b.a. (university of queensland) a thesis submitted …...needs theory (bpnt), in which the...

First Principles at Work; Self Determination Theory and the Mechanism of

Organismic Integration over Individual Dispositions in Entrepreneurship

Graham Fellows

B.A. (University of Queensland)

A thesis submitted in fulfilment of the requirements of the degree of Master of Business

Australian Centre for Entrepreneurship Research

School of Management, QUT Business School

Queensland University of Technology

2016

Abstract

ii

Abstract

Previous research on individual dispositions in entrepreneurship as well as motivation

theories have guided hypotheses regarding the relationship between individual dispositions

in the entrepreneurship domain (risk-taking propensity, innovativeness and proactivity) and

dichotomous motivation states (intrinsic and extrinsic) to entrepreneurial performance. This

thesis examines the individual disposition-entrepreneurial performance relationship in

comparison to a motivation-entrepreneurial performance perspective. Two sub-theories of

self-determination theory (basic psychological needs and organismic integration theories)

were applied to evaluate the mechanism that would best predict entrepreneurial

performance. Data from 385 Australian business owners were obtained in a cross-sectional

study. Structural equation modelling tested two differential process paths that lead to

entrepreneurial performance. First, the relationship between individual dispositions and

entrepreneurial performance was tested. Second, a process path of basic psychological need

satisfaction in the entrepreneurial context (competence, autonomy, and relatedness)

leading to a range of autonomous motivation states (intrinsic, integrated and identified), in

conjunction with controlled motivation (introjected and extrinsic), was proposed and tested.

Autonomous and controlled motivation had direct effects on entrepreneurial performance,

and autonomous motivation factors mediated the effects of the satisfaction of basic

psychological needs on entrepreneurial performance. Furthermore, the autonomous-

controlled motivation mechanism was more predictive of entrepreneurial performance than

individual dispositions in entrepreneurship.

Statement of Original Authorship

iii

Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet requirements

for an award at this or any other higher education institution. To the best of my knowledge

and belief, the thesis contains no material previously published or written by another

person except where due reference is made.

Graham Fellows

September 2016

QUT Verified Signature

Table of Contents

iv

Table of Contents

Abstract ................................................................................................................................................ ii

Statement of Original Authorship .........................................................................................................iii

Table of Contents .................................................................................................................................. iv

Chapter 1: Introduction ........................................................................................................................ 1

Research aim, model and approach .................................................................................................. 4

Theoretical framework ..................................................................................................................... 5

Chapter 2: Literature on Entrepreneurship and Self-Determination .................................................... 9

Entrepreneurial Performance ......................................................................................................... 11

Individual Dispositions in Entrepreneurship ................................................................................... 16

Risk-taking propensity ................................................................................................................. 23

Innovativeness ............................................................................................................................ 26

Proactivity ................................................................................................................................... 28

Individual Entrepreneurial Orientation ....................................................................................... 29

Self Determination Theory .............................................................................................................. 30

Basic Psychological Needs Theory ................................................................................................... 35

Satisfaction of the Need for Competence ................................................................................... 36

Satisfaction of the Need for Autonomy ...................................................................................... 39

Satisfaction of the Need for Relatedness .................................................................................... 42

Organismic Integration Theory ....................................................................................................... 45

Organismic Integration Principles ............................................................................................... 47

Basic Psychological Needs and Organismic Integration .............................................................. 50

Organismic Integration and Entrepreneurial Performance ......................................................... 55

The Mediated Relationship between BPNT, OIT and EP ............................................................. 58

Chapter 3: Methodology ..................................................................................................................... 63

Procedure ....................................................................................................................................... 64

Participants ................................................................................................................................. 65

Measures .................................................................................................................................... 67

Chapter 4: Results ............................................................................................................................... 71

Data Cleaning and Assumption Testing Procedures ........................................................................ 71

Assessment of Normality ............................................................................................................ 71

Table of Contents

v

Missing Data ............................................................................................................................... 72

Common Method Variance ......................................................................................................... 73

Correlations .................................................................................................................................... 75

Preliminary Analyses ....................................................................................................................... 79

Data Analysis ............................................................................................................................... 79

Confirmatory Factor Analysis of the Individual Entrepreneurial Orientation Scale ......................... 80

Confirmatory Factor Analysis of Basic Psychological Needs ............................................................ 82

Confirmatory Factor Analysis of the Motivation at Work Scale ...................................................... 84

Structural Models ........................................................................................................................... 85

IEO-EP Path Model ...................................................................................................................... 86

BPNT-OIT-EP Path Model ............................................................................................................ 88

Path Model Comparison ............................................................................................................. 93

Chapter 5: Discussion.......................................................................................................................... 96

Theoretical Implications ................................................................................................................ 101

Practical Implications .................................................................................................................... 104

Limitations .................................................................................................................................... 106

Conclusion .................................................................................................................................... 109

Reference List ................................................................................................................................... 110

APPENDIX 1: RESEARCH VARIABLES, DESCRIPTIVE STATISTICS AND CORRELATIONS ................. 137

Chapter 1: Introduction

1


Entrepreneurship research has been described as the “scholarly examination of how, by

whom, and with what effects, opportunities to create future goods and services are

discovered, evaluated, and exploited” (Shane & Venkataraman, 2000, p. 218). Underlying

the how, who, what and why of the entrepreneurship phenomenon is a complex decision

process, involving a heterogeneous group of people influenced by individual dispositions

and driven by various motivations. Many scholars have examined the individual dispositions

of entrepreneurs (Shane, 1993; Lumpkin & Dess, 1996; Baum, Locke, & Smith, 2001; Baum &

Locke, 2004; Kuratko, 2005; Cardon, Wincent, & Singh, 2005, 2009; Lau, Shaffer, Chan &

Man, 2012) and their relationship to entrepreneurial performance (Stewart and Roth, 2001,

2004; Baum & Locke, 2004; Collins, Hanges, & Locke, 2004; Rauch & Frese, 2007). Other

researchers have looked at entrepreneurial motivation (Kuratko, Hornsby, & Naffziger,

1997; Shane, Locke, & Collins, 2003; Baum, & Locke, 2004; Segal, Borgia, & Schoenfeld,

2005; Delmar & Wiklund, 2008). However, little research has investigated the

intrinsic/extrinsic nature of that motivation (Amabile, 1997; Cassar, 2004; Carsrud &

Brännback, 2011) and none has examined the range of controlled motivation explained by a

sub-theory of self-determination theory (SDT), namely organismic integration theory (OIT).

Individual dispositions have been studied by entrepreneurial researchers as causes of

entrepreneurial performance (EP), however early research found only weak effects

(Gartner, 1985; Aldrich & Wiedenmayer, 1993). Later research has found moderate effects

(Baum & Locke, 2004; Collins, Hanges, & Locke, 2004; Rauch & Frese, 2007) however, there

still exist dissenting views in the literature as to the existence, strength, or causal validity of


2

the relationships (Amit, Glosten & Muller, 1993; Shaver, 1995; Davidsson, 2007; Gartner,

2007). The mixed results are surprising because entrepreneurs and venture capitalists very

consistently discuss the importance of individual dispositions in terms of their relationship

with positive EP. Further, there is no study that holistically explains the mechanism behind

individual dispositions and their relationship with EP. Identifying the factors underlying a

person’s choice to pursue the creation of a new venture, or their potential to successfully

fulfil the requirements of operating and growing a new venture, is beneficial to

entrepreneurs, investors and the economy, given recent global innovation initiatives.

The dominant psychological model of the relationship between intrinsic and extrinsic

motivation has suggested mutual exclusivity, an antagonism; that were extrinsic motivation

for an activity to increase, intrinsic motivation for the activity is thereby decreased (Deci,

1971; Lepper, Greene, & Nisbett, 1973; Lepper & Greene, 1978, 2015; Deci & Ryan, 1985).

While motivation research has often viewed extrinsic motivation as generally resulting in

negative outcomes (de Charms 1968; Deci, 1971, 1975; Lepper, Greene & Nisbett, 1973;

Deci & Ryan, 1985; Deci, Koestner, & Ryan, 1999), other studies have shown that extrinsic

motivation can result in adaptive behaviour and improved performance (Eisenberger &

Cameron, 1996; Eisenberger, Pierce, & Cameron, 1999; Ryan & Deci, 2000). Most activities a

person undertakes are driven for extrinsic reasons (Bidee, Vantilborgh, Pepermans,

Huybrechts, Willems, Jegers, & Hofmans 2013) but of themselves may provide significant

intrinsic value in developing accompanying interest, pleasure, self-expression, or satisfaction

in meeting personal challenges.


3

This study investigates two process paths to determine which process best describes the

relationship between individual dispositions and EP. The first process path involves an

examination of the relationship between individual dispositions in entrepreneurship (also

known as individual entrepreneurial orientation (IEO)) and EP. The uncertainty around the

IEO-EP relationship represents a consensus gap in the literature and forms the basis for the

first research question, ‘Is there a relationship between the individual dispositions of

entrepreneurs and entrepreneurial performance?’ The extant literature regarding this

relationship is largely atheoretic, positing no clear theoretical mechanisms that explain the

relationship between specific dispositions and performance.

The second process path involves an examination of two mechanisms described by two sub-

theories of SDT (Deci & Ryan, 2000). The first mechanism is described by basic psychological

needs theory (BPNT), in which the satisfaction of three basic needs (the needs for

competence, autonomy and relatedness) is predicted to lead to increased levels of

autonomous motivation (intrinsic, integrated and identified motivation). A second

mechanism, described by a second SDT sub-theory, OIT, predicts that entrepreneurs with

higher levels of autonomous motivation (intrinsic, integrated and identified motivation), in

conjunction with controlled motivation (introjected and extrinsic motivation), will exhibit

increased levels of entrepreneurial performance. There are no prior studies investigating

this BPNT-OIT-EP relationship in the entrepreneurship domain. This represents the second

gap in the literature and forms the basis for the second research question, ‘Is the degree of

motivation to entrepreneurship deterministic of entrepreneurial performance?’ The third

gap in the literature, and the third research question, relate to whether ‘the BPNT-OIT-EP


4

relationship is more predictive of entrepreneurial performance than individual dispositions

(IEO-EP) amongst entrepreneurs?’

Research aim, model and approach

This thesis is based on the premise that the venture decision process is motivationally

driven. For example, if two hypothetical identical ventures were formed based on identical

resources and the same new venture idea with all things being equal, by two different

entrepreneurs with different degrees of autonomous and controlled motivation, the

ventures are likely to experience different outcomes; the motivation is an important driver

of the outcomes achieved.

This thesis explores the foundational proposition that the satisfaction of the basic

psychological needs for competence, autonomy and relatedness, leads to greater

internalisation of external regulation, resulting in increased autonomous motivation. The

BPNT-OIT relationship is introduced as the mechanism by which autonomous and controlled

motivation lead to EP. The degree to which the three basic psychological needs (BPNT) are

satisfied, determines the degree to which integration of identified or integrated motivation,

or intrinsic motivation, occur. In turn, this integration (within oneself) of the autonomous

motivation factors, in conjunction with controlled motivation, predicts EP. Thus, BPNT and

OIT together provide an explanation of the role of motivation in predicting variation in EP,

and the empirical means by which we can identify whether the BPNT-OIT-EP relationship is

more predictive of EP than IEO variables.


5

Theoretical framework

This thesis incorporates self-determination theory (SDT), and Deci and Ryan’s (1985) sub-

theories of basic psychological needs theory (BPNT: which states that autonomy,

competence, and relatedness are basic psychological needs, and are essential to well-being

and performance) and organismic integration theory (OIT: which explains how we

internalise external factors, turning them into motivators or de-motivators). With

internalisation, that is, increased autonomous motivation, these factors become more

motivating. If these factors stay externalised, they may become demotivating.

BPNT posits that the satisfaction of the basic psychological needs of competence, autonomy

and relatedness is essential for optimal performance and if any need is hindered,

performance will be diminished. OIT posits that there are various degrees of externally

regulated motivation (from extrinsic to introjected, identified, and integrated motivation).

Extrinsic and introjected motivation are the controlled forms of motivation, i.e. external to

the person, and autonomous motivation types are internalised forms of external motivation

(which involves identification, and in its highest form, integration) together with intrinsic

motivation (the highest form of internal motivation). OIT further maintains that progress

along this continuum (i.e. internalisation of higher level motivation states) is possible only if

the basic psychological needs of competence, autonomy and relatedness are fulfilled (Ryan

& Deci, 2000). The general relationship of the constructs of individual dispositions (IEO),

BPNT, OIT and EP are shown in a conceptual model depicted in Figure 1.1.


6

Figure 1.1: Conceptual model of BPNT-OIT and IEO related to EP.

The study builds upon self-determination theory (Deci & Ryan, 1985), answers a call from

Carsrud and Brännback (2011, p. 19) for future research on understanding how internal and

external motivations impact entrepreneurial performance, and uses Gagné & Deci’s (2005)

theoretical model of organismic integration. The study proposes and tests the underlying

mechanism (BPNT-OIT) that leads entrepreneurs to exhibit individual dispositions and

achieve entrepreneurial performance. The study further investigates if this mechanism is

more predictive of EP than individual disposition variables. To empirically test these

mechanisms, a sample of 385 business owners recorded in an Australian business database

owned by Survey Sampling International, completed the Individual Entrepreneurial

Orientation (IEO), Basic Psychological Needs (BPNS) and Motivation at Work (MAWS)

questionnaires in conjunction with a series of entrepreneurial performance measures.

Satisfaction of

Basic Psychological

Needs

Autonomous

Motivation

Controlled

Motivation

Entrepreneurial

Performance

Individual

Dispositions

(IEO)


7

This study is important because it addresses uncertainty in the literature about the presence

and strength of individual dispositions in relation to entrepreneurial outcomes. The thesis

contributes to the entrepreneurship literature by explicating the process of regulation and

integration of motivation in entrepreneurs, and more holistically explains the mechanism

underlying individual dispositions and their relationship to entrepreneurial performance.

The theoretical contribution gives back to the psychology literature by evaluating the

application of self-determination theory, particularly organismic integration theory, in

another setting; a setting that has not yet been examined previously.

The study has relevance for venture capitalists who are responsible for high-risk lending

decisions involving the assessment of individuals and teams with the potential to improve

the probability of higher returns on new venture investments; encouraging training,

experience and involvement in entrepreneurship networks, events, incubators, accelerators

and co-working spaces. The thesis provides an understanding of how the assimilative quality

of autonomous regulation may encourage the adoption of an elevated entrepreneurial

mindset within the aspiring entrepreneurial population, which is particularly relevant in a

global economic climate that actively encourages the general population, and Science,

Technology, Engineering and Mathematics (STEM) students in particular, to

entrepreneurship. This thesis argues that analysis of motivation regulation, whilst distal to

entrepreneurial outcomes, is fundamental to entrepreneurship and constitutes the first port

of call in understanding the complex relationship of persona-motivation-intention-

behaviour-action-outcomes.


8

The next chapter proceeds as follows. First, the thesis introduces EP and establishes the

common dependent EP variables for measurement within the entrepreneurship literature.

The multidimensional EP measures most commonly used in the literature are identified and

evaluated. The thesis continues by reviewing the research that has examined the impact of

individual dispositions on EP. The main focus of that review is on the meta-analytic studies

that have been conducted. Self-determination, autonomous motivation and controlled

motivation are then reviewed within the entrepreneurship and psychology literature.

Finally, the underlying mechanism of the relationship between individual dispositions and

entrepreneurial performance is described through the lens of self-determination theory.

The thesis then proceeds with a discussion of the methodology in chapter 3. The results are

presented in chapter 4. The study concludes with a discussion of the findings in Chapter 5.

Chapter 2: Literature on Entrepreneurship and Self-Determination

9


The literature review commences with an introduction of entrepreneurial performance (EP)

and an overview of the dominant representation of EP as a dependent variable in the

entrepreneurship literature. In order to understand where we are going with the review of

the literature we start with the end in mind. EP constitutes the common dependent variable

in the two process paths being analysed in this study. These two process paths, and their

relationship with EP, are investigated and compared in order to examine which process path

is more predictive of performance in the entrepreneurship domain.

The first process path (see Individual Dispositions in Entrepreneurship) involves an

examination of the relationship between individual dispositions in entrepreneurship,

identified as IEO (risk-taking propensity, innovativeness and proactivity) and EP. Prior

analysis of the relationship between individual dispositions and EP has involved a history of

debate as to the veracity and/or relevance of the relationship with EP. This approach

represents the first gap in the literature identified in this study and forms the basis for the

first research question, ‘Is there a relationship between individual dispositions in

entrepreneurship and entrepreneurial performance?’

The second process path (see Self Determination Theory) involves an examination of two

mechanisms described by two sub-theories of self-determination theory (SDT: Deci & Ryan,

2000). The first mechanism is described by basic psychological needs theory (BPNT), in

which the satisfaction of three basic needs (the needs for competence, autonomy and

relatedness) is predicted to lead to increased levels of internalised types of motivation. A


10

second mechanism, described by a second SDT sub-theory, organismic integration theory

(OIT), predicts that entrepreneurs with higher levels of internalised motivation will exhibit

higher levels of entrepreneurial performance. There are no prior studies investigating this

relationship in the entrepreneurship domain. This represents the second gap identified in

the literature. This gap forms the basis for the second research question, ‘Is the degree of

motivation to entrepreneurship deterministic of entrepreneurial performance?’ This in turn

leads to the third research question, ‘Is this underlying mechanism more predictive of

entrepreneurial performance than individual dispositions amongst entrepreneurs?’

The BPNT-OIT-EP relationship is introduced as the mechanism by which individuals’

motivation is determinant of entrepreneurial performance. The degree to which the three

basic psychological needs (BPNT; for competence, autonomy and relatedness) are satisfied,

determines the degree to which autonomous motivation (identified, integrated or intrinsic

motivation) occurs. In turn, the degree to which autonomous motivation (organismic

integration) occurs predicts entrepreneurial performance (EP). BPNT and OIT provide an

explanation of the role of motivation in predicting variation in EP. The BPNT-OIT-EP has not

been previously studied and gives ground for the third gap identified in the literature

(whether the BPNT-OIT-EP relationship is more predictive of EP than IEO). This novel

contribution to the literature is particularly useful for entrepreneurs, entrepreneurship

educators, policy planners and investors as it can be seen that entrepreneurial performance

is not dependent upon individual dispositions, as much as it can be predicted by the degree

to which the basic needs for competence, autonomy and relatedness are satisfied in the

entrepreneurship context, and the subsequent types of motivation experienced by

entrepreneurs.


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In order to establish an understanding of the entrepreneurial outcomes by which these

processes are measured, and in order to be able to make a baseline comparison between

the two processes (IEO-EP and BPNT-OIT-EP) the review first establishes the common

dependent EP variables for measurement. With this goal in mind, the study identifies and

evaluates the multidimensional measures commonly used in the literature. The dependent

variable EP measures that are most consistently represented in the literature are then

introduced. These EP measures include objective performance measures of firm net profit

(Firm$) and personal income (Indiv$), and a subjective performance measure of career

satisfaction (CarSat).

Entrepreneurial Performance

Entrepreneurial performance (EP) is multidimensional (Delmar, 1999), with research

investigating antecedents to entrepreneurial performance having used different

performance variables (Mayer-Haug, Read, Brinckmann, Dew, & Grichnik, 2013). The review

of the literature has found a range of potential indicators of performance, including

objective measures (not influenced by personal feelings or opinions) and subjective

performance measures (involving personal perspective, feelings and/or beliefs) (see

Venkatraman and Ramanujam, 1985, 1986; Chaganti and Schneer, 1994; Zou, Chen, Ghauri,

2010; Mayer-Haug et al., 2013). Performance variables in this study distinguish different

performance effects.


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Objective performance measures identified in entrepreneurship research include

assessments of growth (McKelvie & Wiklund, 2010; Delmar, McKelvie, & Wennberg, 2013),

firm sales (Schoonhoven, Eisenhardt, & Lyman, 1990; Carter, Gartner, & Reynolds, 1996),

employee numbers, acquisitions and investment, profit, return on investment (ROI) and

return on assets (ROA) (Davidsson, Delmar, & Wiklund, 2006). Some studies conceptually or

empirically treat growth as a dependent variable with independent variables explaining

variance in the growth outcomes. Other studies treat growth as a process rather than as an

independent or dependent variable (McKelvie & Wiklund, 2010). Baum and Locke (2004)

chose venture growth as the dependent variable for their study, measured as (a) the

compound annual sales-growth rate and (b) the compound annual employment-growth

rate, from year-end A to year-end B, over the course of a six-year longitudinal study. Baum

and Locke chose these two items due to venture growth being a firm-level outcome that

reflects personal and market performance gains (Kirzner, 1985; Baum & Locke, 2004).

