The Influence of Entrepreneur Personality and Self-Efficacy on Behavioural Activities in the Presence of Information Overload Manisha Karia Thesis submitted in fulfilment of the r equirements for the degree of Doctor of Philosophy Faculty of Business and Enterprise Swinburne University of Technology 2015
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The Influence of Entrepreneur Personality and Self-Efficacy on Behavioural Activities in
the Presence of Information Overload
Manisha Karia
Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy
Faculty of Business and Enterprise
Swinburne University of Technology
2015
i
ABSTRACT
Entrepreneurship is the bedrock of creating new businesses and wealth. Undoubtedly,
the entrepreneur lies at the core of the entrepreneurial process and venture performance.
Prior research has focused on investigating the characteristics of entrepreneurs, the
antecedents of venture creation, and the stages of entrepreneurship. However, the
relationship between entrepreneurs’ characteristics and their behaviours was not given
much attention. Further, recent advances in information and communication technology
have created new challenges for entrepreneurs’ ability and behaviour but this has not
been examined empirically. My research attempts to address these critical issues.
The purpose of the thesis was to examine the impact of the entrepreneur’s personality
characteristics and entrepreneurial self-efficacy on entrepreneurial behavioural activities
in the presence of information overload. Based on a review of extant literature and
discussions with academics and practicing entrepreneurs, I have developed a conceptual
model that incorporates entrepreneurial personality factors, dimensions of
entrepreneurial self-efficacy and various entrepreneurial behavioural activities. Further,
I have included the concept of information overload in my model. In personality
characteristics, I have included three dimensions: the need for achievement, internal
locus of control, and risk-taking propensity. Entrepreneurial self-efficacy has six
implementing finance-related tasks and coping with unexpected challenges. The newly
operationalised construct of entrepreneurial behaviours has eight activities: planning,
controlling, internal communication, human resources management, work-related tasks,
customer service, socialising and politicking. All the variables were hypothesised to
have a positive relationship, excepting information overload, which was posited to have
a negative impact.
The sample was drawn from India, which is a large emerging economy. Data were
collected through a survey covering 1,100 practicing entrepreneurs spread throughout
India. A final usable sample of 403 was obtained. The tests for reliability and validity
ii
of the measurement scale used in this study established the psychometric rigour of the
conceptual model. Each path identified in the conceptual model was tested using
regression-based path analysis.
The results revealed a positive relationship between the personality dimensions of the
need for achievement and risk-taking propensity with all the six dimensions of
entrepreneurial self-efficacy, but the internal locus of control was related positively only
to three dimensions, namely implementing people-related tasks, implementing finance-
related tasks, and coping with unexpected challenges. Similarly, the three entrepreneur
personality characteristics were related to only a few entrepreneurial behavioural
activities, not all. The relationship between entrepreneurial self-efficacy and
entrepreneurial behavioural activities also indicated that only some of these were
related. As expected, information overload has a negative impact on most of the self-
efficacy variables but only on some behavioural activities.
My study provides a significant contribution to the body of literature by confirming that
entrepreneurial self-efficacy has many dimensions that need to be treated differently.
This is the first time information overload has been included in entrepreneurship
studies. I also created a platform for empirically testing entrepreneurial self-efficacy and
entrepreneurial behavioural activities for future research. Overall, the results from my
study have strong implications for scholars, entrepreneurs and policymakers,
particularly those in emerging economies.
Nonetheless, a major limitation of the study is the generalisability of the findings. The
sample is from owner-managers from different cities and industries in India, which may
include inter-regional and inter-industry differences. Therefore, care should also be
taken before these results can be applied to other emerging economies due to their
differences. Future studies could, therefore, undertake an in-depth examination of
regional and industry differences among entrepreneurs in India, as well as replicate the
study in other emerging economies. The concept of entrepreneurial information
overload can be explored further to find how the information-seeking behaviour of
entrepreneurs is impacted by information overload.
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ACKNOWLEDGEMENTS
Blessed are those who find wisdom, those who gain understanding (Proverbs 3: 13).
First and foremost, I would like to thank God, without whose abundant grace this thesis
would have not become a reality. I am truly grateful for God’s provision and guidance
in undertaking this research successfully. Through this research experience, I have
learnt how to face challenges and grow through God’s grace.
I wish to express my sincere thanks to my supervisory team consisting of Dr Malcolm
Abbott and Dr Alexis Espesto of the Swinburne University of Technology, and
Dr Hanoku Bathula of the University of Auckland. Dr Malcolm Abbott was kind
enough to accept me as his research student and also provide guidance and support
during the entire period of the study. I am particularly grateful for his encouragement to
apply for scholarship for my doctoral research. I also wish to thank Dr Alexis Espesto
for his periodic support and feedback on my progress. I also express my deep
appreciation to Dr Hanoku Bathula, who has encouraged and helped me at every stage
in completing this research thesis. I will never be able to thank him enough for his
invaluable support.
I would like to express my sincere gratitude to Dr Sanjaya Gaur of Auckland University
of Technology who was generous in giving his valuable time and expert advice,
particularly in designing the survey and data analysis. I also wish to acknowledge the
support I received from the management and other colleagues of Auckland Institute of
Studies. I want to mention Dr Mike Roberts, Dr Ershad Ali and Sawsan Al-Shamaa for
their timely support and encouragement over the period of my study. Very special
thanks are due to Tony Ó Braonáin for patiently reading my manuscripts and making
suggestions.
As my data were collected from India, I had to seek help from several people in
finalising the survey instrument and also with the collection of data. In this regard, I
wish to acknowledge the support of senior academics from various Indian universities,
Dr. Karuppasamy Ramanathan (Director, Management Studies, Nehru Institute of
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Technology, Coimbatore), Dr. Githa Heggde (Professor of Marketing, WeSchool,
Bengaluru), Dr. Sandip Kar (Chairman, IIMS, Kolkata), and Dr Ramanujam Krishnaraj
(Assistant Professor, Management Studies, SRM University, Chennai). I want to also
thank Mr Ganapathi Batthini, Librarian, Entrepreneurship Development Institute of
India, for his timely help in providing information about the status of entrepreneurship
in India. It is not out of place to thank all the 650 respondents from India who have
spent their valuable time in filling in the surveys and making this study happen. A big
thank you to all the research and administrative staff, Ms Anne Cain, Ms Nadine White
and others at Swinburne University of Technology for their support throughout the last
four years. I especially want to acknowledge the fee scholarship awarded to me by
Swinburne University of Technology.
My special gratitude is to my dearest daughter, Khyaati Narayani, for her undying love,
understanding and support even during the times of frustration. She gave up so many
evenings and weekends so that I could complete my study. During stressful times, she
has been my biggest supporter and has always believed in my ability to complete this
thesis. My special thanks are due to my beloved parents, Rajnikant and Latha Karia,
who have provided me with unconditional love and endless support. They have not
only helped me with their contacts for data collection, but also looked after my daughter
when I was focusing on the thesis. My thanks also go to my loving sister and her
husband, Vaidehi and Tejal Shah, for their encouragement, and to my nieces, Kavya and
Nitya, who have also cheered me up through my doctoral journey.
There are several others that I wish to thank personally, but I am not able to mention all
of them due to limitations of space. I will always remember them with gratitude.
Manisha Karia
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DECLARATION
I, Manisha Karia, declare that: This thesis contains no material which has been accepted for the award to the candidate of any other degree or diploma, except where due reference is made in the text of the examinable outcome; To the best of the candidate’s knowledge, it contains no material previously published or written by another person except where due reference is made in the text of the examinable outcome; and Where the work is based on joint research or publications, it discloses the relative contributions of the respective workers or authors.
Manisha Karia 10 April 2015
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TABLE OF CONTENTS ABSTRACT ...................................................................................................................... i ACKNOWLEDGEMENTS.......................................................................................... iii DECLARATION ............................................................................................................. v LIST OF TABLES ......................................................................................................... xi LIST OF FIGURES ..................................................................................................... xiv LIST OF ABBREVIATIONS ...................................................................................... xv CHAPTER 1 INTRODUCTION ............................................................................. 1
1.1 Factors impacting on the entrepreneur’s performance ........................................................ 1
CHAPTER 4 CONCEPTUAL FRAMEWORK AND HYPOTHESES ........... 103
4.1 Conceptual framework and theoretical model ................................................................ 103
4.2 Personality characteristics and entrepreneurial self-efficacy .......................................... 104
4.2.1 Personality characteristic of need for achievement and dimensions of entrepreneurial self-efficacy.............................................................................................................. 106
4.2.2 Personality characteristic of internal locus of control and dimensions of entrepreneurial self-efficacy .................................................................................... 108
4.2.3 Personality characteristic of risk-taking propensity and dimensions of entrepreneurial self-efficacy.............................................................................................................. 110
4.3 Entrepreneurial information overload and entrepreneurial self-efficacy ........................ 112
4.4 Entrepreneurial information overload and entrepreneurial behavioural activities .......... 113
4.5 Personality characteristics and entrepreneurial behavioural activities ............................ 115
4.5.1 Personality characteristic of need for achievement and entrepreneurial behavioural activities ................................................................................................................... 116
4.5.2 Personality characteristic of internal locus of control and entrepreneurial behavioural activities ................................................................................................................... 118
4.5.3 Personality characteristic of risk-taking propensity and entrepreneurial behavioural activities ................................................................................................................... 119
4.6 Entrepreneurial self-efficacy and entrepreneurial behavioural activities ........................ 121
4.6.1 Dimensions of entrepreneurial self-efficacy and the planning dimension of entrepreneurial behavioural activities ...................................................................... 122
viii
4.6.2 Dimensions of entrepreneurial self-efficacy and the controlling dimension of entrepreneurial behavioural activities ...................................................................... 123
4.6.3 Dimensions of entrepreneurial self-efficacy and the internal communication dimension of entrepreneurial behavioural activities ................................................ 124
4.6.4 Dimensions of entrepreneurial self-efficacy and the human resources dimension of entrepreneurial behavioural activities ...................................................................... 125
4.6.5 Dimensions of entrepreneurial self-efficacy and the work-related task dimension of entrepreneurial behavioural activities ...................................................................... 127
4.6.6 Dimensions of entrepreneurial self-efficacy and the customer service dimension of entrepreneurial behavioural activities ...................................................................... 128
4.6.7 Dimensions of entrepreneurial self-efficacy and the socialising dimension of entrepreneurial behavioural activities ...................................................................... 129
4.6.8 Dimensions of entrepreneurial self-efficacy and the politicking dimension of entrepreneurial behavioural activities ...................................................................... 130
6.5.1 Effects of personality characteristics and entrepreneurial information overload on the searching capability dimension of entrepreneurial self-efficacy.............................. 180
6.5.2 Effects of personality characteristics and entrepreneurial information overload on the planning capability dimension of entrepreneurial self-efficacy ............................... 181
6.5.3 Effects of personality characteristics and entrepreneurial information overload on the marshalling capability dimension of entrepreneurial self-efficacy .......................... 182
6.5.4 Effects of personality characteristics and entrepreneurial information overload on the implementing people-related capability dimension of entrepreneurial self-efficacy184
6.5.5 Effects of personality characteristics and entrepreneurial information overload on the implementing finance capability dimension of entrepreneurial self-efficacy .......... 185
6.5.6 Effects of personality characteristics and entrepreneurial information overload on the coping with unexpected challenges capability dimension of entrepreneurial self-efficacy ..................................................................................................................... 186
6.5.7 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the planning dimension of entrepreneurial behavioural activities. .................................................................................................................. 188
6.5.8 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the controlling dimension of entrepreneurial behavioural activities. .............................................................................................. 190
6.5.9 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the internal communication dimension of entrepreneurial behavioural activities. ..................................................................... 193
6.5.10 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the human resources management dimension of entrepreneurial behavioural activities. ..................................................................... 195
6.5.11 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the work-related tasks dimension of entrepreneurial behavioural activities. .............................................................................................. 198
6.5.12 Testing the effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the customer service dimension of entrepreneurial behavioural activities. ..................................................................... 200
6.5.13 Testing the effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the socialising dimension of entrepreneurial behavioural activities. ..................................................................... 203
x
6.5.14 Testing the effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the politicking dimension of entrepreneurial behavioural activities. ..................................................................... 205
6.5.15 Summary of findings for hypotheses tested ............................................................ 208
6.6.1 Relationship between personality characteristics and entrepreneurial self-efficacy . 212
6.6.2 Relationship between entrepreneurial self-efficacy and entrepreneurial behavioural activities ................................................................................................................... 216
6.6.3 Relationship between personality characteristics and entrepreneurial behavioural activities ................................................................................................................... 217
6.6.4 Impact of entrepreneurial overload on entrepreneurial self-efficacy ........................ 222
6.6.5 Impact of entrepreneurial information overload on entrepreneurial behavioural activities ................................................................................................................... 223
Knight (1921/1971) and Say (1803/2001) to the academic discussion on
entrepreneurship. In modern times, the term entrepreneurship has been used differently
in diverse disciplines over the years (Gartner 1990; Hebert & Link 1989; Ireland &
Webb 2007; Murphy, Liao & Welsh 2006), each contributing to building a general
theory of entrepreneurship. Therefore, to understand what constitutes entrepreneurial
activity and to arrive at an acceptable definition of entrepreneurship and / or an
entrepreneur, the views put forth by different schools of thought were commonly
distinguished as classical, neo-classical, Austrian and behavioural approaches; the main
ideas of these approaches are examined here.
The term ‘entrepreneur’ is derived from the French word ‘entreprendre’ which means
‘to undertake’ (Oxford Dictionary, 2009). The earliest reference to the term
‘entrepreneur’ was made by Cantillon (1680-1734) from an economic perspective by
describing an entrepreneur as one who engages in arbitrage and bears risk. Say (1767-
1832) interpreted the role of the entrepreneur as being central to a firm as a co-ordinator
and manager. He assigns an important position to the entrepreneur in production,
distribution and consumption. Other economists, such as Alfred Marshall (1842-1924),
extended the meaning of entrepreneur to include not only the ‘risks’ relating to the
supply of commodities (production), but also making provision for innovation and
progress (Hebert & Link 1989). Marshall believed entrepreneurs are cost minimisers
and therefore innovators, who embody a set of abilities that are scarce in any society.
An early contributor to the development of the theory of entrepreneurship was
Schumpeter (1883-1950), who focused on innovation as an endogenous process and the
entrepreneur as being a prime mover within the economic system through innovation.
Schumpeter, however, did not support the notion of the entrepreneur as a capitalist and
risk-bearer. Instead, he defines an entrepreneur as a person who seeks opportunities for
profit through ‘new combinations’ in production. This ‘new combination’ is
14
synonymous with innovation, which is the basis for meaningful economic progress. In
this process, old firms that are incapable of carrying out ‘new combinations’ cease to
exist and are replaced by firms that are able to perform the ‘new combination’ or
innovation. Schumpeter observes that such an entrepreneur possesses ‘a mental freedom
… [that] is something peculiar and by nature rare’ (1934, p. 86). It is this rare mental
attitude that distinguishes entrepreneurs as leaders who are willing to establish new
paths.
While scholars like Cantillon (1755) and Marshall (1930) emphasised the risk that
entrepreneurial activity involves, Knight (1885-1972) draws a distinction between risk
and uncertainty, and states that only a subset of individuals in any society (i.e., the
entrepreneurs) exercises judgement effectively whenever uncertainty is involved, and
takes responsibility for the decisions made. As a reward for undertaking tasks bearing
uncertainty, the entrepreneur gains residual payment, prestige, and satisfaction (Knight
1921, 1971). However, uncertainty includes a type of probability which cannot be
classified on any valid basis because it concerns the outcome of a unique event (van
Praag 1999).
Therefore, the ability of an entrepreneur to make a judgement of the amount of
uncertainty involved, and to make an estimate of its value, differentiates him / her from
the rest of society (van Praag 1999).
Kirzner, in his earlier work in 1973, described entrepreneurs as people who display an
alertness to identify and exploit profit opportunities and who require a special type of
knowledge which is “knowing where to look for knowledge” (p.68), although he did not
explicitly mention risk and uncertainty. Hebert and Link (1989) were concerned that
such a view “downplays the importance of uncertainty in human decision making”
(p.47). In a later work, Kirzner (1999) clarifies his view of the entrepreneur as being
alert to opportunities, which requires a willingness to shoulder risks, and states that
uncertainty is endemic in the entrepreneurial firm life-cycle: if entrepreneurs are alert,
they will identify ‘marginal products at multi-period instances over time’. Such
behaviour will depend upon the entrepreneur’s ability to deal with uncertainty and the
degree of risk that is involved.
15
Even according to Schultz (1980), entrepreneurs are those who respond to opportunities
arising from disequilibria rather than having an ability to deal with uncertainty and risk.
Schultz maintains that risk and uncertainty are ever present in the economy and that “the
bearing of risk is not a unique attribute of entrepreneurs . . . [even as] entrepreneurs
assume risk, there also are people who are not entrepreneurs who assume risk” (1980,
p.441). Schultz gives an example of farmers who certainly bear risks. However, they do
the same activities as their ancestors did. Their work is repetitive and very mundane. It
does not require searching for new information, but simply using past experience in
dealing with the allocation of resources. In this example, Schultz highlights that the
bearing of risk alone is not necessarily an attribute unique to entrepreneurship.
After examining the contribution of these various economists (e.g. Cantillon, Kirzner,
Knight, Schultz & Schumpeter), Hebert and Link (1989) proposed a definition of
entrepreneurship by focusing on the individual: “the entrepreneur is someone who
specialises in taking responsibility for and making judgemental decisions that affect the
location, form, and the use of goods, resources, or institutions” (p.47). These authors
claim that their new definition accommodates, within a market system, a range of
entrepreneurial activities such as coordination, arbitrage, ownership, speculation,
innovation and resource allocation.
While the various concepts and views about entrepreneurship discussed above have
merit, several studies (e.g. Gartner 1990; Shane & Venkataraman 2000) carried out in
the 1990s have redefined the concept by presenting frameworks that include different
dimensions covering a range of issues. Gartner (1990) has identified two major
perspectives of entrepreneurship. The first one focuses on the characteristics of
entrepreneurship which include the entrepreneur, innovation, growth, and uniqueness.
The second one focuses on the outcomes of entrepreneurship; this perspective also
regards a situation as being entrepreneurial only if it creates value or if an individual has
gained from the outcome. Shane and Venkataraman (2000), on the other hand, defined
entrepreneurship as a study of an individual’s ability to recognise opportunities, to
evaluate, and to exploit these opportunities. This broader view is more than just firm
creation in that it includes the entrepreneurs’ abilities, as well as how value is created.
16
Taking a different approach, Smilor (1997) terms entrepreneurship as a subversive
activity because “it upsets the status quo, disrupts accepted ways of doing things, and
alters traditional patterns of behaviour” (p.341). This is in line with the seminal works
of Schumpeter (1936, 1942) where he argues that entrepreneurs carry out new
combinations and revolutionise the patterns of production. This characteristic of
revolutionising happens when entrepreneurs start a new venture (Bygrave 1989; Gartner
1990; Low & Macmillan 1988). The concept of entrepreneurship has taken many
forms. We also see that entrepreneurs are involved in franchising (Kaufmann & Dant
1998); they are not only involved in establishing new firms, but also in existing firms
when they undertake corporate entrepreneurship (Covin & Slevin 1991; Wortman
1987). They are involved in formal and informal economies (La Porta & Shleifer 2008).
Entrepreneurs are also involved in social entrepreneurship, which is entrepreneurial
ventures that aim to resolve social problems and improve society in general (Parkinson
& Howorth 2008). Since entrepreneurship takes so many different forms, it is necessary
to examine some definitional issues of entrepreneurship.
2.1.1 Plurality of definitions
The study of entrepreneurship has received attention from scholars in a variety of
disciplines such as economics, management, finance, psychology, anthropology and
sociology (Hebert & Link 1989; Ireland & Webb 2007). This multi-disciplinary interest
in entrepreneurship has given rise to a variety of theories and definitions. Several
studies have attempted to define the term entrepreneurship focusing on different aspects
(e.g. Bygrave & Hofer 1991; Kets de Vries 1996; Low & MacMillan1988). For
example, Schumpeter (1934) and Drucker (1985) focused on innovation or the creation
of new processes, methods, and new products, whereas Low and MacMillan (1988) and
Bygrave and Hofer (1991) defined entrepreneurship as creating a new organisation.
Others such as Aldrich and Zimmer (1986) and Shapero (1977) focus on the
behavioural aspects of entrepreneurship. This means that there is no single definition
that is sufficiently comprehensive to encompass all the factors of entrepreneurship. A
huge variety of definitions are seen in the literature, and the most commonly cited
definitions are identified and tabulated in Table 2.1.
17
Table 2.1: Sample of Definitions of Entrepreneurship/Entrepreneur Author/Source Definition
Schumpeter (1936, p.78) Schumpeter (1942, p.132)
“Everyone is an entrepreneur when he actually ‘carries out new combinations,’ and loses that character as soon as he has built up his business, when he settles down to running it as other people run their businesses.” “The function of entrepreneurs is to reform or revolutionize the pattern of production by exploiting an invention or, more generally, an untried technological possibility for producing a new commodity or producing an old one in a new way, by opening a new source of supply of materials or a new outlet for products, by reorganizing an industry and so on.”
Carland et al. (1984, p.358)
“An entrepreneur is an individual who establishes and manages a business for the principal purpose of profit and growth. The entrepreneur is characterized principally by innovative behaviour and will employ strategic management practices in the business.”
Drucker (1985) Drucker (1995, p.28)
Defines the entrepreneur as an “innovator”. A business person who builds an enterprise without innovating is not, in his view, an entrepreneur at all. “the entrepreneur always searches for change, responds to it, and exploits it as an opportunity”
Low and MacMillan (1988, p.141)
Entrepreneurship is defined as the “creation of new enterprise”.
Bygrave and Hofer (1991, p.14)
“The entrepreneurial process involves all the functions, activities, and actions associated with the perceiving of opportunities and the creation of organizations to pursue them”. “An entrepreneurial event involves the creation of a new organisation to pursue an opportunity.” “An entrepreneur is someone who perceives an opportunity and creates an organization to pursue it.”
Kets de Vries (1996, p.865)
“An entrepreneur is an individual who is instrumental to the conception of the idea of an enterprise and its implementation”
Sharma and Chrisman (1999, p.17)
They define entrepreneurship as “acts of organizational creation, renewal, or innovation that occur within or outside an existing organisation”
Shane and Venkataraman (2000, p.218)
They define entrepreneurship as being when “opportunities to create future goods and services are discovered, evaluated, and exploited”
Hisrich, Peters, & Shepherd (2005, p.8)
“Entrepreneurship is the process of creating something new with value by devoting the necessary time and effort, assuming the accompanying financial, psychic, and social risks, and receiving the resulting rewards”
“Entrepreneurs are individuals who recognize opportunities where others see chaos or confusion.” “Entrepreneurship is a process of innovation and new-venture creation through four major dimensions – individual, organizational, environmental, process – that is aided by collaborative networks in government, education, and institutions.”
18
As can be seen from the table above, identifying a comprehensive definition of
entrepreneur or entrepreneurship is a challenging task, since there is enormous variety
in definitions, some of which do not overlap, each focusing on certain aspects with
regard to what constitutes an entrepreneur or entrepreneurship. Considering the vast
array of divergent views, Bygrave and Hofer (1991) observe that “entrepreneurship
scholars have been embroiled in a never-ending debate over the definition of an
entrepreneur” (p. 13). However, Baumol (1993) considers that definitions are
“complementary rather than competitive, each seeking to focus attention on some
different feature of the same phenomenon” (p.198). It is evident from the review of the
literature that entrepreneurship has evolved from the mere use of resources in order to
survive, to the creative use of resources in order to stimulate wealth (Murphy, Liao &
Welsh 2006). To create wealth, the entrepreneur has to identify opportunities, deal with
uncertainty and be exposed to risk.
As seen in the above discussion, it could be surmised that definitions of
entrepreneurship draw from multiple theoretical perspectives. As Murphy, Liao and
Welsch (2006, p.13) put it, “the body of entrepreneurship research is stratified, eclectic,
and divergent”, generating “many theories and frameworks”. However, a closer scrutiny
of the definitions listed above indicated four aspects that are common to
entrepreneurship: opportunity recognition, risk taking, business creation, and business
growth. The next section examines the role of the individual in the process of
entrepreneurship.
2.2 Entrepreneur’s background
A review of the definitions of entrepreneurship would clearly point out that an
entrepreneur is a central entity to a firm (e.g. Fastré & Van Gils 2007; Kuratko &
Hodgetts 2001; van Praag 2005). As an individual, an entrepreneur is the source of
action that takes place in a firm. Therefore, it is crucial to understand the role of the
entrepreneur in successfully establishing and managing the growth of a firm. In a
business context, establishing a successful firm requires an entrepreneur to deal with
complex scenarios and situations. Not all individuals take up entrepreneurship as their
career option, and not all those who become entrepreneurs are successful. Obviously,
19
the greatest determinant of business success is the entrepreneur himself or herself
(Sahin, Nijkamp & Rietdijik 2009). By behaving entrepreneurially, the individual
engages in a process that creates value for the firm by recognising and exploiting
opportunities.
Within a particular context, the effectiveness of entrepreneurs is influenced by both
demographic and personality characteristics (Sahin, Nijkamp & Rietdijik 2009).
Demographic characteristics have been examined by a number of studies covering
various aspects such as age, gender, and educational backgrounds, characteristics which
have been examined in previous studies (e.g. Kim, Aldrich & Keister 2006; Kourilsky
& Walsad 1998). Personality-related aspects studied include personality traits (Collins,
The table above shows a list of 19 popular personality characteristics found in the
literature. I have already discussed some of these personal characteristics that
distinguish entrepreneurs. Further, Rauch and Frese (2007a) have conducted a meta-
analysis of personality characteristics in entrepreneurship recently and identified a list
of 51 personality characteristics that formed part of the studies included in their
analysis. The detailed results of this study will be discussed later in this chapter, but it is
important to point out that this study found evidence to positively link entrepreneurs’
25
personality characteristics with business creation, and that certain personality traits had
higher correlations as they matched with the entrepreneurial tasks.
In contrast to the above studies, researchers such as Aldrich (1999), Blanchflower and
Oswald (1998), who tried to explain entrepreneurship using personality traits, could not
derive any significant findings. Likewise, Brockhaus and Horwitz (1986) also examined
the relationship between the personality traits of entrepreneurs and business creation,
but could not find any supporting evidence. It is not surprising, then, when Gartner
(1985) argues that using a person-centric approach to document a typical entrepreneur
may not be useful, since there is a significant amount of diversity amongst the types of
entrepreneurs, and the variation among them is even larger than the difference between
an entrepreneur and a non-entrepreneur. Due to this heterogeneity among entrepreneurs,
an ‘average entrepreneur’ does not exist, and an average personality profile of
entrepreneurs cannot be arrived at.
In a context of scepticism over whether personality characteristics impact on
entrepreneurship, Low and MacMillan (1988) question the very purpose of personality-
based research, since most of the studies were “confined largely to documenting and
reporting the [entrepreneurs’] personality characteristics, with little attempt to uncover
causal relationships or to explore implications for practice” (p.141), and they argue that
such personality-based descriptive studies do not help in theory development. Even a
couple of decades later, the lack of an appropriate research approach was observed by
Rauch and Frese (2007a), who point out that many studies in this area “were not
theoretically driven but were descriptive in nature” (p. 358). Not surprisingly, some
authors (Aldrich 1999; Chell 1985; Gartner 1985) have already advocated that it was no
longer useful to study personal characteristics of entrepreneurs as such. Probing this
issue further, Delmar (2000) argues that the study of personality traits in
entrepreneurship is obsolete. Some of the reasons for his belief lie in the limitations of
using personality traits to profile entrepreneurs. For instance, the traits identified consist
of a large list and there is not much of a consistency in the traits identified and linked to
entrepreneurship. Further, these traits are not static, change over a period of time, and
may also be culture-dependent, as most of these studies are US-based. Delmar (2000)
also argues that instead of using multi-dimensional constructs, personality studies are
26
using one-dimensional constructs which are obsolete in relation to modern
psychological research.
As seen in the above discussion, several personality traits/characteristics were used to
profile entrepreneurs. But a more important issue is to examine how these traits impact
on entrepreneurs when they engage in entrepreneurial initiatives. It is important to
recognise that scholars have differentiated between broad and specific personality traits.
The following discussion, therefore, highlights the role of personality characteristics,
both broad and specific types, in influencing entrepreneurial initiatives.
2.2.2.1 Broad personality traits
This stream of research on personality traits has identified several traits, resulting in a
large and diverse list of personality characteristics, for example as seen in Table 2.2.
However, evidence suggests that all the personality traits can be reduced to, or
categorised into, five broad personality categories of traits or characteristics, and
popularly known as the Big Five (Costa & McCrae 1992; Digman 1990). It is suggested
that all the individual personality traits can be viewed as being part of, or embedded in,
one of the Big Five constructs: emotional stability, extraversion, openness to
experience, agreeableness and conscientiousness. The Big Five model has been used by
several researchers to identify and examine the relationships between personality traits
and entrepreneurial aspects such as status and intention.
Previously, the Big Five constructs were examined by several scholars in organisational
and leadership studies (Alessandri & Vecchione 2012; Barrick, Mount & Judge 2001).
For example, in the last two decades, the Big Five model was used to understand
individual differences (Goldberg 1993), predict academic performance of students,
academic motivation (Komarraju, Karau & Schmeck 2009), or understand job
preferences, career successes and job performances (Barrick & Mount 1991; Mount et
al. 2005).
In the entrepreneurship research, studies were undertaken in the Big Five model by
various scholars over the years (Norman 1963; Borgatta 1964; Digman 1990; Costa &
McCrae 1992; Ciavarell et al. 2004; Zhao & Seibert 2006). In the process of
27
development, scholars have identified their own big five constructs (e.g. Norman 1963,
Borgatta 1964). While the list of the Big Five has undergone some changes over the
period, recent studies have finally coalesced around the five constructs, based on the
taxonomy developed by Costa and McCrae (1992). The constructs of the Big Five
model and their corresponding traits are presented in Table 2.3.
Table 2.3 Summary of the Big Five characteristics and their corresponding traits Big Five characteristics Traits Extraversion Assertive, dominant, energetic, active, talkative,
and enthusiastic Emotional stability Positive: calm, even-tempered, self-satisfied,
comfortable, unemotional, hardy, stable, confident, and effective Negative: Anxiety, hostility, depression, self-consciousness, impulsiveness, and vulnerability
Agreeableness
Trusting, forgiving, caring, altruistic, gullible, being courteous, flexible, good-natured, cooperative, soft-hearted and tolerant
Conscientiousness Responsible, well-organised, planful, hardworking, achievement-oriented, motivated, and perseverance
Openness to experience Being imaginative, creative, cultured, curious, original, broadminded, intelligent, artistically sensitive, innovative
Source: Costa and McCrae 1992; Caliendo, Fossen & Kritikos 2014; Ciavarella et al. 2004; Judge et al. 1999; Zhao & Seibert 2006
Each of the Big Five constructs is briefly discussed below. The first construct is
extraversion and relates to the individual being assertive, ambitious, socially oriented,
and seeking leadership roles (Judge et al. 1999). Research findings indicate extraversion
is a clear predicator of performance for managers and salespeople (Barrick & Mount
1991). Being extraverted makes individuals sociable and helps in the development of
social networks (Casciaro 1998). Extraversion is therefore seen to have a positive
impact on networking activities (Zhao & Seibert 2006). This ability to establish
networks with suppliers and customers is likely to increase the chances of venture
success (Baron & Markman 2000).
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The second construct is emotional stability (which is similar to neuroticism in its
negative specification). Individuals with high emotional stability will be even-tempered
and have the ability to maintain relationships (Ciavarella et al. 2004). Emotionally
stable individuals will be more self-confident, stay relaxed in times of pressure and will
be more able to tolerate stress situations (Caliendo, Fossen & Kritikos 2014, Judge et al.
1999). Scoring low on this factor would mean that individuals would be more likely to
experience a multitude of problems such as anxiety, fear, depression and irritability
(Judge et al. 1999). Therefore, individuals with high emotional stability are expected to
become entrepreneurs (Caliendo, Fossen & Kritikos 2014). Entrepreneurs who have
high emotional stability will be able to manage anxiety, address their well-being and,
thereby, manage performance pressures and expectations. Ciavarella et al. (2004) did
not, however, find any relationship between the entrepreneur’s emotional stability and
the survival of the business venture. On the other hand, Zhao, Seibert and Lumpkin
(2010) did find that high emotional stability was positively related to entrepreneurial
intentions as well as performance. The ability to stay calm and even-tempered increases
the likelihood of the entrepreneur being able to perform better.
The third factor is agreeableness, which is related to individuals being co-operative as
well as likeable. A high score on agreeableness means that individuals are co-operative,
courteous and flexible in dealing with others. This may be particularly important where
teamwork and customer service is important. On the other hand, a low score on
agreeableness implies that such individuals are self-centred, inflexible and bargain hard.
In the area of entrepreneurship, researchers (Ciavarella et al. 2004; Baron & Markman
2000) posit that this type of trust and cooperation in the business relationships result in
entrepreneurs’ ability to enter new businesses, achieve new product development,
increase shareholder wealth, and in the likelihood of long-term venture survival.
Risk-taking propensity Ability to handle risk, ability to evaluate risk, copes well with uncertainty, enjoys taking risks, willingness to take chances
Brockhaus (1980b); Buttner & Rosen, (1988); Hartog, Ferrer-i-Carbonell & Jonker (2002); Stewart and Roth (2001)
Proactivity Propensity to act Tendency towards action Initiative Perseverance
Baum, Locke & Smith (2001); Bird (1989); Crant (1996)
Passion Emotional energy Devotion Enthusiasm
Baum, Locke and Smith (2001); Bird (1989); Chen, Yao, & Kotha (2009); Smilor (1997)
Energy level Overall level of functioning in carrying out day-to-day activities i.e. enthusiasm and endurance
Thomas and Mueller (2000)
Innovativeness and creativity
Introduction of new goods Introduction of new methods of production Opening of new markets Industrial reorganisation
Carland et al. (1984); Harris, Gibson & Mick (2009)
Many studies have identified and examined the impact of a single trait. For instance,
locus of control and firm performance ( Boone, Brabander & Witteloostuijn 1996), risk-
taking propensity and entrepreneurship (Brockhaus 1980) or need for achievement and
entrepreneurial behaviour (Collins, Hanges & Locke 2004). While there are many traits
identified as being important for entrepreneurs, three traits have been given much
attention and have been commonly applied in research in entrepreneurship (see Sahin,
Nijkamp & Rietdijk 2009; Tang & Tang 2007). These are: need for achievement,
internal locus of control and risk-taking propensity. Further, in an exhaustive study on
entrepreneurial personality, Chell (2008) refers to these very three specific
characteristics as ‘The Big Three’. For these reasons, I have also chosen these three
personality characteristic in my study. Each of them is discussed below:
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2.2.2.2.1 Need for achievement
One of the most widely discussed psychological measures in entrepreneurship literature
is the personal characteristic of the need for achievement (Collins, Hanges & Locke
2004; Hornaday & Aboud 1971; McClelland 1961). The term is used to describe a
person’s desire for excellence (Cassidy & Lynn 1989). Initially, this concept was
proposed by Murray (1938, cited in Shaver and Scott 1991). According to Murray, the
need for achievement means:
“To accomplish something difficult. To master, manipulate, or organize physical objects, human beings, or ideas. To do this as rapidly, and as independently as possible. To overcome obstacles and attain a high standard. To excel one’s self. To rival and surpass others. To increase self-regard by the successful exercise of talent” (Murray, 1938, p.164, cited in Shaver & Scott, 1991, p.31).
Later on, this concept was examined in depth by McClelland (1961) as referring to a
drive to excel or to achieve a goal. This characteristic is very important as it influences
an individual’s work behaviour to a great extent (Lumpkin & Erdogan 2000). The need
to achieve gives rise to an individual’s expectation of doing something better or faster
than others or even their own personal accomplishments (Hansemark 2003). Such
individuals are high achievers and like situations where they take personal responsibility
and also find solutions to challenges and problems. Achieving targets results in feelings
of accomplishment and satisfaction for them.
In a business context, entrepreneurial occupations provide the opportunities for
individuals who have a high need for achievement (Collins, Hanges & Locke 2004).
According to Littunen (2000), McClelland’s theory suggests that individuals with a high
need for achievement will not only become entrepreneurs but also succeed better than
others in their careers as entrepreneurs. Several studies examined the role of need for
achievement in the entrepreneurship field. In one of the early studies (McClelland
1965), students with a higher need for achievement were found to gravitate towards
business occupations of an entrepreneurial nature. Johnson (1990) reviewed previous
studies on achievement motivation and found a positive relationship between
achievement motivation and entrepreneurship in 20 out of 23 studies. Other studies that
differentiated entrepreneurs from non-entrepreneurs found that entrepreneurs generally
35
have a higher need to achieve than non-entrepreneurs (e.g. McClelland 1965; Langan-
Fox and Roth 1995; Stewart & Roth 2007). A study of female entrepreneurs revealed
the existence of this personality characteristic among them. Langan-Fox and Roth
(1995) developed a typology of female entrepreneurs, namely the need achiever, the
pragmatic and the managerial entrepreneur. Of these, the need achievers scored very
highly on the need achievement, and the managerial entrepreneurs scored highly on
power and influence, with the pragmatics scoring moderately on both motivations of
achievement and power. It can be seen, then, that the need for achievement has an
impact on both male and female entrepreneurs. Bridge, O’Neill and Cromie (2003),
suggest that enterprising people have a need for achievement. It is this need for
achievement that stimulates the individuals to take action (behavioural activities). These
authors also suggest that the high achiever will regard money as a measure of
achievement and in this case, money is not an end in itself, but rather something that
provides an entrepreneur with feedback on their achievement.
Studies were also undertaken to examine the impact of the need for achievement on
behaviour gives an insight into the creation of new ventures and their success (Gartner
1989; Bird, Schjoedt & Baum 2012).
Therefore the question arises as to what entrepreneurs actually do to create and grow
new ventures. The existing literature on entrepreneurial behaviour is limited,
fragmented and ad hoc (Bird & Schjoedt 2009; Luthans, Envick & Anderson 1995;
Mueller, Volery & Von Siemens 2012). In a more recent study, Bird, Schjoedt and
Baum (2012) reviewed management and entrepreneurship journals during the period
2004 to 2010 and found only 91 articles related to the area of entrepreneur behaviour.
Their examination of these studies reveals a paucity of research and also methodological
concerns regarding operationalisation of entrepreneurs’ behaviour. Therefore, Bird et
al. (2012, p.903) observe, “behaviour in entrepreneurship research remains a surprising
63
void …” and suggest more research in this area. Accordingly, I have reviewed the
existing literature to examine first the concept of entrepreneurial behaviour, and second
various ways in which the construct of enterpeneurial behaviour was used in previous
studies.
2.4.1 Concept of entrepreneurial behaviour
According to Bird (1989), entrepreneurial behaviour can be defined as an
“opportunistic, value-driven, value-adding risk-accepting, creative activity where ideas
take the form of organizational birth, growth or transformation” (p.5). A similar
definition is provided by Bird and Schjoedt (2009), who suggest that entrepreneurial
behaviour is the concrete enactment of individual or team tasks or activities required to
start and grow a new organisation. It is about the behaviour of the individual(s) as
entrepreneurs and not the firm’s behaviour. The behaviour needs to be discrete units of
action that can be observed by others in a meaningful way. Therefore, the behaviour of
entrepreneurs that results in starting and growing a new organisation draws upon the
personal attributes of entrepreneurs such as experience, knowledge, skills, abilities,
cognitions, intelligence, intentions and motivation. However, having these personal
attributes (e.g., right knowledge, skills, abilities, motivation and intention) is not
sufficient to create economic value. Instead, the presence of these personal attributes
would allow or enable entrepreneurs to consciously choose entrepreneurial activities
with the intention of finding and exploiting an opportunity and forming an organisation
[or a firm]. Therefore, entrepreneurial behaviour consists of the observable actions
(activities) of an individual and the responses that are evoked by those activities (Bird,
Schjoedt & Baum 2012).
