Researcher's Profile

  • Adviser
  • Yasunori BABA
  • RCAST Adviser
E-mail
yasunori.baba.123gmail.com
Tel
04-7173-3430

Biography

March 1977 BA Economics, The University of Tokyo(UTokyo)
March 1986 D. Phil, University of Sussex, UK.
July 1986 Research Fellow, Science Policy Research Unit, University of Sussex
December 1988 Researcher, National Insti tute of Science and Technology Policy(NISTEP), Science and Technology Agency, Japan
April 1993 Associate Professor, Research into Artifacts, Center for Engineering, UTokyo
April 1997 Professor, Research into Ar ti facts, Center for Engineering, UTokyo
July 2001 Professor, Research Center for Advanced Economic Engineering, UTokyo
April 2004 Professor, RCAST, UTokyo
April 2007 Professor, Department of Advanced Interdisciplinary Studies, Graduate School Of Engineering, UTokyo
April 2018 Adviser, RCAST, UTokyo
April 2018 Professor, Faculty of Economics and Business Administration, REITAKU UNIVERSITY

Research Interests

Empirical Research into Innovation
Current research aims to identify the effect of prevailing academic entrepreneurship on innovation, by firstly asking whether traditional academic scientists or rather entrepreneurial scientists are more likely to contribute to scientific progress, and by secondly asking how academic entrepreneurship affects the scientific norms and forms of sharing scientific resources (for example, material transfer in the life sciences and materials science). Our results indicate that prevailing entrepreneurship can fundamentally change the nature and direction of industrial innovation.

Empirical Research into Dynamic Capabilities
Building on the literature of dynamic capabilities (DC), we analyze the organizational structure of scientific labs that contribute to sustained high-level performance. These capabilities are likely to be generated by the ability to spot scientific opportunities, to pursue those opportunities, and to exploit and re-assign existing resources. We argue that the DC theory provides an important insight into understanding how organizations respond to the noisy signals which come from the environment and preliminary experiments.

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