Determinants of Nascent Social
Entrepreneurship
Ayus Praharaj
366914
August2015
Department of Applied Economics
Erasmus School of Economics, Erasmus University Rotterdam
Supervisor: Dr. Brigitte Hoogendoorn
1
Acknowledgement
I would like to sincerely thank my supervisor, Dr. Brigitte Hoogendoorn, who has been an incessant
source of inspiration for me. It is because of her constructive criticism, detailed feedback, and nuanced
supervision that the quality of this thesishas reached a respectable standard. Her assistance has been
crucial to the completion of this report.
I would also like to extend my gratitude to my family – especially Pradip Kumar Praharaj,
SunitaPraharaj and PrasanjitPraharaj – who remain instrumental in all paths of my life. They are my
backbone and have provided tremendous mental support during the entire course of my Bachelor’s
degree. It is only for their encouragement and support that I will be able to successfully conclude my
undergraduate study with the submission of this thesis.
2
Abstract
This cross-national investigation attempts to explore environmental factors that facilitate
nascent social entrepreneurial activities, from a macro-level perspective. It makes use of
numerous literatures as well as the institutional economics framework to test for both formal
(public spending) and informal (post-materialism, education) variables. Utilizing data from
the Global Entrepreneurship Monitor (GEM) report of 2009, this paper tested multiple
hypotheses with the help of five regression analyses. It was concluded that public spending
had no bearing on the prevalence of nascent social ventures. While education suggested a
noteworthy impact only when assessed for independent effects, post-materialism consistently
illustrated a statistically significant influence on the aforementioned dependent variable.
These results signaled towards the importance of socially constructed norms and selfexpression value systems, rather than legislative regulations established by governmental
institutions. In other words, informal institutions remained an integral element in furthering
nascent social entrepreneurship, while such social start-ups did not seem to extract any
benefits from changes in the formal institutional structure.
Keywords: Social entrepreneurship, nascent social entrepreneurship, Global
Entrepreneurship Monitor (GEM), institutional theory.
3
Table of Contents
1.
Introduction…………………………………………………………………………………………………………………… 5
2.
Literature Review……………….………………………………………………………………………………………….. 9
Definition of Social Entrepreneurship……………………………………………………..………………………………………….9
(Nascent) Social Entrepreneurship and Institutional Theory.…………………………………………………………….. 12
Hypotheses Formulation……………………………………………………..……………………………………………………………. 14
3.
Data and Methodology……………….……………………………………………………………………………….. 18
Sources of Data.……………………………………………………………………………………………………………………………….. 18
Methodology……………………………………………………..…………………………………………………………………………….. 20
4.
Results……….…………………………………………………………………………………………………………………. 23
5.
Discussion…………………………………………………………………………………………………………………….. 28
Contribution of Results……………………………………………………….……………………………………………………………. 28
Limitations…………………………………………………………………………..…………………………………………………………… 30
6.
Conclusion…………………………………………………………………………………………………………………….. 33
7.
Bibliography………………………………………………………………………………………………………………….. 35
8.
Appendices……………………………………………………………………………………………………………………. 40
APPENDIX 1: Description of Variables for Regression Models………………………………………………………………40
APPENDIX 2: Countries and respective Nascent Social Entrepreneurship rates (%)………………………………41
4
Chapter 1
Introduction
As the contemporary world evolves at an ever-increasing pace, entrepreneurial activities have
come to surface and, in effect, taken center stage. For instance, Mark Zuckerberg and Evan
Speigel reformed the social networking arena through their inventions – Facebook and
Snapchat respectively. They optimized commercial expertise to dominate the face of digital
communication in the modern era. On the other hand, One World Health renewed the ideals of
pharmaceutical industry by tying its objectives down with social goals and becoming the first
non-profit pharmaceutical company in the United States. It aims at addressing the need of
developing countries for affordable medications,to treat infectious diseases, which would
otherwise be disregarded due to lack of viable markets (OECD, 2010).
Entrepreneurship, as can be witnessed from the aforementioned examples, is a rather broad
concept, which addresses several aspects of economics. One of its intriguing branches, i.e.
social entrepreneurship, pertains to applying business techniques in an attempt to rectify
societal issues such as poverty and inequality. Social entrepreneurs possess the all-important
trait of engaging in direct actions rather than relying on an external entity to take the initiative
(Martin & Osberg , 2007). Their ability to offer incessant solutions for burning social dilemmas
of the day is esteemed and highly revered (Kerlin, 2009).
As investigations exemplify the influences of social ventures1, there have been numerous
propositions pertaining to increasing the number of social entrepreneurs at global, national and
community levels (Babu & Pinstrup-Andersen, 2007). The popularity of diverse social
enterprises is on the rise, and they have become increasingly integral to the economic as well
as environmental well-being of societies (Mair & Marti, 2006; Zahra et al., 2009). However,
simultaneously, several inquiries have highlighted the notion that despite a considerable
upsurge in awareness, common masses still fail to grasp the concept regarding drivers of
entrepreneurship, especially on a cross-national level.They possess limited understanding of
1
This paper uses “social enterprises” “social ventures” and “social entrepreneurship” interchangeably.
5
social entrepreneurial activities due to a deficiency of empirical studies (Mair & Marti, 2006;
Short et al. 2009; Estrin et al., 2013; Stephan, Uhlaner & Stride, 2014).
Hence, the lack of cognizance vis-à-vis factors that could potentially impact the prevalence of
social enterprises alludes to a need for research onits determinants. Inspections have recently
been conducted regarding drivers of social entrepreneurship, using diverse theories, to analyze
the influence of pertinent variables (Hartog & Hoogendoorn, 2011; Stephan, Uhlaner & Stride,
2014). As a result, the aim of this study would be to enhance our knowledge relating to
prevalence and drivers of a unique feature of social entrepreneurship, from a macro scale
(country level). In other words, the attention of this investigation is channeled towards nascent
social entrepreneurial activities2 solely, since there are little or no empirical research
conducted on prevalence of such infant start-ups specifically.Recent probes have already
indicated the possibility of environmental circumstances altering rates of nascent social
enterprises (Ruvio & Shoham, 2011). Furthermore, additional research have also illustrated the
need to vet nascent social entrepreneurship in order to improve our understanding about
determinants for its prevalence, as academicians speculate that there could be considerable
variations in patterns and reasons behind ‘organizational emergence’ (Åmo, 2014; Brush et al.,
2008; Sarasvathy, 2001).
Articles and journals are consumed for the purpose of drawing intuitions about the
discrepancies that exist in terms of the frequency of social entrepreneurship. They are then
extended to the sub-branch of nascent social entrepreneurship rates. The theory of institutional
economics is leveraged to dissect probable factors that could impact the incidence of such
social entrepreneurial activities. Douglas C. North (1990) is the primary contributor of
institutional framework, which opines that institutionalism consists of restraints that shape
human behavior. Germak and Robinson (2014) have already delved into the intrinsic factors
that are of significance in determining key motivating elements, whichpropel individuals into
getting involved in social entrepreneurship. So, it would be interesting to observe whether
extrinsic (environmental) factors play a decisive role in the occurrence of social enterprises as
well. Moreover, fresh inspections point to institutional approach as the suitable framework for
analyzing effects of environmental factors on the creation and frequency of new social startups (Nicholls, 2010; Urbano et al., 2010). Therefore, overall attention will chiefly be given to
2
Nascent Entrepreneurs are individuals, who claim to have undertaken tangible steps in the past 12 months towards creating a social
enterprise, which they would personally own all or part of. The social enterprise has not provided services, nor paid salaries for more than
three months
6
environmental factors, which, in the context of this paper, encompass economic, social,
political and cultural themes that affect the emergence and prevalence of novel social ventures
(Neck et al. 2009; Townsend 2008). There will be formal and informal institutional factors
involved, which will cover different aspects of individuals’ environments and in turn, provide
us with insights regarding fundamentals that are key to expediting the advent of fresh social
entrepreneurial activities.
