Journal Screenshot

International Journal of Academic Research in Business and Social Sciences

Open Access Journal

ISSN: 2222-6990

An Integrated DEA and PROMETHEE II Method for Complete Ranking: An Application in Life-Insurance Sector

Nor Faradilah Mahad, Nur Azlina Abd Aziz, Farah Azaliney Mohd Amin, Jamilah Mohd Mahyideen

http://dx.doi.org/10.6007/IJARBSS/v11-i10/11123

Open access

Globally, insurance and takaful companies play a crucial role in economic and financial development of a country. Malaysia’s insurance sector has undergone substantial changes compared to two decades ago. Due to intense competition observed in Malaysian insurance industry, efficiency measurement and a complete efficiency ranking of insurance companies are very important for the decision makers so that necessary changes and improvement can be made. Data Envelopment Analysis (DEA) is a non-parametric method that has been acknowledged as an effective method to measure the efficiency of homogeneous decision-making units (DMUs). The main advantage of DEA is its ability to handle multiple inputs and outputs. However, standard DEA has poor discrimination power since it generates too many efficient units especially when the number of DMUs under study is insufficient in comparison to number of inputs and outputs. It cannot discriminate efficient units and therefore unable to give a complete ranking of DMUs. This study aimed to overcome the ranking problem found in standard DEA by integrating DEA and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II. The hybrid method was applied to evaluate the efficiency and ranking of 22 life insurance and takaful companies in Malaysia from the period of 2017 to 2018. Input variables used in this study comprised of fees and commission, and management expenses. Meanwhile, output variables were net premium and generated investment income. The proposed method involved two stages. In the first stage, DEA was applied to obtain the efficient scores for the DMUs. In the second stage, PROMETHEE II was implemented to rank the efficient units. This hybrid method has successfully obtained full ranking of all the insurance companies under study. The inefficient companies can learn strategies and practices from efficient companies to enhance their services. It is recommended for future research to integrate DEA with other Multi Criteria Decision Making (MCDM) methods such as TOPSIS and VIKOR to fully rank the DMUs.

Abidin, Z., & Cabanda, E. (2011). Efficiency of non-life insurance in Indonesia. Journal of Economics, Business, and Accountancy Ventura, 14(3), 197–202. https://doi.org/10.14414/jebav.v14i3.46
Andersen, P., & Petersen, N. C. (1993). A Procedure for Ranking Efficient Units in Data Envelopment Analysis. Management Science, 39(10), 1261–1264. https://doi.org/10.1287/mnsc.39.10.1261
Athawale, V. M., & Chakraborty, S. (2011). A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection. International Journal of Industrial Engineering Computations, 2(4), 831–850. https://doi.org/10.5267/j.ijiec.2011.05.002
Bal, H., Örkcü, H. H., & Çelebio?lu, S. (2010). Improving the discrimination power and weights dispersion in the data envelopment analysis. Computers and Operations Research, 37(1), 99–107. https://doi.org/10.1016/j.cor.2009.03.028
BrandIndex. (2020). 2019 Index Rankings: Malaysia Insurance.
Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research, 24(2), 228–238.
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. In Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software: Second Edition. https://doi.org/10.1007/978-0-387-45283-8
Gavade, R. K. (2014). Multi-Criteria Decision Making?: An overview of different selection problems and methods. International Journal of Computer Science and Information Technologies, 5(4), 5643–5646.
Ibanding. (2020). Top 5 Life Insurance in Malaysia.
Jafari, M., & Mousavi, M. (2017). Performance Analysis and Rating of Insurance Companies Using DEA in Iran Capital Market. Advances in Mathematical Finance & Applications, 2(3), 41–50.
Kuang, H., Kilgour, D. M., & Hipel, K. W. (2015). Grey-based PROMETHEE II with application to evaluation of source water protection strategies. Information Sciences, 294, 376–389. https://doi.org/10.1016/j.ins.2014.09.035
Lotfi, F. H., Fallahnejad, R., & Navidi, N. (2011). Ranking efficient units in DEA by using TOPSIS method. Applied Mathematical Sciences, 5(17), 805–815.
Mahad, N. F., Aziz, N. A. A., Amin, F. A. M., & Mahyideen, J. M. (2021). An Integrated DEA and PROMETHEE II Method for Complete Ranking: An Application in Life-Insurance Sector. International Journal of Academic Research in Business and Social Sciences, 11(10), 963 – 972.
Polat, G., Damci, A., Gurgun, A. P., & Demirli, I. (2016). Urban Renewal Project Selection Using the Integration of AHP and PROMETHEE Approaches. Procedia Engineering, 164, 339–346. https://doi.org/10.1016/j.proeng.2016.11.628
Saad, N. M., Idris, N. E. H., & Edzalina, N. (2011). Efficiency of life insurance Companies in Malaysia and Brunei?: A comparative analysis. International Journal of Humanities and Social Science, 1(3), 111–122.
Sanches, A. M., Loures, de F. R. E., & de Lima, E. P. (2019). Use of PROMETHEE method for decision making in bus fleet maintenance proposal of framework. Procedia Manufacturing, 39, 1913–1920. https://doi.org/10.1016/j.promfg.2020.01.241
Sen, D. K., Datta, S., Patel, S. K., & Mahapatra, S. S. (2015). Multi-criteria decision making towards selection of industrial robot: Exploration of PROMETHEE II method. Benchmarking, 22(3), 465–487. https://doi.org/10.1108/BIJ-05-2014-0046
Shieh, H. S., Hu, J. L., & Ang, Y. Z. (2020). Efficiency of Life Insurance Companies: An Empirical Study in Mainland China and Taiwan. SAGE Open, 10(1), 2158244020902060. https://doi.org/10.1177/2158244020902060
Toloo, M. (2012). Alternative solutions for classifying inputs and outputs in data envelopment analysis. Computers and Mathematics with Applications, 63(6), 1104–1110. https://doi.org/10.1016/j.camwa.2011.12.016
Toloo, M., & Nalchigar, S. (2009). A new integrated DEA model for finding most BCC-efficient DMU. Applied Mathematical Modelling, 13(1), 597–604. https://doi.org/10.1016/j.apm.2008.02.001
Wang, Y. M., Luo, Y., & Lan, Y. X. (2011). Common weights for fully ranking decision making units by regression analysis. Expert Systems with Applications, 38(8), 9122–9128. https://doi.org/10.1016/j.eswa.2011.01.004
Wu, Y., Zhang, B., Wu, C., Zhang, T., & Liu, F. (2019). Optimal site selection for parabolic trough concentrating solar power plant using extended PROMETHEE method?: A case in China. Renewable Energy, 143, 1910–1927. https://doi.org/10.1016/j.renene.2019.05.131
Wu, Y., Zhang, T., & Yi, L. (2020). An Internal Type-2 Trapezoidal Fuzzy Sets-PROMETHEE-II based Investment Decision Framework of Compressed Air Energy Storage Project in China under the Perspective of Different Investors. Journal of Energy Storage, 30(January), 101548. https://doi.org/10.1016/j.est.2020.101548
Zimková, E. (2015). Technical efficiency and super-efficiency of the insurance sector in Slovakia. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 63(6), 2205–2211. https://doi.org/10.11118/201563062205

In-Text Citation: (Mahad et al., 2021)
To Cite this Article: Mahad, N. F., Aziz, N. A. A., Amin, F. A. M., & Mahyideen, J. M. (2021). An Integrated DEA and PROMETHEE II Method for Complete Ranking: An Application in Life-Insurance Sector. International Journal of Academic Research in Business and Social Sciences, 11(10), 982 – 992.