A multiple criteria approach to two-stage data envelopment analysis

Two-stage data envelopment analysis (DEA) models are commonly used in the evaluation and benchmarking of sustainable operations and processes across multiple research fields. To date, however, little attention has been given to the unrealistic weight distribution and weak discrimination power in the modeling and evaluation of the two-stage sustainable operations when using two-stage DEA models. In order to overcome this methodological weakness, the authors use the multiple criteria DEA (MCDEA) approach in the evaluation of the two-stage processes. The outcome is a multiple criteria two-stage DEA model which yields more realistic weights for the inputs and outputs and thus has better discrimination power than traditional two-stage DEA models. The developed model is tested and validated by assessing the sustainable design performances of a sample of car product designs.

• Record URL:
  https://doi.org/10.1016/j.trd.2016.04.008
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1361920916302309
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Mahdiloo, Mahdi
  • Jafarzadeh, Abdol Hossein
  • Saen, Reza Farzipoor
  • Tatham, Peter
  • Fisher, Ron
• Publication Date: 2016-7

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 317-327
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 46
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Automobile industry; Industries; Multiple criteria decision making; Nonparametric analysis; Sustainable transportation; Vehicle design
• Uncontrolled Terms: Data envelopment analysis
• Subject Areas: Design; Environment; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01603390
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 28 2016 4:37PM