Hence, this gives rise to the following research question:
To what extent do environmental factors impact the prevalence of nascent social
entrepreneurship?
The methodology used in this paper relates to multiple regression analyses.Five distinct
models are constructed with the intention of not only examining the effect of formal and
informal institutional factors as a combination, but also shedding light on their independent
impacts (i.e. analysis of formal and informal factors separately) on the rates of nascent social
entrepreneurial activities.Data regarding nascent social enterprises is extracted from the 2009
Global Entrepreneurship Monitor (GEM) report. GEM possesses national teams, which devote
themselves to conducting surveys and acquiring insights about various environmental factors
that might lead to changes in entrepreneurial activities (Terjesen, Lepoutre, Justo, & Bosma,
2012). Their fundamental parameter, as discoursed later in the study, is Total early-stage
Entrepreneurial Activity. However, the scrutiny in this paper centers on one of its branches,
nascent social entrepreneurial activity. The reasoning for selection of certain key
environmental factors stems from the institutional economics approach, as could be observed
from narratives provided in multiple segments of Chapter 2. Figures for independent variables
are exemplified using multiple databases, namely (i) World Bank, (ii) UNESCO, (iii) World
Value Survey, (iv) European Values Study, and (v) International Monetary Fund. In the course
of writing this paper, not only are the determinants of social entrepreneurship addressed, but
also information can be mined by legislators for enhancing the policy designing process.
The outcome for formal institutionsis largely the antithesis of our expectations since public
spending did not have any control over the varying rates of nascent social entrepreneurship.
The informal institutional variable of education possessed a substantial bearing on the
occurrence of nascent social ventures, only when tested for independent effects. It failed to
establish an impact of similar importance when assessed jointly with the other variables. The
second informal factor of post-materialism seemed to possess statistically significant
7
relationship with the prevalence of nascent social entrepreneurial activities overall, therefore,
suggesting that societies where individuals share very close bonds would experience higher
rates of nascent social entrepreneurship.
This introduction is followed by the section of Literature Review, where relevant
articles are discussed. Post discourses of appropriate texts, hypotheses are framed accordingly.
The data mining procedure and research methodologies are elucidated in the section following
Literature Review. Then, the outcomes of regression analyses are described and thoroughly
discussed in the subsequent segments. The research work is then concluded by summarizing
results and their implications, as well as discussing potential limitations and providing
foundations for future research on the theme of (nascent) social entrepreneurship.
8
Chapter 2
Literature Review
Definition of Social Entrepreneurship
Definition of nascent social entrepreneurial activities stems from the interpretation of social
entrepreneurship. However, there are categorical disagreements and disparities regarding the
notion of social entrepreneurship, since researchers believe it could possess multiple
manifestations (Mair & Marti, 2006; Short et al. 2009; Zahra et al. 2009). The concept was
initially brought into the limelight by Bill Drayton, founder of Ashoka: Innovators for the
Public, in the 1980s and 1990s. Charles Leadbeater in his publication, The Rise of the Social
Entrepreneur, also delved into the dynamics of the terminology, upon which, the use of social
entrepreneurship became increasingly common in academic research (Leadbeater, 1997;
Williams et al., 2005). Even in the contemporary era, there have been a multitude of
investigations with the objective of constructing an apt explanation of the term. Present-day
social entrepreneurship encompasses public and private, non-profit and profit activities
(Urbano et al., 2010; Zahra et al., 2009), which aim at providing relief to depressed
communities from a variety of social issues, including health care and education. It has further
been debated that irrespective of whether social entrepreneurial organizations implement nonprofit or for-profit legal forms, they entail a hierarchical arrangement of objectives, whereby
social value takes precedence over accretion of monetary resources (Dacin et al. 2010). For
instance, Bangladesh Rural Advancement Committee (BRAC) and Aravind Eye Hospital have
been imperative to providing support for numerous social issues in developing countries (Daru
& Gaur, 2013). BRAC channels its focus towards providing services such as rural capacity
building, education, health services and micro-credit to the deprived sections in Bangladesh.
Aravind Eye Hospital, on the other hand, countenances price discrimination on eye operations,
in accordance with the patient’s ability to pay, in a host of countries across Asia, Africa and
South America. Hence, the classification of social entrepreneurship varies with drivers and
social circumstances of concern.
9
The abovementioned investigation, conducted by Daru and Gaur (2013), is chiefly macro-level
as they inspect the efficacy of social entrepreneurship on a cross-national level. When
conducting analysis from an international comparative perspective, social entrepreneurship has
to cover regional as well as local differences in terms of what it signifies and the fashion in
which it is utilized to resolve social conundrums, in order to maintain cohesion during scrutiny.
Since this study is also cross-national and targets to provide quantitative outcomes, the
definition of social entrepreneurship utilized in the context of this paper will be rather
generalized. Sartori (1970),in the study conducted by Hartog and Hoogendoorn (2011),
claimed that to extend the universal applicability of a concept, we must compromise on its
specificity. Therefore, the definition that will be used throughout the course of this research is:
social entrepreneurship entails individuals or organizations engaged in entrepreneurial
activities with the aim of attaining social goals (Bosma & Levie, 2010; Mair & Marti, 2006).
Individuals and organizations are stated separately in the aforementioned definition in order to
emphasize the view that activities of individuals need not necessarily be from within an
organizational context. Also, all features of the definition, namely individuals, organizations
and entrepreneurial activities, will be used in their most general forms for the purpose of
incorporating all possibilities. As stated previously, entities with both social and commercial
motives can still be classified as social enterprises, as long as they accomplish tasks of societal
relevance. Peredo and McLean (2006), for example, delineated the hybridity of social
entrepreneurial organizations, adducing ventures that consist of both for-profit and non-profit
constituents. This was echoed by Neck et al. (2009), as he opined the notion that individuals
with amalgamations of for-profit and non-profit motives can yet be considered social
entrepreneurs, as long as their actions generate social value. Thus, employing all operational
terms in their broadest senses will bring about consistency in the process.
However, while there remain discrepancies pertaining to its definition, there has been a robust
uniformity observed amongst researchers in terms of the emergence and usefulness of social
ventures, both nascent as well as mature. The last few decades witnessed an advent of social
entrepreneurship, primarily expedited by countless boiling discourses regarding societal
responsibility of businesses (Drayton, 2002; Leadbeater, 1997). Intermittent phases of
pecuniary meltdowns have exposed the limitations of public sector as a conventional welfare
mechanism, and has fuelled an escalating demand for fresh private divisions (social
entrepreneurs) to take charge of burning social dilemmas (Alvord et al., 2004; Sharir & Lerner,
2006; Yunus & Weber, 2008). Furthermore, policy makers and governmental institutions in
10
developing countries have also taken an interest towards endorsing social enterprises. This has
been triggered by an influx of new non-for-profit organizations and entrepreneurs, which
continue to play integral roles in fighting poverty alleviation as well as other numerous societal
concerns (Smith & Barr, 2007; OECD, 2010). The earlier illustrations of BRAC and Aravind
Eye Hospital astutely support the aforesaid claim. Mohammad Yunus, who orchestrated the
groundbreaking creation of Grameen Bank in Bangladesh, also initiated the micro-financing
movement, and works towards providing loans to entrepreneurs that are rather deprived of
resources. Likewise, social entrepreneurship has also enjoyed success in the developed nations,
aiding the destitute communities and older generation with solutions to issues such as hunger,
education, paucity of resources and environmental degradation (Babu & Pinstrup-Andersen,
2007).
