The 40th Annual Conference of the Institute for Small Business and
Push vs Pull: Does the motivation for an entrepreneurial career vary by country?
Brian A. Polin | Stephan Golla
This paper, presented at the ISBE 2017 conference, is for the individual use of conference delegates and ISBE
members only. Unauthorised republication, sharing or modification is strictly forbidden. For details, please contact
For decades scholars have been investigating what motivates one to become an entrepreneur. Why might
one subject himself to the financial uncertainties of establishing a business, when lower risk employment
options are available? In their search for an explanation, researchers considered multiple variant
explanations for the phenomenon of entrepreneurship. Among the theories that evolved were the "push" or
"necessity" based ones, positing that the predominance of entrepreneurship is primarily a function of the
shortage of employment in existing firms. These were followed by the "pull" or "opportunity" based ones,
offering that entrepreneurship is primarily driven by individuals seeking opportunity or looking to capitalize on
their skills and strengths- both in the form of human and social capital. Eventually these two competing
theories were melded into the push/pull theory of entrepreneurship, claiming that both (sets of) factors,
perhaps even diametrically opposite, determine the intensity of entrepreneurial activity.
As multi-nation studies became more commonplace, it was observed time and again that entrepreneurship,
whether in the form of entrepreneurial intent or actual entrepreneurial activity, varied greatly by country. It
was also observed that entrepreneurial activity is much more widespread in developing nations, when
compared with developed nations. Other studies, using the tripartite factor-driven, efficiency-driven,
innovation-driven paradigm reached the same conclusion- a country's GDP and its rate of entrepreneurship
are inversely related. Beyond the economic prosperity of a nation, or lack thereof, some scholars attempted
to explain the varying levels of entrepreneurial activity among nations in terms of cultural differences- often
times using Hofstede's model of cultural dimensions.
It stands to reason that countries with greater tolerances for uncertainty, for example, might be associated
with higher levels of entrepreneurial activity, but that doesn't provide us with a great deal of information about
the nascent or aspiring entrepreneurs themselves. The question that remains is how (those aspiring to
become) entrepreneurs differ from those who are not, and how these differences vary by country. Are there
specific countries where the entrepreneurs and the non-entrepreneurs are nearly indistinguishable in all
areas other than their chosen career path? Are there countries where the differences between these two
populations are very pronounced? What general conclusions might be reached about different countries
based on the intensity of motivational factors traditionally associated with entrepreneurship?
A cross-country analysis of these two populations within each country will yield interesting results about the
true individual motives of entrepreneurs by filtering out ambient cultural and economic conditions.
From push-based entrepreneurship to push/pull
In an early monograph investigating the development of technology-based firms in Palo Alto, California, the
area that would later become known as "Silicone Valley", Cooper (1971) considered why "some individuals
become entrepreneurs and not others"(p.54). He offers a number of possible explanations including genetics
(intelligence, energy levels), childhood experiences (role models, self-employed fathers) and an orientation
toward science and math, but concludes that "for most men, it is difficult to leave the 'warm bed' of a secure
and satisfying position." In other words, according to his reasoning, one wouldn't sacrifice stable and
satisfying employment and choose entrepreneurship, unless negative circumstances "forced" him into it.
Shapero (1975) determined that entrepreneurs were largely displaced persons (DPs). Most were figurative
DPs who had been fired from their jobs, while others were quite literally DPs, as in the case of political
refugees. Some entrepreneurs hadn't yet been fired from their positions, but their decision to engage in
entrepreneurship stemmed from a feeling that their jobs were leading them nowhere- certainly not to a rosier
Although Brockhaus (1980) entertains the possibility of "being 'pulled' into an extremely appealing business
opportunity", he rejects this notion immediately and concludes that entrepreneurship is driven by a "push" –
either dissatisfaction or displacement from a previous job.
