Electronic copy available at: http://ssrn.com/abstract=2412932

Is entrepreneurship a teachable profession?

An examination of the effects of entrepreneurship education and experience1

Julian Lange

Edward Marram

David Brown

Joel Marquis

William Bygrave

Babson College

ABSTRACT

We examined the conflicting claims of Schumpeter, who stated that entrepreneurship is not a

profession, and Drucker, who wrote that entrepreneurship is a discipline that can be learned (and

presumably taught). We studied the effects of an entrepreneurs education and experience on the startup and subsequent operating performance of a new venture. Taking entrepreneurship

courses enhanced the amount of startup capital raised, but real-world experience enhanced it

more. However, neither taking entrepreneurship courses nor learning how to write a business

plan had any effect on the subsequent operating performance of the business. Previous

entrepreneurship experience enhanced the amount of startup capital raised but did not improve

the operating performance. In contrast, professional experience in generalrather than entrepreneurship-specificgained after graduation before starting a business improved operating performance.

INTRODUCTION

Schumpeter (1934) stated that entrepreneurship is not a profession and that being an entrepreneur

is not a lasting condition; whereas Drucker (1985) claimed that entrepreneurship is a discipline

that can be learned. To investigate these conflicting claims we studied 375 serial entrepreneurs

and 538 one-time entrepreneurs who are alumni Babson College, a leading entrepreneurship

school. We were particularly interested in two of an entrepreneurs most important human assets: education and experience. We reasoned that if entrepreneurship is a profession or

discipline then basic entrepreneurial skills can be learned in school and enhanced with real-world

experience as a practicing entrepreneur.

LITERATURE SUMMARY

The literature that is most relevant to our study deals with the relationship between

entrepreneurial performance and founders human capitaleducation and experience in

1 An earlier version of this paper was presented at the Babson College Entrepreneurship Research Conference,

Texas Christian University, Fort Worth, June 2012.

Electronic copy available at: http://ssrn.com/abstract=2412932

2

particularbecause according to human capital theory, education and experience are the most important determinants of intellectual performance and facilitate assimilating new knowledge

and adapting to new situations (Weick, 1996; van der Sluis, van Praag, Vijverberg, 2008).

Literature on the effect of general education on entrepreneurial performance is fairly extensive,

but published articles on the effect of entrepreneurship-specific education on entrepreneurial

performance are extremely rare. Due to space limitations, we present the following brief

summary of what the literature tells us about the relationship between human assets and

entrepreneurial performance.

Summary General education is related positively to entrepreneurial performance, especially in the USA.

But empirical evidence relating entrepreneurship-specific education with performance is

extremely scarce and not convincing. The literature on creativity and expertise leads to the

conclusion that it takes 10 years to become an expert in any domain; which we infer also applies

to entrepreneurship. There is evidence that high-potential entrepreneurs perform better the

second time around; in contrast, the preponderance of evidence indicates that the performance of

self-employed individualsmainly solo entrepreneursdoes not improve from one new venture to the next.

PROPOSITIONS, HYPOTHESES, & CONTROLS

Effect of entrepreneurship education

Babson College, an undergraduate and MBA business school, introduced its first

entrepreneurship course in the mid-1960s. The program steadily grew so that by the mid-1980s

it had a cluster of three core elective entrepreneurship courses covering the entire entrepreneurial

process from nascent entrepreneurs through to harvest and beyond. The courses are

Entrepreneurship and New Ventures, Financing Entrepreneurial Ventures, and Managing

Growing Businesses. Two variations on those three courses were added to the core in recent

years. The core program was originally designed by a faculty member with extensive experience

as an entrepreneur. And its development over the past 25 years has had, and continues to have,

substantial input from faculty members, both full-time and adjunct, with considerable experience

as entrepreneurs.i

Babsons entrepreneurship program was ranked as the top U.S. program by Gartner and Vesper (1997) in their evaluation of entrepreneurship education programs; and both its undergraduate

and MBA programs have been ranked as top programs ever since. In 2011, the program has 17

full-time faculty members, 33 adjunct faculty, 10 shared faculty, and 11 staff. Babsons latest maxim Entrepreneurial Thought and Action captures the underlying teaching philosophy, which emphasizes experiential learning.

All Babson undergraduatesii and graduate students (almost entirely MBAs) take approximately

20 business courses to complete their degrees. Three-quarters of the alumni in the data set used

for the analyses in the present paper took one or more core elective entrepreneurship course, and

a quarter took none. One way of looking at this is that one elective core entrepreneurship course

amounts to only 5% of the total business courses taken by a student. Its important to keep this

3

in mind when considering whether taking core elective entrepreneurship courses affects the

performance of businesses started by alumni.

Some of the content of the core elective entrepreneurship courses builds on what students have

learned in other business courses. For example, writing a business plan, which is a central

feature of the Entrepreneurship and New Ventures course, requires among other things strategic

management, marketing, operations, accounting, and financial tools that students have learned in

basic business courses that they are required to take. In the Entrepreneurship and New Ventures

course those tools are applied to starting businesses from scratch rather than to ongoing

businesses. We expect that the biggest difference between the performance of businesses started

up and operated by alumni who took core elective entrepreneurship courses and those who took

none would be found in the topics that are unique to the core elective entrepreneurship courses.

Among those unique topics are finding and evaluating opportunities for a new business, writing a

business plan, financing a new business, and managing a new venture from birth through

adolescence to adulthood.

Teaching students to write business plans is ubiquitous in undergraduate and graduate

entrepreneurship programs because most entrepreneurship educators believe that a written

business plan increases the chances that a nascent business will result in an actual startup that

will survive and turn out to be a successful business, even though the theoretical underpinnings

for such a belief are flimsy and the empirical support is skimpy (Honig, 2004).iii

Babson was

one of the first business schools to embed writing business plans in its core elective

entrepreneurship program, and in 1984almost simultaneously with the University of Texas at Austinstarted the first business plan competition anywhere in the academic world. Writing business plans has been and still is a central component of Babsons core elective entrepreneurship program. Thus, just like our peers at in other entrepreneurship programs, we

believe in the following proposition.

P1: Training students to write business plans will make them better entrepreneurs both in

the startup process and subsequently in running their new businesses.

One of the main functions of a written business plan is to project revenue, costs, income, and

cash flows; and thereby estimate how much startup cash will needed to fund a new venture.

