Dynamics of innovation policies and ecosystems in Japan
Name
1020074104-MIT.pdf
Description
Full printable version
Size
13.45 MB
Format
Adobe PDF
Checksum (MD5)
34f4e695d11506c551431155bb05217c
Author(s)
Nagura, Masaru
Advisor(s)
Bryan R. Moser.
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
Many public policies related to innovation have been implemented in Japan, especially focusing on promoting startups from universities, aiming at economic growth from technology. However, innovation ecosystem is complicated and dynamic that make difficult for policymakers to understand the system and evaluate policy effect. In this study, we analyze innovation ecosystem around a university and build a system dynamics model to have policy implications. We study the University of Tokyo and MIT, major universities for a large number of spin-off startups in each country, as cases of ecosystems. The study begins with policy and literature review of innovation and entrepreneurship, to understand present studies and policies. Next, stakeholders, system boundary, and causal relationships are analyzed to frame the system. Then, we build a system dynamics model of innovation ecosystem around a university. We included several causal loop structures in the model. For example, an Entrepreneur boom loop is a reinforcing loop which accelerates foundation of university spin-off startups and conversion of students to become entrepreneurial. A Risk capital depletion loop is a balancing loop which decelerates growth of startups when too many startups look for investment. Multiple loops and stakeholders interact closely in the systems, and the interrelated structures cause delay and side effects in simulation runs of our model. Results of the simulation infer policymakers need to consider combinations of policies rather than implement a single policy. Another interpretation from simulation runs is that patient policy implementation can lead to better outcomes because time delays in the loops make it difficult for policymakers to observe the effect of policies in the short term. Although additional data points are required for further calibration of the model, insights from this study and the model contribute to better understanding of innovation ecosystems around a university.
Description
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 113-120).
Subjects
Engineering and Management Program.
Integrated Design and Management Program.
System Design and Management Program.
MIT Department
Massachusetts Institute of Technology. Engineering and Management Program
System Design and Management Program.
Massachusetts Institute of Technology. Integrated Design and Management Program
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