- Two studies on early-stage entrepreneurship: a MOOC experiment and analysis of Stanford alumni data - The MOOC experiment found that entrepreneurs with mentors who had diverse networks performed better when using an adaptive approach, while a planning approach generally led to better outcomes - The alumni data study examined the effects of strategic changes in startups, finding that changes to minor areas of a business close to the core and a diverse founding team were associated with increased chances of IPO

1. Early Venture Evolution PDW
Chuck Eesley (Stanford University)
Lynn Wu (U. Penn – Wharton)
Wesley Koo (Stanford University)
David Hsu (U. Penn – Wharton)

2. Quick overview – 2 studies
• Early stage – MOOC randomized experiment
• Later stage – Stanford alumni data

3. Visions, Entrepreneurial Adaptation
and Social Networks:
Evidence from a Randomized Experiment on a
MOOC Platform
Charles Eesley (Stanford)
Lynn Wu (Wharton)

4. Early-stage programs
• Accelerator and incubator programs outside of
universities, such as YCombinator, TechStars and
the Founder Institute
• National Science Foundation has recently
launched an $18M program to pair select
engineers and scientists who win SBIR grants with
mentors and to teach them a more adaptive
process for startup creation (I-Corps)

5. Difficult to Observe Entrepreneurial
Processes
Planning Approach
• Create an unwavering vision
• Persistent in executing the
vision
• Less likely to modify the vision
to leverage newly available
resources
• Delmar and Shane, 2003;
Porter, 1980
Adaptive Approach
• Take adv. of new resources and
change the vision if necessary
• Suitable in uncertain
environment such as early stage
entrepreneurship?
• (Baker and Nelson 2005, Blank
2013, Brown and Eisenhardt
1997, McGrath 2010)

6. Networks & Entrepreneurial Strategy
Adaptive & Network
Diversity
• Mentor with diverse networks
offers new and novel
information and opportunities.
• Adaptive entrepreneurs are
likely to take advantage of the
new resources.
Planning & Network
Diversity
• Entrepreneurs would not
always use the resources from
a mentor unless it conforms
with the original vision.
• A mentor in a cohesive
network may collaborate
better with the entrepreneur.

7. Networks & Entrepreneurial Strategies
• Difficult to observe endogenous matching
process between mentors and mentees.
• Difficult to alter coworker and friendship ties.
• Difficult to observe the process of
entrepreneurship.
• Randomized experiments could help.

8. Setting & Data
• NovoEd class: Technology Entrepreneurship
• Class offered: Fall 2013 for 8 weeks
• Free to anyone
• Students in 61 countries in the world
• Goal: Create a video pitch at the end of the
class

9. Summary Statistics
Variable Obs. Mean Std. Dev. Min Max
English 1670 .588 .492 0 1
Male 1670 0.741 .438 0 1
Age 1670 2.169
(25-35)
.833 1 4
Final Grades 1410 11.649 2.858 3.288 19.971
Complete
any assign.
23918 .138 .345 0 1
Completion 23918 .0602 .458 0 1

10. Treatment Effects On Outcomes
(1) (2) (3) (4) (5)
Dependent
var.
Completed
Class
Final Grade Final Grade Earlier Grade Earlier Grade
Diverse -0.00273
(0.00774)
0.298
(0.269)
0.333
(0.267)
0.0499
(0.160)
0.0567
(0.159)
Diverse
Adaptive
0.00591
(0.00773)
0.448*
(0.265)
0.434*
(0.266)
-0.0824
(0.158)
-0.0652
(0.157)
Diverse
Planning
0.00575
(0.00773)
0.511**
(0.256)
0.451*
(0.259)
0.188
(0.158)
0.192
(0.157)
Planning 0.0134*
(0.00773)
0.525*
(0.302)
0.541*
(0.303)
0.125
(0.157)
0.125
(0.156)
Obs. 23,918 1,411 1,411 4,866 4,866

