entrepreneurship productive, unproductive and destructive
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NETWORK SUPPORT AND THE SUCCESS OF NEWLY FOUNDED BUSINESS
BY JOSEF BRUDERL AND PETER PREISENDORFER
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FLOW OF PRESENTATION
• Introduction• Compensation and success theory• Social capital concept• Data, variables, and methods.• Empirical results• Bivariate results• conclusion
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INTRODUCTION
• Network resource, network activity & network support are heavily used to establish firms.
• Entrepreneurs who have a big broad and diverse network are more successful.
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COMPENSATION AND SUCCESS VIA SOCIAL SUPPORT
• Network approach to entrepreneurship
-Personal network
-Organizational network
• Entrepreneurship is “inherently a networking activity”
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• Social relations and social contacts are important channels for gaining access to information
• Network contacts give access to customers and suppliers
• Network contacts may open the possibility to broaden the financial basis of a new firm
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• Advantage of family network
-unpaid family work
-emotional support
-loyal employees
-control of workers
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THE SOCIAL CAPITAL CONCEPT
•Strategies to operationalize the network approach to Entrepreneurship.
•First strategy : The general characteristics of personal networks and explore the effects of these characteristic on business performance.
•Characteristics
•Network size, network density , network diversity, and network redundancy.
•Gives us the description of the network structure.
•The level of utilization of the network in terms of opportunity. Success comes when the entrepreneur makes use of the social network.
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•Second strategy: Looks at the activities carried out by entrepreneurs in the formation stage of their business and the amount of support received out of their network.
Characteristics• The number of people the entrepreneurs has talked to about
starting or running his business.
• To which degree he has mobilized strong or weak ties.• The number of hours he has discussed specific business matters
with friends and acquaintances.• This is more direct way of testing success hypothesis.
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FACTORS FOR SECOND STRATEGY
• Factor A) Based on opportunity structure an entrepreneur embedded in a broad & diverse social network will receive more help out of it.
• Factor B) Entrepreneur embedded in a confined social network or lacking in other basic resources ( Human capital or financial capital) will try harder to mobilize support out of its private network.
• In such conditions the entrepreneur puts in more efforts and succeeds by activating his private network resources which are his social contacts.
• Acc to Light & Karageorgis , Highly developed social networks can compensate shortfalls of the human capital.
•Entrepreneur resorting to social support start business that do not have good prospects because of critical dimensions. Only after gaining control over these critical dimensions one should observe the positive influence of social support.
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SUMMARIZING NETWORK APPROACH TO ENTREPRENEURSHIP
• 1) Based on the compensation hypothesis, entrepreneurs with lower stocks of human capital should make more use of social support during the start up period of their businesses.
• 2) Based on compensation hypothesis, entrepreneur initiating business with smaller amounts of financial start-up capital should receive more social support.
• 3) Based on compensation & success hypothesis simple Bi variate cross tabulations of social support measures and success indicators should show no or even negative effects of network support.
• 4) Based on success hypothesis , after controlling for human capital of founders and start up capital of new business positive influences of network support should show up.
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DATA
• The Munich Founder study
• Based on Interviews- 1990
• Sample Size of 1849
• Complex part- The firm were still in existance or not?
• Interview- Broad,Avg time
• First part- characteristics & devlopement
• Second part- Individual & networking
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STEPS AND OBSERVATIONAddress 6000 founders for Sample
Motivate them
1849 – Conducted interview(39 % response rate)
32% given up untill the date of survey- 1990
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VARIABLES
• Measuring amount of network support
Support from Strong ties
Support from weak ties
Active help from spouse
Emotional Support from Spouse
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SUCECESS VARIABLES
• Measures Organizational Success
- Survival (74%)
- Employment Growth
- Sales Growth(if more than 10%)
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Network Compensation Hypothesis
Ho: The business founders with less favorable human capital profile and with
restricted financial resources try harder to activate their social ties and
receive more support out of other networks.
• Human capital
1. Years of schooling
2. Years of work experience
3. Industry specific experience
4. Self- employment experiencing
5. Management experience
Start-up capital
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Including two more variables
• Gender(Female founder)
• Nationality(Non-German founder)
Nationality: not simply on not having German passport but only on the basis of
their language skills
OLS-regression
• Support from strong ties
• Support from weak ties
• Active help from spouse
• Emotional support from spouse
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Covariates Means of covariates
Support from Strong ties
Support from weak ties
Active help from spouse
Emotional help from spouse
Female founder
0.32 0.089 -0.024 0.341* 0.316*
Non-German founder
0.06 -0.007 -0.158 0.044 0.103
Years of schooling
13.11 -0.019* 0.012* -0.085* -0.027*
Years of work experience
14.53 -0.009* -0.010* 0.014* 0.002
Industry specific experience
0.56 0.061 0.122* -0.263* -0.056
Self employment experience
0.29 -0.134* -0.129* -0.103 -0.110
Management Experience
0.52 -0.055 0.053 0.104 -0.014
Start-up capital
7.08 0.024 0.008 0.071* 0.026
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• Female founder receive more support from strong ties, more active and
emotional support from spouse/life partner and less support from weak ties
• For Nationality the expected positive effects do not show up. Only positive
effect is Non-German founders receive less support from weak ties.