The overarching theme observed above is the role of diverse enterprisesin attempting to meet
the unaddressed needs of masses, which could not be fulfilled by public and other private sector
institutions. As notified in the introduction, this study would also exploit institutional economic
theory as the framework. Institutional economics, initially coined by Walton H. Hamilton in
1919, pertains to the broader review about the role of institutions in shaping economic behavior
(Hamilton, 1987). The concept of institutions is essentially cultivated into a set of authoritative
rules, guidelines and constraints utilized for guiding the decision-making behavior in society
(North, 2005; Scott, 2001). In other words, it argues regarding the role of environment in
modeling how individuals and groups behave. A recent inspection shrewdly showcased the
influence of institutional factors on the new dawn of activities with social goals (Urbano et al.,
2010). Zahra et al. (2008) professed similar thoughts, typically advocating the conviction that
institutions and social enterprises do possess links between them. Thus, expanding on this topic
with a refined focus on the impact of environmental factors on nascent social entrepreneurship
and corresponding quantitative upshots within an institutional framework, could contribute to
existing literature. Moreover, it could also assist in designing policies under different
environments, as policymakers would have deeper knowledge about the effect of institutions
on the creation of social enterprises. The following section would explore the nexus between
institutional theory, environmental factors and social entrepreneurship further.
(Nascent) Social Entrepreneurshipand Institutional Theory
11
As witnessed from multiple research, social enterprises are widely viewed as discernible
alternatives to governmental and other institutions, to address problems that still persist despite
public sector welfare programs (Seelos & Mair, 2005; Yunus & Weber, 2008). As a result,
institutional environment is the watershed that social entrepreneurs should leverage in order to
invoke a desirable modification in the development of their society. Nyssens (2006) also
alluded to the relevance of strongly patterned institutional forms that can advance the process
of social entrepreneurial activities. In fact, ample inspections have been conducted to
substantiate the influence of institutional environment over social entrepreneurship activity
rates (Mair & Marti, 2009).
Douglas C. North (1990, 2005), in his two studies, espoused approaches that can aid in utilizing
institutional theory for the analysis of environmental factors as the catalyst behind the
prevalence of social entrepreneurial activities. He was a staunch adherent of the belief that
entrepreneurs adjust their actions and strategies to act on opportunities via the framework of
institutions. This, in turn, demonstrates the hold of institutional environments over (social)
entrepreneurial activity rates. The view was further extended to vouch for the significance of
relationships between social entrepreneurs and their environment by Townsend (2008).
North (1990) demarcated two separate branches of institutions, namely: formal and informal.
Formal institutions comprise of laws, governmental regulations and constitutional procedures,
which are directed at constructing restrictions as well as incentives for individual and
organizational actions (Bruton et al. 2010). Informal institutions on the other hand, express the
belief and value systems of individuals and organizations. They are rather implicit, culturally
inherited and socially constructed institutions. Comparative entrepreneurship analysis, with an
institutional economics framework, have primarily been conducted on formal institutions
(Estrin et al., 2013), although institutional theorists have advocated for joint effects of both
formal and informal branches (Carney et al. 2009). There is a lack of empirical evidence with
reference to investigation about informal factors (Stephan & Uhlaner, 2010), as most
explorations with respect to informal institutions have primarily been case studies, addressing
diverse social needs (Dana et al., 2006; Harris, 2009). Moreover, in general, there are only a
handful of quantitative enquiries designed towards inculcating institutional theory approach to
examine drivers of social entrepreneurship (Urbano et al. 2010), with very little or no
examinations on determinants of nascent social entrepreneurial activities solely. Thus, to
answer the calls for advancement of research concerning social entrepreneurship with
12
quantitative methodologies (Dacin et al. 2011, Short et al. 2009), this study targets to build on
existing examinations in order to accelerate the process of finding empirical results.
Estrin, Mickiewich and Stephan (2013) for example, provided a quantitative assessment of
social and commercial entrepreneurship by drawing upon formal institutional as well as social
capital theories. By employing framework of institutions in their scrutiny, the likelihood of
individuals partaking in social and commercial entrepreneurial activities was observed to be
positively influenced by constraints on the arbitrary power of the governments in respective
countries. The aforesaid institutional approach also depicted the negative influence of the
independent variable, nation-level government activism, on both individual social and
commercial entrepreneurship. Similarly, Stephan, Uhlaner and Stride (2014) vetted the bearing
that formal and informal institutional factors had on the emergence of social entrepreneurship.
Their method of inspection was in line with the ideals of institutional theorists as focus was
centered on the joint effects of formal regulatory, informal cognitive and normative institutions.
While examining the individual factors, it was observed that both national-level government
activism and post-materialism had strongly positive effects on social entrepreneurship. The
third variable, socially supportive cultures (SSC), also had a positive impact, though its
relationship with social entrepreneurship was found to be rather less robust. The general picture
conveyed in the course of the scrutiny was largely in favor of the belief that both informal and
formal institutions did play key roles in the expediting social entrepreneurial activities. With
the help of findings extracted from these studies, evidence has been procured to discourse the
view that both formal and informal institutions could be pivotal environmental ingredients for
comprehending key driving forces of social enterprises.
As compared to the aforementioned precedents, this paper possesses certain parallels and
dissimilarities. Institutional economics remains the framework, leveraging the contribution of
Douglas North, which was adduced earlier to argue for its relevance in relation to the control
of environmental factors on the prevalence of social entrepreneurship. However, this
investigation pertains to nascent social entrepreneurship activities only. Not only is there a
lack of examination concerning the impact of environmental factors on nascent social
enterprises, but it is also believed that the freshness of start-up activities ostensibly discusses
key features of entrepreneurship (Zahra & Wright, 2011). Furthermore, research conducted on
such embryonic ventures in Israel delineated a strong correlation between environmental
factors and an entrepreneur’s motivation, strategy and success (Ruvio & Shoham, 2011).
Therefore, this paper would attempt to extend the existing convictions by probing the influence
13
of diverse environmental factors on nascent social entrepreneurship, within an institutional
framework. Because the scrutiny only concerns nascent social entrepreneurial activities, the
individuals and organizations ought to be in their infancy, and in accord with its earlier stated
interpretation.
While the dependent variable is different, the environmental factors utilized in this research
would be fairly similar to the ones exploited in the paper of Stephan, Uhlaner and Stride (2014).
This investigation, as based on the dynamics of institutional economics solely, will refer to
both formal and informal institutions. Public spending, which is closely related to government
activism, will represent formal institutions. For informal institutions, post-materialism will be
employed in this study as well, in conjunction with education. The following section will
provide insights into these environmental factors by exemplifying the rationale behind
selecting them, and concluding with multiple hypotheses.
Hypotheses Formulation
As stated previously, in the next paragraphs, four hypotheses will be proposed on the basis of
the theoretical perspective of institutional economics. The objective is to review the prevalence
of nascent social enterprises as comprehensively as possible, since it is well understood that
the creation of such ventures entails a complex mechanism. For that purpose, we aim to
illustrate the function of variables in combinations as well as their independent effects in the
section of Results.
