研究課題/領域番号 |
22K13487
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研究種目 |
若手研究
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配分区分 | 基金 |
審査区分 |
小区分07080:経営学関連
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研究機関 | 京都橘大学 |
研究代表者 |
FAZEKAS BALAZS 京都橘大学, 国際英語学部, 専任講師 (50808368)
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研究期間 (年度) |
2022-04-01 – 2025-03-31
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研究課題ステータス |
交付 (2022年度)
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配分額 *注記 |
2,470千円 (直接経費: 1,900千円、間接経費: 570千円)
2024年度: 910千円 (直接経費: 700千円、間接経費: 210千円)
2023年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2022年度: 910千円 (直接経費: 700千円、間接経費: 210千円)
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キーワード | 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 |
研究開始時の研究の概要 |
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.
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研究実績の概要 |
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.
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現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
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.
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今後の研究の推進方策 |
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.
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