Share:


Measuring technical efficiency of insurance companies using dynamic network DEA: an intermediation approach

    Mohammad Nourani Affiliation
    ; Evelyn Shyamala Devadason Affiliation
    ; VGR Chandran Affiliation

Abstract

This study measures technical efficiency of the Malaysian insurance companies using a new framework for performance efficiency, built on the intermediation approach, by decomposing the complex service processes of insurance companies into two functional divisions, premium accumulation and investment capability. The study employs a dynamic network data envelopment analysis for performance evaluation of insurer (life, general and composite insurers) and ownership (local and foreign) types, spanning the period 2007–2014. The findings reveal a lack of efficiency in the investment capability function among local insurers as compared to their foreign counterparts. While the composite or non-specialized segment performs better in the investment capability function, the general segment achieves better efficiency in the premium accumulation function. The results suggest the high usage of input quantities and lack of total investment as key reasons for low efficiency, particularly among the local insurers. Implications for business excellence for insurance companies are further discussed.

Keyword : performance evaluation, data envelopment analysis, intermediation approach, dynamic network slacks-based measure, insurance companies

How to Cite
Nourani, M., Devadason, E. S., & Chandran, V. (2018). Measuring technical efficiency of insurance companies using dynamic network DEA: an intermediation approach. Technological and Economic Development of Economy, 24(5), 1909-1940. https://doi.org/10.3846/20294913.2017.1303649
Published in Issue
Oct 1, 2018
Abstract Views
20
PDF Downloads
21
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Arena, M. 2008. Does insurance market activity promote economic growth? A cross‐country study for industrialized and developing countries, The Journal of Risk and Insurance 75(4): 921–946. https://doi.org/10.1111/j.1539-6975.2008.00291.x

Avkiran, N. K. 2009. Opening the black box of efficiency analysis: an illustration with UAE banks, Omega 37(4): 930–941. https://doi.org/10.1016/j.omega.2008.08.001

Avkiran, N. K. 2015. An illustration of dynamic network DEA in commercial banking including robustness tests, Omega 55: 141–150. https://doi.org/10.1016/j.omega.2014.07.002

Banker, R. D.; Charnes, A.; Cooper, W. W. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science 30(9): 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078

Barros, C.; Wanke, P. 2016. Cost efficiency of African insurance companies using a finite mixture model, South African Journal of Economic and Management Sciences 19(1): 64–81. https://doi.org/10.4102/sajems.v19i1.1238

Barros, C. P.; Dumbo, S.; Wanke, P. 2014. Efficiency determinants and capacity issues in Angolan insurance companies, South African Journal of Economics 82(3): 455–467. https://doi.org/10.1111/saje.12056

Barros, C. P.; Wanke, P. 2014. Insurance companies in Mozambique: a two-stage DEA and neural networks on efficiency and capacity slacks, Applied Economics 46(29): 3591–3600.

Barros, C. P.; Wanke, P. 2015. Technology gaps and capacity issues in African insurance companies: selected country evidence, Journal of International Development 29(1): 117–133. https://doi.org/10.1002/jid.3098

Berger, A. N.; Humphrey, D. B. 1997. Efficiency of financial institutions: international survey and directions for future research, European Journal of Operational Research 98(2): 175-212. https://doi.org/10.1016/S0377-2217(96)00342-6

Biener, C.; Eling, M. 2012. Organization and efficiency in the international insurance industry: a crossfrontier analysis, European Journal of Operational Research 221(2): 454–468. https://doi.org/10.1016/j.ejor.2012.03.037

Biger, N.; Kahane, Y. 1978. Risk considerations in insurance ratemaking, The Journal of Risk and Insurance 45(1): 121–132. https://doi.org/10.2307/251812

Bjurek, H.; Hjalmarsson, L.; Forsund, F. R. 1990. Deterministic parametric and nonparametric estimation of efficiency in service production: a comparison, Journal of Econometrics 46(1): 213–227. https://doi.org/10.1016/0304-4076(90)90056-Y

Brockett, P. L.; Cooper, W. W.; Golden, L. L.; Rousseau, J. J.; Wang, Y. 2004. Evaluating solvency versus efficiency performance and different forms of organization and marketing in US property-liability insurance companies, European Journal of Operational Research 154(2): 492–514. https://doi.org/10.1016/S0377-2217(03)00184-X