There have been instances when governments systematically retreated from the provision of
public goods, resulting in undesirable market imperfections (Leadbeater, 1997; Nissan,
Castaño & Carrasco, 2012; Salamon, Sokolowski & List, 2003). In those cases, the stock of
resources available pertaining to public goods either remains static or dwindles steadily (Sharir
and Lerner, 2006). Therefore, in order to satiate unfulfilled demands, there is a rise in the
emergence of novel non-profit and social organizations, since a lack of government action fuels
more demand for social entrepreneurship (Dacin et al., 2010; Mair & Marti, 2009; Zahra et al.,
2009). This phenomenon described above is also known as the institutional void theory. The
theory, which is an element of the institutional economics framework, suggests that any
deficiencies in the endowment of public goods by formal institutions (i.e. governments, in this
context), leads to higher rates of social start-ups (Baker et al., 2005). In other words, prevalence
14
of budding (nascent) social entrepreneurial activities will be fairly significant in countries
where provisions of social and public services are inadequate (Cornwall, 1998).
Mair, Battilana and Cardenas (2012), while scrutinizing various social enterprise profiles, also
observed how a socially engaged government led to lower collective demand for social
entrepreneurship. Lower social issues,as a result of efficient formal institutions, would reduce
the onus that social ventures carry to meet public calls and consequently, diminish the impetus
of masses to take part in activities with social goals. Estrin et al. (2013) gathered similar
evidence to conclude for a negative correlation between government activism and social
entrepreneurial start-ups. Thus, extending the inquiry to a macro-level analysis on multiple
countries, with a channeled focus towards nascent social entrepreneurship, the formulated
hypothesis is:
H1: Public spending has a negative impact on the prevalence of nascent social
entrepreneurial activities.
Another variable that can be knotted with the emergence of new and nascent social
entrepreneurship is education. Ties between education and social work can be traced back to
over a hundred years with schools professing the need to indoctrinate educational principles,
which entailed tasks with social motives, in students (Cooke et al., 1912). The article suggested
that social motives, being the controlling principle in social organizations, carry considerable
weight in the lives of pupils.Contemporary studies have also illustrated positive effects of
socially constructed institutions (informal) such as higher level of education on the likelihood
of opening up a start-up firm (Arenius & Minniti 2005; Davidsson & Honig 2003).Åmo (2014),
in an inspection concerning nascent social entrepreneurs amongst the Norwegian population,
observed a predilection of better educated individuals to indulge in such activities.The
aforementioned studies, though provide robust claims for education, are representative of only
micro-level inquiries.
From a macro-level perspective, skills and expertise gained via education can also be leveraged
to guide human behavior towards activities that have potential to eradicate social ordeals and
optimize utility. An article published by the British Council further argues that expertise
imbibed from higher education can play a catalytic role in espousing social enterprises and
sustaining the incessant process of innovation across countries (British Council, 2014). For that
reason, the background of social entrepreneurs is imperative to the incidence and success of
15
fresh social entrepreneurial activities. People might be keener to launch social start-ups if they
possess adequate knowledge to sustain their business (Arenius & Minniti 2005; Chen et al.,
1998). Koellinger et al. (2007) also observed similar outcomes in his macro level crosssectional study across 18 nations, as nascent entrepreneurs were primarily educated and
displayed animmensesense of optimism regarding their capabilities. In the instances depicted
above, the culture of attaining higher education shaped behavior of individuals and countries
collectively. Hence, extending the idea onto nascent social entrepreneurial arena, the
corresponding hypothesis is:
H2: Education has a positive impact on the prevalence of nascent social
entrepreneurial activities.
Post-materialism is another pivotal institutional variable in determining the development of
nascent social enterprises. Inglehart (2008) postulated that post-materialism is essentially the
transformation of individual values, which involves swapping materialistic ideals for a belief
system that is post-materialistic in nature i.e. emphasizes self-expression and quality of life.
They reflect the culturally inherited foundations of countries, which in turn, constitute the
aggregate of all goals that any country’s citizens consider to be of great importance (Schwartz,
2006). In accordance with the concept, if a sizeable portion of the population in a country holds
values that are in line with the establishment of social start-ups, then there will be higher
probabilities of individuals being motivated to partake in new activities and enterprises with
social goals.
Prior reviews on a nation-level perspectivehave hinted towards the view that higher degrees of
post-materialism in a country also lead to greater probabilities that its citizens would engage in
activities such as social entrepreneurship (Hartog & Hoogendoorn, 2011). Interestingly though,
Uhlaner and Thurik (2007) established a negative relationship between post-materialism and
social entrepreneurship. Post dissecting TEA into its branches, a similar association was also
found for post-materialism and nascent social entrepreneurship. However, as suggested by
Baumol’s argument (1990) in Hartog and Hoogendoorn (2011), due to modifications in the
informal institutions of society (i.e. cultural norms, in this context), post-materialistic societies
would drive up novel social entrepreneurial activities. All in all, if countries possess postmaterialistic values, then there would be a higher chance of increase in social start-up ventures.
16
Thus, as with the other hypotheses, prolonging thisview further to nascent social enterprises,
the formulated hypothesis is:
H3: Post-materialism has a positive impact on the prevalence of nascent social
entrepreneurial activities.
17
Chapter 3
Data and Methodology
This section not only introduces the variables explicitly, but also aims at providing narratives
about the types of data obtained and their respective sources. In addition, a clear and succinct
methodology is defined, which is then leveraged in order to test the respective hypotheses.
Source(s) of Data
Dependent Variable
With the aim of acquiring data regarding prevalence of nascent social entrepreneurship, this
study makes use of theGlobal Entrepreneurship Monitor (GEM) report,published in the year of
20093. The GEM report bids to provide insights on the topic of national-level social
entrepreneurial activities via conducting surveys across countries. The primary objectives of
GEM research, with reference to entrepreneurship, focus around establishing cross-country
trends of entrepreneurial activity, along with decoding determinants and policies that could
assist in inspiring similar undertakings. The GEM report of 2009 added an extra dimension to
its coverage since, taking into account the escalating attention of policy makers and
academicians in social entrepreneurship, it constructed a new set of questions channeled
towards socially motivated activities across countries. Thus, in the course of conducting
surveys across 49 different countries4, the GEM group acquired and compiled data about the
percentage of individuals within the age bracket of 18-64 years, who are either in the process
3
GEM is an international research program, which began in 1999 as a joint inspection project between Babson College in
the US and London Business School in the UK. Today, GEM provides data on the level of entrepreneurial activity with
samples of at least 2,000 adults per country and across a total of 54 countries (GEM Report of 2009).
4
The 49 countries are as follows: Algeria, Argentina, Belgium, Bosnia and Herzegovina, Brazil, Chile, China, Colombia,
Croatia, Dominican Republic, Ecuador, Finland, France, Germany, Greece, Guatemala, Hong Kong, Hungary, Iceland, Iran,
Israel, Italy, Jamaica, Jordan, Korea, Latvia, Lebanon, Malaysia, Morocco, Netherlands, Norway, Panama, Peru, Romania,
Russia, Saudi Arabia, Serbia, Slovenia, South Africa, Spain, Switzerland, Syria, Uganda, the United Kingdom, United Arab
Emirates, the United States, Uruguay, Venezuela, the West Bank and Gaza Strip.
Data for Denmark are omitted from analysis as they employed a dissimilar data collection medium. Data for Tonga and
Yemen were excluded on the grounds that their figures were too exceptional for social entrepreneurship. They are,
subsequently, classified as outliers.