However, the limitations of a cross-sectional study impede the ability to objectively measure

such growth longitudinally. In place of growth, an outcome of entrepreneurship that can be

statically measured is profit, at both the individual and the firm level.

At the individual level, and this being an individual level study, the evaluation of personal

income is a relevant measure (Davidsson, 2009). After-tax income represents the amount of

disposable income that an individual has to spend on present consumption or on future

investments. Disposable personal income is often measured nationally as one of the many

key economic indicators used to evaluate the overall health of national economies. There is

a risk associated with the measurement of this variable though; due to the human

propensity to minimise personal taxation obligations it may be difficult to ascertain a true


13

representation of individual income as an accurate and independent measure of

entrepreneurial career performance. Irrespectively, self-reported personal income is

fundamental to the national taxation system and an important indicator of personal and

national financial health. Personal income is therefore an important measure of economic

impact, personally and nationally, in terms of entrepreneurial performance.

At the firm level, ventures are commonly evaluated according to their profit success and

those operating at high net profit ratios are often publicly celebrated. Firm profit is not only

important for operational sustainability, and tax revenues, but also for people considering

starting new ventures (Baumol, 1990) and for personal motivation decisions (Weitzel, Urbig,

Desai, Sanders, & Acs, 2010). Total sales have also been commonly measured in the

literature, however they are largely an indication of gross profit and not necessarily an

indicator of operational efficiency. Sales reflect only one half of the equation of gross profit,

not yet taking into account the cost of goods sold nor operational costs. If the firm were to

spend more in making sales than the sales income it receives, even though those sales may

be spectacular, the firm might be operating at a loss (not accounting for companies using

their revenue to aggressively invest in new products, assets and acquisitions). For this

reason, and in addition to individual net profit, firm net profit is considered a

complementary indicator of entrepreneurial performance (notwithstanding the possibility

of unidentified and unmeasured team and/or co-founder contributions) because firm-level

outcomes reflect personal performance gains (Kirzner, 1985; Baum & Locke, 2004). Firm net

profit is therefore an appropriate measure of entrepreneurial performance in sustainable,

margin-focused, and profit oriented ventures.


14

Key subjective measures used in the literature include self-ratings of success, career

satisfaction (Greenhaus, Parasuraman & Wormley, 1990) and/or life satisfaction (Diener,

Emmons, Larsen, & Griffin, 1985). Within the context of subjective measures of

entrepreneurial performance, EP was conceived by Rauch & Frese (2000) using the Giessen-

Amsterdam Model as “meeting goals, economic success, life style success (e.g., prestige,

satisfying work, contributing to a cause), growth, and others.” According to Davidsson

(2009) an individual level study would ideally relate individual dispositions to individual level

outcomes such as changes in motivation, goal achievement, personal financial success and

satisfaction. In Rauch and Frese’s (2007) meta-analysis of the relationship between

individual dispositions and entrepreneurial performance, ‘business success’ was variably

measured as subjective assessment of non-financial success measures, which included self-

ratings of career satisfaction. Career satisfaction is therefore a consistently applied, self-

report measure of entrepreneurial performance and is deterministically related to an

individual’s own sense of performance.

Additional subjective performance measures have included growth and profit orientations.

Entrepreneurs who want their firm to grow, and intend to hire additional employees, have

started their businesses to achieve something, more so than other business owners. The

Panel Study of Entrepreneurial Dynamics (PSED) research program, a widely reported large

scale longitudinal study, measures such growth aspirations in terms of both venture size and

profit, using subjective self-report measures (Reynolds & Curtin, 2008). Venture size

preference is evaluated as a preference between having a business that is ‘as large as

possible’ versus one which can be managed ‘myself or with a few key employees.’ Profit

preference is evaluated as one that provides ‘a good living, but with little risk of failure, and


15

little likelihood of making you a millionaire’ versus a business that is ‘much more likely to

make you a millionaire but has a higher chance of going bankrupt.’ However, these

measures are aspirational and not outcome based. Whilst treated in the literature as

outcome variables they are more likely to bear an indirect relationship with entrepreneurial

performance by influencing the intended future outcome/s of the venture (Cassar, 2006).

Subjective performance measures such as growth and/or profit orientations, although they

are likely predictors of future EP, they are not reliable measures of actual entrepreneurial

performance.

To best capture the heterogeneity that exists across performance effects and their

associated measures, this study investigates multiple dimensions of entrepreneurial

performance. This review establishes that EP is most effectively measured using both

objective and subjective measures. Accordingly, the study operationalizes three static

entrepreneurial performance items in two dimensions (financial and non-financial

performance). The financial performance dimension, profit, involves a measure of firm net

profit (Firm$) and personal income (Indiv$). Further, a dimension for a non-financial

performance measure is included. In this category, career satisfaction (CarSat) measures the

satisfaction associated with the entrepreneurial journey, and includes elements of goal

attainment and achievement motivation satisfaction. With previous research having found

that meaningful differences in entrepreneurial performance are accounted for by individual

disposition variables (Rauch & Frese, 2007; Mayer-Haug et al., 2013; Frese & Gielnik, 2014),

the next section proceeds to examine the individual disposition variables that are

established in the entrepreneurship literature as the most dominant antecedent

dispositions to entrepreneurial performance.


16

Individual Dispositions in Entrepreneurship

The role that individual dispositions play in shaping entrepreneurial performance has been

the focus of a large volume of research (see Stewart & Roth, 2001; Collins, Hanges, & Locke,

2004; Rauch & Frese, 2007; Rauch, Wiklund, Lumpkin & Frese, 2009; Rosenbusch, Rauch, &

Bausch 2013). This literature is characterised by uncertainty about the presence and

strength of individual dispositions in relation to entrepreneurial outcomes. There have been

mixed results in terms of the effect of personality traits on business success. Some reviews

conclude that there is a positive relationship between personality traits and business

success (Chell, Haworth, & Brearley, 1991; Cooper, Gimeno-Gascon, & Woo, 1992; Caird,

1993; Naffziger, 1995; Stewart & Roth, 2001; Collins, Hanges, & Locke, 2004; Baum & Locke,

2004; Rauch & Frese, 2007). Other studies conclude that there is no such relationship

(Gasse, 1982, p. 66; Sandberg, 1986; Aldrich and Zimmer, 1986; Brockhaus & Horwitz, 1986;

Begley & Boyd, 1987; Low & MacMillan, 1988; Bird & Jelinek, 1988; Gartner, 1989;

Timmons, 1990; Guth, Kumaraswamy, & McErlean, 1991; Shaver & Scott, 1991; Amit,

Glosten & Muller, 1993; Gartner, 2007).

This review briefly introduces the contrasting views of individual dispositions in the

entrepreneurship domain. An examination of the meta-analytic findings for the relationship

between individual dispositions and entrepreneurial performance follows. The thesis

proceeds with a history of the uncertainty about the presence and strength of individual

dispositions in relation to entrepreneurial performance. The uncertainty expressed in the

literature is then balanced with empirical evidence that establishes the most prevalent


17

individual dispositions identified within the literature and their relationship with

entrepreneurial performance.

The literature is characterised by uncertainty regarding the presence, strength and

relevance of individual dispositions in the entrepreneurship domain. Reflecting on the mixed

research, Davidsson (1989) contends that a range of organisational, process, market and

environmental factors are more deterministic of new venture creation than stable, innate

personal characteristics. He argues that the inclusion of individual dispositions “would not

have more than a marginal effect on our ability to explain variations in growth aspirations”

(p. 224). This view assumes that individual dispositions in entrepreneurship are inborn,

unlearned, enduring and/or permanent. The view is also related to new venture creation

(nascent ventures) rather than ongoing business functioning and long-term business

success.

Furthermore, Gartner (1989) and Aldrich (1999), ten years apart in the literature discourse,

were both critical of the notion that there exists a measurable relationship between

individual dispositions and business success. Both authors favoured the idea that

personality traits are not reliable predictors of whether people will act in a particular way in

a particular situation (Ajzen, 1988; Kenrick & Funder, 1988). Gartner proposed an improved

research design, by empirically testing selected samples of individuals before they become

involved in creating new enterprises, focussing on nascent entrepreneurs, so that causality

can be more clearly identified. Aldrich resolved that research on the relationship between

personality traits and entrepreneurial performance had reached an empirical impasse.

These views have been criticised for being based on narrative reviews only (Rauch & Frese,


18

2007). Uncertainty about the presence, strength and/or relevance of individual dispositions

in the entrepreneurship domain remains a current argument.

In contrast, there is consensus within the literature in which researchers recognise that

entrepreneurship is dependent upon the ability to identify new venture ideas (Davidsson,

2015), and act on those ideas by deciding and organizing innovative combinations of

resources for the principal purposes of capital, social or environmental gain (e.g. Kirzner,

1983; Stevenson & Jarillo, 1990; Wiklund, 1998; Shane, 2003; Ardichvili, Cardozo, Ray, 2003;

Sarasvathy, Dew, Velamuri, 2003; McMullen, Plummer, Acs, 2007). As much as

organizational, process, market or environmental factors are significant in the

entrepreneurial process, the ability to navigate these factors and strategize for success

within and around them depends upon the person, their motivational drivers, and their

subsequent behaviour in the form of decisions made and actions taken (Shane, 2003).

This represents a juxtaposition between common author views that on one hand,

organisational, process, market and environmental factors are more deterministic of new

venture development than personal characteristics, whereas it is recognised that the ability

to navigate these factors is dependent upon the individual, their motivation and their

behaviour. Positive entrepreneurial performance will therefore most likely be achieved by

people with an orientation to the venture tasks inherently related to that end. An

orientation to those venture tasks is a direct manifestation of the person’s motivation to

perform those tasks. Individual dispositions that reflect a person’s motivation and

orientation to entrepreneurial venture tasks would therefore be expected to have a

relationship with entrepreneurial performance, particularly once a business is established.


19

Not only is there debate in the literature as to the significance of individual dispositions

related to the tasks of entrepreneurship, there further exists debate as to whether those

individual dispositions are innate or whether they can be learned. Fisher and Koch (2008)

believe that entrepreneurs are born, not made. They seek to dispel the idea that anyone

can be an entrepreneur, stating that the results of their study of 234 Chief Executive Officers

(CEOs) show entrepreneurs are different from corporate managers, and different from the

general population – they argue that this difference is hereditary. They base this on Canli’s

(2006) assertion, in his work on the biology of personality and individual differences, that

there is a biological basis for temperament, and McCrae’s (2004, p. 6) argument that the

source of personality traits is “solely biological.” Shane (2010), a prominent

entrepreneurship author, also takes this approach. Shane argues that genes influence

whether a person will start a business and that they may be deterministic of entrepreneurial

performance.

Whilst a person might start a business with certain strengths of individual dispositions, or an

absence of them, this thesis argues that through assimilation of external influences the

motivation to behave entrepreneurially is not innate nor permanent; the most appropriate

behaviours with which a person can succeed in the entrepreneurship domain can be learned

due to factors of perceived competence, autonomy and relatedness. Motivation and

associated dispositions are adapted and developed. SDT provides a substantively different

point of view to the ‘born not made’ argument, which could be explored in future studies.

There are five meta-analyses of individual dispositions within entrepreneurship research

that provide empirical evidence of relationships between individual dispositions and


20

entrepreneurial performance measures. Rauch & Frese’s (2007) meta-analysis is the most

comprehensive meta-analysis to date that addresses identifiable individual disposition

variables in entrepreneurship. The meta-analysis involved the combination of studies that

matched individual dispositions to entrepreneurship and ‘business success’ (in comparison

to studies that did not match individual dispositions to venture tasks). The meta-analysis

consisted of 116 independent samples from 104 different articles, 54 of which tested the

relationships between owners’ traits and business success. ‘Business success’ included

organizational performance measures of financial outcomes, such as accountant-based

measures and average annual employment growth (objective measures), and nonfinancial

success measures such as self-ratings of success and satisfaction (subjective measures).

Rauch and Frese’s results indicate that traits that are relevant to business operation tasks

produced higher correlations with business performance, r = .250, K = 42, N = 5607, than

traits that were not relevant to business operation tasks, r = .028, K = 13, N = 2777 (r =

sample mean correlation, K = number of studies, N = total number of observations). The

traits matched to entrepreneurship that were significantly related to entrepreneurial

performance were innovativeness, proactive personality, need for autonomy, need for

achievement, generalized self-efficacy and stress tolerance.

Findings from this, and a further four meta-analyses of the entrepreneurship-personality

literature (Stewart & Roth, 2001; Collins et al., 2004; Rauch & Frese, 2007; Rauch et al.,

2009; Rosenbusch et al., 2013) predict the relationship of specific individual dispositions to

entrepreneurial outcomes. Stewart and Roth (2001) compare the risk-propensity within

growth-orientated entrepreneurs, income orientated entrepreneurs and managers; Collins

et al. (2004) focus on the need for achievement and its relationship to entrepreneurial


21

performance; Rauch et al. (2009) analyse entrepreneurial orientation and business

performance at the firm level; and Rosenbusch et al. (2013) examine how firms adjust their

entrepreneurial orientation to external influences (individual level cognition translating to

firm level behaviour), to improve entrepreneurial performance. A summary of these meta-

analyses is shown in Table 2.1.

Table 2.1.

Individual dispositions (IDs) related to business performance.

Individual dispositions r K N Study

Risk Propensity .10 13 1,744 Rauch & Frese (2007)

Risk (growth oriented entrepreneurs) .33 3 1,093 Stewart & Roth (2001)

Innovativeness .27 7 800 Rauch & Frese (2007)

Proactiveness .27 5 678 Rauch & Frese (2007)

Entrepreneurial orientation .26 73 17,935 Rosenbusch et al. (2013)

.24 53 14,259 Rauch et al. (2009)

Need for achievement .30 31 4,115 Rauch & Frese (2007)

.26 28 3,218 Collins, Hanges & Locke (2004)

Need for autonomy .16 8 843 Rauch & Frese (2007)

Generalised Self-efficacy .25 11 1,331 Rauch & Frese (2007)

Locus of control .13 23 3,959 Rauch & Frese (2007)

Note: K = number of studies, N = total number of observations, r = mean correlation

The most extensive of these meta-analyses involve the study of entrepreneurial orientation

(EO; Rauch et al., 2009; Rosenbusch et al., 2013). The EO meta-analyses had an overlap of

41 papers (within a total of 126). Therefore, EO was the focus of a total of 85 related

studies, constituting one-third (39.7%) of all studies within the five meta-analyses. EO is a

firm level construct that reflects individual level factors. EO was conceptualised by Lumpkin

and Dess (1996, p. 138) who state that “the small business firm is simply an extension of the


22

individual who is in charge.” Burgelman (1983, p. 241) argues that in the case of internal

corporate venturing, "the motor of corporate entrepreneurship resides in the autonomous

strategic initiative of individuals at the operational levels in the organization." Single, top-

line managers represent the level at which strategic behaviours are borne out, and such

individuals possess the relevant entrepreneurial dispositions that are reflected in a firm’s

business level strategic choices (Bourgeois & Brodwin, 1984; Anderson & Eshima, 2013).

Accordingly, risk-taking, innovativeness and proactivity are the most consistently identified

dispositions to entrepreneurship in the EO context.

At the individual-level, risk-taking, innovativeness and proactivity are known together as

‘individual entrepreneurial orientation’ (IEO; Bolton & Lane, 2012). Of the many and varied

individual dispositions studied in the entrepreneurship literature, and of the individual

dispositions operationalised as firm-level orientations, risk-taking propensity,

innovativeness and proactivity are collectively the most studied. These IEO factors were the

focus of a further 28 related studies, constituting one-third (13.1%) of all studies within the

five meta-analyses. Taken together, the meta-analytic study of risk-taking propensity,

innovativeness and proactivity, constitute 60% of total studies and 73% of the total number

of observations within the five meta-analyses. Accordingly, this study focuses on risk-taking

propensity, innovativeness and proactivity as being a) representative of prototypical

personal characteristics in entrepreneurship, b) representative of prototypical individual

entrepreneurial orientation (IEO), c) the dominant empirically validated entrepreneurial

orientation construct in the entrepreneurship domain, and d) the focal individual

dispositions for examination in the relationship between prototypical individual differences

in entrepreneurship and entrepreneurial performance.


23

Risk-taking propensity

Risk-taking propensity is the degree to which people are open to taking chances with

respect to risk of loss in decision-making contexts (Sexton and Bowman 1985). Risk-taking is

considered fundamental to entrepreneurship as entrepreneurial decisions are made in

highly uncertain circumstances (Catillon, 1755; Knight, 1921; Kirzner, 1983). Entrepreneurs

bear the ultimate responsibility for their decisions (Knight, 1921; Kilby, 1971; Gasse, 1982)

with risk of personal loss (Hansson & Zalta, 2014). In entrepreneurship, a range of decision

contexts inherently involve risk taking, including dealing with entry into new ventures or

new markets, introducing new products or services, engaging uncertain consumer and

competitive responses, dealing with resource and supplier availability, and most

significantly, having one’s own investment of time and money on the line. Such levels of

potential personal loss are not borne by managers or employees. Stewart and Roth (2001)

focus on the differentiation between entrepreneurs, managers and employees in their

meta-analysis of risk-taking propensity in entrepreneurship.

Differentiation can be made between entrepreneurs who tend to operate one of two main

types of new ventures, either growth-oriented new ventures or independence-oriented new

ventures (see Hessels, Van Gelderen, & Thurik, 2008; Kolvereid, 1992; Wennekers and

Thurik, 1999; Reynolds, 2000; Gundry and Welsch, 2001; Shaver, Gartner, Crosby,

Bakalarova, & Gatewood, 2001; Carter, Gartner, Shaver, & Gatewood, 2003; Gartner et al.,

2004; Cassar, 2006, 2007; Shane, 2009; Douglas, 2013). Although entrepreneurs who focus

on growth, and business owners who focus on lifestyle/income, constitute two different

groups in terms of motivation, both are often classified as entrepreneurs in the literature.


24

Empirical evidence surrounding the phenomenon is divided. Reviews of the

entrepreneurship literature related to risk (e.g., Meyer, Walker, & Litwin, 1961; Chell, 1985;

Brockhaus & Horwitz, 1986; Masters & Meier, 1988; Perry, 1990) have frequently concluded

that entrepreneurs do not have a distinctive risk propensity compared with managers.

However, other views hold that growth oriented entrepreneurs accept higher levels of risk

in their careers and business decisions than family-income oriented entrepreneurs (Stewart

& Roth, 2001) and much higher levels of risk than managers in large organizations (Bird,

1989; Stewart & Roth, 2001).

The reason for these dichotomous views arguably lies in the relative absence of delineation

between growth oriented and income oriented entrepreneurs in the previous studies, and

in the way researchers seek to understand how entrepreneurs think about business

opportunity decisions (Ray, 1994). The process by which entrepreneurs perceive and think

about risk is different from non-entrepreneurs (Norton & Moore, 2002). What is perceived

as involving risk by some may not be perceived as involving risk by others. Entrepreneurs

are more given to the use of biases and heuristics and are likely to perceive less risk in a

particular decision (Busenitz & Barney, 1997). Relatedness to entrepreneurially oriented

social networks and the inherent experience embedded in that social capital, may enable

entrepreneurs to take short cuts in decision-making with relative confidence and greater

competence (Taylor & Thorpe, 2004; Sequeira, Mueller, & McGee, 2007; Fernández-Pérez,

V., Alonso-Galicia, del Mar Fuentes-Fuentes, & Rodriguez-Ariza, 2014). Several studies show

that firm founders have a higher propensity for risk than do members of the general

population, but that firm founders more objectively assess risk and do not perceive their

actions as risky (e.g., Corman, Perles, & Vancini, 1988; Fry, 1993). For example, Sarasvathy,


25

Simon and Lave (1998) found that expert firm founders evaluate entrepreneurial

simulations differently from employee bankers; firm founders saw opportunities in

information that employee bankers thought indicated risk. “It is more insightful to view

entrepreneurs as capable risk managers whose abilities defuse what others might view as

high risk situations” (Low and Macmillan, 1988, p. 147). Entrepreneurs believe that risk can

be reduced by increased effort or skill (competence).

Contrary to the position taken by many researchers that there is no greater risk propensity

within entrepreneurship than for managers (e.g., Meyer et al., 1961; Ray, 1982; Chell, 1985;

Robbins, 1986; Brockhaus & Horwitz, 1986; Masters & Meier, 1988; Richard, 1989; Perry,

1990) there is simple logic, and empirical evidence within two meta-analyses, which support

the argument that risk propensity is positively associated with entrepreneurship.

Entrepreneurs risk their time (often unpaid, or for relatively less money) and their own

capital in order to realise their goals. Rauch and Frese (2007) tested whether risk taking is

differentially related to business success and found a weak correlation between

entrepreneurial risk taking and business success (r = .10).

