
of tangibles resources these entrepreneurs would need to boost their work outcomes. The 
development of their psychological capital through training workshops and the provision of the 
needed physical resources will likely produce a better result than the outcomes of previous 
intervention programmes.  
 
Considering the fact that training programmes are expensive to run and coupled with limited time, 
entrepreneurial interest groups, associations or agencies may likely not be able to invest in the 
development of all these dimensions of psychological capital at the same time. Training 
programmes should focus on the dimension that would have an optimal influence on work 
engagement and in subsequent training programmes, move on to develop the other dimensions. 
Thus as it has been identified in this research context that self-efficacy has the greatest influence 
on work engagement, any training programme within this setting should focus on developing the 
self-efficacy of the individuals. Such targeted intervention programme would help save cost and 
as well help in maximising the level of work engagement of the entrepreneurs. 
 
Maksimov et al. (2017) admit to the fact that micro and small enterprises hold the potential of 
eradicating poverty in the least developed and developing countries. Further evidence from 
Ethiopia (Mezgebo, Ymesel, & Tegegne, 2017) and Tanzania (Tundui & Tundui, 2012) point to 
how women in particular stand to be empowered economically from micro and small-scale 
business activities. Ghanaian women should be encouraged to enter into small businesses. Though 
this is already being done, more awareness needs to be created and seed capital should be given to 
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interested women to start micro and small businesses. This research identified no significant 
difference in the work engagement of men and women. This implies that when women are given 
the needed business and psychological support, they will be absorbed and dedicated to their 
business and likely to succeed as much as their male counterparts. 
 In a similar manner, people of all working ages who are into micro and small businesses should 
be given the necessary support to excel. Not only would they make a profit for themselves and 
earn a decent living, but the nation would benefit from them through the tax that would be 
generated from them. When the technology savvy youth enters into a domain that is predominantly 
traditional in their approach of doing things, they infuse some fresh ideas and introduce technology 
into the craft. Thus adding value and some quality to the product. This calls for a sustained effort 
in driving entrepreneurial agenda and making the work terrain conducive for people of all age 
whiles fostering work engagement among them. 
 
 
5.6 Limitations of the study 
The study was not without some limitations. The main limitation of this study was the inability of 
the researcher to measure the actual job demands experienced by these micro and small-scale 
entrepreneurs. Secondly, the study was a cross-sectional design in nature as data was obtained 
from entrepreneurs at only one point in time. This design, however, does not allow for follow-up 
studies to be undertaken. Since it has been established according to previous researchers that 
psychological capital is a flexible state unlike personality traits (Luthans et al., 2007) It would have 
therefore been appropriate to do a follow-up study on the participants to examine changes if any 
in their psychological capital and also whether changes in their psychological capital actually 
resulted in changes in their work engagement. The sample size used for this study limits the extent 
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to which the research findings may be generalized. With respect to this, it is important to note that 
applications of the findings in this study to other work populations should be done with restraint. 
The situation of micro and small-scale entrepreneurs in other parts of the country may be different 
which possibly might affect the findings of the study. Regardless of these limitations, the 
authenticity and originality of the results and findings obtained are not compromised. The evidence 
provided could be used to design policies and interventions that would help increase the 
psychological capital of entrepreneurs as a way of increasing their levels of work engagement. 
 
5.7 Recommendations for future research 
In order for future researchers to address the limitations identified in this study, some 
recommendations are put forward. It is recommended that future researchers consider a mixed 
method approach that would improve the ability of studies to provide both descriptive and 
explanatory evidence. A more comprehensive information would have been obtained with the use 
of integrated qualitative and quantitative methods. Such studies would help to better understand 
the relationships that exist between important organisational and human variables and the reasons 
behind such relationships especially in developing countries like Ghana. Adopting this technique 
could also be of more help to supervisory agencies and interest entrepreneurial groups in designing 
interventions that address organisational behavioural problems in-depth.  
Also, in order to obtain results and findings that can be generalised across a broader population, 
there is the need for future researchers to gather enough financial and material resources to enable 
them to involve a much bigger sample size. Supervisory bodies and interest groups like the 
National Board for Small Scale Industries, Beauticians association, Entrepreneurs hub and others 
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can be appealed to encourage their members to participate in such studies since the findings would 
inure to their benefit.  
 