18
of or are expected to own (partly/wholly) own a young social enterprises. The GEM reports
utilize Total early-stage Entrepreneurial Activity (TEA) as their principle measure of
entrepreneurship. TEA is essentially the amalgamation of nascent entrepreneurs and owners of
young firms within the surveyed sample i.e. individuals between 18 and 64 years of age. In the
GEM report of 2009, they make use of an additional measure of Social early-stage
entrepreneurship (SEA), which is the aggregate total of nascent and young business
entrepreneurship up to 3.5 years. In that sense, the parameter of SEA is analogous to the general
GEM measure of TEA. For this paper, however, the sub-branch of nascent entrepreneurs will
be the sole focal point for analysis, due to reasons suggested formerly in this paper. Follow-up
questions in their surveys are structured in a manner such that the acquired answers could
determine as to whether individuals can be categorized as nascent or young social entrepreneurs
(Lepoutre et al. 2013). Therefore, there are clearly demarcated figures available for the
different phases of social entrepreneurships, one of which is nascent social entrepreneurship.
Henceforth, Nascent Social Entrepreneurial Activity (expressed in percentages) from the Adult
Population Survey (APS) of GEM report (2009) is used as our dependent variable (Appendix
2). The statistics are available on Table 6 of the GEM report, where social entrepreneurial
activity is divided in terms of phase and gender.
Independent Variables
Multiple sources were opted for, so as to acquire information about the variables to be used in
this inspection.
Public Spending: Reports published on World Bank were exploited to extract data for
the variable of public spending. It is a renowned source for collecting information regarding
the public sector and thus, the variable of public spending is defined in terms of its
interpretation provided by World Bank (Appendix 1). Data provided by the institution is
generally presented as a percentage of the Gross Domestic Product (GDP) of countries, which
would aid in assessing whether larger public or governmental denomination lead to dwindling
social start-ups.
Education: One of the specialized agencies of United Nations, UNESCO, was utilized
for obtaining data on the variable of education. Furthering its intention of endorsing
international collaboration through education, science and culture, UNESCO possesses a
comprehensive database on themes relating to the scholastic aspect of countries. Taking
19
account of the percentage of students enrolled from primary to tertiary education seems to be
an effective indicator of education, as it elucidates the degree to which students make it to
advanced studies. This could, as a result, help in examining whether education levels play a
role in furthering the occurrence of nascent social enterprises. In case of missing data for
specific countries, figures representative of year 2007 were utilized. For the purpose of this
study, they were assumed to be accurate estimates for the succeeding year.
Post-materialism: Data for the variable of post-materialism was attained using a 4-item
index, established by Inglehart (1997). There are two versions of the post-materialism index,
namely 4-item and 12-item indices, for which, data are available in the World Value Survey
(WVS). World Value Survey is a global research project, which aims at scrutinizing the
evolution of value and belief systems of people over time. The 4-item index is widely employed
in investigations (Moors, 2007), as it incorporates noticeably more countries as compared to
its 12-item counterpart and hence, will also be used in the analysis of this study. Data for postmaterialism is obtained primarily from the fifth wave in WVS (year 2005-2009), and also the
fourth wave (year 1999-2004), in case figures for countries are not available in the former
version. In addition, European Values Study (EVS) was then utilized to acquire figures for a
fraction of the remaining countries, for which data could not be obtained from WVS. Numbers
in the analyses would refer to the percentage of individuals in each country that were classified
as post-materialists.
GDPper capita (control variable): A potential crucial element in explaining levels of
entrepreneurial activities is the per capita income (Carree et al., 2007; Wennekers, 2005).
Bosma and Levie (2010) for example, also discoursed about the ability of individuals in richer
countries toserve social needs more effectively, since they are self-sufficient to begin with.
Furthermore, Wennekers et al. (2005) also highlighted the variable as a predictor for nascent
entrepreneurial activity rates. So, in that light, GDP per capita is included in the models as a
control variable with the aim of accounting for potential confounding effects. Data regarding
GDP per capita (in US dollars) will be acquired from the International Monetary Fund (IMF),
where it is adjusted for purchasing power parity as well (PPP).
Methodology
In order to test the hypotheses, multiple linear regression analyses (Ordinary Least Squared –
OLS) are adopted. A host of models are exploited to understand and detect the impact of
20
environmental factors on the prevalence of nascent social entrepreneurship. As stated earlier,
GDP per capita (in PPP) is used as a control variable since former enquiries have consistently
certified the existence of fundamental relationships between the degree of economic
development and a country’s corresponding level of entrepreneurial activity (Reynolds et al.,
2005; Wennekers, Van Stel, Carree & Thurik, 2010). It will be used as the sole variable in our
first model (Model I) in order to determine whether the effect holds true for nascent social
enterprises as well:
nseai= α + β1*gdpi + ut
Where:
nseai– Nascent social entrepreneurship
gdpi– GDP per capita
However, if the regression analysis fails to establish a significant relationship between the
variables in Model I, the control variable of GDP per capita will be removed from the
succeeding models, as the insignificance will deem it inappropriate for the role of a control
variable. The subsequent regressions will be as follows (the variable of GDP per capita is
written in bold to demonstrate that its presence in the succeeding models is dependent on the
findings of Model I):
Model II: nseai = α + β1*pubi + β2* gdpi + ut
Model III: nseai = α + β1* edui + β2* gdpi+ ut
Model IV: nseai = α + β1 * pmti + β2* gdpi+ ut
Where:
nseai– Nascent social entrepreneurship
pubi– Public spending
edui– Education
pmti– Post-materialism
gdpi– GDP per capita
21
Lastly, Model V would include all the variables to inspect the effects of concerned
environmental factors as a combination. General specification of the all-inclusive model used
in this research will be:
nseai= α + β1*pubi + β2*edui + β3*pmti+ β4*gdpi + ut
The model is representative of the regression analysis that comprises of both informal
(education and post-materialism)and formal (public spending) institutional features as
independent variables. This would test for three hypotheses at once, since it is a multivariate
regression and encompasses all germane variables.
As the software tool of STATA is utilized, regressions will be carried out with the use of robust
standard errors. In the course of doing so, estimates of regression coefficients remain the same
as in the routine OLS regression; however, standard error estimates would instead be more
robust to the prospect of failing to meet assumptions of normality and homoscedasticity of
errors.
22
Chapter 4
Results
Prior to running the regressions, a correlation matrix was constructed to check whether there
exist multicollinearity problems between the independent variables. Academicians have argued
that cross-sectional inspections tend to aggrandize the detrimental features of multicollinearity
(Mason & Perreault, 1991). Nonetheless, presence of significant correlations between
independent variables could make the regression findings troublesome to interpret. Results of
the matrix are delineated in Table 1, along with the mean value of nascent social
entrepreneurship, which is 1.12%. This alludes to the notion that for every 100 individuals
across the 49 nations considered in our inquiry; at least one would be a potential nascent
entrepreneur. However, there were considerable variations observed in the sample, since
figures for nascent social enterprises ranged from 0.1% in Saudi Arabia to 3.4% in Venezuela
and Peru. This discrepancy, as mentioned earlier, can be attributed to different institutional
structures and environmental circumstances that might prevail in those countries.