Further, Stewart and Roth (2001) found that growth oriented entrepreneurs have a higher

risk propensity than do managers (observed d = 0.30, corrected d = 0.36). More significantly,

when controlling for entrepreneurial growth orientation, the differences in risk propensity

between entrepreneurs with growth aspirations versus managers (K = 3, N = 1,148) became

large (observed d = 0.73, corrected d = 0.84). The difference in risk propensity between

growth oriented entrepreneurs and income oriented entrepreneurs resulted in an observed

d = 0.60 (K = 3, N = 1,093; corrected d = 0.69). Income-oriented entrepreneurs exhibited


26

much lower levels of risk propensity than those with growth aspirations. Income-oriented

entrepreneurs, in comparison with managers, showed an observed d of 0.11 (K = 3, N =

1,428; corrected d = 0.13). Small business owners exhibited a higher risk propensity than

shown by managers (Stewart & Roth, 2001). The empirical literature demonstrates a robust

relationship between risk taking propensity and entrepreneurial performance. It is thus

hypothesised that risk-taking propensity is positively and significantly related to

entrepreneurial performance. (H1).

Innovativeness

Innovativeness reflects a person’s orientation and interest to look for novel ways of action,

typically involving a creative orientation to problem solving (Patchen, 1965). Innovation is

widely considered a fundamental element of entrepreneurship (e.g., Schumpeter, 1934;

Kirzner, 1983; Drucker, 1985; Lumpkin and Dess, 1996; Davidsson, 2004). Innovativeness is

important for entrepreneurs as it enables them to create and launch new products or

services, make improvements on existing products or services, find a better way of doing

something by applying improved solutions that meet existing market needs, new market

needs, or as yet unidentified market needs (Heunks, 1998; Frankelius, 2009). A firm will

only be innovative to the extent that its human resources are innovative (Lau et al., 2012)

and the trait of innovativeness helps entrepreneurs foster innovation in their firms (Heunks,

1998).

Innovativeness has consistently been identified, both conceptually and empirically, as an

important individual dispositions in terms of entrepreneurial performance (Schumpeter,


27

1934; Chell et al., 1991; Drucker, 1993; Lumpkin and Dess, 1996; Covin and Miles, 1999;

Zhao, Seibert & Hills, 2005; Rauch and Frese, 2007) and is related to business success

(Rosenbusch, Brinckmann, & Bausch, 2011). The entrepreneurial performance and business

success variables in these studies generally relate to return-, growth- or market-based

outcomes as well as respondents' ratings on return-, growth- or market-based performance

indicators. ‘The Individual Behaviour Inventory,’ developed in investigation of corporate

entrepreneurship behaviours (Lau et al., 2012) identified innovation as one of ten

entrepreneurial qualities (which also included risk taking) and found that innovativeness and

risk-taking together explain more than 40 per cent of the variance in individual dispositions

in their study.

Rauch and Frese’s (2007) meta-analysis of the relationship between innovativeness and

business success (K = 7, N = 800) shows that innovativeness is positively related to business

success (r = .27, p < .05). A subsequent meta-analysis of 42 empirical studies on 21,270

firms (Rosenbusch et al., 2011) finds that an innovation orientation has a positive effect on

business performance (r = .196, p < .05), with a stronger impact observed in newer ventures

(r = .206, p < .05) than in more established ventures (r = .069, p < .05). The empirical

literature demonstrates a robust relationship between innovativeness and entrepreneurial

performance. It is thus hypothesised that innovativeness is positively and significantly

related to entrepreneurial performance (H1).


28

Proactivity

Proactive behaviour is exhibited by people when they seek to create their environments

(Crant, 1996). It involves an anticipatory, change-orientation whereby people take an active

and self-starting approach to work goals and tasks and persist in overcoming challenges

(Frese, Kring, Soose, & Zempel, 1996; Frese, Fay, Hilburger, Leng, & Tag, 1997; Frese & Fay,

2001). Individuals low in proactivity tend to be relatively passive, accept things as they are

(an external locus of control) and be shaped by, rather than shape, their surroundings

(Bateman & Crant, 1993). Proactive people take control and make things happen rather

than simply adjusting to a situation or waiting for something to happen; they have an

internal locus of control. Proactivity is important for entrepreneurs because they must be

self-starting and adaptive, create their environment by founding new ventures, decide new

business structures and operations, and identify and act upon new venture ideas (Crant,

2000; Rauch & Frese, 2007). Entrepreneurs need to have the foresight to capitalise on those

ideas in anticipation of, or creation of, future demand (Dess & Lumpkin, 2005).

Within the organisational behaviour literature, proactive personality has been found to be

positively related to job performance (r = .19, p < .05; Thompson, 2005), self-reported,

objective career performance measures (income; r = .15, p < .05) and subjective, career

performance measures (career satisfaction; r = .31, p < .05) (Seibert, Crant, & Kraimer,

1999). Rauch and Frese’s (2007) meta-analytic review finds that proactivity (K = 5, N = 678)

is positively related to business success (r = .27, p < .05). These measures have applicability

to career success in the entrepreneurship context. Proactivity is a necessary element of

individual dispositions and is positively related to entrepreneurial performance. The


29

empirical literature demonstrates a robust relationship between proactivity and

entrepreneurial performance. It is thus hypothesised that proactivity is positively and

significantly related to entrepreneurial performance. (H1).

Hypothesis 1: There is a positive significant relationship between individual dispositions in

entrepreneurship (risk taking propensity, innovativeness, proactivity) and

entrepreneurial performance (firm net profit, personal income and career

satisfaction).

Individual Entrepreneurial Orientation

Collectively, the analysis of the three core individual dispositions in entrepreneurship

literature addresses the issue as to whether or not individual dispositions are deterministic

of entrepreneurial outcomes and confirms that an individual entrepreneurial orientation

consisting of risk taking, innovativeness and proactivity in the entrepreneurial context, has

some explanatory power of entrepreneurial performance. While individual dispositions of

business owners affect entrepreneurial performance, non-personality variables such as

strategies, cognitive ability and environment are additional predictors of entrepreneurial

performance (Davidsson, 1989; Campbell, McCloy, Oppler, & Sager, 1993). Rauch and Frese

(2007) identify that the correlations for the identified individual dispositions are as high as

the correlations for some medical diagnostic relationships that of sufficient size to make

practical conclusions in medicine (for example, conventional x-rays and tooth cavities (r =

.36) or cardiac tests and the prediction of death or myocardial infarction within the first

week of vascular surgery (r = .20)) (Meyer, Finn, Eyde, Kay, Moreland, Dies,… & Reed, 2001).


30

The individual disposition correlations identified within this study should therefore be

considered large enough to be of value. However, this is where the literature stops in the

evaluation of these individual dispositions.

The literature does not yet explore why or how within-person factors such as motivation to

entrepreneurship and individual dispositions are evidenced in the entrepreneurship domain.

The literature has looked to the what (i.e. IEO) but not the how or why. An alternate

explanation may be more predictive of entrepreneurial performance than the identified

individual dispositions. In the next section the study proposes an answer to this gap in the

literature by applying self-determination theory (SDT), specifically examining the processes

involved in two sub-theories of SDT, basic psychological needs theory (BPNT) and organismic

integration theory (OIT). I examine the function of both BPNT and OIT, analyse the

relationship between both constructs, and integrate supporting data for their relationship. I

then explore these two sub-theories of SDT as a mechanism that explains the relationship

between the individual and performance in the entrepreneurship context.

Self Determination Theory

Self Determination Theory (SDT) is an empirically derived theory of human motivation and

personality in social contexts that differentiates motivation in terms of being autonomous

(existing and functioning independently of external influences) or externally controlled

(subject to control or influence from outside the person) (Deci & Ryan, 1985). The theory

has proven useful in several domains, including education (Williams & Deci, 1996; Standage,

Duda, & Ntoumanis, 2005; Ratelle, Guay, Vallerand, Larose, & Senécal, 2007), health care


31

(Williams & Deci, 1996; Williams, McGregor & Zeldman, 2004; Ryan, Patrick, Deci &

Williams, 2008), politics (e.g., Koestner et al. 1996; Losier and Koestner 1999), sports

(Vallerand & Fortier, 1998; Ntoumanis, 2001; Gagne´ et al., 2003), academics (e.g.,

Vansteenkiste, Lens, Soenens, & Luyckx, 2006), work (e.g., Gagne´ and Deci 2005), parental

education (e.g., Assor et al. 2004), and volunteerism (Bidee, et al., 2013). The theory, with

the nuances of the 2nd and 4th sub-theories below, has not yet been applied in the

entrepreneurship domain.

SDT has developed over a period of thirty years to include six mini-theories to address

different (but related) issues. These sub-theories are:

1) Cognitive Evaluation Theory (CET); the effects of social environments on intrinsic

motivation

2) Organismic Integration Theory (OIT); the development of autonomous motivation

from external motivation sources (in which people internalise the value of an

activity into their sense of self, making attitudes or behaviour part of your nature

by learning or unconscious assimilation) and integration (combining these within

your personality to form a harmonious whole)

3) Causality Orientations Theory (COT); looks at general motivational individual

dispositions

4) Basic Psychological Needs Theory (BPNT); the fundamental psychological needs for

competence, autonomy and relatedness that are essential for growth and

wellbeing

5) Goal Contents Theory (GCT); the effects of different goal contents on wellbeing and

performance, and

6) Relationships Motivation Theory (RMT); the development and maintenance of

close personal and group relationships.


32

The first mini-theory considers intrinsic motivation; motivation that is based on behavioural

fulfilment ‘for its own sake.’ CET considers the effects of social contexts on intrinsic

motivation, specifically how rewards, interpersonal controls, and ego-involvements impact

intrinsic motivation, while valuing its relationship competence and autonomy supports

(Deci, 1975; Deci & Ryan, 1985). The assumption that people need to feel autonomous and

competent was fundamental to CET propositions; social-contextual factors that promote

feelings of autonomy and competence were conceived as enhancing intrinsic motivation,

whereas factors that diminish these feelings were conceived as undermining intrinsic

motivation. Debate concerning both the undermining effect, and CET as a theory, followed

(e.g., Calder & Staw, 1975; Deci, Cascio, & Krusell, 1975; Scott, 1975; Deci, 1976), leading to

laboratory experiments and field studies which supported, refined, extended, or refuted the

undermining effect, and CET. CET has limitations in explaining the degree to which a person

is positively motivated by externally regulated behaviours, particularly when daily

behaviours involve, for most of us, a significant portion of extrinsically motivated activities,

some of which are enacted autonomously while others are clearly controlled. For Deci and

Ryan, these studies elicited the question of whether extrinsically motivated behaviours

(which were found to thwart the autonomy need and undermine intrinsic motivation) could

be performed autonomously, and, if so, how autonomous extrinsic motivation would be

promoted (Deci & Ryan, 2012). This question led to the formulation of SDT’s second mini-

theory (OIT) which has been applied in this study.

The second mini-theory (OIT) considers the various degrees of extrinsic motivation in its

various forms, those being related to distinct levels of activity. These include external

regulation, introjection, identification, and integration. OIT is concerned with the BPNT


33

supports for autonomy and relatedness that enhance or hinder internalisation, and

accordingly OIT and BPNT are interrelated and considered important in this study.

The third mini-theory (COT) prescribes individual differences in people’s tendencies to align

themselves with different environments and regulate behaviour in the context of three

types of causality orientations: an autonomy orientation (a person acts out of interest in,

and value for, what is occurring), a control orientation (aligned to rewards, gains, and

approval), and an amotivated orientation (having concern for one’s competence) (Deci &

Ryan, 2012). OIT is more nuanced than COT, with greater variation in the degree of

motivation measured.

The fourth mini-theory (BPNT) expands upon the concept of evolved psychological needs

and their relations to psychological health and well-being (Deci & Ryan, 2012). Psychological

well-being and optimal performance are deemed dependent upon the satisfaction of the

need for autonomy, competence, and relatedness, with the satisfaction of all three needs

being essential, and if any is hindered there will be diminished wellbeing and performance

(Deci & Ryan, 1985). The greater the degree to which an individual satisfies their need for

competence, autonomy and relatedness, the greater their autonomous motivation will be

(Deci & Ryan, 1987).

The fifth mini-theory (GCT) makes the distinction between intrinsic and extrinsic goals and

their impact on motivation and wellness. Extrinsic goals such as financial success,

appearance, and popularity/fame were specifically contrasted with intrinsic goals such as

close relationships, personal growth and community, with the former more likely associated


34

with lower wellness and greater ill-being. Goal orientation explains the existence of the

underlying mechanism of the relationship between individual dispositions and

entrepreneurial performance, but does not fundamentally explain the mechanism itself.

The sixth mini-theory (RMT) is an extension of the relatedness element of BPNT and

considers the development and maintenance of close personal relationships based on

findings that the highest quality personal relationships are ones in which partners support

the autonomy, competence, and relatedness needs of the other. Findings concerning a

person's relatedness to groups, show that some amount of such interactions is not only

desirable, but essential for an individual’s orientation to different degrees of motivation and

well-being. This is because the relationships provide satisfaction of the need for relatedness,

as well as the need for autonomy and to a lesser extent the need for competence (Deci &

Ryan, 2012). This thesis considers these factors of relatedness in the context of BPNT rather

than as a separate, independent analysis.

Accordingly, this study incorporates BPNT and OIT, in order to explain the mechanism by

which individual dispositions evolves and entrepreneurial performance is evidenced (the

second theoretical gap in the literature). These SDT min-theories are applied to address the

second gap in the literature, and the second research question, of whether the degree of

motivation to entrepreneurship is deterministic of entrepreneurial performance. SDT has

not yet been applied to the entrepreneurship domain in the OIT context, which represents

the third gap in the literature. This leads to the assumption-challenging third research

question of whether this underlying mechanism is more predictive of entrepreneurial

performance than individual dispositions amongst entrepreneurs. The OIT context, these


35

gaps in the literature and the corresponding research questions will be addressed in turn in

the section Organismic Integration Theory.

The current section focuses on the fundamental basic psychological needs identified by Deci

and Ryan (1985). The nuances and mechanism by which the satisfaction of the basic

psychological needs for competence, autonomy and relatedness (BPNT) leads to higher

levels of autonomous motivation are then presented. Empirical relationships between the

basic psychological needs and entrepreneurial performance are then identified, with

sequential discussion of the needs for competence, autonomy and relatedness. The thesis

then proceeds to examine and explain OIT in the entrepreneurship context, with a view to

resolve how OIT explains the mechanism to strengthen (or diminish) EP, and how the

differential strengths of motivation types (described by OIT) mediate the relationship

between need satisfaction (as theorised within BPNT) and entrepreneurial performance.

Basic Psychological Needs Theory

The three basic psychological needs described by BPNT are the need for competence -

people seek to improve skills and experience mastery; need for relatedness - people have

the universal want to interact, be connected to, and experience caring for others; and the

need for autonomy - the universal urge to be the causal agents of one's own life and act

according to your own thoughts, emotions, and actions that amount to you being you (Deci

& Ryan, 1985; Deci & Vansteenkiste, 2004). According to SDT, the satisfaction of basic

psychological needs is essential for optimal performance and if any need is hindered there

will be diminished wellbeing and reduced performance (Deci & Ryan, 1985). People need to


36

feel competent, autonomous and related to their social, peer and family groups in order to

maintain their intrinsic motivation - satisfaction of these three needs, from actions taken

within entrepreneurial contexts, is necessary for internalisation of entrepreneurial attitudes

and behaviour (which in its fullest form is integration) to operate effectively in the

entrepreneurship domain (Baumeister & Leary, 1995).

An important distinction to make, before proceeding with the treatment of the need for

competence, autonomy and relatedness variables, is the distinction between the strength of

needs and the degree of need satisfaction. Organisational behaviour studies typically treat

needs as individual differences; people are viewed as differing in the strength of particular

needs (Gagné & Deci, 2005) and their need strength is evaluated in relation to motivation,

job satisfaction, and work performance (e.g., Hackman & Lawler, 1971; McClelland &

Burnham, 1976). SDT defines needs differently - needs are viewed as essential ‘universal

necessities’ for optimal development (Ryan, Sheldon, Kasser, & Deci, 1996; Gagné & Deci,

2005). Accordingly, the needs for competence, autonomy and relatedness exist to the

extent that their satisfaction promotes beneficial outcomes. Rather than focus on the

consequences of the strength of those needs for different individuals, SDT focuses on the

extent to which individuals are able to satisfy the needs (Gagné & Deci, 2005). The first of

the basic psychological needs discussed is the need for competence.

Satisfaction of the Need for Competence

Satisfaction of the need for competence reflects a sense of self-efficacy (Bandura, 1981). The

concepts of perceived competence and self-efficacy are frequently used interchangeably in


37

the literature (Rodgers, Markland, Selzler, Murray, & Wilson, 2014). The SDT conception of

the need for competence relates to the need to master challenging tasks and the belief in

one’s ability to do so (Bandura, 1986; Maddux & Stanley, 1986). Competence in the

entrepreneurship domain, which reflects an internal locus of control, involves an

entrepreneur’s ability to control their motivation, behaviour and social environment

(Bandura, 1977, 1986, 1997). Competence is a key component of ‘can do’ motivation, which

has consistently been linked to proactivity (e.g., Morrison & Phelps, 1999; Axtell, Holman,

Unsworth, Wall, & Waterson, 2000; Kanfer, Wanberg, & Kantrowitz, 2001; Parker, Williams,

& Turner, 2006; Frese, Garst, & Fay, 2007). Competence is important for entrepreneurs as

they must be confident in their abilities to perform various tasks, often unanticipated tasks,

that are necessary for entrepreneurial success in uncertain situations (Baum & Locke, 2004).

However, there are no empirical studies to show the correlation between the need for

competence in the entrepreneurship domain and entrepreneurial performance. In

substitution, both self-efficacy and need for achievement, in the entrepreneurial context,

are close proxies by which the relationship can be more closely evaluated.

Self-efficacy reflects perceived competence and is a proxy for competence, according to

Bandura (1986). Several meta-analyses provide empirical support for the relationship

between self-efficacy (proxied as perceived competence) and entrepreneurial performance.

Stajkovic and Luthans (1998), in a meta-analysis of self-efficacy and the relationship with

work-related performance (K = 157, N = 21,616) found that self-efficacy was significantly

correlated with work-related performance (r = .38) for all levels of task complexity (low,

medium and high). Chen, Casper, & Cortina (2001) also found that self-efficacy has a

positive and significant relationship with work-related performance (r = .23, N = 33). Judge


38

and Bono (2001), in a meta-analysis of 211 studies, found that generalized self-efficacy was

positively correlated with job satisfaction (r = .45) and job performance (r = .23). Self-

efficacy, as a proxy for competence, has relationship with work performance and job

satisfaction.

Growth oriented entrepreneurs are different from income-oriented business owners with

the former being much more likely to seek competence in strategies that focus on market

expansion and new technologies, exhibiting greater intensity towards business ownership

and willingness to incur opportunity costs for the success of their firms (Carland, Carland,

Hoy, & Boulton, 1988; Carland, Carland, & Abhy, 1989; Storey, 1994; Hamilton, 2000;

Feldman & Bolino, 2000; Ryan & Deci, 2000; Gundry & Welsch, 2001; Shane et al., 2003;

Carter et al., 2003; Van Gelderen & Jansen, 2006). Achievement in this context reflects the

desire to organise and exercise action towards growth oriented goal attainments in

circumstances of uncertainty, with elements of risk, innovativeness and proactivity. The

need for competence in growth-oriented entrepreneurs can be equated to the need for

achievement in the entrepreneurship domain.

Growth oriented entrepreneurs are likely to exhibit competence in a more structured,

disciplined approach to organising and managing their businesses, develop strategic

intentions that emphasise market growth and technological change, plan earlier for the

growth of the business, demonstrate stronger commitment to the firm’s success, have

greater willingness to make sacrifices on behalf of the business, utilise team-based

organizational design, and be open to a wider range of financing sources for business

expansion (Gundry & Welsch, 2001). This is due to their competence and their need to


39

achieve in this regard. There is empirical support for this view. Collins, Hanges and Locke

(2004) found that the mean correlation between achievement motivation and business

performance was r = .26 (p < .01). Rauch and Frese’s (2007) meta-analysis of the

relationship between individual dispositions (need for achievement: K = 31, N = 4,115) and

business success found that need for achievement is positively related to business success (r

= .30, p < .05). Need for achievement, as a proxy for competence in the entrepreneurial

context, has a positive relationship with business performance and business success.

All individuals have the need for competence in the domain/s most important to them.