Thus we expect that alumni who were trained to write a business plan as students are more likely

to write better business plans than alumni who were not so trained; and because a business plan

is an important factor in raising money, we expect that alumni trained as students to write

business plans will be more successful in raising startup money. Not all alumni write business

plans before they embark on their new ventures; but those who were trained to write business

plans are more likely to write one than those who were not so trained; and even if they dont have a formal written plan, it is likely that their training in business planning will facilitate their

making financial projections and raising money. So we hypothesize the following:

H1a: Alumni who were trained to write business plans when they were students raise more

startup money than those who were not so trained.

A written business plan is a carefully documented road map that is expected to lead to success.

So is seems reasonable to hypothesize that alumni who have been schooled in the science of

4

writing business plans as students will be better at writing business plans as alumni than their

counterparts without formal training in writing business plans. Hence we propose the following

hypothesis:

H1b: Businesses started by alumni who as students were trained to write business plans

perform better than businesses started by alumni without such training.

(Our performance measures will be defined in the method section of this paper.)

In somewhat similar vein, another aspect that is unique to the core elective entrepreneurship

courses is the financing of startup businesses; it differs from the financing of mid-size and big

businesses, which is the main focus of required basic finance courses. For instance, cash-on-

hand is vital for a startup business, so income and cash flow statements focus on real-time rather

than accrual accounting; and most startup businesses do not own assets, so depreciation and

amortization are insignificant in many instances. Raising money for a startup venture is entirely

different from raising money for an established going concern. The initial startup money comes

from the 4Fs: Founders themselves, family, friends, and foolhardy strangersa topic that is never covered in required finance courses. In comparatively rare instances startup funding

comes from business angels, and in extremely rare cases it is provided by venture capitalists.

Those sources of funding are covered only briefly, sometimes not at all, in required finance

courses. In contrast, bank loans, which are extensively covered in required finance courses, are

seldom a source of funding for startup businesses. The financing of startup and young

businesses is covered extensively in Babsons core elective entrepreneurship courses, which in many instances are taught by instructors with substantial real-world experience as entrepreneurs,

informal investors, business angels, and venture capitalists. Hence, students who take core

elective entrepreneurship courses are well versed in the art and science of raising money for new

ventures. This leads to the following hypothesis:

H2a: Alumni who took core elective entrepreneurship courses as students raise more

startup money than those who were not so trained.

And because startup financing is covered in all the core elective entrepreneurship courses we

hypothesize H2b:

H2b: The more core elective entrepreneurship courses that alumni took when they were

students, the more startup money they raise.

The core elective entrepreneurship courses contain material on managing growing businesses,

and it is the principal topic of one of the courses. It leads to the following hypothesis:

H3: Businesses started by alumni who took core elective entrepreneurship courses as

students outperform businesses started by alumni who took none.

Effect of experience

Practical experience also is expected to be important in the startup process and subsequent

performance of new ventures. That experience could be entrepreneurial, industry specific, or

professional practice gained after graduation.

Founders who have previously founded a business have already been through the process of

raising money for a startup. Hence, it is likely that they will be more successful in raising money

when they start their next business than novice entrepreneurs starting their first business:

5

H4: Entrepreneurs who have prior startup experience raise more money than novice

entrepreneurs.iv

Know-how learned from starting and running a previous business should make entrepreneurs

more successful in running their next business. This is contrary to van der Sluis, van Praag and

Vijverbergs (2008) finding that self-employed individuals do not perform better the second time around. However, it is consistent with Stuart and Abettis (1990) and Gompers, Kovner, Lerner, and Scharfsteins (2010) findings that prior entrepreneurial experience correlated with the early performance of new high-potential ventures:

H5: Businesses started by alumni who have prior startup experience will subsequently

outperform businesses started by novice entrepreneurs.

Entrepreneurs with experience in the same industry as their new venture have know-how that

should help them to raise more startup money because potential investors are probably more

likely to invest in them than in nascent entrepreneurs with no relevant industry experience.

Chatterji (2009), for instance, found that within the medical device industry, former employees

of prominent companies tend to perform better across a number of metrics: time to first funding,

investment valuation, and time to product approval. Also entrepreneurs with relevant industry

experience have a network of potential investors from the same industry. For example,

according to the GEM studies, former work colleagues are a significant source of informal

investment for startup companies (Bygrave and Bosma, 2011). This leads to the following

hypothesis:

H6: The more experience that entrepreneurs have in the same industry as their startup, the

more startup money they raise.

According to Bates (1990) and Schoonhoven, Eisenhardt, and Lyman (1990), entrepreneurs with

more industry experience are less likely to terminate their new ventures because they have a

better understanding of the workings of the industry. And Bhid (2000) found that a substantial

fraction of the Inc. 500v got the idea for their new company while working at their prior

employer. It is a small step to propose that entrepreneurs with previous industry experience are

likely to be more successful. Hence we hypothesize as follows:

H7: The more prior experience that entrepreneurs have in the same industry as their

startup, the more successful is the subsequent performance of their business.

Practical experience after graduatingtermed professional ageshould make entrepreneurs better managers. Researchers into the relationship of age with self-employment have found a -shaped curvilinear relationship (Preisendorfer and Voss, 1990; van der Sluis, van Praag and

Vijverberg, 2008) analogous to the well-known concave age-income profile in human capital

research (Bruederl, J., Preisendorfer, P. and Ziegler, R., 1992). And other researchers into the

relationship between age and an individuals performance have found it to be curvilinear (e.g., Simonton, 1984; Simonton, 2000). So we propose a curvilinear -shaped relationship between professional age and entrepreneurial performance:

H8: There is a curvilinear -shaped relationship between entrepreneurs professional age and the subsequent performance of companies they start.

6

The more professional experience that entrepreneurs have, the more likely they are to spot

superior opportunities; also they are likely to have more extensive networks. Both factors should

enhance their ability to raise startup capital:

H9: The greater their professional age, the more startup money that entrepreneurs raise.

Controls

The above hypotheses are moderated by the age of the business and the gender and highest

degree of the alumni entrepreneurs. We did not include parentage as a control variable because

as van der Sluis, van Praag, Vijverberg (2008) found in their review, the offspring of

entrepreneurs are not themselves more likely to be successful entrepreneurs, as is sometimes

thought but seldom found.

Business Age. In general, the sales revenue, number of employees, and income of new ventures

increase with time; so we control for business age.