There exist correlation coefficients of magnitude over 0.5 between certain independent
variables, which might signal towards the possibility of existence of multicollinearity. For
instance, the control variable of GDP per capita has considerably high correlations with postmaterialism and education (0.6150 and 0.6503 respectively), both statistically significant at the
1% significance level. Surprisingly, relationship between GDP per capita and public spending
was not as strong in terms of magnitude (0.3082). So, governmental expenditure has no
connection with the monetary strength of the country. As for the other additional observations
in the correlation matrix; their correlations are rather weak. Education and post-materialism
possess a correlation which is fairly fragile at 0.4115. Similarly, the correlation between public
spending and education is not adequately strong (0.4158). Therefore, supplementary spending
by governments could impact the behavior of future students and lead to higher enrolments in
primary to tertiary education, although the influence will be weak. The final feature witnessed
is the insignificant and feeble association between public spending and post-materialism. The
23
implication of the aforesaid statement is that post-materialistic cultural norms have no bearing
on government spending and vice-versa.
NSEA
Post-materialism
Education
Public spending
GDP per capita
mean NSEA: 1.12
Table 1: Correlation Matrix
NSEA
1
0.4244*
0.2906
0.0591
0.1272
Post-materialism
Education
Public spending
GDP per capita
1
0.4115**
0.0160
0.6150*
1
0.4158**
0.6503*
1
0.3082
1
* Significant at 1% level
** Significant at 5% level.
There are multiple remedies available for correcting multicollinearity (Brooks, 2008). One of
the mediums is to leave the model as it is, since OLS would still be considered the Best Linear
Unbiased Estimator (BLUE). Multicollinearity generally arises due to issues with variables
rather than data sets and methodologies. Therefore, the model would still be appropriate for
use. However, biased standard errors, as a consequence of multicollinearity, would make it
troublesome to correctly interpret conclusions. Brooks (2008) thus, suggests another solution
to correct for the problem, which necessitates excluding the variable responsible for
multicollinearity from the model(s), GDP per capita, in this context. Yet this is not as
straightforward, since one has to account for potential bias when eliminating a variable from
any model. This in turn, can be checked for using Model I, as an insignificant relation between
GDP per capita and the dependent variable of nascent social entrepreneurial activity would
lead to the removal of the former variable, curing for any probable multicollinearity
conundrums in the process. In the case of a significant link between the aforesaid two variables
in Model I, appropriate measures will then be taken to address multicollinearity.
From Table 2 below, it can be observed that GDP per capita does not form a significant link
with nascent social entrepreneurship. The implication signals towards the ineffectiveness of
the independent variable as control variable in this study. There remains a possibility that in
conjunction with multiple variables, GDP per capita could strike a significant relationship with
the outcome variable; however, multicollinearity might play a role in their correlation. In view
of that, the control variable of GDP per capita can be dropped from the subsequent models,
thus, also correcting for multicollinearity in the process.
24
Table 2: Explaining prevalence of nascent social entrepreneurship using relevant independent variables (standard errors specified in parenthesis); Dependent Variable:
prevalence of nascent social entrepreneurship.
Model Ia
(0.183)
1.035*
Content
Intercept
Model IIb
0.923
(0.464)
0.005
(0.013)
Model IIIc
-0.689
Model IVd
(0.747)
0.484
Model Ve
(0.203)
0.027
(0.774)
-0.008
(0.016)
0.049**
(0.021)
0.009
(0.011)
Formal Factors
Public Spending
Informal Factors
0.060*
Post-materialism
0.022**
Education
(0.019)
(0.009)
Control Variable
GDP per capita
4.86E-06
(5.80E-06)
Obs. (N)
48
41
38
40
30
Rsquared
0.0162
0.0035
0.0844
0.1801
0.2346
* Significant at 1% level
**Significant at 5% level
a
Country excluded from analysis due to missing data: West Bank and Gaza
b
Countries excluded from analysis due to missing data: United Arab Emirates, Argentina, China, Ecuador, Panama, Saudi Arabia, Syria, Venezuela
c
Countries excluded from analysis due to missing data: United Arab Emirates, Bosnia and Herzegovina, Brazil, Germany, Dominican Republic, Ecuador, Jamaica, Malaysia, Peru, West Bank and Gaza, South
Africa
d
Countries excluded from analysis due to missing data: United Arab Emirates, Dominican Republic, Ecuador, Hong Kong, Jamaica, Lebanon, Panama, Syria, West Bank and Gaza
e
Countries excluded from analysis due to missing data:United Arab Emirates, Argentina, China, Ecuador, Panama, Saudi Arabia, Syria, Venezuela, Bosnia and Herzegovina, Brazil, Germany, Dominican Republic,
Jamaica, Malaysia, Peru, West Bank and Gaza, South Africa, Hong Kong, Lebanon.
25
The table also provides a synopsis of the regression analyses that were carried out for the
purpose of answering the hypotheses. Models II, III and IV concern Ordinary Least Squared
(OLS) regressions. Model II delves into the independent effect of public spending, the formal
institutional factor in this investigation, on the prevalence of nascent social entrepreneurship.
It can be observed that the explanatory factor only explains about 0.35% of the variation across
countries in terms of nascent social enterprises. The findings demonstrate a weak (positive)
and considerably insignificant link, failing to establish any parallels between abovementioned
independent and prevalence rates of nascent social start-ups. Therefore, an alteration of public
sector investment by governments would not bring about any substantial changes in the rise of
social enterprises that are still in their nascence or such entrepreneurs who, in the past 12
months, have taken steps towards creating social enterprises that they would own either partly
or in entirety.
Model III carries out an analogous function to Model II, as it attempts to scrutinize the
independent upshot of education on the same dependent variable. On this occasion, the model
explains a much greater percentage (8.44%) of the variation in the prevalence of nascent social
entrepreneurship, although it is still a substantially small fraction. The informal institutional
variable of Educationseemingly possessesa statistically significant and positive bearing on the
prevalence of nascent social ventures, with a correlation of 0.022. Its p-value remains lower
than the 5% significance level (0.025). The inference in this case would be that educational
institutions inculcate a sense of sanguinity and buoyancy in masses to begin their own social
ventures in order to contribute to community. Henceforth, countries that boast of higher
education levels should experience greater prevalence rates of nascent social enterprises.
Model IV served a similar purpose, with post-materialism being the informal institutional
variable vetted on this occasion. The R-squared value is much higher at 18.01%, which implies
that the independent variable highlights larger variations of the dependent variable. Postmaterialism has a strongly significant (and positive) impact on the dependent variable, with a
fairly weak correlation of 0.06 (p-value = 0.003). This indicates towards the positive influence
of societies with emphasis over self-expression and quality of life, on the incidence of novel
and nascent social enterprises.
Lastly, Model V illustrates a multivariate regression model which includes both the
aforementioned formal and informal factors. The proportion of dependent variable explained
by this model (23.46%) is quite inevitably greater than all previous models. While education
26
and public spendingpossess insignificant weightages,post-materialism continues to possess a
significant positive control (p-value = 0.027) over the emergence of nascent social
entrepreneurship at 5% significance level. Most individuals with values of self-expression and
sovereignty carry an incentive to rally the cause of stamping out social conundrums. This in
turn, could be argued as a reason for larger frequency of nascent social enterprises in countries
with fairly greater prevalence of post-materialism.
An important element that necessitates deeper scrutiny is the disharmonized sets of countries
utilized for each model. To be more precise, different groups of countries were left out in each
regression due to lack of data, which could lead to less cohesion in terms of findings (discussed
in the ‘Limitations’ section of ‘DISCUSSION’). Nonetheless, these discoveries lead to the
repudiation of Hypothesis 1 as the formal institutional variable of public spending does not
make any statistically significant difference to the emergence of nascent social entrepreneurial
activities, both when tested for independent (only informal or only formal) effects (Model II)
and in conjunction with theinvolved institutional variables (Model V). Hypothesis 2 can be
partially accepted as education constructs a significant impact on the prevalence of nascent
social entrepreneurship when tested independently (Model III). However, in Model V, when
tested for joint effects, it does not seem to strike any significant linkage with the dependent
variable of the model. Hypothesis 3 however, can be accepted as post-materialism possesses a
statistically significant positive impact on the prevalence of nascent social enterprises in both
Models IV and V.