Similar studies can be carried out in other population such as teachers, police and other public 
sector organisations. This would help broaden the scope of literature with respect to how 
psychological capital and achievement motivation may engender work engagement. Such studies 
would be of great value to the nation as it looks to remove bottlenecks in their operations to fast-
track its development goals.  
  
As a final point, future researchers within the context of Ghana can consider incorporating work 
context and leadership styles into the study of psychological capital and work engagement. How 
this construct affects their psychological capital and work engagement needs to be examined. 
Furthermore, the relationship between demographic factors and work engagement needs to be 
studied further. This calls for more exploration, especially within the Ghanaian context. 
 
 
5.8 Conclusion 
The main purpose of this cross-sectional survey was to examine the relationship between 
psychological capital, achievement motivation and work engagement in micro and small-scale 
entrepreneurs. The outcomes of the study suggest that whiles achievement motivation did not make 
either any significant relationships with the other variables or contributed significantly to the 
variance in work engagement, the psychological capital, on the other hand, had a significant 
positive relationship with work engagement and additionally, made a significant contribution to 
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the variance in work engagement. It was observed that all the four dimensions of psychological 
capital significantly predicted work engagement. Furthermore, findings from the study revealed 
that work engagement does not differ significantly across genders and age groups.  
 
These findings underscore the need for the developing of workplace interventions that promote 
positive organisational behaviour. For example, agencies that nurture young entrepreneurs in 
schools and outside should include in their training modules, exercises that would improve on the 
psychological capital of their participants as a comprehensive way of developing the potential 
talent even as other measures are put in place to stimulate work engagement in the informal sector. 
The implementations of such interventions would enhance the work engagement of entrepreneurs 
which would then affect the growth and sustainability of micro and small businesses. These 
businesses if given the necessary attention and resources would potentially help in alleviating 
poverty and reducing unemployment.
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APPENDICES 
APPENDIX 1: INFORMED CONSENT 
 
             UNIVERSITY OF GHANA 
Official Use only 
Protocol number 
 
  
Ethics Committee for Humanities (ECH) 
 
PROTOCOL CONSENT FORM  
 
 
Section A- BACKGROUND INFORMATION 
 
Title of Study:  Kt Psychological capital and achievement motivation as predictors of work engagement 
 among micro and small-scale entrepreneurs 
Principal Investigator: Emmanuel Anokye Nkansah 
 
Certified Protocol ECH 046/17-18 
Number 
 
Section B– CONSENT TO PARTICIPATE IN RESEARCH 
 
General Information about Research 
You are invited to participate in an academic research project which is aimed at examining the 
relationships between psychological capital, achievement motivation and work engagement in 
entrepreneurs. The purpose of the study is to provide insight into how psychological capital and 
achievement motivation may individually and or collectively impact on the entrepreneurs’ positive 
feelings of vigour, dedication and absorption in their line of work. It will take not more than 30 
minutes for you to complete the questionnaire that will be provided. Your participation in the study 
ends as soon as you complete the questionnaire. It is a paper and pencil questionnaire that will 
require you to respond honestly and objectively to certain statements as they apply to you in your 
line of work. Please feel free to ask questions if you do not understand anything. 
Benefits/Risks of the study 
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This study is not intended to benefit you directly. Nonetheless, your participation in the research 
will help provide insight into how psychological capital and achievement motivation affect work 
engagement of entrepreneurs. There are no foreseeable risks or consequences for taking part in the 
research. You will be allowed to complete the questionnaire in your free time. 
Confidentiality  
You are assured of complete confidentiality of any information you provide. Only the researcher 
will have access to the data you will provide. By signing this form you agree to give such access. 
The results will be reported in an aggregated format (e.g., as averages, etc.), and under no 
circumstance will any individual participant be identified in a publication or presentation 
describing this study. 
Compensation  
You will receive no compensation for taking part in this study 
Withdrawal from Study 
Your participation is voluntary and you may withdraw at any time without penalty. You will not be 
adversely affected if you decline to participate or later stop participating.  
Contact for Additional Information  
You can contact the following for any answers to any questions about the research. 
Emmanuel Anokye Nkansah. (Investigator), Department Of Psychology University of Ghana 
0274774864. enanokye001@st.ug.edu.gh 
Also If you have any questions about your rights as a research participant in this study you may 
contact the Administrator of the Ethics Committee for Humanities, ISSER, University of Ghana 
at ech@isser.edu.gh / ech@ug.edu.gh  or 00233- 303-933-866. 
Section C- PARTICIPANT AGREEMENT 
 
