Efficiency assessment and trends in the insurance industry: A bibliometric analysis of DEA application

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Data Envelopment Analysis is a crucial tool for evaluating the performance of insurance companies, considering its ability to handle multiple inputs and outputs. This study provides a comprehensive bibliometric analysis of Data Envelopment Analysis (DEA) application in the insurance industry from 2010 to 2023, examining 405 documents from 432 sources. Materials from academic databases (Web of Science and Scopus) were used for the analysis. The methodological flow included three stages. For analysis, two sets of keywords were identified: one set oriented toward DEA and the other tailored to the Insurance Industry domain. To analyze and visualize the data, VOSviewer software, version 1.6.19, and RSTUDIO were used. This paper highlights the evolution of DEA methodologies, incorporating advanced techniques like Artificial Intelligence and Machine Learning, and addresses emerging trends such as digital transformation, customer-centric assessments, and sustainability. The analysis reveals significant geographical and sectoral differences in efficiency assessments, with higher efficiency levels typically found in developed markets such as North America and Europe compared to emerging markets in Asia and Africa. It also notes the distinctive efficiency patterns between life and non-life insurance firms, influenced by product complexity and market competition. The findings indicate that DEA remains versatile and essential for performance evaluation in the insurance industry, adapting to challenges through methodological advancements.

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    • Figure 1. Author’s production over time
    • Figure 2. Tree map of keyword occurrence
    • Figure 3. Word frequency over time
    • Figure 4. Trending topics
    • Figure 5. Co-authorship network
    • Table 1. Top journals that widely published on DEA application in the insurance sector
    • Table 2. Descriptive summary
    • Table 3. Authors-leaders of research in the field of DEA in insurance
    • Table 4. Description of clusters formed by co-author
    • Table A1. Summary of DEA application in the insurance industry (2010–2023)
    • Conceptualization
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Data curation
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Formal Analysis
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Investigation
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Methodology
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Software
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Validation
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Visualization
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Writing – original draft
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Writing – review & editing
      K. S. Druva Kumar, J. P. Senthil Kumar
    • Supervision
      J. P. Senthil Kumar