27
Chapter 5
Discussion
Contributions of Results
According to the estimations found in this study, some informal factors might have a role to
play in fuelling impetus for the creation of nascent social enterprises. While post-materialism
and education (partially)showed signs of having an impression of statistical significance, the
formal institutional variable of public spending did not seemingly have any command over
nascent entrepreneurial activities. However, the universal validity of these conclusions might
be weak and insubstantial. For instance, the aforesaid finding, which led to a partial approval
of Hypothesis 2, does not imply an automatic positive impact (or an insignificant impact, when
tested in conjunction with additional environmental factors) of education on accelerating rates
of nascent social entrepreneurship. Inquiries conducted by Zahra et al. (2008) and Arenius &
Minniti (2005) showcased how education indeed had a significant positive effect and allowed
people to leverage their expertise into assembling organizations with societal goals. However,
to counter such claims, Blanchflower et al. (2001) suggested a negatively inclined inspiration
of education towards furthering the cause of social start-up activities. In addition, additional
research has also produced conclusions similar to Model V of this study, since Lin (2000) failed
to establish any significant link between education and its impact on variation in the rates of
start-ups. The evidence may have been pertaining to the entire branch of social
entrepreneurship; however, results could reflect outcomes for their nascent subset in the
process.
Therefore, contrasting reviews suggest that there might not necessarily be a clear and concrete
answer to the question regarding prevalence rates of social enterprises, let alone nascent social
ventures. The fact that education is no longer significant when examined with other germane
variables (post-materialism in Model V) could point to the notion that other factors are of
higher importance when considering infant social enterprises. Hence, policy-makers should
28
also readdress attention to other cultural elements which might trigger nascent social
entrepreneurial activities. Another implication could be directed to refining focus towards the
micro-level features of education, such as regional educational rates and relative nascent social
entrepreneurial rates in respective areas, while retaining a strong grip over the macro-level
facets. Probing the quality of infrastructure available and opportunity to social enterprise
networking might aid the development of youthful pupils (British Council, 2014), to engage in
socially relevant activities in the future. For that reason, espousing more suitable businesses,
which could work in collaboration with educational institutions to provide fitting structure to
students, is an idea that should be thoroughly inspected. Especially for developing countries,
where noteworthy variations in the level of education within the geography exist, micro
policies catered towards aspects discoursed above, could assist in empowering social start-ups.
Macro-policies, although implemented with efficacy on certain occasions, would lose strength
if nascent social entrepreneurial firms do not form the focal point of their strategies.
Post-materialism, as listed above, had a significant positive impact on our dependent variable,
leading up to the recognition of Hypothesis 3 in the process. Accordingly, societies which
prioritized high self-expression and autonomy over materialistic qualities such as economic
security, tended to experience greater rates of nascent social enterprise incidence. Inglehart
(1997) believed that young affluent cohorts had higher probabilities of engaging in work with
social causes, as they were more likely to cherish non-material aims. Therefore, delving into
demographical (intergenerational) as well as cultural lacunas would be intriguing research
topics. There could be dissimilarities observed in terms of age differences since the older
generations, as considered by Inglehart, did not possess the same value systems in order to get
involved in social entrepreneurial activities. So, along with the demographical change, there
was a cultural shift from materialism to post-materialism, i.e. a transition from economic and
physical refuge to autonomy and relative security. Inglehart (1997) anticipates these changes
to take place on a global scale and possess traces in each country that experiences such a
changeover in cultural mechanism. So, gaining perspective on this relationship would aid in
assessment of alterations in the level of (nascent) social entrepreneurial activities.
Next, the formal factor of public spending was deemed ineffective in swaying nascent social
entrepreneurship entry, prompting the rejection of Hypothesis 1 in the process. The popular
belief is that reducing government involvement would lead to a greater demand for social
entrepreneurship and hence, a greater share of the populace joining the social enterprise
creation bandwagon (Estrin et al., 2013; Mair & Marti, 2009). To be more precise, public
29
spending possessed a negative upshot on the absolute level of social enterprises. However, this
viewpoint has not always been supported in empirical research. Studies using institutional
framework, from a behavioral economics standpoint, have also shown support to the notion of
complementary support of government and private institutions (Heutel, 2014; Stephan, Uhlaner
& Stride, 2014). The potential synergy between public and private sector expenditure could
extend to more lucrative options for (nascent) social entrepreneurship (Skocpol, 2008). So,
there could also be instances where government and concomitant institutions work in tandem
with ventures dedicated to societal causes, in order to expedite rates of nascent social
entrepreneurial activities.
Overall, while noteworthy positive effects were registered for the informal factors of postmaterialism and education, the formal institutional variable of public spending could not lodge
a statistically significant impact on the prevalence of nascent social enterprises. Thus, policymakers should work towards designing guidelines that are culturally stimulating. Rather than
refining constitutional procedures and tightening screws on government activism, creating
regulations that nudge individuals as well as groups towards post-materialistic belief systems.
Emphasizing on cleansing cultural values by educating masses regarding collective social
welfare could perhaps enhance incidence rates of social start-ups and other similar ventures.
Limitations
As can be observed with virtually all investigations, this study comes with a few limitations.
The first limitation would pertain to dilemmas concerning the definition of social
entrepreneurship and therefore, nascent social entrepreneurship. Though a comprehensive
procedure was adopted by Lepoutre et al. (2013) to measure the phenomenon, there did not
exist any direct questions to explicitly identify social entrepreneurs. The concept of social
entrepreneurship could allude to different models across countries, which might hamper the
veracity of our findings. Additionally, dissimilar interpretations of social entrepreneurship
would also reflect in the diverse definitions of nascent social entrepreneurial activities across
countries. Country-level assessments would then deliver incorrect indications about differences
in the prevalence rates of (nascent) social enterprises. Furthermore, acquiring solutions for this
conundrum would also be troublesome, since the fact that understanding of (nascent) social
entrepreneurship fluctuates through countries would hinder the search for any common
30
determinants that could potentially explain incidence rates of the phenomenon from a macrolevel perspective.
Secondly, not only GEM lacks coverage as shown above, but also the methodology used by the
research program to measure aspects of social entrepreneurship is inefficient. For instance,
questions alluding to social and community-based intents were included in the preliminary
screening; however, environmental objectives seemed to take a backseat during the whole
procedure. This could advocate for the prospect of environmental social entrepreneurship,
which is an instrumental aspect, being incomplete or under-represented. The numbers recorded
for social entrepreneurship and its branches (i.e. nascent and young business owners) could in
turn, be biased and incomplete as well.
Thirdly, the sample capitalized in this research should be extended further in order to conduct
analysis on a larger dataset. Factor-driven countries were relatively under-represented whereas
innovation-driven economies were dominant in the sample obtained from GEM reports. Larger
and more even datasets could probably reinforce the reliability of our findings.Also, it becomes
problematic to institute significant effects while utilizing smaller samples, as they tend to
restrict statistical power. Noteworthy results for the independent variables of post-materialism
and education even within a considerably small dataset underpins the validity of our outcomes.
