A fuzzy-based decision aid method for product deletion of fast moving consumer goods

Pourya Pourhejazy, Joseph Sarkis, Qinghua Zhu*

*Motsvarande författare för detta arbete

Forskningsoutput: TidskriftsbidragArtikelVetenskapligPeer review

15 Citeringar (Scopus)

Sammanfattning

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.

OriginalspråkEngelska
Referentgranskad vetenskaplig tidskriftExpert Systems with Applications
Volym119
UtgåvaApril
Sidor (från-till)272-288
Antal sidor17
ISSN0957-4174
DOI
StatusPublicerad - 01.04.2019
MoE-publikationstypA1 Originalartikel i en vetenskaplig tidskrift

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