Increased competence in the entrepreneurship domain leads to increased entrepreneurial

performance. When the need for competence is satisfied by capably organising and

executing the required courses of action in the entrepreneurship domain, competence (and

one’s self-efficacy) is strengthened and the likelihood of performing the associated

behaviour is further enhanced. According to SDT, as important a factor as competence is,

feelings of competence in entrepreneurship will not result in optimal entrepreneurial

performance unless accompanied by a sense of autonomy (Fisher, 1978; Ryan, 1982). Thus,

people must not only experience competence, their behaviour must also be self-

determined, accompanied by autonomy, for optimal performance to be achieved (Ryan &

Deci, 2000).

Satisfaction of the Need for Autonomy

The need for autonomy involves independent self-determination, the process by which a

person controls their own life (Van Gelderen & Jansen, 2006). It involves self-regulation and


40

personal endorsement of one’s own actions – the sense that your actions originate from you

(Deci & Ryan, 1985). Autonomy relates to the aspiration to develop and realise personal

values, goals and interests (Assor et al., 2002) having more than just decisional freedoms

but being self-aware, knowing what one’s dreams and individual goals are, and acting on

them (Gelderen, 2010).

The need for autonomy is a principle driver of entrepreneurship (Feldman & Bolino, 2000;

Carter et al., 2003; Caliendo, Fossen, & Kritikos, 2012). Typically, situations that are

characterized by low structure, high autonomy, scarce information, ambiguous information

and uncertainty, facilitate the expression of the need for autonomy (Hattrup & Jackson,

1996). Autonomy is important for entrepreneurs because it enables them to have control

over their environment, set their own goals, incorporate elements of innovation, make their

own decisions independent of external managerial control, and essentially regulate their

own behaviour (Brandstatter, 1997; Cromie, 2000; Rauch & Frese, 2007).

There are two distinct conceptualisations of autonomy to clarify. One is the universal urge

to be the causal agent of one's own life, which is an internal regulation process (Deci &

Vansteenkiste, 2004). The other is the state of being independent, self-governing, on a

behavioural level, such as in the occupational context where people have discretion over

how work is to be performed (job design) and the ability to manage (control) the work-

personal life interface (Grzywacz & Marks, 2000; Clark, 2001; Voydanoff, 2004). However, as

much as there is a distinction between the internal regulation process and state levels of

autonomy there is little distinction between these concepts in how they are measured.

Deci, Ryan, Gagné, Leone, Usunov, & Kornazheva’s (2001) Basic Need Satisfaction at Work


41

Scale (BPNS), which incorporates each of the basic psychological need concepts within a 21-

item questionnaire, utilises state based questions such as “I feel like I am free to decide for

myself how to live my life; I feel pressured in my life; I generally feel free to express my

ideas and opinions.” These self-report questions are very similar to other autonomy

measures in the entrepreneurship literature which focus on the ability to work

independently, make decisions, and take actions (Lumpkin, Cogliser, Schneider, 2009).

Autonomy is argued to be a dominant source of entrepreneurial satisfaction (Binder & Coad,

2012). Research on work satisfaction shows that the self-employed (and entrepreneurs, as

a subgroup of the self-employed) experience higher work satisfaction than the employed

(Hundley, 2001; Bradley and Roberts, 2004; Benz and Frey, 2008a, 2008b; Prottas, 2008;

Schjoedt, 2009). SDT implies that autonomy leads to well-being and this would explain why

autonomy in the entrepreneurial environment might be a compensator for higher income in

a less autonomous position (Ryan & Deci, 2000). Work that provides autonomy are more

intrinsically motivating than work that does not (Corman, Perles & Vancini, 1988). Research

relating to entrepreneurial motivation shows autonomy, rather than financial gain, to be the

most often mentioned, or most importantly rated, motive to start a business (Shane et al.,

2003; Van Gelderen and Jansen, 2006). Empirical support for the concept is found in Rauch

and Frese’s (2007) meta-analysis of the relationship between autonomy and business

success (K = 8, N = 843) which found that the need for autonomy is correlated with business

success (r = .16, p < .05). Satisfaction of the need for autonomy is an important explanation

for how entrepreneurs create control over their environment, set their own goals and make

their venture decisions.


42

Satisfaction of the Need for Relatedness

The need for relatedness is the desire to be connected to, to interact with, to share and care

for others (Ryan & Deci, 1985). Relatedness is similar in concept to what Baumeister and

Leary (1995) call the ‘need to belong,’ and what McLelland (1975) identifies as the ‘need for

affiliation.’ In the entrepreneurship domain the concept of relatedness can be equated with

personal and business networks, which often offer important encouragement in the early

stages of entrepreneurship (Davidsson and Honig, 2003; Mosey and Wright, 2007; Ozgen

and Baron, 2007; Obschonka, Silbereisen, & Schmitt-Rodermund, 2010). This is because

social networks contribute to entrepreneurial intentions (Shane & Cable, 2002; Sequeira et

al., 2007; Prodan & Drnovsek, 2010) and play a leading role in many aspects of business

start-ups (Birley, 1985; Aldrich, 1999; Johannisson, 2000). They provide important means for

the acquisition of information, talent, experience, capital, resources (sometimes below

market price and sometimes free), partnerships, market and community legitimacy, external

stimuli and support to the entrepreneur. These are necessary to discover and exploit

opportunities, and to grow one’s business, particularly when needed resources are often

scarce for business startups (Hoang & Antoncic, 2003; Cantzler & Leijon, 2007; Slotte-Kock &

Coviello, 2010). Entrepreneurship can therefore be facilitated or inhibited by the degree to

which entrepreneurs are related to social networks (Aldrich & Zimmer, 1986).

Relatedness can be measured as social capital in the form of weak and strong ties. Weak ties

are constituted by the relationships with acquaintances which provide entrepreneurs with

access to information and resources beyond that which is available in their own social circle

(strong ties). While specialist information and knowledge are present in large social


43

networks (Granovetter, 1973), strong ties have greater motivational assistance and are

typically more easily available (Granovetter, 1983). Relatedness to social networks is a

source of valuable economic and non-economic resources by which entrepreneurial

performance can potentially be enhanced (Bourdieu, 1986; Nahapiet and Ghoshal, 1998;

Portes, 1998; Zaheer, Gözübüyük, & Milanov, 2010; Mayer-Haug et al., 2013). Furthermore,

these supports are a means of generating relationships in which new venture protagonists

can trust (Zaheer et al., 2010), which in turn improves entrepreneurial performance by

reducing transaction costs (Wu and Leung, 2005). Reduced transaction costs can be seen in

the saving of time; taking short cuts in decision-making with relative confidence; developing

efficiency; acquiring new skills, systems and ideas; mitigating risk; improving innovativeness;

and enhancing venture performance (Davidsson and Honig, 2003; Taylor & Thorpe, 2004;

Sequeira et al., 2007; Fernández-Pérez et al., 2014).

Alternatively, the inhibition of entrepreneurship can be observed in the ‘liability of newness’

which involves a lack of stable ties and fewer established relationships (Stinchcombe, 1965).

The ‘liability of smallness’ may also inhibit nascent entrepreneurship in the resource

disadvantages they face in comparison to larger firms (Aldrich and Auster, 1986). Both

newness and smallness can negatively impact entrepreneurial performance. Utilizing

entrepreneurship networks can be one way for a nascent venture, or a venture with a

growth orientation, to overcome resource constraints. Founders often seek relationships

with entrepreneurial networks, with support provided by political, educational, community

and self-interest organisations (Audretsch, Lehmann, & Plummer, 2009). They partner with

larger firms, more prominent firms, incubators, business accelerators, business angels and


44

venture capitalists (Stuart, Hoang, & Hybels, 1999). Relatedness is key to their

development.

Two meta-analyses of empirical findings in the entrepreneurship literature support the

proposition that relatedness to entrepreneurship networks is positively related to

entrepreneurial performance. A meta-analysis of the relationship between social capital

and business performance (Stam, Arzlanian, & Elfring, 2014; Z = 59, N = 13,263) found that

social capital is significantly and positively related to small business performance (r = .211).

The correlation of ‘structural holes’, which are the relationships by which entrepreneurs

may forge ties to otherwise unconnected others to obtain strategic benefits (Batjargal,

2010), is larger (r = .179) than the correlation of weak ties (r = .085). The correlation of

network diversity (r = .318) is larger still and exhibits the strongest relationship with

entrepreneurial performance. Further, Stam et al. (2014) found that the strength of the

social capital-performance relationship depends on the age of the business (stronger for

new ventures) and the industry in which the firm operates. Weak ties, structural holes, and

network diversity are more valuable for nascent ventures, whereas network size; strong ties

are more positively related to the performance of firms with more time in the market (Stam

et al., 2014).

The second meta-analysis (Crook, Todd, Combs, Woehr, & Ketchen, 2011) of the

relationship between human capital and business performance (N = 68, K = 12,163) showed

that relatedness to social capital networks is positively associated with entrepreneurial

performance, (r = .21, p = .01). The results indicate that relatedness to social capital in the

form of entrepreneurial networks creates value and improves entrepreneurial performance.


45

The satisfaction of the need for relatedness is crucial for internalisation of entrepreneurial

attitudes, values and beliefs (Baumeister & Leary, 1995) and within entrepreneurial

supports the opportunities for the satisfaction of this need increase.

The greater the degree to which the needs for competence, autonomy and relatedness are

met in the entrepreneurial context, the greater the autonomous and intrinsic motivation to

entrepreneurship will be.

Organismic Integration Theory

Organismic Integration Theory (OIT) can help explain how the degree of an individual’s

controlled and autonomous motivation are related to entrepreneurial career performance.

The four external motivation sub-types of OIT (which include extrinsic, introjected,

identified, and integrated regulation) in conjunction with intrinsic motivation in the

entrepreneurship domain, can be used to explain the mechanism by which individual

dispositions leads to entrepreneurial performance. SDT, specifically OIT, has not been

applied to the entrepreneurship domain previously, which represents the second gap in the

literature identified in this study. Within the entrepreneurship literature, and anecdotally

within discussion among psychology- entrepreneurship researchers, the concept of SDT has

been consistently, generically referred to without this differentiation between nuanced sub-

theories. Accordingly, the organismic integration process, described by OIT, has not

previously been investigated as an explanation of the mechanism by which individual

dispositions leads to entrepreneurial performance. This novel contribution forms the basis

for the second research question, ‘Is the degree of motivation to entrepreneurship

deterministic of entrepreneurial performance’ which in turn leads to the assumption-


46

challenging, third research question of ‘Is this underlying mechanism more predictive of

entrepreneurial performance than individual dispositions amongst entrepreneurs?’

These questions relate to the two SDT sub-processes of BPNT and OIT and are examined in

two parts. The first part involves the relationship between the satisfaction of the basic

psychological needs (for competence, autonomy and relatedness) and the autonomous

motivation sub-types of OIT (identification, integration and intrinsic motivation). The

second part involves the relationship between the type of autonomous motivation

regulation, in conjunction with controlled motivation subtypes (introjected and extrinsic)

and entrepreneurial performance outcomes (firm net profit, personal income and career

satisfaction). Further, to evaluate which mechanism (between IEO-EP and BPNT-OIT-EP) is

more predictive of EP, a comparative examination between individual dispositions and

autonomous-controlled motivation as predictors of entrepreneurial performance is made.

This sequence guides the structure of this and subsequent chapters.

First, in order to establish terms of reference, these motivational concepts are defined and

core OIT principles are expanded upon. The relationship between the basic psychological

needs (for competence, autonomy and relatedness) and autonomous motivation is then

identified. The relationship between autonomous-controlled motivation and

entrepreneurial performance is then explored by viewing individual dispositions through the

lens of OIT.


47

Organismic Integration Principles

OIT can be represented as a spectrum of motivational states with three primary divisions;

amotivation, external motivation and intrinsic motivation. It can further be represented

according to controlled and autonomous motivation states. Each motivation state correlates

most strongly with adjacent states and less strongly with nonadjacent states. Although the

motivation states are depicted on one continuum, research shows that there is a clear break

in the consequences of each type of motivation (Koestner, Losier, Vallerand, & Carducci,

1996; Pelletier, Tuson, Greene-Demers, Noels, & Beaton, 1998; Koestner & Losier, 2002;

Ryan, 2010). This spectrum of motivation states is shown in Table 2.2.

Table 2.2

Control-to-autonomy continuum

Amotivation External Motivation Intrinsic

Motivation

Controlled Autonomous

External

Regulation

Introjected

Regulation

Identified

Regulation

Integrated

Regulation

Lack of

Motivation

Controlled

Motivation

Moderately

Controlled

Motivation

Moderately

Autonomous

Motivation

Autonomous

Motivation

Inherently

Autonomous

Motivation

Adapted from Gagné & Deci (2005)

Intrinsically motivated behaviour, activated by an individual’s interest in the activity itself, is

fundamentally autonomous (Gagné & Deci, 2005). Intrinsic motivation exists within the

individual, rather than relying on external pressures to engage in certain behaviour or a

desire for reward. People who are intrinsically motivated are more likely to engage in a task

willingly as well as work to improve their skills; they find the activity inherently interesting


48

and enjoyable. Intrinsic motivation is evidenced when the action or behaviour is performed

because the person enjoys the activity itself, for itself and of itself.

At the other end of the continuum is amotivation, in which behaviour is externally

controlled and wholly lacking in self-determination. In between these two ends is external

motivation. When individuals undertake an action because they can gain something that is

separable from the activity, they exhibit external motivation regulation (Gagné & Deci,

2005). There are four sub-types of external motivation: extrinsic, introjection, identification,

and integration. The subtypes fall along the control-to-autonomy continuum. Extrinsic

regulation is on the controlled end, and integrated regulation is on the autonomous end of

the continuum (Deci & Ryan, 2002).

Externally controlled motivation represents the first division of motivation states, after

amotivation. Extrinsic regulation is the most externally controlled, and thereby the least

self-determined type of external motivation. When people choose a career path in order to

seek approval, or work for the primary motivation of payment, they are extrinsically

regulated (Gagné & Deci, 2005). Introjected regulation occurs as if the regulation of

motivation were controlling the person rather than the person regulating the motivation.

Persons forced by circumstances to go into business for themselves due to having no other

viable option for income than to start a small income generating activity (necessity

entrepreneurs) exhibit introjected regulation. These two factors represent controlled

motivation.


49

Moving from the controlled to the autonomous divisions of motivation states, the following

factors represent the increasing degrees of autonomous motivation. Identified regulation,

whereby an individual feels greater freedom and willingness due to the behaviour being

more in line with their personal goals and identities (Deci & Ryan, 2000), may be found in

individuals who dedicate themselves to entrepreneurial enterprise because the associated

activities have personal significance. This personal significance though, does not necessarily

equate to satisfaction or pleasure. Integrated regulation is evidenced when people have a

full sense that the behaviour is an integral part of who they are, allowing the person to

achieve important life values or benefit society in some way. The behaviour is thus

integrated and internalised, although the qualitative difference that the behaviour is still

regulated by fully internalised factors rather than by the intrinsic enjoyment of the activity

itself, separates it from intrinsic motivation (Deci & Ryan, 2000). Thus, because the person

undertakes the behaviours because it allows them to fulfil values central to their identity, or

because of the benefits that accrue to society or others, the motivation is classed as

integrated regulation. If it were intrinsically motivating, the behaviour would not be

undertaken for the purpose of fulfilling these personal values; it would be undertaken

because of the intrinsic enjoyment. Measures of identified and integrated motivation are

psychometrically difficult to differentiate (Gagné & Deci, 2005). Accordingly, identified and

integrated motivation are captured in this study within the one measurement variable

(Integrated).

Finally, intrinsic motivation is driven by an interest or enjoyment in the activity itself; it

exists within the individual. These three factors (identification, integration and intrinsic

motivation) represent autonomous motivation in the entrepreneurship domain. Some


50

activities, although originally motivated externally, might eventually evoke feelings of

autonomy and contribute to persistence. This progress from controlled motivation to

autonomy develops only if the basic psychological needs of competence, autonomy and

relatedness are fulfilled (Ryan & Deci, 2000).

The context or type of the motivation is evaluated with regard to the degree to which the

activity is self-determined, i.e. the degree of free choice exercised in deciding one's own acts

or states without external compulsion. People must experience satisfaction of their need for

competence, autonomy and relatedness for their behaviour to be self-determined and for

their autonomous motivation to be enhanced (Fisher, 1978; Ryan, 1982; Ryan & Deci, 2000).

The greater the degree to which an individual satisfies their need for competence,

autonomy and relatedness in the context of entrepreneurship, the greater their

autonomous and intrinsic motivation will be when enacting behaviours related to

entrepreneurship. Furthermore, the more autonomously motivated the person, the greater

their association with outcomes of wellness, work engagement and perceived competence

(Grolnick & Ryan, 1987; Ryan & Connell, 1989; Vallerand, 1997). The control-to-autonomy

(extrinsic-to-intrinsic motivation) continuum framework, shown in Table 2.2, is used to

guide the development of the subsequent empirical study.

Basic Psychological Needs and Organismic Integration

A person might be externally controlled, and go into self-employment as a matter of

necessity, choose a career path in order to seek approval, or work for the primary

motivation of payment and thereby exhibit the least self-determined type of external


51

motivation (Deci & Ryan, 2000). Operating a venture can be demanding, repetitive, and not

always inherently enjoyable, particularly if started for reasons of need rather than interest.

Continued repetition of more mundane activities could lead to habituation and fatigue (Van

Yperen & Hagedoorn, 2003). A fundamental difference between external motivation and

intrinsic motivation, according to Deci and Ryan (1985), is the lack of liking for the activity.

A person might learn to introject a behaviour that was initially motivated extrinsically (Ryan

& Connell, 1989). Internalisation might originate from intra and/or interpersonal pressure,

because dependence on the fulfillment of a condition are attached to the activity, such as

feelings of social acceptance or self-esteem (Vallerand, Blanchard, Mageau, Koestner,

Ratelle, Léonard & Marsolais, 2003). Persons forced by circumstances to go into business for

themselves due to having no other viable option for income will likely be extrinsically

motivated by the income that this necessity entrepreneurship brings them. Initially, these

persons might only go into sales, for example, in order to get the basic income required,

reflecting extrinsic motivation. Over time, this behaviour might become internalised, leading

to a sense of pride, or some other ego-affect, after engaging in the behaviour (de Charms,

1968; Ryan, 1982, Gagné & Deci, 2005). These states reflect introjection (Deci & Ryan,

2008). At this level, the persons do not experience a sense of ownership over the principle

to act in business as an entrepreneur, particularly in challenging competitive environments.

However, they feel they should engage in the behaviour anyway (Deci & Ryan, 2000). In this

way, people are likely feeling more self-determined than in the previous scenario, with

higher satisfaction of their need for competence, autonomy and relatedness, although their

behaviour is still externally motivated.


52

Rather than simply take in the expectations and projections of others (introject), a person

might learn to identify with this behaviour (Ryan & Deci, 2000). People who perceive or

identify themselves as effective entrepreneurs and consequently feel motivated to engage

in this behaviour, do so primarily to align with this identity (Vallerand et al., 2003).

Ultimately, people might integrate this alignment with other aspects of their own self-

concept. Social-contextual events (e.g., feedback, communications and rewards) might help

to bring about feelings of competence during the behaviour, which in turn enhance

motivation for the behaviour (Ryan & Deci, 2000). People might not only identify as

competent entrepreneurs, but assimilate and integrate this identity with their self-

perception. This behaviour becomes increasingly more autonomous. While SDT is not a

stage theory, the person may move from extrinsic motivation and introjection through to

identification and finally integration (Gagné & Deci, 2005). Integration results from an

autonomous internalisation of the activity into the person’s identity.

An autonomous internalisation occurs when people freely accept the activity as important

for them, without any dependence on the fulfilment of an external condition attached to it

(Vallerand et al., 2003). Vallerand et al. introduce the analogies of people who have a very

strong orientation for playing the guitar or for dancing. They argue that avid guitar players

or dancers are not just people who play the guitar or dance; they are ‘‘guitar players’’ or

‘‘dancers.’’ The activity is important for them and they identify as ‘‘guitar players’’ or

‘‘dancers’’ and integrate this into their personality. Within entrepreneurs there is thought to

exist an intense positive feeling toward entrepreneurial tasks and activities that are relevant

to the entrepreneur’s own sense of identity (Cardon et al. 2009). People who have an

orientation towards entrepreneurship, particularly scalable, growth-oriented


53

entrepreneurship, identify as “entrepreneurs” (even those without demonstrable or

significant success). Conversely, small business owners who are self-employed by necessity,

don’t typically use the same language in their description of their self-concept. The

‘entrepreneur’ who has internalised the individual dispositions into their identity are more

self-determined still.

