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Efficiency and Productivity in the US Property-Liability Insurance Industry: Ownership Structure, Product and Distribution Strategies

In: Data Envelopment Analysis

Author

Listed:
  • J. David Cummins

    (Temple University)

  • Xiaoying Xie

    (California State University-Fullerton)

Abstract

The chapter examines efficiency and productivity of US property-liability (P-L) insurers using data envelopment analysis (DEA). We estimate pure technical, scale, cost, revenue and profit efficiency over the period 1993–2011. Insurers’ adjacent year total factor productivity changes and their contributing factors are also investigated. In particular, we explore the relationship of insurers’ efficiency with their ownership structure, product and distribution strategies. Regression analyses are also performed to explore the relationships between firm characteristics, efficiency and productivity. The results indicate US P-L insurance industry has improved its efficiency and productivity over time. Insurers’ product strategy, distribution system, and diversification strategy are important determinants of insurers’ efficiency and productivity, along with other firm characteristics.

Suggested Citation

  • J. David Cummins & Xiaoying Xie, 2016. "Efficiency and Productivity in the US Property-Liability Insurance Industry: Ownership Structure, Product and Distribution Strategies," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 113-163, Springer.
  • Handle: RePEc:spr:isochp:978-1-4899-7684-0_6
    DOI: 10.1007/978-1-4899-7684-0_6
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    Citations

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    Cited by:

    1. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    2. Reza Sanei & Farhad Hosseinzadeh lotfi & Mohammad Fallah & Farzad Movahedi Sobhani, 2022. "An Estimation of an Acceptable Efficiency Frontier Having an Optimum Resource Management Approach, with a Combination of the DEA-ANN-GA Technique (A Case Study of Branches of an Insurance Company)," Mathematics, MDPI, vol. 10(23), pages 1-21, November.
    3. Liu, Shuli & Wan, Yulai & Zhang, Anming, 2021. "Does high-speed rail development affect airport productivity? Evidence from China and Japan," Transport Policy, Elsevier, vol. 110(C), pages 1-15.
    4. María Rubio‐Misas, 2022. "Analysis of insurers' performance using frontier efficiency and productivity methods. The great contributions by David Cummins and Mary Weiss," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(4), pages 445-489, December.
    5. Davide Lanfranchi & Laura Grassi, 2021. "Translating technological innovation into efficiency: the case of US public P&C insurance companies," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(4), pages 565-585, December.

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