Do partners matter in scientific funding projects? Examining the impact of collaborative alliances on content novelty

Purpose This study aims to investigate how project novelty is enhanced through various collaborative alliances involving universities, research institutes, enterprises, government agencies, and medical institutes within the context of Chinese scientific funding projects. Design/methodology/approach We first identified two collaborative patterns and eight common collaborative alliances based on the institutional composition of teams. A quantitative approach was then employed to assess project content novelty, integrating large language models and deep learning techniques from a problem-method combination perspective. Finally, the contributions of different alliances to content novelty were analyzed using propensity score matching and ordinary least squares models. Findings The results indicate that inter-university collaboration is the predominant pattern. However, partnerships with other institutions, particularly research institutes, exhibit a higher probability of enhancing project content novelty compared to inter-university collaborations. Originality/value This study highlights the differential enhancement effects of collaborative alliances on project novelty, emphasizing the importance of collaboration with diverse institutions. The findings provide crucial guidance for effectively leading, engaging, facilitating, and supporting project teams toward success.

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Publication Details

Journal
Aslib Journal of Information Management
Published
2025-09-04
DOI
https://doi.org/10.1108/ajim-12-2024-0987
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
0.00

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article

Do partners matter in scientific funding projects? Examining the impact of collaborative alliances on content novelty

Xin‐Yao Yu, Yujiao Sun, Xiao-Ming Huang, Zhizhen Yao
Aslib Journal of Information Management
scientometrics and bibliometrics research
article

Do partners matter in scientific funding projects? Examining the impact of collaborative alliances on content novelty

Xin‐Yao Yu, Yujiao Sun, Xiao-Ming Huang, Zhizhen Yao
article en

Abstract

Purpose This study aims to investigate how project novelty is enhanced through various collaborative alliances involving universities, research institutes, enterprises, government agencies, and medical institutes within the context of Chinese scientific funding projects. Design/methodology/approach We first identified two collaborative patterns and eight common collaborative alliances based on the institutional composition of teams. A quantitative approach was then employed to assess project content novelty, integrating large language models and deep learning techniques from a problem-method combination perspective. Finally, the contributions of different alliances to content novelty were analyzed using propensity score matching and ordinary least squares models. Findings The results indicate that inter-university collaboration is the predominant pattern. However, partnerships with other institutions, particularly research institutes, exhibit a higher probability of enhancing project content novelty compared to inter-university collaborations. Originality/value This study highlights the differential enhancement effects of collaborative alliances on project novelty, emphasizing the importance of collaboration with diverse institutions. The findings provide crucial guidance for effectively leading, engaging, facilitating, and supporting project teams toward success.

Aslib Journal of Information Management
National Sun Yat-sen University (TW), Sun Yat-sen University (CN), Nankai University (CN), Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 77%
scientometrics and bibliometrics research
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Do partners matter in scientific funding projects? Examining the impact of collaborative alliances on content novelty — Xin‐Yao Yu, Yujiao Sun, et al. · Aslib Journal of Information Management (2025) | TGRS Research Map | TGRS