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

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.


INTRODUCTION
The efficiency of the insurance industry is crucial for its sustainability and competitive positioning in the global market.In recent years, the industry has faced numerous challenges, including economic volatility, regulatory changes, and the increasing complexity of risk management.These factors underscore the necessity for robust analytical tools that can help insurance companies assess and enhance their operational efficiency.One such tool, Data Envelopment Analysis (DEA), has gained prominence for its ability to evaluate the performance of decision-making units (DMUs) within the sector by considering multiple inputs and outputs simultaneously.DEA application in the insurance industry is particularly significant due to the sector's inherent complexity and the diverse nature of its operations.Unlike other industries where outputs are tangible and easily quantifiable, the outputs of insurance companies include financial security, risk management services, and customer satisfaction, which are more challenging to measure.DEA provides a comprehensive framework for benchmarking efficiency by creating an efficient frontier against which companies' performances are evaluated.This makes it an invaluable tool for insurers seeking to improve their operational practices and achieve a com-

LITERATURE REVIEW
The application of Data Envelopment Analysis (DEA) in the insurance industry has grown significantly over the past decade.The literature reveals a growing interest in applying DEA to evaluate the efficiency of insurance companies.A notable trend is the shift from traditional efficiency assessments to more comprehensive models that incorporate advanced techniques such as Artificial Intelligence (AI).The post-pandemic worldwide has accelerated the use of AI (Gusti et al., 2024).
The DEA method is one potential tool available that can measure a company's performance in a complex way represented by one indicator (Fenyves & Tarnóczi, 2020).
Cummins and Rubio-Misas (2006) identified the positive effects of deregulation on Spanish insurers' production efficiency (see see Appendix A, Table A1).Similarly, Micajkova (2015) explored the effectiveness of insurance companies in Macedonia, highlighting the potential for efficiency improvements through better resource allocation.It is worth noting that, Table A1 provides a comprehensive summary of the sources cited in the literature review.The table offers a consolidated view, making it easier for readers to reference specific studies and their contributions.This consolidation is crucial for understanding the breadth and depth of DEA application in the insurance industry.
A prominent theme in this literature is the impact of regulatory changes, with identifying deregulation's positive effects on Austrian insurers' production efficiency (Cummins & Xie, 2013).This insight highlights the significance of regulatory environments in shaping the efficiency landscape of insurance markets.Similarly, Micajkova (2015) explores the effectiveness of insurance companies in Macedonia, reflecting the worldwide trend of deregulation as insurance markets adapt to changing economic dynamics.
Efficiency analysis extends beyond deregulation to encompass broader dimensions of insurer performance (Ennsfellner et al., 2004).Research dives into efficiency's intricacies by examining operating and investment efficiency in general insurance companies (M.Garg & S. Garg, 2020).This dual focus offers a comprehensive perspective on how insurers manage their resources and investments to maximize efficiency (Medved & Kavčič, 2012).On the other hand, there will likely be an empirical study of efficiency in Croatia and Slovenia's insurance markets, potentially involving a comparative examination of features influencing the performance of insurers in these neighboring regions.This comparative approach sheds light on the diverse dynamics within regional insurance markets, emphasizing the importance of the context in efficiency evaluations.
Efficiency analysis extends its reach to specific markets and regions, providing insights into the performance of insurers in various geographical contexts.Al-Amri et al. (2012) investigate insurance efficiency in the Gulf Cooperation Council (GCC) countries, offering valuable insights into the performance of insurers in this region characterized by unique economic and regulatory dynamics.This regional focus allows a nuanced understanding of how regional factors influence efficiency.Additionally, Siddiqui's (2020) examination of the Indian life insurance sector goes beyond national boundaries, encompassing both public and private insurers, thereby contributing to the global perspective on insurance efficiency.This expansion of research scope to specific markets and regions enriches the literature by highlighting the contextual nuances that affect insurer performance.
The literature also delves into deregulation's influence and the most crucial conglomeration on insurer efficiency (Ennsfellner et al., 2004).Both discuss the influence of deregulation and its impact on insurance companies, emphasizing the potential benefits of regulatory changes for improving efficiency.This theme underscores the dynamic nature of the insurance industry, where regulatory shifts can have profound implications for insurer performance.Berger et al. (1992) explored the effects of conglomeration and strategic focus in the insurance industry, shedding light on how organizational structures and strategies influence efficiency.Meanwhile, a study of the Spanish insurance industry by Cummins and Xie (2008) potentially reveals the intricate relationship between deregulation, consolidation, and efficiency.Understanding these relationships is vital for policymakers and industry stakeholders seeking to optimize the regulatory environment.
Mergers and acquisitions represent another dimension of insurance industry evolution (Cummins & Xie, 2013).Mergers and acquisitions impact the productivity and efficiency of companies in the property-liability insurance sector in the United States.These corporate strategies have practical consequences on insurance companies' operations, providing valuable insights for insurers contemplating such M&A activity.
Efficiency analysis in the insurance sector extends to the global stage, with comprehensive study providing a panoramic view of the association between efficiency and productivity (Eling & Schaper, 2017;Eling & Jia, 2018).The efficiencyprofitability relationship is industry-dependent, with different dynamics for life and non-life insur-ers.This global perspective highlights the importance of considering industry-specific nuances in efficiency assessments.Specific markets and regions remain fertile ground for research, generating insights into local efficiency dynamics (Ndlovu, 2021).Analyzing efficiency and understanding the impact of productivity returns (Alhassan & Biekpe, 2016;Cooper et al., 1999;Hu et al., 2020;Ndlovu, 2021) and the improvising factors of economies in South Africa's healthcare insurance market contribute to the understanding of the factors influencing efficiency in a specialized sector.
In the context of the insurance sector, the DEA uses methodologies and models based on several critical determinants of efficiency: • Firm Size: Larger insurance firms generally exhibit higher efficiency scores.This can be attributed to economies of scale, which enable more effective resource management and operational efficiencies.For instance, larger firms can spread their fixed costs over a larger volume of business, resulting in lower average costs (Al-Amri et al., 2012).
• Market Conditions: Market conditions, including competition intensity and market saturation, significantly influence efficiency.
Competitive markets force firms to optimize their operations to maintain profitability, leading to higher efficiency scores.Conversely, in less competitive markets, firms may not be as motivated to improve efficiency (Seog, 2009).
• Regulatory Environment: Regulatory frameworks play a pivotal role in shaping efficiency.Supportive regulations that encourage innovation and best practices contribute positively to efficiency outcomes.For example, regulations promoting transparency and consumer protection can drive firms to adopt more efficient processes to comply with standards (Eling & Schaper, 2017).
• Technological Adoption: Technological advancements have significantly impacted the efficiency of insurance firms.Innovations such as automated underwriting systems, data analytics, and digital claims processing have streamlined operations, reduced costs, and improved customer service.Studies consistently show that firms adopting these technologies achieve better efficiency scores (Ashiagbor et al., 2023).
In summary, the systematic literature review on efficiency analysis in the insurance industry is rich and diverse, encompassing many themes, methodologies, and geographic contexts.These studies cooperatively contribute to a nuanced understanding of the factors that influence insurer performance, offering valuable insights for policymakers, industry stakeholders, and researchers seeking to optimize the efficiency and sustainability of insurance markets.
The purpose of this study is to provide a comprehensive bibliometric review of DEA applications in the insurance sector, analyzing trends from 2010 to 2023.

