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International Journal of Academic Research in Accounting, Finance and Management Sciences

Open Access Journal

ISSN: 2225-8329

Incorporating Expert Judgement into Life Insurance and Life Takaful Companies’ Efficiency Measurement Through DEA-AR/FAHP Approach

Nur Azlina Abd Aziz, Nor Faradilah Mahad, Jamilah Mohd Mahyideen, Eley Suzana Kasim

http://dx.doi.org/10.6007/IJARAFMS/v11-i11/11250

Open access

Increased competition within the insurance industry has led to the critical need for insurance companies to utilise their resources efficiently. Data Envelopment Analysis (DEA) model has been widely used to measure the relative efficiency of these companies. However, a limitation of the conventional model indicates that certain crucial factors were ignored in the analysis resulting in unrealistic efficiency outcomes. Hence, the present study aimed to provide a more robust efficiency measurement by incorporating the subjective value of judgement in the standard DEA through a hybrid model which integrates Constant Return Scale model of DEA, Assurance Region Type I (ARI), and Fuzzy Analytic Hierarchy Process (FAHP) method. This proposed DEA-AR/FAHP model was applied on the data gathered from 22 Malaysian life insurance and takaful companies between 2017 and 2018. Findings revealed that the model provides an improved efficiency assessment through the elimination of zero weights and hence deliver more realistic results.

