Overcoming recognition delays in disruptive research: The impact of team size, familiarity, and reputation

Huihuang Jiang, Jianlin Zhou, Yiming Ding and An Zeng

Journal of Informetrics, 2024, vol. 18, issue 4

Abstract: The relationship between disruption and delayed recognition is a critical research topic, yet the connection between the degree of disruption and delayed acknowledgment remains unclear. This study investigates the extent of recognition delay for disruptive papers using the SciSciNet dataset. We conducted a quantitative analysis based on this extensive dataset to examine the relationship between the Disruption Index and the Sleeping Beauty Index, revealing that highly disruptive papers often face a latency period before gaining acknowledgment, with significant variations across disciplines and over time. Our analysis of team dynamics indicates that larger teams, the presence of high-impact authors, fixed teams, and hierarchically structured teams can significantly reduce this delay. These findings provide insights into optimizing team strategies and understanding the complexities of academic recognition. They offer valuable implications for researchers and policymakers aiming to foster and accelerate the acknowledgment of groundbreaking scientific contributions.

Keywords: Bibliometrics; Disruptive; Delayed recognition; Disruption index; Sleeping beauty index (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157724000622
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:18:y:2024:i:4:s1751157724000622

DOI: 10.1016/j.joi.2024.101549

Access Statistics for this article

Journal of Informetrics is currently edited by Leo Egghe

More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().