Brockett, P. L.; Cooper, W. W.; Golden, L. L.; Rousseau, J. J.; Wang, Y. 2005. Financial intermediary versus production approach to efficiency of marketing distribution systems and organizational structure of insurance companies, The Journal of Risk and Insurance 72(3): 393–412. https://doi.org/10.1111/j.1539-6975.2005.00130.x

Charnes, A.; Cooper, W. W.; Rhodes, E. 1978. Measuring the efficiency of decision making units, European Journal of Operational Research 2(6): 429–444. https://doi.org/10.1016/0377-2217(78)90138-8

Chen, L.-R.; Lai, G. C.; Wang, J. L. 2011. Conversion and efficiency performance changes: evidence from the U.S. property-liability insurance industry, The Geneva Risk and Insurance Review 36(1): 1–35. https://doi.org/10.1057/grir.2010.3

Choi, B. P.; Elyasiani, E. 2011. Foreign-owned insurer performance in the US property-liability markets, Applied Economics 43(3): 291–306. https://doi.org/10.1080/00036840802552353

Cooper, W. W.; Seiford, L. M.; Tone, K. 2007. Data envelopment analysis: a comprehensive text with models, applications, references and DEA-Solver software second edition. Springer US.

Cummins, J. D.; Rubio-Misas, M. 2006. Deregulation, consolidation, and efficiency: evidence from the Spanish insurance industry, Journal of Money, Credit, and Banking 38(2): 323–355. https://doi.org/10.1353/mcb.2006.0029

Cummins, J. D.; Turchetti, G.; Weiss, M. A. 1996. Productivity and technical efficiency in the Italian insurance industry. Wharton School Center for Financial Institutions, University of Pennsylvania, Working Paper.

Cummins, J. D.; Weiss, M. A. 2013. Analyzing firm performance in the insurance industry using frontier efficiency and productivity methods, Handbook of insurance. Springer.

Cummins, J. D.; Weiss, M. A.; Xie, X.; Zi, H. 2010. Economies of scope in financial services: a DEA efficiency analysis of the US insurance industry, Journal of Banking & Finance 34(7): 1525–1539. https://doi.org/10.1016/j.jbankfin.2010.02.025

Cummins, J. D.; Weiss, M. A.; Zi, H. 1999. Organizational form and efficiency: the coexistence of stock and mutual property-liability insurers, Management Science 45(9): 1254–1269. https://doi.org/10.1287/mnsc.45.9.1254

Cummins, J. D.; Xie, X. 2008. Mergers and acquisitions in the US property-liability insurance industry: productivity and efficiency effects, Journal of Banking & Finance 32(1): 30–55. https://doi.org/10.1016/j.jbankfin.2007.09.003

Cummins, J. D.; Zi, H. 1998. Measuring economic efficiency of the US life insurance industry: econometric and mathematical programming techniques, Journal of Productivity Analysis 10: 131–145. https://doi.org/10.1023/A:1026402922367

Ding, C.; He, X. 2004. K-means clustering via principal component analysis, in Proceedings of The Twenty-First International Conference on Machine Learning, 4–8 July 2004, Banff, Alberta, Canada, 29. https://doi.org/10.1145/1015330.1015408

Doherty, N. A. 1980. A portfolio theory of insurance capacity, The Journal of Risk and Insurance 47(3): 405–420. https://doi.org/10.2307/252630

Du, J.; Wang, J.; Chen, Y.; Chou, S.-Y.; Zhu, J. 2014. Incorporating health outcomes in Pennsylvania hospital efficiency: an additive super-efficiency DEA approach, Annals of Operations Research 221(1): 161–172. https://doi.org/10.1007/s10479-011-0838-y

Eling, M.; Luhnen, M. 2010a. Efficiency in the international insurance industry: a cross-country comparison, Journal of Banking & Finance 34(7): 1497–1509. https://doi.org/10.1016/j.jbankfin.2009.08.026

Eling, M.; Luhnen, M. 2010b. Frontier efficiency methodologies to measure performance in the insurance industry: overview, systematization, and recent developments, The Geneva Papers on Risk and Insurance – Issues and Practice 35(2): 217–265. https://doi.org/10.1057/gpp.2010.1