2.4.2 Research on entrepreneurial behaviour
To find specific aspects of entrepreneurial behaviour, some scholars have examined the
literature in the area of management, and organisational and psychological studies to
identify ‘behavioural concepts’ that can be applied to entrepreneurship (e.g., Bird 1989;
Gartner, Bird & Starr 1992; Baron 2002). It was not a straightforward identification of
behavioural activities, but was part of other related aspects. For example, Bird’s (1989)
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study gathered a number of person-centred variables (such as experience, education,
motivation and values), the social context of entrepreneurial behaviour, leadership,
competencies and learning. Likewise, Gartner, Bird and Starr (1992) attempted to apply
organisational behaviour theory to ‘emerging’ organisations, but found them to be
limited at that time. Therefore, they suggested ‘richer description’ of entrepreneurial
behaviour. Baron (2002) used an organisational behaviour (OB) model of individual,
interpersonal and organisational spheres to three phases of the entrepreneurship process,
i.e., pre-launch, launch and operations. This research focused on the individual’s
cognition and decision-making issues. He also linked OB concepts to person-specific,
person-centred outcomes such as learning from a mentor, social and emotional
competence, situational leadership, influence processes, and group dynamics of teams.
Similarly, Shook, Priem and McGee (2003) used behavioural research in
entrepreneurship by highlighting judgement or cognition and how it was critical for
individuals engaged in opportunity exploitation activities. They observe, ‘we know very
little about the role of the individual in acquiring resources and organising the company’
(p. 390). On the other hand, other authors tried to identify specific and observable
entrepreneurial behavioural activities, moving away from personality-related constructs.
Shepherd, Douglas and Shanley (2000) argue that venture survival depends on
organising activities such as specifying tasks, allocating people to tasks, defining
authority structures, and building communication channels.
In the last decade, some empirical research in entrepreneurship behaviour was also
conducted. Bird and Schjoedt (2009) placed these studies on entrepreneurial behaviour
under three groups, based on whether it is used as a criterion for sampling, as an
independent variable, or as a dependent variable. Finally, they also describe the
entrepreneur’s behaviour based on social theories. In the first group, behavioural
activities served as a criterion for the selection of entrepreneurs. The most prominent of
these efforts is the Panel Study of Entrepreneurial Dynamics (PSED) conducted
between 1998 and 2000. This was followed by a similar survey on a global scale in the
form of the Global Entrepreneurship Monitor (GEM) project (see Reynolds et al. 2000;
Gartner et al. 2004; Langowitz & Minniti 2007). These surveys, together with
telephone interview and mail questionnaires, cover a broad range of topics that include
activities relating to success in organising entrepreneurial business. Embedded in these
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surveys were two questions that were designed to identify nascent entrepreneurs: (i) Are
you, alone or with others, now trying to start a business? and (ii) Are you, alone or with
others, now starting a new business or new venture for your employer? This survey
provided data that are largely contemporaneous with the new venture creation process.
Researchers were able to use these data to develop a behavioural criterion for
individuals based on whether they have engaged in entrepreneurial activities such as
‘developed a product/service, established credit with suppliers, filed a tax return for a
new business, invested own money (Gartner et al. 2004). The PSED study was
designed to examine the earliest stage of the organisational life-cycle so as to get an
understanding of the new business creation of nascent US entrepreneurs. For example,
Edelman, Manolova and Brush (2008) used these start-up behaviours to compare the
practices of nascent entrepreneurs and the practices that textbooks recommended that
entrepreneurs’ undertake. The authors found that the entrepreneurship textbooks did not
present all the activities involved in the starting up of a new venture, either by
underemphasising some activities or not adequately discussing them.
The second group of studies use entrepreneurial behaviour as an independent variable.
Here, Bird and Schjoedt (2009) refer to specific behaviour such as locating the business
in a specific area, writing a business plan, or seeking outside advice. For instance, Haber
and Reichel (2007) examined the impact of entrepreneurial activities such as writing a
business plan and planning the physical design of the venture, as well as applying for
external support like financial and advisory assistance on the venture performance,
which incidentally was only marginal. In a longitudinal study, Lichtenstein, Dooley and
Lumpkin (2006) examine the start-up activities during the venture creation process,
along with their frequency and pacing. The nine start-up behavioural activities used in
this study are those identified in the PSED study: investing own money, defining the
opportunity, organising a founding team, developing a prototype, forming a legal entity,
installing a business phone, purchasing major equipment, opening a business bank
account and asking for funding. Tornikoski and Newbert (2007) identify certain
behavioural activities of nascent entrepreneurs; these include the demonstration of
improvising behaviours (e.g, preparing a business plan, starting marketing efforts,
applying for patents, opening bank accounts, listing in the phone book and Dunn and
Bradstreet), gathering resources (e.g., purchasing raw materials and equipment), and
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displaying networking behaviour (e.g., asking for funds, and receiving outside
assistance). These authors explain the impact of the entrepreneur’s behaviours/activities
on the nascent organisation’s ability to interact with the external environment
successfully. They found that improvising and resource gathering behaviour were
effective, but not the networking behaviour. Other behaviours were less specific and
cognitive in nature rather than observable behaviour such as self-reports relating to
planning or identifying sources of finance (Alsos, Isaken & Ljunggren 2006). In another
study (Rauch, Frese & Utsch 2005), it is the employees, as stakeholders, who report the
entrepreneurs’ behaviours such as ‘support for personal initiative’ and ‘communicating
business goals’.
The third group of studies view behavioural activities as a dependent variable (Bird &
Schjoedt 2009). These studies, for example, use demographic variables such as age,
gender and human capital (DeTienne & Chandler 2007) and homemaker status (Singh
& Lucas 2005) to predict self-reported entrepreneurial behaviours. In their study of
homemaker entrepreneurs, Singh and Lucas (2005) found that both non-homemaker and
homemaker nascent entrepreneurs undertook activities such as preparing a business
plan. DeTienne and Chandler (2007) used the gender and human capital of the CEO of
young firms as predictors of a sequence of activities relating to start-up opportunity.
Research on family firms reveals that entrepreneurial behaviour is significantly
influenced by the characteristics of the family members, the CEO and the overall family
involvement in the firm (Kellermans et al. 2008). In other cases, belief cognitions and
intentions and individual differences were used as predictors of nascent behaviours
found in PSED or GEM projects (Langowitz & Minniti 2007). In this context, it is
useful to recall the popular theory of planned behaviour (TPB) postulated by Ajzen
(1991), which argues that behavioural intention is the best predictor of behaviour
because intention is “a person’s readiness to perform a given behaviour” (Ajzen 2011,
p.1122). A recent longitudinal study provides strong empirical evidence of how
intentions are linked to entrepreneurial behaviour when engaging in the entrepreneurial
process (Kautonen, van Gelderen & Tornikoksi 2013). Similarly, the study by Kautonen
and his colleagues (2013) on the impact of intention and predictive behaviour control on
business start-up behaviour also showed a positive causal relationship.
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Under the fourth grouping, Bird and Schjoedt (2009) discuss studies that explain
behaviour in the social theory context (Forbes et al. 2006; Lichtenstein, Dooley &
Lumpkin 2006). For example, Forbes and his colleagues (2006) use the theories of
attraction and resource dependence approach to explain the entrepreneurs’ behaviour of
hiring new team members. The authors suggest that the entrepreneurs would engage in
the activity of hiring a new team member if that member had close ties to the venture
capital community or shared a similar culture or values to the entrepreneur. Similarly,
Lichtenstein, Dooley and Lumpkin (2006) examined the activities of an entrepreneur
engaged in the organisation of a new firm. They observe three modes of organising:
organising the vision (expressing a strong vision and vocabulary about the venture
opportunity), strategic organisation (tangible events like formatting a book, deciding to
publish a book or through a web-page, committing personal funds, and coping with non-
venture responsibilities), and tactical organising (developing a product / service,
establishing credit with suppliers, filing tax returns, hiring employees, or investing own
money). As can be seen, many of these activities are behaviourally anchored.
While Bird and Schjoedt (2009) found that entrepreneurial behaviour has been
empirically studied as an independent, dependent and control variable, there are still
gaps in the body of knowledge. Poor measurement, self-reporting, studying students
rather than entrepreneurs, and not including time taken to complete the activity (i.e.
begin time, finish time, new behaviour start time) are some of the limitations. Scholars
have also found that many of these studies focus on vague behavioural constructs which
are difficult for objective observation and also lend themselves to varied interpretation
(Mueller, Volery & Siemens, 2012). There is a consensus among researchers that the
research in this area does not sufficiently address the nature of entrepreneurs’
behaviour, and more empirical data is required that focuses on what entrepreneurs
actually do (Bird & Schjoedt 2009; Bird, Schjoedt & Baum 2012; Gartner, Carter &
Reynolds 2010; Mueller, Volery & Von Siemens 2012).
There were also other studies in the 1990s relating to the observation of entrepreneurial
behaviour which were not covered in Bird and Schjoedt’s (2009) review. For example,
Luthans, Envick and Anderson (1995) examined the methods of research in
entrepreneurship and found that most studies were group-centred and the focus was on
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the measurement of data collected indirectly through surveys. However, entrepreneurs
are more individualistic than group-centered, and therefore need to be studied in their
naturalistic (organisational) settings. The authors suggest the use of an idiographic
approach to identify entrepreneurial behaviour from an insider’s perspective. The
idiographic method uses a direct behavioural observation of the events unfolding in the
given setting and interaction with the internal and external environments. For this
purpose, the authors have undertaken a four-stage process consisting of: (i) an
unstructured direct observation of entrepreneurs’ behaviour, (ii) post-log interviews to
ensure that behaviour was accurately observed, (iii) the use of Delphi technique for the
categorisation of the behaviours, and finally, (iv) the use of structured observation to
measure the frequency of identified behaviour. Accordingly, this method was used to
examine the behaviours of entrepreneurs (Envick & Luthans 1996), and gender
differences in the behaviour of entrepreneurs (Envick & Langford 1998). In Envick and
Luthans’s (1996) study, eight entrepreneurial behavioural categories were identified: i)
planning, ii) controlling, iii) internal communication, iv) human resources management,
v) work-related tasks, vi) customer service, vii) networking and viii) on-the job personal
time. Using the behavioural activities of entrepreneurs found by Envick and Luthans
(1996), Envick and Langford (1998) investigated gender differences in these
entrepreneurial activities. While entrepreneurs of both genders were engaged in the
eight behavioural activities, some significant differences were also found. Female
entrepreneurs engaged in controlling, communication, human resource management and
work-related tasks significantly more often than their male counterparts. On the other
hand, male entrepreneurs engaged in on-the-job personal time significantly more often
than females. There were also other differences, but they were not significant.
As seen above, the literature reveals that the construct of entrepreneurial behaviour has
originated from disciplines such as organisation and psychology. Attempts have been
made to identify entrepreneurs’ behaviours by various scholars (e.g., Brown & Hanlon
2004; Envick & Langford, 1998; Luthans & Ibrayeva 2006). A recent review by Bird,
Schjoedt and Baum (2012) found that studies so far have not addressed the nature of
entrepreneurs’ behaviour adequately, and therefore called for more empirical data to
understand what entrepreneurs actually do. This view is consistent with other
69
researchers such as Mueller, Volery and Von Siemens (2012). The details of some of
these studies are discussed in the section below.
2.4.3 Identifying entrepreneurial behaviours
Brown and Hanlon’s (2004) study attempted to develop entrepreneurial behavioural
scales that can help in identifying training, coaching and developing of entrepreneurs.
The authors surveyed 34 entrepreneurs by conducting a critical incident job analysis.
Each entrepreneur was asked to report up to three examples of effective and ineffective
behaviours that they had observed other entrepreneurs perform. Using this procedure,
the authors were able to identify nine dimensions: relevant background, opportunity
identification, dedication to business, mobilising support and resources from others,
strategic business development and growth, financial management skills, employee
management, marketing/customer relations management and negotiation and risk-
taking.
In 2006, Luthans and Ibrayeva examined the role of self-efficacy among entrepreneurs
in transition economies in two parts / phases. In the first part, the authors found that
entrepreneurs’ self-efficacy had a direct and mediating effect on performance outcomes.
However, the authors believed that self-efficacy could be developed only if they knew
the specific behaviours of entrepreneurs i.e., what they actually did. To seek answers to
this question, the authors undertook a second study, with a sample of 239 from two
transition economies from Central Asia, to examine: (i) what entrepreneurs do in their
day-to-day work schedule and (ii) how frequently they do these activities. They
followed an idiographic approach (suggested by Luthans, Envick & Anderson 1995)
that consisted of different phases of data collection: an unstructured observation, a post-
log survey, Delphi analysis and a final structured observation. For this purpose, they
used a multi-behaviour (more than one behaviour observed) and multi-rater (with more
than one rater) method to focus on directly observable behaviours of entrepreneurs. The
results from this study identified nine categories of entrepreneurial behavioural
activities: planning, controlling, internal communication, human resources management,
work-related tasks, customer service, socialising, politicking, and on-the-job personal
time.
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In the immediate past, Mueller, Volery and Von Siemens (2012) used the sociological
method of structured observation to capture the behaviour of entrepreneurs, six of them
from the start-up stage and six of them in the growth phase. Instead of using the
traditional self-reporting method of data collection, Mueller and his colleagues observed
entrepreneurs in real-time and recorded them to understand the actions of the
entrepreneurs. The findings show that the actions of entrepreneurs in both start-up and
growth phases were characterised by brevity and fragmentation; they engaged in ‘short,
sporadic actions that change in an abrupt, sometimes unpredictable manner (p. 1004).
Both groups spent a considerable amount of time on communication with others. All the
growth phase entrepreneurs and a majority of the start-up entrepreneurs were heavily
involved in performing exploitation activities rather than exploration activities in order
to increase efficiency. They were equally involved in three main functions: (i) human
resources and employee relations, (ii) marketing, sales and public relations and (iii)
administration. Both the groups were also involved in the exchange of information and
opinions, and working analytically and conceptually; however, the two groups differed
significantly on the time spent in both these areas: the start-up entrepreneurs spent 36
per cent of their time on exchanging information and opinions and 28 per cent on
working analytically and conceptually, while the growth stage entrepreneurs spent 54
per cent of their time on exchanging information and opinions and only 12 per cent on
the analytical and conceptual work. Similarly, start-up entrepreneurs were more
involved in environmental monitoring, while growth stage entrepreneurs were more
involved in business development.
Based on their findings, Mueller, Volery and von Siemens (2012), presented a
taxonomy of entrepreneurs’ behaviour that is described by a continuum ranging from
the basic ‘atomic’ level to the superordinate ‘galactic’ level, with two other
intermediary levels: molecular and molar levels. At the ‘atomic’ level, an action
consists of discrete units of individual activities of entrepreneurs that are observed by an
audience (e.g., writing an email, visiting a client etc.). At the second ‘molecular’ level,
the activity captures what entrepreneurs are doing without the observer interpreting the
purpose of these actions (e.g., networking, exchanging information, directing and
controlling, consulting and selling etc.). At the ‘molar’ level, activities are differentiated
71
by the functions within the organisational context (e.g., product development,
marketing, controlling and finance, human resources and employee relations etc.). The
fourth level is named the ‘galactic’ where the activities are divided into two
fundamental forms of organisational behavior: exploitation (e.g., increasing productivity
and resolving problems of the existing business) and exploration (e.g., developing a new
product line or internationalising activities).
Finally, Bird, Schjoedt and Baum (2012) summarise the literature in the area of
entrepreneurial behaviour and endorse the need for further research in this area. Even
while pointing out the existence of some good studies, they observe that the current
research is ad hoc, and, in some cases, examines only one behaviour rather than a range
of behaviours that explain ‘effective entrepreneurship’. They also make
recommendations for further research on a list of critical behaviours they believe are
considered important but are under-researched. The list includes activities such as
establishing operations, hiring employees, and marketing, and selling. Interestingly,
these authors suggest the re-use of published measures from previous studies. My study
uses the behavioural activities identified by Luthans and Ibrayeva (2006) as constructs
in my conceptual model for empirical measurement. As no empirical studies were
conducted in an emerging economy context, we are able to use the entrepreneurs’
behavioural activities identified in a transition economy for our study.
2.5 Entrepreneurial information overload (EIO)
Entrepreneurs face many challenges in their attempts to discover opportunity, create a
venture, and ultimately sustain it. While configuring and gathering resources is
necessary for the success of entrepreneurs’ efforts, a vital ingredient of this process is
information. Possessing or having access to the right amount of information and the
ability to use it optimally helps in effective decision-making relating to new venture
creation and management. However, some scholars have pointed out that when decision
makers face the challenge of dealing with too much information compared to their
ability to deal with it, this leads to a phenomenon known as information overload. I
believe that entrepreneurs, too, as decision makers, face the problem of information
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overload. This section explores the concept of information overload and how it impacts
on entrepreneurs adversely.
2.5.1 Concept of information overload
The literature reveals that information overload has been an issue for many years, but
has come under the spotlight more recently in the context of an increasing number of
technological gadgets, globalisation and the accessibility of information. Previously,
i.e. before the advent of information and communication technologies (ICT), business
managers suffered due to a lack of adequate information necessary for effective
decision-making. But with growing information technology and the ever-changing
environment, the previous paucity of information has changed with an increasing
amount of information available from diverse sources, so much so that the problem now
is not information shortage, but information overload (Speier, Valacich & Vessey,
1999).
The concept was first recognised and examined in the field of psychology (e.g., Miller,
1956). Here, Miller (1956) argued that humans have a fairly limited cognitive ability to
process information, and also that people have different levels of information
processing capability and capacity to store information. He also found that an
individual’s information processing performance increased with increased information
inputs up to a certain threshold point, after which the processing performance decreases
sharply. Interestingly, these views were expressed prior to the advent of modern ICT
technologies. Later, Milford and Perry (1977, p. 131) define information overload as
“the condition in which the amount of input [information] into a system exceeds the
processing capacity of that system”. It implies that information overload occurs when
inputs stream rapidly and where the respondent does not have enough time to sift and
process various inputs of information.
Alluding to the challenge of dealing with information, although not defining it as
information overload, the Noble Prize Laureate, Herbert Simon (1971, p. 40), observes:
“a wealth of information creates a poverty of attention”. He suggests that the
respondent’s ability to process and use the information and make decisions may be
73
limited by his/her cognitive processing capability. In other words, when the respondents
receive much more information than they can handle, this leads to information overload.
Examining this concept, Schultze and Vandenbosch (1998) have referred to information
processing capacity as a U-shaped function, wherein too little information decreases the
cognitive ability, while too much information causes stress and thereby lowers the
processing capacity. However, Eppler and Mengis (2004) suggested that an increase in
information load can, up to a certain time, increase the processing capacity.
Various reasons have been advanced as causing information overload: the amount of
information (Farhoomand & Drury, 2002; Milford & Perry, 1977; O’Reilly, 1980), the
diversity of information (Iselin, 1988; 1993; Milford & Perry, 1977), time pressure
(Schick, Gordon & Haka, 1990) and processing factor (Baron, 1998; Farhoomand &
Drury, 2002; Van Zandt, 2004). Evaristo, Adams and Curley (1995) provided further
insights by explaining how the information characteristics (volume, uncertainty,
complexity and turbulence) and the task characteristics (time pressure, formalisation,
and complexities) could result in an individual’s information load. While the effect of
the ever increasing number of cues is seen as directly contributing to information
overload, Eppler and Mengis (2004) maintain that it is the combination of five factors:
information, in terms of its volume, frequency, intensity and quality; the receiver; the
tasks that need to be accomplished; the organisational design; as well as the information
technology which contribute to information overload at organisational and interpersonal
levels. In general, all the factors above influence an individual’s information
requirements and information processing capacity leading to information overload.
Recognising information overload as a major challenge, it was examined in various
disciplines such as accounting, marketing, organisational studies, and management.
Accountants are key information disseminators within an organisation, and decision
makers rely on their information to make good decisions. But accountants also suffer
from information overload because they work under extreme time pressure (Schick,
Gordon & Haka 1990; Swain & Haka, 2000). In sales management, the salespersons’
information overload was found to negatively affect their sales performance (Hunter
2004). Investigating the information overload from the customers’ perspective, Jacoby
(1984) found that available information could also overload consumers in their purchase
decision, but they were able to deal with it by being highly selective in the quantity and
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type of information they seek. Klausegger, Sinkovics and Zou (2007) found that
approximately 60 percent of managers’ work time in organisations was spent in reading
documents and processing information; however, these managers had collected too
much information which they could not use efficiently and this impacted negatively on
their task accomplishment. Examining the impact of information overload on decision
making, Speier, Valacich and Vessey (1999) argue that when individuals are subjected
to information overload, it reduces their ability to make good decisions. The authors
found that information overload not only increases the time required to make a decision,
but also decreases the quality of decisions. Decision-makers experiencing information
overload may ignore available information and become highly selective or even lose
control over information (Bawden 2001; Edmunds & Morris 2000), which could result
in less than optimal outcomes.
Organisations, also, like individuals, can face information overload when they face a
discrepancy in their information processing capabilities with regard to the amount of
information encountered (O’Reilly 1980). It is noted that each organisation has a
different structure, which also affects the information processing capacity of the unit
(Tushman & Nadler 1978). Further, it is also observed that information overload can
cause a reduction in output capacity (Driver & Mock 1975). When individuals within an
organisation perceive individual information overload, it could result in a reduction in
the overall effectiveness of the management operations (Allen & Wilson 2003). These
negative effects of information overload highlight the importance of this construct and
the need to understand its impact on individuals and organisations. I believe that this
construct is extremely important for entrepreneurs in the current world, as they too are
inundated with information from various sources, and they would not be immune from
this phenomenon.
2.5.2 Information-seeking behaviour in entrepreneurship
Following the discussion above, it is obvious that entrepreneurs, too, like managers,
would suffer from too much information, and therefore the concept of information
overload can be extended to the discipline of entrepreneurship. At the centre of the
entrepreneurship process is the individual who identifies the opportunity, gathers
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resources and brings new products to the market place. To do so effectively,
entrepreneurs need to have information that will enable them to make relevant and
timely decisions. Given the uncertain and dynamic nature of the environment in which
they operate, entrepreneurs need to keep abreast of changes in the environmental factors
in order to make good decisions. If any entrepreneur is bombarded with more
information than he or she can manage, this could impair their ability in to make better
decisions required at various stages of entrepreneurship, namely opportunity seeking,
venture creation and growth.
The literature indicates that entrepreneurs and small business owners / managers
constantly scan and monitor their operating environment in order to look for new
opportunities and also to strengthen their competitive position (Keh, Nguyen & Ng
2007; Welsch & Young 1982). In fact, they are referred to as ‘avid information
gatherers’ and search for information more than executives (Kaish & Gilad 1991, p.49).
The process of venture creation begins with recognising an opportunity, and they arise
from the entrepreneur’s ability to stay alert and be in sync with the changes that occur in
the market conditions (Kirzner 1973; Shane 2000). Scholars view the process of venture
formation as a process of learning where the entrepreneurs have to overcome the
liabilities of newness by using the information acquired by them (Cooper, Folta & Foo
1995). In a recent study, Mueller, Vollery and Von Siemens (2012) found that
entrepreneurs in the start-up stage spend approximately 36 percent of their time in
exchanging information and opinions, and the growth entrepreneurs spend 54 percent of
their time exchanging information and opinions. The dominance of this activity shows
the importance entrepreneurs are placing on environmental scanning. Information is a
critical resource that entrepreneurs use at various stages in the new venture creation and
growth. Thus, the success of a venture depends on the entrepreneur’s role, among
others, of being an information seeker, processor and assimilator.
Ikojo-Odongo and Ochollo (2004) identified three situations in which entrepreneurs
sought information: (i) major incidents: when entrepreneurs sought information
regarding training for new skills, marketing of products and inputs about sources or
supplies and their prices, (ii) minor incidents: when entrepreneurs sought information
on loans, pricing of products, environmental hazards, transport, competitors, record
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keeping, maintenance of equipment, government policies, current developments in trade
and in the country, improving quality and minimising overheads and other business
opportunities and employment, and (iii) business development: including how to
improve planning and management of businesses, to increase output and viability and
the ability to develop business ideas.
Scholars have also examined the entrepreneurs’ information needs in different
countries. A study in Singapore found that businesses considered information about
competitors, markets, business news, environment news – political, social, supplier
trends, regulatory, information technology, demographic trends and new management
methods (de Alwis & Higgins 2001). At the same time, a study of Aboriginal
entrepreneurs in Canada by Vodden, Miller and McBride (2001) reveal the most
important types of information include financing options, business planning, and
information about government programmes, markets, and marketing. A similar study of
ethnic Malaysian would-be entrepreneurs by Kassim (2010) shows that their
information needs commonly revolved around the preparation of business plans,
planning for cash-flow, borrowing capital, business opportunities and profit planning.
Stewart, May and Kalia (2008) compared the entrepreneurial information-seeking
behaviour of entrepreneurs in the US and India, and found that Indian entrepreneurs
scanned the environment more than their counterparts from the US. The authors
conclude that higher scanning frequency by Indian entrepreneurs is associated with
culture, in addition to operating circumstances. According to them, some cultures are
more disposed to greater information seeking.
Information seeking behaviour by entrepreneurs is not uniform, as entrepreneurs do not
have a single profile. Hence Welsch and Young (1982) pointed out that information
seeking behaviour depends on business complexities, cognitive orientation, and degree
of personal relationship between the entrepreneur and the source of information. These
authors have examined the role of personality factors in determining the entrepreneur’s
selection of information sources. They found that internal locus of control was
significantly related to professional, written, institutional and electronic sources of
information. Those with low self-esteem relied on professional sources (e.g, bankers,
accountants and lawyers), but those with high self-esteem did not seek much help and
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used written and institutional sources. Those with a high risk-taking propensity relied
more on trusted personal sources rather than impersonal or professional sources.
According to Cooper, Folta and Woo (1995), entrepreneurs sought information from
two major sources: professional (e.g., accountants, bankers, lawyers) and personal (e.g.,
friends or other personal networks). The authors also found that experienced
entrepreneurs were confident, and displayed less intensity in their information search
efforts compared to inexperienced entrepreneurs. Such behaviour did not change even
when they worked in a new field. Westhead et al. (2005) believed that seemingly low
search intensity by experienced entrepreneurs is because their search behaviour is
effective.
Many small businesses rely heavily on informal information sources such as word of
mouth, family and friends (Birley 1985; Smeltzer, van Hook & Hutt 1991). This is
similar to the findings of Ikoja-Odongo and Ocholla (2004), who studied informal
entrepreneurs’ use of information sources and found them to rely mostly on informal
sources; these include word of mouth, personal experience, and friends, family and
neighbours. This could perhaps be due to the cost associated with these sources. Other
scholars find the use of social networks (Baron, Byrne & Branscombe 2005) and social
capital (De Carolis & Saparito 2006) as sources of information. Social capital, in
particular, facilitates entrepreneurs by providing access to information through
appropriate timing, relevance and quality of information. Ozgen and Baron (2007)
identified three social sources of information that were useful in opportunity
recognition; these were: mentors, informal industry networks, and participation in
professional forums, with all three sources having a positive impact. Interestingly, these
authors also found that the impact of informal industry networks on entrepreneurs’
performance was mediated by their self-efficacy, which happens to be an important
variable of my study.
Casson (2005) believes that some entrepreneurs use information that is available both
publicly and privately and use their own judgement. He argues that differential access to
information generates radical differences in the entrepreneur’s perception of the
business environment and gains from efficient information management. For example,
an entrepreneur may be confident in taking a decision based on information that he or
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she alone is privy to or possesses; others who may not have access to this piece of
information will perceive such a decision to be risky. However, as Casson (2005)
reminds us, no information comes with a seal of endorsement about its truth, and
entrepreneurs make decisions, using this information, based on their perception of risk.
To aid with decision-making during these challenging times, entrepreneurs require
better quality and increased quantity of information (McEwen 2008). However, this
highlights the importance of not only getting the most relevant information, but also of
having the appropriate capability to assimilate the information while making a decision.
2.5.3 Entrepreneurial information overload and its impact
My discussion in the preceding sections shows that entrepreneurs, too, like other
business decision makers, use a lot of information from various sources. They need
information in each of the phases of entrepreneurship, starting from opportunity
recognition. It is the entrepreneur who is central to the firm and therefore plays the
crucial role of an information seeker, processor and assimilator. Information is
recognised as a key resource in decision-making processes (Schick, Gordon & Haka
1990) and entrepreneurs also need to scan the environment to get relevant information
to help them make the right decisions. While the term ‘information overload’ is not
new, it has never been used explicitly in entrepreneurship studies so far. Just as
information overload was customised to different disciplines, such as a salesperson’s
information overload (Hunter 2004; Hunter & Goebel 2008), and managerial
information overload (Farhoomand & Drury 2002), we could term the phenomenon of
information overload faced by entrepreneurs as entrepreneurial information overload
(EIO). Drawing on the literature on information overload from various disciplines, EIO
can be described as ‘a situation when the amount of venture-related information
exceeds the capacity of an entrepreneur to process, analyse and make an effective
decision’. Two major issues here, as in other disciplines, are the amount of information
available and the capacity of the entrepreneurs to use it for optimal outcomes.
Even before the explosion of information became an issue of concern in the last decade,
the study by Kaish and Gilad (1991) shows how entrepreneurs differ from corporate
managers in terms of exposing themselves to information, the sources they use to gather
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information from, and how they evaluate information cues. According to their study,
entrepreneurs in search of opportunities relied less on predictable sources and spent
more time thinking and scanning a broad landscape. Further, they found that
entrepreneurs exhibited more general alertness and were engaged in gathering
information even after hours, mostly through non-verbal scanning. In regard to
assessing and appraising the opportunity, the entrepreneurs relied more on their own
subjective impressions rather than on conventional economic analysis. This study
clearly emphasises the central role of information and information-seeking behaviour in
entrepreneurship.
To understand how we can apply information overload to entrepreneurs, we have to
understand the environment in which the entrepreneur is working. As Klausegger,
Sinkovics and Zou (2007) emphasise, living in an ‘information society’ means that
managers are bombarded with information, even if they are not actively seeking it.
Earlier studies have clearly shown two important conclusions that are relevant to
entrepreneurship: (i) individuals are faced with more information than he or she can
process at any given point in time (Gilbert et al. 1992), and (ii) our information
processing capacity is severely limited and can be readily exceeded (Baron 1998).
These two aspects are applicable to entrepreneurs who face an abundance of
information and find it difficult to sift the information to identify what is relevant and
useful.
A contributing factor to this overload is that there is a plethora of sources from which
information emanates and these sources are constantly growing. It is seen that the
‘information society’ is creating a large amount of information than we can consume,
but with the advent of new technologies, the situation of overload has further
compounded. Feather (2008, p.xviii) believes that “the technological developments of
the past 60 years have made more information more available to more people than at
any other time in human history”. This trend does not seem likely to diminish or stop.
The increase in the trend is visible with the introduction of social media and faster
internet access. As we have seen in the discussion early in this section, entrepreneurs
are avid information seekers and look for venture-related information at all stages of
their venture. They will definitely be faced with an overwhelming amount of
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information coming from various sources and much more than they can assimilate.
Many entrepreneurs, unlike the CEOs of large companies, are small and medium sized
owners and may not be well equipped with the tools to systematically glean sufficient
and relevant information. Baron (1998, p.275) observed that entrepreneurs “face
situations that tend to overload their information-processing capacity and are
characterized by high levels of uncertainty, novelty, emotion, and time pressure”. He
also finds that this pressure is felt more by entrepreneurs than other individuals, and due
to this the entrepreneurs who are impacted by information overload are susceptible to
cognitive biases such as counterfactual thinking, regret over missed opportunities, affect
infusion, self-serving bias, planning fallacy and self-justification (see Baron 1998,
p.279).
The aspect of the information processing ability of entrepreneurs is very important. It is
possible that some personality characteristics such as experience, culture, level of
confidence, and risk-taking propensity of entrepreneurs may impact on their information
seeking behaviour (Forbes 2005; Podoynitsyna, Van der Bij & Song 2011; Stewart,
May & Kalia 2008). These factors underpin how an entrepreneur will seek information,
select it and use it for decision making. However, at this stage, we are not clear how
such personality characteristics are related to the information overload being faced by
entrepreneurs. For example, while Hunter (2004) found that a perception of information
overload lowered self-efficacy (and indirectly affected performance), it was found to
play a positive role in performance outcome (Ozgen & Baron (2007). Obviously, further
investigation is required to understand these relationships between personality
characteristics that influence the information processing capability of entrepreneurs and
information overload faced by entrepreneurs.
To be successful, the entrepreneur needs to have self-efficacy in performing the tasks of
opportunity seeking, venture creation and growth. The key to success is making quality
decisions in all phases of the entrepreneurial process. The ability to perform well
throughout this process depends, among other things, on the entrepreneur’s ability to
identify and use relevant information. The right amount of information helps in coping
with uncertainty, as it reduces the level of uncertainty (Schick, Gordon & Haka 1990).
On the other hand, having an information overload reduces the effectiveness of decision
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making (Miller 1972; Shick, Gordon & Haka 1990) while increasing information
anxiety (Bawden & Robinson 2009). Emotional arousal or physiological responses
resulting from anxiety, stress or fear can negatively impact on self-efficacy (Conger &
Kanungo 1988; Bandura 1977), and can, in turn, adversely impact on entrepreneurs’
behaviour. Therefore, these negative implications of information overload can also have
a detrimental impact on entrepreneurs’ decision-making and performance.
Therefore entrepreneurs can experience information overload when there are too many
sources of information, too much information, not enough time to processs it, frequent
interruptions, and no strategic information management tools to guide them. They may
also lack the capacity to process the information in time and this might increase the
negative effect of the overload. If entrepreneurs feel the effect of information overload,
they, too, like the individuals examined in other disciplines such as marketing, medicine
and psychology may feel stressed or overwhelmed, and see a decrease in self-efficacy
that can potentially result in poor performance. While the problem of information
overload is being studied thoroughly in other disciplines, no study has to date explicitly
examined its impact empirically in entrepreneurship studies. This study seeks to
examine the impact of the entrepreneur’s perception of information overload on his/her
self-efficacy and entrepreneurial behavioural activities.
2.6 Chapter summary
To sum up, this chapter reveals that the entrepreneur who is at the centre of the
entrepreneurship process has a distinctive personality, such as need for achievement,
internal locus of control and risk-taking propensity which not only differentiates
him/her from others, but also enables them to engage in entrepreneurial activities
through their behaviour. Another key antecedent of entrepreneurial behaviour is the
concept of entrepreneurial self-efficacy. It is clear that having confidence in their ability
to undertake entrepreneurial activities provides an impetus to perform them confidently.
While some recent authors have found the multi-dimensional nature of the construct of
entrepreneurial self-efficacy, these dimensions were not investigated separately.
Similarly, two other important aspects related to entrepreneurship have not received
adequate attention from researchers. They are entrepreneurial behaviours and
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information overload, and my review of the literature showed that they are critical to the
field of entrepreneurship. Based on the literature review, it can be seen that the four
entrepreneurship areas, namely the entrepeneur’s personality traits, entrepreneurial self-
efficacy, entrepreneurial behaviours and information overload could be related. I seek
to examine these relationships in the context of emerging economies. Therefore, the
next chapter highlights the key features of India, which is considered to be the second
largest emerging economy after China.
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CHAPTER 3
ENTREPRENEURSHIP ISSUES IN INDIA
This study examines some critical entrepreneurship issues in India, which is a large
emerging economy. According to Bruton, Ahlstrom and Obloj (2008), there has been a
growing focus on entrepreneurial research in emerging markets in the recent past. In
order to understand the context in which the study is undertaken, it is necessary to
examine the main features of the emerging markets, and the background of
entrepreneurship in India. For this purpose, I have structured this chapter as follows.
First, I discuss the concept of emerging markets. Second, I comment briefly on the
country overview. Third, I examine critical issues that relate to entrepreneurship in
India.
3.1 Emerging economies and their characteristics
In spite of popular usage of the term ‘emerging economies’ and interest in these
countries, there is a growing debate around the concept of emerging economies and as
to which countries constitute this category. Some scholars also use the term ‘emerging
markets’ synonymously with the term ‘emerging economies’. Several international
organisations use this term to group different countries. The term ‘emerging economies’
was first coined by Antoine van Agtmael, a former Investment Officer of the
International Finance Corporation (an agency of the World Bank Group) in 1981. For
many multinationals, which mainly operate in mature markets, emerging economies
have become attractive as they offer them the potential for immediate sales, and allow
them to capitalise on their globally recognised brands.
Different scholars (Hoskisson et al. 2000; Mody 2004) have attempted to identify
characteristics that are common to emerging economies. Hoskisson et al. (2000, p.249)
define emerging economies as countries that satisfy two criteria: (i) a rapid pace of
economic development, and (ii) where government policies favour economic
liberalisation and the adoption of a free-market system. Due to these reasons, these
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economies have not only received significant amounts of foreign direct investments
(FDI), but also contributed to a large amount of FDI outflows (UNCTAD, 2005).
Likewise, Mody (2004) also identified two essential features of emerging economies: a)
their high degree of volatility, and b) their transitional character. This idea was endorsed
by Gaur and Kumar (2009), who pointed out that emerging economies are characterised
by uncertain economic and political systems, and inadequate institutional support.
While significant socio-economic changes are a common trend in these countries, many
in the sector also undergo transitions in a variety of fields. For example, transition is
visible in demographic characteristics, such as in fertility rates, life expectancy and
educational status. Irrespective of the classification of emerging economies, these
economies display certain common features such as rapid industrialisation, growing use
of information technology, and bourgeoning consumer markets. Khanna and Palepu
(2010) highlighted the fact that emerging economies are “starting from a lower base and
rapidly catching up” (p.5). An important feature of emerging economies is the
development of private entrepreneurial firms, which are relatively new but have become
increasingly a salient phenomenon (Ahlstrom & Bruton 2002; Kshetri 2009). In general,
emerging economies have rates of social and business activity that place them on a path
of rapid growth and development.
Even over a decade ago, Hoskisson et al. (2000) cautioned researchers that there is no
standard list of countries that could be part of emerging economies. Using the World
Bank’s development indicators, Hoskisson et al. (2000) identified 64 emerging market
economies under four geographic regions, namely Asia, Europe, Latin America and the
Middle East/Africa. Countries even within the same geographic region are not
homogeneous either. To further compound this scenario, different lists of emerging
economies were proposed. For example, Morgan Stanley Capital International (2010)
identified 21 countries, while Dow Jones (2010) classified 35 countries as emerging
markets. A relatively recent report by PricewaterhouseCoopers (2008) predicted that a
group of emerging economies (the E7, consisting of China, India, Brazil, Mexico,
Russia, Indonesia and Turkey) will overtake the developed countries (the G7, consisting
of Canada, France, Germany, Italy, Japan, the UK and the US) by more than 50 percent
by 2050.
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Jim O’Neill, the chairman of Goldman Sachs Management, coined the acronym BRIC,
standing for Brazil, Russia, India and China. These nations form part of the emerging
economies category, but have received increased interest as many economists and
researchers believe that the BRIC countries are among the largest in terms of
demography and economies. Recently, South Africa was added to this list to make the
group BRICS. Country details of this group may be seen in Table 3.1.
Table 3.1 BRICS Countries Details (2012)
Country Gross Domestic Product (US$ Billions)
Current population (in millions)
Per Capita GDP
Literacy rates
Brazil 2254.2 198.66 11340 90.4 percent (2010 est)
Russia 2033.9 143.53 14037 93 percent (2011 est)
India 1875.2 1237 1489 62.8 per cent (2006 est)
China 8227.1 1350.7 6091 95.1 per cent (2010 est)
South Africa 384.31 51.19 7508 93 percent (2011 est)
Source: GDP per capita 2014; Principal Global indicator 2013; Population Total 2014; The World Factbook 2013a) Currently, these BRICS countries together are home to more than 40% of the world’s
population, cover more than a quarter of the world’s landmass, and account for about
25% of the global GDP (BRIC Countries – Background, Latest News, Statistics and
Original Articles, n.d.; Fawzy and Dworski 2010). They are predicted to become
economically powerful, not only in terms of current, but also future, growth, and to
outgrow the US soon.