This integration is still differentiated from intrinsic motivation however, and still coincides

with an auxiliary outcome and therefore still not as inherently interesting, enjoyable,

satisfying, or fulfilling. These are categorical qualities of intrinsic motivation according to

SDT (Ryan & Deci, 2000). Enjoyable activities that people like and engage in on a regular

basis will be internalised to the extent that they are highly valued by the person (Aron, Aron,

& Smollan, 1992; Csikszentmihalyi, Rathunde, & Whalen, 1993). When intrinsically

motivated people undertake entrepreneurial activities out of free will (because they enjoy

the feeling of being an entrepreneur) they are at their most self-determined. They exhibit

the highest order of satisfaction of their need for competence, autonomy and relatedness in

the entrepreneurship domain.

This resultant conceptualisation of integration and internalisation is facilitated by

satisfaction of the basic psychological needs and impaired by their hindrance (Deci and

Ryan, 1985b; Ryan et al., 1985a; Ryan & Deci, 2000; Gagné & Deci, 2005; Ryan, Huta & Deci,

2008). In line with SDT (Deci & Ryan, 2000), by engaging in entrepreneurial activities, people

will likely satisfy the basic psychological needs of autonomy, competence, and relatedness

in the entrepreneurship domain. Each type of motivation, extrinsic through to intrinsic,

correlates most strongly with contiguous motivation types (e.g. intrinsic and identified


54

regulation), and less strongly with non-contiguous motivation types (e.g. intrinsic and

extrinsic regulation) (Ryan, 2010; Pelletier et al., 1998; Koestner, Losier, Vallerand, &

Carducci, 1996; Koestner & Losier, 2002).

SDT postulates that the satisfaction of basic psychological needs promotes intrinsic

motivation and internalisation. SDT distinguishes between autonomous motivation and

controlled motivation. Autonomous motivation includes intrinsic motivation and

internalised external motivation. The degree to which entrepreneurs are autonomously

motivated would be predicted from the degree of support the experience for autonomy,

their perceived competence in tasks related to entrepreneurship, and their relatedness to

the entrepreneurship domain. The degree of their controlled motivation would be predicted

by their degree of coercion or influence experienced by external contingencies (Gagné &

Deci, 2005). Introjection correlates more closely with external control than with

identification (e.g., Ryan et al., 1993) while identification and integration share qualities

with intrinsic motivation and represent autonomous forms of external motivation (Deci &

Ryan, 2012). SDT therefore postulates that the satisfaction of basic psychological needs

predicts intrinsic and autonomous motivation.

Hypothesis 2: There is a positive significant relationship between the satisfaction of the

three basic psychological needs (competence, autonomy, relatedness) and

autonomous motivation (intrinsic motivation, integrated motivation).


55

All hypotheses are represented in Figure 2.1 below for reference.

Figure 2.1. Theoretical model of the hypothesised relationships

Organismic Integration and Entrepreneurial Performance

Autonomous motivation, consisting of a mix of intrinsic motivation and internalised external

motivation as depicted in Table 2.2, is superior in situations that include both complex tasks

that are interesting and in less complex tasks that require discipline (Koestner & Losier,

2002). In the case of autonomous external motivation, there appears to be no performance

advantage to autonomous motivation when a job involves mundane tasks only. However, in

those situations, autonomous motivation is likely associated with greater job satisfaction

(Ilardi, Leone, Kasser & Ryan, 1993; Shirom, Westman & Melamed, 1999). This is ideally

suited to the role of an entrepreneur who is faced with both complex tasks in the ideation

and development of one’s business, and mundane, everyday tasks in the often low-

resourced administration of it.


56

Autonomous motivation is likely to have a positive relationship with entrepreneurial

performance. Positive valuation of an activity (e.g., Deci, Eghrari, Patrick, & Leone, 1994),

the time and energy expended in the activity (Emmons, 1999), and liking for the activity

(Csikszentmihalyi et al., 1993) are all associated with engagement and subsequent positive

performance in activities people are invested in (Vallerand et al., 2003). Entrepreneurs who

freely accept an activity related to operating their venture as important for them, without

any contingencies attached to it (which may be more descriptive of entrepreneurs who

aren’t in it for the money), experience a motivational force, a willingness, to engage in the

activity with a sense of volition and personal endorsement. The greater the autonomy in this

regard the greater the positive psychological wellbeing, affective commitment, effort and

performance benefits (Gagné, Forest, Gilbert, Aubé, Morin, & Malorni, 2010). There is likely

a positive relationship between autonomous (intrinsic and integrated) motivation and

entrepreneurial performance measures (firm net profit, individual income and career

satisfaction).

The relationship between intrinsic motivation and financial performance measures has two

potentialities. On one hand, some people will exhibit a strong relationship between intrinsic

motivation and financial performance outcomes due to their higher competence in

performing and the associated success that results, thereby showing a strong relationship

with financial outcomes and career satisfaction. However, those who are intrinsically

motivated towards satisfaction of some internally generated benefit to greater society

might not be driven to succeed financially rather than to survive in the business to the

degree to which they satisfy these non-financial goals. For these people, there may be a


57

weak relationship between intrinsic motivation and financial performance measures whilst

showing a strong relationship with career satisfaction.

Hypothesis 3: There is a positive significant relationship between autonomous motivation

(intrinsic motivation, integrated motivation) and entrepreneurial

performance (firm net profit, personal income and career satisfaction).

Additionally, autonomous and controlled motivations are clearly not mutually exclusive.

People can be motivated by both to perform (Elfving, 2008) and both have potential

relationships with entrepreneurial performance. Internally, entrepreneurs may be

motivated to succeed and accomplish a personal, market, system, society-changing goal,

whereas externally, they may be motivated to obtain wealth, power or status (Carsrud &

Brännback, 2010). For example, necessity entrepreneurs, forced by circumstances to go into

business for themselves whilst extrinsically motivated, aren’t precluded from achieving

business outcomes. External motivation of itself leads to observable performance

outcomes, although according to SDT that performance is likely less than would otherwise

be achieved when people are intrinsically motivated (Deci & Ryan, 1985). Given that when

people choose a career path as a matter of economic necessity, or work for the primary

motivation of payment, they are externally regulated (Gagné & Deci, 2005); it is logical that

controlled motivation should have a relationship with performance outcomes.

Subsequently, those people who learn to introject a behaviour that was initially motivated

extrinsically may feel a sense of pride or improved status after engaging in this behaviour,

contingent upon positive results as a consequence of the behaviour. Whilst they do not


58

experience a sense of ownership over the principle to act in business as an entrepreneur

they feel that they should engage in entrepreneurship anyway (Gagné & Deci, 2005). This

externally motivated behaviour likely has a relationship with financial performance

measures, such as firm and individual profit, whilst not being related to career satisfaction.

Hypothesis 4: There is a positive significant relationship between controlled motivation

(extrinsic motivation, introjected motivation) and entrepreneurial

performance (firm net profit, personal income and career satisfaction).

The Mediated Relationship between BPNT, OIT and EP

Satisfaction of the three basic needs for competence, autonomy and relatedness predict the

degree to which internalisation of entrepreneurial attitudes and behaviours will occur, that

is, that autonomous motivation will develop. The degree to which internalisation and

integration of entrepreneurial attitudes and behaviours occurs will predict the level of

entrepreneurial career performance. SDT focuses on the degree to which psychological

needs are satisfied (rather than the strength of the needs) as a predictor of outcomes (Deci

& Ryan, 2000). Intrinsic motivation, with elemental psychological needs for autonomy,

competence, and relatedness, activates the operation of the organismic integration process.

This process involves the “internalisation and integration of attitudes, values, motivations,

and emotional regulatory processes” (Deci & Ryan, 2012). When people experience

satisfaction of the needs for relatedness and competence, they will tend to internalise value

and regulate their behaviour (Gagné & Deci, 2005). The degree of satisfaction of the need


59

for autonomy will distinguish whether identification or integration, rather than just

introjection, will occur (Deci & Ryan, 1987). The greater the degree to which an individual

satisfies their need for competence, autonomy and relatedness in the context of

entrepreneurship, the greater their autonomous motivation will be. The greater their

autonomous motivation the more enhanced the person’s behaviours in the

entrepreneurship context will be, leading to greater EP (e.g. Baumeister & Leary, 1995;

Baard, Deci, & Ryan, 2004).

Hypothesis 5: The relationship between the satisfaction of the three basic psychological

needs (competence, autonomy, relatedness) and entrepreneurial

performance (firm net profit, personal income and career satisfaction) is

mediated by the strength of the person’s autonomous motivation.

The primary motive of this thesis is to investigate the mechanism that leads to, and is most

predictive of, EP. IEO (risk-taking propensity, innovativeness and proactivity) was shown to

have a relationship with EP in the summary of 5 meta-analyses of the relationship between

individual dispositions and EP. SDT provides two mechanisms described by two sub-theories

of SDT (Deci & Ryan, 2000) that explain how motivation in the entrepreneurship context

leads to EP. The first mechanism is described by basic psychological needs theory (BPNT), in

which the satisfaction of three basic needs (the needs for competence, autonomy and

relatedness) is predicted to lead to increased levels of internalised types of motivation, in

particular, autonomous motivation. The second mechanism is described by organismic

integration theory (OIT), which predicts that entrepreneurs with higher levels of internalised

motivation will experience optimal levels of entrepreneurial performance. This thesis posits


60

that in the presence of the satisfaction of basic psychological needs - autonomous

motivation and controlled motivation relationships with entrepreneurial performance, the

relationship between IEO and EP will reduce in magnitude.

Hypothesis 6a: The relationship between individual dispositions in entrepreneurship (risk,

innovativeness, proactivity) and entrepreneurial performance (firm profit,

individual profit, career satisfaction) will reduce in magnitude in the

presence of the hypothesised satisfaction of basic psychological needs-

autonomous motivation and controlled motivation relationships with

entrepreneurial performance.

This thesis further posits that the BPNT-OIT relationship predicts EP more strongly than do

individual dispositions (IEO) in entrepreneurship.

Hypothesis 6b: The satisfaction of basic psychological needs in conjunction with the

autonomous-controlled motivation continuum predicts entrepreneurial

performance (firm profit, individual profit, career satisfaction) more strongly

than individual dispositions in entrepreneurship (risk, innovativeness,

proactivity).

In summary, the review of the literature identified the multidimensional nature of EP,

evaluating a range of potential objective and subjective performance indicators, arriving at

measures of firm net profit and personal income (objective) and career satisfaction

(subjective) for this study. The role that individual dispositions play in shaping


61

entrepreneurial performance was examined in the context of uncertainty in the literature,

in conjunction with five meta-analyses of individual dispositions within entrepreneurship

research that provide empirical evidence of the relationships between individual

dispositions and EP measures (Stewart & Roth, 2001; Collins et al., 2004; Rauch & Frese,

2007; Rauch et al., 2009; Rosenbusch et al., 2013). Deductively, risk-taking propensity,

innovativeness and proactivity were identified as being representative of prototypical

personal characteristics in entrepreneurship, and forming an empirically validated construct

of entrepreneurial orientation (IEO). Risk-taking propensity, innovativeness and proactivity

were deemed the most appropriate characteristics for examination in the relationship

between prototypical individual differences in entrepreneurship and entrepreneurial

performance (EP). These findings formed the basis of the first of two process paths

identified in the literature (IEO-EP).

SDT was reviewed in the context of BPNT and OIT, two sub-theories of SDT, which form the

second process path identified in the literature (Deci & Ryan, 2000). The first mechanism of

this process path was described by BPNT, in which the satisfaction of three basic needs (the

needs for competence, autonomy and relatedness) predicts increased levels of autonomous

motivation (intrinsic, integrated and identified motivation). The second mechanism of this

process path was described by OIT, in which entrepreneurs with higher levels of

autonomous motivation (intrinsic, integrated and identified motivation), in conjunction with

controlled motivation (introjected and extrinsic motivation), exhibit increased levels of

entrepreneurial performance (BPNT-OIT-EP). The degree to which the three basic

psychological needs (BPNT; for competence, autonomy and relatedness) are satisfied,

determines the degree to which autonomous motivation (identified, integrated or intrinsic


62

motivation) occurs. In turn, the degree to which autonomous motivation (organismic

integration) occurs predicts EP. Accordingly, this thesis investigates whether 1) in the

presence of the BPNT-OIT-EP relationship, the IEO-EP relationship reduces in magnitude,

and 2) whether BPNT-OIT-EP more strongly predicts EP than IEO-EP.

The next chapter introduces the theoretical model that represents the two process paths

(IEO-EP; Hypothesis 1: BPNT-OIT-EP; Hypotheses 2-5) identified within the review of the

literature. The chapter proceeds with the procedure, sample and measures employed in the

study.

Chapter 3: Methodology

63


In the last chapter, the concept of entrepreneurial performance (EP) was introduced with

the evaluation of the different measures most commonly used within the literature. The

literature review proceeded with an examination of two process paths that lead to

entrepreneurial performance. The first process path (IEO-EP; Hypothesis 1) involves the

relationship between individual dispositions in the entrepreneurship domain, identified as

individual entrepreneurial orientation (IEO; risk taking propensity, innovativeness,

proactivity) and entrepreneurial performance (EP; firm net profit, individual net profit,

career satisfaction). The first process path relates to the first research question, ‘Is there a

relationship between the individual dispositions of entrepreneurs and entrepreneurial

performance?’

The second process path (BPNT-OIT-EP; Hypotheses 2-5) involves the relationship between

the satisfaction of basic psychological needs (BPNT; need for competence, autonomy and

relatedness), autonomous and controlled motivation as depicted by organismic integration

theory (OIT; extrinsic, introjected, integrated and intrinsic motivation) and EP. The second

process path relates to the second research question, ‘Is the degree of motivation to

entrepreneurship deterministic of entrepreneurial performance?’ The theoretical model of

the hypothesised relationships (RQ1; IEO-EP; H1: RQ2; BPNT-OIT-EP; H2-5) is shown in

Figure 3.1 below.


64

Figure 3.1. Theoretical model of the hypothesised relationships

Evaluation and comparison of these two process paths form the investigation of the third

research question, whether ‘the BPNT-OIT-EP relationship is more predictive of

entrepreneurial performance than IEO-EP amongst entrepreneurs?’

Procedure

Stratified, quota based sampling of Australian business owners was undertaken by way of an

internet-enabled panel. The pre-recruited panel was formed by e-mail invitation, banners

and messaging on Survey Sampling International (SSI) sites. SSI participants answer a series

of profiling questions (for example, ‘Do you, or have you owned a business?’) to be matched

with surveys that are related to business. Respondents either qualify and complete the

survey, and the data is provided, or they do not. Participants are rewarded by cash or

points, prizes or sweepstakes, or by being able to donate to charity. Participants were

randomly selected from SSI’s panels to be invited to take the survey. Survey self-selection


65

bias is reduced by specific project details not being included in the invitation. The data were

collected using Qualtrics’ online survey tool. The data were uploaded to SPSS 23 and Amos

23 for analysis.

Participants

A sample of 505 business owners completed the Individual Entrepreneurial Orientation

(IEO), Basic Psychological Needs (BPNT) and Motivation at Work (MAWS) questionnaires in

conjunction with a series of entrepreneurial performance measures. A final sample of 385

business owners was achieved (for data cleaning criteria and procedures see Missing Data).

The final sample showed the following dominant demographic qualities, with full data

reported in Table 3.1. The majority of business owners were also the founders of their

business (85.5%; 329). The most reported period in which businesses were commenced was

2000-2009 (35.6%; 137). The most common business size within the sample was Micro-

business (1 to 4 employees) (41.6%; 160). Fifty to fifty-nine year olds were the predominant

age group (21.6%; 83) and gender was evenly represented (194 males (50.4%) and 191

females (49.6%)). The most common level of education was a Certificate/Diploma (34.3%;

132). The majority of participants had not started any other business prior to the one they

presently own (64.4%; 248). Finally, the most common firm net profit in the previous 12

months was equal AUD 0 -10,000 and AUD 10,001 - 50,000 (25.2%; 97 each) and the most

common individual earnings derived from the business in the previous 12 months was AUD

10,001 - 50,000 (30.1%; 116). The businesses associated with the sample can be categorised

as poor performing and low paying.


66

The quality of the sample with respect to representativeness of entrepreneurs, as opposed

to lifestyle business owners, is very low. Indeed, only 29 out of 385 business owners (7.5%)

expressed a growth orientation. This number is insufficient to make significant findings with

respect to growth-oriented entrepreneurs within the sample. Sample characteristics are

provided in Table 3.1 below.

Table 3.1

Sample Demographics of Business Owners (N = 385)

Characteristic Response Frequency Percentage

Founder Yes 329 85.5

No 56 14.5

Year established 1904-1979 18 4.7

1980-1989 24 6.2

1990-1999 82 21.3

2000-2009 137 35.6

2010-2016 124 32.2

Number of employees, not

including respondent

0 147 38.2

1- 4 160 41.6

5- 19 57 14.8

20- 199 18 4.7

200+ 3 0.8

Age 18-29 37 9.6

30-39 72 18.7

40-49 75 19.5

50-59 83 21.6

60-69 69 17.9

70-79 24 6.2

Gender Female 191 49.6

Male 194 50.4

Education No formal education 3 0.8

Primary School 1 0.3

High school 72 18.7

Certificate/Diploma 132 34.3

Bachelor degree (Undergraduate) 108 28.1

Postgraduate degree (incl. Masters) 55 14.3

Doctoral Degree

14 3.6


67

Characteristic Response Frequency Percentage

Number of previous

businesses

0 248 64.4

1 84 21.8

2 39 10.1

3+ 14 3.6

Firm’s total net profit last 12 <0 29 7.5

months (AUD) 0 - 10,000 97 25.2

10,001 - 50,000 97 25.2

50,001 – 100,000 74 19.2

100,001 – 250,000 47 12.2

250,001 – 500,000 24 6.2

500,001+ 17 4.4

Individual’s total net profit <0 25 6.5

last 12 months (AUD) 0 - 10,000 100 26.0

10,001 - 50,000 116 30.1

50,001 – 100,000 82 21.3

100,001 – 250,000 34 8.8

250,001 – 500,000 17 4.4

500,001+ 3 0.8

Measures

Pre-validated scales were used in the study. Details of the scales used in the study are

provided below. The study incorporated independent variables measured using the

Individual Entrepreneurial Orientation (IEO) Scale, Basic Need Satisfaction at Work Scale

(BPNS), Motivation at Work (MAWS); and dependent variables measured using Firm Net

Profit, Personal Income and the Career Satisfaction Scale (CSS). Full scale items are shown in

Appendix 1.


68

Individual Entrepreneurial Orientation (IEO). The individual disposition items are based on

Lumpkin and Dess' (1996) original five EO (organisational) research variables (risk-taking

propensity, innovativeness, proactiveness, competitive aggressiveness, and autonomy).

Bolton and Lane (2012) used ten items to measure risk-taking propensity (3 items),

innovativeness (4 items) and proactivity (3 items) to measure individual entrepreneurial

orientation. Confirmatory factor analysis (CFA) resulted in three factors (see Confirmatory

Factor Analysis of the Individual Entrepreneurial Orientation Scale in the next chapter).

Factor one demonstrated risk-taking propensity (α = .850) amongst business owners, factor

two comprised innovativeness (α = .854) and factor three constituted proactivity (α = .856).

Items were measured on a scale from 1 (strongly disagree) to 7 (strongly agree).

Basic Psychological Needs Scale (BPNS). Deci et al. (2001) created the Basic Psychological

Needs Scale as a family of scales which address need satisfaction in general, and others that

address need satisfaction in specific domains. This study uses the Basic Need Satisfaction at

Work Scale. The original scale utilised 21 items related to the three basic needs for

competence, autonomy and relatedness. Some studies have incorporated only 9 items, with

3 items per subscale (Deci et al., 2001). Questions have been adapted from the work

context, such as ‘Most days I feel a sense of accomplishment from working’ to the context

of running one’s own business, such as ‘Most days I feel a sense of accomplishment from

running my business.’ Items were measured on a scale from 1 (strongly disagree) to 7

(strongly agree). Three factors represent competence (6 items; α = .672), autonomy (7

items; α = .683) and relatedness (8 items; α = .727). Convergent validity issues are discussed

in the next chapter (see Confirmatory Factor Analysis of Basic Psychological Needs).


69

Motivation at Work Scale (MAWS). Following Gagné et al. (2012) the study uses 12 items to

measure extrinsic (α = .767), introjected (α = .826), integrated (α = .900) and intrinsic

motivation (α = .913) (3 items each). CFA results are presented in the next chapter (see

Confirmatory Factor Analysis of the Motivation at Work Scale). Identified motivation has not

been measured as identified and integrated motivation have been found to be too

psychometrically similar to differentiate, and both represent higher degrees of autonomous

motivation (Gagne´ et al., 2012). Example items include ‘Because I enjoy this work very

much’ and ‘Because my reputation depends on it’. Items were measured on a scale from 1

(strongly disagree) to 7 (strongly agree).

