Cumulative advantage and citation performance of repeat authors in scholarly journals

Author:

Siler KyleORCID,Vincent-Lamarre Philippe,Sugimoto Cassidy R.,Larivière Vincent

Abstract

Cumulative advantage–commonly known as the Matthew Effect–influences academic output and careers. Given the challenge and uncertainty of gauging the quality of academic research, gatekeepers often possess incentives to prefer the work of established academics. Such preferences breach scientific norms of universalism and can stifle innovation. This article analyzes repeat authors within academic journals as a possible exemplar of the Matthew Effect. Using publication data for 347 economics journals from 1980–2017, as well as from three major generalist science journals, we analyze how articles written by repeat authors fare vis-à-vis less-experienced authors. Results show that articles written by repeat authors steadily decline in citation impact with each additional repeat authorship. Despite these declines, repeat authors also tend to garner more citations than debut authors. These contrasting results suggest both benefits and drawbacks associated with repeat authorships. Journals appear to respond to feedback from previous publications, as more-cited authors in a journal are more likely to be selected for repeat authorships. Institutional characteristics of journals also affect the likelihood of repeat authorship, as well as citation outcomes. Repeat authorships–particularly in leading academic journals–reflect innovative incentives and professional reward structures, while also influencing the intellectual content of science.

Funder

Alfred P. Sloan Foundation

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Empirical demonstration of the Matthew effect in scientific research careers;Journal of Informetrics;2023-11

2. A Preliminary Investigation of the Effects of Open Review on Citation Impact;Proceedings of the Association for Information Science and Technology;2023-10

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