armanios august aom

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Government Officials or Mixed Institutions: How Do Ventures Acquire Public Sector Investment in Emerging Economies? Daniel E. Armanios, Stanford University Chuck E. Eesley, Stanford University Li Jizhen, Tsinghua University Kathleen M. Eisenhardt, Stanford University Academy of Management Conference, Boston, MA, August 6, 2012

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Page 1: Armanios august aom

Government Officials or Mixed Institutions: How Do Ventures Acquire Public Sector Investment in Emerging Economies?Daniel E. Armanios, Stanford UniversityChuck E. Eesley, Stanford UniversityLi Jizhen, Tsinghua UniversityKathleen M. Eisenhardt, Stanford University

Academy of Management Conference, Boston, MA, August 6, 2012

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Motivation•How ventures acquire financing in emerging economies remains unclear (Batjargal & Liu 2004; Vissa 2011)

• Public sector an important financing source in emerging economies• Average assets of state-owned banks nearly

2x privately owned banks in emerging economies (Dinç 2005)

• In China, 46% domestic financing sources in public sector(figures from NBSC 2011; CBRC, 2010)

• Scholarship focuses on public sector perspective (Cuervo-Cazurra & Dau, 2009; Mahmood & Rufin, 2005, Spicer

et al, 2005) and not venture perspective

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Introduction• Two Possible Pathways for Public Sector Investment Acquisition

• Government Official Ties (Park & Luo, 2001; Xin and Pearce, 1996)

• Mixed Institutions (Science Parks) (McDermott et al, 2009; Nee 1992, Peng & Heath, 1996)

• Research Questions:1) How do private ventures in emerging

economies acquire public sector investment: government officials or mixed institutions?

2) Are these pathways complements or substitutes?

3) What are the implications of these pathways for venture performance?

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Hypotheses (1)

•Government officials can help ventures gain access to public sector financing (Park & Luo 2001)

•Depends upon entrepreneur’s social capital (Chen & Chen, 2004, Fei 1947/1992, Hermann-Pillath 2010)

•Hypothesis 1a: Ventures whose entrepreneurs have preexisting ties to government officials are more likely to acquire public sector investment.

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Hypotheses (2)• Science Parks gain legitimacy through government backing(McDermott et al, 2009; Tan 1999, 2006)

•With this legitimacy, science parks can: • certify a venture’s quality (Sine et al, 2007)

• leverage public stakeholders to facilitate connections between venture and public sector

•Does not depend upon social capital but upon entrepreneur’s human capital

•Hypothesis 1b: Ventures who are members of mixed institutions such as science parks are more likely to acquire public sector investment.

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Hypotheses (3)•Government officials and science parks produce same outcome yet both incur costs• Government officials: reciprocity costs (Chen

& Chen 2004, Hwang 1987)

• Science Parks: rental costs, fees, and/or equity stake(Grimaldi & Grandi, 2005)

•Hypothesis 1c: Mixed institutions such as science parks help those ventures without government official ties more likely acquire public sector investment.

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Hypotheses (4)• Public sector houses significant financial resources and power over allocation(Acquaah 2007; Li & Atuahene-Gima 2001, Nee 1992; Peng & Luo 2000; Walder 1995)

• Public sector investment provides added benefits over private sector investment• Heightened credibility(Gu 1996; Tan 1999, 2006)

• Protection from political uncertainty(Acquaah 2007; Peng & Luo 2000; Li & Zhang 2007)

•Hypothesis 2: Acquiring public sector investment increases venture performance.

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Research Design•Haidian District: science parks/non-science park firms within same district (controls for district-level policy differences)

•Matched Sample (O’Connor et al., 2006; Obloj & Capron, 2011)

• Ensures treatment (science parks) matched w/most similar control (non-science park)• Surveyed 81 science park, 65 non-science

park firms • N=94 matched science park and non-

science park firms (matching controls: industry and age)

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Measures•Dependent Variables• Public Sector Investment (H1a, H1b, H1c)• Patents (H2)• Venture Growth (H2)

• Independent Variables• Government Official Ties • Science Park

• Additional Controls (industry, policy, age controlled in matching and district selection)• VentureSize2010

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Statistical Methods• Instrumental Variable Analysis• Instrument: Science Park Entry Help• F=18.8: strong instrument• r=0.69 w/Science Park, r=0.16, -0.07, -0.13

w/Public Sector Investment, Patents, and Venture Growth, respectively: indication (but not definitive proof) of instrument’s exogeneity

• Science Park’s Selection Criteria: Market Potential, TMT quality, Sales and Finance Experience

• Public Investment & Patents: P-QMLE, Negative Binomial, Venture Growth: OLS

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Results (1)

N=94

ControlP-QMLE

Model 1

P-QMLE

Model 2P-QMLE

Model 3 P-QMLE

Model 4a P-QMLE

Model 4bNeg Bin

Model 4cOLS

Model 4dIV

(Intercept) 0.687* 0.639* 0.158 0.033 -0.095 -0.095 0.563 0.419

(0.319) (0.328) (0.302) (0.291) (0.303) (0.303) (0.599) (0.807)

