Student Entrepreneurship Across the Globe: A Look … Entrepreneurship Across the Globe: A Look at Intentions and Activities International Report of the GUESSS Project 2013/2014 Philipp

Student Entrepreneurship Across the Globe: A Look at Intentions and Activities

International Report of the GUESSS Project 2013/2014

Philipp Sieger, Urs Fueglistaller, Thomas Zellweger

GUESSS 2013/2014 was generously supported by Ernst & Young (EY) as the international project partner.

We cordially thank EY for their support. Without it, GUESSS in its current form would not have been possible.

www.ey.com

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GUESSS International Report 2013/2014

Citation: Sieger, P., Fueglistaller, U. & Zellweger, T. (2014). Student Entrepreneurship Across the Globe: A Look at Intentions and Activities. St.Gallen: Swiss Research Institute of Small

Business and Entrepreneurship at the University of St.Gallen (KMU-HSG).

KMU-HSG Swiss Research Institute of Small Business and Entrepreneurship at the University of St.Gallen Dufourstrasse 40a CH - 9000 St. Gallen +41 (0) 71 224 71 00 (Telephone) +41 (0) 71 224 71 01 (Fax) www.kmu.unisg.ch

The Swiss Research Institute of Small Business and Entrepreneurship at the University of St.Gallen (KMU-HSG) is dedicated to small- and medium-sized enterprises and entrepreneurship for decades. The main activities are research, teaching, and consulting and services (executive education) in the context of entrepreneurship, SME, and family businesses.

CFB-HSG Center for Family Business at the University of St.Gallen Dufourstrasse 40a CH - 9000 St. Gallen +41 (0) 71 224 71 00 (Telephone) +41 (0) 71 224 71 01 (Fax) www.cfb.unisg.ch The CFB-HSG is an international center focusing on research, teaching, and executive education in the context of family firms and business families. These three pillars represent an integrated self-enforcing circle.

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Table of content

Preface ........................................................................................................................................ 5

1 Introduction ......................................................................................................................... 6

1.1 Starting point and aims of GUESSS ............................................................................. 6

1.2 Theoretical framework .................................................................................................. 7

1.3 Project organization and data collection procedure ...................................................... 7

2 Participants and Sample ....................................................................................................... 8

2.1 Country representatives ................................................................................................ 8

2.2 Universities and respondents ........................................................................................ 9

2.3 Student demographics ................................................................................................. 10

2.4 University studies ....................................................................................................... 11

3 Career Choice Intentions ................................................................................................... 14

3.1 The general level ......................................................................................................... 14

3.2 Across fields of study ................................................................................................. 18

3.3 Across gender ............................................................................................................. 21

4 Determinants of Entrepreneurial Intentions ...................................................................... 24

4.1 A closer look at entrepreneurial intentions ................................................................. 24

4.2 The university context ................................................................................................ 27

4.3 The family context ...................................................................................................... 31

4.4 The role of personal motives ...................................................................................... 32

4.5 The social and cultural context ................................................................................... 35

5 Entrepreneurial Intentions Across Time ............................................................................ 39

6 Nascent Entrepreneurs ....................................................................................................... 48

6.1 Personal characteristics ............................................................................................... 48

6.2 The planned firms ....................................................................................................... 50

7 Active Entrepreneurs ......................................................................................................... 53

7.1 Personal characteristics ............................................................................................... 53

7.2 The existing firms ....................................................................................................... 54

8 Summary and Conclusion .................................................................................................. 58

9 References ......................................................................................................................... 61

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List of figures

Figure 1: Theoretical framework of GUESSS 2013/2014 ...................................................................... 7

Figure 2: List of country representatives ................................................................................................. 8

Figure 3: Countries, universities, and respondents .................................................................................. 9

Figure 4: Male and female students across countries ............................................................................ 10

Figure 5: Students‘ study level .............................................................................................................. 11

Figure 6: Study fields on the global level .............................................................................................. 11

Figure 7: Study fields in groups on the global level .............................................................................. 12

Figure 8: Students’ gender across study fields ...................................................................................... 12

Figure 9: Students’ study performance.................................................................................................. 12

Figure 10: Share of BECL, NSM, and SSC students across countries .................................................. 13

Figure 11: Career choice intentions on the global level ........................................................................ 14

Figure 12: Shift in career groups on the global level ............................................................................ 15

Figure 13: Career choice intentions in groups directly after studies across countries ........................... 16

Figure 14: Career choice intentions in groups 5 years after studies across countries ........................... 17

Figure 15: Career choice groups by study field directly after studies ................................................... 18

Figure 16: Career choice groups by study field 5 years after studies .................................................... 18

Figure 17: Entrepreneurial intentions among BECL students across countries .................................... 19

Figure 18: Entrepreneurial intentions among NSM students across countries ...................................... 20

Figure 19: Entrepreneurial intentions among SSC students across countries ....................................... 21

Figure 20: Career choice intentions by gender directly after studies .................................................... 22

Figure 21: Career choice intentions by gender 5 years after studies ..................................................... 22

Figure 22: Career choice intentions of male and female BECL students 5 years after study ............... 23

Figure 23: Career choice intentions of male and female NSM students 5 years after study ................. 23

Figure 24: Career choice intentions of male and female SSC students 5 years after study................... 23

Figure 25: Strength of entrepreneurial intentions across countries ....................................................... 25

Figure 26: Strength of entrepreneurial intentions across study fields ................................................... 26

Figure 27: Strength of entrepreneurial intentions across study fields and gender ................................. 26

Figure 28: Attendance of entrepreneurship courses .............................................................................. 27

Figure 29: Percentage of study time spent in entrepreneurship classes ................................................ 27

Figure 30: University entrepreneurial climate assessments .................................................................. 28

Figure 31: Entrepreneurial learning assessments across the globe ........................................................ 29

Figure 32: Entrepreneurial university climate vs. strength of entrepreneurial intentions ..................... 30

Figure 33: Entrepreneurial learning vs. strength of entrepreneurial intentions ..................................... 30

Figure 34: Existence of self-employed parents ..................................................................................... 31

Figure 35: Career choice intentions by family background 5 years after studies .................................. 31

Figure 36: Importance of different career motives ................................................................................ 32

Figure 37: Importance of career motives across different career groups .............................................. 33

Figure 38: Importance of „realize your dream“ motive across countries .............................................. 34

Figure 39: Subjective norms across countries ....................................................................................... 35

Figure 40: Risk perceptions across countries ........................................................................................ 37

Figure 41: Subjective norm vs. strength of entrepreneurial intentions .................................................. 38

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Figure 42: Risk perception vs. strength of entrepreneurial intentions ................................................... 38

Figure 43: Career choice groups in GUESSS 2013 (21 countries) ....................................................... 39

Figure 44: Career choice groups in GUESSS 2011 (21 countries) ....................................................... 40

Figure 45: Share of intentional founders across time / countries (5 years after studies) ....................... 40

Figure 46: Change in entrepreneurial intentions across time / countries (5 years after studies) ........... 41

Figure 47: Share of intentional founders across time / countries (5 years after studies, BECL) ........... 42

Figure 48: Change in entrepreneurial intentions across time / countries (5 years after studies, BECL) 42

Figure 49: Share of intentional founders across time / countries (5 years after studies, NSM) ............ 43

Figure 50: Change in entrepreneurial intentions across time / countries (5 years after studies, NSM) 44

Figure 51: Share of intentional founders across time / countries (5 years after studies, SSC) .............. 44

Figure 52: Change in entrepreneurial intentions across time / countries (5 years after studies, SSC) .. 45

Figure 53: Changes in entrepreneurial intentions in all fields / countries (2011 vs. 2013/2014) .......... 46

Figure 54: Share of nascent entrepreneurs across countries .................................................................. 48

Figure 55: Share of nascent entrepreneurs among BECL students across countries ............................. 49

Figure 56: Share of nascent entrepreneurs among NSM students across countries .............................. 49

Figure 57: Share of nascent entrepreneurs among SSC students across countries ................................ 49

Figure 58: Share of nascent entrepreneurs across gender and field of study......................................... 50

Figure 59: Gestation activities already conducted by nascent entrepreneurs ........................................ 50

Figure 60: Industry sectors of planned firms ......................................................................................... 51

Figure 61: Number of co-founders among nascent entrepreneurs ........................................................ 51

Figure 62: Nascent entrepreneurs‘ equity share in the planned firm ..................................................... 52

Figure 63: Degree of newness of the planned firms’ offerings ............................................................. 52

Figure 64: Share of active entrepreneurs across countries .................................................................... 53

Figure 65: Share of active entrepreneurs across study fields ................................................................ 53

Figure 66: Share of active entrepreneurs across gender and field of study ........................................... 54

Figure 67: Founding years of the already created firms ........................................................................ 54

Figure 68: Industry sectors of already created firms ............................................................................. 55

Figure 69: Equity share of active entrepreneurs .................................................................................... 55

Figure 70: Number of co-founders among active entrepreneurs ........................................................... 56

Figure 71: Employees (full-time equivalents) in the already created firms .......................................... 56

Figure 72: Growth intentions of active entrepreneurs ........................................................................... 57

Figure 73: Performance of existing firms relative to competitors ......................................................... 57

List of tables

Table 1: Entrepreneurial intention items ............................................................................................... 24

Table 2: Items to assess university entrepreneurial climate .................................................................. 28

Table 3: Items to assess entrepreneurial learning at the universities ..................................................... 29

Table 4: Items to assess perceived risk of creating an own firm ........................................................... 36

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Preface

What are students’ entrepreneurial intentions and activities across the world? This question is

of highest social and economic relevance. Students represent the entrepreneurs of tomorrow;

their entrepreneurial plans and activities will shape tomorrow’s societies and the overall

economic well-being.

Hence, it is of highest interest for different stakeholders such as academics, practitioners,

educators, policy-makers, and last but not least students how many students intend to pursue

an entrepreneurial career and how those entrepreneurial intentions come into being.

The GUESSS project (Global Universiy Entrepreneurial Spirit Students' Survey) addresses

this question on a global level. For that purpose, the 6th data collection wave in the history of

GUESSS was conducted in 34 countries at more than 700 universities between October 2013

and March 2014. This led to a dataset with more than 109’000 complete student responses.

This report provides an in-depth analysis of this unique dataset, shedding a nuanced light on

students’ entrepreneurial intentions and concrete activities. We focused in particular on cross-

country comparisons, whereby we also consider numerous other relevant aspects, such as

gender and specific social and cultural determinants.

Importantly, we also compare our results to those based on the GUESSS data collection in

2011 which allows us to recognize important trends and developments. Most importantly, we

see that entrepreneurial intentions in most countries seem to be stagnating or have even

declined compared to 2011.

The 2013/2014 edition of GUESSS would not have been possible without the invaluable effort and support of all country teams and of course without the students who responded to our survey invitation. Thank you. We are already looking forward to the next edition of GUESSS in 2015/16.

