Analyzing of CPFR success factors using fuzzy cognitive maps in retail industry


EXPERT SYSTEMS WITH APPLICATIONS, vol.39, no.12, pp.10438-10455, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 39 Issue: 12
  • Publication Date: 2012
  • Doi Number: 10.1016/j.eswa.2012.02.014
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.10438-10455
  • Keywords: Collaborative planning forecasting and replenishment (CPFR), Fuzzy cognitive map (FCM), Information sharing, Decision synchronization, Incentive alignment, SUPPLY CHAIN PERFORMANCE, MANAGEMENT, MODEL, INFORMATION, DETERMINANTS, INTEGRATION, BENEFITS, DESIGN, IMPACT, TRUST
  • Galatasaray University Affiliated: Yes


The retail sector environment is characterized by intense pressure of competition, ever-changing portfolio of products, hundreds of different products, ever-changing customer requirements and be able to stand in a mass market. When considering that the giant retailers work together with their suppliers, each independent operation is seen as a comprehensive structure, consisting of thousands of sub-processes. In short, the retail industry dynamism and work in cooperation with the competitiveness of the sector is one of a rare combination. Of course in such a sector businesses of all sizes in many aspects of creating an efficient and low cost structure is in the effort. Collaborative planning, forecasting and replenishment (CPFR) model which is a scheme integrating trading partners' internal and external information systems is proposed to assist establishing a more effective supply chain structure in retail industry. Although CPFR can provide many benefits, there have been many failed implementations. The aim of this study is to determine the factors that will support better implementation of CPFR strategy in retail industry and analyze them using fuzzy cognitive map (FCM) approach. FCMs have proven particularly useful for solving problems in which a number of decision variable and uncontrollable variables are causality interrelated. A CPFR model made up of three sub-systems, namely information sharing, decision synchronization and incentive alignment, is proposed and "what-if" scenarios for proposed model are developed and interpreted. To our knowledge, this is the first study that uses FCMs for CPFR success factors assessment. (C) 2012 Elsevier Ltd. All rights reserved.