3.2 Importance of emerging markets
These countries have already produced some of the top multinational firms in the world
like Oil and Natural Gas Corporation, Tata Consultancy Services, Infosys Inc, Wipro
Inc, Ranbaxy Pharma etc (India), Sinopec, State Grid Corporation, Industrial and
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Commercial Bank of China, China Telecom (China), CVRD, Petrobras SA, Gerdau SA
(Brazil), Lukoil, Gazprom, Severstal (Russia), and SAB Miller, MTN Group, Naspers
(South Africa). Emerging economies that now include BRICS countries have gained a
prominent position in the world economy (Wright et al. 2005). The developed and
mature economies concentrate on the emerging economies for their future growth of
markets. This is evident from the increase in the amount of foreign direct investments
(FDI) in the emerging markets. Similarly, the FDI outflows from the emerging
economies are also increasing (Surge in foreign direct investment in developing
countries reverses global downturn, 2005; Singal & Jain 2012). Given the growing
importance of the emerging economies, it is critical to understand their economies and
business activities that take place in those countries. Among those countries, India is
only next to China in both population and GDP.
Since the sample for our study is drawn from India, it is necessary to understand the
context and business environment in India. Many scholars have already documented the
institutional factors facilitating or hindering new venture performance (Peng 2002;
Kiggundu 2002). Such factors will definitely influence entrepreneurial development in
India as it opens up its hitherto closed economy and moves towards a more liberalised
system.
3.3 Overview of India
To understand entrepreneurship in emerging markets such as India, it is important to
appreciate the combination of historical factors, cultural values, the religion followed
and social structures. After being ruled by the British for over 200 years, India attained
political independence in 1947. The Republic of India has a population of over one
billion, and is very multicultural, including representation from five major ethnic races
such as Australoid, Mongoloid, Europoid, Caucasian, and Negroid (Government of
India 2014) and religious groups such as Hindus, Christians, Muslims, Sikhs, Buddhists,
Jains, Parsis, and Jews among others. Hindus now constitute the majority of the
population, at about 80%. Table 3.2 shows the diversity of the country in terms of
religions followed and languages spoken.
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As seen in Table 3.1, India has a population of more than 1.2 billion and is growing at
an average rate of 8 per cent per annum. India is also a regional power and the world’s
largest democracy. Economically, it is only next to China as a large emerging economy.
In fact, due to its economic performance in recent decades, India is considered to be ‘the
next Asian Miracle’ (Huang 2008, p. 32).
Table 3.2 India at a glance
Size 3,287,263 sq km
7th largest country in the world
Shares borders
with
India has land borders with Pakistan (2,912km) to the north-west, China (3,380km), Nepal (1,690km) and Bhutan (605km) to the north, Bangladesh (4,053km) and Burma (1,463km) to the east.
Religion (as per the 2001 census) Percentage
Hindus 80.5
Muslims 13.4
Christians 2.3
Sikhs 1.9
Buddhists 0.8
Jains 0.4
Others 0.6
Religion not stated 0.1
Major Languages spoken (2001) Percentage
Hindi 41
Bengali 8.1
Telugu 7.2
Marathi 7
Tamil 5.9
Urdu 5
Gujarati 4.5
Kannada 3.2
Punjabi 2.8
Assamese 1.3
Maithili 1.2
Other 5.9
Source: The World FactBook 2013b; Nationmaster 2014; The Registrar General & Census Commissioner 2011.
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3.4 Entrepreneurship in India
Entrepreneurship is not new to India. Even in ancient times, Indian entrepreneurs and
business people were known for their unique goods and wealth creation. In fact, this is
one of the reasons why the British went to India as traders and eventually colonised it
and made it part of the British Empire. A review of articles by Misra (1992; 2000) give
an outline of the history of entrepreneurship during British rule. In this section, I will
examine entrepreneurship under three different categories, namely the socio-cultural,
the economic and the educational spheres.
3.4.1 Socio-cultural context of entrepreneurship in India
In an Indian context, religion and other socio-cultural factors play an important role (see
Table 3.2 for a list of religions followed in India). According to Lipset (2000), while
structural conditions make development possible, it is the cultural factors that determine
whether the possibility becomes an actuality (or not). But values are embedded in
culture, and so Phelps (2007) observes, ‘values and attitudes are as much part of the
economy as institutions and policies are. Some impede, others enable.’ Hinduism is the
dominant religion and it is strongly associated with the rigid caste system. Singer
(1966) finds that, in comparison to other religions, Hinduism does not offer much
encouragement or value for one to change their situation in terms of material wellbeing.
In ancient times, occupations largely stemmed from the caste system and traditions were
sanctified by religion (Medhora 1965). Based on the Hindu scriptures, society is
segmented into four main varnas (or castes), which were placed in a hierarchy with the
Brahmin (the priest) at the top. The other castes in the hierarchy after the Brahmin are
the Kshatriya (the warrior), the Vaisya (the trader, merchant, landowner) and the Shudra
(the artisan, the commoner, and the peasant). The ‘untouchables’ were placed below the
varna system. Occupational immobility was therefore sanctified by the caste system.
Indian people maintained the status quo by getting into occupations linked to their
cultural conditioning, which is manifested by the caste they were born into. Each
individual has a duty (dharma) specific to the caste of their birth. This is a kind of
sociological division of labour.
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In contrast to the Western cultures, where the entrepreneurial activity stemmed from the
drive to achieve (McClelland 1961), irrespective of their background, commercial
activities in India were largely monopolised by the Vaisya community during the
ancient and medieval periods of Indian history (Tripathi 1971). In fact, Indian society
chose to maintain the status quo by choosing occupations based on their cultural
traditions, and entrepreneurial activity was undertaken by the castes whose duty
(dharma) it was to do business, and not the other castes (Medhora 1965; Dana 2000).
According to Weber (1958), the caste system inhibits innovation in the Indian economic
system due to its rigidity. He observes, “We are now in a position to enquire into the
effects of the caste system on the economy. These effects were essentially negative ...”
(p.111). For these reasons, as Tripathi (1992) observes, the social base of
entrepreneurial growth has remained very limited. However, analysing the impact of the
caste system as a whole on Indian personality with reference to business, Tripathi
(1992) observes, “the result was that the Indian personality, by and large, remained
unentrepreneurial, if not anti-entrepreneurial” (p. 77). But as mentioned earlier, this was
limited to one social group/caste of people.
Researchers (Hozelitz 1960; Nafziger 1978) have noted that entrepreneurship can
develop only when cultural norms permit variability in the choice of paths of life, in
other words, where caste divisions were not rigidly observed. While some of these
social scientists blamed the Hindu value systems for inhibiting the entrepreneurial spirit,
some scholars believe that when the material environment changes, the non-business
classes also take up business ventures (e.g., Mehta & Joshi 2002). To elaborate further,
the authors suggest that apart from the business class (the Parsis, Jains and the Banias),
the Patel community, which is traditionally an agricultural community, has entered the
trading sector. Interestingly, members of the Patel community who migrated to various
parts of the world have carried with them the entrepreneurial culture that helped them to
successfully establish themselves as entrepreneurs in service industries such as hotels,
motels and petrol stations (Bal 2006; Kalnins & Chung 2006).
Recent studies on the rigidity of caste-occupation matching show some interesting
results (Sharma & Singh 1980; Audretsch, Boente & Tamvada 2007). For example,
Sharma and Singh’s (1980) extensive research in northern India (particularly in the state
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of Punjab) concluded that the businesses were dominated by the Vaisya community,
which is consistent with the age-old tradition. People of this community depended on
people of their own caste (familial relations) in identifying opportunities to start
businesses, raise capital, and gain technical know-how, and they were more likely to
start businesses if members of their family were already in business. Another study by
Audretsch, Boente and Tamvada (2007) shows that religion does affect the decision to
become an entrepreneur. They find Vaisyas to be more likely to be self-employed [as
entrepreneurs] and non-Vaisyas to be less likely to be self-employed. According to the
authors, this finding confirms that the class structures of Hinduism continue to influence
occupations, particularly with respect to becoming an entrepreneur.
In the recent past, there seem to be some significant changes in occupational mobility
which breaksthe traditional barriers. For example, Sharma and Singh (1980) found that
there was an increase in the number of lower-caste people emerging on the
entrepreneurial scene. Although the members of other castes have entered the
entrepreneurial field, Sana (1993) observes that there is a higher proportion of industrial
and commercial entrepreneurs who come from the traditional trading castes. For
instance, the Marwaris, a close-knit community of the trading caste, owned 27 of the 78
large corporations in India in 1991, the second being the Parsis, who owned 12. The
Reliance business group and the Tata group are examples of the first and the second
castes (or ethnic group) respectively. Their extraordinary success is attributed to their
caste solidarity. But Murty (2014) suggests that the cosmopolitan outlook that emerged
in the post-reform period has, in a sense, ruptured the link between castes and
professions. Some Dalit people, who were at the bottom of the social hierarchy, have
also become entrepreneurs. Some of them have received support from government
sponsored programmes, as part of affirmative action which supports lower-caste
businesspeople. It is interesting to note that these Dalit entrepreneurs have created their
own federation of commerce, known as the Dalit Indian Chamber of Commerce of India
(http://www.dicci.org) which is affiliated to the Confederation of Indian Industry (CII),
the leading chamber of commerce grouping in India. This provided an opportunity for
the lower caste people to gain significant social mobility through entrepreneurship.
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3.4.2 Economic development and entrepreneurship in India
Prior to gaining independence in 1947, the Indian economy was predominantly agrarian,
and industries were small-scale in nature. These were industries like handicrafts,
involved artisans, or were related to agrarian products. The economy as a whole was
controlled and exploited for colonial interests. The entrepreneurs were mainly in the
form of traditional artisans and home-based rural firms (cottage industries) and matched
their expected caste duties. While British colonial rule was detrimental to these rural-
based industries, many Indian entrepreneurs and businessmen took the lead in
establishing large-scale industries during this time (for details, see Mishra 1992 and
2000). Prominent among them was Jamsetji Tata (1842 - 1905), who was the founder of
India’s iron and steel and hydro-electric industries in the late 19th and early 20th
centuries. He was characterised by his willingness to take risks with capital to invest in
new technology amidst uncertainty. Other such industrialists were Birlas, Dalmia and
Sahu Jain, Shri Ram and J.K. Kasturbhai. Despite being industrialists, they were also
staunch supporters of the Indian independence movement.
To wean itself away from the colonial interests and to gain self-sufficiency, the newly
independent government in India in the 1950s decided to emphasise large-scale
industries, and the traditional small-scale industries were to be an adjunct to meet other
needs of the economy. Accordingly, Pandit Jawaharlal Nehru, the first prime minster of
independent India, and Prof. Mahalonabis, the architect of the economic planning
system, focussed on creating a large industrial sector dominated and controlled by the
government. It was felt that economic development requires huge industrial
infrastructure and that the private sector would not be interested in risky investments
which were unlikely to return profits in the short run. Therefore, it was felt that the
public sector, i.e., the government-owned economic sector, should occupy the
‘commanding heights’ of the economy to champion the developmental goals of the
economy.
As India was a British colony for almost 200 years, foreign direct investment was
viewed with understandable scepticism. Even in independent India, the economy was
known for controls, permits and licences, and quotas with an idealistic view of guiding
it towards national goals. Decision making was slow and quite bureaucratic in nature.
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While democracy has a number of benefits, pro-labour regulations that are a product of
a democratic environment, were found to hinder economic performance (Besley &
Burgess 2004). Therefore, the economic growth rate was stuck at the low rate of 3.5 per
cent, which was pejoratively dubbed the ‘Hindu rate of Growth’. In the late 1980s, the
governments were somewhat unstable and changed in relatively quick succession for
various reasons. Even during this time, India started to slowly recognise the need for
liberalising the economy and started to relax the industrial regulation regime in the
1970s; they followed this up with some significant deregulation in the 1980s
(Panagariya 2004). In 1991, the government that came to power faced a myriad of
economic challenges, including the threat of sovereign default when its foreign
exchange reserves ran extremely low. This situation obviously required a radical
approach to economic policy that significantly departed from previous policies.
However, the launch of bold economic reforms in 1991 was a watershed in the
economic history of India in modern times. The focus was on developing much stronger
infrastructure to support private enterprise. India’s banking sector, capital markets, and
legal system were strengthened significantly. The predominant features of this new
approach included: privatisation, deregulations, and an opening up of the economy for
foreign direct investment. Private investment was encouraged to take an active part in
the economic development of the country. Overall, its economic system shifted away
from the ‘quota-permit raj’ of bureaucratic controls to a market-oriented system. This
resulted in an unleashing of economic potential, and some of the globally recognised
firms and brands developed during this time. Some of them include software giants like
Infosys, Wipro and Tata Consultancy Services, and pharmaceutical firms like Ranbaxy
and Dr. Reddy’s Labs.
In recent times, the government of India is also proactively engaging with
entrepreneurs, particularly with those first generation entrepreneurs, and providing them
with training and development to inculcate an entrepreneurial culture (Government of
India 2014b). With this objective, the Ministry of Micro, Small & Medium Enterprises
has set up three autonomous national-level institutes, namely: the National Institute for
Micro, Small and Medium Enterprises (NI-MSME); the National Institute for
Entrepreneurship and Small Business Development (NIESBUD) and the Indian Institute
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of Entrepreneurship (IIE). These institutes cater to the training and development needs
of potential and new entrepreneurs, as well as provide consultancy services to them.
This shows that there is now a conscious and deliberate attempt to support
entrepreneurship in India.
3.4.2.1 Small-scale sector in India
As mentioned earlier, in the initial decades after independence, the small-scale sector
was viewed as an adjunct to the public sector, which focused on large industries. These
small firms were expected to supply the consumer goods needed to support workers in
the large-scale sector or heavy industries. As the heavy industries were owned and
promoted by the government-owned public sector, only the small-scale sector was open
for private entrepreneurs and small business owners. However, the reforms in 1991
allowed the small-scale sector to grow rapidly. Table 3.3 shows the contribution of the
small-scale sector to the Indian economy from the time when epoch-making economic
reforms started in 1991.
Table 3.3 Contribution of small-scale industry to the Indian economy
Year No. of Units (in lakhs*) Total: Registered and unregistered
seminal work explains that individuals with a high need for achievement have a higher
drive to excel. Jackson (1974, p.6) describes this type of individual as one who
“maintains high standards” as well as one who “aspires to accomplish different tasks".
This characteristic influences an individual’s work behaviour to a great extent (Lumpkin
& Erdogan 2000). Such individuals are high achievers, and they like situations where
they take personal responsibility, particularly when they are faced with problems and/or
challenges. McClelland (1965) found that students with a higher need for achievement
were found to gravitate towards entrepreneurship and other business occupations.
According to Littunen (2000), McClelland’s theory suggests that individuals with a high
need for achievement will not only become entrepreneurs, but succeed better than
others. Empirical studies have shown that need for achievement is positively associated
with entrepreneurship (Caliendo, Fossen & Kritikos 2014; Davidsson 1989; Stewart et
al. 1999).
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Collins, Hanges and Locke’s (2004) meta-analytic study found that individuals with a
higher need for achievement were more attracted to entrepreneurship, as it offers them
an opportunity for a higher degree of control over outcomes and also allows them to
assume personal responsibility. This can be related to the concept of entrepreneurial
self-efficacy, which refers to an individual’s confidence in his/her ability to successfully
launch an entrepreneurial venture (McGee et. al. 2009) and perform entrepreneurial
roles (Chen, Greene & Crick 1998). Clearly, those who possess a higher degree of
entrepreneurial self-efficacy would also like to take personal responsibility in order to
control entrepreneurial outcomes. However, as McGee (2009) pointed out, there are
several dimensions that constitute the construct of entrepreneurial self-efficacy. In my
study, entrepreneurial self-efficacy consists of six different dimensions that were
identified from the literature; they are searching, planning, marshalling, implementing
people-related tasks, implementing finance-related tasks and ability to cope with
unexpected challenges. The first five dimensions were identified by McGee et al. (2009)
and the sixth dimension was taken from the study of DeNoble, Jung and Ehrlich (1999)
which relates to the level of confidence the entrepreneur has in his /her ability to stay
calm in the face of unexpected challenges. It is therefore necessary to examine the
relationship between the personality characteristic of the need for achievement and each
of the six dimensions of entrepreneurial self-efficacy. Accordingly, the following
hypotheses are proposed:
H1a-H1f - Personality characteristics of need for achievement and dimensions of entrepreneurial self-efficacy:
Hypothesis 1a: The personality characteristic of need for achievement is positively associated with the searching capability dimension of entrepreneurial self-efficacy.
Hypothesis 1b: The personality characteristic of need for achievement is positively associated with the planning capability dimension of entrepreneurial self-efficacy.
Hypothesis 1c: The personality characteristic of need for achievement is positively associated with the marshalling capability dimension of entrepreneurial self-efficacy.
Hypothesis 1d: The personality characteristic of need for achievement is positively associated with the implementing people-related capability dimension of entrepreneurial self-efficacy.
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Hypothesis 1e: The personality characteristic of need for achievement is positively associated with the implementing finance-related capability dimension of entrepreneurial self-efficacy.
Hypothesis 1f: The personality characteristic of need for achievement is positively associated with the coping with unexpected challenges capability dimension of entrepreneurial self-efficacy.
4.2.2 Personality characteristic of internal locus of control and dimensions of entrepreneurial self-efficacy
Locus of control is a personality trait that refers to a general expectancy across a range
of situations relating to whether or not an individual has control or power over what
happens to him or her. This construct has two dimensions of locus of control: internal
and external. According to Lefcourt (1966), internal locus of control reflects the degree
to which an individual perceives that an outcome of their behaviour is within their own
control, while the external locus of control reflects the perception of an individual that
the outcomes of their behaviour are determined by external factors and therefore not
within their own control. Hence the individuals with internal locus of control believe
that they can determine their future outcomes by their own actions. Past studies have
also shown that individuals who perceive they have control of the environment, in other
words people who have a high internal locus of control, show a relationship to greater
self-efficacy (Wood & Bandura 1989a; Phillips & Gully 1997). In entrepreneurship, we
expect that entrepreneurs are individuals who possess the personality characteristic of
internal locus of control, as they are self-motivated individuals who take the initiative in
entrepreneurial efforts and who take responsibility for achieving a venture’s set goals
(McClelland 1961; Mueller & Thomas 2001). Researchers have found that nascent
entrepreneurs who had entrepreneurial intentions had a higher degree of internal locus
of control than those who did not have such plans (Borland 1974; Brockhaus 1975).
Cromie and Johns (1993) found that practicing entrepreneurs possessed more internal
locus of control than managers. It is also suggested that a person with high internal
locus of control believes that he/she can use their skill and efforts in order to control the
events in his/her life (Boone, Brabander & Van Witteloostuijn 1996).
The above discussion points out that the ability to take the initiative and responsibility
could be associated with the personality characteristic of internal locus of control of
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entrepreneurs. This kind of psychological attitude forms the basis of entrepreneurial
self-efficacy, where the individual believes in his or her capacity to accomplish a certain
level of performance or achieve desired outcomes, which in turn influences the
individual’s behaviour (Bandura 1986). According to Markman, Balkin and Baron
(2002), individuals are motivated by their perceived self-efficacy rather than by an
objective ability; hence self-perception is very important. The perception of being able
to control an event is closely related to self-efficacy (Phillips & Gully 1997). However,
as discussed earlier, I have identified six different dimensions of entrepreneurial self-
implementing finance-related tasks and ability to cope with unexpected challenges. It
follows that those entrepreneurs who have a high internal locus of control will have also
have a high self-efficacy in activities pertaining to entrepreneurship such as planning,
risk-taking, and coping with the environment. At this stage, there is no empirical
evidence associating the construct of internal locus of control of entrepreneurs with each
of the six entrepreneurial self-efficacy dimensions separately. Therefore, I propose the
following hypotheses:
H2a-H2f – Personality characteristics of internal locus of control and entrepreneurial self-efficacy:
Hypothesis 2a: The personality characteristic of internal locus of control is positively associated with the searching capability dimension of entrepreneurial self-efficacy.
Hypothesis 2b: The personality characteristic of internal locus of control is positively associated with the planning capability dimension of entrepreneurial self-efficacy.
Hypothesis 2c: The personality characteristic of internal locus of control is positively associated with the marshalling capability dimension of entrepreneurial self-efficacy.
Hypothesis 2d: The personality characteristic of internal locus of control is positively associated with the implementing people-related capability dimension of entrepreneurial self-efficacy.
Hypothesis 2e: The personality characteristic of internal locus of control is positively associated with the implementing finance-related capability dimension of entrepreneurial self-efficacy.
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Hypothesis 2f: The personality characteristic of internal locus of control is positively associated with the coping with unexpected challenges capability dimension of entrepreneurial self-efficacy.
4.2.3 Personality characteristic of risk-taking propensity and dimensions of entrepreneurial self-efficacy
An important personality characteristic of entrepreneurs is risk taking. This refers to an
individual’s current tendency to take or avoid risk (Sitkin & Weingart 1995). Risk
taking is inherent in every decision an entrepreneur takes in the face of uncertain
situations, whether it is to become an entrepreneur or to make investment decisions,
particularly so because the outcomes of these decisions are unpredictable (Caliendo,
Fossen & Kritikos 2014). Therefore, the tendency of individuals to take risks has been
viewed as an important characteristic associated with entrepreneurship (Zhao, Seibert &
Lumpkin 2010). Several studies have found that individuals with higher risk-taking
propensity engage in entrepreneurial ventures, while those individuals who are risk
averse choose to work for others (Carland III et al. 1995; Stewart et al. 1999). In another
study, Hartog, Ferrer-i-Carbonell and Jonker (2002) found that entrepreneurs are less
risk averse than employed persons.
But not all studies provide categorical evidence to support a risk-taking propensity by
entrepreneurs. Brockhaus (1980b) could not differentiate between entrepreneurs and
non-entrepreneurs based on the risk-taking characteristic. In a meta-analytic study by
Stewart and Roth (2001), the authors found that entrepreneurs did have a higher risk
propensity compared to managers. But these findings were contested by Miner and Raju
(2004), who suggested that entrepreneurs are actually risk-avoidant, which in turn was
rebutted by Stewart and Roth (2004). Other scholars argue for the need to consider other
factors such as cognitive patterns (Palich & Bagby 1995) and distinct phases of
entrepreneurship (Markman, Baron & Balkin 2005). In a recent meta-analysis, Zhao,
Seibert and Lumpkin (2010) found risk is positively related to entrepreneurial intention,
but not necessarily to other measures of entrepreneurial performance. They also found
that the risk-taking characteristic is particularly important during the early stages of
entrepreneurship when the entrepreneurs seek out opportunities, network, and acquire
resources to embark on their new venture, but they are not sure if this was an asset or a
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liability afterwards. Hence, it cannot be concluded whether risk-taking is compulsory
for entrepreneurs.
Scholars such as Zhao, Seibert and Hills (2005) suggest that individuals who have a
high risk-taking propensity will be more likely to want to pursue entrepreneurial
activities because they may feel more confident in undertaking entrepreneurial roles and
tasks necessary to succeed. Such individuals will be expected to be positively associated
with entrepreneurial self-efficacy, which indicates belief in their confidence in pursuing
their goals (Markman, Balkin & Baron 2002). However, the entrepreneurial self-
efficacy construct in our study constitutes six different dimensions, namely searching,
tasks and ability to cope with unexpected challenges (DeNoble, Jung & Ehrlich 1999;
McGee et al. 2009). How this risk-taking propensity affects each of the dimensions of
entrepreneurial self-efficacy was not, however, examined before. Hence, I propose the
following set of hypotheses:
H3a-3f- Personality characteristics of risk-taking propensity and dimensions of entrepreneurial self-efficacy:
Hypothesis 3a: The personality characteristic of risk-taking propensity is positively associated with the searching capability dimension of entrepreneurial self-efficacy.
Hypothesis 3b: The personality characteristic of risk-taking propensity is positively associated with the planning capability dimension of entrepreneurial self-efficacy.
Hypothesis 3c: The personality characteristic of risk-taking propensity is positively associated with the marshalling capability dimension of entrepreneurial self-efficacy.
Hypothesis 3d: The personality characteristic of risk-taking propensity is positively associated with the implementing people-related capability dimension of entrepreneurial self-efficacy.
Hypothesis 3e: The personality characteristic of risk-taking propensity is positively associated with the implementing finance-related capability dimension of entrepreneurial self-efficacy.
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Hypothesis 3f: The personality characteristic of risk-taking propensity is positively associated with the coping with unexpected challenges capability dimension of entrepreneurial self-efficacy.
4.3 Entrepreneurial information overload and entrepreneurial self-efficacy
Previous research indicates that entrepreneurs who have high levels of entrepreneurial
self-efficacy are positively related to their entrepreneurial intentions and career (Chen,
Greene & Crick 1998, De Noble, Jung & Ehrlich 1999; McGee et al. 2009). Similarly, a
study by Forbes (2005) found a positive relationship between entrepreneurial self-
efficacy and new venture performance. A successful entrepreneur is expected to
perform the tasks of opportunity seeking, venture creation and growth. As De Noble,
Jung and Ehrlich (1999) point out, one of the key dimensions of entrepreneurial self-
efficacy is developing opportunities. This suggests that the key to succeed as an
entrepreneur is to make good decisions at various stages of entrepreneurship, namely
opportunity seeking, venture creation and growth. Understandably, successful
entrepreneurship requires, among others things, an ability to access information to make
relevant and timely decisions. The literature clearly shows that business owners and
managers constantly scan and monitor their operating environment in order to look for
new opportunities and strengthen their competitive position (Keh, Foo & Lim 2007;
Welsch & Young 1982).
In present times, a large amount of information is not only made available to
entrepreneurs, but is also made available sooner (Spira, 2011). Access to the right
amount of information helps in coping with uncertainty by reducing it (Schick, Gordon
& Haka 1990). Further, when information is organised into meaningful schemas, it can
contribute to entrepreneurs’ self-efficacy and performance (Ozgen & Baron 2007;
Markman, Balkin & Baron 2002). However, with the explosion of information
technology and gadgets in the modern world, business managers are subjected to
information overload, which reduces their ability to make good decisions (Speier,
Valacich & Vessey 1999). So now the problem is not just lack of access to information,
but an overload of information (Shapiro & Varian, 1999). This information overload
reduces the effectiveness of decision making (Miller, 1972; Schick, Gordon & Haka
1990) and increases information anxiety (Bawden & Robinson 2008). As mentioned
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earlier (Conger & Kanungo 1988; Bandura 1977), such emotional arousal, or
physiological responses resulting from anxiety, stress or fear, can negatively impact on
self-efficacy. In my study, the entrepreneurial self-efficacy construct has six
dimensions, as discussed earlier, and these are likely to be adversely affected by
information overload. This is because decision makers experiencing information
overload may ignore available information and become selective or even lose control
over information (Bawden 2001; Edmunds & Morris 2000). Based on these arguments,
I propose the following set of hypotheses.
H4a-4f- Entrepreneurial information overload and entrepreneurial self-efficacy dimensions
Hypothesis 4a: Entrepreneurial information overload is negatively associated with the searching capability dimension of entrepreneurial self-efficacy.
Hypothesis 4b: Entrepreneurial information overload is negatively associated with the planning capability dimension of entrepreneurial self-efficacy.
Hypothesis 4c: Entrepreneurial information overload is negatively associated with the marshalling capability dimension of entrepreneurial self-efficacy.
Hypothesis 4d: Entrepreneurial information overload is negatively associated with the implementing people-related capability dimension of entrepreneurial self-efficacy.
Hypothesis 4e: Entrepreneurial information overload is negatively associated with the implementing finance-related capability dimension of entrepreneurial self-efficacy.
Hypothesis 4f: Entrepreneurial information overload is negatively associated with the coping with unexpected challenges capability dimension of entrepreneurial self-efficacy.
4.4 Entrepreneurial information overload and entrepreneurial behavioural activities
The literature shows that with growing information technology and an ever-changing
environment, the state of information inadequacy has changed. Entrepreneurs
consciously engage in gathering information for entrepreneurial decisions and
implementation. But information is now available in abundance from multiple sources,
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leading to information overload. Eppler and Mengis (2004) maintain that a combination
of five factors causes information overload: (i) information in terms of its volume,
frequency, intensity, and quality; (ii) the receiver; (iii) the tasks that need to be
accomplished; (iv) the organisational design; and (v) the information technology. They
combine to overwhelm the information processing capacity of an individual, which
adversely affects decision making (Speier, Valacich & Vessey 1999).
According to Bird, Schjoedt and Baum (2012), entrepreneurial behaviour consists of the
observable actions (activities) of the individual and the responses that are evoked by
those activities. Some of the entrepreneurial behavioural activities identified are:
planning, business location, writing a business plan, human resources management,
seeking outside advice, and seeking external support for financial and advisory
Others refer to behaviours such as gathering resources and networking (Tornikoski &
Newbert 2007). However, the range of behaviours identified is not unanimously
agreed, and scholars believe that the research has not sufficiently addressed the nature
of different entrepreneurial behavioural activities (Bird, Schjoedt & Baum 2012). Many
studies have restricted them to activities in starting a venture or exhibiting the intention
of starting one. In recent times, Luthans and Ibrayeva (2006) have tried to understand
the specific behaviours of practicing entrepreneurs i.e., what they actually do. They
have identified the following activities: planning, controlling, internal communication,
human resources management, work-related tasks, customer service, socialising,
politicking and on-job personal time. Since their study was done in the transition
economies of Kazakhastan and Kyrgyzstan, they can be easily applied to an emerging
economy as they share similar characteristics; therefore, they were used in my study.
However, it must be acknowledged that social psychologists suggest that the behaviours
are constrained by contextual factors. Past research has shown that an individual’s
behaviour can be impacted by information overload in many ways, including omission,
where the individual may fail to attend to all information, and error, where the
information may be assimilated incorrectly (Vickery & Vickery 1987). As mentioned
before, information overload makes individuals frequently suffer from cognitive strain
and stress (Schick, Gordon & Haka 1990) and results in their inability to make timely
decisions (Bawden 2001; Speier, Valacich & Vessey 1999). This can have a negative
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impact on the behavioural activities of entrepreneurs. For example, Klausegger,
Sinkovics and Zou (2007) pointed out that managers collected too much information
which they were unable to use efficiently, and this negatively impacted on their task
accomplishment. It follows that information overload can have a negative impact on the
behavioural activities of entrepreneurs. Hence, the following set of hypotheses is
proposed:
H5a-5h- Entrepreneurial information overload and entrepreneurial behavioural activities
Hypothesis 5a: Entrepreneurial information overload is negatively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 5b: Entrepreneurial information overload is negatively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 5c: Entrepreneurial information overload is negatively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 5d: Entrepreneurial information overload is negatively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 5e: Entrepreneurial information overload is negatively associated with the work-related tasks dimension of entrepreneurial behavioural activities.
Hypothesis 5f: Entrepreneurial information overload is negatively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 5g: Entrepreneurial information overload is negatively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 5h: Entrepreneurial information overload is negatively associated with the politicking dimension of entrepreneurial behavioural activities.
4.5 Personality characteristics and entrepreneurial behavioural activities
Research indicates that entrepreneurs’ personality characteristics play a substantial role
2000). Personality traits in fact “provide the reasons for the person’s behaviour” (Mount
et al. 2005, p.448). These personality characteristics or traits are not merely the
psychological property of an individual, but something that manifests through behaviour
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(McCarthy 2000). Accordingly, these characteristics have been conceptualised as
having the propensity to act, and therefore predict entrepreneurial behaviour (Rauch &
Frese 2000). The literature reveals the existence of several personality characteristics as
being important to entrepreneurship, but only three of them have been identified as ‘the
big three’ (Chell 2008). These three personality characteristics are: need for
achievement, internal locus of control and risk-taking propensity. Further, Rauch and
Frese (2007a) point out that specific personality characteristics that match work
characteristics are more likely to predict entrepreneurial behaviour. Since ‘the big three’
personality characteristics were found to be important for entrepreneurship, the effect of
these characteristics on entrepreneurial behavioural activities is examined in this study.
In the past, what was construed as being entrepreneurial behavioural activities has been
largely confined to activities that engage in the intention to start a venture or actually
starting it. However, this limited understanding of entrepreneurial behaviour is not
practical, as entrepreneurship was seen to be an evolving process rather than a state of
being (Bygrave 1989). Few scholars have focused on the behavioural activities of
practicing entrepreneurs (Luthans, Envick & Anderson 1995; Luthans & Ibrayeva
2006). The entrepreneurial behavioural activities identified in these studies were related
to planning, controlling, internal communication, human resources management, work-
related tasks, customer service, socialising and politicking. I therefore examine the link
between ‘the big three’ personality characteristics and entrepreneurial behavioural
activities in my study.
4.5.1 Personality characteristic of need for achievement and entrepreneurial behavioural activities
As seen earlier, the need for achievement denotes an individual’s drive to excel in
accomplishing a goal (McClelland 1961). By achieving their targets, these individuals
feel a sense of accomplishment and satisfaction. This personality characteristic is found
to influence an individual’s work behaviour (Lumpkin & Erdogan 2000), and raise
his/her expectation of doing something better or faster than others, or even their own
personal accomplishments previously (Hansemark 2003). In the entrepreneurship field,
individuals with a higher need for achievement are more likely to engage in activities
that help them in succeeding in their entrepreneurial efforts (Collins, Hanges & Locke
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2004; McClelland 1965; Tang & Tang 2007). Begley and Boyd (1987) have found a
positive relationship between need for achievement and venture growth rates.
Similarly, Johnson (1990) found that the need for achievement can predict firm
founding, while Collins, Locke and Hanges (2000) showed it to be an effective tool to
differentiate between successful and unsuccessful business founders. Shane, Locke and
Collins (2003) endorse the importance of the need for achievement characteristic in
explaining entrepreneurial activities. In Utsch and Rauch’s (2000) study, achievement
orientation was examined for its effect on venture performance through two mediating
variables, namely innovative and initiative behaviours; the innovative behaviour was
found to have a significant impact. Similarly, Korunka et al. (2003) examined a
complex configuration that included not only entrepreneurs’ personality, but also other
constructs such as resources, environment, and organisational activities, whose effect
was found to exist moderately. Clearly, personality characteristics have an impact on the
entrepreneurs’ observable behavioural activities at varying levels. In my study, I have
included eight specific behavioural activities of entrepreneurs that were identified
recently (Luthans & Ibrayeva 2006), and I propose to examine how they are influenced
by the personality characteristic of need for achievement. Accordingly, the following set
of hypotheses is presented:
H6a-H6h - Need for achievement and entrepreneurial behavioural activities:
Hypothesis 6a: The personality characteristic of need for achievement is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 6b: The personality characteristic of need for achievement is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 6c: The personality characteristic of need for achievement is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 6d: The personality characteristic of need for achievement is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
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Hypothesis 6e: The personality characteristic of need for achievement is positively associated with the work-related tasks dimension of entrepreneurial behavioural activities.
Hypothesis 6f: The personality characteristic of need for achievement is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 6g: The personality characteristic of need for achievement is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 6h: The personality characteristic of need for achievement is positively associated with the politicking dimension of entrepreneurial behavioural activities.
4.5.2 Personality characteristic of internal locus of control and entrepreneurial behavioural activities
Another personality characteristic of entrepreneurs that can influence entrepreneurial
behavioural activities is internal locus of control. This characteristic is pertinent to
entrepreneurs who are self-motivated individuals who take the initiative and engage in
entrepreneurial efforts. They also take responsibility for their outcomes, rather than
depending on others. Prior research has found that individuals with a high degree of
internal locus of control believe that they determine the future outcomes of their actions
(Cromie & Johns 1983; Krueger 2009). Littunen (2000) points out that internal locus of
control is positively associated with entrepreneurial behaviour. Internal locus of control
is found to motivate entrepreneurial behaviour (Mueller & Thomas 2001). Individuals
with high internal locus of control may be frustrated if working for others, and set up
their own ventures (Bridge, O’Neill & Cromie 2003). Recently, Caliendo, Fossen and
Kritikos (2014) found that individuals who scored highly on internal locus of control
had a high probability of starting a business venture.
On the other hand, entrepreneurship does not stop with only intending to start, or
actually establishing, a business venture. Instead, they may be required to stabilise and
put the business on a growth path. Muller, Volery and Von Siemens (2012) observed
entrepreneurs of firms in the growth phase and found them, as practicing entrepreneurs,
to possess different types of behaviours. These are largely similar to the eight
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behaviours of entrepreneurs found by Luthans and Ibrayeva (2006) in transition
economies. I therefore expect the internal locus of control to impact on entrepreneurial
behavioural activities. Accordingly, the following set of hypotheses is proposed:
H7a-H7h - Internal locus of control and entrepreneurial behavioural activities:
Hypothesis 7a: The personality characteristic of locus of control is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 7b: The personality characteristic of locus of control is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 7c: The personality characteristic of locus of control is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 7d: The personality characteristic of locus of control is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 7e: The personality characteristics of locus of control is positively associated with the work-related tasks dimension of entrepreneurial behavioural activities.
Hypothesis 7f: The personality characteristic of locus of control is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 7g: The personality characteristic of locus of control is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 7h: The personality characteristic of locus of control is positively associated with the politicking dimension of entrepreneurial behavioural activities.
4.5.3 Personality characteristic of risk-taking propensity and entrepreneurial behavioural activities
The risk-taking characteristic was found to be the distinguishing characteristic of
entrepreneurs which set them apart from non-entrepreneurs (Begley & Boyd 1987;
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Carland, Carland & Stewart 1999; Palich & Bagby 1995). It is viewed as being inherent
in every decision that entrepreneurs take, as the outcome of these decisions is
unpredictable (Caliendo Fossen & Kritikos 2014). Entrepreneurial activities do have
inherent risks associated with them, so only those individuals with a higher risk-taking
propensity will engage in these activities, while those with a low risk-taking propensity
will most likely work for others (Carland III et al. 1995; Stewart et al. 1999). However,
in other studies, risk-taking could not distinguish entrepreneurs from non-entrepreneurs
(Brockhaus 1980b; Carland III et al. 1995). Miner and Raju (2004) suggested that
entrepreneurs are actually risk-avoidant.
Otherwise, several studies which examine the impact of the risk-taking propensity focus
on its influence on an individual’s decision to become an entrepreneur, and very few
studies explore risk taking’s impact after the commitment to start a business has been
made (McCarthy 2000). Therefore, it is necessary to examine the entrepreneurs’ risk-
taking propensity across a venture’s life cycle, i.e., to go beyond the stage of starting a
business (Stewart & Roth 2001; Baron & Markman 2005). This will allow for
avoidance of survivor bias, if any. To this purpose, my study seeks to understand how a
risk-taking propensity is related to observable behavioural activities of entrepreneurs,
something which has been relatively under-researched (Bird, Schjoedt & Baum 2012).
Mueller, Volery and Von Siemens (2012) presented a taxonomy of entrepreneurs’
behaviours as a venture is established and grows. Luthans and Ibrayeva (2006)
identified eight entrepreneurial behavioural activities in transition economies. It is
therefore important to understand how the risk-taking propensity is related to the
entrepreneurial behavioural activities of practicing entrepreneurs. I propose a positive
relationship between them. Accordingly, the following set of hypotheses is presented:
H8a-H8h – Risk-taking propensity and entrepreneurial behavioural activities
Hypothesis 8a: The personality characteristic of risk-taking propensity is positively associated with the planning capability dimension of entrepreneurial behavioural activities.
Hypothesis 8b: The personality characteristic of risk-taking propensity is positively associated with the controlling dimension of entrepreneurial behavioural activities.
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Hypothesis 8c: The personality characteristic of risk-taking propensity is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 8d: The personality characteristic of risk-taking propensity is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 8e: The personality characteristic of risk-taking propensity is positively associated with the work-related tasks dimension of entrepreneurial behavioural activities.
