Education, Training and Networking for Entrepreneurship in ...

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Table 9.7 Competency of entrepreneurs, by their training Entrepreneurs in Denmark 2008 Trained Not trained Competent 76 % 70 % Less competent 24 % 30 % Sum 100 % 100 % N entrepreneurs 94 206 ing. However, the difference in the small sample is not statistically significant (the probability value is 0.18 in a one-sided chi-square test). Entrepreneurs have a network of advisors with a size that may be small or large. Is entrepreneurs’ network size related to their education? Table 9.8 distinguishes between large networks and small networks and also calculates the average network size within each educational group. Our sample of entrepreneurs within each educational group is small, so small as to render inferences hard. The size of the entrepreneurs’ network appears not to be systematically related to their education in a statistically significant manner (the probability-value is 0.24 for the chi-square test of the cross-tabulation, and the p-value is 0.19 in the anova F-test of differences among the five group-means). In further research during 2009, I will examine the relationship of entrepreneurs’ education to their networking. Table 9.9 Size of entrepreneurs’ advisory network, by their training Starters and owner-managers in Denmark 2008 Trained Untrained Large network 64 % 38 % Small network 36 % 62 % Sum 100 % 100 % Mean size 8,5 6,3 N entrepreneurs 66 159 Entrepreneurs’ advisory network is related to their training, Table 9.9. Trained entrepreneurs network more extensively than untrained entrepreneurs (the difference is statistically highly significant, with p-value 0.0002 in the one-sided chi square test of the cross-tabulation, and p- value 0.0002 in a one-sided t-test of the difference between the two means). Entrepreneurs’ network is also related to their competency to start a business, Table 9.10. Competent entrepreneurs network more extensively than entrepreneurs who do not have this competency (the difference is statistically significant, with p-value 0.02 in the one-sided chi square test of the cross-tabulation, and p-value 0.01 in a one-sided t-test of the difference between the two means). Table 9.8 Size of entrepreneurs’ advisory network, by their education Starters and owner-managers in Denmark 2008 Vocational Short higher Medium higher Long higher Neither education education education education vocational nor higher education Large network 52 % 27 % 50 % 42 % 50 % Small network 48 % 73 % 50 % 58 % 50 % Sum 100 % 100 % 100 % 100 % 100 % Mean size 7,4 5,9 7,5 6,1 7,8 N entrepreneurs 50 26 60 57 30 63
Table 9.10 Size of entrepreneurs’ advisory network, by their competency Starters and owner-managers in Denmark 2008 Competent Less competent Large network 50 % 33 % Small network 50 % 67 % Sum 100 % 100 % Mean size 7,4 5,7 N entrepreneurs 174 45 The above cross-tabulations have examined the relationship between two phenomena at a time, ignoring that the relationship may be affect by other conditions. The above analyses are thus preliminaries to an analysis that considers each phenomenon to have several causes. This more elaborate analysis comes next. Effects among entrepreneurs’ education, training, competency and networking The question now is, what are the effects among entrepreneurs’ education, training, competency and networking? More precisely, how is network size affected jointly by competency, training and education? How is competency affected jointly by training and education? How is training affected by education, while also taking other conditions into consideration, such as gender and age of the entrepreneurs? what the effects of education are upon networking. The effects upon entrepreneurs’ competency from training and education are estimated by regression (Table 9.12 in the Appendix). Entrepreneurs’ training promotes their competency, as we would expect. The frame of reference for ascertaining the effects of education is long higher education. Entrepreneurs with medium or short higher education tend to be less competent than entrepreneurs with long higher education. Entrepreneurs who have neither vocational nor higher education also tend to be less competent than entrepreneurs with long higher education. Vocationally educated entrepreneurs tend to be as competent as entrepreneurs with long higher education. The effects upon entrepreneurs’ training from education are estimated by regression (Table 9.11 in the Appendix). Entrepreneurs with vocational education, with short or medium higher education, or without vocational or higher education have received training more frequently than entrepreneurs with long higher education. In other words, entrepreneurs with long higher education have especially rarely been trained in starting a business. These estimated effects are shown in Figure 9.2, where a positive effect is shown as a solid arrow and a negative effect as a dashed arrow, and the magnitude of an effect is shown by the thickness of the arrow. The effects upon entrepreneurs’ network size from competency, training and education are estimated by regresssion (Table 9.13 in the Appendix). Training has a very large and positive effect upon networking. Competency also has a large and positive effect upon networking. The effects of the various levels of education are hard to estimate because the size of the sample in each educational group is small, so small that we do not obtain statistical significance when testing the effects. So we cannot conclude, with any reasonable confidence, 64
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Education, Training and Networking
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© Thomas Schøtt (and GERA for ite
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Contents Preface ..................
Page 9 and 10:
skab i samfundet, både i Danmark o
Page 11 and 12:
Figur B Entreprenørers ekspansivit
Page 14 and 15: Part 1 Introduction Chapter 1 Is en
Page 16 and 17: How is entrepreneurs’ innovativen
Page 18: ing years, in Denmark and in the ot
Page 21 and 22: The ex-owner-managers are those ans
Page 23 and 24: our survey counting new-business ow
Page 25 and 26: In this chapter, we shall examine e
Page 27 and 28: In short, although entrepreneurial
Page 29 and 30: - In Denmark, there is sufficient d
Page 31 and 32: Where is Denmark positioned compare
Page 33 and 34: - In Denmark, the markets for consu
Page 35 and 36: Table 4.24 Intellectual property ri
Page 37 and 38: The framework overall The framework
Page 39 and 40: provides ample opportunity (and, ty
Page 41 and 42: an arrow represents the magnitude o
Page 43 and 44: Figure 5.4 Plot of developed societ
Page 45 and 46: provided by a college or university
Page 47 and 48: Table 6.3 Training of people, durin
Page 49 and 50: Age and training Does training diff
Page 51 and 52: Chapter 7 People’s education, tra
Page 53 and 54: Table 7.4 Networking, by education
Page 55 and 56: Chapter 8 People’s vocation shape
Page 57 and 58: Table 8.4 Vocation of adults, by th
Page 60 and 61: Part 4 entrepreneurs Chapter 9 Entr
Page 62 and 63: Table 9.1 Education, by vocation Ad
Page 66 and 67: Figure 9.2 Estimated effects among
Page 68 and 69: The response to each question can b
Page 70 and 71: Figure 10.2 Estimated effects upon
Page 72 and 73: entation, Table 11.1. Entrepreneurs
Page 74 and 75: ed by regression (Table 11.6 in the
Page 76 and 77: future. To measure such expectation
Page 78 and 79: Growth-expectations and competency
Page 80 and 81: Part 5 CONCLUSIONS Chapter 13 Expan
Page 82 and 83: Figure 13.1 People’s vocation aff
Page 84: Figure 13.2 Entrepreneurs’ expans
Page 87 and 88: Table 5.4 Linear regression of nati
Page 89 and 90: Table 7.9 Logistic regression of ad
Page 91 and 92: Table 8.9 Logistic regression of ad
Page 93 and 94: very small. The estimated effects a
Page 95 and 96: Table 12.6 Linear regression of gro
Page 98 and 99: Bibliography Ahmad, N., and A. Hoff
Page 100 and 101: myths. Paper for the 3 rd Internati
Page 102 and 103: sættere i netværk” In Freytag,
Page 104 and 105: National Teams in 2008 in Global En
Page 106 and 107: Team Institution National Team Memb
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Thomas Schøtt University of Southe
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