Firm Net Profit. This is measured by using the self-reported firm net profit value over the

last 12 months. In this survey it equates to firm net profit over the 2015 calendar year. Firm

net profit is measured as a single item as dollars per year.

Personal income. Personal income is measured as a single item as dollars per year, using the

self-reported individual net profit value over the last 12 months. In this survey it equates to

personal income over the 2015 calendar year.

Career Satisfaction Scale (CSS). Following Greenhaus, Parasuraman, & Wormley (1990) the

CSS is a widely accepted measure of career satisfaction (Hofmans, Dries, & Pepermans,

2008; Spurk, Abele, & Volmer, 2011; Abele, Spurk, & Volmer, 2011). The CSS is a 5-item

scale, converted to a 7-point scale in this study for consistency. Respondents are asked to

rate their career satisfaction on a 7-point scale from 1 (strongly disagree) to 7 (strongly


70

agree). Items included satisfaction ratings with respect to ‘the progress I have made toward

meeting my goals for income’ and ‘the success I have achieved in my career’ (α = .951).

The theoretical model was subsequently tested for the hypothesised associations between

the research concepts. The next chapter presents the data cleaning and assumption testing

procedures, preliminary analyses and results of the study.

Chapter 4: Results

71

Chapter 4: Results

The previous chapter presented the study’s research methodology and design. A theoretical

model was developed from a review of the relevant literature surrounding the research

topic (see Chapter 3: Methodology), representing the IEO-EP mechanism (RQ1; Hypothesis 1)

of autonomous-controlled motivation and the underlying relationship with entrepreneurial

performance outcomes, and the BPNT-OIT-EP mechanism (RQ2; Hypotheses 2-5) of the

satisfaction of basic psychological needs, autonomous and controlled motivation, leading to

the internalisation of motivational dispositions, and entrepreneurial performance. The

theoretical model was subsequently tested for the hypothesised associations between the

research concepts. This chapter presents the results of those tests.

Data Cleaning and Assumption Testing Procedures

Assessment of Normality

Assumptions of univariate normality were tested by checking the values for skewness and

kurtosis for non-normality. Skewness and kurtosis coefficients were examined to assess the

distribution of the items. Shapiro Wilk statistics were examined by visually checking the

histograms and expected normal probability plots. All items were slightly negatively skewed

with values above -1.208 and less than 1.197, indicating univariate normality (within ±2.00)

(Field, 2000; Trochim & Donnelly, 2008; Gravetter & Wallnau, 2014). Kurtosis values were in

the majority negative, with values above -1.200 and less than 2.412; most distributions were

very slightly leptokurtic (Ruppert, 1987). Kurtosis values ≥7.00 are indicative of departure

from normality and therefore no items are kurtotic (Byrne, 2010, p.103). Departure from

Chapter 4: Results

72

normality is within limits (skewness ≤±2.00, kurtosis ≤7.00) which was further confirmed by

visual confirmation of the histograms of the data (Field, 2013; Pallant, 2013).

Missing Data

The initial sample size for this study was 505 respondents who identified as business

owners. Three forms of missing data were found. First, data were found to be missing for 5

respondents due to participant failure to complete the survey and were removed. These 5

responses were removed and the data were further screened for low-variability responses

to protect against misleading within-group variability, low reliability and errors in hypothesis

testing (Clark, Gironda, & Young, 2003; Meade & Craig, 2011).

Checks were made for problematic responses involving content non-responsivity, defined as

responding without regard to item content (see Nichols, Greene, & Schmolck, 1989). Such

data have previously been described as random response data (Beach, 1989; Berry, Wetter,

Baer, Larsen, Clark, & Monroe, 1992) or careless responding (Curran, Kotrba, & Denison,

2010). ‘Inattentive’ or ‘careless’ response references appear more appropriate than

‘random’ response given that such responses are inherently non-random in nature (Meade

& Craig, 2011). Accordingly, repeat responses that did not reflect attention to the content

were identified, for example, responding with the same value response across most items in

the survey. Additionally, inconsistent responses to reverse coded items provided

identification of further problematic responses. While reversing coded items is often

intended to reduce the effects of response styles (the tendency to answer items regardless

their content) there is no consensus that this is an effective strategy (van Sonderen,

Chapter 4: Results

73

Sanderman, & Coyne, 2013). While the reverse coding may not reduce the tendency to

answer items regardless of their content, it makes such responses more identifiable.

Subsequently, sixty-three cases of problematic responses were deleted list-wise.

Third, outlier analysis is recommended by Meade and Craig (2011) as another index for

careless response checks. The multivariate outlier analysis approach was used to identify

respondents who consistently provided responses far from the mean of a set of items

(Ehlers, Greene-Shortridge, Weekley, & Zajack, 2009). A multivariate assessment of each

observation was conducted using Mahalanobis D2 at a value of p = .001 (Tabachnick & Fidell,

2013). If the averaged Mahalanobis distance D2 exceeded this critical value, the item was

flagged for removal. Fifty-two multivariate outliers with responses consistently far from the

mean of the item sets were detected and flagged at the critical Mahalanobis D2 value of p =

.001 and were removed accordingly (Meade & Craig, 2011).

Common Method Variance

Due to the data being self-reported and collected through the same survey instrument,

common method variance (CMV) may be attributed to the measurement method and may

cause measurement error and bias of the estimates. The observed relationship variance

may be increased or decreased depending upon the method variance (Avolio, Yammarino, &

Bass, 1991; Crampton, & Wagner, 1994; Doty & Glick, 1998; Podsakoff, MacKenzie, Lee, &

Podsakoff, 2003). Harman’s one-factor test (via SPSS) and confirmatory factor analysis (via

AMOS) were conducted to test for CMV. First, all items were submitted to an exploratory

factor analysis (EFA), using un-rotated principle axis factoring with single factor extraction. If

substantial CMV were present, either a) the factor analysis would report a single factor, or

Chapter 4: Results

74

b) one general factor would explain more than 50% of the covariance among the variables

(see Andersson & Bateman, 1997; Aulakh & Gencturk, 2000; Podsakoff et al., 2003;

Krishnan, Martin & Noorderhaven, 2006). The threshold of 50% is a customary heuristic

(Eichhorn, 2014). Un-rotated principle axis factoring with single factor extraction explained

32.1% of the variance. Thus, according to Harman’s Single Factor analysis, no general factor

is present, (Harman, 1960). The CMV test results do not preclude the possibility of CMV,

however they do suggest that CMV is not of great concern for these measurement models

and thus is unlikely to confound the interpretations of results.

The Harman single-factor test has been criticised as a diagnostic test that “does nothing to

statistically control for (or partial out) method effects” (Podsakoff et al., 2003; p. 889).

Alternatively, a confirmatory factor analysis (CFA) common latent factor technique is a more

refined test of the extent to which a single factor can account for all of the variance in the

data. Using the latent variable approach, a first-order factor was added, with all of the

measurement items as indicators, to the theoretical model. The effect of the method factor

on all measures was thereby modelled (limitations of this approach are discussed in the next

chapter; see Limitations). The common latent factor method resulted in a common load

factor of .70, indicating a common method variance of 49%. While a heuristic 50% threshold

has been proposed (Eichhorn, 2014), Cote and Buckley (1987) examined the presence of

common method variance across 70 psychology-sociology, marketing, business, and

education studies. The amount of variance attributable to method biases varied

considerably by discipline and type of construct examined; with some disciplines commonly

reporting high CMV. For example, Cote and Buckley found that attitude measures contain

an average of 40.7% CMV (Podsakoff et al., 2003; p. 880).

Chapter 4: Results

75

The estimates of the item variance components in this study are possibly biased due to the

error terms in the measurement models being an aggregation of systematic, non-

systematic, and method effects (Lance, Noble & Scullen, 2002), thus making it difficult to

assess item validity and how well each measure reflects the individual disposition, need

satisfaction or motivational factor it is intended to represent. The methods may result in a

systematic effect on the observed correlation between the measures, providing a rival

explanation for the correlation observed between the measures (Podsakoff et al., 2003).

Accordingly, CMV is a factor in the measures employed in this study, however, a high level

of CMV is typical of the measures used in this study. Further, the magnitude of zero order

correlations varies considerably, for example, from 0.04 (Extrinsic-Innovativeness) to more

than 0.74 (Competence-Relatedness). Thus, while measurement error can overestimate the

observed correlation between the measures (Cote and Buckley, 1988) this level of bias may

be cause for concern but does not invalidate the research findings (Doty & Glick, 1998).

Correlations

Correlations and internal consistency estimates among all measure variables are shown in

Table 4.1 at the end of this section. It was predicted that individual dispositions in

entrepreneurship (IEO; risk taking propensity, innovativeness, proactivity) are related to

entrepreneurial performance (firm net profit, personal income and career satisfaction). The

correlations between IEO variables and the financial dependent variables are very weak,

offering some support for the theory of the relationship between individual dispositions in

entrepreneurship and their relationship with entrepreneurial performance. Both risk taking

propensity and innovation were found to have a significant weak relationship with firm net

Chapter 4: Results

76

profit (r = .11, p = < .05; r = .13, p = < .05 respectively), but were not significantly correlated

with personal income. Proactivity was not significantly correlated with either of the two

financial dependent variables, however it was significantly correlated with the subjective

non-financial dependent variable, career satisfaction (r = .39, p = < .01). All three IEO

variables were shown to be significantly related to career satisfaction. Proactivity had a

moderate relationship with career satisfaction (r = .39, p = < .01), and was stronger than

both risk propensity (r = .14, p = < .01) and innovativeness (r = .16, p = < .01) in this

relationship. These correlations show partial support for the relationship between IEO

variables and EP (H1).

All variables identified within the self-determination theory (SDT) sub-theories, basic

psychological needs theory (BPNT; satisfaction of the needs for competence, autonomy,

relatedness) and organismic integration theory (OIT; extrinsic, introjected, integrated and

intrinsic motivation) show significant correlations that support their theoretical

relationships (refer to Table 4.1 for correlations). The three BPNT variables (competence,

autonomy, relatedness) are significantly positively related to each of the OIT variables

(extrinsic, introjected, integrated and intrinsic motivation). The satisfaction of the basic

psychological needs is least strongly associated with extrinsic motivation and most strongly

associated with intrinsic motivation. The correlations are incremental in strength, from

extrinsic motivation to introjected (weakest), introjected to integrated, and integrated to

intrinsic (strongest). These correlations, specifically the relationship between BPNT factors

and autonomous motivation (intrinsic and integrated motivation), provide substantial

support for the theoretical relationship between BPNT and OIT (see Koestner, Losier,

Vallerand, & Carducci, 1996; Pelletier et al., 1998; Koestner & Losier, 2002; Ryan, 2010) (H2).

Chapter 4: Results

77

Support for the theoretical BPNT-OIT-EP relationships introduced in the study is found in all

four OIT variables showing significant moderate relationships with career satisfaction, with

the autonomous motivation variables showing the strongest relationship (H3). Extrinsic

motivation had a moderate significant relationship with both firm and individual profit,

which is in keeping with SDT and gives support for H4. Extrinsic motivation has a stronger

relationship with the financial dependent variables than introjected motivation, and the

autonomous motivation variables of integrated and intrinsic motivation. Hypothesis four is

well supported. Intrinsic motivation shows no significant relationship with the financial

dependent variables, however integrated motivation shows a weak significant relationship

to personal income. All four OIT variables show strong significant relationships with career

satisfaction, providing further support for hypotheses 3 and 4. The three BPNT variables

show weak, non-significant in the main, relationships with firm and individual profit. This is

inconsistent with the expectation of a mediated relationship between BPNT variables and

EP (H5). The strength of the BPNT-OIT-EP correlations is substantially higher than the IEO-

EP correlations providing good support for H6a and H6b. Means, standard deviations and

Pearson correlations among all measure variables are shown in Table 4.1 below.

Chapter 4: Results

78

Table 4.1

Means, Standard Deviations, Correlations and Internal Consistency Among All Variables (N= 385)

Variables Mean SD (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

(1) Risk-taking 4.17 1.19 (.850)

(2) Innovation 4.55 1.09 .548** (.854)

(3) Proactivity 5.17 1.02 .412** .474** (.856)

(4) Competence 5.26 0.92 .321** .372** .530** (.672)

(5) Autonomy 5.54 0.99 .237** .296** .511** .669** (.683)

(6) Relatedness 5.46 0.90 .200** .294** .515** .738** .698** (.727)

(7) Intrinsic 5.30 1.16 .298** .288** .408** .597** .568** .552** (.913)

(8) Integrated 5.24 1.14 .287** .256** .419** .586** .530** .475** .693** (.900)

(9) Introject 4.59 1.26 .331** .286** .324** .340** .268** .293** .436** .502** (.826)

(10) Extrinsic 4.17 1.25 .150** .037 .080 .253** .133** .122* .257** .428** .494** (.767)

(11) Firm Profit 3.40 1.53 .109* .129* .013 .055 -.069 -.016 .034 .094 .222** .368** ( - )

(12) Personal Income 3.28 1.49 .082 .024 -.009 -.042 -.102* -.083 .015 .104* .179** .327** .664** ( - )

(13) Career Satisfaction 4.86 1.22 .135** .160** .388** .443** .330** .417** .375** .437** .265** .343** .195** .124* (.951)

** p < 0.01 level (2-tailed) *p < 0.05 level (2-tailed); Scale Cronbach alpha coefficients reported on diagonal; IEO-EP; BPNT-OIT; BPNT-EP; OIT-EP

Chapter 4: Results

79

Preliminary Analyses

Data Analysis

The preliminary analyses section of Chapter 4 is divided into three sub-sections. The fit of

three respective factor solutions to measurement models was assessed by confirmatory factor

analysis (CFA) using AMOS 23. First, the individual entrepreneurial orientation (IEO) scale was

tested. Second, the basic psychological needs scale was tested. Third, the motivation at work

scale was tested. The adequacy of model fit was examined through the following four

goodness-of-fit indices (Hu & Bentler, 1999): chi-square statistics; root-mean-square error of

approximation (RMSEA) of .05 or less; Standardized Root-Mean-Square Residual (SRMR) of .08

or less; and Comparative Fit Index (CFI), best if above .95. SRMR, RMSEA, and the CFI were

chosen based on evidence that they are sensitive to misspecified factor correlations and

misspecified factor loadings, and are commonly used in conjunction with maximum likelihood

estimation (Hu & Bentler, 1998, 1999; Brown, 2006). Common method variance (CMV) tests

were conducted on the three measurement models; IEO, BPNS and MAWS. To compare two or

more models, the χ2 difference test was used when models were nested, and the Akaike

Information Criterion (AIC: Akaike, 1987) was examined when models were not nested, with

smaller values being indicative of a better fit of the hypothesized model. The guiding

acceptable thresholds of model fit indices are shown in Table 4.2.

Chapter 4: Results

80

Table 4.2

Model fit indices (MFI) and their acceptable thresholds

Fit Index Threshold Reference

Absolute Fit Indices

χ2 (chi squared) Byrne (2011)

df (degrees of freedom)

p < .05 indicates significance

Standardised Root Mean Residual (SRMR) < .05 indicates good fit Hu & Bentler (1998)

Approximate Fit Index

Root Mean Square Approximation (RMSEA) < .05 indicates good fit

< .08 is acceptable

Hu & Bentler (1998)

Incremental Fit Index

Comparative Fit Index (CFI) > .95 Albright & Park (2009)

Confirmatory Factor Analysis of the Individual Entrepreneurial Orientation Scale

The IEO measurement model consisted of three latent factors (risk, innovativeness and

proactivity) and 10 observed variables. An initial test of the measurement model revealed an

unsatisfactory fit to the data: χ2 = 215.53, df = 32, p < .000; RMSEA = .122; SRMR = .068; CFI =

.915; and AIC = 261.53). The CFA of the IEO model was checked to assess whether any of the

items were co-varying with other items above a modification index (MI) of 10.00. Error item

Innovation 3 co-varied with error item Innovation 4 at 25.09; the error items were co-varied (r

= 0.30) and the CFA was re-run (AIC = 222.70). The fit of the model was improved. Checks of the

modification indices revealed that Proactivity 1 co-varied with a number of items (Innovation 4

at 17.11; Innovation 3 at 16.62; Risk 3 at 16.03). Proactivity 1 was not removed to maintain

internal consistency of the proactivity scale. No further modifications could be made to

improve the model fit. Post-modification, the measurement model revealed an improved

model fit (χ2 difference test shows a change from 215.53 to 174.70) but still a poor fit to the

data: χ2 = 174.70, df = 31, p < .000; RMSEA = .110; SRMR = .063; and CFI = .933. All

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standardised estimates were above .704 and all the SMC statistics were above .495. The

squared multiple correlations (SMC), which are included below, represent the proportion of

variance of each of the 10 items that is explained by the latent factor on which it loads, that is,

is shared with the other items that form that factor. The item Risk 1 has an SMC estimate of

0.649, which means that 64.9% of the variance of the item Risk 1 is shared by all other risk

items indicating that this item measures the same as the other items. The model explains Risk 3

the best (73.3% of the variance explained), and explains other items reasonably well, although

it does not explain Innovativeness 3 and Innovativeness 4 as well, explaining only about half of

the variation. The proportion of the total variation explained by the three factors is 60.3% (the

percentage of variation explained in the model). The standardised estimates and SMCs for the

final version of the IEO model are presented in Table 4.3 below. All the items were retained.

Table 4.3

IEO Standardised Estimates, Critical Values and Squared Multiple Correlations

Standardised Estimates

IEO Items 1 2 3 SMC*

Risk-taking Innovativeness Proactivity

Risk 1 .805 .649

Risk 2 .769 .591

Risk 3 .856 .733

Innovativeness 1 .786 .618




Proactivity 1 .829 .688

Proactivity 2 .834 .695

Proactivity 3 .787 .619 *Note: all estimates significant at p < .001

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Confirmatory Factor Analysis of Basic Psychological Needs

The BPNS measurement model consisted of three latent factors (competence, autonomy and

relatedness) and 21 observed variables. An initial test of the measurement model revealed a

poor fit to the data: χ2 = 1659.28, df = 186, p < .000; RMSEA = .144; SRMR = .156; CFI = .581;

and AIC = 1749.28). Autonomy 5 and Relatedness 7 were found to be not statistically reliable (p

> .05); these items were removed and the CFA was re-run (AIC = 1490.56). Many items were

found to have low squared multiple correlations (SMCs). Using SMCs as estimates of variable

communality, Competence 3, 14, 19; Autonomy 11, 13, 20; and Relatedness 9, 16, 18 were

removed. After these items were modified, the Akaike information criteria (AIC: Akaike, 1973,

1987) were checked to ensure they continued to decrease; both statistics decreased and model

fit improved at each interval (final AIC = 237.54). The final measurement model revealed good

fit to the data: χ2 = 94.86, df = 32, p < .000; RMSEA = .072; SRMR = .035; and CFI = .964. Given

the significant reduction in scale items that did not reflect the construct being investigated,

construct validity should be confirmed.

Benson (1998; also see Benson & Hagtvet, 1996) outlined a framework of three stages required

to establish construct validity: substantive, structural, and external. The first stage (substantive)

refers to the work done in the literature review of this study in defining the theoretical and

empirical domains of the construct. The second stage (structural) involves examination of the

relationships between the items by assessing the correlations, internal consistency, and factor

analysis. The third stage (external) involves examining if the construct is related to external

constructs in ways that are theoretically expected (Johnston & Finney, 2010). In this study, the

third (external) stage involves novel work done by Johnston and Finney (2010) who, following

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83

Benson’s (1998) program of construct validity, gathered external validity evidence for the

BPNS. The authors found that the three needs factors are distinct, and related to external

variables both theoretically and empirically. Johnston and Finney’s (2010) study examined the

dimensionality of the measure and used the resulting factor structure (which highly

corresponds with those items removed and retained within this study) to assess relationships

with theoretically-related variables (see Gagné, 2003; Wei, Philip, Shaffer, Young, & Zakalik,

2005; Vansteenkiste et al., 2006; Meyer, Enstrom, Harstveit, Bowles, & Beevers, 2007;

Thøgersen-Ntoumani & Ntoumanis, 2007; Niemiec, Ryan, & Deci, 2009; Kashdan, Mishra,

Breen, & Froh, 2009). The final model represents the theoretical SDT construct of BPNT well,

and provides support for Johnston & Finney’s criticism and reduction of the original BPNS

model (discussed in more detail in Theoretical Implications). The standardised estimates and

SMCs for the final version of the BPNS Model are presented in Table 4.4. All standardised

estimates were above .571 and all SMC statistics were above .326 (Relatedness 15).

