Trends and Patterns in Insurance Research: A Bibliometric Analysis (2020–2024)

Abstract

Purpose

This study presents an extensive bibliometric analysis aimed at delineating the landscape of research within the insurance literature from 2020 to 2024.

Methodology

Leveraging methodologies such as keyword cooccurrence analysis, cocitation analysis, and bibliographic coupling, the study identifies pivotal clusters of research topics. The bibliographic data was sourced from Scopus, renowned for its comprehensive coverage across social, engineering, and natural sciences. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, 1,608 documents were initially scrutinized, resulting in a refined dataset of 714 documents. Utilizing VOSviewer for science mapping, the study underscores three predominant categories of analysis: keyword cooccurrence, cocitation, and bibliographic coupling. Employing a dual-pronged approach for keyword selection, the study began by examining five freely accessible publications. Analysis was conducted employing two primary bibliometric techniques: performance analysis, gauging the efficacy of research components, and science mapping, elucidating interdependencies among research entities. Notably, the study utilized VOSviewer and Biblioshiny—a web interface for bibliometrics based on the R programming language—as the principal tools for bibliometric analysis.

Findings

This comprehensive investigation sheds light on the thematic evolution and interconnectedness within insurance research, providing valuable insights for scholars, practitioners, and policymakers alike.

Citation

Chand, K., Chandel, A., Tiwari, R. and Chauhan, A.S. (2024), "Trends and Patterns in Insurance Research: A Bibliometric Analysis (2020–2024)", Taneja, S., Kumar, P., Reepu, Kukreti, M. and Özen, E. (Ed.) Data Alchemy in the Insurance Industry, Emerald Publishing Limited, Leeds, pp. 153-181. https://doi.org/10.1108/978-1-83608-582-920241025