Developing distinctive two-stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management

Mohsen Khodakarami, Amir Shabani, Reza Farzipoor Saen*, Majid Azadi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

73 Citations (Scopus)

Abstract

Sustainable supply chain management (SSCM) has received much attention from scholars and practitioners in the past years. It has become a method for simultaneous improvement of economic, social, and environmental performance. SSCM evaluation, therefore, is a significant duty for any types of organizations. Among evaluation methods, data envelopment analysis (DEA) seems to be an appropriate technique for assessment of the SSCM. One of the uses of DEA is to evaluate the efficiency of two-stage processes, where all the outputs from the first stage are intermediate measures that are considered as the inputs to the second stage. The resulting two-stage DEA models assess both the overall efficiency score of the whole process and each of the individual stages. Notwithstanding, there are major weaknesses in the previous extensions of two-stage DEA models. Firstly, a challenging issue is that suggestions for improvements are offered only for input and output measures, and intermediate measures are neglected. Although, some extensions for network structures take into account intermediate measures, they arbitrarily assign an input or output role for the measures, thus in optimal solution for inefficient DMUs, this measures are forced to respectively take a lower or upper amount. Secondly, the efficiency scores are calculated based on inputs and outputs. That is, while the models consider these measures by corresponding constraints, the intermediate measures are not included in the objective function, or incorrectly assign an input or output role. Thirdly, in some cases, the former developments specify points on the efficient frontier only for inefficient stages, while for a network which is entirely inefficient such points are also required. Moreover, the organization (which in DEA terminology is named decision making unit) is supposed to be divided into two autonomous departments. It means that the performance of one department is quite unrelated to another department, while from the organizational perspective this is called into the question. To overcome these shortcomings, in this paper, innovative models are proposed. The proposed ideas are used for evaluating the sustainability of supply chains in resin producing companies.

Original languageEnglish
Pages (from-to)62-74
Number of pages13
JournalMeasurement: Journal of the International Measurement Confederation
Volume70
DOIs
Publication statusPublished - Jun 1 2015

Keywords

  • Black-box
  • Data envelopment analysis
  • DEA
  • Sustainable supply chain management
  • Two-stage

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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