Title: Modelling supply chain coordination in fuzzy environment

Authors: Rajendra Kumar Shukla; Dixit Garg; Ashish Agarwal

Addresses: Department of Mechanical and Automation Engineering, Amity University, Noida, U.P., India ' Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Haryana, India ' Mechanical Engineering Department, Indira Gandhi National Open University, New Delhi, India

Abstract: For allocating the components or services to trading partner, it would be significant to analyse level of coordination in their supply chain. For improving overall supply chain performance, an integrated approach of analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment are used. This paper presents how fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution can be integrated for a more consistent evaluation and prioritisation of trading partner based on identified coordination criteria. Questionnaire survey is used to collect data from auto industries on factors reported in literature review. Based on factor analysis of survey data and further experts opinion four coordination criteria namely joint decision-making, information sharing, use of information technology tools and resource sharing determined are used to develop model. A case study of an Indian manufacturing company is described to illustrate the application of the proposed method. Fuzzy AHP is used to calculate relative weights of each coordination criterion and then partners are ranked based on closeness coefficient, calculated for each partner by using fuzzy TOPSIS.

Keywords: supply chain coordination; partner prioritisation; modelling; fuzzy AHP; FAHP; analytical hierarchy process; fuzzy TOPSIS; supply chain management; SCM; joint decision making; information sharing; information technology; resource sharing; case study; India; manufacturing industry.

DOI: 10.1504/IJBPSCM.2016.077166

International Journal of Business Performance and Supply Chain Modelling, 2016 Vol.8 No.2, pp.130 - 156

Accepted: 27 Feb 2015
Published online: 22 Jun 2016 *

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