In a revisiting of Cooper's (1971) earlier work, Cooper and Dunkelberg (1986) consider the different paths to
business ownership, where ownership includes founding (entrepreneurship), purchasing and inheriting. As in
the case of earlier works, the term "pull" is nowhere to be found, but in a departure from previous works they
consider such factors as "to let you do the kind of work you wanted to do" and "to avoid having to work for
others" as factors in the decision to become one's own boss. These would later become known as "pull"
motivators, and will be addressed shortly in this paper.
Amit and Muller (1995) operationalize push and pull entrepreneurship as two mutually exclusive alternatives
on a push/pull continuum. With two Likert-scored survey items for push, where agreement is indicated as a
negative score, and two for pull, where agreement is indicated with a positive score, an overall negative
score indicates a push entrepreneur, while a positive score suggests pull as the motivation for one's decision
to become and entrepreneur. Beyond the mere classification of push and pull-motivated entrepreneurs, they
provide strong support to their hypothesis that pull (or opportunity) driven entrepreneurs are more successful.
Amit and Miller's conclusions about the differing success rates between push and pull entrepreneurs suggest
that the distinction between push and pull is not purely an academic one, but one with significant economic
ramifications. Acs and Varga (2005) highlighted this distinction even further with a study of 11 countries and
found that opportunity (or pull) entrepreneurship had a positive effect on a nation's economic development,
whereas necessity (or push) entrepreneurship had no effect at all. Addressing "good" and "bad", Baumol
(1996) distinguishes between productive and largely unproductive entrepreneurial activities. The former
group includes innovation, while the latter group consists of "rent seeking activities" that do not contribute to
a greater good. This finding will be revisited in the concluding section of the paper.
Variations from country to country
In addition to Acs and Varga (2005), numerous other studies have investigated entrepreneurial differences
from country to country. The research questions often asked address the degree to which a nation's culture
influences entrepreneurship. Rather than being able to attribute varying frequencies of entrepreneurship
exclusively to aspects of a county's culture, findings are often contradictory. In their study of 14 countries,
Schlaegel, He and Engle (2013) found the country's cultural dimensions to have only a "very small
moderating effect. (605)", they also found GDP and "ease of doing business" to be significantly negatively
associated with entrepreneurial intent. Estay, Durrieu and Akhter (2013) conclude that characteristics of
French entrepreneurs include risk taking, accomplishment, control and creativity, and while this is only a
single-country study, it may be possible to extrapolate regarding other countries as well. Hofstede,
Noorderhaven, Thurik, Uhlaner, Wennekers & Wildeman (2004) argue that the rate of entrepreneurship in a
given society depends both upon the capabilities and preferences of the individuals and the opportunities
provided by the society.
Tajeddini and Mueller (2009) compare "entrepreneurial characteristics" in techno-entrepreneurs in the UK
and Switzerland. While the differences for these values tend to be small between these two populations, the
difference in autonomy is quite large. This provides ample evidence that differences may be attributable to
cultural differences, rather than the intensity of the desire to become an entrepreneur. When comparing
populations in multiple countries it is necessary to distinguish between the entrepreneurial motivations and
cultural factors that both influence these values. Because of cultural differences between the countries, it is
natural that the importance of each of the factors should vary from country to country, even independent of
entrepreneurial intent. A high score for a particular dimension in a particular country may be a reflection of
the importance of that motivational dimension, but it may also be a reflection of the importance that particular
culture places on that particular value. This distinction will be address in the next section.
In order to compare different populations and the motivations that drive one to engage in entrepreneurship,
we utilized the most recent Global University Entrepreneurial Spirit Students Survey (GUESSS) data.
GUESSS is a research project about the context of entrepreneurship. Its purpose is to grasp the
entrepreneurial intent and activity of students using a geographical and temporal comparison (Project Goals).
Data is gathered using an on-line survey in English and/or the local language of the country.
Nearly 110,000 university students in 34 countries participated in the survey. Among the hundreds of survey
items was a 10 dimensional scale for "career motives". Respondents indicated on a 7-point Likert-scale how
influential each dimension was in their choosing a career path. The scale, developed and validated by
Soutaris, Zerbinati and Al-Laham (2007) is based on Kolvereid's (1996) predictors of employment choice
intentions and consists of ten motives:
(1) to have a challenging job;
(2) to have an exciting job;
(5) to be your own boss;
(6) to have power to make decisions;
(7) to have authority;
(8) to realize a dream;
(9) to create something; and,
(10) to take advantage of creative needs.