• Strong ties is only supporting the hypothesis that negative effects of our
human capital makes to mobilize more social support.
• Founders with more years of schooling receive less support from strong ties
and all except having strong support from weak ties.
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• Self-employment is consistently connected with all negative effects.
• Remaining 3 variables the pattern is mixed.
• Out of 11 significant human coefficients 8 have the expected negative
signs, so there might be some truth in Ho.
• Financial resource coefficient contradicts the hypothesis since it is +ve for
all variables.
• So, Ho is true only for human resources but not for financial resources.
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Network Success Hypothesis
Bivariate Results
Success or failure of a new firm can be extracted with:-
1. Individual characteristics of the founding person
2. Characteristics of the new firm itself
3. Characteristics of the environment of the firm.
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• Characteristics of the founding person-gender, nationality and
five human capital variables such as years of schooling, years
of work experience, industry specific experience, self
employment experience
• Characteristics of new firm-liability of newness(young firms
are prone to failure) and liability of smallness(small firms have
more chances of failure)
• Smallness and start up size-number of employees in the first
year, sales volume in first year
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BASELINE MODEL FOR THE SUCCESS OF NEW BUSINESS
Covariates Means of covariates
Survival Employment Growth
Sales Growth
Female Founder 0.32 0.025 (0.98) -0.152(3.70) -0.129(3.08)Non German Founder
0.06 -0.044(0.85) -0.050(0.58) 0.055(0.63)
Years of schooling
13.11 0.017(3.97) 0.001(0.12) -0.015(2.31)
Years of work experience
14.53 0.004(3.42) -0.006(3.34) -0.007(3.61)
Industry specific experience
0.56 0.104(4.36) 0.092(1.92) 0.125(2.49)
Self employment experience
0.29 -0.033(1.24) -0.007(0.19) -0.027(0.69)
Management experience
0.52 0.011(0.46) -0.053(1.55) -0.005(0.13)
Follower Business
0.24 0.053(1.82) -0.109(2.8) -0.173(4.16)
Start up capital(natural log)
7.08 0.007(2.51) 0.011(2.53) 0.016(3.07)
No. of employees in first year(natural log)
0.24 0.046(3.08) 0.031(1.63) 0.018(0.83)
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Covariates Means of covariates
Survival Employment Growth
Sales Growth
Sales volume in first year(natural log)
11.17 - - -0.047(6.47)
Registered in commercial register
0.20 0.185(5.38) 0.108(2.07) 0.053(0.99)
Industry: manufacturing
0.04 0.234(5.69) 0.068(1.19) -0.010(0.17)
Industry: construction 0.01 0.210(3.29) -0.061(0.72) 0.004(0.04)
Industry: wholesale trade
0.11 0.008(0.20) 0.009(0.17) 0.058(0.96)
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Covariates Means of covariates
Survival Employment Growth
Sales Growth
Industry: sales intermediaries
0.05 -0.013(0.23) 0.064(0.76) 0.023(0.25)
Industry: transportation
0.09 -0.076(1.61) -0.047(0.58) -0.066(0.85)
Industry: insurance
0.07 -0.018(0.36) -0.137(1.35) -0.140(1.07)
Industry: restaurant
0.08 -0.061(1.28) -0.116(1.15) -0.162(1.56)
Industry: education/publishing
0.03 0.089(1.27) -0.102(1.00) 0.026(0.25)
Industry: consultation
0.18 0.035(0.91) 0.093(1.64) 0.065(1.01)
Industry: other services
0.09 0.020(0.41) -0.078(1.08) -0.117(1.59)
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MULTIVARIATE ANALYSIS • It is based on the statistical principle, which involves observation
and analysis of more than one statistical variable at a time
• Indicates that high network support increases the probability of
survival and growth
• Support from strong ties shows more convincing effects than
from weak ties measure.
• Support from family network increases success than compared to
outside network
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Network support varibles
survival Employement growth Sales growth
Support from strong ties(Medium)
0.056*(1.97) 0.037(0.88) 0.033(0.71)
(High) 0.093*(3.04) 0.068(1.46) 0.178*(3.21)
Support from weak ties (Medium)
0.005(0.19) 0.019(0.53) 0.075(1.92)
(High) 0.058(1.69) 0.046(1.00) 0.138*(3.63)
Active help from spouse (Medium)
0.105*(3.57) 0.068(1.57) 0.091(1.88)
(High) 0.093*(3.43) 0.018(0.45) 0.095*(2.23)
Emotional support form spouse (Medium)
0.017(0.58) 0.074(1.78) 0.045(0.99)
(High) 0.075*(2.77) 0.065(1.51) 0.078(1.65)
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CONCLUSION• Network approach to entrepreneurship
• Support from personal network improves survival and growth of newly founded business
• Support from strong ties is important
• No confirmation that entrepreneurs compensate shortfalls of human and capital by resorting to network but partial confirmation with respect to human capital
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LIMITATIONS ON THE RESEARCH
• Did not look at the organizational network
• No information about the network founding
• Data is confined to German region
• Measurement of networking variables