Table 4.4

BPNS Standardised Estimates and Squared Multiple Correlations

Standardised Estimates

BPNS Items 1 2 3 SMC*

Competence Autonomy Relatedness

Competence 4 .604 .364



Autonomy 1 .789 .623

Autonomy 8 .836 .699

Autonomy 17 .627 .393

Relatedness 2 .768 .589



Relatedness 21 .735 .540 *Note: all estimates significant at p < .001

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Confirmatory Factor Analysis of the Motivation at Work Scale

The MAWS measurement model consisted of four latent factors (intrinsic motivation,

integrated motivation, introjected motivation and extrinsic motivation) and 12 observed

variables. An initial test of the measurement model revealed a poor fit to the data: χ2 = 232.79,

df = 48, p < .000; RMSEA = .100; SRMR = .075; CFI = .939; and AIC = 292.79. All the factor

loadings for the indicators on the latent variables were reliable (p < .001); each latent factor

was well represented by its respective indicators. The CFA of the MAWS Model was checked to

assess whether any of the items were co-varying with other items above a modification index

(MI) of 10.00. Error item Extrinsic 2 co-varied with error item Extrinsic 3 at 25.33; error item

Extrinsic 2 and error item Extrinsic 3 were co-varied and the CFA was re-run (r = .38; AIC =

256.68). The AIC value reduced and the model fit improved. Extrinsic 3 co-varied with a number

of items with a modification index > 10.00 (with the latent Intrinsic factor at 19.50; Intrinsic 1 at

21.07; Intrinsic 2 at 15.872 and Integrated 3 at 15.01). Extrinsic 3 was a candidate for removal

with the lowest squared multiple correlation, however, the item was not removed in the

interest of construct validity. All 12 items were retained.

The model explains Intrinsic 2 the best (86.9% of the variance explained), and explains other

items well, although it does not explain Introjected 1, Extrinsic 2 or Extrinsic 3 as well;

explaining only about half to less than 20% of the variation respectively. The proportion of the

total variation explained by the four factors is 65.9% (the percentage of variation explained in

the model). The final model showed satisfactory fit to the data: χ2 = 194.68, df = 47, p < .000;

RMSEA = .090; SRMR = .065; and CFI = .951. The standardised estimates and SMCs for the final

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85

version of the MAWS Model are presented in Table 4.5. All of the standardised estimates were

above .431 and all of the SMC values were above .185 (Extrinsic 3).

Table 4.5

Confirmatory Factor Analysis of MAWS Path Loadings

MAWS Items Standardised Estimates

1 2 3 4 SMC*

Intrinsic Integrated Introjected Extrinsic

Intrinsic 1 .879 .773



Integrated 1 .896 .861



Introjected 1 .745 .554



Extrinsic 1 .856 .733

Extrinsic 2 .733 .537

Extrinsic 3 .431 .185 *Note: all estimates significant at p < .001

Structural Models

Due to the problematic nature of the measures inherently associated with a full latent BPNT-

OIT-EP model it is ideal to describe the directed dependencies among the variables by way of a

path model. The model resulted in very poor model fit, with no obvious solution. As a

compromise, factor scores were used to capture the latent variables without resorting to

unweighted composite variables (which would involve an assumption that all items have an

equal relationship with the underlying construct). An assumption that all items have an equal

relationship with the underlying construct would not be consistent with empirical findings to

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86

the contrary, with differential relationships between individual BPNS subscale scores and

external variables being exhibited (e.g. Gagné, 2003; Vansteenkiste et al., 2006; Thøgersen-

Ntoumani & Ntoumanis, 2007; Kashdan et al., 2009). Accordingly, path models were created to

test the directed dependencies among the IEO-EP variables and the directed dependencies

among the BPNT-OIT-EP variables. All variable scores were estimated using factor score

weights. This procedure was conducting using Amos 23. Path models were then tested using

these factor scores. The IEO-EP path model was tested first to establish the base reference

point for comparison between the BPNT-OIT-EP and IEO-EP models.

IEO-EP Path Model

The IEO-EP path model depicts the relationship between independent variable IEO factors (risk-

taking, innovativeness, proactivity) and the three dependent variables (firm net profit, personal

income, career satisfaction). Both the latent factor and direct path models were tested. In the

below model, factor scores were used to capture the latent IEO variable for consistency in the

comparison between the IEO-EP and BPNT-OIT-EP models. The three IEO factors form one

latent construct (Individual Entrepreneurial Orientation) which represents the general tendency

to behave entrepreneurially. The IEO-EP path model relationships are shown in Figure 4.1.

Figure 4.1. IEO-EP Path Model Relationships

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87

An initial test of the IEO-EP path model revealed very poor fit to the data: χ2 = 232.79, df = 48,

p < .000; RMSEA = .100; SRMR = .075; and CFI = .939. The modification indices showed that

personal income error item co-varied with the firm net profit error item with a modification

index of 168.85; the personal income error item and the firm net profit error item were co-

varied within the model (r = .66). The remaining dependent variable error terms were co-varied

for comparison compatibility with the BPNT-OIT-EP model. The model fit improved, χ2 = 54.10,

df = 6, p < .000; RMSEA = .144; SRMR = .054; CFI = .914; and AIC = 84.10 (except for RMSEA).

Similarly, the risk-taking and innovativeness error terms were co-varied (r = .47; AIC = 45.36).

The final model showed improvement and good model fit: χ2 = 13.36, df = 5, p < .020; RMSEA =

.066; SRMR = .044; and CFI = .985. The IEO factor loadings were identified for risk-taking (.458),

innovativeness (.530) and proactivity (.895). The standardised coefficients for the IEO-EP Model

are shown in Table 4.6.

Table 4.6

Standardised Direct and Total Effects for IEO-EP Model

Independent

Variables

Dependent

Variables

β b S.E. Hypothesis support

Direct Effects

IEO Firm Net Profit -.006 -.021 .169 H1 N

IEO Personal Income -.015 -.052 .168 H1 N

IEO Career Satisfaction .355*** 1.010 .156 H1 Y

Note. *p< .05; **p<.01; ***p<.001

Hypothesis 1 proposed that individual dispositions (risk taking propensity, innovativeness,

proactivity) would relate to EP (firm net profit, personal income and career satisfaction). IEO, as

a 1st order latent variable, is significantly and positively related to one of the three dependent

variables, career satisfaction (β = .36, p < .001). IEO was not significantly, nor positively, related

Chapter 4: Results

88

to firm net profit nor personal income. Hypothesis 1 was partially supported (career

satisfaction).

BPNT-OIT-EP Path Model

Several researchers have merged the BPNS factors as a total needs satisfaction score (Gagné,

2003; Vansteenkiste et al., 2006; Meyer et al., 2007). Several researchers have merged external

and introjected motivation regulation into a controlled motivation latent variable, and

combined identified and intrinsic motivation regulation into an autonomous motivation latent

variable (e.g., Vansteenkiste, Lens, De Witte, De Witte, & Deci, 2004). Accordingly, factor scores

were used to capture three latent variables in Satisfaction of BPN, controlled motivation and

autonomous motivation. The BPNT-OIT-EP path model relationships are shown in Figure 4.2.

Figure 4.2. BPNT-OIT-EP Path Model Relationships

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89

An initial test of the BPNT-OIT-EP path model revealed a poor fit to the data: χ2 = 333.43, df =

52, p < .000; RMSEA = .119; SRMR = .081; and CFI = .875. The modification indices showed that

multiple error terms co-varied within the model. Within-construct error items were co-varied

as the model was sequentially rerun. The dependent variable error items were co-varied (χ2 =

289.15, df = 49). Controlled was co-varied with the autonomous error item (r = .61, χ2 = 226.29,

df = 48). Error item risk was co-varied with error item innovativeness (r = .40, χ2 = 175.33, df =

47). The final model showed a good fit to the data: χ2 = 175.33, df = 47, p < .000; RMSEA = .08;

SRMR = .06; and CFI = .943. The standardised direct, indirect and total effects for the BPNT-OIT-

EP model are shown in Table 4.7.

Table 4.7

Standardised Direct, Indirect and Total Effects for the BPNT-OIT-EP model

Independent

Variables

Dependent

Variables

β b S.E. Hypothesis support

Direct Effects

IEO Firm Net Profit -.003 -.009 .274 H1 N

IEO Personal Income .053 .144 .249 H1 N

IEO Career Satisfaction .132 .298 .181 H1 N

Satisfaction (BPN) Autonomous .785*** .930 .069 H2 Y

Autonomous Firm Net Profit -.540* -.881 .369 H3 N

Autonomous Personal Income -.174 -.276 .313 H3 N

Autonomous Career Satisfaction .037 .048 .221 H3 N

Controlled Firm Net Profit .753*** 1.295 .287 H4 Y

Controlled Personal Income .548*** .918 .243 H4 Y

Controlled Career Satisfaction .253* .348 .166 H4 Y

Satisfaction (BPN) Firm Net Profit .114 .221 .326 - -

Satisfaction (BPN) Personal Income -.211 -.396 .287 - -

Satisfaction (BPN) Career Satisfaction .257† .396 .205 - -

Indirect Effects

Satisfaction (BPN) Firm Net Profit -.424** -.819 .463 H5 N

Satisfaction (BPN) Personal Income -.136 -.256 .382 H5 N

Satisfaction (BPN) Career Satisfaction .029 .044 .288 H5 N

Note. β = Standardised regression weights; b = Unstandardised regression weights; CR = Critical ratio; SE =

Standardised Error; †p < .1; *p < .05; **p <.01; ***p <.001.

Chapter 4: Results

90

Direct Effects

Hypothesis 1 proposed a relationship between IEO (risk taking propensity, innovativeness,

proactivity) and the dependent variables (firm net profit, personal income and career

satisfaction). IEO had no significant relationship with firm net profit, individual income or

career satisfaction. Support for hypothesis 1 therefore was not obtained. Hypothesis 2

proposed that the satisfaction of the three basic psychological needs (competence, autonomy,

relatedness) has relationship with autonomous motivation (intrinsic motivation, integrated

motivation). Support was found for hypothesis 2 in satisfaction of BPN having a strong

significant relationship with autonomous motivation (β = .79, p < .001). Support for hypothesis

3 (the positive relationship between autonomous motivation and EP (firm net profit, personal

income and career satisfaction) was not found. Autonomous motivation showed a significant,

but negative, relationship with firm net profit. Autonomous motivation was not significantly

related to personal income or career satisfaction. Hypothesis 4 (the relationship between

controlled motivation (extrinsic motivation, introjected motivation) and EP (firm net profit,

personal income and career satisfaction) was supported across each of the dependent

variables; firm net profit (β = .753, p < .001), personal income (β = .548, p < .001), and career

satisfaction (β = .253, p < .05).

Indirect Effects

Hypothesis 5 suggests that a positive relationship between BPNT and EP is mediated by the

person’s autonomous motivation. In order to test for indirect effects of Satisfaction (BPN) upon

the entrepreneurial outcomes proposed, a test using the bootstrapping method to estimate

the standard error of the indirect effect with maximum likelihood estimates and 1000 samples

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91

was conducted via Amos 23. Support for hypothesis 5 was not found. Satisfaction (BPN) was

negatively significantly and indirectly related with firm net profit (β = -.42, p < .01). Satisfaction

(BPN) had no significant relationship with personal income or career satisfaction. A suppression

effect may be observed when the direct and mediated effects of an independent variable (IV)

on a dependent variable (DV) have opposite signs (Tzelgov & Henik, 1991; Cliff & Earleywine,

1994; MacKinnon, Krull, & Lockwood, 2000). This is the case for the direct relationship

between the satisfaction of BPN and firm net profit, reported as .114, p = .50, and the indirect

relationship between the satisfaction of BPN and firm net profit, reported as -.424, p < .01.

While hypothesis five was not supported, suppression effects may be the cause. Figure 4.3

illustrates the path model with the significant standardised and non-significant pathways

shown.

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92

Figure 4.3. Observed BPNT-OIT-EP Model

Chapter 4: Results

93

Path Model Comparison

Hypothesis 6a proposed that in the presence of the satisfaction of basic psychological needs in

conjunction with autonomous-controlled motivation, the relationship between individual

dispositions in entrepreneurship (risk, innovativeness, proactivity) and entrepreneurial

performance (firm profit, individual profit, career satisfaction) will reduce in magnitude. In the

IEO-EP model estimation, IEO was found to have a significant relationship with only career

satisfaction (β = .36, p < .001). The paths from IEO to firm and individual profit were not

significant and were very small in magnitude. In the full BPNT-OIT-EP model estimation, no

significant relationship was found between IEO and firm net profit, personal income, nor career

satisfaction. The potential for reduction for firm net profit or individual profit was limited due

to the small magnitude of the relationship in the IEO model. However, for IEO to career

satisfaction, the coefficient was of sufficient size that a drop of some magnitude was observed.

To test the significance of the magnitude of the diminution of the IEO - career satisfaction

relationship, the path in the full model was constrained to the higher value of the

unstandardized path found in the IEO only model. Results showed that model fit for the

constrained model was not significantly different than for the unconstrained model, suggesting

the drop in magnitude of the coefficient for IEO to career satisfaction was not significant

(career satisfaction: χ2 = 1.21, df = 1, p = .73). While the drop in the magnitude of the path was

sizeable, the hypothesis was not statistically supported.

Hypothesis 6b proposed that the BPNT-OIT relationship predicts EP more strongly than

individual dispositions (IEO) in entrepreneurship. In the full BPNT-OIT-EP model, controlled

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94

motivation (introjected and extrinsic motivation) exhibited moderate to strong relationships

with all three EP dependent variables. Extrinsic motivation was significantly related to firm

profit (β = .75, p < .001), significantly related to personal income (β = .55, p < .001), and

significantly related to career satisfaction (β = .25, p < .01). Autonomous motivation (integrated

and intrinsic motivation) for this sample was moderately negatively related to firm net profit (β

= -.54, p < .05). In comparison, within the IEO-EP model, IEO was not significantly, nor

positively, related to firm net profit nor personal income; IEO was significantly and positively

related to only one of the three dependent variables, career satisfaction (β = .36, p < .001).

Within the full model, the relationships between a person’s motivation and entrepreneurial

outcomes (BPNT-OIT-EP) have stronger and broader significant relationships to the different

(objective and subjective) dimensions of EP, than the relationship between IEO and EP. While it

was expected that both autonomous motivation and controlled motivation would be the

confluence in the reduction of the significance of the IEO-EP relationship, controlled motivation

(for this sample) had the dominant effect while autonomous motivation effects appear to have

been suppressed. In terms of comparative effect sizes and significant paths, the BPNT-OIT-EP

relationship more strongly predicts EP than IEO variables. Hypothesis 6b was supported.

In summary, the final IEO-EP path model showed good fit to the data, however IEO showed a

significant and positive relationship with career satisfaction only, and was not significantly, nor

positively, related to firm net profit nor personal income; Hypothesis 1 was only partially

supported. The final BPNT-OIT-EP path model did not provide support for Hypothesis 1 (IEO

had no significant relationship with firm net profit, individual income or career satisfaction).

Support for hypothesis 2 (the satisfaction of BPN having a strong significant relationship with

autonomous motivation) was found, while support for hypothesis 3 (the positive relationship

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95

between autonomous motivation and EP) was not found. Autonomous motivation was not

significantly related to personal income or career satisfaction. In contrast, solid support was

found for hypothesis 4 in the relationship between controlled motivation (extrinsic motivation,

introjected motivation) and EP. H4 was supported across each of the dependent variables; firm

net profit, personal income and career satisfaction. This is likely attributable to the generally

poor performing and low paying nature of the sample. Satisfaction (BPN) was negatively,

significantly and indirectly related with firm net profit, and had no significant relationship with

personal income or career satisfaction, meaning that hypothesis 5 was not supported, possibly

due to a suppression effect (Tzelgov & Henik, 1991; Cliff & Earleywine, 1994; MacKinnon, Krull,

& Lockwood, 2000).

Path model comparisons between the IEO-EP and BPNT-OIT-EP models tested hypothesis 6a

(that in the presence of the satisfaction of the BPNT-OIT-EP relationship, the relationship

between IEO-EP will reduce in magnitude). While the reduction in magnitude of the coefficient

for IEO to career satisfaction was not significant, the reduction in the magnitude of the path

was sizeable, but not sufficiently significant that hypothesis 6a was statistically supported.

Within the full BPNT-OIT-EP model (testing BPNT-OIT-EP vs IEO-EP), the relationships between

a person’s motivation and entrepreneurial outcomes (BPNT-OIT-EP) had stronger and broader

significant relationships to the different (objective and subjective) dimensions of EP, than the

IEO-EP relationships. Hypothesis 6b was supported by the finding that in terms of comparative

effect sizes and significant paths, the BPNT-OIT-EP relationship more strongly predicted EP than

the IEO variables. The next chapter proceeds with a discussion of these findings.

Chapter 5: Discussion

96


This thesis aimed to explore the foundational proposition that the satisfaction of the basic

psychological needs for competence, autonomy and relatedness, leads to autonomous

motivation (intrinsic and integrated motivation). The BPNT-OIT relationship was introduced as

the mechanism by which autonomous and controlled motivation (extrinsic and introjected

motivation) lead to EP. It was hypothesised that the degree to which the three basic

psychological needs (BPNT) are satisfied, determines the degree to which autonomous

motivation occurs. In turn, the degree to which autonomous motivation occurs (achieved by

organismic integration of the motivation factors), in conjunction with controlled motivation, is

argued to predict EP. Thus, it was proposed that BPNT and OIT together provide an

explanation of the role of motivation in predicting variation in EP, and that the BPNT-OIT-EP

relationship is more predictive of EP than IEO variables. Turning to the hypotheses in turn, this

study makes several theoretical and applied contributions to these arguments, and the

entrepreneurship and psychology literatures.

First, Gartner (1989) and Aldrich (1999) were both critical of the notion that there exists a

measurable relationship between individual dispositions and entrepreneurial performance (EP).

Davidsson (1989, p. 224) argued that the inclusion of individual dispositions “would not have

more than a marginal effect on our ability to explain variations in growth aspirations”.

Meta-analyses of the entrepreneurship literature (Stewart & Roth, 2001; Collins et al., 2004;

Rauch & Frese, 2007; Rauch et al., 2009; Rosenbusch et al., 2013) evince a different picture of

the relationships between individual dispositions and EP. Of the most widely studied individual

dispositions, risk-taking, innovativeness and proactivity are the most established in terms of


97

being representative of individual dispositions and related to EP. These three dispositions are

known together at the individual-level as ‘individual entrepreneurial orientation’ (IEO) and are

argued to predict EP at the individual level (Bolton & Lane, 2012; Bolton, 2012). Individual

dispositions in entrepreneurship were proposed to be positively and significantly related to EP.

It was hypothesised (H1) that IEO, as a 1st order latent variable, was significantly and positively

related to each of the three dependent EP variables (firm net profit, personal income and

career satisfaction). IEO showed a weak significant relationship with career satisfaction, while

the relationships with firm net profit and personal income were not statistically significant. The

goodness of fit statistics for the IEO-EP model showed a good fit of the model to the data. The

results, in conjunction with the external sources of meta-analytic results in the review of the

literature, provide some determination for the general conclusion that individual dispositions

are at least associated with entrepreneurial performance. Hypothesis 1 was partially

supported.

Second, it was hypothesised (H2) that the satisfaction of basic psychological needs

(competence, autonomy, relatedness) in the entrepreneurship domain is significantly and

positively related to autonomous motivation (intrinsic and integrated). Strong support was

found for this relationship; the theoretical BPNT-OIT constructs were well supported. Similarly,

external examination of the construct established that these findings related very well to

external testing of the construct in theoretically expected ways. Further, the reduced BPNT

model adequately fit the data consistent with external analyses of similarly reduced models.


98

Third, the OIT component variables, measured using latent autonomous (intrinsic, integrated)

and controlled (introjected, extrinsic) motivation variables, were hypothesised to be significant

positive predictors of EP (H3). The latent psychological needs satisfaction variable

(competence, autonomy, relatedness) was significantly related to the latent OIT autonomous

variable but did not provide support for the relationship between the OIT autonomy construct

and EP for this sample (see sampling issues discussion in the Limitations section). SDT suggests

that people who are intrinsically motivated are more likely to find the activity inherently

interesting and enjoyable, engage in required tasks proactively, improve their skills, and

experience greater levels of performance (Ryan & Deci, 2000a). In the entrepreneurship

domain it is expected that such performance would relate to financial return-based outcomes

and career satisfaction, however, this is not reflected in these results and hypothesis 3 was not

supported. These results are not in concert with Deci and Ryan’s (1985, 2000) work in SDT.