Explaining the link between these motives and self-employment, Soutaris et al (2007) determine that
"Attitude towards self-employment’ is the difference between perceptions of personal desirability in becoming
self-employed and organisationally employed. Therefore, ‘high’ attitude towards self-employment actually
indicates that the respondent is more in favour of self-employment than organisational employment."
Moreover, these motivators are not only predictors of self-employment, but predictors of self-employment of
the pull variety. Although not present in the GUESS survey data, some scholars include a number of push
motives (job dissatisfaction, children in the family necessitating flexible work, etc.) as predictors of push self-
employment (Kirkwood, 2009). As the dependent variable, student-survey participants were asked students
about their preferred occupational choice immediately after graduation, as well as five years hence, as
shown in table 1.
Insert Table 1 here
The data show that a mere 6.6% of respondents consider starting their own enterprise directly after
graduation. This figure increases significantly when participants were asked about their choice career five
years after graduation. Here, 30.7% see the option of working in their own startup as a potential career path.
An increase in the percentage of survey participants expressing a desire to become entrepreneurs from
immediately post-graduation to five years post-graduation is not surprising, as many of those innately
desiring to become entrepreneurs only feel comfortable doing so after they have accumulated professional
experience in pre-existent firms. While the 30.7% figure may seem quite large, no general sweeping
statements may be made, as the percentage of participants desiring to become entrepreneurs five years
post-graduation varies greatly on a country-by-country basis. As per table 2, more than 50% of the students
in Mexico, Argentina, Columbia and Russia express an interest in entrepreneurship. By contrast, the figure
for Japan, Denmark, Germany and Switzerland, all countries traditionally associated with technological
advances, does not exceed 18%! As will be explained in the section below, this seems to contradict what
one might intuitively think about nations perceived to be innovative versus those whose economies are
largely based on industry and manufacturing.
Insert Table 2 here
In order to facilitate the investigation of the different levels of motivation, we first reduced the ten items to
three components by applying principal component analysis with varimax rotation. Here, we confirmed the
factor structure as per the extant literature (Sieger, Gruber, Fauchart and Zellweger, 2016; Carter, Gartner,
Shaver and Gatewood, 2003; Kolvereid, 1996).
The three components we extracted represent the three main (classes of) motives for seeking a specific
career path. The motive “power” (Eigenvalue = 3.955, Cronbach’s Alpha =0.79) consists of items “freedom”
(factor loading = 0.66), “independence” (0.746), “be your own boss” (0.749), “have power to make decisions”
(0.732), and “have authority” (0.669); the motive “challenge” (Eigenvalue = 1.260, Cronbach’s Alpha 0.76)
consists of items “have a challenging job” (factor loading = 0.794) and “have an exciting job” (0.829); and
finally, the motive “creativity” (Eigenvalue = 1.160, Cronbach’s Alpha 0.65) consists of items “realize your
dream” (factor loading = 0.585), “create something” (0.853), and “take advantage of your creative needs”
(0.844). All cross loadings are smaller than 0.4. KMO Measure = 0.81. Overall, the three factor structure
explains 63% of variance.
