Investigating how network filters regulate flows and influences in interorganizational networks across field boundaries

Research Project

Project/Area Number	22K13487
Research Category	Grant-in-Aid for Early-Career Scientists
Allocation Type	Multi-year Fund
Review Section	Basic Section 07080:Business administration-related
Research Institution	Kyoto Tachibana University
Principal Investigator	FAZEKAS BALAZS 京都橘大学, 国際英語学部, 専任講師 (50808368)
Project Period (FY)	2022-04-01 – 2025-03-31
Project Status	Granted (Fiscal Year 2022)
Budget Amount *help	¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000) Fiscal Year 2024: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000) Fiscal Year 2023: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000) Fiscal Year 2022: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Keywords	social network analysis / organizational networks / organizational fields / networks / alliance networks / network filters / network friction / management / ネットワーク / 新制度学派 / フィールド / 組織論 / バウンダリー
Outline of Research at the Start	Network theory has identified different effects that the overall network has on individuals in the network. This research, however, argues that hidden walls exist in social networks that alter these effects. Moreover, these hidden boundaries can act as filters that filter network effects and influences. The aim is to identify different kinds of boundary filters and analyze their importance for the stability of social structures, such as organizations and larger organizational groups.
Outline of Annual Research Achievements	The first phase of research moved forward in three ways. 1&2. In 2022, a considerable amount of time was spent on developing theoretical underpinnings in two theoretical papers. The first paper delve into the fundamental concepts of social fields, networks, and the impact of fields on networks. Titled, "A Theory of Fields and Networks: How Field Forces Influence Network Advantage," it is currently in the journal review process. Additionally, another paper is being drafted, examining various potential filters that may create friction within network ties. Both papers are purely theoretical without quantitative or qualitative data. 3. To complement the existing nanotechnology and biotechnology datasets, a joint-patent alliance network has been created using the IIP dataset. Although this initiative is still a work in progress and requires additional data, preliminary quantitative analysis is already underway. One of the primary focuses is to explore the boundaries between universities and industries, investigating the potential filters along the boundaries.
Current Status of Research Progress	Current Status of Research Progress 1: Research has progressed more than it was originally planned. Reason While there was a great deal of progress with my theoretical work, the empirical work posed some difficulties due to the large size of the database. Even with the better performing computer, large networks (over 10,000x10,000 nodes) are difficult to process, taking longer as expected. Especially, visualizing (even parts of) the network is quite cumbersome. This led to less money spent in the first year than originally planned. However, the bulk of the network construction work has been completed in March and preliminary analyses can now be conducted. I plan to begin collecting additional data from June and start presenting the papers in domestic and, if possible, international venues.
Strategy for Future Research Activity	In April, I entered the second year of the project. Currently, I'm working on the draft of my second paper, exploring the theory of network friction. Additionally, I plan to develop a third theoretical paper focusing on network structure and its role in filtering effects, expanding on previous work. Concurrently, I'm collecting additional organizational data for statistical testing, marking the transition into the quantitative phase. Several separate quantitative papers are planned to explore different dimensions of the data. However, there is a gap between theory and data. The quantitative work will narrow down to specific subsets, investigating different filtering effects and structural features.