"I have read or have had someone read all of the above, asked questions, received answers 
regarding participation in this study, and am willing to give consent for me, my child/ward to 
participate in this study. I will not have waived any of my rights by signing this consent form. 
Upon signing this consent form, I will receive a copy for my personal records." 
 
________________________________________________ 
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Name of Participant 
_________________________________________________    _______________________ 
Signature or mark of Participant    Date    
 
If participant  cannot read  and or understand the form themselves, a witness must sign 
here:  
I was present while the benefits, risks and procedures were read to the volunteer. All questions 
were answered and the volunteer has agreed to take part in the research.  
_________________________________________________ 
Name of witness 
 
________________________________________________   _______________________   
Signature of witness  / Mark     Date 
 
I certify that the nature and purpose, the potential benefits, and possible risks associated with 
participating in this research have been explained to the above individual.  
 
__________________________________________________  
Name of Person who Obtained Consent 
 
___________________________________________    ______________________ 
Signature of Person Who Obtained Consent    Date   
 
 
 
 
 
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APPENDIX II 
DATA COLLECTION INSTRUMENT 
UNIVERSITY OF GHANA 
DEPARTMENT OF PSYCHOLOGY 
 
 
DATA COLLECTION INSTRUMENT 
 
The researcher is a student of the University of Ghana conducting a study on “Psychological capital and 
achievement motivation as predictors of work engagement among micro and small-scale 
entrepreneurs.” This study will provide empirical evidence to micro and small-scale entrepreneurs on 
how psychological capital and achievement motivation individually and collectively enhance their level 
of work engagement. The micro and small-scale business sector has largely been ignored in studies on 
work engagement. Therefore your participation will help researchers understand the impact of positive 
personal resources in promoting work engagement of micro and small-scale entrepreneurs. The 
questionnaire will take about 15 minutes to complete. There are no anticipated risks in participating in 
this study. Any information you give out will be kept confidential. Results of the study shall be presented 
in aggregated forms and will have no links to you personally in any way.  If you agree to participate in 
this study, please read the instructions and continue to fill out the questionnaire. For further information 
or questions about this research please contact Emmanuel Anokye Nkansah on 0274774864. 
  
Instructions  
The questionnaire is in four sections: section A to section D and should be completed by you. Please be as 
truthful and accurate as possible in your responses to ensure true results of the study.  
Thank you.  
 
 
SECTION A.  Demographic data 
 
1. Gender:  Male     Female  
2. Please state number of employees you have……………… 
3. Please how long has the business been in existence:…………….. 
4. Nature of job (eg. IT, Food etc)……………… 
5. Marital status: Married      Single       Divorced    Separated  
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6. Please state your age:…………….. 
 
SECTION B 
Instructions: Below are statements that describe how you may think about yourself right now. Use the 
following scale to indicate your level of agreement or disagreement with each statement. 
Strongly   Disagree Disagree Somewhat Somewhat Agree Strongly Agree 
1 2 Disagree Agree 5 6 
3 4 
 
 
1 I feel confident analyzing a long-term problem to find a solution. 1 2 3 4 5 6 
2 I feel confident in representing my work area in meetings with 1 2 3 4 5 6 
my workers 
3 I feel confident contributing to discussions about the company's 1 2 3 4 5 6 
strategy. 
4 I feel confident helping to set targets/goals in my work area. 1 2 3 4 5 6 
5 I feel confident contacting people outside the company (e.g., 1 2 3 4 5 6 
suppliers, customers) to discuss problems. 
 