Gender. Many previous studies have demonstrated a noticeable difference between men and

women when it comes to entrepreneurship. For example, the Global Entrepreneurship Monitor,

GEM, reported that in high income countries men were 33% more likely than women to be

active entrepreneurs (Minniti, Arenius, and Langowitz, 2005); and (Reynolds, Carter, Gartner,

Greene, and Cox, 2002) found that in the U.S. men were twice as likely as women to be nascent

entrepreneurs. Lange, Mollov, Pearlmutter, Singh, and Bygrave (2007) in a study of businesses

started by entrepreneurs with bachelors or masters degrees in business found that those started by men had higher sales revenue and more employees than those started by women. Hence, we

control for gender.

Degree. Undergraduates are younger than MBA students, so at the time of graduation and for

several years afterward they have lower opportunity costs for becoming an entrepreneur

compared with being an employee simply because they are paid less than MBAs. Also recent

undergraduates generally have lower personal living costs. Thus it is conceivable that recent

undergraduates may start businesses that are more modest than ones started by recent MBAs.

Whats more, years of schooling are related positively with entrepreneurial performance (e.g., Robinson and Sexton, 1994); and MBAs have more total years in school than bachelors. Also most MBAs get work experience between graduating with a bachelors degree and enrolling in graduate school. Hence, although the core courses in the undergraduate and MBA program are

very similar, we differentiate alumni according to their highest Babson degrees.

METHOD

Survey

We emailed a 55-question surveyvi

to all 14,920 alumni for whom the school had an email

address. We followed up the initial email with two subsequent ones. The response rate was

27.4%. We culled the data set down to 3,775 alumni who graduated during the 25-year period,

1985 through 2009; 41.8% had bachelors degrees and 58.2% mastersalmost entirely MBAs with a few MSs; 72.3% had been full-time students, 27.7% part-time, of whom nearly all were

7

MBAs; 32.4% were women, 67.6% men; and their average age was 37. Sixty-seven percent

took at least one core entrepreneurship elective course at Babson and 33% took none.

Data set

For the analyses presented in this paper we examined 913 alumni (24.2% of the respondents)

who had founded or co-founded one or more independent businesses for which they worked full

time and were classified as entrepreneurs.vii

In all, the 913 alumni entrepreneurs had started a

total of 1,300 full-time businesses as some had started more than one.viii

To test our hypotheses

dealing with operating performance, we excluded companies with zero sales revenue or no

employees other than the entrepreneurs themselves. Amounts of money were adjusted for

inflation with the CPI to year-end 2009 dollars.

Dependent variables Our hypotheses deal with performance when starting up and subsequently operating a business.

At the startup phase, we measured the amount of money raised from pre-startup through the first

12 months of operating. We measured operating performance with sales revenue, number of

employees, and earnings before taxes (EBT),ix

at the time the questionnaire was being

completed. If the company was no longer operating as an independent entity, we asked what its

revenue, earnings before taxes, and number of employees were at its peak. We recognize that

there is a never-ending debate about how to measure the performance of private companies; for

example, Brush and Vanderwerf (1992). We would argue, however, that short of an independent

audit of a companys books, our measures are about as valid and reliable as can reasonably be expected with self-reported data. Income, measured by earnings before taxes, is the least reliable

of our dependent variables because all the companies in our dataset are private and how they

compute their EBT depends on many factors including their legal form (sole proprietorship, C

corporation, sub-chapter S, limited liability company, etc.), method of depreciating assets,

treatment of accruals, andperhaps most important of allfounders salaries and perquisites.

In our regression models we used the logarithms of each of the dependent variables because the

distributions of the raw data were skewed.

Independent variables for experience

Previously started a new business. A dummy variable indicated if a founder was a first-time

entrepreneur or had previously founded a full-time new venture.

Founders' combined years of experience in the same industry. We measured industry

experience by the total number of years that the founding team members combined had worked

in the same industry prior to founding their new venture.

Professional years experience between graduation and startup. This was the elapsed time from

graduation to starting a full-time business.

(Professional years experience). This term was included in the regression models to test for

curvilinearity.

Independent variables for entrepreneurship education

Wrote student business plan at Babson. This was a dummy variable indicating whether or not

alumni had written a business plan when they were students.

8

1 core entrepreneurship courses taken. This was a dummy variable indicating alumni who took

one core elective entrepreneurship course when they were Babson students.

2 core entrepreneurship courses taken. This was a dummy variable indicating alumni who took

two core elective entrepreneurship courses when they were Babson students.

3 core entrepreneurship courses taken. This was a dummy variable indicating alumni who took three or more core elective entrepreneurship courses when they were Babson students.

Control variables Gender. This was a dummy variable, Female = 0, Male = 1.

Babson degree. This was a dummy variable, BS = 0, Masters =1.

Business Age. This was the age of the company in years; the distribution was skewed so we

used the logarithm in the regression models.

RESULTS

Descriptive statistics Table 1 shows the descriptive statistics for the raw values (not the logarithms) of the variables in

our regression models. Mean annual revenue was $5.5 million (median $500,000); mean

earnings before tax was $0.85 million (median $0.12 million); mean number of employees 31

(median 5); mean sales per employee was $0.29 million (median $0.13 million); mean startup

money raised was $1.5 million (median $0.11 million). The average age of the companies was

5.4 years (median 4 years). 89% of the entrepreneurs were male, 11% female; 41% had BS

degrees and 59% had masters (almost entirely MBAs); 38% had previous startup experience,

62% had none; founders mean combined experience in the same industry as the startup was 16.7 years (median 10 years); alumnis mean professional experience was 6.0 years (median 5 years); 75% of the entrepreneurs had written business plans as Babson students; 24% of the

entrepreneurs took no core elective entrepreneurship courses when they were Babson students,

23% took one, 27% took two, and 26% took three or more.

9

TABLE 1

Descriptive statistics

Mean Median Sales $5,457,257 $500,000

Number of Employees 31.0 5.00

EBT $852,202 $123,743

Sales per Employee $285,796 $125,000

Startup Money Raised $1,465,987 $113,572

Gender: F = 0, M = 1 0.89

Degree: B = 0, M = 1 0.59

Business Age (Years) 5.44 4.00

Founders' Previous Startup Experience: No=0, Yes=1 0.38

Founders' Combined Experience in Same Industry, Years 16.66 10.00

Professional Experience, Years 6.03 5.00

(Professional Experience) 69.67 25.00

Wrote Student Business Plan: No=0, Yes=1 0.75

One Entrepreneurship Course: No=0, Yes=1 0.23

Two Entrepreneurship Courses: No=0, Yes=1 0.27

Three or more Entrepreneurship Courses: No=0, Yes=1 0.26

Regression model Startup process. The regression model for the amount of money raised from conception to the

end of the first 12 months of operating as a full-time business was highly significant(p=1.4x10-7)

,

Table 2. The logarithm of startup money raised correlated positively with the entrepreneur

having previously started a business (p=0.0004), founders combined experience in the same industry (p=0.007), professional experience (p=0.02), taking one core elective entrepreneurship

course (p=0.012), taking two core elective entrepreneurship courses (p=0.011), and taking three

or more core elective entrepreneurship courses (p=0.003); and correlated negatively with

professional experience squared (p=0.1). It did not correlate with having written a business plan

as a student. The control variables, gender, and Babson degree (bachelors or masters) were not significant.

