2019 | 29 | 3 | 77-98
Article title

Flexible measure in the presence of the partial input to output impacts process

Title variants
Languages of publication
Precise recognition of the nonparametric measurement approach in the production process and proper application of accurate techniques to categorise the variables play a key role in the process of improving performance of decision-making units (DMUs). The classical data envelopment analysis (DEA) models require that the status of all inputs and outputs measures be precisely specified in advance. However, there are situations where a performance measure can play input role for some DMUs and output role for the others. This paper introduces an approach to determine the situation of such flexibility where in the presence of resource sharing among subunits, the partial input will impact output in DEA. As a result, DMUs have a fair evaluation when compared to each other. Likewise, the maximum improvement is obtained in aggregate efficiency due to partial input to output impacts. The proposed approach is applied to a set of real data collected from 30 branches of an Iranian bank.
Physical description
  • Department of Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, P.O. Box 1616, Iran,
  • Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Namjoo Street, Rasht, P.O. Box 1914, Iran,
  • Department of Applied Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, P.O. Box 1616, Iran,
  • School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, Province 230026, P.R. China,
  • AMIRTEIMOORI A., EMROUZNEJAD A., KHOSHANDAM L., Classifying flexible measures in data envelopment analysis: A slack-based measure, Measurement, 2013, 46, 4100–4107.
  • AN Q., CHEN H., WU J., LIANG L., Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output, Ann Oper. Res., 2015, 235, 13–35.
  • BANKER R.D., CHARNES A., COOPER W.W., Some models for estimating technical and scale inefficiencies in DEA, Manage. Sci., 1984, 30 (9), 1078–1092.
  • BANKER R.D., MOREY R., Efficiency analysis for exogenously fixed inputs and outputs, Oper. Res., 1986, 34, 513–521.
  • BEASLEY J., Comparing university departments, Omega, 1990, 8 (2), 171–183.
  • BEASLEY J., Determining teaching and research efficiencies, J. Oper. Res. Soc., 1995, 46, 441–452.
  • BI G., DING J., LIANG L., WU J., Models for dealing with dual factors in DEA. Extensions, Proc. 7th International Conference on Data Envelopment Analysis, 2009, available at∼banker/dea2009/paper/Bi.pdf
  • CASTELLY L., PESENTI R., UKOVICH W., A classification of DEA models when the internal structure of the decision making units is considered, Ann. Oper. Res., 2010, 173, 207–235.
  • CHARNES A., COOPER W.W., Programming with linear fractional functions, Nav. Res. Log. Q., 1962, 9, 181–186.
  • CHARNES A., COOPER W., RHODES E., Measuring the efficiency of decision making units, Eur. J. Oper. Res., 1978, 2 (6), 428–444.
  • CHEN W.C., Revisiting dual-role factors in data envelopment analysis. Derivation and implications, IEEE Trans., 2014, 46 (7), 653–663.
  • COOK W.D., HABABOU M., TUENTER H., Multicomponent efficiency measurement and shared inputs in data envelopment analysis. An application to sales and service performance in bank branches, J. Prod. Anal., 2000, 14, 209–224.
  • COOK W.D., HABABOU M., Sales performance measurement in bank branches, Omega, 2001, 29, 299–307.
  • COOK W.D., BALA K., Performance measurement with classification information. An enhanced additive DEA model, Omega, 2003, 31, 439–450.
  • COOK W.D., GREEN R.H., ZHU J., Dual-role factors in data envelopment analysis, IEEE Trans., 2006, 38 (2), 105–115.
  • COOK W.D., ZHU J., Classifying inputs and outputs in data envelopment analysis, Eur. J. Oper. Res., 2007, 180, 692–699.
  • COOK W.D., IMANIRAD R., Data envelopment analysis in the presence of partial input to output impacts, J. Centr. Cath., 2011, 4 (2), 182–196.
  • DING J., DONG W., BI G., LIANG L., A decision model for supplier selection in the presence of dual-role factors, J. Oper. Res. Soc., 2015, 66 (5), 737–746.
  • IMANIRAD R., COOK W.D., ZHU J., Partial input to output impacts in DEA: Production considerations and resource sharing among business sub-units, Nav. Res. Log., 2013, 60 (3), 190–207.
  • IMANIRAD R., COOK W.D., AVILES-SACOTO S.V., ZHU J., Partial input to output impacts in DEA. The case of DMU-specific impacts, Eur. J. Oper. Res., 2015, 244 (3), 837–844.
  • KORDROSTAMI S., JAHANI S.N., Evaluating the performance and classifying the interval data envelopment analysis, Int. J. Manage. Sci. Eng. Manage., 2014, 9, 243–248.
  • KUMAR A., JAIN V., KUMAR S., A comprehensive environment friendly approach for supplier selection, Omega, 2014, 42 (1), 109–123.
  • LI W.H., LIANG L., AVILES-SACOTO V.S., IMANIRAD R., COOK W.D., ZHU J., Modeling efficiency in the presence of multiple partial inputs to outputs processes, Ann. Oper. Res., 2017, 250 (1), 235–248.
  • PARADI J.C., ZHU H., A survey on bank branch efficiency and performance research with data envelopment analysis, Omega, 2013, 41 (1), 61–79.
  • SAEN R.F., A new model for selecting third-party reverse logistics providers in the presence of multiple dual-role factors, Int. J. Adv. Manuf. Tech., 2010, 46 (1), 405–410.
  • TOLOO M., KESHAVARZ E., MARBINI A.H., Dual-role factors for imprecise data envelopment analysis, Omega, 2017, 77 (C), 15–31.
  • WANKE P., BARROS C.P., EMROUZNEJAD A., Assesing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping. A case of Mozambican banks, Eur. J. Oper. Res., 2016, 249 (1), 378–389.
  • WANG K., HUANG W., WU J., Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA, Omega, 2014, 44, 5–20.
  • WU J., ZHU Q., JI X., Two-stage network processes with shared resources and resources recovered from undesirable outputs, Eur. J. Oper. Res., 2016, 251 (1), 182–197.
  • WU J., XIONG B., AN Q., Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs, Ann. Oper. Res., 2017, 255 (1–2), 257–276.
Document Type
Publication order reference
YADDA identifier
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.