Education, Training and Networking for Entrepreneurship in ...

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Table 8.7 Logistic regression of adults’ vocation, prospective starter contrasted non-entrepreneurs Adults (only non-entrepreneurs and prospective starters) in Denmark 2003-08 Coefficient Odds ratio Probability-value Medium higher education 0,0 1,0 Short higher education 0,1 1,1 0,61 two-tailed Vocational education - 0,1 0,9 0,25 two-tailed Neither higher nor voc. ed. - 0,2 0,8 0,02 two-tailed Competency 1,6 4,7 0,0001 one-tailed Networking with starter 0,9 2,5 0,0001 one-tailed Gender (female 0, male 1) 0,2 1,2 0,0002 one-tailed Age (logarithmic) - 1,4 0,2 0,0001 one-tailed Constant 1,3 Training * 0,3 1,3 0,08 one-tailed N = 16.889 adults * Estimated by 2008 data regression estimates using the data for 2003-08 and also the estimated effect of training using the data from 2008 (with 2012 surveyed adults), as marked with an asterix. The regression in Table 8.6 examines vocation by contrasting entrepreneurs with non-entrepreneurs. Some independent variables are not always causally prior to vocation, but are often effects of vocation, notably does being an entrepreneur such as an owner-manager often affect competency and networking. To better estimate the effects of competency, networking and the other independent variables upon vocational choice; we can contrast the non-entrepreneurs with entrepreneurs in the earliest phase, the prospective starters, as here in Table 8.7. The results are fairly similar to those in Table 8.6, notably both competency and networking, have positive effects. Table 8.7 is not used Table 8.8 Logistic regression of adults’ vocation, starter contrasted non-entrepreneur Adults (only non-entrepreneurs and starters) in Denmark 2003-08 Coefficient Odds ratio Probability-value Medium higher education - 0,1 0,9 0,52 two-tailed Short higher education 0,2 1,2 0,26 two-tailed Vocational education - 0,4 0,6 0,0001 two-tailed Neither higher nor voc. ed. - 0,5 0,6 0,001 two-tailed Competency 1,4 4,1 0,0001 one-tailed Networking with starter 0,9 2,4 0,0001 one-tailed Gender (female 0, male 1) 0,4 1,6 0,0001 one-tailed Age (logarithmic) - 0,4 0,7 0,001 one-tailed Constant - 3,0 Training * 0,3 1,3 0,14 one-tailed N = 17.514 adults * Estimated by 2008 data 89
Table 8.9 Logistic regression of adults’ vocation, owner-manager contrasted non-entrepreneur Adults (only non-entrepreneurs and owner-managers) in Denmark 2003-08 Coefficient Odds ratio Probability-value Medium higher education - 0,3 0,7 0,0001 two-tailed Short higher education - 0,1 0,9 0,20 two-tailed Vocational education - 0,3 0,8 0,0003 two-tailed Neither higher nor voc. ed. - 0,2 0,8 0,02 two-tailed Competency 1,8 6,0 0,0001 one-tailed Networking with starter 0,8 2,3 0,0001 one-tailed Gender (female 0, male 1) 0,5 1,7 0,0001 one-tailed Age (logarithmic) 0,8 2,1 0,0001 one-tailed Constant - 6,6 Training * - 0,2 0,9 0,23 one-tailed N = 17529 adults * Estimated by 2008 data for any figure in the monograph, but is included here to show robustness of results. The robustness of estimated effects can also be examined by focusing on vocation in a contrast between non-entrepreneurs and starters, as here in Table 8.8. The results are similar. Table 8.8 is not used for any figure in the monograph, but is included here to show robustness of results. Effects are also estimated for vocation as a contrast between non-entrepreneurs and ownermanagers, as here in Table 8.9. The coefficients are fairly similar to those in the regresssions using staters or prospective starters (the estimated coefficient for training is here negative, but quite insignificant). Table 8.9 is not used for any figure in the monograph, but is included here to show robustness of results. Notes to Chapter 9 Figure 9.2 in Chapter 9 is based on Tables 9.11, 9.12 and 9.13. The unit of analysis is an entrepreneur. The sample is the entrepreneurs identified in our surveys of adults in Denmark. The sample of entrepreneurs is fairly representative of the population of entrepreneurs in Denmark, because the sampled adults are a fairly representative sample of the population of adults in Table 9.11 Logistic regression of entrepreneurs’ training Entrepreneurs in Denmark 2008 Coefficient Odds ratio Probability-value Medium higher education 0,5 1,7 0,17 two-tailed Short higher education 0,5 1,7 0,24 two-tailed Vocational education 0,5 1,7 0,19 two-tailed Neither vocational nor hi ed 0,4 1,5 0,33 two-tailed Gender (female 0, male 1) 0,2 1,2 0,24 one-tailed Age (logarithmic) - 0,9 0,4 0,01 one-tailed Constant 2,1 N = 305 entrepreneurs 90
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Education, Training and Networking
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© Thomas Schøtt (and GERA for ite
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Contents Preface ..................
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skab i samfundet, både i Danmark o
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Figur B Entreprenørers ekspansivit
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Part 1 Introduction Chapter 1 Is en
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How is entrepreneurs’ innovativen
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ing years, in Denmark and in the ot
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The ex-owner-managers are those ans
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our survey counting new-business ow
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In this chapter, we shall examine e
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In short, although entrepreneurial
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- In Denmark, there is sufficient d
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Where is Denmark positioned compare
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- In Denmark, the markets for consu
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Table 4.24 Intellectual property ri
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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 64 and 65: Table 9.7 Competency of entrepreneu
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: Table 7.9 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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Page 114: Thomas Schøtt University of Southe
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