10

TABLE 2

Regression model for startup money raised

B Sig.(Constant) 10.029 .000

Gender, Female = 0, Male = 1 .445 .150

Babson degree: BS = 0, Masters =1 -.134 .573

.838 .000

.015 .007

.109 .020

(Professional years experience) -.004 .096

Wrote student business plan at Babson, Dummy -.361 .216

.883 .012

.886 .011

1.102 .003

Number of observations 473

F 5.403

Significance 1.4x10-7

R-square .104

Adjusted R-square .085

1 core entrepreneurship courses taken, Dummy

2 core entrepreneurship courses taken, Dummy

3 core entrepreneurship courses taken, Dummy

Ln(Startup

Money Raised)

Previously started a new business, Dummy

Founders' combined years of experience in the same industry

Professional years experience between graduation and startup

Operating performance. All three regression models for the operating performance were

significant, Table 3: ln(sales revenue), p=5.2x10-10

; ln(number of employees), p=1.1x10-6

; and

ln(EBT), p=0.006. One control variable, ln(age), was highly significant in all three models.

Another control variable, gender, was significant in the ln(sales revenue) model (p=0.04) and the

ln(number of employees) model (p=0.054), but was not significant in the ln(EBT) model. The

remaining control variable, Babson degree, was not significant in any of the models.

11

TABLE 3

Regression models for operating performance

B Sig. B Sig. B Sig.(Constant) 10.876 .000 .471 .210 10.301 .000

Gender, Female = 0, Male - 1 .757 .041 .494 .054 .416 .297

Babson degree: BS = 0, Masters =1 .093 .712 .045 .797 .093 .751

Log Business Age .904 .000 .458 .000 .552 .002

.388 .119 .514 .003 -.053 .854

.007 .209 .006 .163 .010 .175

.196 .000 .072 .039 .160 .005

(Professional years experience) -.010 .001 -.005 .020 -.006 .096

Wrote student business plan at Babson, Dummy .231 .461 -.049 .820 -.122 .730

.505 .157 .490 .049 .294 .462

-.075 .842 .298 .247 .049 .909

.013 .973 .233 .382 .194 .661

Number of observations 270 282 215

F 6.781 4.750 2.506

Significance 5.2x10-10

1.1x10-6 .006

R-square .224 .162 .119

Adjusted R-square .191 .128 .072

2 core entrepreneurship courses taken, Dummy

3 core entrepreneurship courses taken, Dummy

Ln(Sales

Revenue)

Ln(Number

Employees)

Ln(EBT)

Professional years experience between graduation and startup

Founders' combined years of experience in the same industry

Previously started a new business, Dummy

1 core entrepreneurship courses taken, Dummy

Having previously started a business was significant in only one of the models, ln(number of

employees), p=0.003. Founders combined experience in the same industry as the startup was not significant in any of the three models. Professional experience was significant in all three

models: ln(sales revenue), p=0.0001; ln(number of employees), p=0.04; and ln(EBT), p=.005.

Professional experience squared correlated negatively in all three models: ln(sales revenue),

p=0.001; ln(number of employees), p=0.02; and ln(EBT), p=0.096. Having written a business

plan as a student was not significant in any of the models; taking one, two, or three or more core

elective entrepreneurship courses was not significant in any of the models with one exception

that we discuss in the next section.

Hypotheses Entrepreneurship education correlated with raising money during the startup process, Table 4.

Specifically, the amount of startup money increased with taking core elective entrepreneurship

courses, but was not affected by whether or not an alumnus wrote a business plan as a student.

However, entrepreneurship education did not correlate with the subsequent operating

performance of a new venture except that taking one core elective entrepreneurship course

correlated positively with the number of employees (p=0.049); this might be a spurious

correlation because if taking one course was significant then taking two or better yet three of

more courses should have been even more significant, whereas neither came close to being

significant. We ran a regression (not exhibited in this paper) of ln(sales per employee). The

result was similar to the ln(sales revenue) regression except that taking one entrepreneurship

course was not significant nor were taking two or three or more courses. Thus we think that the

12

correlation between taking one entrepreneurship course and number of employees is probably a

statistical anomaly.

TABLE 4

Results of hypotheses

Startup process Operating Performance

EXPERIENCE Startup money

raised Sales revenue Number of employees EBT

Previously started a new business H4 ACCEPT H5sr REJECT H5emp ACCEPT H5EBT REJECT Founders' combined years experience in the same industry

H6 ACCEPT H7sr REJECT H7emp REJECT H7EBT REJECT Professional years experience between graduation and startup

H9 ACCEPT1 H8sr ACCEPT1 H8emp

ACCEPT1 H8EBT ACCEPT

1 (P

13

with 0.88 for taking one core elective entrepreneurship course. Simplistically put, real-world

experience is twice as effective as taking one core elective entrepreneurship course with respect

to raising startup money.

When it comes to the subsequent operating performance of new businesses, professional

experience is significant in all three models; while entrepreneurship educationtaking one or more core elective entrepreneurship coursesis significant in only one of the models and that correlation might be a statistical quirk. As we mentioned earlier, one core elective

entrepreneurship course is approximately 5% of all the business courses that students take, so

perhaps it is not surprising that it appears to have little influence on the operating performance

post-startup. An alternative explanation might be found in Lazears (2004) jack-of-all-trades theory of entrepreneurship, which reasoned that general skills are more important than special

skills for entrepreneurs; he supported his argument with evidence that alumni of Stanford

University Business School were more likely to be entrepreneurs if they had taken a more

diversified set of courses than a specialized set when they were students. Unfortunately, Lazear

did not study the relationship between the diversity of courses and entrepreneurial performance,

so we can only surmise that diversity of courses taken might be related to performance. If that is

the case, it could be argued that the post-startup performance of alumni businesses is not related

to how many core elective entrepreneurship courses alumni took as students; instead, it is related

to the diversity of all their elective business courses.