6 I feel confident presenting information to a group of colleagues. 1 2 3 4 5 6 
7 If I should find myself in a jam at work, I could think of many 1 2 3 4 5 6 
ways to get out of it. 
8 At the present time, I am energetically pursuing my work goals. 1 2 3 4 5 6 
9 There are lots of ways around any problem. 1 2 3 4 5 6 
10 Right now I see myself as being pretty successful at work. 1 2 3 4 5 6 
11 I can think of many ways to reach my current work goals. 1 2 3 4 5 6 
12 At this time, I am meeting the work goals that I have set for 1 2 3 4 5 6 
myself. 
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13 When I have a setback at work, I have trouble recovering from it, 1 2 3 4 5 6 
moving on. 
14 I usually manage difficulties one way or another at work. 1 2 3 4 5 6 
15 I can be “on my own,” so to speak, at work if I have to. 1 2 3 4 5 6 
16 I usually take stressful things at work in stride. 1 2 3 4 5 6 
17 I can get through difficult times at work because I've experienced 1 2 3 4 5 6 
difficulty before. 
18 I feel I can handle many things at a time at this job. 1 2 3 4 5 6 
19 When things are uncertain for me at work, I usually expect the 1 2 3 4 5 6 
best. 
 
20 If something can go wrong for me work-wise, it will 1 2 3 4 5 6 
21 I always look on the bright side of things regarding my job. 1 2 3 4 5 6 
22 I'm optimistic about what will happen to me in the future as it 1 2 3 4 5 6 
pertains to work. 
23 In this job, things never work out the way I want them to. 1 2 3 4 5 6 
24 I approach this job as if “every cloud has a silver lining.” 1 2 3 4 5 6 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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SECTION C 
Use the following scale to indicate your level of agreement or disagreement. Yes – 3 Not certain – 2 No-  
1  
1 Is being comfortable more important to you than getting ahead? 3 2 1 
2 Are you satisfied to be no better than most other people at your job? 3 2 1 
3 Do you like to make improvements to the way the business you belong to 3 2 1 
functions? 
4 Do you take trouble to cultivate people who may be useful to you in your 3 2 1 
career? 
5 Do you get restless and annoyed when you feel you are wasting time? 3 2 1 
6 Have you always worked hard in order to be among the best in your own line? 3 2 1 
7 Would you prefer to work with a congenial but incompetent partner rather than 3 2 1 
with a difficult but highly competent one? 
8 Do you tend to plan ahead for your job or career? 3 2 1 
9 Is "getting on in life" important to you? 3 2 1 
10 Are you an ambitious person? 3 2 1 
11 Are you inclined to read of the successes of other rather than do the work of 3 2 1 
making yourself a success? 
12 Would you describe yourself as being lazy? 3 2 1 
13 Will days often go by without your having done a thing? 3 2 1 
14 Are you inclined to take life as it comes without much planning? 3 2 1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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SECTION D 
 
Please read each statement carefully and indicate how often you feel it by indicating the number (from 1 
to 6) that best describes how frequently you feel that way. 
Never(0) Almost never    Rarely(2) Sometimes(3)   Often(4) Very Always(6) 
          (1)    often(5)  
    
 
1. _______ At my work, I feel bursting with energy 
2. ________ I find the work that I do full of meaning and purpose  
3. ________ Time flies when I'm working  
4. ________ At my job, I feel strong and vigorous  
5. ________ I am enthusiastic about my job  
6. ________ When I am working, I forget everything else around me  
7. ________ My job inspires me  
8. ________ When I get up in the morning, I feel like going to work 
9. ________ I feel happy when I am working intensely 
10. ________ I am proud on the work that I do  
11. ________ I am immersed in my work 
12. ________ I can continue working for very long periods at a time  
13. ________ To me, my job is challenging  
14. ________ I get carried away when I’m working  
15. ________ At my job, I am very resilient, mentally  
16. ________ It is difficult to detach myself from my job 
17. ________ At my work I always persevere, even when things do not go well  
 