Yours sincerely,

Prof. Philipp Sieger Prof. Urs Fueglistaller Prof. Thomas Zellweger KMU-HSG / CFB-HSG

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1 Introduction

1.1 Starting point and aims of GUESSS

The international research project GUESSS stands for "Global University Entrepreneurial Spirit Students´ Survey" and has been founded at the Swiss Research Institute of Small Business and Entrepreneurship at the University of St.Gallen (KMU-HSG) in 2003. Until 2006 it was labeled ISCE (International Survey on Collegiate Entrepreneurship). Its research focus is on students’ entrepreneurial intentions and activities.

With every data collection wave, GUESSS has grown and has become more internationally, culminating in the 6th edition in 2013/2014 with 34 participating countries.

The aims of GUESSS can be summarized as follows:

Systematic and long-term observation of entrepreneurial intentions and activities of students

Identification of antecedents and boundary conditions in the context of new venture creation and entrepreneurial careers in general

Observation and evaluation of Universities' activities and offerings related to the entrepreneurial education of their students

GUESSS intends to create value for different stakeholders:

Participating countries generate insights on their respective basic conditions for entrepreneurship in general

They also learn more about the entrepreneurial power of their students

Participating Universities are enabled to assess the quantity and quality of their offerings in the context of entrepreneurship

Politics and public are sensitized for entrepreneurship in general and new venture creation in particular, and hopefully identify need for action

Students can benefit from the implementation of respective actions in the long term

Overall, GUESSS is maybe the largest entrepreneurship research project in the world. We seek to further increase its global scope in the future and aim for an even stronger impact in research and practice.

For more information about GUESSS please see http://www.guesssurvey.org

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1.2 Theoretical framework

The theoretical foundation of GUESSS is the Theory of Planned Behavior (Ajzen, 1991, 2002; Fishbein & Ajzen, 1975). Its underlying argument is that the intention to perform a specific behavior is influenced by three main factors: attitude toward the behavior, subjective norms, and perceived behavioral control.

At GUESSS, we focus on career choice intentions in general and entrepreneurial intentions in particular. We investigate additional factors that may impact the evolvement of career choice or entrepreneurial intentions through the three main elements of TPB. Examples are the university context, the family context, personal motives, and the social/cultural context. The overall theoretical framework is illustrated in the following figure.

Figure 1: Theoretical framework of GUESSS 2013/2014

1.3 Project organization and data collection procedure

The GUESSS project is organized by the KMU-HSG at the University of St.Gallen (Switzerland). The responsible project manager is Assistant Professor Philipp Sieger. The supervisory board consists of Prof. Urs Fueglistaller (President), Prof. Thomas Zellweger, Prof. Norris Krueger, and Dr. Frank Halter.

Every participating country is represented by one main country team. These country teams, in turn, recruit other universities in that country who also would like to take part in the data collection.

For each data collection wave since 2003, the GUESSS core team at the University of St.Gallen has been developing a comprehensive survey that meets the highest academic standards. The link to the online survey is then sent out to the different country teams who then forward it to their own students or to their university partners (who then also forward it to their respective students). Data is collected and prepared centrally.

University context

Family context

Personal motives

Attitude

Subjective norms

Perceived behavioral control

Career choice intentions

Social/cultural context

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2 Participants and Sample

2.1 Country representatives

# Country Representative University

1 Argentina (ARG) Prof. Silvia Carbonell Aranzazu Echezarreta

IAE Business School

2 Australia (AUS) Prof. Paull Weber Louis Geneste

Curtin University of Technology

3 Austria (AUT) Prof. Norbert Kailer Birgit Wimmer-Wurm

Johannes Kepler University Linz

4 Belgium (BEL) Prof. Dr. Hans Crijns Karen de Visch

Vlerick Leuven Gent Management School

5 Brazil (BRA) Prof. Edmilson Lima UNINOVE - Universidade Nove de Julho 6 Canada (CAN) Prof. Alexandra Dawson Concordia University, Montreal 7 Colombia (COL) Prof. Claudia Alvarez Universidad de Medellin

8 Denmark (DEN) Prof. Britta Boyd Prof. Kristian Philipsen

University of Southern Denmark

9 England (ENG) Prof. Robert Blackburn Arif Attar

Kingston University, Kingston

10 Estonia (EST) Prof. Urve Venesaar Tallinn University of Technology

11 Finland (FIN) Prof. Asko Miettinen Sampo Kokkonen

Lappeenranta University of Technology

12 France (FRA) Prof. Alain Fayolle Emeran Nziali

EM Lyon Business School

13 Germany (GER) Dr. Heiko Bergmann University of St.Gallen 14 Greece (GRE) Prof. Katerina Sarri University of Western Macedonia 15 Hungary (HUN) Dr. Szilveszter Farkas Budapest Business School 16 Israel (ISR) Prof. Brian Polin Jerusalem College of Technology

17 Italy (ITA) Prof. Tommaso Minola Giovanna Campopiano

University of Bergamo

18 Japan (JAP) Prof. Tomoyo Kazumi Senshu University

19 Liechtenstein (LIE) Prof. Dr. Urs Baldegger Simon Zäch

University of Liechtenstein

20 Luxembourg (LUX) Prof. Pol Wagner Frédéric Ternes

Institut Universitaire International Luxembourg

21 Malaysia (MAL) Prof. Raja Suzana Kasim Universiti Malaysia Kelantan 22 Mexico (MEX) Prof. Juan Arriaga EGADE Business School, Tecnologico de Monterrey

23 Netherlands (NED) Prof. Roy Thurik Dr. Ingrid Verheul Sofia Karali

Erasmus University, Rotterdam

24 Nigeria (NIG) Prof. Tomola Obamuyi Adekunle Ajasin University

25 Poland (POL) Prof. Adrianna Lewandowska Lukasz Tylczynski

Family Business Institute Poznań

26 Portugal (POR) Prof. Joao Leitao Prof. Miguel Amaral

Technical University of Lisbon Instituto Superior Tecnico

27 Romania (ROM) Dr. Lilian Ciachir University of Bucharest

28 Russia (RUS) Prof. Galina Shirokova Tatyana Tsukanova

St.Petersburg State University Graduate School of Management

29 Scotland (SCO) Dr. Erik Monsen University of Strathclyde, Glasgow

30 Singapore (SIN) Prof. Poh Kam Wong Low Pei Chin

National University of Singapore

31 Slovenia (SLO) Prof. Jaka Vadnjal Predrag Ljubotina

GEA College of Entrepreneurship

32 Spain (ESP) Prof. Joan Batista Prof. Ricard Serlavos Maika Valencia

ESADE

33 Switzerland (SUI) Prof. Philipp Sieger Prof. Rico Baldegger

University of St.Gallen HEG Fribourg

34 USA Prof. Torsten Pieper Prof. Pramodita Sharma

Kennesaw State University (KSU) University of Vermont (UVM)

Figure 2: List of country representatives

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2.2 Universities and respondents

The following table lists all countries and the characteristics of the respective data collection

efforts. We note that the number of students that have actually received a personal invitation

to take part in the GUESSS survey is sometimes relatively difficult to tell. The reason is that

not all universities that took part in GUESSS sent out personal emails to students. In many

cases, the GUESSS survey was announced in newsletters, on websites, or on Facebook pages.

If personal emails were sent to the students’ university email account, it is also not always

guaranteed that those accounts are used regularly. Also, universities did not always send out

those emails to the total student population, but only to a subgroup of students.

As a whole, the numbers given below have been provided to the best knowledge of the

country teams and university partners. However, the overall response rate is likely to be an

underestimation.

Responses Valid Percent # of universities # addressed students Response rateARG 190 .2 14 1800 10.6AUS 495 .5 6 3500 14.1AUT 4220 3.9 34 149587 2.8BEL 402 .4 16 n.a. n.a.BRA 12561 11.5 104 220000 5.7CAN 509 .5 2 7436 6.8COL 801 .7 22 5700 14.1DEN 1027 .9 10 28000 3.7ENG 654 .6 20 n.a. n.a.ESP 10545 9.7 21 126870 8.3EST 1391 1.3 23 33880 4.1FIN 704 .6 12 33943 2.1FRA 332 .3 14 14450 2.3GER 10570 9.7 44 292000 3.6GRE 435 .4 8 2500 17.4HUN 8844 8.1 31 161000 5.5ISR 1086 1.0 17 4500 24.1ITA 7765 7.1 46 142698 5.4JPN 890 .8 19 5835 15.3LIE 203 .2 2 607 33.4

LUX 153 .1 4 6457 2.4MEX 637 .6 17 5000 12.7MYS 2452 2.2 21 7400 33.1NED 9907 9.1 67 268808 3.7NGR 7 .0 1 n.a. n.a.POL 11860 10.9 37 115000 10.3POR 213 .2 3 3000 7.1ROM 277 .3 10 n.a. n.a.RUS 4578 4.2 35 26400 17.3SCO 280 .3 11 68900 0.4SIN 6471 5.9 9 88990 7.3SLO 903 .8 44 22000 4.1SUI 7419 6.8 33 87200 8.5USA 245 .2 2 25768 1.0Total 109026 100.0 759 1959229 5.5

Figure 3: Countries, universities, and respondents

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2.3 Student demographics

Before we start with detailed analyses of students’ entrepreneurial intentions and activities

across the globe, we need to know whom we are actually talking about. Hence, it is

imperative to take a closer look at the demographic characteristics of our respondents.

The respondents’ mean age is 23.1 years (median = 22 years); 58.4% of them are female. This

is comparable to the last GUESSS data collection in 2011. On average, the students have 1.6

siblings. Given the increasing interest in gender research, we note that the share of female

students varies significantly across countries. Female students are most dominant in Slovenia

and Scotland, whereby male students dominate particularly in Portugal and Liechtenstein.1

100.0

77.9

61.6

60.3

56.8

52.6

51.1

49.8

49.0

48.6

47.3

46.0

45.0

44.2

44.1

44.0

43.4

42.6

42.6

42.5

41.6

40.6

39.7

39.4

38.4

37.3

36.3

35.1

34.8

33.2

30.5

30.2

29.9

28.8

26.4

0.0

22.1

38.4

39.7

43.2

47.4

48.9

50.2

51.0

51.4

52.7

54.0

55.0

55.8

55.9

56.0

56.6

57.4

57.4

57.5

58.4

59.4

60.3

60.6

61.6

62.7

63.7

64.9

65.2

66.8

69.5

69.8

70.1

71.2

73.6

0% 20% 40% 60% 80% 100%

NGR

POR

LIE

JPN

MEX

ITA

ARG

FIN

SIN

COL

MYS

BEL

BRA

GRE

GER

AUS

ISR

CAN

HUN

LUX

AVERAGE

ESP

DEN

SUI

NED

FRA

ENG

AUT

USA

POL

RUS

ROM

EST

SCO

SLO

Male

Female

Figure 4: Male and female students across countries 1 We note that the share of male students in Nigeria is 100%. Given that only 7 responses were collected there,

we do not discuss this number here. Throughout the report, Nigeria is excluded for several analyses to avoid biases and misinterpretations that are due to the very small sample size in that country.