METHOD
The initial step involved an exhaustive search across prominent academic databases, with a predominant focus on Web of Science and supplemented by a limited number of papers from Scopus.Methodological flow includes three stages: •  The average age of these documents is 8.42 years, suggesting a relatively young yet established body of literature.Each document, on average, has garnered 24.83 citations, reflecting their academic impact.Notably, the dataset does not include any references, but it does highlight 1,237 unique keywords, underlining the diverse topics and themes explored in this field.The surge in publications during this period can be attributed to several factors, including increased academic interest, advancements in DEA methodologies, and a heightened focus on efficiency due to economic pressures and competitive market conditions.Moreover, the diversification of DEA models, such as Network DEA and Twostage DEA, has allowed for more nuanced analysis, catering to the complex nature of insurance operations.The efficiency analysis in the insurance industry has yielded a wealth of knowledge, predominantly employing DEA as the primary methodology.Researchers have delved into various dimensions of insurer performance, shedding light on critical factors that influence efficiency outcomes.Notably, studies have uncovered the impact of regulatory changes, with evidence pointing towards the positive effects of deregulation on insurer efficiency.Comparative regional analyses have played a pivotal role in understanding the contextual nuances shaping efficiency, providing insights into the diversity of dynamics across different markets.However, as this literature matures, several noteworthy gaps and areas for further exploration emerge.