 
 
 
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APPENDIX III 
RELIABILITY OF STUDY VARIABLES 
Scale: Psychological Capital Questionnaire  
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
           Reliability Statistics  
Cronbach's Alpha N of Items  
.917 24  
 
scale: Self-efficacy 
 
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
.Reliability Statistics 
Cronbach's Alpha N of Items 
.845 6 
 
 
 
 
 
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Scale: Hope 
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
Reliability Statistics 
Cronbach's Alpha N of Items 
.878 6 
 
Scale: Resilience 
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
Reliability Statistics 
Cronbach's Alpha N of Items 
.728 6 
 
Scale: Optimism 
 
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
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Reliability Statistics 
Cronbach's Alpha N of Items 
.617 6 
 
 
Scale: Achievement Motivation  
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
Reliability Statistics 
Cronbach's Alpha N of Items 
.701 14 
 
Scale: Utrecht Work Engagement  
Case Processing Summary 
 N % 
Valid 171 100.0 
Cases Excludeda 0 .0 
Total 171 100.0 
a. Listwise deletion based on all variables in the 
procedure. 
 
 
Reliability Statistics 
Cronbach's Alpha N of Items 
.787 17 
 
 
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APPENDIX IV 
DESCRIPTIVE STATISTICS 
N Minimum Maximum Mean Std. Deviation Skewness Kurtosis 
Std. Std. 
 Statistic Statistic Statistic Statistic Statistic Statistic Error Statistic Error 
Work engagement 171 58.00 95.00 77.83 8.113 -.377 .186 .035 .369 
Psychological .186 
171 58.00 135.00 112.16 17.523 -1.289 1.687 .369 
capital 
Efficacy 171 13.00 36.00 30.22 5.162 -1.602 .186 2.582 .369 
Hope 171 14.00 36.00 28.246 5.754 -.705 .186 -.300 .369 
Resilience 171 15.00 35.00 27.158 4.895 -.619 .186 .026 .369 
Optimism 171 14.00 33.00 26.532 4.747 -1.168 .186 .407 .369 
Achievement .186 .369 
171 22.00 42.00 34.427 5.540 .379       -.836 
motivation 
Valid N (listwise) 171         
 
 
 
 
 
 
 
 
 
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APPENDIX V 
REGRESSION TABLES 
 
Model Summary 
Model R R Square Adjusted R Std. Error of Change Statistics 
Square the Estimate R Square F Change df1 df2 Sig. F Change 
Change 
1 .661a .437 .434 6.10325 .437 131.407 1 169 .000 
a. Predictors: (Constant), totpsycap 
 
 
 
 
ANOVAa 
Model Sum of Squares df Mean Square F Sig. 
Regression 4894.884 1 4894.884 131.407 .000b 
1 Residual 6295.198 169 37.250   
Total 11190.082 170    
a. Dependent Variable: totweng 
b. Predictors: (Constant), totpsycap 
 
 
Coefficientsa 
Model Unstandardized Coefficients Standardized t Sig. 
Coefficients 
B Std. Error Beta 
(Constant) 43.485 3.032  14.341 .000 
1 
totpsycap .306 .027 .661 11.463 .000 
a. Dependent Variable: totweng 
 
 
 
 
 
 
 
