Scientists’ disciplinary characteristics and collaboration behaviour under the convergence paradigm: A multilevel network perspective

Jing Li and Qian Yu

Journal of Informetrics, 2024, vol. 18, issue 1

Abstract: The convergence paradigm underlines the importance of integrating multiple disciplines through collaboration. However, the crucial question of how scientists' disciplinary characteristics influence scientific collaboration remains unresolved. Using an exponential random graph model for multilevel networks, this study provides insights into the impact of scientists' disciplinary characteristics on their collaborative behaviour based on data from the Materials Genome Initiative, a typical convergence field. These results show that: under the convergence paradigm, scientists with a greater number of affiliated disciplines or with greater disparities in knowledge systems among their affiliated disciplines are less active in collaboration, whereas scientists with more balanced competence across their affiliated disciplines are more active. Scientists are more likely to collaborate with people who have a similar ability to integrate multidisciplinary knowledge. Scientists with a focus on applied disciplines are more likely to collaborate than are those with a preference for basic disciplines. Scientists who focus more on peripheral and external disciplines are more active in collaboration than scientists who focus on core and internal disciplines. Scientists collaborate based on shared disciplines and utilise the unique disciplines of their collaborators to advance knowledge and thus expand their own research space. This study provides evidence for the selection of partners based on scientists' disciplinary characteristics and highlights its importance for interdisciplinary teams and project management.

Keywords: Disciplinary characteristics; Scientific collaboration; Convergence; Multilevel network; Interdisciplinary (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:18:y:2024:i:1:s175115772400004x

DOI: 10.1016/j.joi.2024.101491

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