Abd. Majid, M. S., Abdul Hamid., & Faradilla. (2017). Assessing the productivity of insurance companies in Indonesia: A non-parametric approach. Journal of Applied Economic Sciences, 12(6), 1593-1605.
Abidin, Z., & Cabanda, E. (2011). Efficiency of non-life insurance in Indonesia. Journal of Economics, Business and Accountancy Ventura, 14(3), 197 – 202.
Allen, R., Athanassopoulos, A., Dyson, R., & Thanassoulis, E. (1997). Weights restrictions and value judgements in data envelopment analysis: evolution, development and future directions. Annals of Operations Research, 73, 13-34.
Almulhim, T. (2019). Analysis of takaful vs. conventional insurance firms’ efficiency: Two- stage DEA of Saudi Arabia’s insurance market. Cogent Business & Management, 6(1), 1633807.
Antonio, M. S., Ali, M. M., & Akbar, N. (2013). A comparative analysis of the efficiency of takaful and conventional insurance in Malaysia. International Journal of Excellence in Islamic Banking and Finance, 182(881), 1-13.
Bal, H., Örkcü, H. H., & Çelebio?lu, S. (2010). Improving the discrimination power and weights dispersion in the data envelopment analysis. Computers & Operations Research, 37(1), 99-107.
Bank Negara of Malaysia. (2020). Retrieved from
https://www.bnm.gov.my/index.php?ch=li&cat=insurance&type=L&fund=0&cu=0
Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247.
Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Chen, F. C., Liu, Z. J., & Kweh, Q. L. (2014). Intellectual capital and productivity of Malaysian general insurers. Economic Modelling, 36, 413-420.
Coelli, T. J., Rao, D. S. P., O'Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis. Springer Science & Business Media.
Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references. Springer Science & Business Media.
Cummins, J. D., Tennyson, S., & Weiss, M. A. (1999). Consolidation and efficiency in the US life insurance industry. Journal of Banking & Finance, 23(2-4), 325-357.
Deng, H. (1999). Multicriteria analysis with fuzzy pairwise comparison. International Journal of Approximate Reasoning, 21(3), 215–231.
Dyson, R. G., Allen, R., Camanho, A. S., Podinovski, V. V., Sarrico, C. S., & Shale, E. A. (2001). Pitfalls and protocols in DEA. European Journal of Operational Research, 132(2), 245-259.
Eling, M., & Luhnen, M. (2010). Efficiency in the international insurance industry: A cross- country comparison. Journal of Banking & Finance, 34(7), 1497-1509.
Emrouznejad, A., & Thanassoulis, E. (2014). Introduction to performance improvement management software (PIM-DEA). In Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis (pp. 256-275). IGI Global.
Kahraman, C., Cebeci, U., & Ruan, D. (2004). Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey. International Journal of Production Economics, 87(2), 171–184.
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.
Khalili, M., Camanho, A. S., Portela, M. C. A. S., & Alirezaee, M. R. (2010). The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs. European Journal of Operational Research, 203(3), 761-770.
Kubler, S., Robert, J., Derigent, W., Voisin, A., & Le Traon, Y. (2016). A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert Systems with Applications, 65, 398–422.
Life Insurance Association of Malaysia. (2019). Retrived from http://www.liam.org.my/images/news/en/SmartInvestor_LIAM_June_2019.pdf
Mansur, S., & Radam, A. (2000). Productivity and efficiency performance of the Malaysian life insurance industry. Jurnal Ekonomi Malaysia, 34, 93-105.
Masud, M. M., Rana, M. S., Mia, M. A., & Saifullah, M. K. (2019). How productive are life insurance institutions in Malaysia? A Malmquist approach. Journal of Asian Finance, Economics and Business, 6(1), 241-248.
Matsawali, M. S., Abdullah, M. F., Yeo, C.P., Abidin, S. Y., Zaini, M. M., Ali, H. M., Alani, F., & Yaacob, H. (2012). A study on takaful and conventional insurance preferences: The case of Brunei. International Journal of Business and Social Science, 3(22), 163- 176.
Meador, J. W., Ryan, H. E., & Schellhorn, C. D. (2000). Product focus versus diversification: Estimates of X-Efficiency for the US life insurance industry. In T. P. Harker and S. A. Zenios (Eds.), Performance of financial institutions: Efficiency, Innovation, Regulation (175–198). Cambridge University Press.
Mohamad, N. S., Paszil, A. N. F., & Hashim, N. Z. (2019). A two-stage model in evaluating the efficiency of life insurance companies based on DEA/AHP method. Universiti Teknologi MARA Negeri Sembilan, Malaysia.
Ozdemir, M. S., & Saaty, T. L. (2006). The unknown in decision making. What to do about it. European Journal of Operational Research, 174, 349–359.
Premachandra, I. (2001). Controlling factor weights in data Envelopment analysis by incorporating decision maker's value judgement: An approach based on AHP. International journal of information and management sciences, 12(2), 67-82.
Rusydiana, A. S., & Nugroho, T. (2017). Measuring efficiency of life insurance institution in Indonesia: Data Envelopment Analysis approach. Global Review of Islamic Economics and Business, 5(1), 12-24.
Saad, N. M. (2012). An analysis on the efficiency of takaful and insurance companies in Malaysia: a non-parametric approach. Review of Integrative Business & Economics Research, 1(1), 33-56.
Saad, N. M., Abd Majid, M. S., Yusof, M. R., Yusof, J., Duasa, A., & Rahim, A. (2006). Measuring efficiency of insurance and takaful companies in Malaysia using Data Envelopment Analysis (DEA). Review of Islamic Economics, 10, 5-26.
Saad, N. M., & Idris, N. E. H. (2011). Efficiency of life insurance companies in Malaysia and Brunei: A comparative analysis. International Journal of Humanities and Social Science, 1(3), 111-122.
Saaty, T. L. (1994). Highlights and critical points in the theory and application of the Analytic Hierarchy Process. European Journal of Operational Research, 74, 426–447.
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.
Vahidnia, M. H., Alesheikh, A. A., & Alimohammadi, A. (2009). Hospital site selection using fuzzy AHP and its derivatives. Journal of Environmental Management, 90(10), 3048–3056.
Van Laarhoven, P. J., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 11, 229–241.
Kumar, V. N., & Ganesh, L. S. (1996). An empirical analysis of the use of the Analytic Hierarchy Process for estimating membership values in a fuzzy set. Fuzzy Sets and Systems, 82(1), 1–16.
Wang, Y.-M., Luo, Y., & Hua, Z. (2008). On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research, 186(2), 735–747.
Wang, Z. L., Kim, J., Selvachandran, G., Smarandache, F., Son, L. H., Abdel-Basset, M., Thong, P.H., & Ismail, M. (2019). Decision Making Methods for Evaluation of Efficiency of General Insurance Companies in Malaysia: A Comparative Study. IEEE Access, 7, 160637–160649.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.

In-Text Citation: (Aziz et al., 2021)
To Cite this Article: Aziz, N. A. A., Mahad, N. F., Mahyideen, J. M., & Kasim, E. S. (2021). Incorporating Expert Judgement into Life Insurance and Life Takaful Companies’ Efficiency Measurement Through DEA-AR/FAHP Approach. International Journal of Academic Research in Business and Social Sciences, 11(11), 202–221.