One explanation of why professional age is related to performance is that practical experience

makes entrepreneurs better managers of their own businesses. Another explanation is that

seasoned alumni are more likely to find better opportunities for new ventures than recent

graduates. A business founded on a better opportunity and managed by an entrepreneur with

considerable professional experience is likely to be a superior performer. The optimum

professional age appears to fall in the region of 10 or so years. Interestingly, a study of

university scientists who were granted PhDs between 1974 and 1984 found that 10 years was the

peak professional age for founding technology ventures (Ding and Choi, 2008). We dont want to make too much of our finding that the peak of the performance curve is for companies started

by alumni with about 10 years of professional experience, but we cant resist pointing out that it agrees nicely with the time that it takes to become an expert (e.g., Simon and Case, 1973).

Our finding that professional age is correlated with performance both when starting up and

operating a business seems to conflict with Cooper, Gimeno-Gascon, and Woos (1994) finding that management know-how had only a weak direct effect on the performance of a new venture.

Cooper et al. (1994) speculated that the effect of management know-how on venture

performance comes from the enhanced ability of firms rich in management know-how to raise

initial financial capital for their business, but has no significant effect on subsequent

performance. We think it is counterintuitive to believe that prior management experience does

not enhance operating performance; and it appears that venture capitalists agree: otherwise they

would not team up neophyte entrepreneurs with seasoned managers, e.g., Eric Schmidt with

Larry Page and Sergey Brin (Google); Armas Markkula, Jr. with Steve Jobs and Steve Wozniak

(Apple); and Meg Whitman with Pierre Omidyar (eBay).

14

Cooper et al. (1994), however, found that industry specific know-how was a strong predictor of

subsequent performance whereas we found that it only affected the amount of startup money

raised but not subsequent operating performance. The explanation might lie in our different

research methods. Cooper et al. (1994) used a dummy variable for performance, a dummy

variable for management experience, and an interval scale for measuring industry similarity,

whereas we used ratio variables for performance, prior experience in the same industry, and

professional experience. Also Cooper et al. (1994) looked at performance of three- year-old

companies, whereas the average age of the companies in our sample was 5.4 years; which might

be a possible reason for the difference between our findings, because the value of prior industry

experience depreciates with time, whereas staying abreast of current developments in the

industryregardless of prior industry knowledgeappreciates (Baron, 2006). But we confess that our finding that industry experience does not affect future performance seems to be what else counterintuitive and merits more research. Perhaps a clue to another possible explanation might be discovered in Kirschenhofer and Lechners (2005) empirical study of habitual entrepreneurs, which found among other things that depth of industry experience had a negative influence on performance while breadth of experience had a positive influence. It seems

therefore that a variety of experiences, which make the entrepreneur a generalist, prepares an

entrepreneur better for her/his endeavors than a deep but specialized experiencea finding that is compatible with Lazears (2004) theory.

A few researchers have used sales growth rate as a measure of performance (e.g., Bailey, 1986;

Ensley, Pearce, and Hmieleski, 2006.) We too set up a regression model with ln(latest sales

revenue/age of company) and dropped ln(age) as a control variable. It produced a regression

model (not exhibited in this paper) in which the significant B-coefficients for professional

experience and professional experience squared were almost identical to those for the ln(sales

revenue) model shown in Table 3. Bailey (1986) postulated that companies run by owners

whose behavior is predominantly entrepreneurial grow faster than those run by owners whose

behavior is predominantly managerial. From which it could be inferred that businesses run by

alumni who take entrepreneurship courses should grow faster than those run by alumni who take

none. However, we found no significant difference between the two groups; which, if Baileys postulate is correct, implies that alumni who took entrepreneurship courses ran their businesses

no more entrepreneurially than their counterparts who took none.

There have been very few studies of entrepreneurship program alumni, and they deal almost

entirely with intentions to be an entrepreneur (e.g., review by Pittaway and Cope, 2007). Studies

of startup and post-startup performance of businesses founded by alumni of entrepreneurship

programs are extremely rare and more often than not are methodologically flawed, so it is not

possible to make a direct comparison of our findings with previous research. The research that

comes closest to ours is Charney and Libecaps (2002) study of graduates of the University of Arizona Business School. They examined the careers of alumni who as students had taken an

entrepreneurship concentration and those who had not. They found that entrepreneurship

graduates had higher personal income and higher personal assets. Among other things, they

found that the sales growth of small companies employing entrepreneurship graduates was

higher than those without entrepreneurship graduates. Unfortunately, they did not isolate small

businesses that were started by Arizona entrepreneurship graduates from companies where they

were only employees, so we cannot compare their results with ours.

15

CONCLUSIONS AND IMPLICATIONS

The most striking finding is that professional age, regardless of whether or not it included

entrepreneurship experience, had the strongest correlation with both startup and operating

performance. Prior startup experience correlated only with startup performance but not with

operating performance. This suggests that Schumpeter (1934) was correct to claim that

entrepreneurship is not a profession in the classic sense such as accounting, engineering,

medicine, and law are, because if it were, then operating performance should improve with

entrepreneurial experience, but we found that it didnt. However, at the startup stage both entrepreneurship education and prior entrepreneurial experience correlated with amount of

startup money raised. We believe it indicates that parts of the startup process are a discipline that

can be learned; which is limited support for Druckers claim.

From a students perspective, there is a trade-off between the fees for taking core elective entrepreneurship courses and the cost of getting real-world practical experience or as some put it

(Robinson and Sexton, 1994) an education from the school of hard knocks. According to Jeans (1884), Thomas Carlyle wrote, Experience is the best schoolmaster, only the school fees are rather heavy.x For instance, experience gained from starting a new venture that turns out to be a mediocrity or a failure is likely to be expensive for an entrepreneur both in terms of personal

investment in the business and opportunity costs.

Our study indicates that taking core elective entrepreneurship courses is more valuable than

learning how to write a student business plan, because we found no significant relationship

between being trained to write a business plan as a student and the amount of startup money

raised or the post-startup performance. When our finding is considered along with other findings

that businesses started with written business plans do not outperform ones started without them

(Honig, 2004; Honig and Karlsson, 2004, Lange, Mollov, Pearlmutter, Singh, and Bygrave,

2007), we wonder why teaching students to write business plans is emphasized so much in

entrepreneurship education. As Honig (2004) observed, neither teaching business plans nor

writing business plans is sufficiently justified by empirical or theoretical literature. It is a topic

that urgently requires much more attention from researchers.