Fourthly, when combined with the lack of harmonized data available for explanatory variables,
it leads to irregularas well as fewer data points, which can be comprehended from the models
used in this study (Table 2).Uneven data availability for the independent variables calls for
different groups of countries to be used as per the requirement of each model. This however,
could create inconsistencies and lead to lack of structure. In other words, there arises a
possibility of some countries being used in one model, but dropped in others due to missing
data. These minor differences could make it troublesome to reach a concrete conclusion,
especially regarding the independent effects of environmental factors used in this paper, as the
samples in entirety are not identical. Perhaps adopting uniform data or similar clusters of
countries for all models could solve the aforementioned potential problem.
The fifth limitation refers to data extraction for explanatory variables, which could have been
more efficient in terms of the uniformity of sources. Data for post-materialism for instance,
had to be obtained from World Value Survey (WVS) and European Values Study (EVS). This
could lead to asymmetries in data as both sources possess their respective techniques of
acquiring statistics regarding post-materialistic values, which in turn, could differ from one
31
another. Furthermore, figures for the sample were mined from multiple waves (fourth and fifth),
which represented two different time periods. Therefore, there was a lack of consistency in the
numbers attained due to missing data, which might present a false understanding of the impact
of the variable on the prevalence rates of nascent social entrepreneurship across countries. This
is because of the systematic risks that countries are exposed to, at various stages. For instance,
a recession hit country might report materialistic values temporarily due to urgency of
monetary security. However, over time, as the recession subsides, post-materialistic values
might begin to surface among the populace again. So, for example, high percentages of
emergence of new social start-ups in the fourth wave (1999-2004) do not imply an automatic
replication of results in the fifth wave. Organized data collection from a single source would be
ideal for grinding out consistent and accurate conclusions.
Lastly, the methodology for analysis, in this paper, involved regression analyses (OLS), which
are not effective for establishing causal relations between variables. They do enhance our
understanding regarding the relationship that exists amongst relevant variables; however, do
not necessarily signal causality. There could also be numerous extrinsic factors, (not taken into
account due to data inaccessibility or other complexities) which might have impacted the
emergence of new social start-ups. Moreover, since majority of the data for concerned variables
were collected in 2009, i.e. during the economic crisis, it is difficult to predict whether our
results are unbiased.This is because economic and political state of affairs could have disturbed
the data, influencing the outcomes of this research in the process.
Chapter 6
32
Conclusion
The concept of nascent social entrepreneurship is in its infancy and possesses the prospective
characteristics to entice academicians as well as policymakers. As stated at the outset, findings
of quantitative research can smoothen the policy designing process, as they proffer key insights
into factors that incentivize initiatives such as administering newborn enterprises that work
towards alleviating societal issues. This paper delves into environmental factors that could
orchestrate greater rates of nascent social ventures on a cross-country level. Hypotheses were
formulated in accordance with the institutional economics approach, with data from GEM
report of 2009 utilized for analysis.
The propositions used in this study add to existing stream of literature that aims at discovering
determinants for social entrepreneurship, from a macro-level standpoint. Using the institutional
framework countenanced by Douglas North, this paper explored both formal and informal
configurations, which could potentially expedite or hinder prevalence rates of nascent social
entrepreneurship. The results indicated possibilities of multiple environmental institutional
factors influencing the emergence of nascent social ventures to a considerable extent. However,
statistically significant effects were only confined to the informal institutional elements. Postmaterialism possessed a substantial and positive influence on the prevalence of nascent social
entrepreneurial activities, when tested for both independent and joint effects.The informal
institutional
factor
of
education,
however,expressed
significantonly
when
tested
independently. The formal institutions, represented by public spending, did not seemingly have
an impact on the advent of nascent social start-ups. While results for informal institutions are
aligned with the institutional economics approach to a certain extent, formal institutions should
be dissected in depth to establish a clear concrete conclusion.
Further investigations are required to comprehend the relationships with higher efficacy.
Perhaps addition of multiple variables to increase strength of both formal and informal
institutional variables in the regression analyses would provide us with a comprehensive
picture regarding incidence rates of nascent social entrepreneurship. Additionally, delving into
other branches of social entrepreneurial activities, such as young business owners and social
entrepreneurs in established organizations (data provided by GEM) could also provide key
insights for policymakers to take collective decisions regarding policies that espouse such
activities. Analyses could also be segmented demographically as well as by gender, in order to
inspect different dimensions of social enterprises. Finally, micro-level analyses pertaining to
33
prevalence rates of nascent social entrepreneurial activities would serve policy-makers well, as
that would provide them with granular details about the influence of each environmental
institutional factor. It would offer exhaustive information on the designing procedures that they
should undertake in order to ensure higher nascent social ventures on the micro-level, which
could accordingly reflect in analyses across countries.
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Appendices
APPENDIX 1: Description of Variables for Regression Models
39
Dependent
Independent Variables
Variable
Control
Variable
Variable
Description
Source
Nascent Social
Entrepreneurial
Activity (NSEA)
Nascent Entrepreneurs are individuals, who claim to have undertaken
tangible steps in the past 12 months towards creating a social
enterprise, which they would personally own all or part of. The social
enterprise has not provided services, nor paid salaries for more than
three months.
GLOBAL ENTREPRENEURSHIP
REPORT (2009)
Public Spending
Expense is cash payments for operating activities of the government
in providing goods and services as a percentage of gross domestic
product. This includes compensation of employees (such as wages
and salaries), interest and subsidies, grants, social benefits, and other
expenses such as rent and dividends.
WORLD BANK
(http://data.worldbank.org/topic/public-sector)
Post-materialism
The degree to which the population of a society are willing to adopt
non-materialistic values such as self-expression and autonomy, over
materilistic ones such as economic security.
WORLD VALUE
SURVEY(http://www.worldvaluessurvey.org/)
&
EUROPEAN VALUES
STUDY(http://www.europeanvaluesstudy.eu/)
Education
The (gross) percentage of students enrolled from primary
to tertiary education, both sexes.
UNESCO(http://data.uis.unesco.org/)
GDP per capita
Gross domestic product per capita adjusted for purchasing power
parities in US dollars.
INTERNATIONAL MONETARY
FUND(http://www.imf.org/external/index.htm)
APPENDIX 2: Countries and respective Nascent Social Entrepreneurship rates (%)
40
Country Name
United Arab Emirates
Argentina
Belgium
Bosnia and Herzegovina
Brazil
Switzerland
Chile
China
Colombia
Germany
Dominican Republic
Algeria
Ecuador
Spain
Finland
France
United Kingdom
Greece
Guatemala
Hong Kong SAR, China
Croatia
Hungary
Iran, Islamic Rep.
Iceland
Israel
Nascent Social
Entrepreneurship
(%)
Country Name
2,40
2,20
1,00
0,60
0,20
2,40
1,70
1,40
2,70
0,50
0,80
0,80
0,40
0,40
1,20
1,60
0,80
1,30
0,10
0,20
1,30
2,00
1,00
2,30
0,90
41
Nascent Social
Entrepreneurship
(%)
Italy
0,80
Jamaica
1,20
Jordan
0,30
Korea, Rep.
0,40
Lebanon
0,40
Latvia
1,40
Morocco
0,30
Malaysia
0,20
Netherlands
0,50
Norway
0,60
Panama
0,90
Peru
3,40
Romania
1,30
Russian Federation
0,40
Saudi Arabia
0,10
Serbia
0,40
Slovenia
1,30
Syrian Arab Republic
0,70
Uganda
0,70
Uruguay
1,90
United States
2,90
Venezuela, RB
3,40
West Bank and Gaza
0,20
South Africa
1,20