Hypothesis 8f: The personality characteristic of risk-taking propensity is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 8g: The personality characteristic of risk-taking propensity is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 8h: The personality characteristic of risk-taking propensity is positively associated with the politicking capability dimension of entrepreneurial behavioural activities.
4.6 Entrepreneurial self-efficacy and entrepreneurial behavioural activities
In general, self-efficacy beliefs have been touted as being a very important variable in
understanding the behaviour of an individual because they cause individuals to reflect
on their capabilities and subsequently regulate their choices and efforts (Bandura 1982).
If the individual perceives a particular behaviour to be beyond his/her ability, then the
individual will not act in that direction, even if there is a perception of demand for such
behaviour (Boyd & Vozikis 1994). In fact, Shane, Locke and Collins (2003) have
singled out self-efficacy as being the best predictor of an individual’s performance in a
task, and they assert that individuals with high self-efficacy will “exert more effort for a
greater length of time, persist through setbacks, set and accept higher goals and develop
better plans and strategies for the task” (2003, p. 267). It is theorised that a sense of
entrepreneurial self-efficacy is essential to increase the probability of entrepreneurial
actions (Boyd & Vozikis 1994). They also suggest identifying key efficacy perceptions
in determining future performance (i.e. behaviour) levels of individuals. As Bridge,
O’Neill and Cromie (2003, p.90) assert, ‘perceived self-efficacy leads to intentions
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which ultimately lead to behaviour’, but behaviour, in turn, could influence self-
efficacy.
As discussed earlier in this chapter, this study is examining the entrepreneurial
behavioural activities of practicing entrepreneurs as identified by the studies done by
Luthans, Envick and Anderson (1995) and Luthans and Ibrayeva (2006). The
behavioural activities examined are activities in the areas of planning, controlling,
internal communication, work-related tasks, human resources management, customer
service, socialising and politicking. Thus it is proposed that there is positive association
between each specific entrepreneurial self-efficacy dimension and each dimension of
the entrepreneurial behavioural activities.
4.6.1 Dimensions of entrepreneurial self-efficacy and the planning dimension of entrepreneurial behavioural activities
While entrepreneurial self-efficacy was examined earlier in different studies (e.g., Chen,
and coping with unexpected challenges. However, none of these dimensions was
directly tested empirically with entrepreneurial behavioural activities, which provided
me with an opportunity to examine their relationship in this study. Studies have
examined the importance of early business planning and advocated its importance in
helping entrepreneurs achieve their goals and also make quick decisions (Delmar &
Shane, 2003). Therefore, practicing entrepreneurs are expected to continue planning
even after the venture is established and growing. Luthans and Ibrayeva (2006)
observed that entrepreneurs spent a good amount of their time in planning activities.
Hence, I propose the following set of hypotheses that shows a positive relationship
between different dimensions of entrepreneurial self-efficacy and the planning
dimension of entrepreneurial behavioural activities:
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Hypothesis 9a: The entrepreneurial self-efficacy dimension of searching is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 10a: The entrepreneurial self-efficacy dimension of planning is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 11a: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 12a: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 13a: The entrepreneurial self-efficacy dimension of implementing finance-related is positively associated with the planning dimension of entrepreneurial behavioural activities.
Hypothesis 14a: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the planning dimension of entrepreneurial behavioural activities.
4.6.2 Dimensions of entrepreneurial self-efficacy and the controlling dimension of entrepreneurial behavioural activities
The entrepreneurial self-efficacy dimension used in my study consists of six
implementing finance-related tasks, and coping with challenges. Though these
dimensions were drawn from the studies of McGee et al. (2009) and DeNoble, Jung and
Ehrlich (1999), they were not empirically tested against the actual behavioural activities
undertaken by entrepreneurs. In particular, we know that entrepreneurial self-efficacy
helps a person’s belief in their ability to successfully launch a venture. But such
activities need proper control of venture establishment and growth. These include
activities such as ensuring that work is done as per the plan, monitoring financial
performance, and inspecting equipment (Luthans & Ibrayeva 2006). Hence, I propose
the following set of hypotheses that shows a positive relationship between different
dimensions of entrepreneurial self-efficacy and the controlling dimension of
entrepreneurial behavioural activities:
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Hypothesis 9b: The entrepreneurial self-efficacy dimension of searching is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 10b: The entrepreneurial self-efficacy dimension of planning is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 11b: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 12b: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 13b: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the controlling dimension of entrepreneurial behavioural activities.
Hypothesis 14b: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the controlling dimension of entrepreneurial behavioural activities.
4.6.3 Dimensions of entrepreneurial self-efficacy and the internal communication dimension of entrepreneurial behavioural activities
Prior empirical studies involving the entrepreneurial self-efficacy construct had only a
single score as a measure of the construct. However, my study has six dimensions
within entrepreneurial self-efficacy; these are searching, planning, marshalling,
implementing people-related tasks, implementing finance-related tasks, and coping with
unexpected challenges, which were adapted from DeNoble, Jung and Ehrlich (1999)
and McGee et al. (2009). These dimensions of entrepreneurial self-efficacy show an
individual’s belief in their ability to perform six different roles. On the other hand, an
important responsibility of entrepreneurs is internal communication. Entrepreneurship
researchers (Bird 1989; Baum, Locke & Kirkpatrick 1998) have underscored the
importance of communicating the entrepreneur’s vision to the management team and as
regards the venture as a whole. Further, entrepreneurs are required to regularly
communicate with their teams, suppliers, customers, employees and so on, in order to
realise venture goals and objectives. Therefore, having confidence in their
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entrepreneurial ability is expected to have a positive impact on the entrepreneurs’
communication responsibility towards the venture. Accordingly, I propose the following
set of hypotheses showing a positive link between all the six dimensions of
entrepreneurial self-efficacy and the internal communication dimension of
entrepreneurial behavioural activities:
Hypothesis 9c: The entrepreneurial self-efficacy dimension of searching is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 10c: The entrepreneurial self-efficacy dimension of planning is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 11c: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 12c: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 13c: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
Hypothesis 14c: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the internal communication dimension of entrepreneurial behavioural activities.
4.6.4 Dimensions of entrepreneurial self-efficacy and the human resources dimension of entrepreneurial behavioural activities
According to Chen, Greene and Crick (1998), entrepreneurial self-efficacy refers to an
individual’s confidence in his/her ability to successfully perform entrepreneurial roles
and tasks. They provide empirical evidence as to its positive relationship with
entrepreneurial intentions. Likewise, DeNoble, Jung and Ehrlich (1999) also found
similar evidence. Compared to the studies that took a unitary view of self-efficacy
and coping with unexpected challenges. In this context, Sirmon and Hitt (2003) strongly
believe that human capital is a very important resource for a business venture, and
suggest that this resource be managed well to create value for the venture. Luthans and
Ibrayeva (2006) observe that practicing entrepreneurs undertake various human
resource activities like staffing, training and motivating their employees. It is expected
that confidence exhibited by individual entrepreneurs, as expressed by their level of
entrepreneurial self-efficacy, will have a positive impact on how they use human
resources. However, we do not know if the level of impact by these different
dimensions of entrepreneurial self-efficacy on the human resources dimension of
entrepreneurs’ behaviour is uniform or varies. To examine these relations further, I
propose the following set of hypotheses:
Hypothesis 9d: The entrepreneurial self-efficacy dimension of searching is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 10d: The entrepreneurial self-efficacy dimension of planning is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 11d: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 12d: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 13d: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
Hypothesis 14d: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the human resources management dimension of entrepreneurial behavioural activities.
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4.6.5 Dimensions of entrepreneurial self-efficacy and the work-related task dimension of entrepreneurial behavioural activities
As seen earlier, the dimensions of entrepreneurial self-efficacy indicate the level of
confidence by entrepreneurs in their ability to undertake specific tasks and roles related
to entrepreneurship. In fact, entrepreneurial self-efficacy scales used by Chen, Greene
and Crick (1998) identify 22 specific tasks and roles. Further, the confidence in
performing these tasks was used to differentiate between entrepreneurs and non-
entrepreneurs. Therefore, entrepreneurial self-efficacy was used as an important
antecedent to behaviour or actions that an entrepreneur will undertake (Ajzen 2002). At
the same time, studies have identified underlying multiple dimensions within the
construct of entrepreneurial self-efficacy (eg. DeNoble, Jung & Ehrlich 1999; McGee et
al. 2009). But Luthans and Ibrayeva (2006) have identified that entrepreneurs undertake
work-related operational activities such as filing invoices, organising the work area and
pricing the products. These activities are also very important for the business. In my
study, I have used six different dimensions of entrepreneurial self-efficacy and expect
them to have a positive impact on work-related dimensions of entrepreneurial
behavioural activities. Therefore, to examine these relationships empirically, I propose
the following set of hypotheses:
Hypothesis 9e: The entrepreneurial self-efficacy dimension of searching is positively associated with the work-related task dimension of entrepreneurial behavioural activities.
Hypothesis 10e: The entrepreneurial self-efficacy dimension of planning is positively associated with the work-related task dimension of entrepreneurial behavioural activities.
Hypothesis 11e: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the work-related task dimension of entrepreneurial behavioural activities.
Hypothesis 12e: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the work-related task dimension of entrepreneurial behavioural activities.
Hypothesis 13e: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the work-related task dimension of entrepreneurial behavioural activities.
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Hypothesis 14e: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the work-related task dimension of entrepreneurial behavioural activities.
4.6.6 Dimensions of entrepreneurial self-efficacy and the customer service dimension of entrepreneurial behavioural activities
Boyd and Vozikis (1994) proposed that self-efficacy was a critical antecedent of
entrepreneurial intentions and actions. Chen, Greene and Crick (1998) provided
empirical evidence to support the assertion that entrepreneurial self-efficacy is
positively related to entrepreneurs’ intentions. As mentioned earlier, scholars such as
DeNoble, Jung and Ehrlich (1999) and McGee et al. (2009) have identified different
dimensions within the construct of entrepreneurial self-efficacy. In my study, the
construct of entrepreneurial self-efficacy has six dimensions, and I expect them to have
a positive impact on the customer service dimension of entrepreneurial behavioural
activities that was identified by Luthans and Ibrayeva (2006). In an earlier study,
Thompson (1999) argued that the success of any business is dependent on the ability of
the entrepreneur or entrepreneurial manager to find a valuable strategic fit where the
organisation’s resources and capabilities are utilised well to satisfy the expectations of
key stakeholders, including customers. Accordingly, I propose the following set of
hypotheses:
Hypothesis 9f: The entrepreneurial self-efficacy dimension of searching is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 10f: The entrepreneurial self-efficacy dimension of planning is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 11f: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 12f: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the customer service dimension of entrepreneurial behavioural activities.
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Hypothesis 13f: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the customer service dimension of entrepreneurial behavioural activities.
Hypothesis 14f: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the customer service dimension of entrepreneurial behavioural activities.
4.6.7 Dimensions of entrepreneurial self-efficacy and the socialising dimension of entrepreneurial behavioural activities
The defining feature of self-efficacy is an individual’s belief in his/her ability to
perform. In the context of entrepreneurial self-efficacy, this belief translates into
confidence to perform tasks relevant to entrepreneurship. A critical component for
entrepreneurship has been identified as networking and socialising (Manolova et al.
2007; Watson 2007). By networking and socialising, entrepreneurs gain access to
information, new contacts for business, and emotional support, all of which support
their entrepreneurial efforts. These socialising behaviours, in turn, add to the
entrepreneur’s self-efficacy. Therefore, it is reasonable to expect a positive relationship
between entrepreneurial self-efficacy and the socialising dimension of an entrepreneur’s
behaviour identified by Luthans and Ibrayeva (2006). However, such relationships were
not empirically tested in a situation where the entrepreneurial self-efficacy construct
consisted of multiple dimensions. Hence the following set of hypotheses is proposed:
Hypothesis 9g: The entrepreneurial self-efficacy dimension of searching is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 10g: The entrepreneurial self-efficacy dimension of planning is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 11g: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 12g: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the socialising dimension of entrepreneurial behavioural activities.
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Hypothesis 13g: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the socialising dimension of entrepreneurial behavioural activities.
Hypothesis 14g: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the socialising dimension of entrepreneurial behavioural activities.
4.6.8 Dimensions of entrepreneurial self-efficacy and the politicking dimension of entrepreneurial behavioural activities
Several studies have indicated the importance of politicking and lobbying for business
Paris 2000). In developing economies, where institutions are weak, it is powerful
individuals that influence decision making in all areas of the society (see Kuncoro
2006). Therefore, entrepreneurs are expected to lobby politicians and other individuals
of influence to gain support for their entrepreneurial ventures and activities. In order to
undertake the activity of politicking, entrepreneurs need self-efficacy, a belief that they
can undertake this activity of politicking with confidence. Therefore, entrepreneurial
self-efficacy is important for entrepreneurs as they interact with politicians and other
influential people who wield enormous social and political power. Accordingly, I
propose the following set of hypotheses:
Hypothesis 9h: The entrepreneurial self-efficacy dimension of searching is positively associated with the politicking dimension of entrepreneurial behavioural activities.
Hypothesis 10h: The entrepreneurial self-efficacy dimension of planning is positively associated with the politicking dimension of entrepreneurial behavioural activities.
Hypothesis 11h: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the politicking dimension of entrepreneurial behavioural activities.
Hypothesis 12h: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the politicking dimension of entrepreneurial behavioural activities.
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Hypothesis 13h: The entrepreneurial self-efficacy dimension of implementing finance-related capability is positively associated with the politicking dimension of entrepreneurial behavioural activities.
Hypothesis 14h: The entrepreneurial self-efficacy dimension of coping with unexpected challenges is positively associated with the politicking dimension of entrepreneurial behavioural activities.
4.7 Chapter summary
The chapter puts forward a conceptual framework based on the variables identified in
the literature review. My conceptual framework proposes several associations: between
personality characteristics and various dimensions of entrepreneurial self-efficacy;
between personality characteristics and entrepreneurial behavioural activities; and
between entrepreneurial self-efficacy and entrepreneurial behavioural activities. It also
proposes that information overload will have an adverse impact on both entrepreneurial
self-efficacy and entrepreneurial behavioural activities. Based on the theory underlying
these relations, a number of hypotheses have been developed for empirical testing. The
methodology used to test these hypotheses is discussed in Chapter 5.
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CHAPTER 5
RESEARCH METHODOLOGY
In this chapter, the methodology used to test the proposed model and hypothesis
presented in Chapter Four is discussed. Specifically, this chapter covers the research
strategy and the methodology used in addressing the research problem. Further, this
chapter includes various aspects such as the operationalisation of each variable of the
proposed model, the rationale behind this, the development of the survey instrument,
validity and reliability analysis, sample selection, the data collection method, and a
description of the statistical analysis employed in this study.
5.1 Research approach and strategy
The research approach used will influence the nature and conduct of any research
undertaken as well as the interpretation of existing knowledge in the literature (Baker &
Foy 2008). This study employs a positivist approach using the deductive process of
theory testing. The decision to use this approach is because this research begins with a
theoretical perspective that has been drawn together from the review of extensive extant
literature. The concepts of this theoretical model have been operationalised to gain an
understanding of the relationships existing between the variables. The data that help us
to observe these concepts in the empirical world are sought using surveys from the field.
5.2 Measurement / operationalisation of variables
Gill, Johnson and Clark (2010, p. 50) define operationalisation “as the creation of rules
for using indicators of abstract concepts which tell us when instances of the concept
have empirically occurred”. The variables used in the study are abstract concepts
gathered from reviewing the literature. Gill, Johnson and Clark (2010) state that to
examine these variables, they have to be overtly linked to something that is observable
in such a way that the variation can be measured. In other words, the variables have to
be operationalised. Accordingly, the variables used in the study have been
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operationalised using observable indicators drawn from past studies. The variables
have been operationalised and tested for reliability and validity by various researchers in
earlier empirical studies. The development of each of the variables used in the study is
detailed below.
5.2.1 Personality characteristics
While many personality characteristics were examined in studies on entrepreneurship,
three personality traits have been widely discussed in the literature and have shown a
high level of validity. They are: (i) need for achievement, (ii) internal locus of control
and (iii) risk-taking propensity (Schaper, Volery, Weber & Lewis 2011, Gartner 1985,
Brockhaus 1982). In fact, they are termed ‘the big three’ (Chell 2008). This study, too,
examines these three personality traits as they have not been tested much in the context
of emerging economies.
5.2.1.1 Need for achievement
A popularly used scale was developed by Cassidy and Lynn (1989); it measures
achievement motivation using seven dimensions: the work ethic, the pursuit of
excellence, status aspiration, competitiveness, acquisitiveness for money and material
wealth, mastery, and dominance. Some scholars (Ward 1997; Hart, Stasson, Fulcher &
Mahoney 2008) have questioned the validity of this seven-factor scale on the grounds
that their corresponding factors explain less than half of their variance. Using the
approach taken by Cassidy and Lynn (1989), Littunen (2000) choose four-dimension
scales to test achievement motivation; these dimensions are: work ethic, pursuit of
excellence, mastery and dominance. Another study by Lee and Tsang (2001) used
measures prescribed by the Edwards (1959) EPPS manual. For my study, questions
were chosen from the Lee and Tsang (2001) study. The Alpha value is 0.81, and the
factor loadings range from 0.76-0.86 for the questions. The three questions chosen from
Lee and Tsang’s study were considered to be representative to test the need for
achievement.
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5.2.1.2 Internal locus of control
The construct of internal locus of control contributed by Rotter’s social learning theory
has been frequently used in entrepreneurship studies. It measures an individual’s belief
in his/her ability to control his/her life. Most studies using this construct use the Rotter’s
Internal–External scale (I-E scale). The I-E scale consists of internal and external loci
of control. The I-E scale has been proposed as a uni-dimensional scale, and this has
been mentioned as a fundamental weakness, since the construct of locus of control is
multi-dimensional (Furnham 1986). Therefore, some entrepreneurship scholars have
objected to this scale on the ground that not all the dimensions assessed by Rotter’s I-E
scale are equally plausible predictors of a specific setting of a new venture creation
1991). Later on, other authors (e.g., Levenson 1981) used constructs with three
dimensions, one being internal attributing and the second, external locus of control, was
further divided into chance attributing, and powerful others. Littunen (2000) further
adopted these dimensions to capture an entrepreneur’s locus of control.
The current study focuses on ‘internal locus of control’ only. This is because of two
reasons: i) a majority of the entrepreneurship studies have found internal locus of
control to be a more valid predictor than external control for entrepreneurial behaviour
(Littunen 2000), and ii) in the Indian context of a caste-dominated social structure (see
Misra 2000), internal locus of control is expected to help overcome the mitigating
factors of a caste-based social system. To operationalise this variable, I have adapted
measures of internal locus of control from the study conducted by Littunen (2000).
5.2.1.3 Risk-taking propensity
The risk-taking propensity construct measures the entrepreneur’s risk perception and
risk propensity. In a significant study, Covin and Slevin (1989, p. 86; 1998, p.234)
measured top management’s risk-taking propensity, using three questions examining:
“i) proclivity for high risk projects with chances of very high returns or low risk projects with normal and certain rates of returns, ii) whether the top managers find it is best to explore the environment via cautious, incremental behaviour or
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by bold, wide-ranging acts which they believe are necessary to achieve the firm’s objectives, and iii) whether the manager adopts a cautious posture to minimise the probability of making costly decisions or a bold, aggressive posture in order to maximise the probability of exploiting potential opportunities”.
Building on Covin and Slevin’s measures, Naldi et al. (2007) framed three questions
covering three other items: (i) high risk projects, (ii) fearless and powerful measures and
(iii) fearless and aggressive position. Risk taking was examined in the context of family
firms and non-family firms. The alpha value for risk taking in family firms was 0.83 and
in non-family firms it was 0.76. Covin and Slevin’s (1989) study focuses more on a
respondent’s rating of the risk-taking propensity of his or her top managers, rather than
rating their proclivity to take or avoid personal risks. This study focuses on the
entrepreneur’s risk-taking propensity and its impact on the entrepreneur’s behaviour.
Therefore, only two questions from Naldi et al.’s (2007) study were taken. These
questions were further reworded to suit the current study.
Wagener, Gorgievski and Rijsdijk (2010) adopted three questions from Van den Brink,
et al. (2004). The questions have an alpha value of 0.80. For this study, only two
questions were used in the study. The third question (‘I am prepared to invest much of
my own capital to take a chance’) was not used because this study focuses on practising
entrepreneurs who are also owner-managers, rather than on those who intend to be
entrepreneurs (or potential entrepreneurs). This item was not relevant to our sample
respondents as they have already invested and are practicing entrepreneurs.
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Table 5.1 Operationalisation of entrepreneur’s personality characteristics Construct (Source)
Items
Need for achievement (Lee & Tsang 2001)
1. I will not be satisfied unless I have achieved the desired level of results.
2. Even though people tell me ‘that it cannot be done’, I will persist.
3. I look upon my work as simply a way to chieve my goals.
Internal locus of control
(Littunen 2000)
4. I am usually able to protect my personal interest. 5. My life is determined by my own actions. 6. I can pretty much determine what will happen in my life. 7. When I make plans, I am almost certain to make them
work.
Risk-taking propensity
(Naldi et al. 2007): Items 8-9.
(Wagener, Gorgievski
& Rijsdijk 2010): Items 10-11.
8. I can take fearless decisions to maximise the chance of exploiting all opportunities.
9. I regularly take calculated risks in order to obtain a potential advantage
10. If I get a chance, I take risks, even if the consequences
may be potentially unfavourable. 11. I take fearless decisions to achieve my venture
objectives, even in a turbulent business environment
Table 5.1 shows the dimensions used to measure personality characteristics of
entrepreneurs. Based on the requirements of this study, the personality scale created
consists of 11-items to measure the three important personality dimensions of
entrepreneurs: 1) need for achievement, 2) internal locus of control, and 3) risk-taking
propensity. A 7-point Likert scale ranging from 1= “Not at all” to 7 = “extremely well”
is used to examine the extent to which the statements best described the entrepreneur.
5.2.2 Entrepreneurial self-efficacy (ESE)
The concept of self-efficacy, which has its roots in social cognitive theory as postulated
by Bandura (1977), has been applied to entrepreneurship by various researchers (e.g.,
Chen, Greene & Crick 1998). The construct of ESE should capture “the degree to
which individuals believe that they are capable of performing the tasks associated with
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new-venture management” (Forbes 2005). To operationalise entrepreneurial self-
efficacy, a careful examination of existing literature and scales was undertaken.
While self-efficacy has been applied broadly across various research domains, Bandura
(1997, p.6) cautions researchers that “self-efficacy beliefs should be measured in terms
of particularised judgments of capability that may vary across realms of activity,
different levels of task demands within a given activity domain, and under different
situational circumstances”. He advises researchers to examine self-efficacy in specific
contexts and research domains. This caution has gone unheeded in different studies
where self-efficacy assessments have examined general attitudes about capabilities
rather than being tailored to specific activity domains as suggested by Bandura (Pajares
1997).
Unfortunately, some studies in entrepreneurship apply and measure general self-efficacy
in the area of entrepreneurship (e.g. see Baum and Locke 2004; Markman Baron &
Balkin 2005), although the concept of entrepreneurship has been recognised as a multi-
Doing so does not allow for higher predictive power. In other words, it was difficult to
identify the specific areas, within the construct of self-efficacy, which were influenced
or which impacted on entrepreneurship as the case may be. To remedy this issue, the
scale developed for my study took into account suggestions made by researchers in
three ways: a) to use ESE scales that measured specific areas of the activity domain; b)
to use a multi-dimensional scale; and c) not to create one composite score for the whole
ESE construct.
To operationalise the entrepreneurial self-efficacy construct, it was first important to
identify the tasks that are associated with entrepreneurship. My study follows McGee et
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al.’s (2009) framework. Responding to the call of Forbes (2005) and Kolvereid and
Isaksen (2006) for refining the ESE construct, McGee and his associates (2009)
examined the then existing scales and took the shortcomings and suggestions into
consideration to develop their own five-factor scale that included dimensions of: (i)
searching, (ii) planning, (iii) marshalling, (iv) implementing-people, and (v)
implementing-finance. McGee et al.’s (2009) study focused mainly on nascent
entrepreneurs, that is, those who have never owned a business and who did not currently
own a business, but who, however, were actively involved in attempting to start a new
business (Reynolds, 1999). The Alpha values for each of the constructs were: searching
(0.84); planning (0.84); marshalling (0.80); implementing people (0.91); and
implementing-finance (0.84). Since the focus of this study is to examine practicing
owner-managers, another factor was added – i.e., coping with unexpected challenges, as
this was seen as being important in predicting entrepreneurial behaviour (see DeNoble,
Jung & Ehrlich 1999). The factor loading for the three questions adopted from DeNoble
et al. 1999) were 0.67, 0.79 and 0.78.
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Table: 5.2 Operationalisation of entrepreneurial self-efficacy
Construct (Source)
Item Measures
Searching (McGee et al. 2009)
1. Brainstroming a new idea for a product or service 2. Identifying the need for a new product or service 3. Designing a product or service that will satisfy customers
needs and wants Planning (McGee et al. 2009)
4. Estimating customer demand for a new product or service 5. Determining a competitive price for a new product or
service 6. Designing an effective marketing/advertising campaign for
a new product or service Marshalling (McGee et al. 2009)
7. Getting others to support your vision and plan for the new business
8. Networking with others-i.e., making contact with and exchanging information
9. Clearly and concisely explaining your business idea in everyday terms to relevant stakeholders/parties
Implementing people (McGee et al. 2009)
10. Supervising your subordinates 11. Recruiting suitable employees 12. Delegating tasks and responsibilities to your employees 13. Dealing effectively with day-to-day problems/crises
faced by your employees 14. Inspiring, encouraging, and motivating your employees 15. Training employees
Implementing finance (McGee et al. 2009)
16. Estimating the amount of start-up funds and working capital requirement for your business
17. Organising and maintaining the financial rewards of your business
18. Managing the financial assets of your business 19. Reading and interpreting financial statements
Coping with unexpected challenges (DeNoble, Jung & Ehrlich 1999)
20. Working productively under continuous stress, pressure and conflict
21. Tolerating unexpected changes in business conditions 22. Persisting in the face of adversity
On the whole, the scale measures the level of confidence the entrepreneurs have in their
ability to undertake entrepreneurial activities (see Table 5.3). This 22-item scale
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measures the entrepreneurial self-efficacy construct that incorporates the following
2009) in three ways: a) to use behaviour activities that were observed and not just self-
reported, b) to use a multi-dimensional scale, and c) not to create one composite score
for the whole entrepreneurial behavioural activities construct.
Table 5.4 below shows the dimensions used to operationalise entrepreneurial
behavioural activities. A 7-point Likert scale is attached to these behavioural items to
test how effectively the respondent can carry out an activity. The exemplars of the
observed behaviours were converted into questions. For example, under the dimension
controlling, Luthans and Ibrayeva (2006) observed the activity “checking the work
done”. In my study, this activity was framed into “making sure the work is done as per
the plan”. Similarly, each item identified under the dimensions of planning, controlling,
and work-related tasks, was converted into activities. For internal communication, the
exemplar given was “talking with employees or a business partner”. This was divided
into two separate activities and given as “interaction with business partner/s” and
“interaction with key employees”. In human resource management, there were only
four activities mentioned in Luthans and Ibrayeva (2006). A fifth one was related to
“involvement in the selection of your employees”, and was added to the questionnaire
for this study.
For the dimension customer service, the items “explaining the product or service to
customers”, and “quoting prices to customers” were covered together under the item
“involvement in sales presentations”. For the dimension socialising, the activity “chit-
chatting about relevant social events” was not written separately since this activity is
inherent in the chosen four activities, namely “socialising with suppliers”, “socialising
with bankers”, “socialising with customers” and “socialising with other partners”.
These items do include all types of socialisation – it could include the sending or
receiving of information between the entrepreneur and the outside party with the aim of
getting to know each other and in this process their discussions could be business or
non-business related, so a separate item on chit-chatting about relevant social events
was not included.
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Table 5.3 Operationalisation of entrepreneurial behavioural activities
Construct (Source) Items
Planning (Luthans & Ibrayeva 2006)
1. Scheduling of appointments with prospective clients 2. Prioritisation of projects/activities 3. Involvement in strategy formalisation
Controlling (Luthans & Ibrayeva 2006)
4. Making sure that the work is done as per the plan 5. Monitoring of financial performance of the venture 6. Inspection of the state of the physical assets/equipment
Internal communication (Luthans & Ibrayeva 2006)
7. Interaction with your business partner/s (e.g. suppliers, distributors etc.)
8. Interaction with key employees 9. Interaction with key customers 10. Participation in venture-related meetings
HR management (Luthans & Ibrayeva 2006)
11. Involvement in the selection of your employees 12. Involvement in the training of your employees 13. Involvement in socialisation with your employees 14. Providing guidance to your employees 15. Inspiring employees to achieve higher goals
Work-related tasks (Luthans & Ibrayeva 2006)
16. Involvement in dealing with invoices 17. Involvement in pricing decisions for the key customers 18. Involvement in negotiations with your suppliers
Customer service (Luthans & Ibrayeva 2006)
19. Involvement in sales presentations (e.g. explaining the product or service to customers)
20. Involvement in the selling of your products/services 21. Handling customer complaints
Socialising (Luthans & Ibrayeva 2006)
22. Socialisation with suppliers 23. Socialisation with bankers 24. Socialisation with customers 25. Socialisation with other business partner/s
26. Calling on government officials 27. Lobbying government officials 28. Lobbying elected officials 29. Discussing political issues related to business with
business associations/professional bodies
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For the final dimension politicking, another item was included which was not in the
Luthans and Ibrayeva study (2006). This item was “lobbying with government
officials”. In India, government departments are complex, and therefore liaising with
relevant government officials becomes necessary (Elg, Schaumann & Ghauri 2012).
Therefore, my study has also included the item “lobbying with government officials”
which is different from “lobbying with elected officials”.
The scale is made up of 29 items, and is used to examine the effectiveness of the
entrepreneur in engaging in each of the activity ranges from “not well at all = 1”, to
“extremely well = 10”, where the mid-point 4 = moderately well. The response scale
also includes “NA”, which the respondent can circle if any of the behaviours is not
applicable to them.
5.2.4 Entrepreneurial information overload (EIO)
To the best of the researcher’s knowledge, information overload (IO) has not been
examined in the entrepreneurship domain. Information overload implies that the
information processing demands more of the entrepreneur’s time and capacity than is
available for the entrepreneur to process the information. This construct has been
examined and applied in disciplines such as psychology (Miller 1956), organisation
2004; Klausegger, Sinkovics & Zou 2007), accounting (Swain & Haka 2000) and
management information systems (Schultze & Vandenbosch 1998). To capture a clear
and comprehensive view of this issue and its effect on the entrepreneur, the construct
for this study was adapted from Hunter and Goebel (2008), who examined the impact of
information overload on sales performance. Their construct of information overload
consisted of questions relating to sales presentation, product information, sales
techniques and how the volume of this information overwhelmed or frustrated a
salesperson. Since Hunter and Goebel’s (2008) measures focus on the impact of IO for
salespeople, the items were reworded and made relevant for the context of the
entrepreneurship study in the form of EIO, which was operationalised in terms of 7
items. These items are shown below in table 5.4.
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Table 5.4 Operationalisation of entrepreneurial information overload
1. I feel overwhelmed due to the amount of information to be considered for making business decisions.
2. I am unable to handle the amount of information that I receive in a typical work week for making the best possible work-related decisions.
3. The amount of information that I process makes me feel stressed. 4. I feel stressed that I am losing control of the business operations because of the
volume of information that I have gathered. 5. The amount of information that I have to deal with in order to make decisions
for business growth is overwhelming. 6. The amount of available information delays my response to competitors’
actions in the market. 7. I often miss important deadlines due to the availability of an overwhelming
amount of information.
The construct of EIO measures the effects of information overload on the entrepreneur
and the activities he/she has to undertake. A sample item is “I feel overwhelmed due to
the amount of information to be considered for making business decisions”. The
response format used is a 7-point Likert scale where 1= “strongly agree” and 7=
“strongly disagree”. The EIO scale consists of 7 items designed to measure the effects
of information on the entrepreneur and the activities he/she undertakes.
5.2.5 Firm and entrepreneur related questions
There were three questions in this section. The first two questions were related to the
demographics of the firm. The third question was related to the profile of the
entrepreneur.
5.2.5.1 Firm demographics
In addition to the key variables under study, participants were asked to indicate the
number of employees in the firm at the time of filling out this survey and the industry.
The number of employees is considered a proxy for the size of the firm. The industry
categories were taken from the New Zealand Statistics website. Respondents had to
tick the appropriate box. To accommodate any business that is not in the listed
category, a separate option labelled ‘others, please specify’ was made available.
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5.2.5.2 Firm details
This question was designed to capture more firm details such as when the company was
founded, the industry/ies the firm operates in, international presence, total sales, and
assets owned.
5.2.5.3 Demographics
The next sets of questions were designed to gather the entrepreneur’s demographic
characteristics. There were a total of eleven items in this section. This included details
about the entrepreneur’s ownership of the business, experience, age and level of
education.
5.3 Developing and validating the survey instrument
Before finalising the survey instrument, I consulted academics and
practicing entrepreneurs both in New Zealand and in India. Their feedback was
gathered to confirm appropriate measures used in the questionnaire. To enhance the
validity of the survey instrument, the preliminary questionnaire was sent to the senior
academics with expertise in the field of entrepreneurship in New Zealand and in India
for their feedback on the questionnaire phraseology. They were asked to comment on
whether the questions were easy to understand (i.e. free of jargon, inappropriate
assumptions), whether the instructions were clear, whether the questions were biased or
leading and so on.
The questionnaire was finalised following advice and feedback received from the
academics and practicing entrepreneurs. On receiving feedback, two main things were
done. First, the wording of a number of ambiguous questions was changed. Second, the
question on academic qualification was designed to suit the Indian education system.
Once the questionnaire was ready, it was submitted to the Swinburne University of
Technology ethics committee. After receiving the ethics approval, it was distributed.
The questionnaire consists of parts relating to the key constructs of entrepreneurial self-
efficacy, entrepreneurial behavioural activities, entrepreneur’s personality, information
overload, and sample characteristics. Items in each part will be measured using Likert
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scales or closed-ended questions. Apart from these, demographic data about the
respondents were also included.
5.3.1 Time allocated to answer for each question
Table 5.5 shows the approximate time allocated for respondents to answer the questions
in each section. While the table indicates that the approximate time allocated to filling
the survey is 35 minutes, it would take the respondents another 10 minutes to read the
cover letter attached to the survey.
Table 5.5 Time allocated to answer for each section
Section Administration time Entrepreneurial self-efficacy 8 minutes Effectiveness of entrepreneurial behavioural activities
10 minutes
Personality characteristics 4 minutes Entrepreneurial information overload 3 minutes Firm performance 5 minutes Demographics 5 minutes Approximate time to answer the survey 35 minutes
5.4 Sample selection
The aim of this study was to empirically test the relationships among the
entrepreneurship-related variables identified in the literature review with the focus being
to generalise the results. The theoretical basis for this study, developed in Chapter 4,
shows the hypothesis to be tested. Accordingly, I sought to examine the relationships
between the entrepreneur’s personality characteristics, entrepreneurial self-efficacy, and
entrepreneurial behavioural activities in the context of entrepreneurial information
overload faced by these entrepreneurs.
For the purpose of this study, I have used the definition of an entrepreneur as proposed
by Carland et al. (1984) to guide sample selection. They describe an entrepreneur as
“an individual who establishes and manages a business for the principal purpose of
profit and growth” (p.358). The focus is on India, a large emerging market. India is a
very big country with a culturally diverse population and is home to many millions of
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entrepreneurs (Government of India 2014b). Therefore, sample selection and size are
major concerns in this study.
The sample was drawn from among practicing entrepreneurs based in India. I used a
broad definition of entrepreneurs as those who owned and also actively managed their
business ventures (Stewart & Roth 2001; Rauch & Frese 2007). The sample comprised
of owner–managers of firms in India. For this purpose, potential respondents were
selected from the list of entrepreneurs, who are members of business and social
organisations like the Confederation of Indian Industry (CII) and Rotary Clubs. Since I
am originally from India, I have personal contacts, which I used for this purpose. From
these sources, an initial sample of about 1100 owner-managers of businesses was
randomly selected.
I also had some preliminary discussions with academics of a few universities,
entrepreneurs and local business organisations in India during the months of December
2009 and January 2010 when I visited India to attend an international conference in
Delhi. In my discussions with the academics in the field of entrepreneurship, it also
became evident that my area of research had not been covered. They have a wide
network of entrepreneurs, small businesses and local business and trade organisations,
and have principally agreed to provide the necessary contacts and other support required
to facilitate the collection of data.
To get a good representation of this vast country, I ambitiously distributed the
questionnaires in all parts of India: West, East, South and North. The cities that were
included in the survey were New Delhi, Calcutta, Ahmadabad, Bangalore, Chennai, and
Coimbatore.
For this study, I have used the methods suggested by scholars to increase response rates:
a covering letter or pre-notification letter, follow-ups, reminder mails, and return
envelope with stamps (Fox, Crask & Kim 1988; Kanuk & Conrad 1975). Another
method suggested was drop-and-collect surveys (Brown 1987). The drop and collect
survey technique is a cheap and fast way of collecting responses (Brown 1987). I have
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used this approach in some cases where the entrepreneurs were busy and wanted some
time to complete their questionnaires.
A covering letter with the questionnaire was to introduce the purpose of the research
and request participation. The questionnaires were hand-delivered through friends,
business people, and academics. In some cases, hard copies were mailed to
academics/business friends in a particular city, who then helped out distributing the
surveys. Where respondents were unable to fill in the responses immediately, they
were asked whether they were happy to keep it ready for collection, or if they wished,
they could send it back by surface mail. In such cases, they were handed a postage-paid
return envelope. For the respondents who were happy to keep it ready for collection, the
people who distributed them earlier personally picked them up. So we used different
methods such as hand delivery and personal pick-up, hand delivery and postal return,
postal delivery and postal return, as well as postal delivery and personal pickup.
For the surveys where the respondents had chosen to return them by mail, the initial
distribution was followed after one month by a reminder which mailed another copy of
the questionnaire along with a general follow-up letter and a phone call. Previous
studies that used mail questionnaires reported a response rate ranging from 20%-100%
(Kanuk & Conrad 1975), and by using the drop and collect survey method, the response
rate was up to 70% (Brown 1987). Since in many cases the questionnaire was given out
by both friends and academics, there was a higher response rate. I received over 650
responses. However, after the initial screening of the questionnaires, I had only 403
usable responses. The details of the final sample selection may be seen in Table 5.6.
Table 5.6 Final response number Total number of surveys given out 1100
Returned filled out responses 650
Response rate for all returned surveys 59%
Total responses usable for data entry 403
Response rate for usable surveys 37%
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While screening the data collected, care was taken to identify any outliers. Osborne and
Overbay (2004) remind researchers of the importance to check for outliers and exclude
these since they have the potential to cause extreme scores in a data set. However, not
all outliers may be illegitimate contaminants of the data set (Barnett & Lewis 1994);
therefore I inspected each filled-in survey and used only 403 out of the 650 returned
surveys. While each survey was inspected, some of the surveys were not used because
they were insufficiently completed, as the respondents had not filled in some key
sections or in some cases they had put in multiple responses. In some cases, the
respondents appeared to not be serious about filling the form in and felt they just had to
fill it in, perhaps, because the form had been passed on to them from their friends.
Although care was taken with the wording, readability and understandability of the
questions, it seemed that some respondents had not understood what was required of
them. The surveys received from the rural areas mainly had these problems, which
could be due to low levels of education and literacy. Most of these respondents were
either not educated or educated in their local languages, while the surveys handed out
were in English only.
Outliers can also be caused due to data recording errors (Osborne & Overbay 2004). So
once the data were entered into SPSS, the records were checked a second time to ensure
that the data entry was correctly done. Care was also taken not to misrepresent any
data. Since Hayes’ (2013) procedure for the regression-based path analysis involves
boot strapping, it takes care of the potential problems that may arise due to non-normal
sample. Therefore a normality test was not required.