Fourth, controlled motivation (introjected and extrinsic motivation) was hypothesised to have a

significant positive relationship with EP (H4). Extrinsic motivation was found to have positive

significant strong (firm net profit), moderate (personal income) and weak (career satisfaction)

relationships with the dependent variables. In keeping with SDT, in which monetary rewards

are identified as an extrinsic motivator (Deci & Ryan, 1985), extrinsic motivation has a stronger

relationship with the financial dependent variables than autonomous motivation (which

actually shows a moderate significant negative relationship with firm net profit). This finding

fits part of the theory well; support for the autonomous motivation relationship was not found

within this sample, whereas strong support for the controlled motivation relationship was

found. People are externally motivated by financial incentives according to SDT (Deci & Ryan,

2000). When people undertake an action because they can gain something that is separable


99

from the activity, when they work for the primary motivation of payment, they are externally

motivated (Gagné & Deci, 2005). Many activities people undertake are based in extrinsic

reasons (Bidee, Vantilborgh, Pepermans, Huybrechts, Willems, Jegers, & Hofmans 2013) but of

themselves may still provide significant value in developing accompanying interest, pleasure,

self-expression, or satisfaction. Extrinsic motivation is therefore expected to have a relationship

with measures of EP, particularly financial measures, and this study supports that hypothesis;

thus hypothesis 4 was supported.

Fifth, the satisfaction of the three basic psychological needs (competence, autonomy,

relatedness) was hypothesised to have a positive, indirect relationship with EP, mediated by

autonomous motivation (H5). The three BPNT variables show weak, non-significant

relationships with personal income and career satisfaction, and a significant negative

relationship with firm net profit. This is contrary to the expected relationship. SDT suggests that

people who are autonomously motivated are more likely to find the activity inherently

interesting and enjoyable, are likely to be proactive, seek mastery, and experience greater

levels of performance (Ryan & Deci, 2000a). The lack of support for this hypothesis may be due

to suppression effects (present when the direct and mediated effects of an IV on a DV have

opposite signs) (Tzelgov & Henik, 1991; Cliff & Earleywine, 1994; MacKinnon et al., 2000),

which is the case for the satisfaction of BPN (IV) and firm net profit (DV) in the final BPNT-OIT-

EP relationship. Hypothesis 5 was not supported.

Sixth, the most important finding of this study lies within its assumption challenging approach

in comparing the predictive capacity of OIT variables over IEO variables with regard to EP.

Hypothesis 6a proposed that in the presence of the satisfaction of the BPNT-OIT relationship,


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the relationship between IEO-EP will reduce in magnitude. The study found that for this

sample, the relationship between IEO and EP reduced in magnitude in the presence of the

BPNT-OIT-EP relationship, however, while the reduction in the magnitude of the relationship

was sizeable, it did not reach statistical significance. Hypothesis 6b proposed that the BPNT-OIT

relationship predicts EP more strongly than do individual dispositions (IEO) in

entrepreneurship. In terms of comparative predictive capacity of each relationship, in the

presence of the satisfaction of basic psychological needs in conjunction with autonomous-

controlled motivation, the BPNT-OIT variables were stronger predictors of EP than individual

disposition variables in the entrepreneurship domain. The results support the theory that the

BPNT-OIT-EP relationship is an underlying mechanism by which autonomous and controlled

motivation leads to entrepreneurial performance. The degree to which the three basic

psychological needs for competence, autonomy and relatedness are satisfied, determines the

degree to which autonomous motivation (organismic integration) occurs. In turn, the degree to

which organismic integration occurs predicts entrepreneurial performance. It is likely not a

matter of individual dispositions in entrepreneurship having small to no explanatory power

(findings for the first hypothesis and the summation of meta-analytic studies in the domain

negate this) but that their effects are actioned through other variables such as the motivation

variables identified in this study. In this respect, the study’s results agree with Baum et al.’s

(2004), in which it was suggested that the effects of personality traits operate through specific,

non-trait mechanisms. The operation of these individual dispositions through this specific, non-

trait motivation mechanism and their manifestation in the entrepreneurial context present an

opportunity for further study.


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Theoretical Implications

The following theoretical implications are presented in an order that follows the presentation

of the hypotheses of this study. First, a large volume of research has focussed on the role that

individual dispositions play in shaping entrepreneurial performance (see Stewart & Roth, 2001;

Collins, Hanges, & Locke, 2004; Rauch & Frese, 2007; Rauch et al., 2009; Rosenbusch et al.,

2013). It has been surprising that this literature is characterised by uncertainty about the

presence and strength of individual dispositions in relation to entrepreneurial outcomes,

particularly considering the broad base of anecdotal evidence of the relationship in statements

by entrepreneurs themselves. There must be a reason that some reviews conclude that there is

a positive relationship between personality traits and business success (Stewart & Roth, 2001;

Collins, Hanges, & Locke, 2004; Baum & Locke, 2004; Rauch & Frese, 2007) and others conclude

that there is no such relationship (Davidsson, 1989; Gartner, 1989, 2007; Aldrich, 1999) and

they are not reliable predictors of whether people will behave in a particular way (Ajzen, 1988;

Kenrick & Funder, 1988).

This study contributes to the theoretical understanding of these relationships by applying SDT,

and more specifically BPNT and OIT, to the entrepreneurship context to show that the

contrasting views of individual dispositions in the entrepreneurship domain are likely based on

variation in the level of analysis of these dispositions. Examining these relationships through

the lens of BPNT and OIT reveals an underlying mechanism that explains the manifestation of

individual dispositions in entrepreneurship, based on the degree to which basic psychological

needs in entrepreneurship are satisfied and the correlating degree to which people experience

autonomous and controlled motivation in the entrepreneurship domain. Indeed, while


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individual dispositions may not be reliable predictors of whether people will behave

entrepreneurially in the context of operating their venture (Ajzen, 1988; Kenrick & Funder,

1988), empirically testing for the BPNT-OIT-EP factors in samples of individuals in

entrepreneurship shows that relationships can be more clearly identified according to SDT.

Second, while authors have addressed the influence of autonomous and controlled motivation

in entrepreneurship through the lens of SDT (e.g. Douglas, 2014; Allison, Davis, Short, & Webb,

2015), there have been no studies that have focussed on the nuances of these two SDT sub-

theories. These two sub-theories, BPNT (satisfaction of the needs for competence, autonomy

and relatedness) and OIT (intrinsic, integrated, identified, introjected and extrinsic motivation)

represent a novel contribution to the entrepreneurship literature. The results of the study

showed that the BPNT-OIT measurement model had strong convergent validity in the

entrepreneurship context. The study makes a contribution to the psychology and

entrepreneurship literatures in applying SDT, specifically BPNT and OIT, to a previously

unapplied domain in the entrepreneurship context.

Third, the study adds to knowledge about entrepreneurship with this first empirical study of

the autonomous-controlled motivation continuum of motivation variables, and their

relationship with EP within this domain. The strength of these correlations suggest that they

are predictive of performance in the entrepreneurship domain, and importantly, they are more

predictive of EP than individual dispositions. Rauch and Frese (2007) provide an interesting

benchmark for the relative importance of such correlations, with the relative applicability of

correlations in the medical domain. Correlations for some medical diagnostic relationships are

sufficiently sizeable to make practical conclusions in medicine (for example, conventional x-rays

and tooth cavities (r = .36), or cardiac tests and the prediction of death or myocardial infarction


103

within the first week of vascular surgery (r = .20)) (Meyer et al., 2001). The strength of the

BPNT-OIT-EP correlations identified within this study should therefore be considered large

enough to be of value. Given the limitations of this study the correlations at least provide an

indication of an effect that needs to be further examined.

Additionally, the study adds to the SDT measurement literature. The theoretical three-factor

BPNS model did not adequately fit the data. Previous studies of the BPNS have found that

misfit of the BPNS model is associated with large standardized residuals between Relatedness 7

and Relatedness 16, inappropriate utilisation of Autonomy 14 on the Autonomy subscale,

negatively-worded items failing to represent their respective construct, and low applicability of

items Autonomy 4, 11 and 20 (Johnston & Finney, 2010). Similar to Johnston & Finney’s

findings, the results of this study show low reliabilities associated with the need for

competence (below 0.67) and that large amounts of variance are not accounted for by

substantive factors. This study revealed misfit of the data resulting in a final modified model

that was even more parsimonious in its retention of valid items than Johnston & Finney’s final

supported model (a final ten item, three-factor model with no negative method effect versus a

final sixteen-item, three-factor model with a negative method effect). The final model used in

this study avoids the negatively-worded item-construct failure associated with the original 21-

item BPNS model, incorporates similarly retained items to those of the Johnston & Finney’s

(2010) evaluation, and paints a similar picture of the problematic nature of the original

theoretical three-factor BPNS model.

Lastly, the thesis touches on the entrepreneurship ‘origins’ literature with regard to the

‘entrepreneurs are born not made’ argument. In work on the biology of personality and


104

individual dispositions, Canli (2006) asserts that there is a biological basis for temperament.

Fisher and Koch (2008) follow the assertion with the belief that entrepreneurs are born, not

made. They argue against the idea that anyone can be an entrepreneur. They argue that the

individual dispositions in entrepreneurs are hereditary. McCrae (2004) also argues that the

source of personality traits is “solely biological.” Shane (2010) argues that genes influence

whether a person will start a business and that they may be deterministic of entrepreneurial

performance. In contrast to these views, this thesis provides substantive argument that

hereditary factors aren’t likely to be dominant predictors of entrepreneurship. This study

presents the alternate paradigm of the mechanism of autonomous and controlled motivation

to behave entrepreneurially. This study provides strong convergent validity between the

theoretical grounding of this mechanism and empirical evidence that these motivation states,

and thereby manifested individual dispositions, are not necessarily innate nor permanent; the

most appropriate behaviours with which a person can succeed in the entrepreneurship domain

can be learned; motivation and associated behaviours are adapted and developed. SDT

provides a substantively different point of view to the ‘born not made’ theoretical argument.

The review of the literature provides explanation of how entrepreneurial values and behaviours

are assimilated and internalised, and the organism, the individual, the entrepreneur, is changed

and evolves (however this is not tested in this cross-sectional study).

Practical Implications

These results have practical implications for facilitating venture growth (with the caveat that

further research addressing the limitations experienced in this study would be beneficial). The

autonomous-controlled motivation continuum findings could be relevant to venture capitalists


105

who have to decide which applicants to fund. Venture capitalists and business angels who

participate in high-risk lending are interested in methods of assessing entrepreneurial

motivations, capabilities, tendencies and team capacities; looking for qualities that can be

synergised to potentially improve the probability of higher returns on new venture

investments. Competence is optimally developed through enactive mastery (Bandura, 1997)

that comes from training, experience and involvement in entrepreneurship networks.

Internalisation of external influences within entrepreneurship networks, incubators,

accelerators and co-working spaces, is experienced through relatedness to those

entrepreneurial communities. These qualities are likely to be desired by potential

entrepreneurs and expected by investors. Involvement in entrepreneurial networks can be

intentionally chosen by the potential entrepreneur to build needed skills and develop

autonomous motivation, or it may be mandated by venture capitalists as a condition of

funding.

Another potential implication exists for organisations that are concerned with

entrepreneurship incubating and pedagogy. Identifying trends in the relationship between

motivations and assimilation characteristics could be used to develop pedagogical techniques,

methods of instruction and facilitation that are cognisant of the different motivational

predispositions, thereby enhancing the preparedness of students and aspiring entrepreneurs to

be involved in related groups and events, and pursue entrepreneurial careers. The

understanding of the assimilative quality of autonomous external regulation may encourage

the adoption of an elevated entrepreneurial mindset within the aspiring entrepreneurial

population. Considering that national governments around the world are looking for ways to

encourage Science, Technology, Engineering and Mathematics (STEM) students to


106

entrepreneurship, this may play a part in enabling such students to reduce inhibition and see

opportunity in places, groups and activities (related to entrepreneurship) where it wasn’t

previously perceived. Practitioners may be confident about the findings that motivation

variables are important direct predictors of entrepreneurial performance.

Limitations

The following limitations are grouped according to methodology, measures and sample.

Turning to methodology first, this study is based on cross-sectional correlations; the study was

a static evaluation of a time dynamic phenomenon and therefore alternative explanations

cannot be excluded. Conclusions cannot be drawn regarding causal effects. This is particularly

important considering the variance of competence and motivation factors can change because

of entrepreneurial success. As Davidsson (2009, p. 154) suggests, if the study were related

instead to people’s cumulative success over several entrepreneurial endeavours the result

would be more capable of supporting entrepreneurship theory. Accordingly, reverse causality

cannot be ruled out (for example, failure is unlikely to satisfy the satisfaction of basic

psychological needs in the entrepreneurship context, leading to reduced autonomous

motivation). A longitudinal study would be necessary to empirically determine the direction of

causation and that the findings are not unique to a cross-section in time. A longitudinal diary

study of entrepreneurs as they enter, experience and fulfil time in an entrepreneurial program

or network would more effectively evaluate the internalisation of external influences and the

subsequent differences in entrepreneurial performance.


107

Second, although the study reviewed various literature in search of relevant individual

dispositions for study, other individual dispositions may be important and more contemporarily

studied but not yet as empirically established. For example, passion and tenacity (grit) are

gaining ground in contemporary entrepreneurship research. However, each may arguably be a

manifestation of autonomous motivation. Third, the study used firm profit, individual profit and

career satisfaction to represent entrepreneurial performance; however, there are other

indicators of performance (sales, venture growth, innovation, intangible assets) that should be

studied. Fourth, the data were based on self-reports; it would be ideal to test these self-report

measures for convergent validity with financial reports, though this was not within the capacity

of this study. Fifth, while tests for common method variance were performed and suggests that

CMV is a potential concern for this study, the results do not preclude the possibility of CMV

within the measurement models. The magnitude of zero order correlations varies considerably

however, and while the level of bias may be cause for concern it does not invalidate the

research findings (Doty & Glick, 1998). Sixth, the basis upon which BPNT-OIT-EP versus IEO-EP

comparative strength conclusions are made could be further tested. The comparison could be

extended from the observation of the number, breadth and effect size of significant

relationships to the different (objective and subjective) dimensions of EP, to include statistical

testing such as dominance analysis or semi-partial correlation testing.

Moving to measures, and seventh, the original BPNS model showed significant misfit to the

data due to large standardized residuals between items, negatively-worded items failing to

represent their respective construct, and low applicability of items (Johnston & Finney, 2010).

While the final reduced model used in this study avoids the negatively-worded item-construct


108

failure associated with the original 21-item BPNS general model, it would be ideal to include an

improved measure of the satisfaction of basic psychological needs.

Eighth, sampling issues stem from a broad definition of entrepreneurship being applied by

default in the chosen sample. The sample effectively defined entrepreneurship in this study as

ownership and active management of business ventures (Stewart & Roth, 2001). Although this

definition is commonly accepted by entrepreneurship scholars it does not reflect the growth

oriented nature of entrepreneurship argued for within the literature review. Ninth, sampling

convenience motivated the choice of the Australia-wide SSI Survey sample and cross-sectional

study design. The quality of the sample in terms of growth-oriented entrepreneurs would be

lower than if the sample were drawn from individuals currently involved, or starting to become

involved, in high-impact entrepreneurship. The predominant age group of this sample was 50-

59 years old, their businesses in the majority were 5-15 years old, the predominant profit level

(both firm and individual) was in the AUD 10,001 - 50,000 range and in the majority

respondents were not oriented to business growth. The businesses associated with the sample

are, on average, low performing and low paying; these factors are not indicative of high career

satisfaction or higher entrepreneurial performance. It would be ideal to apply this study to a

distinctly growth-oriented sample of entrepreneurs who are involved in an entrepreneurship

program or network, to make a comparison between the two samples.

Last, having two distinct groups, growth-oriented (whose numbers were very low) and income-

oriented entrepreneurs generalised within the same sample, has implications for statistical bias

(and in the context of this sample, the ability to test for significant differences between the two

groups). With two such groups combined within the study, motivational differences between


109

growth oriented entrepreneurs and income oriented (salary substituting) business owners will

be minimized because of a decreased mean of the observable characteristic/motivation in the

(growth oriented) entrepreneurial group. The statistical differences between growth oriented

entrepreneurs and the self-employed are therefore biased downward. Accordingly, this study

presents future opportunities for improvement in study design, appropriate changes to leading

measures and reconsidered sampling decisions.

Conclusion

This cross-sectional study of the mechanism of autonomous-controlled motivation and the

underlying relationship with entrepreneurial performance challenges the assumption that

individual disposition variables are ideal predictors of entrepreneurial performance. The study

found that the satisfaction of the needs for competence, autonomy and relatedness in the

entrepreneurship domain is positively related to autonomous motivation, and that the

autonomous-controlled motivation continuum predicts entrepreneurial performance (firm

profit, individual profit, career satisfaction) more strongly than individual dispositions in

entrepreneurship (risk, innovativeness, proactivity). The sample associated with this study

reflected much stronger, and positive, controlled motivation than autonomous motivation. The

finding that the autonomous and controlled motivation states matter, opens opportunities for

research exploration centred on the study of motivation types based in OIT, individual

dispositions and mediators. Furthermore, motivation assessment and training may have a role

in the development of entrepreneurs. Entrepreneurship support programs could market the

positive transformative nature of competence building, autonomy enhancing and relatedness

enriching benefits of participation in such entrepreneurial programs and their networks, to

encourage more people to entrepreneurship.

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APPENDIX 1: RESEARCH VARIABLES, DESCRIPTIVE STATISTICS AND CORRELATIONS

137


Table A1.1

Original IEO Survey Item Statements and Code

Code Item Statements

Risk1 I like to take bold action by venturing into the unknown

Risk2 I am willing to invest a lot of time and/or money on something that might yield a high

return

Risk3 I tend to act “boldly” in situations where risk is involved

Innov1 I often like to try new and unusual activities that are not typical but not necessarily

risky

Innov2 In general, I prefer a strong emphasis in projects on unique, one-of-a-kind approaches

rather than revisiting tried and true approaches used before

Innov3 I prefer to try my own unique way when learning new things rather than doing it like

everyone else does

Innov4 I favour experimentation and original approaches to problem solving rather than

using methods others generally use for solving their problems

Proact1 I usually act in anticipation of future problems, needs or changes

Proact2 I tend to plan ahead on projects

Proact3 I prefer to “step-up” and get things going on projects rather than sit and wait for

someone else to do it


138

Table A1.2

Deci & Ryan’s (2000) BPNS Before and After Modification

Code Items Before Modification Autonomy1 I feel like I can make a lot of inputs in deciding how my business is run.

Related2 I really like the people I engage with while running my business.

Competence3(R) I do not feel very competent when I am running the business.

Autonomy4(R) I feel pressured while running my business.

Comptence5 People I work with tell me I am good at what I do.

Related6 I get along with people while running my business.

Related7(R) I pretty much keep to myself while running my business.

Autonomy8 I am free to express my ideas and opinions in running my business.

Related9 I consider the people I work with to be my friends.

Competence10 I have been able to learn interesting new skills while running my business.

Autonomy11(R) While running my own business, I have to do what I am told by others.

Related12 People I work with in running my business care about me.

Competence13 Most days I feel a sense of accomplishment from running my business.

Autonomy14 My feelings are taken into consideration when running my business.

Competence15(R) While running my business I do not get much of a chance to show how capable I am.

Related16(R) In running my business, there are not many people at work that I am close to.

Autonomy17 I feel like I can pretty much be myself while running my business.

Related18(R) The people I work with do not seem to like me much.

Competence19(R) While running my business I often do not feel very capable.

Autonomy20(R) There is not much opportunity for me to decide for myself how to run my business.

Related21 People I engage with in running my business are pretty friendly towards me.

Note: (R) depicts reverse scored item


139

Table A1.3

Gagne and Deci’s (2012) MAWS Scale Items

Code Items

Intrins1 Because I enjoy this work very much

Intrins2 Because I have fun doing my job

Intrins3 For the moments of pleasure that this job brings me

Ident1 I chose this job because it allows me to reach my life goals

Ident2 Because this job fulfills my career plans

Ident3 Because this job fits my personal values

Intro1 Because I have to be the best in my job, I have to be a “winner”

Intro2 Because my work is my life and I don’t want to fail

Intro3 Because my reputation depends on it

Ext1 Because this job affords me a certain standard of living

Ext2 Because it allows me to make a lot of money

Ext3 I do this job for the pay check

Table A1.4

Career Satisfaction (AoM) Greenhaus, Parasuraman & Wormley (1990)

Code Items

CarSat1 I am satisfied with the success I have achieved in my career.

CarSat2 I am satisfied with the progress I have made toward meeting my overall career goals.

CarSat3 I am satisfied with the progress I have made toward meeting my goals for income.

CarSat4 I am satisfied with the progress I have made toward meeting my goals for advancement.

CarSat5 I am satisfied with the progress I have made toward meeting my goals for the development of new skills.

b.a. (university of queensland) a thesis submitted …...needs theory (bpnt), in which the...

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