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Model Summary 
Model R R Square Adjusted R Std. Error of Change Statistics 
Square the Estimate 
R Square F Change df1 df2 Sig. F Change 
Change 
1 .700a .490 .487 5.81239 .490 162.226 1 169 .000 
2 .736b .542 .537 5.52169 .052 19.263 1 168 .000 
3 .740c .548 .540 5.50472 .006 2.037 1 167 .155 
4 .768d .590 .580 5.25945 .042 16.939 1 166 .000 
a. Predictors: (Constant), Efficacy 
b. Predictors: (Constant), Efficacy, Hope 
c. Predictors: (Constant), Efficacy, Hope, Resilience 
d. Predictors: (Constant), Efficacy, Hope, Resilience, Optimism 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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ANOVAa 
Model Sum of Squares df Mean Square F Sig. 
Regression 5480.616 1 5480.616 162.226 .000b 
1 Residual 5709.466 169 33.784   
Total 11190.082 170    
Regression 6067.921 2 3033.960 99.510 .000c 
2 Residual 5122.161 168 30.489   
Total 11190.082 170    
Regression 6129.659 3 2043.220 67.429 .000d 
3 Residual 5060.423 167 30.302   
Total 11190.082 170    
Regression 6598.212 4 1649.553 59.633 .000e 
4 Residual 4591.870 166 27.662   
Total 11190.082 170    
a. Dependent Variable: totweng 
b. Predictors: (Constant), Efficacy 
c. Predictors: (Constant), Efficacy, Hope 
d. Predictors: (Constant), Efficacy, Hope, Resilience 
e. Predictors: (Constant), Efficacy, Hope, Resilience, Optimism 
 
 
 
 
 
 
 
 
 
 
 
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Coefficientsa 
Model Unstandardized Coefficients Standardized t Sig. Collinearity Statistics 
Coefficients 
B Std. Error Beta Tolerance VIF 
(Constant) 44.586 2.648  16.840 .000   
1 
Efficacy 1.100 .086 .700 12.737 .000 1.000 1.000 
(Constant) 42.594 2.556  16.665 .000   
2 Efficacy .738 .116 .469 6.336 .000 .497 2.013 
Hope .458 .104 .325 4.389 .000 .497 2.013 
(Constant) 41.288 2.707  15.251 .000   
Efficacy .710 .118 .452 6.037 .000 .483 2.068 
3 
Hope .331 .137 .235 2.414 .017 .286 3.492 
Resilience .211 .148 .127 1.427 .155 .340 2.940 
(Constant) 45.154 2.752  16.408 .000   
Efficacy .756 .113 .481 6.694 .000 .479 2.089 
4 Hope .278 .132 .197 2.112 .036 .284 3.526 
Resilience .531 .161 .321 3.294 .001 .261 3.831 
Optimism -.469 .114 -.275 -4.116 .000 .555 1.801 
a. Dependent Variable: totweng 
 
 
 
 
 
 
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APPENDIX VI 
INDEPENDENT T TEST 
 
Group Statistics 
 Gender N Mean Std. Deviation Std. Error Mean 
Male 104 77.0673 7.92595 .77720 
totweng 
Female 67 79.0149 8.31664 1.01604 
 
Independent Samples Test 
 Levene's Test for t-test for Equality of Means 
Equality of 
Variances 
F Sig. t df Sig. (2- Mean Std. 95% Confidence 
tailed) Differenc Error Interval of the 
e Differenc Difference 
e 
Lower Upper 
Equal variances 1.247 .266 - 169 .126 -1.94762 1.26589 -4.44662 .55138 
assumed 1.539 
totweng 
Equal variances   - 135.9 .130 -1.94762 1.27921 -4.47733 .58210 
not assumed 1.523 97 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Group Statistics 
 Age_group N Mean Std. Deviation Std. Error Mean 
Young 136 77.9706 7.93580 .68049 
totweng 
Old 35 77.2857 8.87021 1.49934 
 
 
 
 
Independent Samples Test 
 
Levene's Test for Equality t-test for Equality of Means 
of Variances 
F Sig. t df Sig. (2- Mean Std. Error 95% Confidence Interval 
tailed) Difference Difference of the Difference 
Lower Upper 
Equal variances .500 .480 .444 169 .657 .68487 1.54140 -2.35800 3.72775 
assumed 
totweng 
  
Equal variances not .416 48.927 .679 .68487 1.64654 -2.62409 3.99384 
assumed 
 
 
 
 
 
 
 
 
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