Table 5.7 shows a breakup of the responses received from the various cities taken in this study.
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Table 5.7 Geographical distribution of responses of the sample
Region covered
State/ Union Territory
City Number of responses
North Union Territory New Delhi 10
Punjab Chandigarh 7
West Gujarat Ahmadabad 39
Maharashtra Mumbai 2
East West Bengal Kolkata 95
South Tamil Nadu Chennai 28
Coimbatore 59
Karnataka Hosur 12
Bengaluru 127
Andhra Pradesh Hyderabad 24
Total 403
Baruch (1999) mentions the importance of reporting the response rate, since this
information helps clarify the validity of a study, and this includes taking into account
the difference between returned and usable questionnaires. He finds that in most cases,
the unusable questionnaires are due to missing data and usually the percentage of such
unusable questionnaires is negligible. However, he also acknowledges that the
difference can be significant in some cases, as seen in my current study. However, our
final sample of 403 meets the requirements of being just over 3 times the number of
items (128 items x 3 = 384 respondents) as mentioned by Cattell (1978) and Gorsuch
(1983). This sample of 403 is also above the range of 100 to 400 recommended by Hair
et al. (1995) for factor analytic studies. Further explanation regarding the sample is
given in 5.7.1.
5.5 Statistical analyses
The quantitative data collected were analysed statistically using SPSS which helps the
researcher complete calculations at the click of a button. The data collected were firstly
examined for completeness. Codes were given to each item on the questionnaire (see
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Table 5.8) and the data were defined and entered into SPSS. The next step was to
provide the logical dimensions of validity (content validity) by subjecting the data to an
exploratory factor analysis, and then its statistical dimension of reliability (construct
validity) was checked. In order to investigate our theoretical model and to examine the
relationships between variables, regression-based path analysis was used.
Table 5.8 Abbreviation used in coding
Abbreviation Definitions
PC Personality characteristics PCnAch Personality characteristic of need for achievement PCLoC Personality characteristic of internal locus of control PCRisk Personality characteristic of risk-taking propensity ESE Entrepreneurial self-efficacy Search Entrepreneurial self-efficacy dimension of searching Plg Entrepreneurial self-efficacy dimension of planning Mrsh Entrepreneurial self-efficacy dimension of marshalling Impple Entrepreneurial self-efficacy dimension of implementing people
related tasks Impfin Entrepreneurial self-efficacy dimension of implementing finance
related tasks Copch Entrepreneurial self-efficacy dimension of coping with unexpected
challenges EBA Entrepreneurial behavioural activities BhvPlg Entrepreneurial behavioural activity of planning BhvCon Entrepreneurial behavioural activity of controlling BhvCom Entrepreneurial behavioural activity of internal communication BhvHRM Entrepreneurial behavioural activity of human resources
management BhvTas Entrepreneurial behavioural activity of work-related tasks BhvSer Entrepreneurial behavioural activity of customer service BhvSoc Entrepreneurial behavioural activity of socialising BhvPol Entrepreneurial behavioural activity of politicking EIO Entrepreneurial information overload
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5.5.1 Review of sample size based on validity and reliability
An important issue of any quantitative study that affects the validity and reliability of
the instrument and determines the suitability of data for factor analyses depends on the
sample size. An adequate sample allows for findings to be generalised (Carmeli 2008).
MacCullum et al. (1999) and Fabrigar et al. (1999) argue that an adequate sample size
depends on factors such as type and number of variables and the overall structure of the
research. For instance, the properties of the variables should be taken into account when
deciding sample size (Fabrigar et al. 1999). They suggest that under good conditions
(communalities of .70 or higher), a sample of 100 might be enough, and under poor
conditions, no sample size may be sufficient to give accurate generalisation of the
population. However, the authors believe that a sample less than 400 will lead to
distorted results. Many scholars recommend that the ratio of sample size to the number
of variables should be at least three to six times the number of items, with five being the
most ideal (Cattell 1978; Gorsuch 1983). Gorsuch (1983) recommended that the sample
size should be at least 100, while others (Comrey & Lee 1992) urge researchers to
obtain a sample of at least 500 or more. A sample size in the range of 100 to 400 has
been considered as appropriate for factor analytic studies (Hair et al. 1995). In this
study, I have obtained an effective sample size of 403, and based on the
recommendations of scholars (MacCallum et al. 1999; Fabrigar et al. 1999; Hair et al.
1995), this could be considered sufficient. The indicators used to measure the
constructs have been evaluated using validity tests and reliability tests as discussed in
the next section.
5.5.1.1 Validity
Validity refers to “the degree to which a measure measures what it is supposed to be
measuring” (Webb 2000, p. 216). The validity test is done to ensure that the
variables/items have also measured the construct as was intended so that the study can
rely on the answers the respondents provide. Kidder and Judd (1986) recommend that
every survey instrument must pass face validity, either formally or informally. While
the measures used in my study were taken from previous studies that have used the
same scales, the conceptual framework of my study brings together the constructs in a
different context to be applied in a different scenario, and a face validity test was also
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done. Accordingly, in my study, the content or face validity is assessed by a group of
academics and practicing entrepreneurs in both countries, India and New Zealand.
Further, exploratory factor analysis (EFA) was used. EFA is used to identify a set of
latent constructs underlying a range of measured variables (Fabrigar et al. 1999). This
can be done without imposing a preconceived structure on the outcome (Child 1990).
Fabrigar et al. (1999) recommend the use of EFA when the communalities are low and
where there are modest numbers of measured variables per factor, since EFA produces
more accurate results. They also recommend using EFA when there is an insufficient
basis to specify an a priori model. Accordingly, in this case, EFA was carried out using
SPSS 20.0. EFA allows for determining an appropriate number of factors as well as the
pattern of factor loadings. For this purpose, the Maximum Likelihood (ML) method of
factor extraction is used. Using the ML estimation for EFA allows extracting a vast
array of goodness-of-fit information that can be further used to determine the
appropriate number of factors (Fabrigar et al. 1999).
Fabrigar et al. (1999) also suggest that factors be rotated in multidimensional space,
which will help explain the data well and arrive at a solution with the best simple
structure. In this study, oblique rotations have been used so as to estimate the
correlations among factors, thereby providing solutions with correlated factors. Oblique
rotations are shown to “provide a more accurate and realistic representation of how
constructs are likely to be related to one another” (Fabrigar et al. 1999). Gorsuch
(1983) advises using oblique over orthogonal rotation as a general approach to
achieving solutions with simple structure. The Promax method of oblique rotation
suggested by Hendrickson and White (1964) was used in my study.
5.5.1.2 Reliability
Scale reliability is concerned with the extent to which a measuring procedure
consistently yields the same results on repeated trials (i.e when the measure is used over
and over again) (Peters 2002; Webb 2000). When the survey instrument is free from
error, it will yield consistent results (Peterson 1994). One way to check this is to assess
the survey instrument by the test-retest method. This method was not practically
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feasible to use in this study. Therefore, to ensure reliability, the internal consistency test
could be used (Kerlinger 1986). Internal consistency of the scales used in the survey
may be assessed by item to total correlation and co-efficient alpha (Cronbach 1951).
The item to total correlation examines the coherencies of the responses of each item in
relation to the other items and the entire survey. For the scale to be reliable, all items
should correlate with the total. The acceptable value of an item to a total correlation
should be 0.3 and above. Where the item to total correlation is less than 0.3, this means
that the particular item in question does not correlate very well with the overall scale.
In this context, the item to correlation for each item should be examined along with the
new Cronbach’s alpha value if the item was deleted. Cronbach alpha is a popularly
used measure for internal consistency of a multi-item scale (Peterson 1994). The
threshold criteria for Cronbach alpha in most studies follow Nunnally’s (1978)
suggestion of .70 or higher for reliability. Nevertheless, Peterson (1994) observes that
Cronbach himself advocates that criteria of .50 and .30 are also acceptable. In this
study, I have applied a threshold value of .70, which meets the higher threshold
suggested by Nunnally (1978).
5.5.2 Data analysis
Initially, data are described with the aim of providing a summary picture of the sample
used. This has been done using descriptive statistics. Here, the sample has been
described in terms of their age, gender and qualifications to better understand the
entrepreneurs in the study. Regression-based path analysis was employed to investigate
the relationships between variables as proposed in the hypothesis, based on the
theoretical model discussed in Chapter 4. Here, multiple regressions are used because
this technique “allows additional factors to enter into the analysis separately so that the
effect of each can be estimated” (Sykes 1993, p. 8). Regression allows for estimating
the quantitative effect of the casual variable on the dependent variables, and the
statistical significance of the estimated relationships can also be assessed. The degree
of confidence noted enables the hypothesis to be tested.
Based on the literature review, path one examines the association between the
personality traits and entrepreneurial self-efficacy. Path two examines the association
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between entrepreneurial self-efficacy and entrepreneurial behaviour. Path three
examines the association between personality traits and entrepreneurial behaviour.
Paths four and five examine the association between entrepreneurial information
overload and dimensions of entrepreneurial self-efficacy and entrepreneurial
behavioural activities respectively.
5.6 Chapter summary
This chapter elucidates the research methods used in the current study. It explains the
sampling technique used, as well as the size and response rate. The face validity of the
survey instrument has been described. The reliability and validity analyses carried out
in the study are described. Finally, the statistical and analytical tools used in the study to
test and interpret the hypotheses are also elaborated on.
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CHAPTER 6
RESULTS AND DISCUSSION
This chapter discusses the relationships between various categories of variables relating
to entrepreneurs’ personality characteristics, entrepreneurial self-efficacy,
entrepreneurial behaviour and entrepreneurial information overload. The data were
collected by administering questionnaires between 8 February 2012 and 30 December
2012 in major cities in India. To analyse the data collected, the IBM SPSS 20.0
statistical computational package was used. The results and analysis are presented in
this chapter in four parts. First, the sample characteristics are collated and presented.
Second, a discussion on the measurement properties, which includes the reliability and
validity tests, is presented. Third, the results of regression analyses conducted for
hypothesis testing are reported. Fourth, the results have been analysed to gain insights
into the relationships between variables proposed in the conceptual framework.
6.1 Sample characteristics
As discussed in Chapter 5, a total of 650 responses was received, but only 403 were
found to be usable for data entry. The respondents were business owner-managers,
consisting of 63% of founder-owners, 29.3% of owners inheriting their business, 26%
who bought the business from others and 1.2 % who became owners of the business by
other means such as stock options. The demographic characteristics of the respondents
are presented in Table 6.1.
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Table 6 .1 Sample Demographics (n=403)
Characteristics Category Frequency Percent Gender (n=401) Male 355 88.5
Female 46 11.5 Age (n=402) 21-25 years 23 5.7
26-30 years 33 8.2 31-35 years 68 16.9 36-40 years 72 17.9 41-45 years 68 16.9 46-50 years 62 15.4 51-55 years 38 9.5 56-60 years 18 4.5 61-65 years 11 2.7 > 66 years 9 2.2
Education (n=401) No formal qualification
12 3
Secondary school qualification
24 6
Undergraduate diploma
16 4
Bachelor’s/Graduate diploma
164 40.9
Bachelor’s Honours/PG diploma
54 13.5
Master’s degree 125 31.2 Doctorate 6 1.5
6.1.1 Firm characteristics
Table 6.2 gives the breakup of the industry sector which the respondents’ businesses
belong to. Although there is a good representation from various industries, there is a
higher representation of firms in the service industry. For example, education and
training (16.4), wholesale/retail trade (12.9%) and IT (10.2 %) constituted the bulk of
the sample.
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Table 6 .2 Characteristics of the respondents’ firms (n=403) Firm details Industry sector the business belongs to Frequency Percent
Agriculture, Forestry & Fishing 19 4.7 Accommodation, cafes & restaurants 28 6.9 Transport and warehousing 32 7.9
Financial and insurance services 16 4
Administrative and support services 11 2.7 Arts and recreation services 15 3.7 Electricity, gas, water supply 24 6 Construction 33 8.2 Information,media and telecommunications 41 10.2 Property and real estate 40 9.9 Health care and social assistance 26 6.5 Mining and manufacturing 19 4.7 Wholesale/Retail trade 52 12.9 Education and training 66 16.4 Tourism and hospitality 21 5.2 Others 17 4.2
6.2 Measurement properties
Scholars attest that the ability to test the hypotheses and the quality of inferences
depend on the procedures that were used to develop the measures, the survey
instrument, and evidence that the measures are of good quality (see Churchill 1979;
Webb 2000; Peters 2002). While the survey questions were checked for the wording,
layout and applicability to the context of the study, the measurements used should also
be assessed for their reliability and validity. Churchill (1979) and Webb (2000) remind
us that the measurements should not only be tested for reliability, but also validity, since
a valid measure will always be reliable, but a reliable measure may not be valid.
Accordingly, once the data were collected, the measurement was subjected to both
validity and reliability tests.
To establish the psychometric properties of the measures used in our study, I conducted
reliability and validity analysis. For the purpose of reliability analysis, first I looked at
the correlations among all the items to see that they were highly correlated within the
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construct and differentiated from other constructs. After this, I calculated Cronbach’s
Alpha for each construct and checked for item-to-total correlation. The results of this
are presented in the following tables under the section reliability analysis.
6.2.1 Reliability analysis
Coefficient alpha is the most used and well established measure to examine the internal
consistency of a set of items (Churchill 1979; Nunnally 1978; Peters 1979). Churchill
(1979, p.68) suggests that “coefficient alpha absolutely should be the first measure one
calculates to assess the quality of the instrument”. A higher co-efficient alpha indicates
that the sample of items captures the construct it is intended to capture, and the items in
the pool share a common core. Churchill (1979) states that if the alpha is low, it means
that the sample of items is not successful in capturing the construct which motivated the
measure, and suggests that if the item pool is sufficiently large, the items that do not
share equally the common core should be eliminated. He recommends calculating the
correlation of each item with the total score and plotting these correlations in decreasing
order of magnitude, and eliminating any item with correlations near zero. Also he
suggests removing the items which cause a substantial or sudden drop in the item-to-
total correlations. I have followed this procedure, and present the results in the next
section.
6.2.1.1 Reliability test for Entrepreneurial Self-efficacy
Table 6.3 presents the correlation matrix for entrepreneurial self-efficacy, and Table 6.4
shows the reliability analysis results for measures of the entrepreneurial self-efficacy
construct.
161
162
Table 6.4: Reliability Analysis Results for Measurement Scales in the Study of Entrepreneurial Self Efficacy
Composite measures for the dependent and independent variables were first developed
by averaging the items for each of the scales. By averaging the items, it is assumed that
all the items in that scale contribute equally to the construct. This is advised only for
established scales whose psychometric properties can be established in the given
sample. We have shown this to be the case in the reliability and validity section of this
chapter.
177
For testing the hypotheses, items representing each dimension of entrepreneurial self-
efficacy, entrepreneurial behavioural activities, and personality characteristics were
averaged to provide a composite value for each construct. All the items under the
entrepreneurial information overload construct were also combined to form a composite
variable.
6.3.1 Correlation matrix for composite variables
Table 6.29 shows the mean, standard deviation and correlation among the composite
variables used for hypothesis testing.
178
179
6.4 Common method bias Since there is a possibility that the characteristics of late respondents may be similar to
those of non-respondents, I formally tested for response bias using the procedure
suggested by Oppenheim (1966). Tests for nonresponse bias was done by comparing
responses received from the first and second rounds of mailing. The t-tests results
showed no significant difference between the first and second mailing.
6.5 Hypothesis testing
Most of the constructs proposed in the theoretical model, i.e. entrepreneurial self-
efficacy (ESE), personality characteristics (PC), and entrepreneurial behavioural
activities (EBA) had multiple factors. To test the hypotheses, regression-based path
analysis using Hayes (2013) PROCESS tool for SPSS was carried out, because such a
type of regression-based path analysis considers the various conditions in combination.
In Chapter 4, I presented the conceptual framework proposing relationships between
various variables, and also a corresponding set of hypotheses. The hypotheses were
tested for the proposed relationships between personality characteristics and
entrepreneurial self-efficacy (H1a - H1f, H2a - H2f, H3a - H3f), and the relationship
between entrepreneurial information overload and entrepreneurial self-efficacy (H4a-
H4f). Tables 6.30 to 6.35 present the results of the analysis for the relationship between
personality characteristics and entrepreneurial self-efficacy as well as the association of
EIO on each dimension of entrepreneurial self-efficacy. The hypotheses of the main
effects on relationships between entrepreneurial information overload on entrepreneurial
behavioural activities (H5a – H5h), personality characteristics on entrepreneurial
behavioural activities (H6a – H6h; H7a-H7h; H8a-H8h), and entrepreneurial self-
efficacy on entrepreneurial behavioural activities ( H9a-H9h; H10a-H10h; H11a-H11h;
H12a-H12h; H13a-H13h; H14a-H14h) were also tested. The results of these tests are
presented in Tables 6.36 - 6.43.
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6.5.1 Effects of personality characteristics and entrepreneurial information overload on the searching capability dimension of entrepreneurial self-efficacy (H1a, H2a, H3a, and H4a) Table 6.30 Testing of PC and EIO association with searching capability dimension
of ESE Dependent Variable: Searching (search) Model Summary: R2 = .32, F = 32.98, p <.001 Standardised beta
The results, as can be seen in Table 6.30, suggest that the need for achievement
dimension of personality characteristics (PCnAch: β=0.35, p ≤.000) and the risk-taking
dimension of personality characteristics (PCRisk: β=0.18, p ≤.01) are positively related
to the searching capability dimension of entrepreneurial self-efficacy. This evidence
suggests that entrepreneurs who have a high need for achievement and risk-taking
propensity also perceive their level of confidence in searching for market and product
information to be high. The results also show that there is no direct effect of the internal
locus of control dimension of personality characteristics on the searching dimension of
entrepreneurial self-efficacy (PCLoC: β=0.11, p =0.154). The results also show that, as
hypothesised, entrepreneurial information overload is negatively associated with the
searching capability of entrepreneurial self-efficacy (EIO: β=-0.10, p ≤ 0.05). It shows
that information overload reduces entrepreneurs’ confidence in their searching ability.
The relevant hypotheses and results are shown below:
H1a : Personality characteristics of need for achievement is positively associated with
the searching capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.35, p ≤ 0.000).
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H2a: Personality characteristics of locus of control is positively associated with the
searching capability dimension of entrepreneurial self efficacy.
This hypothesis was not supported (β=0.11, not significant [p=.154]).
H3a: Personality characteristics of risk-taking propensity is positively associated with
the searching capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.18, p ≤ 0.01 [p=.002]).
H4a: Entrepreneurial information overload is negatively associated with the searching
capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=-0.10, p ≤.05, [p=.013]).
6.5.2 Effects of personality characteristics and entrepreneurial information overload on the planning capability dimension of entrepreneurial self-efficacy (H1b, H2b, H3b, and H4b)
Table 6.31 Testing of PC and EIO association with planning dimension of ESE
Dependent Variable: Planning (Plg) Model Summary: R2 = .21, F=18.83, p < .001 Standardised beta
Entrepreneurial characteristics of need for achievement (PCnAch: β=0.16, p < 0.01) and
risk-taking (PCRisk: β=0.21, p < 0.000) dimensions of personality characteristics are
shown to have a positive relationship with the entrepreneur’s self-efficacy in planning.
There is, however, no relationship between the locus of control dimension of
personality characteristics and entrepreneurial self-efficacy dimension of planning. The
result also shows no association between entrepreneurial information overload and
planning, and therefore the hypothesis (H2b) is rejected. The relevant hypotheses and
results are shown below:
182
H1b: Personality characteristics of need for achievement is positively associated with
the planning capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.16, p ≤ .010).
H2b: Personality characteristics of locus of control is positively associated with the
planning capability dimension of entrepreneurial self efficacy.
This hypothesis was not supported (β=0.10, not significant [p= .177]).
H3b: Personality characteristics of risk-taking propensity is positively associated with
the planning capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.21, p ≤ .000).
H4b: Entrepreneurial information overload is negatively associated with the planning
capability dimension of entrepreneurial self efficacy.
This hypothesis was not supported (β=-.05, not significant, [p= .290]).
6.5.3 Effects of personality characteristics and entrepreneurial information overload on the marshalling capability dimension of entrepreneurial self-efficacy (H1c, H2c, H3c, H4c)
Table 6.32 Testing of PC and EIO association with the marshalling capability dimension of ESE
Dependent Variable: Marshalling (Mrsh) Model Summary: R2 = .20, F= 16.74, p < .001 Standardised beta
Two of the three entrepreneur personality characteristics dimensions, namely need for
achievement (PCnAch: β=.14, p < .05) and risk taking (PCRisk: β=.22, p ≤.000), are
shown to have a positive relationship with the entrepreneur’s self-efficacy in
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marshalling and organising resources for the firm. However, internal locus of control is
not associated with the marshalling dimension of entrepreneurial self-efficacy (PCLoC:
β=12, p =.142). As hypothesised, entrepreneurial information overload is negatively
associated with the marshalling dimension (EIO: β=-.11, p ≤ .05). It negatively impacts
on the entrepreneurs’ confidence in their ability to organise resources. The relevant
hypotheses and results are shown below:
H1c: Personality characteristics of need for achievement is positively associated with
the marshalling capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.14, p ≤ 0.05, [p=.020]).
H2c: Personality characteristics of locus of control is positively associated with the
marshalling capability dimension of entrepreneurial self efficacy.
This hypothesis was not supported (β=0.12, not significant [p = .142]).
H3c: Personality characteristics of risk-taking propensity is positively associated with
the marshalling capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.22, p ≤.000).
H4c: Entrepreneurial information overload is negatively associated with the
marshalling capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=-.11, p ≤.05, [p=.018]).
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6.5.4 Effects of personality characteristics and entrepreneurial information overload on the implementing people-related capability dimension of entrepreneurial self-efficacy (H1d, H2d, H3d, H4d)
Table 6.33 Testing of PC and EIO association with the implementing people-
related capability dimension of ESE Dependent Variable: Implementing people-related capability(Impple) Model Summary: R2 = .25, F = 20.94, p <.001 Standardised beta
All the three characteristics, need for achievement (PCnAch: β=0.21, p ≤.000), locus of
control (PCLoC: β=0.12, p ≤ 0.05) and risk-taking propensity (PCRisk: β=0.13, p ≤.01))
have been shown to have a direct and positive relationship to the entrepreneur’s
confidence level in implementing people-related tasks (supervising staff and other
human resource activities). This is expected, because entrepreneurs who have a need to
achieve and a high internal locus of control will take control and have confidence in
their own ability to supervise and lead people. There is also, however, a negative
relationship between entrepreneurial information overload (EIO) and the implementing
people-related task dimension of entrepreneurial self efficacy (EIO: β=-.09, p ≤ 0.05) as
hypothesised. When entrepreneurs feel overloaded with information, they lack
confidence in their ability to supervise and undertake other human resource activities.
The relevant hypotheses and results are shown below:
H1d: Personality characteristics of need for achievement is positively associated with
the implementing people-related capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.21, p ≤ .000).
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H2d Personality characteristics of locus of control is positively associated with the
implementing people-related capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.12, p ≤ . 05, [p=. 046]).
H3d Personality characteristics of risk-taking propensity is positively associated with
the implementing people-related capability dimension of entrepreneurial self-efficacy.
This hypothesis was supported (β=0.13, p ≤ .01, [p=.009]).
H4d Entrepreneurial information overload is negatively associated with the
implementing people-related capability dimension of entrepreneurial self-efficacy.
This hypothesis was supported (β=-.09, p ≤ 0.05, [p=.029]).
6.5.5 Effects of personality characteristics and entrepreneurial information overload on the implementing finance capability dimension of entrepreneurial self-efficacy (H1e, H2e, H3e, H4e)
Table 6.34 Testing of PC and EIO association with the implementing finance-
related capability dimension of ESE Dependent Variable: Implementing finance-related capability (Impfin) Model Summary: R2 = .22, F = 19.34, p <.001 Standardised beta
** p≤.01. *p≤.05. All the three personality characteristics, namely need for achievement (PCnAch:
β=0.15, p ≤ .05), locus of control (PCLoC: β=0.18, p ≤.05) and risk-taking propensity
(PCRisk: β=0.18, p ≤ .01) have been shown to have a direct and positive relationship to
the entrepreneur’s confidence level in implementing finance-related tasks (maintaining
financial records, understanding statements, and estimating financial requirements of
the firm). The results show that entrepreneurial information overload (EIO) does not
affect the implementing finance dimension of entrepreneurial self-efficacy. The
186
hypothesis (H4e) was therefore rejected. The relevant hypotheses and results are shown
below:
H1e Personality characteristics of need for achievement is positively associated with
the implementing finance-related capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.15, p ≤ .05, [p=.027]).
H2e Personality characteristics of locus of control is positively associated with the
implementing finance-related capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.18, p ≤.05; [p=.013]).
H3e Personality characteristics of risk-taking propensity is positively associated with
the implementing finance-related capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.18, p ≤ .01, [p=.003]).
H4e: Entrepreneurial information overload is negatively associated with the
implementing finance-related capability dimension of entrepreneurial self efficacy.
This hypothesis was not supported (β=-.08, not significant [p=.056]).
6.5.6 Effects of personality characteristics and entrepreneurial information overload on the coping with unexpected challenges capability dimension of entrepreneurial self-efficacy (H1f, H2f, H3f, H4f)
Table 6.35 Testing of PC and EIO association with the coping with unexpected
challenges capability dimension of ESE Dependent Variable: Coping with unexpected challenges (Copch) Model Summary: R2 = .23, F = 21.38, p < .001 Standardised beta
All the three personality characteristics (need for achievement (PCnAch: β=0.15, p
≤.05), locus of control (PCLoC: β=0.16, p ≤ .05) and risk-taking propensity (PCRisk:
β=0.20, p ≤ .000)) have been shown to have a direct and positive relationship to the
entrepreneur’s confidence level in coping with challenges. When the entrepreneur has a
high need for achievement, high locus of control and a high risk-taking propensity, they
feel confident in their ability to cope with any challenge that comes their way. However,
we see that there is a strong negative relationship between EIO and the ESE dimension
of coping with challenges (EIO: β=-.13, p ≤ 0.01). This is expected, since the
entrepreneur does have to seek information when trying to cope with challenges and
therefore feels the negative impact of information overload on their self-efficacy in
coping with the challenges. The relevant hypotheses and results are shown below:
H1f: Personality characteristics of need for achievement is positively associated with
the coping with challenges capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.15, p ≤ .05, [p=.011]).
H2f: Personality characteristics of locus of control is positively associated with the
coping with challenges capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.16, p ≤ .05, [p=.025]).
H3f: Personality characteristics of risk-taking propensity is positively associated with
the coping with challenges capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=0.20, p ≤ .000).
H4f: Entrepreneurial information overload is negatively associated with the coping with challenges capability dimension of entrepreneurial self efficacy.
This hypothesis was supported (β=-0.13, p ≤.01, [p=.001]).
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6.5.7 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the planning dimension of entrepreneurial behavioural activities. (H5a, H6a, H7a, H8a, H9a, H10a, H11a, H12a, H13a, H14a)
Table 6.36 Relationship between ESE, EIO and PC and the planning dimension of EBA
Dependent Variable: Planning (BhvPlg) Model Summary : R2 = .24, F = 22.38, p < .001 Standardised beta
The table above shows the results of testing the association of all six dimensions of
entrepreneurial self-efficacy, entrepreneurial information overload, and the three
dimensions of personality characteristics on the planning variable of entrepreneurial
behavioural activities. As can be seen from the table, surprisingly, none of the items of
the entrepreneurial self-efficacy construct are associated with the planning dimension of
entrepreneurial behavioural activities. It was expected that the entrepreneurs’ self-
efficacy in searching, planning, marshalling, implementing people-related tasks,
implementing finance-related tasks and coping with unexpected challenges would be
related to the behavioural activity of planning, where the entrepreneur would formulate
objectives and decide on what to do to achieve those objectives. As hypothesised,
entrepreneurial information overload is also not associated with the planning dimension.
With regard to the personality characteristics, only one of the dimensions, namely need
for achievement, shows association with this dimension (PCnAch: β=0.15, p ≤.05). The
relevant hypotheses and results are shown below:
189
H5a: Entrepreneurial information overload is negatively associated with the planning
dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β=-0.09, not significant, [p = .182]).
H6a: Personality characteristics of need for achievement is positively associated with
the planning dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β=0.15, p ≤ .05, [p=.014]).
H7a: Personality characteristics of locus of control is positively associated with the
planning dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β=0.08, not significant [p = .275]).
H8a: Personality characteristics of risk-taking propensity is positively associated with
the planning capability dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= -0.09, not significant, [p =.182]).
H9a: The entrepreneurial self-efficacy dimension of searching is positively associated
with the planning dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.16, not significant, [p =.100]).
H10a: The entrepreneurial self-efficacy dimension of planning is positively associated
with the planning dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β=- 0.02, not significant, [p =.814]).
H11a: The entrepreneurial self-efficacy dimension of marshalling is positively
associated with the planning dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.11, not significant, [p =.182]).
H12a: The entrepreneurial self-efficacy dimension of implementing people-related
capability is positively associated with the planning dimension of entrepreneurial
behavioural activities.
This hypothesis was not supported (β= 0.11, not significant, [p =.182]).
190
H13a: The entrepreneurial self-efficacy dimension of implementing finance-related
capability is positively associated with the planning dimension of entrepreneurial
behavioural activities.
This hypothesis was not supported (β= 0.14, not significant, [p =.067]).
H14a: The entrepreneurial self-efficacy dimension of coping with challenges is
positively associated with the planning dimension of entrepreneurial behavioural
activities.
This hypothesis was not supported (β= -0.01, not significant, [p =.883]).
6.5.8 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the controlling dimension of entrepreneurial behavioural activities. (H5b, H6b, H7b, H8b, H9b, H10b, H11b, H12b, H13b, H14b)
Table 6.37 Relationship between ESE, EIO and PC and the controlling dimension of EBA
Dependent Variable: Controlling (BhvCom) Model Summary : R2 = .38, F = 25.18, p <.001 Standardised beta
The table above shows the results of testing the association of all six dimensions of
entrepreneurial self-efficacy, entrepreneurial information overload and the three
dimensions of personality characteristics on the controlling variable of entrepreneurial
191
behavioural activities. As can be seen from the table, within the entrepreneurial self-
efficacy construct, two dimensions, implementing people related tasks (Impple: β=0.13,
p ≤ 0.05) and implementing finance related tasks (Impfin: β=0.32, p ≤ 0.000), are
positively associated with the controlling dimension of entrepreneurial behavioural
activities. Controlling is the process of monitoring the actual situation as well as the
performance in the firm and then ensuring that the desired results are achieved (Luthans
& Ibrayeva 2006, p.106). If the entrepreneurs’ self-efficacy in the implementing people
and finance related tasks is high, they will be able to undertake the controlling activity
very efficiently. Clearly, the findings in this study support this theory.
Among the personality characteristics, only one of the dimensions, namely internal
locus of control, shows a positive relationship with this dimension (PCLoC: β=0.15, p ≤
.05). The finding suggests that entrepreneurs with a high internal locus of control will
engage in controlling activities well. This is expected, because successful entrepreneurs
do believe that they have significant control over the outcomes of the firm (Brockhaus
1980a). These findings support Krueger’s (1993) identification of a close link between
an individual’s desire for control and the initiating and maintaining of goal-directed
behaviours. However, entrepreneurial information overload is not associated with the
controlling dimension. The relevant hypotheses and results are shown below:
H5b: Entrepreneurial information overload is negatively associated with the controlling
dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= -0.04, not significant, [p =.383]).
H6b: Personality characteristics of need for achievement are positively associated with
the controlling dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.07, not significant, [p =.195]).
H7b: Personality characteristics of locus of control is positively associated with the
controlling dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.15, p≤ 0.05, [p =.026]).
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H8b: Personality characteristics of risk-taking propensity is positively associated with
the controlling dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= -0.01, not significant [p =.885).
H9b: The entrepreneurial self-efficacy dimension of searching is positively associated
with the controlling dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.03, not significant [p=.666]).
H10b: The entrepreneurial self-efficacy dimension of planning is positively associated
with the controlling dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.09, not significant, [p =.145]).
H11b: The entrepreneurial self-efficacy dimension of marshalling is positively
associated with the controlling dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.00, not significant, [p =.986]).
H12b: The entrepreneurial self-efficacy dimension of implementing people-related
capability is positively associated with the controlling dimension of entrepreneurial
behavioural activities.
This hypothesis was supported (β= 0.13, p≤0.05, [p =.049]).
H13b: The entrepreneurial self-efficacy dimension of implementing finance is positively
associated with the controlling dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.32, p ≤.000).
H14b:The eEntrepreneurial self-efficacy dimension of coping with unexpected
challenges is positively associated with the controlling dimension of entrepreneurial
behavioural activities.
This hypothesis was not supported (β= 0.02, not significant, [p =.785]).
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6.5.9 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the internal communication dimension of entrepreneurial behavioural activities. (H5c, H6c, H7c, H8c, H9c, H10c, H11c, H12c, H13c, H14c)
Table 6.38 Relationship between ESE, EIO and PC and the internal communication dimension of EBA
Dependent Variable: Internal Communication (BhvCom) Model Summary: R2 = .38, F = 25.40, p < .001 Standardised beta
Table 6.38 above shows the results of testing the association of all six dimensions of
entrepreneurial self-efficacy, entrepreneurial information overload and the three
personality characteristics dimensions on the internal communication dimension of
entrepreneurial behavioural activities. As can be seen from the table, in the
entrepreneurial self-efficacy construct, the dimension implementing people related tasks
(Impple: β=0.30, p ≤ .000) is positively associated with the communication dimension
of entrepreneurial behavioural activities. Communication includes sending and
receiving information, and if the entrepreneur has a high level of self-efficacy in his or
her ability to deal with people (implementing people related task dimension), it can be
expected that they also engage in activities related to internal communication
effectively.
194
The results also show that entrepreneurial information overload is negatively impacting
on the entrepreneur’s ability to engage in sending and receiving information (EIO: β=-
0.08, p ≤ .050). Among the personality characteristics, none of the dimensions showed
any association with the behavioural activity of internal communication. The relevant
hypotheses and results are shown below:
H5c: Entrepreneurial information overload is negatively associated with the internal
communication dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= -0.08, p ≤ .050).
H6c: Personality characteristics of need for achievement is positively associated with
the internal communication dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.04, not significant, [p =.432]).
H7c: Personality characteristics of locus of control is positively associated with the
internal communication dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.11, not significant, [p =.106]).
H8c: Personality characteristics of risk-taking propensity is positively associated with
the internal communication dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.05, not significant, [p =.309]).
H9c: The entrepreneurial self-efficacy dimension of searching is positively associated
with the internal communication dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.04, not significant, p =.403).
H10c: The entrepreneurial self-efficacy dimension of planning is positively associated
with the internal communication dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.07, not significant, [p =.200]).
H11c: The entrepreneurial self-efficacy dimension of marshalling is positively
associated with the internal communication dimension of entrepreneurial behavioural
activities.
195
This hypothesis was not supported (β= 0.03, not significant, [p =.565]).
H12c: The entrepreneurial self-efficacy dimension of implementing people-related
capability is positively associated with the internal communication dimension of
entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.30, p ≤.000).
H13c: The entrepreneurial self-efficacy dimension implementing finance-related
capability is positively associated with the internal communication dimension of
entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.08, not significant, [p =.167]).
H14c: The entrepreneurial self-efficacy dimension of coping with unexpected
challenges is positively associated with the internal communication dimension of
entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.05, not significant, p =.403).
6.5.10 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the human resources management dimension of entrepreneurial behavioural activities. (H5d, H6d, H7d, H8d, H9d, H10d, H11d, H12d, H13d, H14d)
Table 6.39 Relationship between ESE, EIO and PC and the human resources management dimension of EBA
Dependent Variable: Human Resources Management (BhvHRM) Model Summary : R2 = .41, F = 26.06, p <.001 Standardised beta
The association of all six dimensions of entrepreneurial self-efficacy, entrepreneurial
information overload and the three personality characteristics dimensions on the human
resources management dimension of entrepreneurial behavioural activities was also
tested. As can be seen from Table 6.39, in the entrepreneurial self-efficacy construct,
there is a significant positive association between the dimensions of implementing
people-related tasks (Impple: β=0.39, p ≤ 0.000) and coping with unexpected challenges
(Copch: β=0.14, p ≤ 0.05) with the human resources management dimension of
entrepreneurial behavioural activities. This is an expected outcome. Entrepreneurs who
have a high self-efficacy in their ability to recruit, supervise, inspire and train
employees, as well as deal with problems faced by employees, will obviously be able to
engage very well in the activities relating to human resources management.
However, the results show no association between entrepreneurial information overload
and the human resource management dimension. Personality characteristics such as
need for achievement, internal locus of control and risk-taking propensity are also not
related to the human resources management of entrepreneurial behavioural activities.
The relevant hypotheses and results are shown below:
H5d: Entrepreneurial information overload is negatively associated with the human
resources management dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= -0.01, not significant, [p =.726]).
H6d: Personality characteristics of need for achievement is positively associated with
the human resources management dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.06, not significant, [p =.248]).
H7d: Personality characteristics of locus of control is positively associated with the
human resources management dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.08, not significant, [p =.164]).
H8d: Personality characteristics of risk-taking propensity is positively associated with
the human resources management dimension of entrepreneurial behavioural activities.
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This hypothesis was not supported (β= 0.04, not significant, [p =.397]).
H9d: The entrepreneurial self-efficacy dimension of searching is positively associated
with the human resources management dimension of entrepreneurial behavioural
activities.
This hypothesis was not supported (β= 0.07, not significant, [p =.219]).
H10d: The entrepreneurial self-efficacy dimension of planning is positively associated
with the human resources management dimension of entrepreneurial behavioural
activities.
This hypothesis was not supported (β= 0.08, not significant, [p =.156]).
H11d: The entrepreneurial self-efficacy dimension of marshalling is positively
associated with the human resources management dimension of entrepreneurial
behavioural activities.
This hypothesis was not supported (β= -0.10, not significant, [p =.084]).
H12d: The entrepreneurial self-efficacy dimension of implementing people-related
capability is positively associated with the human resources management dimension of
entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.39, p ≤ .000).
H13d: The entrepreneurial self-efficacy dimension of implementing finance-related
capability is positively associated with the human resources management dimension of
entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.04, p not significant, [p =.517]).
H14d: The entrepreneurial self-efficacy dimension coping with unexpected challenges is
positively associated with the human resources management dimension of
entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.14, p≤.05, [p =.012]).
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6.5.11 Effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the work-related tasks dimension of entrepreneurial behavioural activities. (H5e, H6e, H7e, H8e, H9e, H10e, H11e, H12e, H13e, H14e)
Table 6.40 Relationship between ESE, EIO and PC and the work-related tasks dimension of EBA
Dependent Variable: Work Related Tasks (BhvTas) Model Summary : R2 = .40, F = 27.72, p < .001 Standardised beta
The association of all six dimensions of entrepreneurial self-efficacy, entrepreneurial
information overload and the three personality characteristics dimensions with the
entrepreneurs performing activities that are of central concern to the business itself
(work-related tasks) was tested. Table 6.40 presents the results of these tests.
As seen in Table 6.40, three dimensions of entrepreneurial self-efficacy, namely
searching (search: β=0.12, p ≤ .05), implementing people-related tasks(Impple: β=0.18,
p ≤ .05), and implementing finance-related tasks (Impfin: β=0.26, p ≤ .000) have a
positive association with work-related tasks. The personality characteristic of risk-
taking propensity is also positively related to work-related tasks. Entrepreneurial
information overload is negatively associated with work-related tasks ((EIO: β=-0.11, p
≤ 0.01). The entrepreneurial self-efficacy dimensions of planning, marshalling, coping
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with unexpected challenges and the personality characteristics of need for achievement
and locus of control are not associated with the work-related tasks. The relevant
hypotheses and results are shown below:
H5e: Entrepreneurial information overload is negatively associated with the work-
related tasks dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.39, p ≤.01, [p=.006]).
