論文 / 著書情報
Article / Book Information
題目(和文)

連携・知識構造特性に基づく科学運営のためのデータ計装

Title(English)

Data instrumentation for management of science based oncollaboration and knowledge-structural features

著者(和文)

宮下修人

Author(English)

Shuto Miyashita

出典(和文)

学位:博士（技術経営）,
学位授与機関:東京工業大学,
報告番号:甲第12139号,
授与年月日:2021年9月24日,
学位の種別:課程博士,
審査員:仙石 愼太郎,梶川 裕矢,橋本 正洋,笹原 和俊,西山 伸宏

Citation(English)

Degree:Doctor (Management of Technology),
Conferring organization: Tokyo Institute of Technology,
Report number:甲第12139号,
Conferred date:2021/9/24,
Degree Type:Course doctor,
Examiner:,,,,

学位種別(和文)

博士論文

Category(English)

Doctoral Thesis

種別(和文)

論文要旨

Type(English)

Summary

Powered by T2R2 (Tokyo Institute Research Repository)

（博士課程）Doctoral Program論 文 要 旨ＴＨＥＳＩＳ ＳＵＭＭＡＲＹ

系・コース： イノベーション科学
イノベーション科学
学生氏名：
宮下修人

Department of, Graduate major inStudent’s Name系コース

申請学位（専攻分野）：

博士

Academic Degree Requested

Doctor of

指導教員（主）：Academic Supervisor(main)

指導教員（副）：Academic Supervisor(sub)（技術経営）
仙石 愼太郎梶川 裕矢

要旨（英文 800 語程度）
Thesis Summary （approx.800 English Words ）This thesis, entitled ‘data instrumentation for management of science based on collaboration and knowledge-structuralfeatures’, aims at the instrumentation to enable data-driven decision making for the management of scientific research, which
consists of five Chapters.
Scientific research, particularly publicly-funded scientific research and development (R&D) for innovation and solving
multifaceted societal issues, is significantly increasing in scale and complexity. However, the literature on strategic andorganizational management of scientific research (so-called ‘the management of science’) at universities and public research
institutes is still underdeveloped compared to the literature of management of technology that mainly includes industrialR&D. Furthermore, methodologies that enable the acquisition of prescriptive knowledge in the management of science need
to be developed alongside the descriptive knowledge that has been nurtured based on conventional scientometrics. To addressthese outstanding issues, it is essential to develop a methodology for the instrumentation of structural features in scientificresearch by focusing on collaboration and knowledge structures in large-scale R&D programs and their descendant projects.
Based on the understanding, a methodology for capturing the real-time status of a scientific research project was developed
to support data-driven decision making by defining activity indicators for scientific research based on network science andconventional scientometrics.
Chapter 1 provides a background of the research including the concept of the management of science, its relation toscientometrics and the significance of instrumentation. The research objective is disseminated in this chapter as to develop amethodology for instrumentation of structural features of research activities by focusing on the collaboration and knowledge
structures in large-scale R&D projects centred on science research. Further, a general framework is provided as themicro-meso-macro architecture that corresponds to phenomena at the individual (or team), project and program levels,respectively.
Chapter 2 focuses on the system structure of an interdisciplinary R&D program and its descendant projects based on
empirical observation of the FIRST Program and its descendant NanoBio First project. In the program-level analysis, thelinkage of research funds and human resources to the outcomes is examined using a structural equation model, whichsuggests that different mechanisms work in the creation of academic outcomes and intellectual properties. In the project-levelanalysis, factors that promote or impede the creation of intellectual properties are explored. It was found that a collaboration
between a central university and a startup firm (which has a complementary role) established a knowledge logistics system torealize not only the social implementation of research results through joint patent applications but also cultivated a reciprocal
mindset and flexible resource management according to the R&D stage.
Chapter 3 explores the interactive dynamics of collaboration and knowledge structures in an interdisciplinary R&D projectby visualizing the co-author and the co-word networks, respectively, based on bibliographic analyses of publications. By
introducing the graph entropy as a measure of the complexity of these weighted network structures, the instrumentation ofindividual and institutional R&D activities can be visualized. Co-author and co-word network analyses constructed upon
bibliographic information from publications in the case of the COINS project confirmed that these networks have distinctive
structural features and different modes of time-course evolution.
Chapter 4 examines a qualitative case study on how changes in the collaboration and knowledge structures at the team andindividual levels can influence those at the project level in achieving R&D project goals based on the COINS project. Basedon the information from the key participants in the COINS project and the qualitative and time-course observation of theco-author and co-word networks at the individual level, an R&D strategy taken by each observed individual was assigned to
one of four quadrants comprised with two independent axes: the production/consumption of core/peripheral knowledge,
which was in line with the result of the graph entropy-based collaboration and knowledge structures in Chapter 3.
Furthermore, based on the observations and analysis of the COINS project, these results were verified to be consistent with
the R&D strategy and organization management in the real world.
Finally, in Chapter 5, the insights obtained from the previous chapters were summarized. The instrumentation of thecollaboration and knowledge structures in R&D activities at the program, project, team, and individual levels, respectively,
enable the observation of organizational and managerial phenomena at each level and the identification of mechanisms

implemented across levels, which can lead to a structural understanding of large-scale R&D programs and projects.
Methodological developments in the instrumentation of organizational and managerial phenomena in scientific research willcontribute to the systematization of management of science and will help practitioners to support evidence-based
management and data-driven decision making.

備考 : 論文要旨は、和文 2000 字と英文 300 語を 1 部ずつ提出するか、もしくは英文 800 語を 1 部提出してください。
Note : Thesis Summary should be submitted in either a copy of 2000 Japanese Characters and 300 Words (Engｌish) or 1copy of 800
Words (English).
注意：論文要旨は、東工大リサーチリポジトリ（T2R2）にてインターネット公表されますので、公表可能な範囲の内容で作成してください。
Attention: Thesis Summary will be published on Tokyo Tech Research Repository Website (T2R2).