Developing Network DEA Model with Undesirable Outputs for Evaluation of Green Supply Chain Management


1 MSc. Graduate of Industrial Engineering, Faculty of Industrial Engineering, Urmia University of Technology, Urmia,

2 Associate professor, Faculty of Industrial and Mechanical Engineering, Qazvin branch, Islamic Azad University


By increasing environmental laws and regulations and raising public awareness of environmental protection, companies cannot easily ignore environmental issues if they want to work in global markets and compete with other companies. Green Supply Chain Management has become a proactive approach to enhance environmental performance. Under stakeholder pressures and regulations, firms need to enhance (GSCM) practice, which are influenced by practices such as green purchasing, green design, product recovery, and collaboration with customers and suppliers. As proactive firms adopt GSCM, their economic performance and environmental performance will be enhanced. Hence, GSCM evaluation is very important for any company. One of the techniques that can be used for evaluating GSCM is data envelopment analysis (DEA). Traditional models of data envelopment analysis (DEA) are based upon thinking about production as a “black box”. One of the drawbacks of these models is to omit linking activities the objective of this study to propose network DEA model for evaluating the GSCM in the presence of undesirable outputs. A four-stage supply chain demonstrates the application of the proposed model.


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