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2.4 University studies

Next, we take a closer look at the student characteristics with regard to their actual studies.

First of all, we note that 76.1% of all students are undergraduate (Bachelor) students, with

19.9% being graduate (Master) students. The share of students on other levels (e.g., PhD,

MBA) is negligibly small.

76.1

19.9

2.5 .3 1.2

Undergraduate (Bachelor)

Graduate (Master)

PhD (Doctorate)

Postdoc / Faculty member

MBA / Executive Education

Figure 5: Students‘ study level

22.4% of all students are studying in the field of “Business / Management”, which constitutes

the largest group in our sample. While considerable 15.6% of all students are studying in a

field that is not captured by our comprehensive selection of choices, the second largest group

is “Engineering and architecture” (15.1%) followed by “Economics”. As we will outline later

in this report, the field of study is a decisive factor when it comes to career choice intentions

in general and to entrepreneurial intentions in particular.

22.4

15.6

15.18.6

8.1

7.4

5.6

5.1

4.93.6

2.0 1.6Business / Management

Other

Engineering and architecture

Economics

Other social sciences (including education)

Medicine and health sciences

Information science / IT

Linguistics and cultural studies (including psychology, philosophy, religion)

Mathematics and natural sciences

Law

Agricultural science, forestry, and nutrition science

Art, science of art

Figure 6: Study fields on the global level

To facilitate a comparative analysis, we follow the procedure commonly used at GUESSS and

group the study fields into three main categories: “Business, economics, and law” (BECL),

“Natural sciences and medicine” (NSM), and “Social sciences” (SSC).

BECL includes “Business / Management”, “Economics”, and “Law”; NSM includes

“Engineering and architecture”, “Mathematics and natural sciences”, “Information science /

%

%

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IT”, “Agricultural science, forestry, and nutrition science”, and “Medicine and health

sciences”; and SSC comprises “Linguistics and cultural studies (including psychology,

philosophy, religion)” as well as “Other social sciences (including education)”. “Other”,

finally, includes the actual “Other” category plus “Art, science of art”.

34.6

35.1

13.1

17.2

BECL (business, economics and law)

NSM (natural sciences and medicine)

SSC (social sciences)

Other

Figure 7: Study fields in groups on the global level

Also here, it is worthwhile to look at students’ gender. As it could be expected, the majority

of NSM students is male, whereby female students dominate in BECL and even more in SSC.

39.9

54.5

22.6

60.1

45.5

77.4

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%




Male

Female

Figure 8: Students’ gender across study fields

We were also interested if students have a regular job next to their studies. 36.3% report that

this is the case, whereby they spend 25.7 hours per week on their job (average).

Also, students were asked how they would rate their own average study performance on a

scale from 1 (far below average) to 7 (far above average). The average value of 4.78 suggests

that students generally see them as performing slightly above average. Only 9.3% of the

students see themselves as being below average. Approximately every fourth student (25.4%)

sees him- or herself as being at least “Pretty above average”.

.6 2.0 6.7 29.8 35.7 21.2 4.2

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Far below average

Pretty below average

Rather below average

Equal

Rather above average

Pretty above average

Far above average

Figure 9: Students’ study performance

%

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Finally, as we expect that the field of study is an important determinant of career choice

intentions in general and of entrepreneurial intentions in particular, we investigate the

relevance of the different study fields across the GUESSS countries to facilitate later cross-

country comparisons. There are obvious differences across countries, which is of course also

due to the type and number of participating universities. BECL students constitute more than

75% of the sample in Canada, Australia and France. Portugal, on the other hand, is an

exception with 99% of the students enrolled in NSM-related study fields.

1

22

23

24

24

26

26

27

27

29

29

32

32

33

34

34

35

41

41

41

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47

55

58

58

62

63

65

66

71

77

84

95

99

45

39

26

41

51

33

54

38

34

41

28

38

41

32

39

35

32

49

44

5

35

18

20

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15

32

14

20

18

26

0

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6

1

0

12

19

20

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13

25

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11

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7

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3

4

26

13

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

POR

MYS

GER

SCO

AUT

ITA

DEN

SIN

EST

ISR

BRA

NED

ESP

SLO

SUI

ARG

AVERAGE

GRE

COL

FIN

ROM

HUN

POL

ENG

LUX

USA

MEX

RUS

BEL

JPN

LIE

NGR

FRA

AUS

CAN

BECL

NSM

SSC

OTHER

Figure 10: Share of BECL, NSM, and SSC students across countries

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3 Career Choice Intentions

3.1 The general level

One of the most central questions for GUESSS is what students intend to do after their

studies. Which career path do they plan to follow? What do they want to do directly after

completion of their studies, and what is their long-term career plan? The following figure

reports what the students in our global sample want to be right after completion of their

studies (orange bars) and 5 years later (green bars).

The first six options illustrate career paths as an employee, be it in the private sector, in the

public sector, or in a non-profit organization. The first three options, namely being employed

in a small, medium-sized, or large firm, are clearly the most preferable ones directly after

studies. Referring to five years later, we see that their attractiveness decreases significantly.

Referring to entrepreneurial intentions, only 6.6% of all students report that they want to work

in their own firm right after studies. 5 years after completion of studies, however, 30.7% of all

students want to have their own firm, which is an impressive number. Roughly every seventh

student falls into the group of students that are still undecided what to do after studies or 5

years later. More potential entrepreneurs might be found there in addition.

12.1

.4

1.3

6.6

10.2

6.4

3.2

22.0

20.7

17.0

14.5

2.3

2.0

30.7

10.2

6.8

2.9

19.0

7.9

3.9

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0

Other / do not know yet

A successor in a firm currently notcontrolled by my family

A successor in my parents' /family's firm

A founder (entrepreneur) workingin my own firm

An employee in public service

An employee in Academia(academic career path)

An employee in a non-profitorganization

An employee in a large firm (250or more employees)

An employee in a medium-sizedfirm (50-249 employees)

An employee in a small firm (1-49employees)

5 years after studies

Directly after studies

Figure 11: Career choice intentions on the global level

%

15


To illustrate the relevance of different types of occupations and the respective shifts

depending on the time horizon, we group the different career options into “Employee”,

“Founder”, and “Successor”.2

Interestingly, almost 80% of all students intend to work as an employee right after studies; 5

years later, this is true for only 50.6%. Most of those “short-term employees” who want to

leave employment after a few years intend to become founders. This “first employee, then

founder” pattern is consistent with findings of previous GUESSS editions (Sieger et al.,

2011).

50.6

79.6

30.7

6.6

4.3

1.8

14.5

12.1

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%


Directly after studies

Employee

Founder

Successor

Other

Figure 12: Shift in career groups on the global level

The global sample of the GUESSS project allows us to explore students’ career choice

intentions in more detail and to do meaningful cross-country comparisons. Even though the

results need to be interpreted with caution due to the differences in sample size, included

universities, study levels, and study fields, a first descriptive analysis is helpful here.

Right after completion of studies, we see that the share of intentional founders is highest in

Argentina, Poland, Mexico, and Colombia. Overall, despite a few exceptions, there seems to

be an underlying pattern that the share of intentional founders is higher in developing

countries. Developed and industrialized countries such as Japan, Switzerland, Austria, and

Germany can all rather be found at the lower end of the following Figure.3

2 We use the terms “entrepreneurial intentions” and “founding intentions” synonymously. Strictly speaking, also

becoming a successor in the parents’ firm or in a firm owned by other persons represents a type of entrepreneurial career. If we use “entrepreneurial intention” to refer to both becoming a founder and/or a successor, we mention this explicitly.

3 In the following tables Nigeria has been excluded due to the very low number of usable responses.

%

16


82

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POR

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BRA

LIE

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Employee

Founder

Successor

Other

Figure 13: Career choice intentions in groups directly after studies across countries

5 years after completion of studies, the pattern looks similar: the share of intentional founders

is highest in Mexico, Argentina, Colombia, and Russia. In those countries, more than half of

all surveyed students want to work in their own firm at this point in time. Again, developed

countries such as Austria, Switzerland, Germany, and Japan exhibit comparably low numbers.

17


However, we argue that the fact that 18% of all surveyed students want to create their own

firm within 5 years after completion of their studies in Austria, Switzerland, and Germany for

instance is still a good number from an entrepreneurial point of view.

63

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Employee

Founder

Successor

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Figure 14: Career choice intentions in groups 5 years after studies across countries

18


3.2 Across fields of study

As noted above, the field of study is a decisive factor in the context of career choice intentions

in general and entrepreneurial intentions in particular. Hence, we first split our analysis of

career choice groups depending on the field of study.

Right after studies, we observe that the share of intentional founders is of approximately equal

size among SSC and NSM students; BECL students exhibit a higher share (7.6%).

80.6

81.6

77.8

7.6

5.1

5.3

2.6

1.4

0.9

9.2

11.9

16.0

0% 20% 40% 60% 80% 100%

BECL

NSM

SSC

Employee

Founder

Successor

Other

Figure 15: Career choice groups by study field directly after studies

5 years after completion of studies, the situation looks a bit different. The share of intentional

founders among NSM students is considerably higher than among SSC students; and among

BECL students, the share is considerably higher than among NSM students. In concrete

numbers, more than one third of all BECL students (36.2%) want to work in their own firm at

that point in time, which we regard as a very impressive number.

46.9

52.2

57.6

36.2

29.2

21.3

5.6

4.0

2.3

11.4

14.6

18.8

0% 20% 40% 60% 80% 100%

BECL

NSM

SSC

Employee

Founder

Successor

Other

Figure 16: Career choice groups by study field 5 years after studies

19


Also here, we exploit our global dataset and investigate the relevance of the entrepreneurial

career path across countries depending on the field of study. This allows us to draw a more

realistic picture of the students’ entrepreneurial intentions in the different countries. Given

that the differences between study fields are larger when it comes to entrepreneurial intentions

5 years after completion of studies, we focus our analysis on that point in time.

First, we investigate BECL students and find that the share of intentional founders is highest

in Argentina, Mexico, Colombia, and Russia (all above 50%). At the lower end, we again find

developed countries like Switzerland, Germany, Austria, and Japan. But still, the situation

may not be as critical as the table might suggest at first sight. In fact, approximately every

fifth BECL student in Switzerland, Germany, or Austria wants to be a founder 5 years after

study, which is still an encouraging number.

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ESP

LIE

ENG

MYS

EST

POL

ROM

POR

RUS

COL

MEX

ARG

Figure 17: Entrepreneurial intentions among BECL students across countries

%

20


Among NSM students, the overall pattern looks very similar: while absolute numbers are

lower than for BECL students, developing countries are mostly above-average, and developed

countries are below-average in many cases.