Our paper makes the following contributions to entrepreneurship research. It is an extensive

study of the effect of entrepreneurship education on the entrepreneurial performance of a

relatively large sample of Babson College alumni. It looks at the effect of taking one, two, or

three or more core entrepreneurship elective courses; and it examines the effect of writing a

student business plan. It also examines the correlation between performance and practical

experience measured by having previously started a business, by having worked in the same

industry as the startup, and by professional age, which is the number of years from graduation to

starting up a new venture. It compares the relative effects of formal education and practical

experience on performance. In so doing, it addresses the pleas of policy makers and others for

more studies of the outcomes of an entrepreneurship education.

16

Here are some implications for students, educators, policy makers, and researchers based on the

findings reported in this paper and our previous paper on entrepreneurial intentions (Lange et al.,

2011)xi

:

Students. Core elective entrepreneurship courses will increase your intentions to become an

entrepreneur. And they will enhance the amount of startup money that you raise if you actually

fulfill those intentions and become an entrepreneur. Taking more than one core course will

strengthen your intentions to become an entrepreneur and will marginally enhance the amount of

startup capital that you raise. Writing a student business plan will also strengthen your

entrepreneurial intentions. But neither taking core elective entrepreneurship courses nor writing

a student business plan will enhance the operating performance of your business. Experience in

the real world before you start a new venture will enhance your performance both when you are

in the startup process and when you are operating your business.

Educators. Specialized entrepreneurship education increases students intentions to become entrepreneurs and enhances their ability to raise funds when starting their businesses, but does

not improve the subsequent operating performance. Thus, we think the emphasis of

undergraduate and MBA entrepreneurship courses should be on the pre-startup and startup

process. While it is useful to include writing a business plan in the curriculum, it should not be

the main focus because it is not the most effective pedagogical tool for enhancing either

entrepreneurial intentions or entrepreneurial performance. Since our results show that real-

world experience trumps entrepreneurship education, we think that experiential learning should

be an overarching principle in entrepreneurship pedagogy.

Policy makers and supporters of entrepreneurship programs. Specialized entrepreneurship

education increases students entrepreneurial intentions, and the effect is long lasting. It also enhances alumnis effectiveness in raising startup capital and the effect is also long lasting. We think it is a mistake to evaluate the effectiveness of specialized entrepreneurship education by

measuring the number of new ventures started by alumni at graduation or soon afterward,

because our analysis shows that the best performing new ventures are started by alumni

approximately 10 years after graduation.

Researchers. We hope that other schools will study the effectiveness of their entrepreneurship

programs so that we can see what can be generalized. An ideal study would compare businesses started by alumni from all disciplines (science, humanities, engineering, business, art,

music, etc.) who took elective entrepreneurship courses with those who took none. Our finding

about real-world experience needs more study; particularly, our finding that the amount of prior

experience in the same industry does not improve the long-term performance of a business. And

as we and othersespecially Honig (2004)have pleaded, we need more studies into the effectiveness of a written business plan both as a teaching tool and in the actual performance of

new ventures.

17

REFERENCES

Bailey, J. E. (1986). Learning styles of successful entrepreneurs. In Ronstadt, R., Hornaday, J.

A., Peterson R., and Vesper, K. H. (Eds.), Frontiers of Entrepreneurship Research 1986.

Wellesley, MA: Babson College. pp 199-210.

Baron, R. A. (2006). Opportunity recognition as pattern recognition: how entrepreneurs connect the dots to identify new business opportunities. Academy of Management Perspectives, 20, 10419.

Bates, T. (1990) Entrepreneur human capital inputs and small business longevity, Review of

Economic Statistics, 72(4), pp. 551 559. Bhid, A., 2000. The Origin and Evolution of New Businesses. Oxford University Press, Oxford.

Bruederl, J., Preisendorfer, P. and Ziegler, R. (1992) Survival chances of newly founded business

organizations. American Sociological Review 57(2): 227242. Brush, C.G. & VanderWerf, P. 1992. A Comparison of Methods and Sources for Obtaining

Estimates of New Venture Performance. Journal of Business Venturing. 7:2, pp. 157-170

Bygrave, W. (1994). The Portable MBA in Entrepreneurship. NY: John Wiley & Sons, Inc.

Bygrave, W. and Bosma, N. (2011). Investor Altruism: Financial Returns from Informal Investments in Businesses Owned by Relatives, Friends, and Strangers. Upcoming in

The Dynamics of Entrepreneurial Activity, Minniti, M. ed. Oxford University Press,

2011.

Charney, A.H. and Libecap, G. D. (2002). The contribution of entrepreneurship education: An

analysis of the Berger program. International Journal of Entrepreneurship Education

1(3).

Chatterji, A., 2009. Spawned with a silver spoon? Entrepreneurial performance and innovation in

the medical device industry. Strategic Management Journal 30, 185206. Cooper, A., Gimeno-Gascon, J. and Woo, C. (1994) Initial human and financial capital as

predictors of new venture performance. Journal of Business Venturing 9(5): 371395. Ding, W. and Choi, E. (2008). Divergent paths or stepping stones: A comparison of scientists

advising and founding activities. Working Paper Series, Institute of Research on Labor

and Employment, University of California, Berkeley.

Dosi, G., 1988, Sources, Procedures, and Microeconomic Effects of Innovation, Journal of Economic Literature, 26, 11201171.

Drucker, P.F. (1985). Innovation and entrepreneurship. New York: Harper and Row.

Ensley, M. D., Pearce, C. L., and Hmieleski, K. M. (2006). The moderating effect of

environmental dynamism on the relationship between entrepreneur leadership behavior

and new venture performance. Journal of Business Venturing, 21 pp. 243263. Gompers, P., Kovner, A., Lerner, J., and Scharfstein, D. (2010). Performance persistence in

entrepreneurship. Journal of Financial Economics, 96 (1), 1832. Honig, B. (2004). Entrepreneurship Education: Toward a Model of Contingency-Based Business

Planning. Academy of Management Learning and Education, 2004, Vol. 3, No. 3, 258273.

Honig, B. and Karlsson, T. (2004) Institutional forces and the written business plan, Journal of

Management, 30(1), pp. 29 48. Jeans, W. T. (1884). The Creators of the Age of Steel. London: Chapman and Hall

Jobs, S. Business Week, February 6, 2006. p. 66.

18

Kirschenhofer, F. and Lechner, C. (2005). Long-term performance of habitual entrepreneurs which direction to go? Workshop on Firm Exit and Serial Entrepreneurship at the Max

Planck Institute (Jena, Germany) at 13-14, January 2006.

Lange , J., Marram, E., Pencheva, S., Tan, Y., and Bygrave, W. (2010). Entrepreneurs and Non-

Entrepreneurs: Careers of 3,821 Babson Alumni. Working paper.