Venture Size20100.035 0.026 0.147+ 0.144* 0.115+ 0.115+ 0.247+ 0.216

(0.114) (0.107) (0.094) (0.082) (0.076) (0.076) (0.187) (0.236)

Gov’t Official Ties   0.167   0.258* 0.621** 0.621** 1.106** 1.143*

H1a   (0.165)   (0.155) (0.213) (0.213) (0.401) (0.492)

Science Park     0.605*** 0.660*** 0.963*** 0.963*** 1.950*** 2.184***

H1b     (0.167) (0.174) (0.212) (0.212) (0.425) (0.610)

Gov’t Official Ties * Science Park

        -0.762** -0.762** -1.473* -1.660*

H1c         (0.325) (0.325) (0.683) (0.890)

Science Park Type Fixed Effects

Included Included Included Included Included Included Included Included

pseudo-R2 0.064 0.079 0.210 0.247 0.319 0.319 0.296 0.194***p<0.001,**p<0.01,*p<0.05,+p<0.10 (one-tailed)

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Results (2)

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Results (3)

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Results (4)N=94

ControlOLS

Model 1aOLS

Model 1bIV

(Intercept) -83.372+ -90.357+ -104.658*(55.687) (55.331) (61.151)

Venture Size201036.622* 33.959* 36.800*(20.332) (17.422) (18.018)

Gov’t Official Ties7.042 2.081 2.553(11.931) (10.345) (14.148)

Science Park10.746 -2.886 2.482(12.150) (10.251) (18.129)

Public Sector Investment   9.437+ 12.246+H2   (6.494) (7.780)

Science Park Type Fixed Effects Included Included Included

pseudo-R20.382 0.423 0.456***p<0.001,**p<0.01,*p<0.05,+p<0.10 (one-tailed)

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Results (5)

N=94

ControlP-QMLE

Model 1aP-QMLE

Model 1bNeg Bin

Model 1cOLS

Model 1dIV

(Intercept) -0.785 -1.551* -1.805* -2.027+ -1.871(0.762) (0.915) (0.784) (1.576) (1.711)

Venture Size20100.502* 0.565* 0.682*** 0.996* 0.749(0.219) (0.264) (0.217) (0.601) (0.589)

Gov’t Official Ties0.381 -0.124 0.056 0.230 1.085(0.368) (0.380) (0.410) (0.815) (1.041)

Science Park -0.370 -1.047* -0.591 -1.802+ -0.536(0.548) (0.573) (0.634) (1.176) (1.853)

Public Sector Investment   0.443*** 0.350* 0.985* 0.740+H2   (0.099) (0.164) (0.429) (0.543)

Science Park Type Fixed Effects Included

Included Included Included Included Included

pseudo-R20.115 0.233 0.172 0.188 0.134 One-tailed hypothesis testing: ***p<0.001,**p<0.01,*p<0.05,+p<0.10

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Summary

• Two pathways to acquire public sector investment• Personal Ties to Gov’t Officials• Mixed Institutions (Science Parks)

• These pathways are substitutes

• Acquiring public sector investment increases performance

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Discussion & Contributions•Networks• Social capital or network actions->tie

formation (Hallen & Eisenhardt 2012, Powell et al 1996)

• Here: mixed institutions->tie formation (particularly those lacking social capital)

• Institutions• Mixed institutions->performance (theory, Nee 1992)• Here: Mixed institutions->performance (test)

• Emerging Economies• Gov’t Ties->Performance(Li & Zhang 2007, Peng & Luo 2000)

• Market Institutions->Performance(Cuervo-Cazurra & Dau 2009)

• Here: Mixed Institutions->Performance

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Acknowledgements• US NSF EAPSI program• NSF Graduate Research Fellowship• Stanford Graduate Research

Fellowship• Stanford Technology Ventures

Program• Qin Lan• Li Xiaoqi• Wang Yiran• Kou Yixin• Mao Liqing• Lin Xin• Qian Jin Jian• Luo Jing• Li “Frank” Heng• Mengying Zhang• Xuan Ping Lim

• Li Sha• Klaus Meyer• Riitta Katila• Robert Eberhart• Marc Schneiberg• Henning Piezunka• Walter Powell• Daisy Chung• Dan Wang• Curtiss Cobb• Yishen Wang• Hong Yun• Zheng Feng• Liu Tong• Mo Yingchuan• Chen Rui

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Thank You!

•Questions or comments? Email: [email protected]

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Appendix (1): Robustness Checks• Counterargument #1: Science parks select those w/government ties (t-tests indicate firms with government ties outside science park)• Counterargument #2: Government ties signal of venture quality (t-tests between science/non-science park and with/without gov’t ties show no performance differences)• Counterargument #3: Private Sector Investment not Public Sector Investment matters more (with Private Sector Investment included, Public Sector Investment still matters more)

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Appendix (2): Backup Material for Questions•Handling nonlinearity in IV Analysis