H6e: Personality characteristics of need for achievement is positively associated with
the work-related tasks dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.04, not significant, [p =.444]).
H7e: Personality characteristics of locus of control is positively associated with the
work-related tasks dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β=- 0.01, not significant, [p =.869]).
H8e: Personality characteristics of risk-taking propensity is positively associated with
the work-related tasks dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.15, p ≤ .01, [p =.004]).
H9e: The entrepreneurial self-efficacy dimension of searching is positively associated
with the work-related task dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.12, p≤.050).
H10e: The entrepreneurial self-efficacy dimension of planning is positively associated
with the work-related task dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.01, not significant [p =.902]).
H11e: The entrepreneurial self-efficacy dimension of marshalling is positively
associated with the work-related task dimension of entrepreneurial behavioural
activities.
This hypothesis was not supported (β= 0.05, not significant, [p =.408]).
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H12e: The entrepreneurial self-efficacy dimension of implementing people-related
capability is positively associated with the work-related task dimension of
entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.18, p≤.05).
H13e: The entrepreneurial self-efficacy dimension of implementing finance-related
capability is positively associaedn with the work-related task dimension of
entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.26, p ≤ .000).
H14e: The entrepreneurial self-efficacy dimension of coping with unexpected
challenges is positively associated with the work-related task dimension of
entrepreneurial behavioural activities.
This hypothesis was not supported (β=- 0.03, not significant, [p =.712]).
6.5.12 Testing the effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the customer service dimension of entrepreneurial behavioural activities. (H5f, H6f, H7f, H8f, H9f, H10f, H11f, H12f, H13f, H14f)
Table 6.41 Relationship between ESE, EIO and PC and the customer service dimension of EBA
Dependent Variable: Customer Service (BhvSer) Model Summary : R2 = .36, F = 26.66, p < .001 Standardised beta
The association of all six dimensions of entrepreneurial self-efficacy, entrepreneurial
information overload and the three personality characteristics dimensions with the
customer service dimension of entrepreneurial behavioural activity was tested. Table
6.41 presents the results of these tests.
Of the six dimensions of entrepreneurial self-efficacy, two dimensions, i.e.,
implementing people-related tasks (Impple: β= 0.35, p ≤.000) and implementing
finance-related tasks (Impfin: β= 0.14, p ≤.05), have a positive association with the
customer service dimension of entrepreneurial behavioural activities. The other
entrepreneurial self-efficacy dimensions such as searching, planning, marshalling and
coping with unexpected challenges do not show any association with the customer
service dimension. Entrepreneurial information overload is also not associated with
customer service. Among the personality characteristics, only need for achievement
(PCnAch: β= 0.13, p ≤ .05) is positively associated with customer service, while
internal locus of control and risk-taking propensity are not. The relevant hypotheses
and results are shown below:
H5f: Entrepreneurial information overload is negatively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= -0.05, not significant, [p =.264]).
H6f: Personality characteristics of need for achievement is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.13, p≤ .05, [p =.035]).
H7f: Personality characteristics of locus of control is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.02, not significant, [p =.750]).
H8f: Personality characteristics of risk-taking propensity is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.09, not significant, [p =.086]).
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H9f: The entrepreneurial self-efficacy dimension of searching is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.05, not significant, [p =.410]).
H10f: The entrepreneurial self-efficacy dimension of planning is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.05, not significant, [p =.681]).
H11f: The entrepreneurial self-efficacy dimension of marshalling is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.02, not significant, [p =.776]).
H12f: The entrepreneurial self-efficacy dimension of implementing people-related capability is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.35, p ≤.000).
H13f: The entrepreneurial self-efficacy dimension implementing finance-related capability is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.14, p ≤ .05, [p =.044]).
H14f: The entrepreneurial self-efficacy dimension of coping with unexxpected challenges is positively associated with the customer service dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.01, not significant, [p =.848]).
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6.5.13 Testing the effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the socialising dimension of entrepreneurial behavioural activities. (H5g, H6g, H7g, H8g, H9g, H10g, H11g, H12g, H13g, H14g)
Table 6.42 Relationship between ESE, EIO and PC and the socialising dimension of EBA Dependent Variable: Socialising (BhvSoc) Model Summary : R2 = .05, F = 13.27, p < .001 Standardised beta
The association of entrepreneurial self-efficacy, personality characteristics and
entrepreneurial information overload with the socialising dimension of entrepreneurial
behavioural activities was tested. Socialising includes networking and communicating
with outside parties. Interestingly, none of the dimensions of entrepreneurial self-
efficacy had an impact on the entrepreneurial behavioural activity of socialising. The
results also show that entrepreneurial information overload likewise has no effect on the
socialising activity. Only one personality characteristic, internal locus of control, (β=
0.18, p ≤. 05) has a significant positive relationship to the socialising activity, while the
other two characteristics, need for achievement and risk-taking propensity, had no
relationship. The relevant hypotheses and results are shown below:
H5g: Entrepreneurial information overload is negatively associated with the socialising
dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β=- 0.01, not significant, [p =.891]).
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H6g: Personality characteristic of need for achievement is positively associated with
the socialising dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.03, not significant, [p =.660]).
H7g: Personality characteristic of locus of control is positively associated with the
socialising dimension of entrepreneurial behavioural activities.
This hypothesis was supported (β= 0.18, p ≤ .05, [p=.026]).
H8g: Personality characteristic of risk-taking propensity is positively associated with
the socialising dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.03, not significant [p =.681]).
H9g: The entrepreneurial self-efficacy dimension of searching is positively associated
with the socialising dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= -0.01, not significant [p =.868]).
H10g: The entrepreneurial self-efficacy dimension of planning is positively associated
with the socialising dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.07, not significant [p =.423]).
H11g: The entrepreneurial self-efficacy dimension of marshalling is positively
associated with the socialising dimension of entrepreneurial behavioural activities.
This hypothesis was not supported (β= 0.11, not significant [p =.192]).
H12g: The entrepreneurial self-efficacy dimension of implementing people-related
capability is positively associated with the socialising dimension of entrepreneurial
behavioural activities.
This hypothesis was not supported (β= 0.15, not significant [p =.088]).
H13g: The entrepreneurial self-efficacy dimension of implementing finance-related
capability is positively associated with the socialising dimension of entrepreneurial
behavioural activities.
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This hypothesis was not supported (β= 0.10, not significant [p =.198]).
H14g: The entrepreneurial self-efficacy dimension of coping with unexpected
challenges is positively associated with the socialising dimension of entrepreneurial
behavioural activities.
This hypothesis was not supported (β= 0.10, not significant, p =.198).
6.5.14 Testing the effects of entrepreneurial self-efficacy, entrepreneurial information overload and personality characteristics on the politicking dimension of entrepreneurial behavioural activities. (H5h, H6h, H7h, H8h, H9h, H10h, H11h, H12h, H13h, H14h)
Table 6.43 Relationship between ESE, EIO and PC and the politicking dimension
of EBA Dependent Variable: Politicking (BhvPol) Model Summary : R2 = .19, F = 7.24, p < .001 Standardised beta
and coping with unexpected challenges, but not for the other three dimensions.
2. Next, I have examined the relationship between the entrepreneurs’ personality
characteristics and entrepreneurial behavioural activities. I found that there is a
positive relationship between the personality characteristic of need for achievement
and the entrepreneurial behavioural activities of planning and customer service
activities. With regards to the personality characteristic of internal locus of control,
I found a positive relationship with three entrepreneurial behavioural activities,
namely controlling, socialising and politicking. On the other hand, the personality
characteristic of risk-taking propensity had a positive relationship with only the
work-related tasks of entrepreneurial behaviour.
3. The relationship between entrepreneurial self-efficacy and entrepreneurial
behavioural activities was also examined. It is pertinent to note that there are six
dimensions in the construct of entrepreneurial self-efficacy and eight dimensions in
the construct of entrepreneurial behavioural activities. My examination of these
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relationships shows that not all dimensions of entrepreneurial self-efficacy and
activities of entrepreneurial behavioural activities are related significantly. The
entrepreneurial self-efficacy dimension of searching capability was positively
associated with entrepreneurial behaviours of the work-related tasks dimension.
The entrepreneurial self-efficacy dimensions of planning and marshalling were not
associated with any of the entrepreneurial behavioural activities. The entrepreneurial
self-efficacy dimension of implementing-people was positively associated with five
dimensions of entrepreneurial behavioural activities, namely controlling, internal
communication, human resources management, work-related tasks, and customer
services. The implementing-finance dimension of entrepreneurial self-efficacy was
positively related with three entrepreneurial behaviours, namely controlling, work-
related tasks and customer services. The entrepreneurial self-efficacy dimension of
coping with unexpected challenges was found to be positively associated with the
entrepreneurial behaviour activity of human resources management.
4. The results examining the impact of entrepreneurial information overload on six
dimensions of entrepreneurial self-efficacy revealed that it had a negatively
significant relationship with four dimensions of entrepreneurial self-efficacy,
namely searching, marshalling, implementing people and coping with unexpected
challenges capabilities. The two dimensions not found to be significantly related
were planning and implementing finances.
5. The impact of entrepreneurial information overload on eight entrepreneurial
behavioural activities was also tested. The results indicated that entrepreneurial
information overload was negatively related to two entrepreneurial behavioural
activities, namely the communication and the work-related tasks.
7.2 Contribution to theory
After a comprehensive literature review of key factors that affect entrepreneurship, a
conceptual model was developed which showed potential relationships between
personality characteristics of entrepreneurs, their self-efficacy and entrepreneurial
behaviour. It also included the impact of information overload, which, although
recognised as an issue, has not been empirically tested in the discipline of
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entrepreneurship. All of these key proposed relationships were empirically tested in my
study in an emerging economy context making a significant contribution to the
literature. The main contributions to theory are mentioned below:
1. Zahra (2007) suggested that existing theories developed in the West should be
tested in the emerging economies. Taking a cue from that suggestion, I was able to
develop a model and test that in an emerging economy. The results in the area of
personality traits and entrepreneurial self-efficacy were on the lines predicted based
on existing theory (Philips & Gully 1997; Zhao, Seibert & Hills 2005). With regard
to entrepreneurial behaviour, I was able to convert observed behaviour into
objective constructs and test the relationship with entrepreneurs’ personality
characteristics and entrepreneurial self-efficacy. The results indicated some positive
relationships. This provides a basis for further research.
2. By studying the Indian entrepreneurs, this research has added value to the
entrepreneurship studies undertaken in the emerging economies. While India has a
growing population of entrepreneurs, the quantity of published research in this area
is not a fair representation of the magnitude of the entrepreneurial activity. Thus
this study contributes to gaining a better understanding of practicing Indian
entrepreneurs.
3. While previous studies have recognised the multi-dimentionality of the concept of
entrepreneurial self-efficacy, they used a composite score to measure its effect and
thereby were not in a position to capture the effect of individual dimensions. One
prominent exception has been McGee et al. (2009), who identified five different
dimensions within entrepreneurial self-efficacy. I have used these five multi-
dimensions along wth another dimension of ‘coping with challenges’ identified by
DeNoble et al. (1999). The results from my study confirm the need to treat the self-
efficacy dimensions separately, even in an emerging economy.
4. Bird et al. (2012) called for more studies to test entrepreneurial behavioural
activities using well constructed multi-item measures. Following this call, I have
developed a scale to operationalise the entrepreneurial behaviours based on the
observed activities by Luthans and Ibreyeva (2006) in a transitional economy. The
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results from my study show how entrepreneurial behaviours are impacted by other
factors of entrepreneurship, and lay the ground for further research in this area.
5. The concept of information overload has been extensively applied in fields such as
psychology, organistion science, marketing, accounting and management
information system (Eppler & Mengis 2004). However, its application in the
entrepreneurship domain is not that visible. To the best of my knowledge, my study
is the first of its kind where the concept of information overload has been
empirically tested for its impact on entrepreneurship. Results indicate the negative
influence on some dimensions of self-efficacy and entrepreneurial behaviours, as
hypothesised, and confirm the relevance of information overload to entrepreneurship
literature.
7.3 Practical implication of the results
The results from this study have several implications for educators, practitioners and
policy makers. I discuss them below:
7.3.1 Implications for educators of entrepreneurship
i) My study shows that the theories of entrepreneurship developed in the mature
economies can be applied to emerging economy contexts as recommended by Zahra
(2007). However, these concepts have to be suitably modified and adapted after
thoroughly examining the local socio-economic environment.
ii) Entrepreneurial self-efficacy was identified as a multi-dimensional construct in
recent studies. My study considered six dimensions in entrepreneurial self-efficacy and
examined each of them empirically for their impact on other variables, for example on
personality characteristics and entrepreneurial behavioural activities. Educators can
now design entrepreneurship courses to train students in specific competences that can
help build their entrepreneurial self-efficacy and improve behavioural outcomes.
Furthermore, as careers and professions become more specialised, it will be useful to
233
identify industry-specific entrepreneurial self-efficacy dimensions and match them with
the industry-specific tasks.
iii) Traditionally, the focus of educators was on developing entrepreneurship skills in
nascent or potential entrepreneurs to start a new venture, but my study identified and
tested specific entrepreneurial behavioural activities of practicing entrepreneurs who are
managing real businesses. This identification of entrepreneurial behavioural activities
can guide educators to also design curricula to train practicing entrepreneurs in
important behavioural activities that are relevant to an industry and / or region.
iv) By identifying and empirically examining the role of entrepreneurial information
overload in my study, I have brought this concept into the entrepreneurship domain.
My results showed that information overload has adversely impacted on some
dimensions of entrepreneurial self-efficacy and entrepreneurial behavioural activities.
Educators can bring this aspect of information overload into the mainstream of the
entrepreneurship curriculum and prepare students with appropriate tools to meet this
new environmental challenge.
7.3.2 Implications for entrepreneurship practitioners
i) Personality characteristics of entrepreneurs were found to impact on entrepreneurial
self-efficacy dimensions. Practicing entrepreneurs should recognise the importance of
the variables that are relevant to industry and gain competence in them.
ii) My study has empirically tested eight specific activities of entrepreneurial
behavioural activities for their relationship with three characteristics of personality and
six dimensions of entrepreneurial self-efficacy. Using this approach, practicing
entrepreneurs in emerging economies can identify important behaviours that help them
to perform effectively in their ventures. They can even prioritise these behaviours based
on the needs of their venture or local business environment.
iii) As a corollary to the above point, entrepreneurial behavioural activities were found
to have certain antecedents in the form of personality characteristics, entrepreneurial
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self-efficacy and entrepreneurial information overload. It will be useful for
entrepreneurs to introspect and assess their cognitive abilities and competences.
iv) Information overload was found to adversely impact on many dimensions of
entrepreneurial self-efficacy and some activities of entrepreneurial behavioural
activities. Hence, it becomes necessary, even in an emerging economy like India, to
reduce information overload by applying heuristics and other time management tools
and techniques.
7.3.3 Implications for policy makers
i) Many government agencies offer entrepreneurship training programmes. However,
they mainly focus on writing a business plan or starting a new venture. The results from
my study provide some practical input for designing programmes that focus not only on
how to start new ventures, but also how to manage them by learning behaviours
required in the field.
ii) Results from my study show that entrepreneurs in India possess competences
relevant for entrepreneurship. Using my study’s approach, governments and other non-
governmental bodies can identify the deficient competences among entrepreneurs and
train them by designing policies and establishing appropriate infrastructure.
iii) Since we know that a large part of India’s workforce is engaged in the informal
economy, and that the average number of employees, even in registered firms, is low (3
to 5 employees based on different studies), it is important for government to channel
efforts and resources to improve the productivity and scalability of the small business
entrepreneurs. Therefore, the creation of a supportive culture to improve entrepreneurs’
cognitive and behavioural capabilities through multiple government agencies is
necessary in order to leverage economic gains through entrepreneurship.
iv) Given the increased impact of information overload on the modern-day
entrepreneurs and business owners, it is necessary that they be provided with support
through appropriate institutions. For example, this could take the form of a one-stop
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centre where relevant and commonly required information is made available to
entrepreneurs or online resource and support centres could be developed.
7.4 Limitations of the study
Although my study has some significant contributions to make to the literature and
practicing entrepreneurs, I recognise that there are quite a few limitations to it.
First, the main limitation is the generalisability of the results, due to the fact that my
sample is drawn from India only. While India is an advanced and large emerging
economy which shares many common characteristics with other emerging economies,
the contextual factors vary across countries. Therefore, care should be taken before
these results are applied directly to another emerging economy, or even mature
economies, without further testing of this model in those countries.
Second, the sample was drawn from cities that are quite dispersed in India, and which
may not be homogenous in their characteristics. Hence the findings of this study may
not be generalisable to all the entrepreneurs in India, and particularly to those in the
rural areas.
Third, due to time and travel constraints, the questionnaires were self-administered.
There could have been some issues relating to language or conceptual clarity. A
significant proportion of responses (about 30 percent) had to be discarded for various
reasons, and some of them could be due to this factor.
Fourth, there could be a bias from self-reporting. Carr and Sequeira (2007) highlighted
the possibility that respondents may overstate their perceived ability. This bias may
have occurred in my study if some respondents overstated their perceived ability on
certain variables.
7.5 Directions for future research
The results from my study can lead to several research initiatives. I briefly discuss each
of them below:
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First, further research could be undertaken so as to determine the generalisability of the
results of this study. Since the multidimensionality of the entrepreneurial self-efficacy
was empirically tested and the results showed that each dimension had a different
influence, it is important to do more research both in developed and emerging
economies on each of these dimensions of entrepreneurial self-efficacy. Further, there
may be additional dimensions that could be identified.
Second, although the study was done in India as a whole, the sample did not cover all
areas to adequately represent the country fully. In a large country like India, there are
several regional variations based on cultural and religious practices. Hence, future
research could include replicating this study for the various regions in India to gain
insights into what is relevant to a localised context.
Third, this study provides insights into the impact of entrepreneurial information
overload on entrepreneurial self-efficacy and entrepreneurial behavioural activities.
Future research adopting the construct of entrepreneurial information overload should
employ a more extensive measure for this construct to ensure adequate domain
coverage. An exploration of the causes of entrepreneurial information overload will
help to better understand when and how entrepreneurs are impacted. It will also be
interesting to find out the impact of entrepreneurial information overload on the
different stages of the entrepreneurial venture i.e., opportunity identification, starting the
venture and growing the venture. Such a study would help understand the information
needs of entrepreneurs and how such information-seeking behaviour is impacted by
entrepreneurial information overload.
Fourth, my study in an emerging economy found an adverse impact of entrepreneurial
information overload on entrepreneurship. Given this finding, it is likely that
entrepreneurial information overload will impact on entrepreneurs in mature economies
even more. Therefore, similar studies could be undertaken in future in other emerging
economies as well as in developed countries. The findings of such research would be
helpful in offering important extensions to the entrepreneurial information overload
construct used in my study.
237
Fifth, the conceptual framework of my study has not included venture performance.
Future research, therefore, can examine how personality characteristics, entrepreneurial
self-efficacy and entrepreneurial behavioural activities can impact on the performance
of a venture in terms of both financial and non-financial measures.
Sixth, using my conceptual framework to examine entrepreneurs industry-wise may
reveal the competences and cognitive abilities that are industry-specific. For example,
fast growing service industries such as software and tourism may need a different set of
capabilities compared to those from traditional industries such as mining or handicrafts,
some of which are still large contributors to the rural economy.
Finally, entrepreneurship is generally recognised as a process that can be divided into
three stages: pre-launch (the period prior to starting a venture), launch (the start-up
phase) and the post-launch (the period of development beyond the start-up phase).
Perhaps a longitudinal study could be done to capture the impact of the constructs at
different points in the process of the venture. It would be interesting to compare the
four dimensions used in this study in the early stages of the venture development as
opposed to the more mature enterprise.
7.6 Concluding remarks
Overall, my study extends previous research in the area of personality characteristics,
entrepreneurial self-efficacy and entrepreneurial behavioural activities, and it created a
new conceptual model for empirical testing. It also included a new variable in the form
of entrepreneurial information overload. Although the importance of personality
characteristics, entrepreneurial self-efficacy and entrepreneurial behavioural activities
are widely acknowledged, there is still a dearth of such studies, particularly so in
emerging economies. The results suggest that the personality characteristics of need for
achievement, internal locus of control, and risk-taking propensity are positively related
to entrepreneurial self-efficacy, even in India, an emerging economy, which is similar to
the relationships found in previous studies conducted in mature economies. It is also
seen that entrepreneurs from emerging economies are adversely affected by information
overload. If that is the case in an emerging economy, it is very likely to have an adverse
238
impact on entrepreneurs in mature economies. Overall, my study takes an important
step towards understanding entrepreneurs in a large emerging economy such as India,
and also establishes a robust research platform for future research that can be used both
in emerging and mature economies.
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REFERENCES
Acs, Z & Audretsch, D 2010, ‘Introduction to the 2nd Edition of the Handbook of Entrepreneurship Research’, in ZJ Acs & DB Audretsch (eds) Handbook of Entrepreneurship Research, Springer, New York, pp.1-19. Adler, S 1996, ‘Personality and work behaviour: exploring the linkages’, Applied Psychology, vol. 45, no.3, pp.207-224. Ahlstrom, D & Bruton, GD 2002, ‘An institutional perspective on the role of culture in shaping strategic actions by technology-focused entrepreneurial firms in China’, Entrepreneurship Theory and Practice, vol.26, no.4, pp. 53-69. Ahlstrom, D & Bruton, GD 2006, ‘Venture capital in emerging economies: networks and institutional change’, Entrepreneurship Theory & Practice, vol. 30, no. 2, pp. 299-320. Ahmad, NH, Ramayah, T, Wilson, C & Kummerow, L 2009, ‘Is entrepreneurial competency and business success relationship contingent upon business environment? A study of Malaysian SMEs’, International Journal of Entrepreneurship Behaviour & Research, vol. 16, no.3, pp.182-203. Ahmed, SU 1985, ‘nAch, risk-taking propensity, locus of control and entrepreneurship’, Personality and Individual differences, vol. 6, no.6, pp.781-782. Ajzen, I 1991, ‘The theory of planned behavior’, Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211. Ajzen, I 2002, ‘Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior’, Journal of Applied Social Psychology, vol. 32, no. 4, pp. 665-683. Ajzen, I 2011, ‘The theory of planned behaviour: reactions and reflections’, Psychology and Health, vol. 26, no.9, pp.1113-1127. Aldrich, HE 1999, Organizations evolving, Sage, Thousand Oaks, CA. Aldrich, HE & Waldinger, R 1990, ‘Ethnicity and entrepreneurship’, Annual Review of Sociology, vol. 16, pp. 111-135. Aldrich, HE & Zimmer, C 1986, ‘Entrepreneurship through social networks’, in DL Sexton & RW Smilor (eds) The art and science of entrepreneurship, Balinger Publishing, Cambridge, MA, pp. 2-23. Alessandri, G & Vecchione, M 2012, ‘The higher-order factors of the Big Five as predictors of job performance’ Personality and Individual Differences, vol. 53, no. 6, pp.779-784.
240
Allen, D & Wilson, TD 2003, ‘Information overload: context and causes’, The New Review of Information Behaviour Research, pp. 31- 44. Alsos, G, Isaksen, E, & Ljunggren, E 2006, ‘New venture financing and subsequent business growth in men- and women-led businesses’, Entrepreneurship Theory and Practice, vol. 30, no.5, pp.667–686. Alvarez, SA, & Barney, JB 2005, ‘How do entrepreneurs organize firms under conditions of uncertainty?’ Journal of Management, vol. 31, no.5, pp. 776-793. Anna, AL, Chandler, GN, Jansen, E & Mero, NP 2000, ‘Women business owners in traditional and non-traditional industries’, Journal of Business Venturing, vol. 15, no. 3, pp. 279-303. Audretsch, DB, Boente, W, Tamvada, JP 2007, ‘ Religion and entrepreneurship’, Jena economic research papers, No. 2007,075, viewed 10 December 2013, <http://www.econstor.eu/bitstream/10419/25667/1/559546769.PDF>. Baker, MJ & Foy, A 2008, Business and Management Research: How to complete your research project successfully, (2nd edn), Westburn Publishers Ltd, Scotland, UK. Bal, G 2006, ‘Entrepreneurship among diasporic communities: a comparative examination of Patidars of Gujarat and Jats of Punjab’, Journal of Entrepreneurship, vol. 15, no.2, pp.181-203. Bandura, A 1977, ‘Self-efficacy: Toward a unifying theory of behavioral change’, Psychological Review, vol.84, no. 2, pp. 191-215. Bandura, A 1982, ‘Self-efficacy mechanism in human agency’, American Psychologist, vol. 37, no. 2, pp. 122-147. Bandura, A 1983, ‘Self-efficacy determinants of anticipated fears and calamities’, Journal of Personality and Social Psychology, vol. 45, pp.464-469. Bandura, A 1984, ‘Recycling misconceptions of perceived self-efficacy’, Cognitive Therapy and Research, vol. 8, no.3, pp.231-255. Bandura, A 1986, The social foundations of thought and action, Prentice Hall, Englewood Cliffs, NJ. Bandura, A 1993, ‘Perceived self-efficacy in cognitive development and functioning’, Educational psychologist, vol. 28, no.2, pp.117-148. Bandura, A 1997, Self-efficacy: the exercise of control, WH Freeman, New York. Barbosa, SD, Gerhardt, MW & Kickul, JR 2007, ‘The role of cognitive style and risk preference on entrepreneurial self-efficacy and entrepreneurial intentions’, Journal of Leadership & Organizational Studies, vol. 13, no.4, pp.86-104.
Barman, A 2013, 'Alliances of Indian management education in the vortex of globalization-excellence under triangles and quadrangles', Journal of Global Business Issues, vol. 7, no. 2, pp. 31-37. Barnett, V & Lewis, T 1994, Outliers in statistical data, 3rd edn, John Wiley & Sons, New York. Baron, RA 1998, ‘Cognitive mechanisms in entrepreneurship: why and when entrepreneurs think differently than other people’, Journal of Business venturing, vol.13, no.4, pp.275-294. Baron, RA 2000, ‘Psychological perspectives on entrepreneurship: cognitive and social factors in entrepreneurs ’successes, Current directions in psychological science, vol.4, no.1, pp.15-18. Baron, RA 2002, ‘OB and entrepreneurship: The reciprocal benefits of closer conceptual links’, Research in Organizational Behavior, vol.24, pp.225-269. Baron, RA 2007, ‘Behavioral and cognitive factors in entrepreneurship: Entrepreneurs as the active element in new venture creation’, Strategic Entrepreneurship Journal, no.1-2, pp. 167-182. Baron, RA, Byrne, D & Branscombe, NR 2005, Social Psychology, 11th edn, Allyn and Bacon, Boston. Baron, RA & Markman, GD 2000, ‘Beyond social capital: How social skills can enhance entrepreneurs’ success’, The Academy of Management Executive, vol. 14, no. 1, pp.106-116. Baron, RA & Markman, GD 2005, ‘Toward a process view of entrepreneurship: the changing relevance of individual-level variables across phases of new firm development’, in MA Rahim, RT Golembiewski & KD Mackenzie (eds), Current topics in management, vol. 9 pp. 45-64, Transaction Publishing, New Brunswick, NJ. Barrick, MR & Mount, MK 1991, ‘The Big Five personality dimensions and job performance: a meta analysis’, Personnel Psychology, vol. 44, no.1, pp. 1-26, Barrick, MR & Mount, MK 2005, ‘Yes, personality matters: moving on to more important matters’, Human Performance, vol.18, no.4, pp. 359-372. Barrick, MR, Mount, MK & Judge, TA 2001, ‘Personality and performance at the beginning of the new millennium: what do we know and where do we go next?’, International Journal of Selection and Assessment, vol. 9, no.1-2, pp.9–30. Barringer, BR & Greening, DW 1998, ‘Small business growth through geographic expansion: a comparative case study’, Journal of Business Venturing, vol. 13, no.6, pp. 467-492.
242
Barron, A 2010, ‘Unlocking the mindsets of government affairs managers: cultural dimensions of corporate political activity’, Cross Cultural Management, vol.17, no.2, pp.101-117. Bartram, D 2005, ‘The great eight competencies: a criterion-centric approach to validation’, Journal of Applied Psychology, vol. 90, no.6, pp.1185–1203. Baruch, Y 1999, ‘Response rate in academic studies-A comparative analysis’, Human relations, vol.52, no.4, pp.421-438. Baum, JR & Locke, EA 2004, ‘The relationship of entrepreneurial traits, skill, and motivation to subsequent venture growth’, Journal of Applied Psychology, vol. 89, no. 4, pp. 587-598. Baum, JR, Locke, EA & Kirkpatrick, SA 1998, ‘A longitudinal study of the relation of vision and vision communication to venture growth in entrepreneurial firms’, Journal of Applied Psychology, vol.83, no.1, pp.43-54. Baum, JR, Locke, EA & Smith, KG 2001, ‘A multidimensional model of venture growth’, Academy of Management Journal, vol. 44, pp. 292-303. Baumol, WJ 1993, ‘Formal entrepreneurship theory in economics: existence and bounds’, Journal of Business Venturing, vol. 8, no.3, pp.197-210. Bausch, A & Rosenbusch, N 2005, ‘Does innovation really matter? A meta-analysis on the relationship between innovation and business performance’, Babson Kauffman Entrepreneurship Research Conference, Babson, USA. Bawden, D 2001, ‘Information overload’, Library and information briefings, no.92, pp.1-15. Bawden, D & Robinson, L 2009, ‘The dark side of information: overload, anxiety and other paradoxes and pathologies’, Journal of information science, vol. 35, no.2, pp.180-191. Begley, TM & Boyd, DP 1987, ‘Psychological characteristics associated with performance in entrepreneurial firms and smaller businesses’, Journal of Business Venturing, vol. 2, no. 1, pp. 79-93. Besley, T & Burgess, R 2004, ‘Can labour regulations hinder economic performance? Evidence from India’, Quarterly Journal of Economics, vol. 119, pp. 91-134. Betz, N & Hackett, G 1981, ‘The relationship of career-related self-efficacy expectations to perceived career options in college men and women’, Journal of Counseling Psychology, vol. 28, no.5, pp. 399–410. Betz, N & Hackett, G 1986, ‘Applications of self-efficacy theory to understanding career choice behavior’, Journal of social and Clinical Psychology, vol. 4, no.3, pp. 279-289.
243
Bhardwaj, BR 2014, ‘Impact of education and training on performance of women entrepreneurs: a study in emerging market context’, Journal of Entrepreneurship in Emerging Economies, vol.6, no.1, pp.38-52. Bird, B. 1988, ‘Implementing entrepreneurial ideas: the case for intention’, The Academy of Management Review, vol. 13, no. 3, pp. 442-453. Bird, B 1989, Entrepreneurial behaviour, Scott, Foresman, Glenview, IL. Bird, B & Schjoedt, L 2009, ‘Entrepreneurial behaviour: its nature, scope, recent research, and agenda for future research’, In AL Carsrud & M Brannback (eds), Understanding the Entrepreneurial Mind, Springer, New York, pp. 327-358. Bird, B, Schjoedt, L & Baum, RJ 2012, ‘Editor’s Introduction. Entrepreneurs’ behavior: elucidation and measurement’, Entrepreneurship Theory & Practice, vol. 36, no. 5, pp. 889-913. Birley, S 1985, ‘The role of networks in the entrepreneurial process’, Journal of Business Venturing, vol. 1, no. 1, pp. 107-117. BITS Pilani 2014, Technology Business Incubator, BITS Pilani, viewed 2 February 2014,<http://www.bits-pilani.ac.in/pilani/technologybusiness/ TechnologyBusinessIncubator>. Blanchflower, DG 2004, 'Self-employment: more may not be better', Swedish Economic Policy Review, vol.11, no.2, pp. 15-74. Blanchflower, DG & Meyer, B, 1991, ‘Longitudinal analysis of young entrepreneurs in Australia and the United States’, National Bureau of Economic Research, Working paper No. 3746, Cambridge, MA. Blanchflower, DG & Oswald, A 1998, ‘What makes an entrepreneur?’ Journal of Labour Economics, vol.16, no.1, pp. 26-60. Bonnet, C & Furnham, A 1991, ‘Who wants to be an entrepreneur? A study of adolescents interested in a Young Enterprise scheme’, Journal of Economic Psychology, vol. 12, no.3, pp.465-478. Boone, C, Brabander, BD & Van Witteloostuijn A 1996, ‘CEO Locus of control and small firm performance: an integrative framework and empirical test’, Journal of Management Studies, vol. 33, no. 5, pp. 667-699. Borgatta, EF 1964, ‘The structure of personality characteristics’, Behavioral Science, vol.9,no.1, pp. 8-17. Borland, CM 1974, ‘Locus of control, need for achievement and entrepreneurship’, Doctoral Dissertation, University of Texas, Austin. Bouchikhi, H 1993, ‘A constructivist framework for understanding entrepreneurship performance’, Organization Studies, vol.14, no. 4, pp.549-570.
244
Boyd, NG & Vozikis, GS 1994, ‘The influence of self-efficacy on the development of entrepreneurial intentions and actions’, Entrepreneurship Theory and Practice, vol. 18, no. 4, pp. 63-77. Brandstatter, H 1997, ‘Becoming an entrepreneur – a question of personality structure?’, Journal of Economic Psychology, vol.18, no.2, pp. 157-177. BRIC Countries – Background, Latest News, Statistics and Original Articles, n.d., Global Sherpa, viewed 2 February 2014, <http://www.globalsherpa.org/bric-countries-brics>. Bridge, S, O'Neill, K & Cromie, S 2003, Understanding Enterprise: entrepreneurship and Small Business, 2nd edn, Palgrave Macmillan, New York. Brinckmann, J, Salomo, S, & Gemuenden, H 2011, 'Financial Management Competence of Founding Teams and Growth of New Technology-Based Firms', Entrepreneurship: Theory & Practice, vol. 35, no. 2, pp. 217-243. Brockhaus, RH 1975, ‘I-E locus of control scores as predictors of entrepreneurial intentions’, Proceedings of the 35th Annual Meeeting of the Academy of Management, New Orleans, Louisiana, USA, August 1975, pp. 433-435. Brockhaus, RH 1980a, ‘Psychological and Environmental Factors Which Distinguish the Successful from the Unsuccessful Entrepreneur: a Longitudinal Study’, Academy of Management Proceedings, Academy of Management, vol. 1980, no.1, pp. 368-372. Brockhaus, RH 1980b, ‘Risk taking propensity of entrepreneurs’, Academy of Management Journal, vol. 23, no. 3, pp. 509-520. Brockhaus, RH 1982, ‘The Psychology of the entrepreneur’, in CA Kent, DL Sexton and KL Vesper (eds), Encyclopedia of Entrepreneurship, Prentice-Hall, Englewoods Cliffs, NJ. Brockhaus, RH & Nord, WR 1979, ‘An exploration of factors affecting the entrepreneurial decision: personal characteristic vs. Environmental conditions’, Academy of Management Proceedings, pp. 364-368. Brockhaus, RH & Horwitz, PS 1986, ‘The Psychology of the entrepreneur’, in DL Sexton and RW Smilor (eds.), The art and science of entrepreneurship, Ballinger Publishing Company, Cambridge, MA, pp. 25-48. Brown, S 1987, ‘Drop and collect surveys: a neglected research technique’, Marketing Intelligence and Planning, vol.5, no.1, pp.19-23. Brown, TC & Hanlon, D 2004, ‘Developing behavioural observation scales to foster effective entrepreneurship’, Journal of Small Business and Entrepreneurship, vol.17, no.2, pp.103-116. Bruton, GD, Ahlstrom, D & Obloj, K 2008, ‘Entrepreneurship emerging economies: where are we today and where should the research go in the future’, Entrepreneurship Theory and Practice, vol. 32, no.1, pp.1-14.
245
Buttner, EH & Rosen, B 1988, ‘Bank loan officers’ perceptions of the characteristics of men, women, and successful entrepreneurs’, Journal of Business Venturing, vol. 3, no. 3, pp. 249-258. Bygrave, WD 1989, ‘The entrepreneurship paradigm (2): chaos and catastrophes among quantum jumps?’, Entrepreneurship Theory and Practice, vol. 14, no.2, pp.7-30. Bygrave, W & Hofer, C 1991, ‘Theorizing about entrepreneurship’, Entrepreneurship Theory and Practice, vol. 16, no. 2, pp. 3-22. Caliendo, M, Fossen, MF & Kritikos, AS 2010, ‘The impact of risk attitudes on entrepreneurial survival’, Journal of Economic Behaviour and Organization, vol. 76, no. 1, pp. 45-63. Caliendo, M, Fossen, MF & Kritikos, AS 2012, ‘Trust, positive reciprocity, and negative reciprocity: do these traits impact entrepreneurial dynamics?’, Journal of Economic Psychology, vol.33, no.2, pp.394-409. Caliendo, M, Fossen, MF & Kritikos, AS 2014, ‘Personality characteristics and the decision to become and stay self-employed’, Small Business Economies, vol. 42, no. 4, pp.787-814. Caliendo, M & Kritikos, AS 2008, ‘Is entrepreneurial success predicatable? An ex-ante of the character-based approach’, Kyklos, vol. 61, no.2, pp.189-218. Cantillon, R 1931, Essai sur la Nature du Commerce en General, (H. Higgs, Trans.). MacMillan and Co (first edition 1755), London. Carland, JW & Carland, JA 1991, “An Empirical Investigation into the Distinctions Between Male and Female Entrepreneurs and Managers”, International Journal of Small Business, vol. 9, no. 3, pp. 62-72. Carland III, JW, Carland, JW, Carland, JAC & Pearce, JW 1995, ‘Risk taking propensity among entrepreneurs, small business owners and managers’, Journal of Business and Entrepreneurship, vol. 7, no.1, pp. 12-23. Carland, JAC, Carland, JW & Stewart, WH 1999, ‘Risk taking propensity: an attribute of entrepreneurship?: a comparative analysis, Academy of Entrepreneurship Journal, vol. 5, no.2, pp. 37-50. Carland, JW, Hoy, F, Boulton, WR & Carland, JAC 1984, ‘Differentiating entrepreneurs from small business owners: A conceptualization’, Academy of Management Review, vol. 9, no. 2, pp. 354-359. Carmeli,A 2008, ‘Top management team behavioural integration and the performance of service organizations’, Group & Organization Management, vol. 33, no.6, pp.712-735. Carr, JC & Sequeira, JM 2007, ‘Prior family business exposure as intergenerational
246
influence and entrepreneurial intent: A theory of planned behaviour approach’, Journal of Business Research, vol. 60, no. 10, pp. 1090-1098. Carree, M & Thurik, AR 2010, ‘ The impact of entrepreneurship on economic growth’, In ZJ Acs & D Audretsch (eds), Handbook of Entrepreneurship Research: an interdisciplinary survey and introduction, 2nd edn, Springer, New York, pp. 557-594. Carter, NM, Gartner, WB, Shaver, KG & Gatewood, EJ 2003, ‘The career reasons of nascent entrepreneurs’, Journal of Business Venturing, vol. 18, pp. 13-39. Cassidy, T & Lynn, R 1989, ‘A multifactorial approach to achievement motivation: the development of comprehensive measure’, Journal of Occupational Psychology, vol. 62, pp.301-312. Casciaro, T 1998, ‘Seeing things clearly: social structure, personality, and accuracy in social network perception’, Social Networks, vol.20, no.4, pp.331-351. Casson, M 2005, ‘Entrepreneurship and theories of the firm’, Journal of Economic Behavior & Organization, vol. 58, no. 2, pp. 327-348. Cattell, RB 1978, The scientific use of factor analysis, Plenum, New York. Chandler, GN & Jansen, E 1992, ‘The founder's self-assessed competence and venture performance’, Journal of Business Venturing, vol. 7, no.3,pp.223-236. Chattopadhyay, R & Ghosh, A 2002, ‘Predicting entrepreneurial success: a socio-psychological study’, Journal of Entrepreneurship, vol. 11, no. 21, pp. 22 – 31. Chell, E 1985, ‘The entrepreneurial personality: a few ghosts laid to rest?’ International Small Business Journal, pp. 43-54. Chell, E 2008, The entrepreneurial personality: a social construction, 2nd edn, Routledge, East Sussex, London. Chell, E, Haworth, J & Brearley, S 1991, The entrepreneurial personality-concepts, cases and categories, Routledge, London. Chen, CC, Greene, PG & Crick, A 1998, ‘Does entrepreneurial self-efficacy distinguish entrepreneurs from managers?’, Journal of Business Venturing, vol.13, no.4, pp.295-315. Chen, CC, Gully, MS & Eden D 2001, ‘Validation of a new general self-efficacy scale’, Organizational Research Methods, vol.4, no.1, pp.62-83. Chen, CC, Gully, MS & Eden, D 2004, ‘General self-efficacy and self-esteem: toward theoretical and empirical distinction between correlated self-evaluations’, Journal of Organisational Behaviour, vol. 25, no.3, pp. 375-395.
