Title
A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation
Document Type
Article
Publication Date
3-17-2016
DOI
https://doi.org/10.1007/s00521-016-2274-z
Abstract
The evaluation of sustainable suppliers is one of the most complex tasks in sustainable supply chain management (SSCM). Classical data envelopment analysis (DEA) and dynamic DEA (DDEA) models are heavily dependent on historical data and do not forecast future efficiencies of decision-making units (DMUs). The primary objective of this paper is to present a new predictive paradigm for ranking sustainable suppliers in SSCM. The proposed model combines goal programming and DDEA in an integrated and seamless paradigm to determine the future efficiencies of DMUs (suppliers). It also shifts the decision maker’s role from monitoring the past to planning the future. A case study is presented to demonstrate the applicability of the proposed model and exhibit the efficacy of the procedures and algorithms.
Language
English
Recommended Citation
Tavana, Madjid; Shabanpour, Hadi; Yousefi, Saeed; and Saen, Reza Farzipoor, "A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation" (2016). Business Systems and Analytics Faculty Work. 127.
https://digitalcommons.lasalle.edu/bsa_faculty/127
Comments
Tavana, M., Shabanpour, H., Yousefi, S. and Farzipoor Saen, R. (2017) ‘A Hybrid Goal Programming and Dynamic Data Envelopment Analysis Framework for Sustainable Supplier Evaluation,’ Neural Computing and Applications, Vol. 28, No. 12, pp. 3683-3696.