Nash bargaining game model for two parallel stages process evaluation with shared inputs

International Journal of Advanced Manufacturing Technology

Volumn 67, Issue 1-4, 2013, Pages 475-484

  Jalali Naini, Seyed Gholamreza ^a   Moini, Alireza ^a   Jahangoshai Rezaee, Mustafa ^a,b  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b URMIA UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Bank branches; Data envelopment analysis; Game theory; Nash bargaining game; Power plants; Two stage process

Indexed keywords

BANK BRANCHES; COMPETITIVE STRATEGY; DECISION MAKING UNIT; INTERMEDIATE MEASURE; NASH BARGAINING GAME; NON-PARAMETRIC TECHNIQUES; THERMAL POWER PLANTS; TWO-STAGE PROCESS;

DATA ENVELOPMENT ANALYSIS; POWER PLANTS; SUPPLY CHAINS; THERMOELECTRIC POWER PLANTS;

GAME THEORY;

EID: 84887520594     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-012-4498-0     Document Type: Article

References (20)

1. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429-444
2. Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078-1092
3. Weber CA, Desai A (1996) Determinants of paths to vendor market efficiency using parallel coordinates representation: a negotiation tool for buyers. Eur J Oper Res 90:142-155
4. Easton L, Murphy DJ, Pearson JN (2002) Purchasing performance evaluation: with data envelopment analysis. Eur J Purch Supply Manag 8:123-134
5. Chen Y, Liang L, Yang F (2006) A DEA game model approach to supply chain efficiency. Ann Oper Res 145:5-13
6. Cook WD, Liang L, Zhu J (2010) Measuring performance of two-stage network structures by DEA: a review and future perspective. Omega 38:423-430
7. Seiford LM, Zhu J (1999) Profitability and marketability of the top 55 US commercial banks. Manag Sci 45(9):1270-1288
8. Zhu J (2000) Multi-factor performance measure model with an application to Fortune 500 companies. Eur J Oper Res 123(1):105-124
9. Chilingerian J, Sherman HD (2004) Health care applications: from hospitals to physician, from productive efficiency to quality frontiers. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis. Springer, Boston
10. Kao C, Hwang SN (2008) Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan. Eur J Oper Res 185(1):418-429
11. Castelli L, Pesenti R, Ukovich W (2004) DEA-like models for the efficiency evaluation of hierarchically structured units. Eur J Oper Res 154(2):465-476
12. Chen Y, Zhu J (2004) Measuring information technology's indirect impact on firm performance. Inf Technol Manag J 5(1-2):9-22
13. Tone K, Tsutsui M (2010) Dynamic DEA: a slacks-based measure approach. Omega 38(3-4):145-156
14. Chen Y, Liang L, Yang F, Zhu J (2006) Evaluation of information technology investment: a data envelopment analysis approach. Comput Oper Res 33(5):1368-1379
15. Avkiran NK (2009) Opening the black box of efficiency analysis: an illustration with UAE banks. Omega 37:930-941
16. Yu M-M, Lin ETJ (2008) Efficiency and effectiveness in railway performance using a multi-activity network DEA model. Omega 36:1005-1017
17. Liang L, Yang F, Cook WD, Zhu J (2006) DEA models for supply chain efficiency evaluation. Ann Oper Res 145(1):35-49
18. Liang L, Cook WD, Zhu J (2008) DEA models for two-stage processes: game approach and efficiency decomposition. Nav Res Logist 55:643-653
19. Nash JF (1950) The bargaining problem. Econometrica 5:155-162
20. Seiford LM, Zhu J (2002) Modeling undesirable factors in efficiency evaluation. Eur J Oper Res 142(1):16-20