생성집합을 이용한 다 기간 성과평가를 위한 DEA 모델 개발 및 공학교육혁신사업 사례적용
Multi-period DEA Models Using Spanning Set and A Case Example
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DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU’s input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.
Abstract
DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU’s input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.
참고문헌 (18)
- Banker, R.D, "Some models for estimating technical and scale inefficiencies in data envelopment analysis", Management Science, 30(9), pp.1078~1092 (1984)
- Charnes, A, "Measuring the efficiency of decision making units", EJOR, 2(6), pp.429~444 (1978)
- Charnes, A, "A developmental study of data envelopment an alysis in measuring the efficiency of maintenance units in the US Air Forces", Annals of Operations Research, 2, pp.59~94 (1985)
- Chen, Y, "Measuring super-efficiency in DEA in the presence of infeasibility", EJOR, 161, pp.545~551 (2005)
- Esmaeilzadeh, A, "A super- efficiency model for measuring aggregative efficiency of multi-period production systems", Measurement, 46(10), pp.3988~3993 (2013)
- Gazori-Nishabori, A, "Multi-period network data envelopment analysis to measure efficiency of a real business", Journal of Industrial and Systems Engineering, 12(3), pp.55~77 (2019)
- Hajiagha, S. H, "Multi-period data envelopment analysis based on Chebyshev inequality bounds", Expert Systems with Applications, 42(21), pp.7759~7767 (2015)
- Jablonsky, J, "Efficiency analysis in multi-period systems:an application to performance evaluation in Czech higher education", Central European Journal of Operational Research, 24, pp.283~296 (2016)
- Jablonsky, J, "Multi-period data envelopment analysis models and resource allocation:A case study", Journal of Physics Conf. Series (2018)
- Kao, C, "Multi-period efficiency and Malmquist productivity index in two-stage production systems", EJOR, 232(3), pp.512~521 (2014)
- Kao, C, "Efficiency decomposition in two-stage data envelopment analysis: An applicationton on-life insurance companies in Taiwan", EJOR, 185, pp.418~429 (2008)
- Kao, C, "Multi-period efficiency measurement in data envelopment analysis: The case of Taiwanese commercial banks", Omega, 47, pp.90~98 (2014)
- Lee, T, "A multi-period output DEA model with consistent time lag effects", Computers & Industrial Engineering, 93, pp.267~274 (2016)
- 마진희, "한국 물류기업들의 경영효율성 및 다기간 생산성 분석", 물류학회지, 32(1), pp.43~52 (2022), 한국물류학회
- Nikolaou, P, "Lessons to be Learned from Top-50 Global Container Port Terminals Efficiencies: A Multi-Period DEA-Tobit Approach", Maritime Transport Research, 2, pp.100032~ (2021)
- Park, K, "Measurement of multiperiod aggregative efficiency", EJOR, 193(2), pp.567~580 (2009)
- 손동훈, "다기간 자료포락분석을 이용한 전기차 충전소 효율성 변화 분석", 한국산업경영시스템학회지, 44(2), pp.1~14 (2021), 한국산업경영시스템학회
- Xu, Y.W, "Efficiency measurement in multi-period network DEA model with feedback", Expert Systems with Applications, 175, pp.114815~ (2021)