RESULTS AND DISCUSSION
The mid-2010s, especially around 2013 and 2015, appear to be peak periods for several authors, indicating a significant surge in research output and influence during this time.(Xie, 2010).
Figure 2 shows a visual representation of the key themes in journal publications.The most prominent keyword is "data envelopment analysis," which accounts for 11% of the focus, highlighting a strong interest in performance and efficiency evaluation.Other significant keywords include "insurance," "human," and "health insurance," indicating that research frequently addresses financial aspects and human factors.Additionally, terms such as "productivity," "organizational," and "decision making" reflect a focus on improving management practices and operational efficiency.The tree map also shows a diverse range of topics, including "economics," "public health," and "health care policy," underscoring the interdisciplinary nature of the work.In total, the image encompasses 54 distinct keywords.
Figure 3 illustrates the cumulative occurrences of key terms in the journal publications from 1994 to 2024."Data envelopment analysis" shows a significant rise, indicating its growing importance in research.Other terms like "insurance," "efficiency," and "health insurance" also display in- The steady growth in the use of keywords such as "human," "decision making," and "productivity" suggests a broadening scope that includes human factors and operational efficiency.This temporal analysis highlights the evolving focus of research over the past three decades.
Within the framework of this study, key trends and topics in the literature were analyzed (Figure 4).The study highlights a significant shift towards healthcare and insurance sectors, with frequent terms like "health care planning," "health insurance," and "life insurance," indicating a growing focus in these areas.Regional studies on China and Taiwan have become prominent, reflecting increased geographical interest.The persistent appearance of terms such as "efficiency," "productivity," and "regression analysis" underscores the central themes of DEA.From 2016 onwards, there is a notable rise in publication volume, suggesting expanding research output.This analysis provides valuable insights into the evolving land- scape of DEA research, guiding future directions and emphasizing areas of significant impact.The most important thing to understand is that methodological diversification is a definite need.
In the context of this study, a robust international partnership between the United States, China, and European countries is being followed.Notable collaboration with countries in Asia, South America, and Africa also reflects DEA's global research network.This is evidence that cross-border collaboration is essential to advance DEA research and its application worldwide.
A comprehensive overview has been conducted of the clusters formed by co-authors based on their geographical collaborations in the field of DEA applications in the insurance industry.The analysis reveals four distinct clusters of countries, each characterized by unique research dynamics and contributions (Table 4).Cluster 1, dominated by the United States, China, and russia, reflects a diverse blend of developed and emerging markets, underscoring their pivotal roles in driving DEA research across vast and complex insurance ecosystems.This cluster illustrates significant engagement in developing and applying DEA methodologies to enhance efficiency in large-scale insurance operations.In contrast, Cluster 2, which includes countries like Iran, Poland, and Ukraine, primarily represents transitional and developing economies.Research efforts within this cluster often focus on adapting DEA techniques to suit the evolving regulatory and economic landscapes of these regions.Cluster 3, featuring countries such as Germany, Italy, and Spain, comprises predominantly European nations with wellestablished insurance sectors.The research here is inclined towards advanced DEA applications tailored to mature market conditions and sophisticated regulatory frameworks.Lastly, Cluster 4, encompassing nations like Slovenia, Croatia, and Namibia, highlights regions with smaller or nascent insurance markets.Studies in this cluster typically explore the optimization of resources and operational efficiencies in these less mature environments.These clusters collectively underscore the global nature of DEA research in the insurance industry and reveal how regional collaborations are influenced by the specific characteristics and needs of various markets (Figure 5).This diversity in collaboration points to the rich array of research focus and the adaptation of DEA methodologies to address different operational contexts within the global insurance landscape.
Geographical and sectoral differences in efficiency assessments are also evident.Studies

CONCLUSION
This bibliometric analysis of DEA applications in the insurance industry from 2010 to 2023 provides valuable insights into the evolution of efficiency assessment in this sector.The study reveals a notable increase in research activity, particularly post-2015, reflecting the rising recognition of DEA as a crucial tool for measuring and improving efficiency in insurance firms.Key themes identified in the literature include health insurance, insurance companies, efficiency, productivity, and organizational management, highlighting the primary areas of focus for researchers.
The country collaboration map underscores the significant contributions of the United States, China, and European countries to DEA research in the insurance sector.These regions not only produce a substantial volume of research but also engage in extensive international collaborations, fostering the exchange of ideas and methodologies.This global network of research collaboration is pivotal in advancing the application of DEA and addressing the diverse challenges faced by the insurance industry worldwide.The trend analysis indicates a shift towards more sophisticated and integrated methodologies, combining DEA with other quantitative techniques such as regression analysis.This evolution reflects the need for more robust models to tackle the complex and multifaceted nature of efficiency assessment in the insurance industry.Moreover, the increasing focus on specific segments within the insurance sector, such as health insurance and life insurance, suggests a deeper investigation into the unique operational dynamics and efficiency determinants pertinent to these areas.
In summary, this bibliometric review highlights the critical role of DEA in enhancing operational efficiency within the insurance industry.The increasing research activity, evolving methodologies, and extensive international collaborations underscore the dynamic and vibrant nature of this field.Future investigations should focus on the identified gaps, such as the impact of regulatory environments and the role of InsurTech in enhancing efficiency.

Figure 1
Figure 1 shows the publication history of various authors from 1997 to 2023.Each circle represents the number of articles published by an author in a given year, with larger circles indicating more articles.The shade of each circle signifies the total citations per year, with darker shades representing higher citation counts.Authors such as Cummins

Figure 2 .
Figure 2. Tree map of keyword occurrence

Table 1 .
Top journals that widely published on DEA application in the insurance sector .D. and Brockett P. L exhibit extended periods of activity, with Cummins J. D. peaking around 2013 in both publications and citations.Eling M. shows significant publication activity around 2015, while Kweh Q. L., Lu W. M., and Barros C. P.
Figure 1.Author's production over time J

Table 3 .
Authors-leaders of research in the field of DEA in insurance Xie X. and Kao C. have also made notable contributions to the DEA literature in insurance.Their research often focuses on methodological innovations and practical applications of DEA to evaluate the efficiency and productivity of insurance operations.Their insights have helped in refining the analytical tools used to assess performance in this sector