Lange, J., Marram, E., Solai Jawahar, A., Yong, W., and Bygrave, W. (2011). Does an

entrepreneurship education have lasting value? A study of careers of 3,775 alumni.

Frontiers of Entrepreneurship Research 2011, 31: 210-225.

Lange, J., Mollov, A., Pearlmutter, M., Singh, S., and Bygrave, W. (2007). Pre-start-up Formal

Business Plans and Post-start-up Performance: A Study of 116 New Ventures. Venture

Capital, Vol. 9, No. 4, 237 256. Babson College, Wellesley MA, USA. Lazear, E. (2004) Balanced skills and entrepreneurship. American Economic Review 94(2):208

211.

Lehman, H. (1953). Age of Achievement. Princeton, N.J.: Princeton University Press.

Questions, in R.J. Sternberg and R.A. Finke, eds., The Nature of Insight, Cambridge, MA: MIT Press, 332.

Minniti, M., Arenius, P., & Langowitz, N. (2005). 2004 Report on women and entrepreneurship.

In Global Entrepreneurship Monitor. Wellesley, MA: The Center for Womens Leadership at Babson College.

Minniti, M. and Bygrave, W. 2001. A Dynamic Model of Entrepreneurial Learning.

Entrepreneurship: Theory and Practice, 25:3, 5-16.

National Council for Graduate Entrepreneurship (NCGE) (2004). Making the journey from

student to entrepreneur: A review of the existing research into graduate

entrepreneurship, National Council for Graduate Entrepreneurship Report, URL (April 2006): http://www.ncge.org.uk/review.php

Nystrm, H. (1993), Creativity and entrepreneurship, Creativity and Innovation Management, Vol. 2 No. 4, pp. 237-42.

Pittaway, L. and Cope, J. (2007). Entrepreneurship education: A systematic review of the

evidence. International Small Business Journal, 2007 25: 479.

Reynolds, P., Carter, N., Gartner, W., Greene, P., & Cox, L. (2002). The entrepreneur next door,

characteristics of individuals starting companies in America. Kansas City, MO: Ewing

Marion Kauffman Foundation.

Robinson, P. and Sexton, E. (1994) The effect of education and experience on self-employment

success. Journal of Business Venturing 9(2): 141156. Schoonhoven, C. B., Eisenhardt, K. M. and Lyman, K. (1990) Speeding products to market:

waiting time to first product introduction in new firms, Administrative Science Quarterly,

35, pp. 177 207. Schumpeter, J. A. (1934, 16

th printing, 2012). The theory of economic development. Cambridge,

MA: Harvard University. P. 78.

Simon, H. A. and Chase, W. G., 1973, Skill in Chess, American Scientist, 61, 394403. Simonton, D. K. (1984). Creative productivity and age: A mathematical model based on a two-

step cognitive process. Volume 4, Issue 1, March 1984, Pages 77-111.

Simonton, D. K. (2000). Creativity: Cognitive, personal, developmental, and social aspects,

American Psychologist 55:1, 151-158.

19

Starr, J. and Bygrave, W. (1991). The assets and liabilities of prior start-up experience: An

exploratory study of multiple venture entrepreneurs. In Churchill, N. C. et al. (Eds.),

Frontiers of Entrepreneurship Research 1991. Wellesley, MA: Babson College. pp. 211-

227.

Stuart, R. W. and Abetti, P. A. (1990). Impact of entrepreneurial and management experience on

early performance. Journal of Business Venturing, Volume 5, Issue 3, May 1990,Pages

151-162.

Van der Sluis, J., Van Praag, M., and Vijverberg, W. (2008). Education and Entrepreneurship

Selection and Performance: A Review of the Empirical Literature, Journal of Economic

Surveys Vol. 22, No. 5, pp. 795841. Weick, K. (1996) Drop your tools: an allegory for organizational studies. Administrative Science

Quarterly 41: 301314.

20

ENDNOTES

i Babsons entrepreneurship program also has specialty elective courses including family business, management buy-outs and buy-ins, franchising, corporate entrepreneurship, sustainability, and venture capital. ii Babsons undergraduate education blends liberal arts and business courses.

iii Honigs paper is a critique of business planning and written business plans in entrepreneurship education.

iv This hypothesis is virtually identical to Starr and Bygraves (1991) Proposition 2 for multiple venture

entrepreneurs.

v The Inc. 500 is an annual list of the 500 fastest-growing private companies in the U.S.; introduced in 1982.

vi The complete questionnaire is available from the lead author.

vii

We included only full-time entrepreneurs in our analyses. After all, alumni who have full-time jobs as employees but also own a part-time business as a sideline have not risked their careers, can rely on a steady salary for their full-

time jobs, and probably have not put much of their personal net worth on the line for their part-time business. viii

See Lange et al. (2010) for details. ix Table 1 in Van der Sluis, Van Praag, and Vijverbergs (2008) summarizes performance measures used in 117

studies of the effect of general education on entrepreneurship. Revenue growth was used 9 times, profit 4 times, and

jobs created only twice. x Jeans was writing about a costly commercial mistake made by a youthful Sir Henry Bessemer, the great inventor-

entrepreneur. Two decades later he invented the Bessemer process for converting iron to steel; it made him very

wealthy, and his investors earned 81 times their original capital. xi Our previous paper (Lange et al., 2011) deals with entrepreneurial intentions (in contrast this papers focus on

performance).

REFERENCES

Bailey, J. E. (1986). Learning styles of successful entrepreneurs. In Ronstadt, R., Hornaday, J.

A., Peterson R., and Vesper, K. H. (Eds.), Frontiers of Entrepreneurship Research 1986.

Wellesley, MA: Babson College. pp 199-210.

Baron, R. A. (2006). Opportunity recognition as pattern recognition: how entrepreneurs connect the dots to identify new business opportunities. Academy of Management Perspectives, 20, 10419.

Bates, T. (1990) Entrepreneur human capital inputs and small business longevity, Review of

Economic Statistics, 72(4), pp. 551 559. Bhid, A., 2000. The Origin and Evolution of New Businesses. Oxford University Press, Oxford.

Bruederl, J., Preisendorfer, P. and Ziegler, R. (1992) Survival chances of newly founded business

organizations. American Sociological Review 57(2): 227242. Brush, C.G. & VanderWerf, P. 1992. A Comparison of Methods and Sources for Obtaining

Estimates of New Venture Performance. Journal of Business Venturing. 7:2, pp. 157-170

21

Bygrave, W. (1994). The Portable MBA in Entrepreneurship. NY: John Wiley & Sons, Inc.