Insert Table 3 here
These factors are used to assess the different motives that drive people towards self-employment. In order to
confirm that these three motives predict attitudes towards the establishment of an entrepreneurial venture,
we performed a logistic regression. To further investigate the wide disparities in the desire to engage in
entrepreneurship by country, particularly noting the "nature" of the countries at both ends of the distribution,
we calculated a dummy variable to reflect their economic status. Porter, Sachs and McArthur (2002) created
a nomenclature to classify countries based on their stage of economic development. From subsistence-level
agriculture, a country's first stage of economic development is called factor-driven, whereby a country
produces primary commodities with largely unskilled labor. None of the countries in our sample were at this
stage of economic development. Efficiency-driven countries compete economically primarily on the basis of
their production of "standard" goods and services. These are countries traditionally associated with low-cost,
or efficient, manufacturing. Innovation-based countries compete on the basis of new technologies and high
rates of social learning. "Start-up", "hi-tech" and other terms connoting goods and services stemming from
investment in research and development are generally associated with this classification of countries. Table
4 classifies the countries on the basis of their economic group, based on the Global Economic Monitor
Insert Table 4 here
The logistic regression results are shown in table 5. Two motive factors “Power” and “Creation” are positively
related to the dependent variable “Self-Employment 5 Years after Graduation” with an odds ratio of 1.826
and 1.625 respectively and p-value <1%. The motive “Challenge” is not confirmed as a predictor of starting
an own venture with an odds ratio <1 and a non-significant p-value of 0.843. The results also show a positive
relationship between country’s economic status and self-employment. The odds ratio of 0.32 with a p-value
<1% shows that efficiency-based countries show higher startup potential than innovation-based countries.
Our interim findings may be stated as follows:
There is a strong correlation between the "power" motive and the desire to become an entrepreneur
There is a strong correlation between the "creation" motive and the desire to become an
The correlation between "challenge" and the desire to become an entrepreneur cannot be confirmed
There is a strong correlation between a country's developmental status and the desire to become an
entrepreneur, namely, the desire to become an entrepreneur in efficiency-based country is
significantly higher than the desire to become an entrepreneur in innovation-based countries
These findings confirm the 'descriptive' findings stated earlier, but leave unanswered the fundamental
question of what drives entrepreneurial orientation. More specifically, might the differences between Mexico,
Argentina, Columbia and Russia on the one hand and Japan, Denmark, Germany and Switzerland on the
other be attributed to culturally embedded preferences, or is there really a huge tendency towards startups?
Does entrepreneurship vary from country to country quantitatively only, or are there qualitative differences as
well between an aspiring German entrepreneur and his counterpart in Mexico?
Insert Table 5 here
In order to indeed determine how entrepreneurs from efficiency-based countries vary from those in
innovation-based countries, it was necessary to factor out the ambient culture of the country. For our
purposes, it was necessary to determine if a high score for "power", for example, was attributable to an
entrepreneurial orientation, or if it stemmed from a general importance attributed to "power" in a given
society. Our "measure of differences" addresses this.
Insert Table 6 here
We calculated the factor scores for “power”, “creative” and “challenge” for each innovation and efficiency-
based country individually. Within each of these countries, we calculated the factor scores separately for
those desiring to become entrepreneurs and those preferring to be employed by others. The "measure of
differences" is the difference in these factors scores for each of these two "populations" within each country.
If, traditionally, (aspiring) entrepreneurs are motivated by a personal need for power, the expression of
creativity and the need to be challenged, then those desiring to be entrepreneurs should attribute higher
scores to each of these factors than the non-entrepreneurs from the same country. By addressing these
differences, and considering how entrepreneurs and non-entrepreneurs within each country differ from each
other, we were able to neutralize the impact of the culture that varies greatly from country to country.
Table 6 presents a mean of 0.710 for innovation-driven countries and a mean of 0.520 for efficiency
countries. This means that for the motive "power" the difference in the factor score between entrepreneurs
and non-entrepreneurs in both groups of countries is positive. Not surprisingly, entrepreneurs rank power
higher than non-entrepreneurs, as this is one of the "needs" driving them to become entrepreneurs in the first
place. The fact that this difference is positive, for both groups of countries, may be somewhat trivial. The
innovative finding worthy of note here is the significant difference between the 0.710 for innovation-driven
countries and a mean of 0.520 for efficiency countries. The t-test in the lower section of the table confirms
the significance of the difference (between innovation and efficiency-based countries) between the
differences (between entrepreneurs and non-entrepreneurs).
Conceptually, table 7 illustrates a pattern for "creative" similar to the one seen in table 6 for "power". The
difference in the "creative" factor score between entrepreneurs and non-entrepreneurs in innovation-based
countries is 0.40, while the difference between these two populations in efficiency-driven countries is 0.17.
