A fuzzy-based decision aid method for product deletion of fast moving consumer goods. (1st April 2019)

• Record Type: Journal Article
• Authors: Pourhejazy, Pourya; Sarkis, Joseph; Zhu, Qinghua
• Is Part Of: Expert systems with applications. Volume 119(2019)
• Page Start: 272
• Page End: 288
• Publication Date: 2019-04-01
• Subjects: Product deletion -- Supply chain -- Fast-moving consumer goods -- Multi-criteria decision-making -- Fuzzy inference system; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2018.11.001
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Supply chain and competitive factors are developed for product deletion. Models of the Nested-Fuzzy Inference System with Interactions is introduced. A practical case is used to verify the model for decision on product deletion. Considering supply chain factors shows a difference in product deletion decision. Abstract: Technological and market cycles pressure organizations to introduce new products. To make room for the new products, product deletion (PD) decisions are inevitable. PD implementation, however, is beyond the reactive elimination of mature or low-profit products. As a competitive and proactive managerial tool, PD requires incorporation of supply chain financial and non-financial attributes to not only benefit organizations, but also maintain important partnerships. To successfully apply strategic PD, consideration of a broader set of decision factors is necessary. To update the traditional view, this paper introduces supply chain and competitive factors to product deletion decision-making (PDDM). Given the complex multi-criteria problem, including both qualitative and quantitative factors and the relative uncertainties and interaction between the factors, a Nested-Fuzzy Inference System with Interactions (NFISI) model as part of a multi-stage, multi-method expert system is introduced to aid the decision-making process. The model is verified using a practical case in a major fast-moving consumer goods (FMCG) company. The priority of alternative products for deletion is obtained through the application of the developed model considering the newly introduced factors. The results provide initial, albeit idiosyncratic, insights with a discussion of practical implications. It is demonstrated that considering supply chain factors makes a difference in PDDM outcomes. A brief overview of research opportunities is finally presented to guide researchers in contributing to this under-studied subject.