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Figure 18: Entrepreneurial intentions among NSM students across countries

Also for SSC students, we note the same main pattern, with absolute numbers being below

those of NSM students.

%

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Figure 19: Entrepreneurial intentions among SSC students across countries

3.3 Across gender

In recent years, the interest of scholars and practitioners in gender aspects of entrepreneurship

has been increasing significantly. Hence, we follow this stream of research and take a closer

look at male and female students, respectively.

First, we depict the career choice intentions of male and female students. Directly after

studies, the share of intentional founders among males is considerably higher than among

females (8.6% versus 5.1%). Also the career path of a successor, be it in the parents’ firm (if

existing) or in a firm not owned by one’s parents, is less attractive for female students (1.5%

versus 2.1%). Taken together, 10.7% of all male students strive for an entrepreneurial career

path, compared to only 6.6% of all female students.

%

22


78.2

80.6

8.6

5.1

2.1

1.5

11.1

12.8

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

FemaleEmployee

Founder

Successor

Other

Figure 20: Career choice intentions by gender directly after studies

Related to 5 years after completion of studies, the differences are even larger: 35.1% of all

male students want to be entrepreneurs, but only 27.5% of all female students. The share of

intentional successors, however, is almost equal.

47.5

52.7

35.1

27.5

4.7

4.0

12.7

15.7

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

FemaleEmployee

Founder

Successor

Other

Figure 21: Career choice intentions by gender 5 years after studies

One could argue that this is at least partly due to the varying share of female students in the

different study fields. We noted in chapter 2.4 that the majority of SSC and BECL students

are female, whereas males dominate in NSM-related fields. Given that the share of intentional

founders among BECL students is highest and that 60.1% of all BECL students are female,

this would not make us expect that the share of intentional founders among females is

systematically lower than among males.

We examine gender differences in the different study fields in the following, focusing on

students’ intentions related to 5 years after study. For BECL students, males are clearly more

entrepreneurial than females. Among NSM students, the share of intentional founders is

considerably higher among males as well; there, we note that the “Other” category is much

more relevant for females.

Interestingly, gender differences are lowest among SSC students, as the share of intentional

employees is equal and as the share of intentional founders among males is only 2.7% higher

than among females. Overall, our results indicate that a gender difference indeed exists in the

entrepreneurial intentions context. More research is deemed necessary here.

23


43.4

49.1

40.2

33.5

6.2

5.3

10.2

12.1

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

FemaleEmployee

Founder

Successor

Other

Figure 22: Career choice intentions of male and female BECL students 5 years after study

49.1

55.9

33.8

23.6

4.2

3.8

12.9

16.7

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

FemaleEmployee

Founder

Successor

Other

Figure 23: Career choice intentions of male and female NSM students 5 years after study

57.6

57.6

23.4

20.7

2.5

2.2

16.4

19.5

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Male

FemaleEmployee

Founder

Successor

Other

Figure 24: Career choice intentions of male and female SSC students 5 years after study

24


4 Determinants of Entrepreneurial Intentions

4.1 A closer look at entrepreneurial intentions

Before we start with a detailed analysis of potential determinants of entrepreneurial intentions

according to the GUESSS research model, we note that we have investigated entrepreneurial

intentions by using a “black or white” question pertaining to the intention to pursue an

entrepreneurial career so far. Put differently, we have considered students as intentional

entrepreneurs in case they indicated that they want to work in their own firm at different

points in time.

While this approach is common and reliable (Zellweger et al., 2011), a potential weakness is

that students who seriously think about becoming an entrepreneur at some point in their career

but still prefer other options when asked for a “black or white” decision are regarded as non-

entrepreneurs. In other words, such an analysis disregards the entrepreneurial spirit of

students whose for instance second choice would be to become an entrepreneur.

To account for this, we take a more nuanced look at entrepreneurial intentions by using a

question that asked students to indicate their level of agreement to a number of statements that

capture their general intention to become an entrepreneur in the future (Linan & Chen, 2009).

The items are listed in the following table. An aggregated entrepreneurial intention measure

was generated by calculating the mean of all six answers that were anchored from 1 (strongly

disagree) to 7 (strongly agree).

Item number Text

1 I am ready to do anything to be an entrepreneur.

2 My professional goal is to become an entrepreneur.

3 I will make every effort to start and run my own firm.

4 I am determined to create a firm in the future.

5 I have very seriously thought of starting a firm.

6 I have the strong intention to start a firm someday.

Table 1: Entrepreneurial intention items

In the next step, we calculated the average value of this variable in the different GUESSS

countries (see following figure). The results confirm the main pattern that we already obtained

when analyzing the concrete career choice intentions of our students. Specifically, many

developing countries can be found on top of the figure, such as Mexico, Colombia, Argentina,

Malaysia, and Russia. Below the global average there are many developed countries such as

France, the Netherlands, Austria, Switzerland, Germany and Japan.

25


2.5

2.5

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4.2

4.3

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4.6

5.0

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5.2

5.7

0.0 1.0 2.0 3.0 4.0 5.0 6.0

DEN

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POL

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MYS

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COL

MEX

Figure 25: Strength of entrepreneurial intentions across countries

Also an analysis based on field of study confirms our initial findings, as the average value of

the entrepreneurial intentions measure just described is highest for BECL students, second

highest for NSM students, and lowest for SSC students (see figure below). Country-specific

patterns that deviate from our main findings could not be found; therefore, we do not report

the country-specific values for BECL, NSM, and SSC students separately here.

Furthermore, we tested for gender differences and confirmed that the aggregated

entrepreneurial intention measure exhibits lower average values for female students compared

to male students (3.5 compared to 4.0). When testing for gender differences between the

different fields of study, we consistently find that the level of entrepreneurial intentions is

lower for females than for males across all fields of study, which is in line with our general

findings already illustrated above.

26


4.1

3.6

3.0

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

BECL (business,economics and law)

NSM (natural sciencesand medicine)


Figure 26: Strength of entrepreneurial intentions across study fields

4.3

3.9

3.2

3.9

3.2

2.9

0.0 1.0 2.0 3.0 4.0 5.0

BECL

NSM

SSC

Female

Male

Figure 27: Strength of entrepreneurial intentions across study fields and gender

These analyses show that both types of measures, namely the “black or white” binary measure

and the multi-item continuous measure, are valid and reliable across all countries. In the

following, we now turn to examining different potential antecedents of entrepreneurial

intentions. In that endeavor, we follow the already presented GUESSS research model and

take a closer look at four types of antecedents: the university context, the family context, the

role of personal motives, and the social/cultural context. Depending on the type of analysis we

use either our binary entrepreneurial intention measure or our continuous one.

27


4.2 The university context

An important element of the GUESSS research model is the role of the university in the

context of entrepreneurial intentions. In academic research, the design, content, and effects of

entrepreneurship education represents a major stream of research (Lima et al., 2014).

Hence, we asked the students to what extent they have been attending entrepreneurship-

related courses and offerings. As the following figure shows, less than 10% of all students are

studying in a program specifically dedicated to entrepreneurship. Almost two thirds of our

respondents did not attend any entrepreneurship-related course at all. Around every fifth

student, however, has attended an entrepreneurship course as compulsory or elective course

(multiple answers were possible).

62.4

19.4

21.5

7.3

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

I am studying in a specific program onentrepreneurship.

I have attended at least oneentrepreneurship course as compulsorypart of my studies.

I have attended at least oneentrepreneurship course as elective.

I have not attended a course onentrepreneurship so far.

Figure 28: Attendance of entrepreneurship courses

Also, we asked students what percentage of their total study time they did devote to

entrepreneurship courses. The global average is 25.9%, with the median being 20. As the

following figure shows, 37% of all students have spent 10% or less of their total study time

for entrepreneurship courses; 58% have spent up to 20% in this type of courses. This signals

that entrepreneurship education is available for the majority of students, whereby the share of

students who have barely attended any related offerings at all is still considerable.

37

21

13.5

9.1

6.2

13.2

Up to 10%

11 to 20%

21 to 30%

31 to 40%

41 to 50%

More than 50%

Figure 29: Percentage of study time spent in entrepreneurship classes

%

28


Next, we examine the entrepreneurial climate that exists at the different universities. Students

were asked to indicate the extent to which they agree to the statements listed in the following

table (Luethje & Franke, 2004). Answers ranged from 1 (not at all) to 7 (very much).

Item number Item text 1 The atmosphere at my university inspires me to develop ideas for new

businesses. 2 There is a favorable climate for becoming an entrepreneur at my

university. 3 At my university, students are encouraged to engage in entrepreneurial

activities.

Table 2: Items to assess university entrepreneurial climate

The global average is 4.0, which constitutes the middle of our scale. The figure below shows

that almost 30% of all students show a level of agreement of 3 or lower. Almost half of all

students assess the entrepreneurial climate at their university as being between 3 and 5.

Overall, this reveals a quite neutral assessment of the universities’ entrepreneurial climate on

the global level.

14.4

15.4

23.1

23.2

16.2

7.7

Level of agreement: >1-2






Figure 30: University entrepreneurial climate assessments

We refrained from calculating average values for all the GUESSS countries separately as

those numbers strongly depend on the universities that took part in the different countries. For

instance, at a small university that offers specific entrepreneurship programs and courses, it is

very likely that the overall climate is more entrepreneurship-friendly than at a large university

where a wide array of study fields are offered. Given the country-level heterogeneity in terms

of number of universities included, types of universities (e.g., public or private), and size of

the universities, the corresponding results would be heavily biased and would not allow to

draw valid conclusions.

We are not only interested in students’ attendance of entrepreneurship classes and in their

perceptions regarding the entrepreneurial climate at their university, but also in how much

they have been learning at their university with regard to entrepreneurship. We thus asked

%

29


them to indicate the extent to which they agree to a few statements about their learning

progress during their studies (1=not at all, 7=very much). The question started with “The

courses and offerings I attended…” and offered the following statements (cf. Souitaris et al.

2007):

Item number Item text 1 …increased my understanding of the attitudes, values and motivations of

entrepreneurs. 2 …increased my understanding of the actions someone has to take to start a

business. 3 …enhanced my practical management skills in order to start a business. 4 …enhanced my practical management skills in order to start a business. 5 …enhanced my ability to identify an opportunity.

Table 3: Items to assess entrepreneurial learning at the universities

Again, the global average is 4.0, and the distribution of the different agreement levels looks

pretty similar as with the entrepreneurial climate question.

14

14.3

21.424.8

18.2

7.3







Figure 31: Entrepreneurial learning assessments across the globe

Beyond those initial insights, a key question is to what extent the university, be it through the

entrepreneurial climate or through concrete entrepreneurial learnings, can enhance students’

entrepreneurial intentions. To get first insights into this relationship we provide two plots

below. The first one illustrates the relationship between university entrepreneurial climate and

entrepreneurial intentions; the second one does the same for entrepreneurial learning.

