Project 985 China entrepreneurship analysis

1. Does Institutional Change in
Universities Influence High-Tech
Entrepreneurship? Evidence from
China’s Project 985
Charles E. Eesley
Jian Bai Li
Delin Yang

2. Institutionalization
• Prior theory on institutionalization: 3 stages (Berger
and Luckmann, 1966; Tolbert and Zucker, 1996; Scott, 2013)
– Habituation: patterned behavior
– Objectification: shared meanings
– Sedimentation: exteriority
• Implicit assumption: relevant practitioners initiate
institutionalization process

3. Practitioner vs. Non-practitioner
• Practitioner initiates institutionalization:
– Habituated practices emerge out of repeated working
responses to real-life problems
– Objectification a posteriori: meanings analytically
abstracted from repeated practice
Habituation serves as a filter: institutionalized ideas,
structures, and practices must be viable within the
larger institutional environment

4. Practitioner vs. Non-practitioner
• Non-practitioner initiates institutionalization
– Insufficient knowledge of challenges practitioners face
and insufficient incentive to find workable practices to
tackle these challenges
– Objectification a priori: meanings synthetically
constructed or taken from another context
Institutional inconsistency: institutionalized beliefs and
practices don’t conform to the realities of the larger
institutional context

5. Research Question
How does institutional change that attempts to
institutionalize beliefs actually affect the behavior
and performance of their target organizations when
such beliefs are inconsistent with the larger
institutional environment?

6. Context: Project 985
• Gov't policy: launched May 4th, 1998
• Aim: increase the national innovative and
technological capability of China
– Increase beliefs about the importance of intellectual
property and innovation
– Provided funding to universities for R&D (10-20%
increase per year for 5 years)
• At discretion of the univ
• Equipment, labs, international conferences, attract overseas
researchers, new curricula
• Increased publication rates (Zhang et al., 2013)

7. Hypotheses
• Project 985 fosters local environments that are
conductive to the emergence of positive beliefs
regarding innovation and IP
– Teachers and research mentors
– Curriculum changes
– Opportunities to practice innovation in lab settings
H1: Alumni who graduate from 985 universities after the
implementation of Project 985 are more likely to hold the
belief that intellectual property protection is important.

8. Hypotheses
• Beliefs and strategic behavior
– Beliefs act as guides for how to interpret info & make
decisions (Rindova and Kotha, 2001; Tripsas, 2009)
– Belief in innovation and IP  propensity to engage in
innovation
H2: Firms founded by alumni who hold the belief that IP is
important are likely to invest more in technologically
intensive activities.

9. Hypotheses
• Innovation and IP is inconsistent with China’s
institutional environment
– Poor IP protection, contract laws, and judiciary
institutions (Xin and Pearce, 1996; Peng and Luo, 2000; Li and
Zhang, 2007)
H3: Firms that invest more in technologically intensive
activities are more likely to exhibit lower performance.

11. Survey Construction
• Refined our measures through in-depth interviews
with 42 entrepreneurs, investors, and government
officials.
– Better understand the context of our study and improve
the appropriateness and precision of our survey
questions.
• Follow-up phone calls with some of our
respondents after the surveys were collected to
gain better understanding of their answers.

12. Sample
• Population:
– 62.5% in engineering
11.9% in sciences
– 12.9% in humanities
(architecture, medicine
and law comprise the
remainder)
– 25-30% women19.2%
doctorate degrees
– 53.4% graduate
degrees
• Tsinghua survey
sample:
– 62.2% engineering
– 10.6% sciences13.7%
humanities
– 28% women
– 19.3% doctorate
degrees
– 53.9% graduate
degrees

13. Sample
• Tsinghua alumni survey:
– 723 entrepreneurs
– 570 - highest degree from 985 university
– 153 - highest degree from non-985 university
– Slight increase in entrepreneurship post-985, no
differences in human/social capital levels
• Advantages: difference in where individuals
received highest degree enables us to test our
hypotheses

14. Variables
• Dependent Variables
– H1: IP Importance, measure of alumni’s beliefs
regarding the importance of IP protection
– H2: ln(R&D intensity), measure of entrepreneurs’
activities regarding technology innovation
– H3: ln(Revenues), measure of performance (most recent
year)

15. Variables
• Independent Variables
– H1: Post*Treated, differences-in-differences estimator of
Project 985’s effects on beliefs regarding innovation
– H2: IP Importance
– H3: ln(R&D Intensity)

16. Variables
• Controls
– Human Capital (Overseas, Masters, PhD, serial)
– Social Capital (govindex, student leader, Communist
Party)
– University (Highest University Rank)
– Firm-level controls (Firm Size, firm age)
– Industry fixed effects
– Macroeconomic conditions (GDP)

17. Econometric Analysis
• H1: differences-in-differences analysis
– Treatment group: Tsinghua alumni who received
highest degree from 985 university
– Control group: Tsinghua alumni who received highest
degree from non-985 university
– Treatment and control universities are matched along
key attributes
– Pre - post difference based on graduation year
Model: IP Importance=ordinal logit(Post985, Treated,
Post985*Treated, Controls, Error)

18. Econometric Analysis
• H2: test direct effect of IP Importance on ln(R&D
Intensity)
• H3: test direct effects of ln(R&D Intensity) on
ln(Revenues)
Models:
H2: ln(R&D Intensity)=ols(IP Importance, Controls, Error)
H3: ln(Revenues)=ols[ln(R&D Intensity), Controls, Error]

25. Discussion
• RQ: how inconsistent institutionalization attempts
actually affect their target organizations
• Findings:
– Beliefs and practices can still become objectified in a
localized context—even if they’re inconsistent
– Inconsistent beliefs and practices do lead to lower
performance, such that they are unlikely to acquire
exteriority

26. “Yes Project 985…had a pretty big effect on how
I view innovation and IP. Before I had no idea
what IP even was…I mean everyone in China
downloaded stuff off of the internet and
bought [pirated] CD’s, and nobody really
cared [about IP]. Now I’m starting to see that,
if I want to make money off of my
innovations, then IP is pretty important.”

27. “I know that a lot of [Chinese] people are hyped
about technology entrepreneurship, but I
think that the kind of technology
entrepreneurship that happens in Silicon
Valley won’t work [in China]. People forget
that China is still a command economy, and
Silicon-Valley style innovation doesn’t work
so well in a command economy. So even if you
innovate, you still have to play by the
command economy rules…and that’s hard.”

28. Discussion
• Contributions:
– Boundary condition: distance between actors initiating
institutionalization and relevant practice
• Smaller distance  address inconsistency during
habituation
• Larger distance  inconsistency may not be apparent
until the sedimentation stage, when objectified beliefs
and practices come into contact with the larger
environment

29. Thank You!
Charles E. Eesley
Jian Bai Li
Delin Yang
Management Science and Engineering
Stanford University
cee@stanford.edu
jamberli@stanford.edu

31. Robustness Checks
• Alternative measures
– Factor created out of ip_importance, product
newness, and development time
– entrepreneurial performance by using
ln(Firm_size)
• Selection effects - two-step Heckman model

32. Robustness Checks
• University or Graduate School Effects
– Remove Tsinghua/Beida, non-grad students
• Alternative Explanations
– Increased the likelihood for individuals with lower
human or social capital to start new ventures
– Project 985 may have led to the founding of a few very
high-performing firms - Quantile regression