Färe, R.; Grosskopf, S.; Whittaker, G. 2007. Network DEA, Chapter 12 in J. Zhu, W. Cook (Eds.). Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis. Springer US. https://doi.org/10.1007/978-0-387-71607-7_12

Färe, R.; Whittaker, G. 1995. An intermediate input model of dairy production using complex survey data, Journal of Agricultural Economics 46(2): 201–213. https://doi.org/10.1111/j.1477-9552.1995.tb00766.x

Farrell, M. J. 1957. The measurement of productive efficiency, Journal of the Royal Statistical Society. Series A (General) 120(3): 253–290. https://doi.org/10.2307/2343100

Fecher, F.; Pestieau, P. 1993. Efficiency and competition in OECD financial services, The Measurement of Productive Efficiency: 374–385.

Golany, B.; Roll, Y. 1989. An application procedure for DEA, Omega 17(3): 237–250. https://doi.org/10.1016/0305-0483(89)90029-7

Hair, J. F.; Black, W. C.; Babin, B. J.; Anderson, R. E. 2009. Cluster analysis, Chapter 9 in Multivariate Data Analysis. 7th ed. Prentice-Hall.

Haugen, R. A.; Kroncke, C. O. 1970. A portfolio approach to optimizing the structure of capital claims and assets of a stock insurance company, The Journal of Risk and Insurance 37(1): 41–48. https://doi.org/10.2307/251517

Huang, L.-Y.; Ma, Y.-L.; Pope, N. 2012. Foreign ownership and non-life insurer efficiency in the Japanese marketplace, Risk Management and Insurance Review 15(1): 57–88. https://doi.org/10.1111/j.1540-6296.2011.01202.x

Huang, W.; Eling, M. 2013. An efficiency comparison of the non-life insurance industry in the BRIC countries, European Journal of Operational Research 226(3): 577–591. https://doi.org/10.1016/j.ejor.2012.11.008

Hwang, S.-N.; Kao, T.-L. 2008. Using two-stage DEA to measure managerial efficiency change of nonlife insurance companies in Taiwan, International Journal of Management and Decision Making 9(4): 377–401. https://doi.org/10.1504/IJMDM.2008.019362

Jain, A. K. 2010. Data clustering: 50 years beyond K-means, Pattern Recognition Letters 31(8): 651–666. https://doi.org/10.1016/j.patrec.2009.09.011

Jain, A. K.; Murty, M. N.; Flynn, P. J. 1999. Data clustering: a review, ACM computing surveys (CSUR) 31(3): 264–323.

Kao, C. 2009. Efficiency decomposition in network data envelopment analysis: a relational model, European Journal of Operational Research 192(3): 949–962. https://doi.org/10.1016/j.ejor.2007.10.008

Kao, C.; Hwang, S.-N. 2008. Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan, European Journal of Operational Research 185(1): 418–429. https://doi.org/10.1016/j.ejor.2006.11.041

Kuo, K.-C.; Kweh, Q. L.; Ting, I. W. K.; Azizan, N. A. 2017. Dynamic network performance evaluation of general insurance companies: an insight into risk management committee structure, Total Quality Management & Business Excellence 28(5–6): 542–558. https://doi.org/10.1080/14783363.2015.1100516

Kweh, Q. L.; Lu, W.-M.; Wang, W.-K. 2014a. Dynamic efficiency: intellectual capital in the Chinese non-life insurance firms, Journal of Knowledge Management 18(5): 937–951. https://doi.org/10.1108/JKM-06-2014-0240

Kweh, Q. L.; Lu, W.-M.; Wang, W.-K.; Su, M.-H. 2014b. Life insurance companies’ performance and intellectual capital: a long-term perspective, International Journal of Information Technology & Decision Making 13(4): 755–777. https://doi.org/10.1142/S0219622014500588

Liu, J. S.; Lu, L. Y.; Lu, W.-M.; Lin, B. J. 2013. A survey of DEA applications, Omega 41(5): 893–902. https://doi.org/10.1016/j.omega.2012.11.004