The plots indicate a positive relationship between the level of the entrepreneurial climate and

entrepreneurial intentions on one hand and between the level of entrepreneurial learning and

entrepreneurial intentions on the other hand. This emphasizes the crucial role that the

university context plays when it comes to the formation of entrepreneurial intentions.

%

30


Figure 32: Entrepreneurial university climate vs. strength of entrepreneurial intentions

Figure 33: Entrepreneurial learning vs. strength of entrepreneurial intentions

31


4.3 The family context

In academic research there is a long-standing debate how the occupational background of the

parents influences childrens’ career choice intentions. In general, research tends to agree that

children of entrepreneurial parents are more likely to become entrepreneurs themselves

(Laspita et al., 2012).

We thus asked the students if their father, their mother, or both of them are currently self-

employed. More than two thirds of all students report that none of them is self-employed

(68.7%). Almost 10% of the respondents indicate that both of their parents are self-employed.

68.7

17.1

5.48.8

No

Yes, father

Yes, mother

Yes, both

Figure 34: Existence of self-employed parents

We split our sample into students with and without entrepreneurial parents and examined their

respective career choice intentions 5 years after completion of their studies. As expected, we

see a difference: 42.5% of all students with entrepreneurial parents intend to follow an

entrepreneurial career path, be it as a founder or as a successor in the parents’ firm (or in

another firm). For students without entrepreneurial parents, this share is only 31.5%.

While these differences might be partly explained by the fact that students without

entrepreneurial parents do not have the option to take over their parents’ firm one day, also

the share of students who intend to work in a firm that they created on their own is

significantly different (34.7% for students with entrepreneurial parents compared to 28.8% for

students without entrepreneurial parents). Hence, our analyses support the notion that having

an entrepreneurial family background is conducive to childrens’ entrepreneurial intentions.

53.3

44.5

28.8

34.7

2.7

7.8

15.1

13.0

0% 20% 40% 60% 80% 100%

No entrepreneurial parents

Entrepreneurial parents

Employee

Founder

Successor

Other

Figure 35: Career choice intentions by family background 5 years after studies

%

32


4.4 The role of personal motives

Another important determinant of career choice intentions in general and entrepreneurial

intentions in particular are career motives. Logically, some motives are more likely to be

satisfied by pursuing an entrepreneurial career than others.

Hence, we examined how students assess the importance of different motives when they

decide about their future career path. As the following figure shows, “realize your dream” is

the strongest motive on global average (1=not important at all, 7=very important), followed

by “have an exciting job”. The least important motives, which are in turn still important in

absolute terms, are “have authority” and “be your own boss”.

4.58

4.98

5.41

5.44

5.48

5.48

5.55

5.66

5.94

6.08

4.50 5.00 5.50 6.00 6.50

Be your own boss

Have authority

Take advantage of creative needs

Have power to make decisions

Create something

Have a challenging job

Independence

Freedom

Have an exciting job

Realize your dream

Figure 36: Importance of different career motives

To examine differences between the three main career paths of becoming a founder, an

employee, or a successor, we split our analysis into those groups. The following figure

illustrates the importance of the abovementioned motives for each group. For intentional

founders, we see that the most important motives are “realize your dream”, “have an exciting

job”, “create something”, and “independence” (the bars in the figure are sorted this way).

Compared to the other career paths, we see that for instance “create something”, “take

advantage of creative needs”, and “be your own boss” are significantly more important for

intentional founders. Interestingly, career reasons that are intuitively attributed to an

entrepreneurial career, such as “realize an own dream” or “having an exciting job”, have high

values among intentional employees as well.

33


4.85

4.05

5.43

5.21

5.54

5.24

5.36

5.23

5.90

5.94

5.29

5.52

5.63

5.81

5.87

5.88

5.90

5.99

6.05

6.38

5.39

5.18

5.61

5.44

5.74

5.76

5.77

5.60

6.03

6.18

3.50 4.00 4.50 5.00 5.50 6.00 6.50

Have authority

Be your own boss

Have a challenging job

Take advantage of creativeneeds

Freedom

Have power to make decisions

Independence

Create something

Have an exciting job

Realize your dream

Successor

Founder

Employee

Figure 37: Importance of career motives across different career groups

Given the fact that “realize your dream” is the most important career motive for intentional

founders, we illuminate how important this motive is in the different countries of the

GUESSS sample. We see that this motive is most important in Colombia, Mexico, Romania,

Brazil, Argentina, and Slovenia, with the lowest importance in France, Japan, and Germany.

Again, we note that the “lowest importance” has to be seen in relative terms; in absolute

terms, the last mentioned three countries still have average values of almost 5 (France) or

slightly below or at 5.5 (Japan and Germany). Hence, this career motive is also important

there. Nevertheless, it seems like our underlying “developing versus developed” country

pattern also appears regarding the “realize your dream” motive.

34


4.99

5.46

5.50

5.60

5.60

5.75

5.78

5.82

5.86

5.90

5.92

5.92

5.95

5.96

5.97

5.99

6.03

6.08

6.12

6.16

6.20

6.21

6.23

6.25

6.28

6.31

6.34

6.35

6.43

6.45

6.53

6.54

6.64

6.67

4.50 5.00 5.50 6.00 6.50 7.00

FRA

JPN

GER

FIN

SUI

ISR

DEN

AUT

SCO

BEL

LUX

LIE

POR

HUN

SIN

NED

AUS

AVERAGE

GRE

EST

ENG

CAN

USA

POL

ITA

MYS

RUS

ESP

SLO

ARG

BRA

ROM

MEX

COL

Figure 38: Importance of „realize your dream“ motive across countries

35


4.5 The social and cultural context

Scholars agree that entrepreneurial decision-making is deeply embedded in the social and

cultural context that individuals live in. Put differently, social and cultural factors have an

important effect on the formation of entrepreneurial intentions. Hence, we first investigate the

social pressure that is exerted by individuals’ immediate environment. We do so by drawing

on the concept of “subjective norm” from the theory of planned behavior (Ajzen, 1991). It

captures the reaction that individuals expect from close peers if a certain behavior is executed.

Theory postulates that the more positive the expected reaction is, the more likely it is that

actual intentions to perform the behavior under consideration are formed.

In our case, we asked students how different people in their environment would react if they

(the students) would pursue a career as an entrepreneur. The people (or groups of people)

were close family members, friends, and fellow students. The responses were anchored at 1

(very negatively) and 7 (very positively) (Linan & Chen, 2009). The following figure reports

the mean values of the aggregated items per country.

4.22

5.16

5.18

5.20

5.22

5.30

5.31

5.37

5.41

5.43

5.47

5.48

5.49

5.50

5.52

5.53

5.55

5.56

5.57

5.65

5.68

5.70

5.72

5.75

5.76

5.76

5.78

5.82

5.88

5.88

5.91

5.94

6.02

6.28

4.00 4.50 5.00 5.50 6.00 6.50

JPN

SIN

GRE

GER

FIN

SCO

AUT

DEN

ITA

SUI

HUN

BEL

AUS

NED

LUX

AVERAGE

ESP

ENG

USA

POL

SLO

MYS

FRA

POR

CAN

ROM

EST

ISR

LIE

RUS

ARG

COL

BRA

MEX

Figure 39: Subjective norms across countries

36


The global average is 5.53, which is relatively high. In general, subjective norms with regard

to entrepreneurship thus seem to be quite positive. However, there are important country-level

differences to observe. Interestingly, the four countries with the most positive expected

reaction of the immediate environment are all from Latin America: Mexico, Brazil, Colombia,

and Argentina. In the upper half of the list, above the global average, we also find former

communist countries such as Russia, Estonia, Romania, and Poland. This indicates a truly

entrepreneurship-friendly social context in those countries.

Developed industrialized countries can mostly be found below the global average. However,

we note that this is not as dramatic as it might seem: the values are still quite high in absolute

terms (higher than 5, with the exception of Japan). Hence, being below average “just” means

that the expected reaction of the environment is not as positive as in other countries, but it is

still positive and thus conducive to entrepreneurial intentions.

Second, we are interested to what extent becoming an entrepreneur is regarded as risky. This

is because risk is a key aspect of entrepreneurship, and scholars are interested in related

factors such as the level of uncertainty avoidance in a society (Hofstede, 2001).

To assess this, students were asked to indicate their level of agreement with a few statements

(1=strongly disagree, 7=strongly agree) that are listed in the following table (see also

Pennings & Wansink, 2004).

Item number Item text 1 I consider staring up my own business to be very risky. 2 I think it is dangerous to manage your own business. 3 I believe that business ownership has high risk.

Table 4: Items to assess perceived risk of creating an own firm

The strongest risk perceptions can be found in Poland, followed by Japan, USA, Denmark, and Germany (all with values at or above 5). The lowest values are found in Latin American countries (Argentina, Colombia, Mexico, and Brazil).

37


3.90

4.08

4.09

4.31

4.36

4.37

4.42

4.43

4.47

4.58

4.65

4.68

4.72

4.73

4.73

4.74

4.76

4.77

4.78

4.80

4.82

4.85

4.87

4.87

4.90

4.90

4.93

4.97

4.97

4.98

5.00

5.05

5.07

5.16

5.50

3.00 3.50 4.00 4.50 5.00 5.50 6.00

ARG

COL

MEX

BRA

ROM

EST

NGR

LIE

FRA

ENG

SUI

RUS

POR

GRE

BEL

SCO

HUN

ESP

AUS

LUX

FIN

AVERAGE

SLO

AUT

ITA

MYS

CAN

NED

ISR

SIN

GER

DEN

USA

JPN

POL

Figure 40: Risk perceptions across countries

To provide first initial insights into the relationship with entrepreneurial intentions, we depict

two plots in the following. The first one illustrates the relationship between subjective norms

and entrepreneurial intentions; the second one does the same for risk perceptions and

entrepreneurial intentions.

As expected, we see a positive relationship between subjective norms and entrepreneurial

intentions and a negative relationship between risk perceptions and entrepreneurial intentions.

This illustrates the crucial relevance of the social and institutional context that students are

embedded in.

38


Figure 41: Subjective norm vs. strength of entrepreneurial intentions

Figure 42: Risk perception vs. strength of entrepreneurial intentions

39


5 Entrepreneurial Intentions Across Time

The unique study design of the GUESSS project allows us to track the strength of

entrepreneurial intentions across time. We can evaluate if students’ entrepreneurial intentions

in different countries have been increasing or decreasing over the last years. In order to do

this, we compare the data generated in the GUESSS project in 2013/2014 with the GUESSS

data collected in Spring 2011.

Of course, we have to be very cautious, as the two samples differ in terms of participating

countries and participating universities. For instance, out of the 34 GUESSS countries that

took part in the 2013/2014 edition, 21 were also participants of the 2011 edition. In addition,

the number and types of universities participating in each country also varies between 2011

and 2013/2014, as does the number of responding students per university and per country.

