A new network epsilon-based DEA model for supply chain performance evaluation

Computers and Industrial Engineering

Volumn 66, Issue 2, 2013, Pages 501-513

  Tavana, Madjid ^a,b   Mirzagoltabar, Hadi ^c   Mirhedayatian, Seyed Mostafa ^d   Saen, Reza Farzipoor ^e   Azadi, Majid ^e  

^a LA SALLE UNIVERSITY   (United States)

^b UNIVERSITY OF PADERBORN   (Germany)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

^d ISLAMIC AZAD UNIVERSITY   (Iran)

^e ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Epsilon based measure; Network data envelopment analysis; Supply chain performance evaluation

Indexed keywords

COMPLEX NETWORKS; DATA ENVELOPMENT ANALYSIS; DECISION MAKING; EFFICIENCY; SEMICONDUCTOR DEVICE MANUFACTURE; SUPPLY CHAINS;

DECISION MAKING UNIT; EPSILON-BASED MEASURE; EVALUATION PROBLEMS; NETWORK DATA; ORGANIZATIONAL UNITS; RELATIVE PERFORMANCE; SEMICONDUCTOR INDUSTRY; SUPPLY CHAIN PERFORMANCE;

PROBLEM SOLVING;

EID: 84885178086     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2013.07.016     Document Type: Article

References (32)

1. Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiency in data envelopment analysis. Management Science, 30(9), 1078-1092.
2. Charnes, A., Cooper, W. W., Lewin, A. Y., & Seiford, L. M. (1994). Data envelopment analysis: Theory, methodology, and application. Norwell: Kluwer Academic Publishers.
3. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
4. Chen, C., & Yan, H. (2011). Network DEA model for supply chain performance evaluation. European Journal of Operational Research, 213(1), 147-155.
5. Chen, Y., & Zhu, J. (2004). Measuring information technology's indirect impact on firm performance. Information Technology and Management, 5(1-2), 9-22.
6. Chow, G., Heaver, T. D., & Henriksson, L. E. (1994). Logistics performance: Definition and measurement. International Journal of Physical Distribution and Logistics Management, 24(1), 17-28.
7. Cook, W. D., & Seiford, L. M. (2009). Data envelopment analysis (DEA)-Thirty years on. European Journal of Operational Research, 192(1), 1-17.
8. Cooper, W. W., Seiford, L. M., & Tone, K. (1999). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Boston: Kluwer Academic Publishers.
9. Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses with DEA solver software and references. New York: Springer Science and Business Media.
10. Emrouznejad, A., & De Witte, K. (2010). COOPER-framework: A unified process for non-parametric projects. European Journal of Operational Research, 207(3), 1573-1586.
11. Emrouznejad, A., Parker, B. R., & Tavares, G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sciences, 42, 151-157.
12. Estampe, D., Lamouri, S., Paris, J. L., & Brahim-Djelloul, S. (2013). A framework for analyzing supply chain performance evaluation models. International Journal of Production Economics, 142(2), 247-258.
13. Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120, 253-290.
14. Golany, B., Hackman, S. T., & Passy, U. (2006). An efficiency measurement framework for multi-stage production systems. Annals of Operations Research, 145(1), 51-68.
15. Halme, M., Joro, T., Korhonen, P., Salo, S., & Wallenius, J. (1999). A value efficiency approach to incorporating preference information in data envelopment analysis. Management Science, 45(1), 103-115.
16. Kao, C. (2009). Efficiency decomposition in network data envelopment analysis: A relational model. European Journal of Operational Research, 192(3), 949-962.
17. Kao, C., & Hwang, S. N. (2007). 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.
18. Kleindorfer, P. R., Kunreuther, H. C., & Schoemaker, P. J. H. (1993). Decision sciences: An integrative perspective. New York: Cambridge University Press.
19. Korhonen, P., Rytokoski, S., & Syrjanen, M. (2001). A critical analysis of radial projection in data envelopment analysis. Working paper. Helsinki School of Economics and Business Administration.
20. Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation. Annals of Operations Research, 145(1), 35-49.
21. Lin, C. T., Chiu, H., & Tseung, Y. H. (2006). Agility evaluation using fuzzy logic. International Journal of Production Economics, 101(2), 353-368.
22. Quariguasi Frota Neto, J., & Angulo-Meza, L. (2006). Alternative targets for data envelopment analysis through multi-objective linear programming: Rio de Janeiro Odontological Public Health System Case Study. Journal of the Operational Research Society, 58, 865-873.
23. Saranga, H., & Moser, R. (2010). Performance evaluation of purchasing and supply management using value chain DEA approach. European Journal of Operational Research, 207(1), 197-205.
24. Seiford, L. M. (1997). A bibliography for data envelopment analysis. Annals Operations Research, 73, 393-438.
25. Talluri, S., Narasimhana, R., & Nairb, A. (2006). Vendor performance with supply risk: A chance-constrained DEA approach. International Journal of Production Economics, 100(2), 212-222.
26. Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3), 498-509.
27. Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European Journal of Operational Research, 197(1), 243-252.
28. Tone, K., & Tsutsui, M. (2010). An epsilon-based measure of efficiency in DEA-A third pole of technical efficiency. European Journal of Operational Research, 207(3), 1554-1563.
29. Torabi, S. A., & Hassini, E. (2009). Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: An interactive fuzzy goal programming approach. International Journal of Production Research, 47(19), 5475-5499.
30. Wong, W. P., Jaruphongsa, W., & Lee, L. H. (2008). Supply chain performance measurement system: A Monte Carlo DEA-based approach. International Journal of Industrial and Systems Engineering, 3(2), 162-188.
31. Wong, W. P., & Wong, K. Y. (2007). Supply chain performance measurement system using DEA modeling. Industrial Management and Data Systems, 107(3), 361-381.
32. Yu, M. M., Ting, S. C., & Chen, M. C. (2010). Evaluating the cross-efficiency of information sharing in supply chains. Expert Systems with Applications, 37(4), 2891-2897.