247
Chen, XP, Yao, X & Kotha, S 2009, ‘Entrepreneur passion and preparedness in business plan presentations: a persuasion analysis of venture capitalists’ funding decisions’, The Academy of Management Journal, vol.52, no.1, pp.199-214. Child, D 1990, The essentials of factor analysis, 2nd edn, Cassel Educational Limited, London. Churchill, GA 1979, ‘A paradigm for developing better measures of marketing constructs’, Journal of Marketing Research, vol.16, pp.64-71. Ciavarella, MA, Buchholtz, AK, Riordan, CM, Gatewood, RD & Stokes, GS 2004, ‘The Big Five and venture survival: is there a linkage?’ Journal of Business Venturing, vol. 19, no.4, pp. 465-483. CIIE 2014, We inspire India’s Future Entrepreneurs, CIIE, viewed 30 January 2014, < http://www.ciieindia.org/index.php?file=about>. Collins, CJ, Hanges, PJ & Locke, EA 2004, ‘The Relationship of Achievement Motivation to Entrepreneurial Behavior: a Meta-Analysis’, Human Performance, vol. 17, no.1, pp. 95-117. Collins, CJ, Locke, EA & Hanges PJ 2000, ‘The relationship of need for achievement to entrepreneurial behaviour: a meta analysis’, Working paper, University of Maryland, College Park MD. Colombo, MG & Delmastro, M 2001, Technology-Based entrepreneurs: does internet make a difference? Small Business Economics, vol. 16, no. 3, pp. 177-190. Comrey, AL & Lee, HB 1992, A first course in factor analysis, Erlbaum, Hillsdale, New Jersey. Conger, JA & Kanungo, RN 1988, ‘The empowerment process: integrating theory and practice’, Academy of management review, vol.13, no.3, pp.471-482. Cooper, AC, Folta, TB & Woo, C 1995, ‘Entrepreneurial information search’, Journal of Business Venturing, vol. 10, no.2, pp. 107-120. Cordon, MS & Stevens, CE 2004, ‘Managing human resources in small organisations: What do we know?’ Human Resource Management Review, vol.14, pp.295-323. Costa, PT. Jr. & McCrae, RR 1992, Revised NEO Personality Inventory (NEO-PI-R) and NEO Five Factor Inventory (NEO-FFI) professional manual, Psychological Assessment Resources, Odessa, FL. Covin, JG & Slevin, DP 1989, ‘Strategic Management of small firms in hostile and benign environments’, Strategic Management Journal, vol.10, no.1, pp. 75-87. Covin, JG, & Slevin, DP 1991, ‘A conceptual model of entrepreneurship as firm behavior’ Entrepreneurship Theory and Practice, vol. 16, no. 1, pp. 7-25.
248
Covin, JG & Slevin, DP 1998, ‘Adherance to plans, risk taking, and environment as predictors of firm growth’, The Journal of Technology Management Research’, vol.9, no.2, pp.207-237. Crant, MJ 1996, ‘The proactive personality scale as a predictor of entrepreneurial intentions’, Journal of Small Business Management, vol. 34, no. 3, pp. 42-50. Cromie, S 2000, ‘Assessing entrepreneurial intentions: some approaches and empirical evidence’, European Journal of Work and Organizational Psychology, vol. 9, no. 1, pp. 7-30. Cromie, S & Johns, S 1983, ‘Irish entrepreneurs: Some personal characteristics’, Journal of Occupational Behaviour, vol. 4, no.4, pp. 317-324. Cronbach, L 1951, ‘Coefficient alpha and internal structure of tests’, Psychometrica, vol.16, no.3, pp.297-334. Dana, LP 2000, ‘Creating entrepreneurs in India’, Journal of Small Business Management, vol. 38, no.1, pp.86-91. Datta, PB & Gailey, R 2012, ‘Empowering women through social entrepreneurship: case study of a women's cooperative in India’, Entrepreneurship Theory & Practice, vol. 36, no. 3, pp. 569-587. Davidsson, P 1989 ‘Need for Achievement and Entrepreneurial Activity in Small Firms’, in KG Grunert & F Ölander (eds), Understanding Economic Behaviour, Springer, Netherlands, pp. 47–64. Davidsson, P, Low, M & Wright, M 2001 ‘Editors’ introduction: Low and MacMillan ten years on – Achievements and future directions for entrepreneurship research’, Entrepreneurship Theory & Practice, vol. 25, no. 4, pp.5-16. de Alwis, SM & Higgins, SE 2001, ‘Information as a tool for management decision making: a case study of Singapore’, Information Research, vol. 7, no. 1, viewed 9 August 2011 < http://InformationR.net/ir/7-1/paper114.html>. De Carolis, DM & Saparito, P 2006, ‘Social capital, cognition, and entrepreneurial opportunties: a theoretical framework’, Entrepreneurship Theory & Practice, vol.30, no.1, pp. 41-56. Delmar, F 2000, ‘The psychology of the entrepreneur’, In S Carter and DJ Evans (eds), Enterprise and small business: principles, practice and policy, Pearson Education, London, pp.132-154. Delmar, F & Shane, S 2003, ‘Does business planning facilitate the development of new ventures?’, Strategic Management Journal, vol.24, no.12, pp.1165-1185. DeNoble, A, Jung, D & Ehrlich, S 1999, ‘Entrepreneurial self-efficacy: the development of a measure and its relationship to entrepreneurship’, in PD Reynolds, WD Bygrave, S
249
Manigart, CM Mason, GD Meyer, HJ Sapienza and KG Shaver (eds), Frontiers of entrepreneurship research, Babson College, Wellesley, MA, pp. 73–87, DeTienne, DR & Chandler, G 2007, ‘The role of gender in opportunity identification’, Entrepreneurship Theory & Practice, vol.31, no.3, pp.365-386. Digman, JM 1990, ‘Personality structure: emergence of the five-factor model’, Annual Review of Psychology, vol. 41, no.1, pp. 417-440. Driver, MJ & Mock, TJ 1975, ‘Human Information Processing, Decision Style Theory, and Accounting Information Systems’, The Accounting Review, vol.50, no.3, pp. 490-508. Drnovsek, M & Glas, M 2002, ‘The entrepreneurial self-efficacy of nascent entrepreneurs: the case of two economies in transition’, Journal of enterprising culture, vol. 10, no. 2, pp. 107-131. Drucker, PF 1985, Innovation and entrepreneurship: practice and principles, Heinemann, London. Drucker, PF 1995, Innovation and entrepreneurship, Harper Business, London. Douglas, EJ & Shepherd, DA 2002, ‘Self-Employment as a career choice: attitudes, entrepreneurial intentions, and utility maximization’, Entrepreneurship Theory and Practice, vol. 26, no. 3, pp.81-90. Dow Jones 2010, Dow Jones emerging markets total stock market indexes, viewed 24 January 2014, <http://www.djindexes.com> Dubini, P & Aldrich, H 1991, ‘Personal and extended networks are central to the entrepreneurial process’, Journal of Business Venturing, vol. 6, no.5, pp. 305-313. Dudley, NM, Orvis, KA, Lebiecki, JE & Cortina, JM 2006, ‘A meta-analytic investigation of conscientiousness in the prediction of job performance: examining the intercorrelations and the incremental validity of narrow traits’, Journal of Applied Psychology, vol.91, no.1, pp.40-57. Durant, DE & Nord, WR 1976, ‘Perceived leader behavior as a function of personality, characteristics of supervisors and subordinates’, Academy of Management Journal, vol.19, no.3, pp.427-438. Eccles, J 1994, ‘Understanding women’s educational and occupational choices’, Psychology of Women Quarterly, vol.18, pp.585–609. Edelman, LF, Manolova, TS & Brush, CG 2008, ‘Entrepreneurship education: correspondence between practices of nascent entrepreneurs and textbook prescriptions for success’, Academy of Management Learning & Education, vol. 7, no.1, pp. 56-70.
250
Edmunds, A, & Morris, A 2000, ‘The problem of information overload in business organizations: A review on the literature’, International Journal of Information Management, vol.20, no.1, pp.17–28. Edwards, AL 1959, Edwards personal preference schedule, The Psychological Corporation, New York. Eggers, JH, Leahy, KT & Churchill, NC 1994, ‘Entrepreneurial leadership and the development of small businesses’, Paper presented at the 14th Annual Entrepreneurial Research Conference, Wellesley, MA. Elg, U, Schaumann, J & Ghauri, P 2012, ‘ Managing political actors through network partners: market-driving multinationals in emerging markets’, in A Hadjikhani, U Elg, P Ghauri (eds), Business, Society and Politics (International Business and Management, Volume 28), Emerald Group Publishing Limited, pp. 133-153. Endres, AM & Woods, CR 2006,’ Modern Theories of Entrepreneurial Behavior: a Comparison and Appraisal’, Small Business Economics, vol.26, no.2, pp.189-202. Envick, BR & Langford, M 1998, ‘Behaviors of entrepreneurs: A gender comparison’, Journal of Business and Entrepreneurship, vol. 10, no.1, pp. 106-115. Envick, BR & Luthans, F 1996, ‘Identifying the activities of entrepreneurs-managers: an idiographic approach’, Proceedings of the 3rd Annual Academy of Entrepreneurship Conference, October, Maui, Hawaii, 1996. Eppler, MJ & Mengis, J 2004, ‘The concept of information overload: a review of literature from organization science, accounting, marketing, MIS, and related disciplines’, The Information Society, vol. 20, no. 5, pp. 325-344. Epstein, S & O’Brien EJ 1985, ‘The person-situation debate in historical and current perspective’, Psychological Bulletin, vol.98, no.3, pp.513-537. Evaristo, R, Adams, C & Curley, S 1995, ‘Information Load Revisited: a Theoretical Model’ ICIS 1995 Proceedings. Paper 18, viewed 30 December 2013, <http://aisel.aisnet.org/icis1995/18> Fabrigar, LR, Wegenar, DT, MacCallum, RC & Strahan, EJ 1999, ‘Evaluating the use of exploratory factor analysis in psychological research’, Psychological Methods, vol.4, no. 3, pp.272-299. Farhoomand, AF & Drury, DH 2002, ‘Managerial information overload’, Communications of the ACM, vol.45, no.10, pp.127-131. Fastré, G & van Gils, A 2007, ‘ Competence development in entrepreneurship: the role of university education’, in MK McCuddy, H van den Bosch, WB Martz, AV Matveev & KO Morse (eds), The challenges of educating people to lead in a challenging world, Springer, Netherlands, pp. 385-398.
251
Fawzy, L & Dworski, L 2010, Emerging business online: global markets and the power of B2B internet marketing, FT Press, NewYork. Feather, J 2008, The information society: a study of continuity and change 5th edn, Facet Publishing, London. Feldman, DC & Bolino, MC 2000, ‘Career patterns of the self-employed: career motivations and career outcomes’, Journal of Small Business Management, vol. 38, no.3, pp.53-68. Forbes, DP 2005, ‘The effects of strategic decision making on entrepreneurial self-efficacy’, Entrepreneurship Theory & Practice, vol. 29, no.5, pp.599-526. Fox, RJ, Crask, MR & Kim, J 1998, ‘Mail Survey Response Rate: a meta-analysis of selected techniques for inducing response’, The Public Opinion Quarterly, vol. 52, no.4, pp. 467-491. Frank, H, Lueger, M & Korunka, C 2007, ‘The significance of personality in business start-up intentions, start-up realization and business success’, Entrepreneurship & Regional Development: An International Journal, vol.19, no.4, 227-251. Frese, M 2009, ‘Towards a psychology of entrepreneurship: an action theory perspective’, Foundations and Trends in Entrepreneurship, vol.5, pp.437-496. Furnham, A 1986, ‘Economic locus of control’, Human Relations, vol.39, no.1, pp.29–43. Galbraith, JR 1974, ‘Organization design: an information processing view’, Interfaces, vol.4, no. 3, pp.28-36. Garcia, ME, Schmitz, JM & Doerfler, LA 1990, ‘A fine-grained analysis of the role of self-efficacy in self-initiated attempts to quit smoking’, Journal of Consulting and Clinical Psychology, vol.58, no.3, pp.317-322. Gardner, DG & Pierce, JL 1998, ‘Self-esteem and self-efficacy within the organizational context: an empirical examination’, Group & Organization Management, vol. 23, no.1, pp.48-70. Gartner, WB 1985, ‘A conceptual framework for describing the phenomenon of new venture creation’, Academy of Management Review, vol.10, pp.696-706. Gartner, WB 1989, ‘Who is an Entrepreneur? Is the wrong question’, Entrepreneurship Theory & Practice, vol. 13, no.4, pp.47-68. Gartner, WB 1990, ‘What are we talking about when we talk about entrepreneurship’, Journal of Business Venturing, vol.5, pp.15-28. Gartner, WB, Carter, NM & Reynolds, PD 2010, ‘Entrepreneurial behaviour: firm organizing processes’, in Z.J. Acs, D.B. Audretsch (eds.), Handbook of
252
Entrepreneurship Research: An interdisciplinary survey and introduction, International Handbook Series on Entrepreneurship 5, Springer, New York, pp. 99-127. Gartner, WB, Bird, BJ & Starr, JA 1992, ‘Acting as if: Differentiating entrepreneurial from organizational behavior’, Entrepreneurship Theory and Practice, vol.16, no.3, pp.13–31. Gartner, WB, Shaver, KG, Carter, NM & Reynolds PD 2004, Handbook of Entrepreneurial Dynamics’, Sage, Thousand Oaks, CA. Gasse, Y 1982, ‘Elaborations on the psychology of the entrepreneur’, In CA Kent, DL Sexton and KH Vesper (eds), Encyclopaedia of Entrepreneurship, Prentice Hall, Englewood Cliff, NJ, pp.57-66. Gatewood, EJ, Shaver, KG & Gartner, WB 1995, ‘A longitudinal study of cognitive factors influencing start-up behaviors and success at venture creation’, Journal of Business Venturing, vol.10, no. 5, pp.371-391. Gaur, AS & Kumar, V 2009, ‘International diversification, business group affiliation and firm performance: empirical evidence from India’, British Journal of Management, vol.20, no.2, pp.172-186. GDP per capita 2014, The World Bank Group, viewed 5 February 2014, <http://data.worldbank.org/indicator/NY.GDP.PCAP.CD> Gibb, AA 1994, ‘Do we really teach (approach) small business the way we should?’ Journal of Business and Entrepreneurship, vol.11, no.2, pp.11-27. Gilad, BS 1982, ‘On encouraging entrepreneurship: an interdisciplinary approach’, Journal of Behavioral Economics, Vol. 11 No.1, pp.132-63. Gilad, BS 1986, ‘Entrepreneurial decision making: some behavioral considerations’ , in BS Gilad, & S Kaish, (eds),Handbook of Behavioral Economics, Volume A, Behavioral Microeconomics, JAI Press, Greenwich, CT, pp. 189-208. Gilbert, DT, McNulty, SE, Giuliano, TA & Benson, JE 1992, ‘Blurry words and fuzzy deeds: the attribution of obscure behavior’, Journal of Personality and Social Psychology, vol.62, no.1, pp.18-25. Gill, J, Johnson, P & Clarke, M 2010, Research methods for managers, 4th edn, Sage Publications Ltd, London. Gist, ME 1987, ‘Self-efficacy: implications for organizational behavior and human resource management’, Academy of Management Review, vol.12, no.3, pp.472-485. Gist, ME & Mitchell, TR 1992, ‘Self-efficacy: a theoretical analysis of its determinants and malleability’, Academy of Management Review, vol.17, no.2, pp.183–211. Global Entrepreneurship Monitor 2010, GEM 2010 Global Report, viewed 30 January 2013, <http://www.gemconsortium.org/docs/266/gem-2010-global-report>.
253
Goldberg, LR 1993, ‘The structure of phenotypic personality traits’, American Psychologist, vol. 48, no. 1, pp.26-34. Gorsuch, RL 1983, Factor Analysis, 2nd edn, Erlbaum, Hillsdale, New Jersey. Government of India 2014, India at a glance: profile, india.gov.in, National Portal of India, viewed 4 January 2014, < http://india.gov.in/india-glance/profile> Govindarajan, V 1989, 'Implementing competitive strategies at the business unit level: implications of matching managers to strategies', Strategic Management Journal, vol.10, no.3, pp.251 -270. Gray, JH 1999, ‘A predictive model of small business success’, Academy of Entrepreneurship Journal, vol. 5, no.2, pp.25-36. Habib, W M, Roni, NN & Haque, T 2005, ‘Factors affecting women entrepreneurship in India: a multivariate analysis’, Journal of Business Studies, vol.26, no.1, pp. 249-258. Haber, S & Reicheil, A 2007, ‘The cumulative nature of the entrepreneurial process: the contribution of human capital, planning and environment resources to small venture performance’, Journal of Business Venturing, vol. 22, no.1, pp.119-145. Hackett, G 1995, ‘Self-efficacy in career choice and development’, In A Bandura (ed), Self-efficacy in changing societies, Cambridge University Press, New York, pp.232-258. Hair, JFJ, Anderson, RE, Tatham, RL & Black, WC 1995, Multivariate data analysis, 4th edn, Prentice Hall, Saddle River, NJ. Hansemark, OC 2003, Need for achievement, locus of control and the prediction of business start-ups: A longitudinal study, Journal of Economic Pschology, vol. 24, no.3, pp.301-319. Harper, D 1998, ‘Institutional conditions for entrepreneurship’, Advances in Austrian Economics, vol. 5, pp. 241-275. Harris, ML, Gibson, SG & Mick, TD 2009, ‘Examining the relationship between personality and entrepreneurial attitudes: evidence from U.S. College students’. Small Business Institute Journal, vol.3, no.1, pp. 21-51. Hartog, J, Ferrer-i-Carbonell, A & Jonker, N 2002, ‘Linking measured risk aversion to individual characteristics’, Kyklos, vol.55, no.1, 3-26. Hayes, A 2013, An Introduction to mediation, moderation, and conditional process analysis: a regression-based approach,Guildford Press, New York. Hebert, RF & Link, AN 1989, ‘In search of the meaning of entrepreneurship’, Small Business Economics, vol.1, no.1, pp.39-49.
254
Hendrickson, AE & White, PO 1964, ‘Promax: a quick method for rotation to orthogonal oblique structure’, British Journal of Statistical Psychology, vol.17, no.1, pp. 65–70. Heunks, FJ 1998, ‘Innovation, creativity, and success’, Small Busienss Economics, vol.10, no.3, pp.263-272. Hisrich, R, Langan-Fox, J & Grant, S 2007, ‘Entrepreneurship Resaerch and Practice: a call to action for psychology’, vol.62, no.6, pp.575-589. Hisrich, RD, Peters, MP & Shepherd, DA 2005, Entrepreneurship, 6th edn, McGraw Hill/Irwin, New York. Hmieleski, KM & Corbett, AC 2008, ‘The contrasting interaction effects of improvisational behavior with entrepreneurial self-efficacy on new venture performance and entrepreneur work satisfaction, Journal of Business Venturing, vol. 23, no.4, pp.482-496. Holland, JL 1985, ‘Making vocational choices’, Prentice Hall, Englewood Cliffs, NJ. Holmes, TJ & Schmitz, JA 1990, ‘A theory of entrepreneurship and its application to the study of business transfers’, The Journal of Political Economy, vol. 98, no.2, pp.265-294. Hornaday, JA & Aboud, J 1971, ‘Characteristics of successful entrepreneurs, Personnel Psychology, vol. 24, pp.141-153. Hoskisson, RE, Eden, L, Lau, CM & Wright, M 2000, ‘Strategy in emerging economies’, Academy of Management Journal, vol. 43, no. 3, pp.249-267. Hozelitz, B 1960, Sociological Aspects of Economic Growth, Collier McMillan, London. Huang, Y 2008, ‘The next Asian miracle’, Foreign Policy, vol.167, pp.32-40. Hull, DL, Bosley, JJ & Udell, GG 1980, ‘Reviewing the hunt for the heffalump: identifying potential entrepreneurs by personality characteristics’, Journal of Small Business Management, vol. 18, no.1, pp.11-18. Hunter, GL 2004, ‘Information overload: guidance for indentifying when information becomes detrimental to sales forces performance’, Journal of Personal Selling & Sales Management, vol.24, no.2, pp.91-100. Hunter, GL & Goebel, DL 2008, ‘Salesperson’s information overload: scale development, validation, and its relationship to salesperson job satisfaction and performance’, Journal of Personal Selling & Sales Management, vol.28, no.1, pp.21-35. Ikoja-Odongo, JR & Ocholla, DN 2004, ‘Information seeking behavior of the informal sector entrepreneurs: the Uganda experience’, Libri, vol.54, no.1, pp.54-66.
255
Ireland, RD & Webb, JW 2007, ‘A cross-disciplinary exploration in entrepreneurship research’, Journal of Management, vol. 33, no. 6, pp. 891-927. Iselin, ER 1988, ‘The effects of information load and information diversity on decision quality in a structured decision task’, Accounting, Organizations and Society, vol.13, no.2, pp.147-164. Iselin, ER 1993, ‘The effects of the information and data properties of financial ratios and statements on managerial decision quality’, Journal of Business Finance & Accounting, vol.20, no.2, pp. 249–267. Jackson, DN 1974, Personality research form manual, 2nd edn, Research Psychologists Press, Port Huron, MI. Jacoby, J 1984, ‘Perspectives on information overload’, Journal of Consumer Research, vol.10, no.4, pp.432-435.
Javillonar, GV & Peters, G 1973, ‘Sociological and social psychological aspects of Indian entrepreneurship’, The British Journal of Sociology, vol. 24, no.3, pp. 314-328. Jennings, DF & Zeithaml, CP 1983, ‘Locus of control: a review and directors for entrepreneursial research’, Academy of Management Proceedings, Academy of Management, vol. 1983, no.1, pp.417-421. Johnson, BR 1990, ‘Towards a multidimensional model of entrepreneurship: the case of achievement motivation and the entrepreneur’, Entrepreneurship Theory and Practice, vol. 14, pp. 39–54. Judge, TA & Bono, JE 2001, ‘ Relationship of core self-evaluations traits – self-esteem, generalized self-efficacy, locus of control, and emotional stability – with job satisfaction and job performance: a meta-analysis’, Journal of Applied Psychology, vol. 86, no.1, pp.80-92. Judge, TA, Erez, A & Bono, JE 1998, ‘The power of being positive: the relation between self-concept and job performance’, Human Performance, vol. 11, no. 2-3, pp.176-187. Judge, TA, Higgins, CA, Thoresen, CJ & Barrick, MR 1999, ‘ The Big Five personality traits, general mental ability, and career success across the life span’, Personnel Psychology, vol. 52, no.3, pp. 621–652. Judge, TA, Locke, EA, Durham, CC & Kluger, AN 1998, ‘Dispositional effects on job and life satisfaction: the role of core evaluations’, Journal of Applied Psychology, vol.83, no.1, pp.17-34. Kaish, S & Gilad, B 1991, ‘Characteristics of opportunities search of entrepreneurs versus executives’, Journal of Business Venturing, vol.6, no.1, pp. 45–61.
256
Kalnins, A & Chung, W 2006, ‘Social capital, geography, and survival: Gujarati immigrant entrepreneurs in the U.S. lodging industry’, Management Science, vol.52, no.2, pp.233-247. Kanuk, L & Conrad, B 1975, ‘Mail surveys and response rates: a review’, Journal of Marketing Research, vol.12, pp. 440-453. Kassim, NA 2010, ‘Information needs of Malaysian Bumipetra would-be entrepreneurs’, Malaysian Journal of Library & Information Science, vol.15, no.2, pp. 57-69. Kaufmann, PJ & Dant, RP 1998, ‘Franchising and the domain of entrepreneurship research’, Journal of Business Venturing, vol.14, no.1, pp.5-16. Kautonen, T, van Gelderen, M & Tornikoski, ET 2013, ‘Predicting entrepreneurial behaviour: a test of the theory of planned behaviour’, Applied Economics, vol.45, no.6, pp.697-707. Keh, HT, Foo, MD & Lim, BC 2002, ‘Opportunity evaluation under risky conditions: the cognitive processes of entrepreneurs’, Entrepreneurship Theory and Practice, vol. 27, no.2, pp.125-148. Keh, HT, Nguyen, TTM & Ng, HP 2007, ‘The effects of entrepreneurial orientation and marketing information on the performance of SMEs’, Journal of Business Venturing, vol.22, no.4, pp. 592-611. Keller, KL & Staelin, R 1987, ‘Effects of quality and quantity of information on decision effectiveness’, Journal of Consumer Research, vol.14, no.9, pp.200-213. Kellermanns, FW, Eddleston, KA, Barnett, T & Pearson, A 2008, ‘An exploratory study of family member characteristics and involvement: effects entrepreneurial behavior in the family firm’, Family Business Review, vol. 21, no.1, pp.1-14. Kerlinger, FN 1986, Foundations of Behavioral Research, 3rd edn, Holt, Rinehart and Winston Inc., Orlando, Florida. Kets de Vries, MFR 1977, ‘The entrepreneurial personality: a person of the crossroads’, Journal of Management Studies, vol.14, no.1, pp.34-57. Kets de Vries, MFR 1996, ‘The anatomy of the entrepreneur: clinical observations’, Human Relations, vol.49, no.7, pp.853-883. Khanduja, D & Kaushik, P 2008, ‘Synergising entrepreneurship, incubated business and socioeconomic upliftment in rural India’, International Journal of Entrepreneurship and Small Business, vol.6, no.1, pp.68-79. Khanna, T & Palepu KG 1997, ‘Why focused strategies may be wrong for emerging markets’, Harvard Business Review, vol.75, no. 4, pp.41–51.
Khanna, T & Palepu, KG 2010, Winning in Emerging Markets: a Road Map for Strategy and Execution, Harvard Business Press, Boston, Massachusetts.
257
Kidder, L & Judd, C 1986, Research methods in social relations, 5th edn, Holt, Rinehart and Winston, New York. Kiggundu, M. 2002, ‘Entrepreneurs and entrepreneurship in Africa: what is known and what needs to be done. Journal of Development Entrepreneurship, vol. 7, no.3, pp. 239-258. Kihlstrom, RE & Laffont, JJ 1979, ‘A general equilibrium entrepreneurial theory of firm formation based on risk aversion’, The Journal of Political Economy, vol. 87, no.4, pp.719-748. Kilby, PM 1971, Entrepreneurship and Economic Development, MacMillan, New York. Kim, PH, Aldrich, HE & Keister, LA 2006, ‘Access (not) denied: the impact of financial, human, and cultural capital on entrepreneurial entry in the United States’, Small Business Economics, vol.27, no.1, pp.5–22. Kingdon, GG 2007, ‘The progress of school education in India’, Oxford Review of Economic Policy, vol. 23, no. 2, pp.168-195. Krishnan, L 2013, ‘The role of competencies and personality in determining success of entrepreneurs in SMEs in Karnataka’, International Business Management, vol.7, no.4, pp.258-266. Kirkwood, J 2009, ‘Is a lack of self-confidence hindering women entrepreneurs?’, International Journal of Gender and Entrepreneurship, vol.1, no. 2, pp.118 - 133 Kirzner, IM 1973, Competition and Entrepreneurship, University of Chicago Press, Chicago. Kirzner, IM 1985, Discovery and the Capitalist Process, University of Chicago Press, Chicago. Kirzner, IM 1999, ‘Creativity and/or alertness: a reconsideration of the Schumpeterian entrepreneur’, Review of Austrian Economics, vol.11, no.1, pp. 5-17. Klausegger, C, Sinkovics, RR & Zou, H 2007, ‘Information overload: a cross-national investigation of influence factors and effects’, Marketing Intelligence & Planning, vol.25, no.7, 691-718. Knight, FH 1971, Risk, Uncertainty and Profit, G.J. Stigler (ed), University of Chicago Press, Chicago (First edition 1921). Koellinger, P, Minniti, M & Schade, C 2007, ‘ “I think I can, I think I can”: overconfidence and entrepreneurial behavior”, Journal of Economic Psychology, vol.28, no.4, pp.502-27. Kolveried, L 1996, ‘Prediction of employment status choice intentions’, Entrepreneurship Theory & Practice, vol.21, no.1, pp.47-57.
258
Kolvereid, L & Isaksen, E 2006, ‘ New business start-up and subsequent entry into self-employment’, Journal of Business Venturing, vol. 21, no.6, pp.866-885. Kolvereid, L, Shane, S & Westhead, P 1993, ‘Is it equally difficult for female entrepreneurs to start businesses in all countries?’, Journal of Small Business Management, vol. 31, no.4, pp.42-51. Komarraju, M, Karau, S & Schmeck, R 2009, ‘Role of the Big Five personality traits in predicting college students' academic motivation and achievement’, Learning and Individual Differences, vol.19, no.1, pp.47-52. Kopple, B & Peterson, RE 1975, ‘Industrial entrepreneurship in India: a reevaluation, The Developing Economies, vol.13, no.3, pp. 318-330. Korunka, C, Frank, H, Lueger, M & Mugler, J 2003, ‘The Entrepreneurial Personality in the Context of Resources, Environment, and the Startup Process—a Configurational Approach’, Entrepreneurship Theory & Practice, vol.28, no.1, pp.23-42. Kourilsky, ML & Walstad, WB 1998, ‘Entrepreneurship and female youth: knowledge, attitudes, gender differences, and educational practices’, Journal of Business Venturing, vol.13, no.1, pp. 77-88. Krueger, NF 1993, ‘The impact of prior entrepreneurial exposure on perceptions of new venture feasibility and desirability’, Entrepreneurship Theory and Practice, vol.18, no.1, pp. 5-21. Krueger, NF 2009, ‘Entrepreneurial intentions are dead: long live entrepreneurial intentions’, in AL Casrud & M Brannback (eds), Understanding the entrepreneurial mind, Springer, New York, pp. 51-72. Krueger, NF & Brazeal, DV 1994, ‘Entrepreneurial potential and potential entrepreneurs’, Entrepreneurship Theory and Practice, vol.18, no.3, pp. 91-104. Krueger, N, Reilly, M, & Carsrud, A 2000, ‘Competing models of entrepreneurial intentions’, Journal of Business Venturing, vol.15, no.5, pp. 411–432. Kshetri, N 2009, ‘Entrepreneurship in post-socialist economies: a typology and institutional contexts for market entrepreneurship’, Journal of International Entrepreneurship, vol.7, no.3, pp. 236-259. Kuncoro A 2006, ‘Corruption and business uncertainty in Indonesia’, ASEAN Economic Bulletin, vol.23, no.1, pp.11-30. Kuratko, DF 2005, ‘The emergence of entrepreneurship education: development, trends, and challenges’, Entrepreneurship Theory & Practice, vol. 29, no. 5, pp. 577-597. Kuratko, DF & Hodgetts, RM 2001, Entrepreneurship: a contemporary approach, 5th edn, Harcourt Inc, Orlando, Fl.
259
Kuratko, DF & Hodgetts, RM 2007, Entrepreneurship: theory, process, practice, 7th edn, Thomson/South Western Publishing, Mason, OH. La Porta, R & Shleifer, A 2008, ‘The unofficial economy and economic development’, Brookings Papers on Economic Development, vol.39, no.2, pp.275-363. Landier, A, 2002, Entrepreneurship and the stigma of failure, Working paper, University of Chicago Graduate School of Business, viewed 20 September 2013, <http://www.cepr.org.uk/meets/wkcn/6/696/papers/landier2.pdf> Langan-Fox, J & Roth, S 1995, ‘Achievement-motivation and female entrepreneurs’, Journal of Occupational and Organizational Psychology, vol. 68, no.3, pp.209–218. Langowitz, N & Minniti, M 2007, ‘The entrepreneurial propensity of women’, Entrepreneurship Theory & Practice, vol. 31, no.3, pp.341-364. Lawton T & Rajwani T 2011, ‘Designing lobbying capabilities: managerial choices in unpredictable environments’, European Business Review, vol.23, no.2, pp.167-189. Lee, C 1983, ‘Self-efficacy and behavior as predictors of susequent behavior in an assertiveness training program’, Behavior Resaerch and Therapy, vol.21, no.3, pp.225-232. Lee, C 1984, ‘Accuracy of efficacy and outcome expectations in predicting performance in a a stimulated assertiveness task’, Cognitive Therapy and Research, vol.8, no.1 pp.37-48. Lee, C & Bobko, P 1994, ‘Self-efficacy beliefs: comparison of five measures’, Journal of Applied Psychology, vol.79, no.3, pp. 364-369. Lee, DY & Tsang, EWK 2001, ‘The effects of entrepreneurial personality, background and network activities on venture growth’, Journal of Management Studies, vol.38, no.4, pp.583-602. Lefcourt, HM 1966, Internal versus external control of reinforcement: A review, Psychological Bulletin, vol.65, no.4, pp.206-220. Lent, RW & Hackett, G 1987, ‘Career self-efficacy: empirical status and future directions’, Journal of Vocational Behaviour, vol.30, no.3, pp.347-382. Lévesque, M & Minniti, M 2006, ‘The effect of aging on entrepreneurial behavior’, Journal of Business Venturing, vol.21, no.2, pp.177-194. Levenson, H 1974, ‘Activism and powerful others: distinctions within the concept of internal-external control’, Journal of Personality Assessment, vol. 38, no.4, pp.377-383. Levenson, H 1981, ‘Differentiating among internality, powerful others and chance’, in H Lefcourt (eds), Research with the locus of control construct: vol 1, Assessment Methods, Academic Press, New York, pp.15-63.
260
Li, J, Zhang, Y & Matlay, H 2003, ‘Entrepreneurship in China’, Education and Training, vol. 45, no. 8/9, pp.495-505. Lichtenstein, B, Dooley, K & Lumpkin, G 2006, ‘Measuring emergence in the dynamics of new venture creation’, Journal of Business Venturing, vol.21, no.2, pp.153-175. Lipset, SM 2000, ‘Values and entrepreneurship in the Americas’, in R. Swedberg (ed), Entrepreneurship: the social science view, Oxford University Press, New York, pp. 110-128. Littunen, H 2000, ‘Entrepreneurship and the characteristics of the entrepreneurial personality’, International Journal of Entrepreneurial Behaviour, vol.6, no.6, pp. 295-309. Lumpkin, GT & Erdogan, B 2004, ‘If not entrepreneurship, can psychological characteristics predict entrepreneurial orientation? A pilot study’, The ICFAI Journal of Entrepreneurship Development, vol. 1, no.1, pp.21-33. Luthans, F, Envick, BR & Anderson, RD 1995, ‘ A proposed idiographic approach to the study of entrepreneurs’, Academy of Entrepreneurship Journal, vol. 1, no. 1, pp. 1-18. Luthans, F & Ibrayeva, ES 2006, ‘Entrepreneurship self-efficacy in Central Asian transition economies: quantitative and qualitative analysis’, Journal of International Business Studies, vol.37, no.1, pp.92-110. Low MB & MacMillan, I 1988, ‘Entrepreneurship: past research and future challenges’, Journal of Management, vol.14, no.2, pp.139-161. MacCullam, RC, Widaman, KF, Zhang, S & Hong, S 1999, ‘Sample size in factor analysis’, Psychological Methods, vol.4, no.1, pp.84-99. MacDonald, AP, Jr 1970, ‘Revised scale for ambiguity tolerance: reliability and validity’, Psychological Reports, vol. 26, no.3, pp. 791-798. Marlatt, G, Baer, JS & Quigley, LA 1995, ‘Self-efficacy and addictive behavior’, in A Bandura (eds), Self-efficacy in changing societies, Cambridge University Press, New York, pp. 289-315. Marshall, A 1930, Principles of Economics, Macmillan and Co., London (first edition 1890). Markman, GD, Balkin, D & Baron, RA 2002, ‘Inventors and new venture formation: The effects of general self-efficacy and regretful thinking’, Entrepreneurship Theory and Practice, vol.27, no.2, pp.149–165. Markman, GD & Baron, RA 2003, ‘Person-entrepreneurship fit: why some people are more successful as entrepreneurs than others’, Human Resource Management Review, vol. 13, no.2, pp.281-301.
261
Markman,GD, Baron, RA & Balkin, DB 2005, ‘Are preseverance and self-efficacy costless? Assessing entrepreneurs’ regretful thinking’, Journal of Organizational Behavior, vol.26, no.1, pp.1-19. Man, TWY, Lau, T & Chan, KF 2002, ‘The competitiveness of small and medium enterprises: a conceptualization with a focus on entrepreneurial competetence’, Journal of Business Venturing, vol.17, no.2, pp.123-142. Man, TWY, Lau, T & Snape, E 2008, ‘Entrepreneurial competencies and the performance of small and medium enterprises: an investigation through a framework of competitiveness’, Journal of Small Business and Entrepreneurship, vol.21, no.3, pp.257-276. Manimala, MJ 2008, ‘Entrepreneurship education in India: an assessment of SME training needs against current practices’ , International Journal of Entrepreneurship and Innovation Management, vol. 8, no.6, pp.624-647. Manolova, TS, Carter, NM, Manev, IM, & Gyoshev, BS 2007, ‘The differential effect of men and women entrepreneurs' human capital and networking on growth expectancies in Bulgaria’, Entrepreneurship Theory and Practice, vol.31, no.3, pp.407-426. Maurer, TJ 2001, ‘Career-relevant learning and development, worker age, and beliefs about self-efficacy for development’, Journal of Management, vol. 27, no.2, pp.123-140. Mazzarol, T 2007, ‘Different strokes for different folks – stimulating entrepreneurship in regional communities’, in Dana, LP & Anderson, RB (eds), International handbook of research on indigenous entrepreneurship, Edward Edgar, Cheltenham, UK, pp.494-507. Mazzarol, T & Reboud, S 2006, ‘The strategic decision making of entrepreneurs within small high innovator firms’, International Entrepreneurship and Management Journal, vol.2, no.2, pp.261-280. Mazzarol, T, Volery, T, Doss, N & Thein, V 1999, ‘Factors influencing small business start-ups: a comparison with previous research’, International Journal of entrepreneurial Behaviour & Research, vol.5, no.2, pp.48-63. McCarthy, B 2000, ‘The cult of risk taking and social learning: a study of Irish entrepreneurs’, Management Decision, vol.38, no.8, pp.563-575. McClelland, DC 1961, The achieving society, Van Nostrand, Princeton, N.J. McClelland, DC 1965, ‘N Achievement and Entrepreneurship: A longitudinal study’, Journal of Personality and Social Psychology, vol.1, no.4, pp. 392-396. McCrae, RR 1987, ‘Creativity, divergent thinking, and openness to experience’, Journal of Personality and Social Psychology, vol. 52, no. 6, pp.1258-1265.