However, the country teams of those 21 countries did not change between 2011 and

2013/2014; hence, we do not assume that there is a systematic difference with regard to the

data collection procedure and in particular with regard to the university recruitment strategy.

When recognizing trends and developments in the following, we kept those potential

limitations in mind and were thus very cautious in interpreting the data. Nevertheless, we

believe that important indications can be derived. We analyzed the career choice intentions in

the 21 “double” countries as a first step. From the 2013/2014 dataset, we could rely on 71’051

answers; from the 2011 dataset, 89’803 responses could be used.

For 2013/2014, we see that 6.6% of all students intend to become an entrepreneur directly

after studies (founder or successor), compared to 32.5% 5 years after studies. Intentional

founders account for 5.2% and 28.4%, respectively. The 2011 data reveals higher numbers:

there, 14.9% of all students are classified as intentional entrepreneurs directly after studies

(founder or successor), and 42.9% related to 5 years after studies (intentional founders

account for 11% and 34%, respectively). This is a first sign that entrepreneurial intentions,

and particularly founding intentions, are lower in 2013/2014 compared to 2011 (cf. the

following figures).

52.5

81.1

28.4

5.2

4.1

1.4

15.0

12.3

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%


Directly after studies Employee

Founder

Successor

Other

Figure 43: Career choice groups in GUESSS 2013 (21 countries)

40


38.4

67.8

34.0

11.0

8.9

3.9

18.7

17.4

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%


Directly after studies Employee

Founder

Successor

Other

Figure 44: Career choice groups in GUESSS 2011 (21 countries)

To delve deeper into this issue, we analyze the share of intentional founders in the 21

countries separately. We focus on intentional founders referring to 5 years after completion of

studies as we believe that this provides a picture that is a bit more reliable than if we look at

intentional founders directly after studies. Moreover, additional analyses not reported here

showed that the general trends that we discuss in the following are rather independent of the

time frame. The following figure shows that while several countries exhibit comparable

numbers, many countries report significant changes.

30.7

24.7

27.2

28.6

30.3

29.0

27.1

30.3

36.7

28.2

42.8

33.0

39.7

39.1

37.5

32.1

36.1

41.4

47.1

53.5

60.4

10.4

17.6

17.7

18.4

24.7

24.7

27.0

27.1

27.7

28.8

32.9

33.3

33.5

33.5

35.4

35.7

36.2

41.4

52.6

63.2

66.6

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

JPN

GER

SUI

AUT

FIN

SIN

GRE

NED

FRA

LUX

ROM

BEL

ENG

BRA

HUN

POR

EST

LIE

RUS

ARG

MEX

Share of intentional founders 2013/2014

Share of intentional founders 2011

Figure 45: Share of intentional founders across time / countries (5 years after studies)

%

41


To further illuminate the changes in the different countries, the following figure shows the 21

countries sorted by the magnitude of change. The share of intentional founders has been

increasing in 6 countries, has been quite stable in 5 countries (less than 1% change), and has

been decreasing considerably in 12 countries.

We acknowledge that the formation of entrepreneurial intentions is affected by a multitude of

different factors, and we reiterate that our findings in this chapter have to be interpreted with

caution given the sampling issues described above. Nevertheless, given these numbers, we

dare to derive from our analysis that students’ intentions to create an own firm have rather

been declining over the last years in most countries.

-20.2

-10.2

-9.9

-9.5

-9.0

-7.1

-6.2

-5.6

-5.6

-4.3

-3.2

-2.1

-0.1

0.0

0.0

0.4

0.6

3.6

5.5

6.1

9.7

-25.0 -20.0 -15.0 -10.0 -5.0 0.0 5.0 10.0 15.0

JPN

AUT

ROM

SUI

FRA

GER

ENG

FIN

BRA

SIN

NED

HUN

GRE

LIE

EST

BEL

LUX

POR

RUS

MEX

ARG

Figure 46: Change in entrepreneurial intentions across time / countries (5 years after studies)

For even more nuanced insights, we split our analyses depending on study field in the

following. For BECL students, the share of intentional founders 5 years after studies for both

2013/2014 and 2011 in all countries are shown in the following figure.

The analysis of the respective shifts across time in Figure 47 reveals that again Argentina,

Portugal, Mexico, and Russia are among the “winners”. Among those countries whose share

of intentional founders has been dropping most significantly, striking similarities can be

found compared to the overall findings illustrated above. Hence, the changes on the country

level are well-reflected in the changes among BECL students in the different countries.

%

42


11.1

29.1

27.7

33.1

29.3

38.6

30.3

32.8

37.8

32.0

47.1

42.3

40.3

38.6

43.1

46.3

44.4

34.0

49.0

62.3

52.9

10.3

18.6

21.3

22.3

26.4

28.3

29.8

30.1

31.6

31.8

35.2

36.0

38.8

39.6

42.0

42.9

44.3

50.0

56.2

70.1

75.4

0.0 20.0 40.0 60.0 80.0

JPN

AUT

GER

SUI

FIN

FRA

SIN

LUX

NED

GRE

BEL

BRA

HUN

LIE

ENG

EST

ROM

POR

RUS

MEX

ARG



Figure 47: Share of intentional founders across time / countries (5 years after studies, BECL)

-11.9

-10.8

-10.5

-10.2

-6.4

-6.3

-6.1

-3.4

-3.0

-2.7

-1.5

-1.2

-0.8

-0.5

-0.2

-0.1

1.0

7.2

7.8

16.0

22.5

-15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0 25.0

BEL

SUI

AUT

FRA

GER

BRA

NED

EST

FIN

LUX

HUN

ENG

JPN

SIN

GRE

ROM

LIE

RUS

MEX

POR

ARG

Figure 48: Change in entrepreneurial intentions across time / countries (5 years after studies, BECL)

%

%

43


For NSM students, the absolute numbers for both 2013/2014 and 2011 are shown in the

following figure.

32.1

22.9

21.4

26.0

24.0

26.0

31.3

26.1

41.1

18.9

19.0

26.2

38.4

40.7

34.1

37.9

40.9

50.0

46.9

53.9

61.3

10.1

16.7

17.7

19.9

21.1

22.6

23.6

25.0

27.3

30.4

32.6

33.3

34.4

34.5

35.7

36.3

38.5

40.4

45.1

54.1

62.0

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

JPN

GER

SUI

AUT

NED

FIN

SIN

LUX

ENG

BEL

GRE

FRA

HUN

BRA

POR

EST

ROM

LIE

RUS

ARG

MEX



Figure 49: Share of intentional founders across time / countries (5 years after studies, NSM)

The differences between the two datasets are illustrated in Figure 50. Surprisingly, the

situation for NSM students looks different compared to BECL students. In Greece, Belgium,

and France, the share of intentional founders has been increasing considerably. The countries

with the highest increase for BECL students, Argentina, Portugal, Mexico, and Russia, only

show moderately higher shares or even a lower share (Russia).

Hence, the absolute increase in the share of intentional founders in those countries seems to

be mainly driven by the stronger entrepreneurial drive among BECL students.

%

44


-22.1

-13.9

-9.6

-7.7

-6.3

-6.2

-6.2

-4.0

-3.7

-3.4

-2.9

-2.4

-1.8

-1.6

-1.1

0.1

0.7

1.7

7.2

11.5

13.6

-25.0 -20.0 -15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0

JPN

ENG

LIE

SIN

GER

BRA

AUT

HUN

SUI

FIN

NED

ROM

RUS

EST

LUX

ARG

MEX

POR

FRA

BEL

GRE

Figure 50: Change in entrepreneurial intentions across time / countries (5 years after studies, NSM)

The absolute numbers for SSC students can be found in the following table. France, Portugal,

and Liechtenstein do not appear because data was not available in both datasets.

19.0

30.7

22.1

39.3

29.1

29.4

15.5

29.8

29.8

43.9

25.5

17.2

25.0

23.7

29.9

27.7

50.0

43.6

10.8

11.5

11.9

13.8

14.7

14.9

16.0

19.8

22.8

22.9

23.2

25.0

25.0

26.7

27.8

40.1

42.9

57.1

0.0 10.0 20.0 30.0 40.0 50.0 60.0

SUI

JPN

GER

FIN

AUT

ENG

GRE

SIN

BRA

ROM

NED

BEL

LUX

EST

HUN

RUS

ARG

MEX



Figure 51: Share of intentional founders across time / countries (5 years after studies, SSC)

%

%

45


Looking at the changes reported in the figure below, the main pattern seems a bit similar to

the one found among BECL students. In Mexico and Russia, the share of intentional founders

has been increasing significantly between 2011 and 2013/2014. Argentina, however, reports a

decrease of the share of intentional founders of 7.1%. As with BECL and NSM students, we

see that only a few countries report stronger entrepreneurial intentions than 2011; very few

remain stable; and the majority of countries reports weaker entrepreneurial intentions among

their students.

-25.5

-21.0

-19.2

-14.5

-14.4

-10.2

-10.0

-8.2

-7.1

-7.0

-2.3

-2.1

0.0

0.5

3.0

7.8

12.4

13.6

-30.0 -25.0 -20.0 -15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0

FIN

ROM

JPN

ENG

AUT

GER

SIN

SUI

ARG

BRA

NED

HUN

LUX

GRE

EST

BEL

RUS

MEX

Figure 52: Change in entrepreneurial intentions across time / countries (5 years after studies, SSC)

To be able to discuss the situation in the different countries in a more comprehensive and

integrated way, we combined the changes in the different study fields just discussed in one

figure.

There are a few countries that show a quite ambiguous picture. For instance, in Argentina,

entrepreneurial intentions among BECL students have been rising significantly between 2011

and 2013/2014. For NSM students, however, they remained stable, and for SSC students, they

declined by more than 7%. In Belgium, entrepreneurial intentions have become weaker

among BECL students but significantly stronger among NSM and SSC students. In Estonia,

numbers for BECL and NSM students have been declining, but increased for SSC students.

France, in addition, shows a sharp decline for BECL students and a strong increase for NSM

students. Also Russia falls into the “ambiguous” category, as entrepreneurial intentions are

stronger for BECL and SSC students but slightly weaker for NSM students.

%

46


-8.2

-10.0

12.4

-21.0

-2.3

13.6

0.0

-19.2

-2.1

0.5

-10.2

-25.5

3.0

-14.5

-7.0

7.8

-14.4

-7.1

-3.7

-7.7

-1.8

-2.4

1.7

-2.9

0.7

-1.1

-9.6

-22.1

-4.0

13.6

-6.3

7.2

-3.4

-1.6

-13.9

-6.2

11.5

-6.2

0.1

-10.8

-0.5

7.2

-0.1

16.0

-6.1

7.8

-2.7

1.0

-0.8

-1.5

-0.2

-6.4

-10.2

-3.0

-3.4

-1.2

-6.3

-11.9

-10.5

22.5

-28.0 -14.0 0.0 14.0 28.0

SUI

SIN

RUS

ROM

POR

NED

MEX

LUX

LIE

JPN

HUN

GRE

GER

FRA

FIN

EST

ENG

BRA

BEL

AUT

ARG

BECL change

NSM change

SSC change

Figure 53: Changes in entrepreneurial intentions in all fields / countries (2011 vs. 2013/2014)

%

47


There are a few countries, however, who exhibit a decline in entrepreneurial intentions

consistently across all study fields. Those are Austria, Brazil, England, Finland, Germany,

Hungary, Japan, the Netherlands, Romania, Singapore, and Switzerland. This means that in

11 out of 21 countries, students’ entrepreneurial intentions in 2013/2014 are weaker compared

to 2011 in all study fields. Only Mexico reports increasing numbers in all fields.