11. Mentors and Performance
(1) (2) (3)
Dependent var. Final Grade Final Grade Final Grade
Found a Mentor 0.974**
(0.376)
0.718*
(0.394)
0.762*
(0.390)
# Mentors
Approached
-0.0110
(0.0232)
-0.0144
(0.0229)
Having a Diverse
Mentor
0.683*
(0.373)
0.593
(0.370)
Pursued Adaptive
Approach
0.588
(0.405)
0.592
(0.411)
English 0.0208
(0.249)
Male -0.0768
(0.216)
Age 0.381***
(0.128)
Obs. 1,080 1,075 1,075

12. Effects of Strategic Change on Venture Performance:
The Implications of Change Location, Level and Top
Management Team Composition
Charles Eesley
Stanford University
David Hsu
Wharton School, Management Department,
University of Pennsylvania
Wesley Koo
Stanford University

13. Stanford Alumni Data
• Survey of 143,482
individuals—all living
Stanford alumni, current
faculty and selected
(research) staff—to explore
the influence of education on
life and career choices.
• Responses were received
from 27,780 individuals, for a
response rate of 19.5
percent.
• These numbers are the
percentage of respondents
out of the total number in
that category who received
the email.
– Women: 19%
– Men: 19%
– Business: 23%
– Earth Sciences: 30%
– Education: 30%
– Engineering: 22%
– Law: 20%
– H&S: 13%
– Medicine: 27%

15. IPO
minor, core 0.383** 0.409**
(0.120) (0.125)
major, core -0.0264 0.0953
(0.130) (0.136)
minor, peripheral 0.225+ 0.296*
(0.129) (0.135)
major, peripheral 0.152 0.229+
(0.122) (0.127)
industry fixed
effect
Y Y Y Y Y Y
department fixed
effect
Y Y Y Y Y Y
_cons -15.85 -15.87 -15.65 -15.86 -15.44 -15.32
(13.79) (13.74) (13.80) (13.80) (13.73) (13.80)
N 2300 2300 2300 2300 2300 2300

16. IPO(1) (2) (3) (4)
<20 years <10 years <5 years
minor, core change 0.383** 0.347* 0.496* 0.792*
(0.120) (0.150) (0.209) (0.342)
team diversity 0.261** 0.234* 0.422* 0.887**
(0.0937) (0.118) (0.187) (0.296)
startup experience 0.0171 -0.00214 -0.135 -0.361+
(0.0537) (0.0660) (0.100) (0.188)
industry experience 0.00407 -0.000315 -0.00311 0.00887
(0.00663) (0.00938) (0.0152) (0.0263)
mean age -0.00911 -0.0185+ -0.0277 -0.0504
(0.00831) (0.0109) (0.0177) (0.0368)
team size -0.0141 0.000138 -0.163 -0.152
(0.0585) (0.0740) (0.121) (0.191)
firm age 0.0706*** 0.143*** 0.305*** 0.743***
(0.00800) (0.0142) (0.0383) (0.210)
gender 0.0490 0.0600 0.123 -0.0401
(0.128) (0.162) (0.233) (0.421)
grad. year 0.00668 0.00521 0.000226 -0.0101
(0.00677) (0.00917) (0.0147) (0.0307)
had board 0.310** 0.293* 0.369+ 0.463
(0.114) (0.147) (0.211) (0.356)
crisis 0.233* 0.420** 0.718*** 0.0332
(0.114) (0.136) (0.209) (0.659)
Industry fixed effect Y Y Y Y
Department fixed effect Y Y Y Y
_cons -15.85 -12.14 -2.388 18.38
(13.79) (18.69) (30.00) (62.24)
N 2300 1638 988 567

17. Conclusion
• Contrary to work on discovery-driven planning, “lean startup”, we
find that at the early stages, a planning approach appears to be more
effective.
• Davis, Eisenhardt et al. (2009) simulation – suggests entrepreneurial
firms add structure and established firms stick to stable
environments.
• Adaptive approach is inferior to the planning approach contrary to
the popular notion that adaptive is better for early stage
entrepreneurship.
• However finding a mentor with high network diversity can mitigate
the disadvantages of using adaptive approach.
• Important to examine processes of entrepreneurship through RCT to
elicit causal inferences.