Data envelopment scenario analysis with imprecise data

In the existing DEA models, we have a centralized decision maker (DM) who supervises all the operating units. In this paper, we solve a problem in which the centralized DM encounters limited or constant resources for total inputs or total outputs. We establish a DEA target model that solves and deals with such a situation. In our model, we consider the decrease of total input consumption and the increase of total output production; however, in the existing DEA models, total output production is guaranteed not to decrease. Considering the importance of imprecise data in organizations, we define our model so as to deal with interval and ordinal data. A numerical illustration is provided to show the application of our model and the advantages of our approach over the previous one.

[1]  A. Athanassopoulos.  Decision Support for Target-Based Resource Allocation of Public Services in Multiunit and Multilevel Systems , 1998 .

[2]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[3]  Boaz Golany,et al.  An Interactive MOLP Procedure for the Extension of DEA to Effectiveness Analysis , 1988 .

[4]  S. Lozano,et al.  Centralized Resource Allocation Using Data Envelopment Analysis , 2004 .

[5]  Joe Zhu,et al.  Imprecise DEA via Standard Linear DEA Models with a Revisit to a Korean Mobile Telecommunication Company , 2004, Oper. Res..

[6]  Kaoru Tone,et al.  Data Envelopment Analysis , 1996 .

[7]  Emmanuel Thanassoulis,et al.  Estimating preferred target input−output levels using data envelopment analysis , 1992 .

[8]  Jian-Bo Yang,et al.  Interval efficiency assessment using data envelopment analysis , 2005, Fuzzy Sets Syst..

[9]  Antreas D. Athanassopoulos,et al.  Assessing the comparative spatial disadvantage (CSD) of regions in the European Union using non-radial data envelopment analysis methods , 1996 .

[10]  A D Athanassopoulos,et al.  ASSESSING THE COMPARATIVE SPATIAL DISADVANTAGE OF EUROPEAN REGIONS USING NON-RADIAL DATA ENVELOPMENT ANALYSIS MODELS , 1996 .

[11]  Gang Yu,et al.  An Illustrative Application of Idea (Imprecise Data Envelopment Analysis) to a Korean Mobile Telecommunication Company , 2001, Oper. Res..

[12]  Lawrence M. Seiford,et al.  Data envelopment scenario analysis for setting targets to electricity generating plants , 1999, Eur. J. Oper. Res..

[13]  Joe Zhu,et al.  Imprecise data envelopment analysis (IDEA): A review and improvement with an application , 2003, Eur. J. Oper. Res..

[14]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[15]  W. Cooper,et al.  Idea and Ar-Idea: Models for Dealing with Imprecise Data in Dea , 1999 .

[16]  Pekka J. Korhonen,et al.  Resource Allocation Based on Efficiency Analysis , 2004, Manag. Sci..

[17]  G. Jahanshahloo.  Data Envelopment Analysis with Imprecise Data , 2011 .

[18]  A. Athanassopoulos.  Goal programming & data envelopment analysis (GoDEA) for target-based multi-level planning: Allocating central grants to the Greek local authorities , 1995 .

[19]  A D Athanassopoulos,et al.  GOAL PROGRAMMING AND DATA ENVELOPMENT ANALYSIS (GODEA) MODELS FOR MULTI LEVEL MULTI UNITORGANIZATIONS: AN APPLICATION TO GREEK LOCAL AUTHORITIES , 1995 .

[20]  Teresa León,et al.  A fuzzy mathematical programming approach to the assessment of efficiency with DEA models , 2003, Fuzzy Sets Syst..