Altogether, as already stated above and despite all possible data and sample limitations, and

despite a few countries as exceptions, we believe we can conclude that students’

entrepreneurial intentions in 2013/2014 are not as strong any more as in 2011. The possible

reasons for this could be manifold. One example could be the overall economic environment.

In many countries, the economic situation in Autumn/Winter 2013/2014 looks better than in

Spring 2011. In 2011, the effects of the global economic crisis that started in 2008/2009 were

more prevalent than in 2013/2014. This means that the students surveyed recently find more

and better job opportunities in the regular job market, which reduces the share of so-called

“necessity entrepreneurs” who want to create a firm because they cannot find a good job

elsewhere.

In any case, we call for more in-depth analyses on the country level to shed further light on

this intriguing phenomenon.

48


6 Nascent Entrepreneurs

6.1 Personal characteristics

After we have investigated students’ career choice intentions and particularly entrepreneurial

intentions in great detail, we now turn to a group of students that is of unique interest not only

for GUESSS but also for entrepreneurship researchers and practitioners in general: those

students who are already in the process of actually starting their own firm.

To identify them, all students were asked: “Are you currently trying to start your own

business / to become self-employed?” In total, 16’429 students answered with “yes” (15.1%)

and can thus be classified as so-called “nascent entrepreneurs”.

The differences between countries are considerable. Despite a few exceptions, developing

countries are more likely to be above average, and developed countries are more likely to be

below average. Argentina and Malaysia exhibit very high values. This might be due to the

sample characteristics in those countries and has thus to be interpreted with caution.

52 51

38

27 27 27 24 22 21 2118 18 18 17 16 16 15 15 14 12 12 11 11 10 9 9 8 8 7 7 7 5 5 3

0

10

20

30

40

50

60

MY

S

AR

G

ME

X

POL

CO

L

RO

M

HU

N

RU

S

AU

S

GR

E

EN

G

ES

T

LIE

USA SI

N

CA

N

BR

A

AV

ER

AG

E

POR

FRA

FIN

JPN

BE

L

NE

D

ES

P

LU

X

ISR

ITA

SCO

DE

N

GE

R

AU

T

SUI

SLO

Figure 54: Share of nascent entrepreneurs across countries

Some of the differences may also be due to the varying relevance of the different main study

fields already discussed. Consequently, we analyze the share of nascent entrepreneurs in the

different field of study groups on the global level in a first step. We see that nascent

entrepreneurs are most prominent among BECL students (18.0%), with the share among NSM

and SSC students being significantly lower (13.5% and 10.1%, respectively).

To get more nuanced insights into country differences, we report the share of nascent

entrepreneurs among BECL, NSM, and SSC students in the different countries separately in

the following. While numbers are varying, the main underlying pattern that could be expected

based on our previous analyses can be confirmed.

%

49


54 54

40 39

30 2925 24 23 21 21 19 19 18 18 18 17 15 13 13 13 13 12 12 10 10 10 10 8 7 6 6 5

00

10

20

30

40

50

60

MY

S

AR

G

ME

X

RO

M

POL

CO

L

HU

N

RU

S

AU

S

SIN

LIE

GR

E

ES

T

USA

AV

ER

AG

E

EN

G

BR

A

CA

N

FRA

NE

D

FIN

ISR

JPN

SCO

DE

N

ES

P

BE

L

LU

X

ITA

SUI

AU

T

GE

R

SLO

POR

Figure 55: Share of nascent entrepreneurs among BECL students across countries

5247

39 38

27 2724 22 22

1916 14 14 14 13 13 11 11 10 10 10 10 9 8 7 7 7 6 6 5 4 4 4

00

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Figure 56: Share of nascent entrepreneurs among NSM students across countries

48

33

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19 19 17 15 14 14 14 13 13 13 1210 9 7 7 7 5 5 5 4 4 3 2 2 0 0 0

0

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Figure 57: Share of nascent entrepreneurs among SSC students across countries

In several parts of this report we have paid attention to gender differences. We also do that

with regard to nascent entrepreneurs and find that the share of nascent entrepreneurs among

male students is 20.3%, whereas the share among female students is 11.4%. Also when

investigating the different fields of study separately, female students are consistently less

likely to be nascent entrepreneurs, as the following figure shows.

%

%

%

50


24.0

17.6

15.9

14.1

8.5

8.4

0.0 5.0 10.0 15.0 20.0 25.0 30.0

BECL

NSM

SSC

Female

Male

Figure 58: Share of nascent entrepreneurs across gender and field of study

6.2 The planned firms

We now take a closer look at the firms that the abovementioned nascent entrepreneurs are

planning to create. The nascent entrepreneurs in our sample intend to found their firm in 13.2

months. They plan to invest 61.6% of their average weekly working time in their to-be-

created company (median=61). This shows that the new firms will most likely not be a full-

time job, at least in the phase immediately after the actual firm creation.

For detailed information about how far the nascent entrepreneurs have already proceeded in

the founding process, we asked them which gestation activities they already completed

(multiple answers possible). 18.1% have done none of the possible steps that our question

offered. Almost one third of the nascent entrepreneurs has already written a business plan.

The activities that have already been conducted the most are information collection about

markets and competitors and the discussion with potential customers. Taken together, we see

heterogeneity within the group of nascent entrepreneurs, whereby a considerable share of

nascent entrepreneurs has proceeded quite far in the founding process.

6.6

14.6

16.9

18.1

18.4

19.2

20.4

30.0

32.5

41.8

62.2

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

Applied for a patent, copyright or trademark

Registered the company

Attempted to obtain external funding

Nothing of the above done so far

Sold product or service

Started marketing or promotion efforts

Purchased material, equipment or machinery

Started product/service development

Wrote a business plan

Discussed product or business idea with potential customers

Collected information about markets or competitors

Figure 59: Gestation activities already conducted by nascent entrepreneurs

Regarding the industry sector where the planned firms will be active in, we see that the most

attractive sector is trade (wholesale/retail), followed by the “Other” category and

%

%

51


“Information technology and communication”. For students who selected the “Other”

category we offered the possibility to enter free text answers; however, no specific pattern

was visible when coding these answers. We have thus no reason to believe that an important

industry sector was missing in our comprehensive initial list.

18.4

16.6

13.2

8.8

8.6

6.8

6.8

6.1

5.9

4.84.0 Trade (wholesale/retail)

Other

Information technology and communication

Advertising / Marketing / Design

Tourism and gastronomy

Consulting (law, tax, management, HR)

Education and training

Other services (including finance, insurance, etc.)

Architecture and engineering

Health services

Construction and manufacturing

Figure 60: Industry sectors of planned firms

The nascent entrepreneurs in our sample intend to create their firm together with 1.27 partners

on average. As shown in the next figure, around one quarter of the nascent entrepreneurs

intend to create the firm alone, 35.8% with one partner, and almost one quarter with two

partners. Founding teams with four or more members are quite rare (12.9% in total).

27.3

35.8

24.0

7.95.0

No Co-Founders

1 Co-Founder

2 Co-Founders

3 Co-Founders

>3 Co-Founders

Figure 61: Number of co-founders among nascent entrepreneurs

%

%

52


Based on those insights, it is of interest if the nascent entrepreneurs will be minority or

majority owners in the planned firm. On average, their equity share will be 66%, with the

median being 61%. This clearly points to majority ownership. Having a closer look reveals

that only approximately every fourth nascent entrepreneur will own 49% or less of the firm’s

equity. Almost half of the nascent entrepreneurs will own between 50% and 99%, and almost

3 out of 10 nascent entrepreneurs will own all the firm’s equity.

7.6

14.5

48.9

29

Up to 24%

25-49%

50-99%

100%

Figure 62: Nascent entrepreneurs‘ equity share in the planned firm

Lastly, we asked the nascent entrepreneurs how new the service or product that the company

will offer in the market is compared to what is already offered in the market. Around 75% of

all nascent entrepreneurs report that their offerings will at least be new to some customers; the

remaining quarter of the planned firms will thus focus on imitating existing offerings. Almost

40% state that their products and services will be new to the majority of customers, and in

almost 18% of all cases, the offerings will be completely novel. These numbers illustrate the

high degree of innovativeness and newness among the planned firms.

17.8

39.218.6

24.3 New to all customers

New to majority ofcustomers

New to minority ofcustomers

Not new at all

Figure 63: Degree of newness of the planned firms’ offerings

%

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7 Active Entrepreneurs

7.1 Personal characteristics

GUESSS is not only interested in students’ entrepreneurial intentions, but also in their

concrete entrepreneurial activities. Hence, we identified students who are already running

their own business (who are already self-employed). Globally, 5.5% of all participating

students are already entrepreneurs (6’016 students).

As with the nascent entrepreneurs, the share of the so-called “active entrepreneurs” varies

considerably across countries. Reasons for that are manifold and may also partly be rooted in

sample specifications; nevertheless, we give a descriptive overview here. Results are quite

similar compared to the nascent entrepreneur analysis: highest rates can be found in

Argentina, Malaysia, and Mexico, whereby developing countries generally seem to have a

higher share of active entrepreneurs than developed countries.

2927

1613 13

11 109 9 8 7 7 7 6 6 6 6 5 5 5 5 5 4 4 4 4 4 4 3 3 3 3 2 1

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Figure 64: Share of active entrepreneurs across countries

An analysis of the share of active entrepreneurs according to study field interestingly shows

that active entrepreneurs are more prevalent in the social sciences than in the natural sciences

(see next figure). As expected, the share of active entrepreneurs is highest among BECL

students. Our analysis of the share of active entrepreneurs in the different study fields

depending on country did not reveal significantly different results compared to our previous

analyses. Hence, we do not report those results in detail here.

6.2

4.9

5.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0




Figure 65: Share of active entrepreneurs across study fields

%

%

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Also gender-wise we see important differences. 7.9% of all male students are active

entrepreneurs compared to only 3.8% of all female students. Divided by study field, we see

that the share of female active entrepreneurs is less than half in all fields. The gender gap

among active entrepreneurs thus seems to be even larger than among nascent entrepreneurs.

Interestingly, the share of male active entrepreneurs among SSC students is almost as high as

among BECL students (only 1.2% difference).