262
McEwen, T 2008, ‘Environmental scanning and organizational learning in entrepreneurial ventures’, The Entrepreneurial Executive, vol.13, pp.1-16. McGee, JE, Peterson, M, Mueller, SL & Sequeira, JM 2009, ‘Entrepreneurial self-efficacy: Refining the measure’, Entrepreneurship Theory and Practice, vol.34, no.4, pp.965-988. Medhora, P 1965, ‘Entrepreneurship in India’, Political Science Quarterly, vol. 80, no.4, pp.558-580. Mehta, D & Joshi, B 2002, ‘Entrepreneurial innovations in Gujarat’, AI & Society, vol.16, no.1-2, pp.73-88. Meredith, GG, Nelson, RE & Neck, PA 1982, ‘The practice of entrepreneurship’, Geneva, International Labour Office. Milford, JT & Perry, RP 1977, ‘A methodological study of overload’, The Journal of General Psychology, vol.97, pp.131-137. Mill, JS 1848, Principles of political economy with some of their applications to social philosophy, C.C.Little & Brown, Boston. Miller, G 1956, ‘The magical number seven, plus or minus two: some limits on our capacity for processing information’, Psychological Review, vol.63, no.2, pp.81–97. Miller, H 1972, ‘Environmental Complexity and Financial Reports’, The Accounting Review, vol, 47, no.1, pp.31- 37. Miller, D, Kets de Vries, MFR & Toulouse, JM 1982, ‘Top executive locus of control, and its relationship to strategy-making, structure, and environment’, Academy of Management Journal, vol.25, no.2, pp.237-253. Miner, JB & Raju, NS 2004, ‘Risk propensity differences between managers and entrepreneurs and between low- and high-growth entrepreneurs: a reply in a more conservative vein’, Journal of Applied Psychology, vol.89, no.1, pp.3–13. Ministry of Finance n.d., Economic Survey 2005-2006, Ministry of Finance, viewed 30 January 2014, <http.indiabudget.nic.in/es2005-2006/industry.htm> Government of India 2014a, Annual Report 2006-2007, Ministry of Micro, Small and Medium Enterprises, viewed 2 February 2014, <http://msme.gov.in/WriteReadData/DocumentFile/ssi-ar-eng-2006-07.pdf>. Government of India 2014b, Annual report 2012-2013, Ministry of Micro, Small and Medium Enterprises, viewed 2 February 2014, <http://www.dcmsme.gov.in/ANNUALREPORT-MSME-2012-13P.pdf>. Mishra, N 2013, ‘The hidden growth’. The Indian Express. 6 August, viewed December 2013,<http://indianexpress.com/article/opinion/columns/the-hidden-growth/>.
263
Misra, AM 1992, ‘Entrepreneurial decline and the end of Empire: British business in India, 1919-1949’, Doctoral dissertation, University of Oxford, Oxford. Misra, AM 2000, ‘Business Culture and Entrepreneurship in India, 1860-1950’, Modern Asian Studies, vol.34, no.2, pp.333-348. Misra, PN 1987, Development Banks and the new entrepreneurship in India, National Publishing House. Mitsuhashi, H & Bird, A 2011, ‘Stigma of failure and limited opportunities for ex-failed entrepeneurs’ redemption in Japan’, in C Usui (eds), Comparative entrepeneurship initiatives: Studies in China, Japan and the USA, Palgrave Macmillan, London, pp. 222-244. Mody, A 2004, ‘What is an emerging market?’, IMF working paper no.177, pp.1-23. Moe, KO & Zeiss, AM, 1982, ‘ Measuring self-efficacy expectations for social skills: a methodological inquiry’, Cognitive Therapy and Resaerch, vol.6, no.2, pp.191-205. Morgan Stanley Capital International 2010, Index Definitions: MSCI Emerging Market (EM) Index, Morgan Stanley Capital International, viewed 2 January 2014 <http://www.mscibarra.com>. Moruku, RK 2013, ‘Does entrepreneurial orientation predict entrepreneurial behaviour?’, International Journal of Entrepreneurship, vol.17, pp.41-60. Mount, MK, Barrick, MR, Scullen, SM & Rounds J 2005, ‘Higher-order dimensions of the Big Five personality traits and the Big Six vocational interest types’, Personnel Psychology, vol. 58, no.2, pp. 447-478. Mueller, SL & Goic, S 2003, ‘East-west differences in entrepreneurial self-efficacy: implications for entrepreneurship education in transition economy’, International Journal of Entrepreneurship Education, vol. 1, no. 4, pp.613-632. Mueller, S, Volery, T & von Siemens, B 2012, ‘ What do entrepreneurs actually do? An observational study of entrepreneurs’ everyday behavior in the start-up and growth stages’, Entrepreneurship Theory & Practice, vol. 36, no. 5, pp. 995-1017. Mueller, SL & Thomas, AS 2001, ‘Culture and entrepreneurial potential: a nine country study of locus of control and innovativeness’ Journal of Business Venturing vol.16, no.1, pp. 51-75. Murphy, PJ, Liao, J & Welsh, HP 2006, ‘A conceptual history of entrepreneurial thought’, Journal of Management History, vol. 12, no.1, pp. 12-35. Murty, M 2014, ‘ “It’s true, India has emerged”: gender, class, and the entrepreneurial subject in India’s mainstream media’, Communication, Culture & Critique, vol.7, pp.210-227.
264
Naffziger, EW 1978, ‘Class, caste and entrepreneurship: a study of Indian industrialists’, The University Press of Hawaii, Honolulu. Naldi, L, Nordqvist, M, Sjöberg, K & Wiklund, J 2007, ‘Entrepreneurial orientation, risk taking, and performance in family firms’, Family Business Review, vol. 20, no.1, pp.33-47. NationMaster, 2014, NationMaster, viewed on 2 February 2014 <http://www.nationmaster.com/index.php>. Norman, WT 1963, ‘Toward an adequate taxonomy of personality attributes: replicated factor structure in peer nomination personality ratings’, Journal of Abnormal & Social Psychology, vol. 66, pp. 574-583. Nunnally, JC 1978, Pschometric Theory, 2nd edn, MacMillan, New York. Nunziata, L & Rocco, L 2011, ‘ The implications of cultural backgrounds on labour market choices: the case of religion and entrepreneurship’, IZA Discussion paper series, No 6114, Institute for the study of Labor (IZA).
Oppenheim AN 1966, Questionnaire design and attitude measurement, Heinemann, London. O’Reilly III, CA 1980, ‘Individuals and information overload in organizations: is more necessarily better?, Academy of Management Journal, vol. 23, no. 4, pp. 684-696. Osborne, JW & Overbay, A 2004, ‘The power of outliers (and why researchers should always check for them)’, Practical assessment, research & evaluation, vol.9, no.6, pp. 1-12. Ozgen, E & Baron, RA 2007, ‘Social sources of information in opportunity recognition: Effects of mentors, industry networks, and professional forums’, Journal of Business Venturing, vol.22,no.2, pp. 174-192. Oxford Dictionary 2009, The Oxford Dictionary, Oxford University Press, Oxford. Pajares, F 1997, ‘Current directions in self-efficacy research’, in M Maehr & PR Printich (eds), Advances in motivationa nd achievement, vol.10, JAI Press, Greenwich, CT, pp. 1-49. Palich, LE & Bagby, RD 1995, ‘Using cognitive theory to explain entrepreneurial risk-taking: challenging conventional wisdom’, Journal of Business Venturing, vol.10, no.6, pp. 425-438. Palmer, M 1971, ‘The application of psychological testing to entrepreneurial potential’, California Management Review, vol. 13, no.3, pp.32-38. Panagariya, A 2004, ‘Growth and Reforms during 1980s and 1990’, Economic and Political Weekly, vol. 39, no.25, pp.2581-2594.
265
Pandey, J & Tewary, NB 1979, ‘Locus of control and achievement values of entrepreneurs’, Journal of Occupational Psychology, vol. 50, no.2, pp. 107-111. Parkinson, C & Howorth, C 2008, ‘The language of social entrepreneurs’, Entrepreneurship and Regional Development, vol. 20, no. 3, pp. 285-309. Patel, VG 1987, ‘Entrepreneurship development programme in India and its relevance to developing countries’ Prepared for the Economic Development Institute of the World Bank, Washington, Entrepreneurship Development Institute of India, Ahmedabad. Peng, MW 2002, ‘Towards an institution-based view of business strategy’, Asia Pacific Journal of Management, vol.19, no.2/3, pp.251-267. Peter, PJ 1979, ‘Reliability: a review of psychometric basics and recent marketing practices’, Journal of Marketing Research, vol.16, no.1, pp.6-17. Peters, LD 2002, ‘Theory testing in social research’, The Marketing Review, vol.3, no.1, pp.65-82. Peterson, RA 1994, ‘A meta-analysis of Cronbach’s coefficient alpha’, Journal of Consumer Research, vol.21, no.1, pp. 381-391. Petrides, KV 2011, ‘A general mechanism for linking personality traits to affect, motivation, and action’, New Ideas in Psychology, vol. 29, pp.64-71. Phelps, E 2007, ‘It is all about attitude’, Newsweek International Edition, April 30. Phillips, JM & Gully SM 1997, ‘Role of goal orientation, ability, need for achievement, and locus of control in the self-efficacy and goal-setting process’, Journal of Applied Psychology, vol. 82, no. 5, pp. 792-802. Pintrich, PR & Schunk, DH 1995, ‘Motivation in education: theory, research, and applications’, Prentice Hall, Englewood Cliffs, NJ. Pistrui, D, Welsch, HP, Wintermantel, O, Liao, J & Pohl, HJ 2000, Entrepreneurial orientation and family forces in the New Germany: Similarities and Differences between East and West German Entrepreneurs, Family Business Review, vol.13, no.2, pp. 251-263. Podoynitsyna, K, Van der Bij, H & Song, M 2011, ‘The role of mixed emotions in the risk perception of novice and serial entrepreneurs’, Entrepreneurship Theory & Practice, vol. 36, no. 1, pp. 115-140. Population Total 2014, The World Bank Group, viewed 5 February 2014, <http://data.worldbank.org/indicator/SP.POP.TOTL> Prabhu, VP, McGuire, SJ, Drost, EA & Kwong, KK 2012, ‘Proactive personality and entrepreneurial intent: is entrepreneurial self-efficacy a mediator or moderator?’, International Journal of Entrepreneurial Behaviour & Research, vol. 18, no. 5, pp.559 – 586.
266
Prasad, V, Naidu, G, Kinnera Murthy, B, Winkel, D, & Ehrhardt, K 2013, 'Women entrepreneurs and business venture growth: an examination of the influence of human and social capital resources in an Indian context', Journal Of Small Business & Entrepreneurship, vol.26, no. 4, pp. 341-364. PricewaterhouseCoopers 2008, The world in 2050: Beyond the BRICs - a broader look at emerging market growth prospects, viewed on 2 August 2010, <http://www.pwc.co.uk/economics>. Rauch, A & Frese, M 2000, Psychological approaches to entrepreneurial success. A general model and an overview of findings. in CL Cooper & IT Robertson (eds), International Review of Industrial and Organizational Psychology, Wiley, Chichester, pp. 101-142. Rauch, A & Frese, M 2007a, ‘Let’s put the person back into entrepreneurship research: a meta-analysis on the relationship between business owners’ personality traits, business creation, and success’, European Journal of Work and Organizational Psychology, vol. 16, no.4, pp.353-385. Rauch, A & Frese, M 2007b, Born to be an entrepreneur? Revisiting the personality approach to entrepreneurship, in JR Baum, M Frese & R Baron (eds) The Psychology of Entrepreneurship Research, Lawrence Erlbaum Associate, Mahwah, NJ, pp. 41-65. Ravi S 2014, What drives entrepreneurship? Some evidence from India, Working paper July 2014, Brookings Institution India Center, India. Reynolds, PD 1999, ‘National panel study of U.S. business startups: background and methodology’ in JA Katz (eds), Advances in entrepreneurship: Firm emergence, and growth vol.4, JAI Press, Stamford, CT, pp.153-227. Reynolds, PD, Hay, M, Bygrave, WD, Camp, SM & Autio, E 2000 Global Entrepreneurship Monitor: 2000 Executive Report, Kaufmann Foundation, Kansas City, MO. Ripsas, S 1998, ‘Towards an Interdisciplinary Theory of Entrepreneurship’, Small Business Economics, vol. 10, no.2, pp.103-115. Robinson, PB & Sexton, EA 1994, ‘The effect of education and experience on self-employment success’, Journal of Business Venturing, vol.9, no.2, pp.141-156. Rotter, JB 1966, ‘Generalized expectancies for internal versus external locus of control of reinforcement’, Psychological Monographs, vol. 80, no. 1, pp. 1-2. Rutten, M 2001, ‘Family Enterprises and Business Partnerships: rural Entrepreneurs in India, Malaysia, and Indonesia’, Journal of Entrepreneurship, vol.10, no.2, pp.165-189. Sahin, M, Nijkamp, P & Rietdijik, M 2009, ‘Cultural diversity and urban innovativeness: personal and business characteristics of urban migrant entrepreneurs’,
267
Innovation: The European Journal of Social Science Research, vol. 22, no.3, pp.251-288. Sana, A 1993, ‘The caste system in India and its consequences’, International Journal of Sociology and Social Policy, vol. 13, no. 3/4, pp.1 – 76. Say, JB 2001, A treatise on political economy or, The production, distribution & consumption of wealth, (C.R. Prinsep, Trans), Batoche (first edition, 1803), Kitchener, Canada. Schaper, M, Volery, T, Weber, P & Lewis, K, 2011, Entrepreneurship and Small Business, 3rd eds, John Wiley & Sons Australia Ltd, Milton, Queensland. Scheré, JL 1982, ‘Tolerance of ambiguity as a discriminating variable between entrepreneurs and managers’, Academy of management proceedings, vol.1982, no.1, pp. 404-408. Scherer, R, Adam, J, Carley, S & Wiebe, F 1989, ‘Role model performance effects on development of entrepreneurial career preference’, Entrepreneurship: Theory and Practice, vol.13, no.3, pp.53-71. Schick, A., Gordon, L., and Haka, S 1990, ‘Information overload: a temporal approach’, Accounting Organizations and Society, vol. 15, no. 3, pp. 199–220. Schjoedt, L & Shaver, KG 2012, ‘Development and validation of a locus of control scale for the entrepreneurship domain’, Small Business Economics, vol. 39, no.3, pp. 713-726. Schultz, TW 1975, ‘The value of the ability to deal with disequilibria’, Journal of Economic Literature, vol. 13, no.3, pp. 827-46. Schultz, TW 1980, ‘Investment in entrepreneurial ability’, Scandinavian Journal of Economics, vol. 82, no.4, pp. 437-448. Schultze, U & Vandenbosch, B 1998, ‘Information overload in a groupware environment: now you see it, now you don’t’, Journal of Organizational Computing and Electronic Commerce, vol. 8, no.2, pp.127–148. Schumpeter, JA 1934, The Theory of Economic Development. Harvard University Press (First edition 1911), Cambridge, Mass. Schumpeter, JA 1942, Capitalism, Socialism and Democracy, Harper and Row, New York. Seligman, M 1990, Learned Optimism, Knopf , NY. Sexton, DL & Bowman, NB 1986, ‘Validation of a personality index: comparative psychological characteristics analysis of female entrepreneurs, managers, entrepreneurship students, and business students’, in R Ronstadt, R Peterson, & KH
268
Vesper, eds., Frontiers of Entrepreneurship Research. Wellesley, MA: Boston Center for Entrepreneurial Studies, pp. 40-51. Shane, S 2000, ‘Prior knowledge and the discovery of entrepreneurial opportunities’, Organization Science, vol. 11, no.4, pp.448–469. Shane, S, Locke, EA & Collins, CJ 2003, ‘Entrepreneurial motivation’, Human Resource Management Review, vol. 13, no.2, pp. 257-279. Shane, S & Venkataraman, S 2000, ‘The promise of entrepreneurship as a field of research’, The Academy of Management Review, vol. 25, no.1, pp. 217-226. Shapero, A 1977, ‘ The displaced, uncomfortable entrepreneur’, Psychology Today, vol. 9, no.6, pp. 83-88. Shapero, A 1982, ‘Social dimensions of entrepreneurship’, in C Kent, D Sexton, & K Vesper (eds), The encyclopedia of entrepreneurship, Englewoods Cliffs, NY, Prentice Hall, pp. 72-90. Shapiro, C & Varian, HR 1999, Information Rules: a strategic guide to the network economy, Harvard Business School Press, Boston, MA. Sharma, K.L & Singh, H 1980, Entrepreneurial growth and development programmes in Northern India: a sociological analysis, Abhinav Publications, New Delhi. Sharma, P & Chrisan, JJ 1999, ‘Toward a reconciliation of the definitional issues in the field of corporate entrepreneurship’, Entrepreneurship Theory and Practice, vol. 23, no. 3, pp. 11-28. Shaver, KG 2003. ‘The Social Psychology of Entrepreneurial Behaviour’. In ZJ Acs and DB Audretch (eds), Handbook of Entrepreneurship Research. Kluwer Acadmic Publishers, Great Britain, pp. 331-357. Shaver, KG & Scott, LR 1991, ‘Person, process, and choice: the psychology of new venture creation’, Entrepreneurship Theory and Practice, vol. 16, no. 2, pp. 23-45. Shelton, SH 1990, ‘Developing the construct of general self-efficacy’, Psychological Reports, vol. 66, pp.987-994. Shenk, D 1997, Data smog. Surviving the information glut, Abacus, London. Shepherd, DA, Douglas, E & Shanley, M 2000, ‘New venture survival: ignorance, external shocks, and risk reduction strategies’, Journal of Business Venturing, vol. 15, no. 5, pp.393-410. Sherer, M, Maddux, JE, Mercadante, B, Prentice-Dunn, S, Jacobs, B & Rogers, RW 1982, ‘The self-efficacy scale: construction and validation’, Psychological Reports, vol. 51, pp.663–671.
269
Shivani, S, Mukherjee, SK & Sharan, R 2006, ‘Socio-cultural influences on Indian entrepreneurs: the need for appropriate structural interventions’, Journal of Asian Economics, vol.17, no.1, pp.5-13. Shook, CL, Priem, RL & McGee, JE 2003, ‘Venture creation and the enterprising individual: a review and synthesis’, Journal of Management, vol. 29, no.3, pp.379-399. Simon, HA 1971,‘Designing organizations for an information rich world’, in M Greenberger, (ed), Computers, Communications and The Public Interest, John Hopkins Press, Baltimore, MD. SINE 2013, Society of Innovation and Entrepreneurship, SINE, viewed 30 January 2013 <http://www.sineiitb.org/>. Singal, A & Jain, AK 2012, ‘Outward FDI trends from India: emerging MNCs and strategic issues’, International Journal of Emerging Markets, vol.7, no.2 pp. 443-456. Singer, M 1966, ‘Religion and Social Change in India: The Max Weber Thesis Phase Three’, Economic Development and Cultural Change, vol.14, pp.497–505. Singh, RP & Lucas, LM 2005, ‘Not just domestic engineers: an exploratory study of homemaker entrepreneurs’, Entrepreneurship Theory and Practice, vol. 29, no.1, pp. 79-90. Sirmon, DG & Hitt, MA 2003, ‘Managing resources: linking unique resources, management and wealth creation in family firms’, Entrepreneurship Theory and Practice, vol.27, no.4, pp.339–358. Sitkin, SB & Weingart, LR 1995, ‘Determinants of risky decision-making behavior: a test of the mediating role of risk perceptions and propensity’, Academy of Management Journal, vol. 38, no. 6, pp. 1573-1592. Smeltzer, LR, van Hook, BL & Hutt, RW 1991, ‘Analysis of the use of advisors as information sources in venture startups’, Journal of Small Business Management, vol.29, no.3, pp. 10-20. Smilor, RW 1997, ‘Entrepreneurship reflections on a subversive activity’, Journal of Business Venturing, vol. 12, no.5, pp. 341-346. Smith, NR & Miner JB 1985, ‘Motivational considerations in the success of technologically innovative entrepreneurs: extended sample findings’, in J Hornaday, E Shile, J Timmons & K Vesper, (eds), Frontiers of entrepreneurship research vol.4, Babson College, Wellesley, MA, pp. 488-495. Spector, PE 1982, 'Behavior in organizations as a function of employee's locus of control', Psychological Bulletin, vol. 9, no. 1, pp. 482-489. Speier, C, Valacich, JS, & Vessey, I 1999, ‘The influence of task interruption on individual decision making: an information overload perspective. Decision Sciences, vol. 30, no.2, pp.337–359.
270
Spira, JB 2011, Overload! How too much information is hazardous to your organisation, John Wiley & Sons, Hoboken, NJ. Srivastav, N & Syngkon, RAJ 2008, ‘Emergence of small scale industries and entrepreneurship in the rural area of Northeastern states of India: an analytical approach’, The ICFAI University Journal of Entrepreneurship Development, vol.5, no.2, pp.6-22. Stajkovic, AD & Luthans, F 1998, ‘Self-efficacy and work-related performance: a meta-anlaysis’, Psychoological Bulletin, vol. 124, no. 2, pp. 240-261. Stevenson, HH, Roberts, MJ & Grousbeck, HI 1985, New business ventures and the entrepreneur, Richard D. Irwin, Burr Ridge, IL. Stewart, WH, May, RC & Kalia, A 2008, ‘Environmental perceptions and scanning in the United States and India: Convergence in entrepreneurial information seeking?’, Entrepreneurship Theory & Practice, vol. 32, no.1, pp. 83-106. Stewart, WH & Roth, PL 2001 ‘Risk propensity differences between entrepreneurs and managers: A meta-analytic review’, Journal of Applied Psychology, vol. 86, no. 1, pp. 145 –153. Stewart, WH & Roth, PL 2004. ‘Data-quality affects meta-analytic conclusions: a response to Miner and Raju (2004) concerning entrepreneurial risk propensity’, Journal of Applied Psychology, vol. 89, no.1, pp. 14 – 21. Stewart, WH, Jr & Roth, PL 2007, ‘A meta-analysis of achievement motivation. Differences between entrepreneurs and managers’, Journal of Small Business Management, vol. 45, no.4, pp. 401-421. Stewart, WH, Jr, Watson, WE, Carland, JC, Carland, JW 1999, ‘A proclivity for entrepreneurship: A comparison of entrepreneurs, small business owners, and corporate managers’, Journal of Business Venturing, vol. 14, no.2, pp. 189-214. Surge in foreign direct investment in developing countries reverses global downturn, 2005, UNCTAD (United Nations Conference on Trade and Development), UNCTAD/PRESS/PR/2005/034, 29/09/05, viewed 1 October 2011, <http://archive.unctad.org/Templates/Webflyer.asp?docID=6334&intItemID=6180&lang=1> Swain, MR & Haka, SF 2000, ‘Effects of information load on capital budgeting decisions’, Behavioral Research in Accounting, vol.12, pp.171–199. Sykes, A 1993, An introduction to regression analysis, Chicago Working Paper in Law and Economics, University of Chicago Law School, viewed 4 October 2012, <http://www.law.uchicago.edu/Lawecon/WkngPprs_01-25/20.Sykes.Regression.pdf>. Tang, J & Tang, Z 2007, ‘The relationship of achievement motivation and risk-taking propensity to new venture performance: a test of the moderating effect of
271
entrepreneurial munificence’, International Journal of Entrerpeneurship and Small Business, vol.4, no.4, pp. 450-472. Thandi, HS & Dini, K 2010, ‘Unleasing ethinic entrepreneurship: proactive policy-making in a changing Europe’, International Journal of Business and Globalisation, vol.4, no.1, pp.35-54. Thandi, H & Sharma, R 2004, ‘MBA students' preparedness for entrepreneurial efforts’, Tertiary Education and Management, vol. 10, pp. 209-226. The Registrar General & Census Commissioner, 2011, Religious composition, Ministry of Home Affairs, Government of India, viewed 20 January 2014, < http://censusindia.gov.in/Census_Data_2001/India_at_glance/religion.aspx> The World Factbook 2013a, Central Intelligence Agency, viewed 5 February 2014, <https://www.cia.gov/library/publications/the-world-factbook/> The World Factbook 2013b, Central Intelligence Agency, viewed on 2 February 2014, <https://www.cia.gov/library/publications/the-world-factbook/geos/in.html> Thomas, AS & Mueller, SL 2000, ‘A case for comparative entrepreneurship: assessing the relevance of culture’, Journal of International Business Studies, vol. 31, no. 2, pp. 287-301. Thompson, JL 1999, ‘A strategic perspective of entrepreneurship’, International Journal of Entrepreneurial Behaviour & Research, vol.5, no.6, pp.279-296. Timmons, JA 1978, ‘Characteristics and role demands of entrepreneurship’, American Journal of Small Business, vol. , pp.5–17. Timmons, JA 1994, New Venture Creation:Entrepreneurship for the 21st Century. Burr Ridge, IL, Irvin. Timmons, JA, Smollen, LE & Dingee, ALM 1985, New Venture Creation, 2nd edn, Irwin, Homewood, IL. Tkalac Verčič, A, Verčič, D & Sriramesh, K 2012, ‘Internal communication: definition, parameters, and the future’, Public relations review, vol.38, no.2, pp.223-230. Tornikoski, ET & Newbert, SL 2007, ‘Exploring the determinants of organizational emergence: a legitimacy perspective’, Journal of Business Venturing, vol. 22, pp. 311-335. Tripathi, D 1971, ‘Indian Entrepreneurship in Historical Perspective: a Re-interpretation’, Economic and Political Weekly, vol.6, no.22, pp.M59-M66. Tripathi, D, 1981, The dynamics of a tradition: Kasturbhai Lalbhai and his entrepreneurship, Manohar, New Delhi.
272
Tripathi, D 1992 ‘Indian business houses and entrepreneurship: a note on research trends’, Journal of Entrepreneurship, vol. 1, no.1, pp. 75-97. Tushman, M & Nadler, D 1978, ‘Information processing as an integrating concept in organizational design’, Academy of Management Review, vol. 3, pp. 613-624. Urban, B 2010, ‘Cognitions and motivations for new venture creation decisions: linking expert decisions: linking expert scripts to self-efficacy, a South African study’, The International Journal of Human Resources Management, vol. 21, no.9, pp.1512-1530. Utsch, A & Rauch, A 2000, ‘Innovativeness and initiative as mediators between achievement orientation and venture performance’, European journal of work and organizational psychology, vol. 9, no.1, pp. 45-62. van den Brink, F, Koch, B, Ardts, J & van Lankveld, J 2004, Wat heeft de Kramer in zijn mars? De rol van persoonlijkheidskenmerken bij verschillende typen ondernemerschap, GITP, Tilburg, The Netherlands. van der Veen, JH 1976, ‘Commercial Orientation of Industrial Entrepreneurs in India’, Economic and Political Weekly, vol.11, no.35, pp.M91-94 van Praag, MC 1999, ‘Some classic views on entrepreneurship’, De Economist, vol. 147, no. 3, pp. 311-335. van Praag, MC & Versloot, PH 2008, ‘The economic benefits and costs of entrepreneurship: a review of the research’, Foundations and Trends in Entrepreneurship, vol. 4, no.2, pp. 65-154. van Praag, MC 2005, Successful entrepreneurship: confronting economic theory with empirical evidence, E.Elgar, Northampton, MA. van Zandt, T 2001, ‘Information overload in a network of targeted communication’ INSEAD Working Paper 2001/36/EPS. Viewed 30 December 2013, <http://ged.insead.edu/fichiersti/inseadwp2001/2001-36.pdf> Vasumathi, A, Govindarajulu, S, Anuratha, EK & Amudha, R 2003, ‘Stress and coping styles of an entrepreneur: An empirical study’, Journal of Management Research, vol.3, no.1, pp.43-51. Vecchio RP 2003, ‘Entrepreneurship and leadership: common trends and common threads’, Human Resource Management Review, vol. 13, no. 2, pp. 303–327. Vickery, BC & Vickery A 1987, Information science in theory and practice, Butterworth, London. Vinchur, AJ, Schippmann, JS, Switzer, FSI & Roth, PL 1998, ‘A meta-analytic review of predictors of job performance for salespeople’, Journal of Applied Psychology, vol. 83, no. 4, pp. 586-597.
273
Vodden, K, Miller, A & McBride, J 2001, ‘Assessing the business information needs of aboriginal entrepreneurs in British Columbia’, Report: western Economic Diversification Canada and the BC Ministry of Small Business, Tourism and Culture. Simon Fraser University, Community Economic Development Centre, Canada. von Thünen, JH 1960, ‘The isolated state in relation to agriculture and political economy’, in BM Dempsey (ed.) The Frontier Wage, vol. 2, Loyola University Press, London, pp.197-368. Wagener, S, Gorgievski, M & Rijsdijk, S 2010, ‘Businessman or host? Individual difference between entrepreneurs and small business owners in the hospitality industry’, The Service Industries Journal, vol. 30 no. 9, 1513-1527. Ward, EA 1997, ‘Multidimensionality of achievement motivation among employed adults’, Journal of Social Psychology, vol.137, no.4, pp.542-544. Watson, J 2007, ‘Modeling the relationship between networking and firm performance’, Journal of Business Venturing, vol. 22, no.6, pp. 852-874. Webb J 2000, ‘Questionnaires and their design’, The Marketing Review, vol.1, no.2, pp. 197-218. Weber M1958, The religion of India: the sociology of Hinduism and Buddism, The Free Press, Glencoe. Welsch, HP & Young, EC 1982, ‘The information source selection decision: the role of entrepreneurial personality characteristics’, Journal of Small Business Management, vol. 20, no. 4, pp. 49-57. Westhead, P, Ucbasaran, D, Wright, M & Binks, M 2005, Novice, serial and portfolio entrepreneur behaviour and contributions, Small Business Economics, vol. 25, no. 2, pp. 109-132. Wetherbe, JC 1991, ‘Executive information requirements: getting it right’, MIS Quarterly, vol.15, no.1, pp.51-61. Wennekers, S & Thurik, R 1999, ‘Linking entrepreneurship and economic growth’, Small Business Economics, vol.13, no.1, pp. 27-56. Williams, CC & Gurtoo, A 2013, ‘ Beyond entrepreneurs as heroic icons of capitalist society: a case study of stree entrepreneurs in India’, International Journal of Entrepreneurship and Small Business, vol. 19, no. 4, pp.421-437. Wilson, F, Kickul, J & Marlino, D 2007, ‘Gender, entrepreneurial self-efficacy, and entrepreneurial career intentions: implications for entrepreneurship education’, Entrepreneurship Theory and Practice, vol. 31, no. 3, pp. 387-406. Wong, PK, Ho, YP & Autio, E 2005, ‘Entrepreneurship, innovation and economic growth: evidence from GEM data’, Small Business Economics, vol. 24, no. 3, pp. 335-350.
274
Wood, R & Bandura, A 1989a, ‘ Social cognitive theory of organizational management’, Academy of Management Review, vol. 14, no. 3, pp. 361-384. Wood, R & Bandura, A 1989b, ‘Impact of conceptions of ability on self-regulatory mechanisms and complex decision making’, Journal of personality and social psychology, vol. 56, no. 3, pp.407-415. Wooten, W 1991, ‘The effects of self-efficacy on job acceptance behaviour among American college students’, Journal of Employment Counseling, vol. 28, no. 2, pp.41-48. Wortman, MS 1987, ‘Entrepreneurship: an integrating typology and evaluation of the empirical research in the field’, Journal of Management, vol. 13, no.2, pp. 259-279. Wright, M, Filatotchev, I, Hoskisson, RE &Peng, MW 2005, ‘Strategy research in emerging economies: challenging the conventional wisdom’, Journal of Management studies, vol.42, no.1, pp.1-33. Zahra, SA 2007, ‘Contextualizing theory building in entrepreneurship research’, Journal of Business Venturing, vol. 22, no. 3, pp. 443-452. Zeithaml, VA 2000, ‘Service quality, profitablity, and the economic worth of customers: what we knowand what we need to learn’, Journal of the Academy of Marketing Science, vol.28, no.1, pp.67-85. Zhao, H & Seibert, SE 2006, ‘The big five personality dimensions and entrepreneurial status: a meta-analytical review’, Journal of Applied Psychology, vol. 91, no. 2, pp. 259-271. Zhao, H, Seibert, SE & Hills, GE 2005, ‘The mediating role of self-efficacy in the development of entrepreneurial intentions’, Journal of Applied Psychology, vol. 99, no. 6, pp. 1265-1272. Zhao, H, Seibert, SE & Lumpkin, GT 2010, ‘The relationship of personality to entrepreneurial intentions and performance: a meta-analytic review’, Journal of Management, vol. 36, no. 2, pp. 381-404.
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APPENDICES Appendix A.1
Ethics Approval from the Swinburne’s Human Research Ethics Committee (SUHREC), Swinburne University of Technology
SUHREC Project 2012/005 Ethics Clearance
From: Kaye Goldenberg <[email protected]> To: [email protected] Cc: Nadine White <[email protected]> Date: 2/7/2012 2:00 PM To: Dr Malcolm Abbott, FHEL/ Ms Manisha Karia [BC: Ms Manisha Karia] CC: Ms Nadine, White, Research Admin. Co-ordinator, FHEL Dear Dr Abbott, SUHREC Project 2012/005 Entrepreneurial self-efficacy and entrepreneurial performance: The moderating role of Information Overload Dr Malcolm Abbott, FHEL/ Ms Manisha Karia Approved Duration: 07/02/2012 To 07/02/2013 [Adjusted] I refer to the ethical review of the above project protocol undertaken on behalf of Swinburne's Human Research Ethics Committee (SUHREC) by SUHREC Subcommittee (SHESC4) at a meeting held on 20 January 2012. Your response to the review as e-mailed on 6 February 2012 was reviewed by a SHESC4 delegate. I am pleased to advise that, as submitted to date, the project has approval to proceed in line with standard on-going ethics clearance conditions here outlined. - All human research activity undertaken under Swinburne auspices must conform to Swinburne and external regulatory standards, including the National Statement on Ethical Conduct in Human Research and with respect to secure data use, retention and disposal. - The named Swinburne Chief Investigator/Supervisor remains responsible for any personnel appointed to or associated with the project being made aware of ethics clearance conditions, including research and consent procedures or instruments approved. Any change in chief investigator/supervisor requires timely notification and SUHREC endorsement.
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- The above project has been approved as submitted for ethical review by or on behalf of SUHREC. Amendments to approved procedures or instruments ordinarily require prior ethical appraisal/ clearance. SUHREC must be notified immediately or as soon as possible thereafter of (a) any serious or unexpected adverse effects on participants and any redress measures; (b) proposed changes in protocols; and (c) unforeseen events which might affect continued ethical acceptability of the project. - At a minimum, an annual report on the progress of the project is required as well as at the conclusion (or abandonment) of the project. - A duly authorised external or internal audit of the project may be undertaken at any time. Please contact me if you have any queries about on-going ethics clearance. The SUHREC project number should be quoted in communication. Chief Investigators/Supervisors and Student Researchers should retain a copy of this e-mail as part of project record-keeping. Best wishes for the project. Yours sincerely Kaye Goldenberg Secretary, SHESC4 ******************************************* Kaye Goldenberg Administrative Officer (Research Ethics) Swinburne Research (H68) Swinburne University of Technology P O Box 218 HAWTHORN VIC 3122 Tel +61 3 9214 8468
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Appendix A.2
SUHREC Project 2012/005 Final Report Acknowledgment
To: Ms Manisha Karia cc Assoc Prof Malcolm Abbott, FBE Dear Manisha SUHREC Project 2012/005 Entrepreneurial self-efficacy and entrepreneurial performance: The moderating role of Information Overload Revised Project Title: The Influence of Entrepreneur Personality and Self-Efficacy on Behavioural Activities in the Presence of Information Overload Dr Malcolm Abbott, FHEL/FBE; Ms Manisha Karia Approved Duration for Human Research Activity: 07/02/2012 To 07/02/2013 I confirm receipt of progress/final reports on the human research activity conducted for the above project in line with ethics clearance conditions issued. Best wishes for your higher degree submission. Yours sincerely Keith --------------------------------------------------------------------- Keith Wilkins Secretary, SUHREC & Research Ethics Officer Swinburne Research (H68) Swinburne University of Technology P O Box 218 HAWTHORN VIC 3122 Tel +61 3 9214 5218 Fax +61 3 9214 5267
APPENDIX A.3 QUESTIONNAIRE PARTICIPANT CONSENT INFORMATION SHEET
FACULTY OF BUSINESS AND ENTERPRISE SWINBURNE UNIVERSITY OF TECHNOLOGY
Consent Information Statement
PROJECT TITLE: Entrepreneurial self-efficacy and entrepreneurial performance: The moderating role of Information Overload PRINCIPAL INVESTIGATOR(S): Ms.Manisha Karia, Doctoral student, Swinburne University of Technology, under the supervision of Associate Professor Malcolm Abbott, Associate Dean (Research), Swinburne University of Technology. WHAT IS THE STUDY ABOUT? The aim of the study is to identify how the performance of entrepreneurs is influenced by various factors such as personality characteristics, their self-confidence, and information availability. The study is particularly focused on entrepreneurs from emerging countries. You are invited to participate in this study by filling in the questionnaire enclosed with the consent information statement. WHY IS THE STUDY IMPORTANT? The current study focuses on entrepreneurial self-efficacy, entrepreneurial personality and will examine its relationship on entrepreneurial behavioural activities in the context of emerging markets. This study is important because: a) the focus is on understanding practicing entrepreneurs, b) theories developed in mature economies are examined for their relevance and application in emerging markets, and c) it helps in understanding the role of entrepreneurial information overload in the entrepreneur’s ability to perform their activities. WHAT IS THE RESEARCHER’S INTERESTS? This study is undertaken to wholly satisfy the requirements for my doctoral studies. In the process, I would share my findings through publication in journals and other forums relating to academic and professional bodies. WHAT DOES THE STUDY INVOLVE? Participation in the study involves filling in a questionnaire. This questionnaire has seven sections. For the most part, you will be required to tick or circle the options provided. Further, there is an opportunity, at the end of the questionnaire, to make any comment that you feel is relevant to the study. WHAT IS THE TIME COMMITMENT? Should you agree to participate, the completion of this questionnaire would take approximately 30 minutes of your time. There is no other commitment involved. WHAT ARE THE PARTICIPANT’S RIGHTS AND INTERESTS Your participation in this survey is voluntary. You are free to not answer any question that you feel uncomfortable about, and you may withdraw from the study at any time. Your
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identity will be kept confidential and anonymous. The data collected through this survey will be kept secure. You may seek clarification on any of the questions mentioned in the survey instrument. A summary of the research results will be made available to you, should you wish to see it. If you would like a copy of these findings, you can email me on [email protected]. By completing the questionnaire it will be deemed that you have given consent to participate in this research. WILL ALL DATA PROVIDED BE CONFIDENTIAL? You will not be required to give your name or identify yourself in the questionnaire. Data will be stored separately in a locked filing cabinet. No information about any individual will be given to Swinburne University of Technology, or to any other individual or organisation. All processed data will be stored electronically with password protection. Only the researcher Manisha Karia and her supervisors will have access to the data. The purpose of the study is to better understand entrepreneurs as a population and therefore you will not be identified individually. Data will be analysed and reported on an aggregate (group-level) basis only. Individual responses will not be analysed or reported, therefore individuals will not be identifiable. WHAT WILL BE THE RESEARCH OUTCOMES? This research is undertaken as part of the requirement for completion of the degree of PhD, hence will lead to publication of thesis. Findings from this project may also be shared with other academics through presentations in professional and academic bodies. They may also be published in academic journals. Your anonymity will be preserved and will not be identified in publications. HOW DO I TAKE PART IN THE STUDY? If you would like to participate in this research, please complete the questionnaire. Further information about the project – who to contact If you would like further information about the project, please do not hesitate to contact my supervisor: Dr Malcolm Abbott, Associate Dean (Research), Faculty of Higher Education Swinburne University of Technology, Lilydale Campus on 00 61 3 9215 7306 or at [email protected] Concerns/complaints about the project – who to contact: This project has been approved by or on behalf of Swinburne’s Human Research Ethics Committee (SUHREC) in line with the National Statement on Ethical Conduct in Human Research. If you have any concerns or complaints about the conduct of this project, you can contact:
Research Ethics Officer, Swinburne Research (H68), Swinburne University of Technology, P O Box 218, HAWTHORN VIC 3122.
Tel (03) 9214 5218 or +61 3 9214 5218 or [email protected] Please retain this sheet for your records.