Lu, W.-M.; Kweh, Q. L.; Nourani, M.; Huang, F.-W. 2016. Evaluating the efficiency of dual-use technology development programs from the R&D and socio-economic perspectives, Omega 62: 82–92. https://doi.org/10.1016/j.omega.2015.08.011

Lu, W.-M.; Wang, W.-K.; Kweh, Q. L. 2014. Intellectual capital and performance in the Chinese life insurance industry, Omega 42(1): 65–74. https://doi.org/10.1016/j.omega.2013.03.002

Macminn, R. D.; Witt, R. C. 1987. A financial theory of the insurance firm under uncertainty and regulatory constraints, The Geneva Papers on Risk and Insurance – Issues and Practice: 12(1): 3–20. https://doi.org/10.1057/gpp.1987.1

Mahajan, J. 1991. A data envelopment analytic model for assessing the relative efficiency of the selling function, European Journal of Operational Research 53(2): 189–205. https://doi.org/10.1016/0377-2217(91)90134-H

Müller, W. 1981. Theoretical concepts of insurance production, The Geneva Papers on Risk and Insurance – Issues and Practice: 6(4): 63–83. https://doi.org/10.1057/gpp.1981.23

Nourani, M.; Devadason, E. S.; Kweh, Q. L.; Lu, W.-M. 2017. Business excellence: the managerial and value-creation efficiencies of the insurance companies, Total Quality Management & Business Excellence: 28(7–8): 879–896. https://doi.org/10.1080/14783363.2015.1133244

Pfeffer, I.; Klock, D. R. 1974. Perspectives on insurance. Prentice-Hall.

Punj, G.; Stewart, D. W. 1983. Cluster analysis in marketing research: review and suggestions for application, Journal of Marketing Research: 20(2): 134–148. https://doi.org/10.2307/3151680

Tone, K. 2001. A slacks-based measure of efficiency in data envelopment analysis, European Journal of Operational Research 130(3): 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5

Tone, K.; Tsutsui, M. 2009. Network DEA: a slacks-based measure approach, European Journal of Operational Research 197(1): 243–252. https://doi.org/10.1016/j.ejor.2008.05.027

Tone, K.; Tsutsui, M. 2010. Dynamic DEA: a slacks-based measure approach, Omega 38(3): 145–156. https://doi.org/10.1016/j.omega.2009.07.003

Tone, K.; Tsutsui, M. 2014. Dynamic DEA with network structure: a slacks-based measure approach, Omega 42(1): 124–131. https://doi.org/10.1016/j.omega.2013.04.002

Trowbridge, C. L. 1975. Insurance as a transfer mechanism, The Journal of Risk and Insurance 42(1): 1–15. https://doi.org/10.2307/251584

Von Lanzenauer, C. H.; Wright, D. D. 1977. Optimizing claims fluctuation reserves, Management Science: 23(11): 1199–1207. https://doi.org/10.1287/mnsc.23.11.1199

Wanke, P.; Azad, M. A. K.; Barros, C. P. 2016. Financial distress and the Malaysian dual baking system: a dynamic slacks approach, Journal of Banking & Finance 66: 1–18. https://doi.org/10.1016/j.jbankfin.2016.01.006

Wanke, P.; Barros, C. P. 2016. Efficiency drivers in Brazilian insurance: a two-stage DEA meta frontierdata mining approach, Economic Modelling 53: 8–22. https://doi.org/10.1016/j.econmod.2015.11.005

Wanke, P.; Barros, C. P.; Faria, J. R. 2015. Financial distress drivers in Brazilian banks: a dynamic slacks approach, European Journal of Operational Research 240(1): 258–268. https://doi.org/10.1016/j.ejor.2014.06.044

Wu, Y.-C.; Ting, I. W. K.; Lu, W.-M.; Nourani, M.; Kweh, Q. L. 2016. The impact of earnings management on the performance of ASEAN banks, Economic Modelling 53: 156–165. https://doi.org/10.1016/j.econmod.2015.11.023

Xie, X. 2010. Are publicly held firms less efficient? Evidence from the US property-liability insurance industry, Journal of Banking & Finance 34(7): 1549–1563. https://doi.org/10.1016/j.jbankfin.2010.01.007

Zhu, J. 2014. Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets. Springer US. https://doi.org/10.1007/978-3-319-06647-9