9.4

6.5

8.2

4.0

2.9

4.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0

BECL

NSM

SSC

Female

Male

Figure 66: Share of active entrepreneurs across gender and field of study

7.2 The existing firms

The already created firms are, on average, around 4 years old. As the following figure shows,

most of the firms in our sample have been created in 2013; 59% in 2011 or later. Almost one

fourth of all firms, on the other side, have been created in 2007 or earlier.

28.0

17.3

13.7

10.6

4.7

4.7

2.8

2.8

2.612.9

2013

2012

2011

2010

2009

2008

2007

2006

2005

Earlier

Figure 67: Founding years of the already created firms

On average, the active entrepreneurs spend 26.9% of their average weekly working time on

their own firm. This clearly signals that these firms are “side projects” where the students

only spend 1-2 days a week for. But still, this is a considerable amount of time, given that

full-time studies are done in parallel.

%

%

55


Regarding industry, we see a similar pattern as among nascent entrepreneurs: while the

“Other” category is the most frequently mentioned one among the active entrepreneurs, it is

very closely followed by “Trade (wholesale/retail)”, with “Information technology and

communication” being the third most attractive one. This shows that the intentions of nascent

entrepreneurs in which sector to create their firm seem to be quite stable.

19.4

19.0

13.69.1

9.0

7.1

6.6

4.6

4.1

3.93.6 Other

Trade (wholesale/retail)

Information technology and communication

Advertising / Marketing / Design

Education and training

Consulting (law, tax, management, HR)

Other services (including finance, insurance, etc.)

Health services

Architecture and engineering

Tourism and gastronomy

Construction and manufacturing

Figure 68: Industry sectors of already created firms

The average share of equity that the active entrepreneurs own is 68.7% (median=75%).

Almost 75% of all active entrepreneurs own at least 50% of the equity, with remarkable

44.1% of all entrepreneurs owning the firm completely (see following figure).

11.3

15.5

29.1

44.1Up to 24%

25-49%

50-99%

100%

Figure 69: Equity share of active entrepreneurs

Regarding co-founders, data shows that almost half of all active entrepreneurs have created

their firm on their own. Every fourth active entrepreneur has one co-founder. Interestingly, we

see that the planned number of co-founders among the nascent entrepreneurs is considerably

higher than among active entrepreneurs. As shown in chapter 6.2, only around one quarter of

%

56


all nascent entrepreneurs intends to create the firm alone; the average number of co-founders

among nascents is 1.27 compared to 0.91 among actives. This signals that some intentional

co-founders might still drop out during the firm creation process.

48.6

26.7

14.4

5.94.4

No Co-Founders

1 Co-Founder

2 Co-Founders

3 Co-Founders

>3 Co-Founders

Figure 70: Number of co-founders among active entrepreneurs

As to be expected, the average number of employees (full-time equivalents) is quite low (2.8).

In fact, 59% of all active entrepreneurs do not have any employees at all, which means that

their company is a classic “one-man/one-woman firm”. On the other hand, more than 20% of

all firms employ 2 or more employees, and almost 4% of the firms have more than 10

employees. We regard those numbers as encouraging, as they show the economic and also

social impact that students’ new ventures are obviously making.

59.019.2

7.0

8.3

2.6

3.9

0 employees

1 employee

2 employees

3-5 employees

6-10 employees

More than 10 employees

Figure 71: Employees (full-time equivalents) in the already created firms

Next to the current number of employees we are also interested in the growth intentions of our

active entrepreneurs. Hence, we asked them how many employees they intend to have in 5

years. For respondents where both numbers were available, we calculated the intended growth

rate. While there are a few outliers, we note that the median (the number where half of the

responses are below it and the other half above it) is 3. So the average active entrepreneur in

our sample plans to triple the size of his or her firm within the next 5 years.

%

%

57


A closer look at the data reveals that slightly more than 20% of all active entrepreneurs do not

plan to grow their firm at all. In that case, the firms are likely to stay a side-project or a one-

women/one-man show. Almost 40% of all active entrepreneurs, on the other side, plan to

grow their firm tenfold or more in the next five years, which we regard as an ambitious

number that illustrates the entrepreneurial thrive among those entrepreneurs.

21.7

17.5

6.614.7

25

14.5

No growth

Double

Triple

Quadruple

Tenfold

More than tenfold

Figure 72: Growth intentions of active entrepreneurs

Lastly, we assessed the performance of the students’ firms. For that purpose, we asked

students to rate the performance of their firm compared to its competitors since its

establishment from 1 (much worse) to 7 (much better). The relevant performance dimensions

were sales growth, market share growth, profit growth, job creation, and innovativeness.

The average value is 4.1, which corresponds to “equal performance”. A closer look at the

distribution of the answers reveals that almost two thirds of all respondents judge their firm as

showing performance that is roughly comparable to the competitors (from “slightly worse” to

“slightly better”. Very obviously under- or over-performing firms are quite rare. But still,

8.4% of the active entrepreneurs think their firm is performing “much better” than

competition.

4.77.1

12.9

26.925

15

8.4

Much worse

Worse

Slightly worse

Equal

Slightly better

Better

Much better

Figure 73: Performance of existing firms relative to competitors

%

%

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8 Summary and Conclusion

This report presents and discusses a high number of findings and in-depth insights into

students’ entrepreneurial intentions and activities. In the following, we will highlight a few

key learnings.

Referring to students’ career choice intentions in general, GUESSS 2013/2014

confirms the “first employee, then founder” pattern already found in previous editions

of GUESSS.

Directly after studies, 6.6% of all students want to work in their own firm; 5 years

later, this applies to 30.7% of all students.

As a general trend, entrepreneurial intentions are found to be strongest in developing

countries and weaker in developed countries. Thereby we emphasize that the absolute

values for developed countries are still quite high.

Referring to the main field of study, we find consistently that BECL students have

stronger entrepreneurial intentions that NSM or SSC students.

Our data shows significant differences in entrepreneurial intentions across gender.

Female students consistently exhibit lower entrepreneurial intentions compared to

male students.

Our investigation of the determinants of entrepreneurial intentions shows that the

university context in general and entrepreneurial learning at the universities in

particular are important antecedents.

In line with previous research we confirm that students with entrepreneurial parents

are more likely to become entrepreneurs themselves.

Personal career choice motives are found to be a driving factor behind career choice

intentions / entrepreneurial intentions as well.

The social and cultural context is identified as an important antecedent of

entrepreneurial intentions. Social pressure from individual’s immediate environment

as well as risk attitudes show a positive and negative relationship with entrepreneurial

intentions, respectively.

Very importantly, our analyses show that entrepreneurial intentions among students

across the globe have been decreasing in the majority of countries that took part both

in the GUESSS 2011 and in the GUESSS 2013/2014 edition.

Regarding the existence of nascent entrepreneurs, we find important cross-country

differences as well, whereby the “developing versus developed” country pattern is

visible again.

The planned firms will often be created by founding teams and show a considerable

level of innovativeness. The nascent entrepreneurs surveyed by GUESSS will be the

majority owners in the majority of cases.

59


Students who have already created an own firm are majority owners in the majority of

cases as well.

The existing firms are often run as “one man / one woman” firms. While many

entrepreneurs do not want to grow their firm in the next 5 years (21.7%), the share of

active entrepreneurs with high growth intentions is even higher (around 40% wish to

grow their firm tenfold or more in 5 years).

Based on those findings, we derive a few key recommendations for different stakeholders.

Universities

o Our findings illustrate the crucial importance of universities in the

development of entrepreneurial intentions. Hence, we call for more and better

entrepreneurship education offerings.

o We note, however, that entrepreneurship education can have a two-fold effect.

On the one hand, the positive effects of entrepreneurship education are

uncontested, as it may enhance students’ relevant skills and capabilities, and

may “prepare” them for an entrepreneurial career. On the other hand,

entrepreneurship education may make some students realize that becoming an

entrepreneur may also have disadvantages and that it is challenging and

difficult to be successful. Put differently, some students may have a bit of a

“romantic” or biased expectation of entrepreneurship and might be brought

“back to reality” by attending entrepreneurship education offerings. Hence,

entrepreneurship education could “sort” out students with unrealistic

expectations but make the “remaining” intentional entrepreneurs more

committed and more skilled.

Students

o As a general message, we encourage students to explicitly consider an

entrepreneurial career path. We do not say that everyone should become an

entrepreneur; but everyone should ideally consider if creating an own firm or

taking over an existing one is a viable option that matches one’s skills,

motives, and general preferences.

o As universities more and more offer entrepreneurship-related courses and

lectures, we encourage students to attend them to be better able to evaluate

entrepreneurship as a possible career path.

Public

o We show that student entrepreneurship can add value to society and economy

in general, as seen with the jobs already created and to-be-created by students’

entrepreneurial ventures.

60


o It is thus important to further improve the basic conditions and regulatory

frameworks for new ventures.

o This is even more important as we find that entrepreneurial intentions among

students have been decreasing over the last few years.

Researchers

o The sixth edition of GUESSS shows again the unique value that lies in

collaborative, international research efforts.

o The unique dataset that has been generated should be exploited in different

ways, be it for practitioner-oriented reports or academic publications.

o Investigating cross-cultural patterns and the influence of social and cultural

factors is a promising avenue for future research.

o Again, we emphasize that given the heterogeneity observed in the GUESSS

sample with regard to countries, universities, and students included, results

have to be interpreted with care.

In sum, with its sixth data collection wave, GUESSS again tries to contribute to global

research on students’ entrepreneurial intentions and activities, hopefully delivering enriching

insights for numerous stakeholders; not only in this report, but in many other publications to

come.

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Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. Thousand Oaks, CA: SAGE.

Laspita, S., Breugst, N., Heblich, S., & Patzelt, H. (2012). Intergenerational transmission of entrepreneurial intentions. Journal of Business Venturing, 27(4), 414-435.

Lima, E., Lopes, R. A., Nassif, V. M. J., & Silva, D. (2014). Opportunities to improve entrepreneurship education: Contributions considering brazilian challenges. Journal of Small Business Management, forthcoming.

Linan, F., & Chen, Y. W. (2009). Development and cross-cultural application of a specific instrument to measure entrepreneurial intentions. Entrepreneurship Theory and Practice, 33(3), 593-617.

Luethje, C., & Franke, N. (2004). Entrepreneurial intentions of business students: A benchmarking study. International Journal of Innovation and Technology, 1(3), 269-288.

Pennings, J. M. E., & Wansink, B. (2004). Channel contract behavior: The role of risk attitudes, risk perceptions, and channel members' market structures. The journal of business, 77(4), 697-724.

Sieger, P., Fueglistaller, U., & Zellweger, T. (2011). Entrepreneurial intentions and activities of students across the world : International report of guesss 2011. St.Gallen: KMU-HSG.

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Documents

Student Entrepreneurship Across the Globe: A Look … Entrepreneurship Across the Globe: A Look at Intentions and Activities International Report of the GUESSS Project 2013/2014 Philipp