Evaluating Performance of Telecommunication Branch : Application of DEA with Non-Discretionary Factor
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Improving efficiency of the telecommunication is crucial to the development and growth of Korean economy. Recently, it has become important with the huge development of information technology and its greater potential for extensive impact on the rest of the economy. Hence, it is useful to determine the factors that help enhance efficiency in telecommunication and consider them in improving the evaluation model. This study applies DEA (data envelopment analysis) to evaluate the relative efficiency of 51 branches of a Korean telecommunication company. Using the super-efficiency approach, we tested outliers which may affect the results and ranked the efficient branches. A method of deriving key variables applied to business operation is proposed to identify the key performance indicators for evaluation that takes environmental (non-discretionary) factors into account. We used the extended CCR model proposed by Banker and Morey to investigate the influence of non-discretionary factor. The information provided by the model (slacks, weights) and the sensitivity analysis shows that the most important indicator that affects the branch performance is operating cost. The results of sensitivity analysis show that average efficient score decreases from 0.972 (base case) to 0.863 for CASE2-COST. The average score of the data proves the priority of operating cost over other indicators. The effect of environmental (non-discretionary) variable was found to be significant. The population effect was positive and improved overall efficiency by 0.91% on average. Non-discretionary factor plays a meaningful role explaining the performance of branches. The performance optimization report can help a manager of an inefficient branch to develop branch strategies. Managers can identify the top-performing units, study best practices and adopt the strategy to the organization.
Abstract
Improving efficiency of the telecommunication is crucial to the development and growth of Korean economy. Recently, it has become important with the huge development of information technology and its greater potential for extensive impact on the rest of the economy. Hence, it is useful to determine the factors that help enhance efficiency in telecommunication and consider them in improving the evaluation model. This study applies DEA (data envelopment analysis) to evaluate the relative efficiency of 51 branches of a Korean telecommunication company. Using the super-efficiency approach, we tested outliers which may affect the results and ranked the efficient branches. A method of deriving key variables applied to business operation is proposed to identify the key performance indicators for evaluation that takes environmental (non-discretionary) factors into account. We used the extended CCR model proposed by Banker and Morey to investigate the influence of non-discretionary factor. The information provided by the model (slacks, weights) and the sensitivity analysis shows that the most important indicator that affects the branch performance is operating cost. The results of sensitivity analysis show that average efficient score decreases from 0.972 (base case) to 0.863 for CASE2-COST. The average score of the data proves the priority of operating cost over other indicators. The effect of environmental (non-discretionary) variable was found to be significant. The population effect was positive and improved overall efficiency by 0.91% on average. Non-discretionary factor plays a meaningful role explaining the performance of branches. The performance optimization report can help a manager of an inefficient branch to develop branch strategies. Managers can identify the top-performing units, study best practices and adopt the strategy to the organization.
참고문헌 (25)
- Productivity analysis in the service sector with data envelopment analysis, "Avkiran, N.", ~ (2006)
- Banker, R.D., "A relative efficiency model for the evaluation of public health nurse productivity", Mellon University Mimeo, ~ (1988)
- Banker, R.D., "Efficiency analysis for exogenously fixed inputs and outputs", Operations research, 34(4), pp.513~521 (1986)
- Berg, S., "Water Utility Benchmarking : Measurement, Methodology, and Performance Incentives" (2010), International Water Association
- Camanho, A. S., "Efficiency analysis accounting for internal and external non-discretionary factors", Computers & Operations Research, 36(5), pp.1591~1601 (2009)
- Charnes, A., "Measuring the efficiency of decision making units", European Journal of Operational Research, 2(6), pp.429~444 (1978)
- Cooper, W. W., "An illustrative application of IDEA (imprecise data envelopment analysis)to a Korean mobile telecommunication company", Operations Research, 49(6), pp.807~820 (2001)
- Cooper, W. W., "Data Envelopment Analysis-A comprehensive Text with Models, Applications, reference and DEA-solver software" (2007), Springer
- Cordero-Ferrera, J. M., "Enhancing the inclusion of non-discretionary inputs in DEA", Journal of the Operational Research Society, 61(4), pp.574~584 (2010)
- Giokas, D.I., "Efficiency ranking of the OECD member states in the area of telecommunications : A composite AHP", DEA study, 2008, pp.32(9), 672~685
- 한유정, "DEA와 AHP를 이용한 대학의 성과 평가", 산업경영시스템학회지, 37(3), pp.51~63 (2014), 한국산업경영시스템학회
- Lam, P.L., "Productivity analysis of the telecommunications sector in China", Telecommunications Policy, 32(8), pp.559~571 (2008)
- Lotfi, F. H., "Nondiscretionary factors and imprecise data in DEA", International Journal of Math Analysis, 1(5), pp.237~246 (2007)
- Masson, S., "Operational efficiency and service delivery performance :A comparative analysis of Indian telecom service providers", Benchmarking : An International Journal, 23(4), pp.893~915 (2016)
- Muniz, M. A., "Separating managerial inefficiency and external conditions in data envelopment analysis", European Journal of Operational Research, 143(3), pp.625~643 (2002)
- Nigam, V., "Benchmarking of Indian mobile telecom operators using DEA with sensitivity analysis", Benchmarking An International Journal, 19(2), pp.219~238 (2012)
- Pahwa, A., "Performance evaluation of electric distribution utilities based on data envelopment analysis", IEEE Transactions on Power Systems, 18(1), pp.400~405 (2003)
- Scheel, H., "EMS : efficiency measurement system user’s manual, Operations Research and Witshaftinsformetik", University of Dortmund, ~ (2000)
- Sherman, H.D., "Analyzing performance in service organizations", MIT Sloan Management Review, 54(4), pp.37~ (2013)
- Sherman, H.D., "Service Productivity Management, Improving Service Performance using Data Envelopment Analysis(DEA)" (2006), Springer
- Shin, R., "Costly Gains to Breaking Up :LECs and the Baby Bells", Review of Economics and Statistics, 98, pp.357~361 (1993)
- Sueyoshi, T., "Measuring efficiencies and returns to scale of Nippon Telegraph & Telephone in production and cost analyses", Management Science, 43(6), pp.779~796 (1997)
- Tsai, H. C., "The comparative productivity efficiency for global telecoms", International Journal of Production Economics, 103(2), pp.509~526 (2006)
- Uri, N. D., "Technical efficiency, allocative efficiency, and the implementation of a price cap plan in telecommunications in the United States", Journal of Applied Economics, 4(1), pp.163~186 (2001)
- Yang, H.H., "Using DEA window analysis to measure efficiencies of Taiwan's integrated telecommunication firms", Telecommunications Policy, 33(1), pp.98~108 (2009)