Title: Green supplier selection: a novel fuzzy double frontier data envelopment analysis model to deal with undesirable outputs and dual-role factors

Authors: Majid Azadi; Seyed Mostafa Mirhedayatian; Reza Farzipoor Saen; Mahshid Hatamzad; Ehsan Momeni

Addresses: Department of Industrial Management, Faculty of Management and Accounting, Karaj Branch, Islamic Azad University, Karaj, Iran ' Young Researchers Club, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran ' Department of Industrial Management, Faculty of Management and Accounting, Karaj Branch, Islamic Azad University, P.O. Box 31485-313, Karaj, Iran ' Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran ' Department of industrial Engineering, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

Abstract: In recent years, green movements, governments and institutions have forced many companies to improve their environmental performance. As a result of this growing interest in the environment, many companies have created integrated relationships with their suppliers to present green products and services. In public transportation sector, the evaluation and selection of appropriate green suppliers according to green supply chain management (GSCM) criteria is necessary for the sustainable development of urban transportation system. Among many evaluation selection methods, data envelopment analysis (DEA) is an appropriate method for green supplier selection. In this paper, to select green suppliers, we propose a new fuzzy double frontier DEA model in the presence of undesirable outputs and dual-role factors. A case study is presented to illustrate the applicability of the proposed model.

Keywords: green SCM; supply chain management; GSCM; green suppliers; supplier selection; data envelopment analysis; DEA; undesirable outputs; dual-role factors; fuzzy logic; public transport; sustainable development; sustainable transport; sustainability; urban transport.

DOI: 10.1504/IJISE.2017.081516

International Journal of Industrial and Systems Engineering, 2017 Vol.25 No.2, pp.160 - 181

Available online: 06 Dec 2016

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