Bygrave, W. and Bosma, N. (2011). Investor Altruism: Financial Returns from Informal Investments in Businesses Owned by Relatives, Friends, and Strangers. Upcoming in

The Dynamics of Entrepreneurial Activity, Minniti, M. ed. Oxford University Press,

2011.

Charney, A.H. and Libecap, G. D. (2002). The contribution of entrepreneurship education: An

analysis of the Berger program. International Journal of Entrepreneurship Education

1(3).

Chatterji, A., 2009. Spawned with a silver spoon? Entrepreneurial performance and innovation in

the medical device industry. Strategic Management Journal 30, 185206. Cooper, A., Gimeno-Gascon, J. and Woo, C. (1994) Initial human and financial capital as

predictors of new venture performance. Journal of Business Venturing 9(5): 371395. Ding, W. and Choi, E. (2008). Divergent paths or stepping stones: A comparison of scientists

advising and founding activities. Working Paper Series, Institute of Research on Labor

and Employment, University of California, Berkeley.

Dosi, G., 1988, Sources, Procedures, and Microeconomic Effects of Innovation, Journal of Economic Literature, 26, 11201171.

Drucker, P.F. (1985). Innovation and entrepreneurship. New York: Harper and Row.

Ensley, M. D., Pearce, C. L., and Hmieleski, K. M. (2006). The moderating effect of

environmental dynamism on the relationship between entrepreneur leadership behavior

and new venture performance. Journal of Business Venturing, 21 pp. 243263. Gompers, P., Kovner, A., Lerner, J., and Scharfstein, D. (2010). Performance persistence in

entrepreneurship. Journal of Financial Economics, 96 (1), 1832. Honig, B. (2004). Entrepreneurship Education: Toward a Model of Contingency-Based Business

Planning. Academy of Management Learning and Education, 2004, Vol. 3, No. 3, 258273.

Honig, B. and Karlsson, T. (2004) Institutional forces and the written business plan, Journal of

Management, 30(1), pp. 29 48. Jeans, W. T. (1884). The Creators of the Age of Steel. London: Chapman and Hall

Jobs, S. Business Week, February 6, 2006. p. 66.

Kirschenhofer, F. and Lechner, C. (2005). Long-term performance of habitual entrepreneurs which direction to go? Workshop on Firm Exit and Serial Entrepreneurship at the Max

Planck Institute (Jena, Germany) at 13-14, January 2006.

Lange , J., Marram, E., Pencheva, S., Tan, Y., and Bygrave, W. (2010). Entrepreneurs and Non-

Entrepreneurs: Careers of 3,821 Babson Alumni. Working paper.

Lange, J., Marram, E., Solai Jawahar, A., Yong, W., and Bygrave, W. (2011). Does an

entrepreneurship education have lasting value? A study of careers of 3,775 alumni.

Presented at the Babson College Entrepreneurship Research Conference, Syracuse

University.

Lange, J., Mollov, A., Pearlmutter, M., Singh, S., and Bygrave, W. (2007). Pre-start-up Formal

Business Plans and Post-start-up Performance: A Study of 116 New Ventures. Venture

Capital, Vol. 9, No. 4, 237 256. Babson College, Wellesley MA, USA. Lazear, E. (2004) Balanced skills and entrepreneurship. American Economic Review 94(2):208

211.

22

Lehman, H. (1953). Age of Achievement. Princeton, N.J.: Princeton University Press.

Questions, in R.J. Sternberg and R.A. Finke, eds., The Nature of Insight, Cambridge, MA: MIT Press, 332.

Minniti, M., Arenius, P., & Langowitz, N. (2005). 2004 Report on women and entrepreneurship.

In Global Entrepreneurship Monitor. Wellesley, MA: The Center for Womens Leadership at Babson College.

Minniti, M. and Bygrave, W. 2001. A Dynamic Model of Entrepreneurial Learning.

Entrepreneurship: Theory and Practice, 25:3, 5-16.

National Council for Graduate Entrepreneurship (NCGE) (2004). Making the journey from

student to entrepreneur: A review of the existing research into graduate

entrepreneurship, National Council for Graduate Entrepreneurship Report, URL (April 2006): http://www.ncge.org.uk/review.php

Nystrm, H. (1993), Creativity and entrepreneurship, Creativity and Innovation Management, Vol. 2 No. 4, pp. 237-42.

Pittaway, L. and Cope, J. (2007). Entrepreneurship education: A systematic review of the

evidence. International Small Business Journal, 2007 25: 479.

Reynolds, P., Carter, N., Gartner, W., Greene, P., & Cox, L. (2002). The entrepreneur next door,

characteristics of individuals starting companies in America. Kansas City, MO: Ewing

Marion Kauffman Foundation.

Robinson, P. and Sexton, E. (1994) The effect of education and experience on self-employment

success. Journal of Business Venturing 9(2): 141156. Schoonhoven, C. B., Eisenhardt, K. M. and Lyman, K. (1990) Speeding products to market:

waiting time to first product introduction in new firms, Administrative Science Quarterly,

35, pp. 177 207. Schumpeter, J. A. (1934, 16

th printing, 2012). The theory of economic development. Cambridge,

MA: Harvard University. P. 78.

Simon, H. A. and Chase, W. G., 1973, Skill in Chess, American Scientist, 61, 394403. Simonton, D. K. (1984). Creative productivity and age: A mathematical model based on a two-

step cognitive process. Volume 4, Issue 1, March 1984, Pages 77-111.

Simonton, D. K. (2000). Creativity: Cognitive, personal, developmental, and social aspects,

American Psychologist 55:1, 151-158.

Starr, J. and Bygrave, W. (1991). The assets and liabilities of prior start-up experience: An

exploratory study of multiple venture entrepreneurs. In Churchill, N. C. et al. (Eds.),

Frontiers of Entrepreneurship Research 1991. Wellesley, MA: Babson College. pp. 211-

227.

Stuart, R. W. and Abetti, P. A. (1990). Impact of entrepreneurial and management experience on

early performance. Journal of Business Venturing, Volume 5, Issue 3, May 1990,Pages

151-162.

Van der Sluis, J., Van Praag, M., and Vijverberg, W. (2008). Education and Entrepreneurship

Selection and Performance: A Review of the Empirical Literature, Journal of Economic

Surveys Vol. 22, No. 5, pp. 795841. Weick, K. (1996) Drop your tools: an allegory for organizational studies. Administrative Science

Quarterly 41: 301314.