Again, the t-test in the lower section of the table confirms the significance of the difference between these
Insert Table 7 here
Contrary to the findings for "power" and "creative", which concluded that the "difference of the differences"
was significant, the "difference of the differences" for “challenge” is smaller and not statistically significant.
Insert Table 8 here
At the outset of this paper, we asked the question that has been asked many times before: what motivates
one to become an entrepreneur? While the factors are many, the data presented in table 2 depict a pattern
of higher levels of entrepreneurship in developing countries than in developed countries. This observation
raised the possibility that entrepreneurship in efficiency-based and innovation-based countries may be driven
by different motivators altogether. The quantitative differences in entrepreneurship between developed and
developing countries are readily observed, but are there qualitative differences as well? To further consider
this phenomenon, and isolate country-specific cultural influences, we compared entrepreneurs and non-
entrepreneurs within each country. As tables 6 and 7 (and to a much lesser degree 8) illustrate, traditional
entrepreneurial motivators distinguish between entrepreneurs and non-entrepreneurs in innovation-based
countries more than they do in efficiency-based countries. Stated differently, if the motivations detailed in
table 3 are associated with pull entrepreneurship, and they are less pronounced in distinguishing between
entrepreneurs and non-entrepreneurs in efficiency-based countries, is entrepreneurship in these countries of
push variety? Dawson and Henley (2012) suggest that it may be difficult to "disentangle" push and pull
motivations and that both may be present in the decision to become an entrepreneur. That notwithstanding,
when comparing the two types of countries, entrepreneurship may be more push than pull in efficiency-
based countries. Do entrepreneurs in efficiency-based countries choose their career path as a matter of last
resort? Why does this matter?
As addressed earlier in the paper, scholars distinguish between "good" and "bad" (or neutral)
entrepreneurship, where "good" and "bad" correlate with push and pull (Amit and Muller, 1995; Acs and
Varga, 2005; Baumol, 1996). Bygrave, Hay, Ng and Reynolds (2003) graphically depict this distinction:
At one end of that spectrum is a lone, self-employed person in an impoverished region for whom
eking out a subsistence living from a micro-business is better than no work at all. At the other end is
a team of high-tech superstars in a technology metropolis with a high-potential opportunity that they
believe will change the way in which we work, live, and play (105).
Governments must determine if the entrepreneurship within their jurisdictions is of the former or latter variety.
Where it is of the latter variety, government policy should prioritize the integration of these unwilling
entrepreneurs into the workforce. Not only are push entrepreneurial ventures less successful, but the
preconditions facilitating push entrepreneurship often keep university graduates out of the workforce.
Directions for further investigation
While the thrust of this paper has been to investigate the differences between entrepreneurs in efficiency-
based and innovation-based countries, and their motivations for engaging in entrepreneurship, it has not
investigated the nature of the entrepreneurial activities themselves in each of these two types of countries.
Undoubtedly, at the macro-level, one who is intrinsically motivated perform an act will do so better than one
who does it because he is compelled to do so, but are there factors other than motivation at play? How does
the role of bureaucracy or the regulatory infrastructure differ between the two types of countries, and what is
their impact on the success of the entrepreneurial ventures they host? Does the degree of enforcement of
intellectual property laws preclude "good" entrepreneurship in some efficiency-based countries?
Entrepreneurship has the power to change the world for the better, but only if it is the right type of
entrepreneurship. The conditions that enable "good" entrepreneurship do not occur in a vacuum. It is the
job of government policy makers to strategize, prioritize and create these conditions.
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Table 1: Occupational Choices Directly and 5 Years After Graduation
Table 2: Willingness of Self Employment per Country
Table 3: Principal Components of Motives
Table 4: Efficiency and Innovation Based Economies
Table 5: Logistic Regression, Dependent Variable “Self-employed 5 Years After Graduation
Table 6: Means Difference Test Factor “Motive Power”
Table 7: Means Difference Test Factor “Motive Creativity”
Table 8: Means Difference Test Factor “Motive Challenge”