Abstract
In this study, a hybrid model based on ANFIS (Adaptive Neuro-Fuzzy Inference Systems), a predictive intelligent-based technique, and TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was implemented for sustainable supplier selection. Selection of supplier is a crucial task for companies to achieve the objectives of inbound and outbound supply chain system. This selection process may be complex due to the inclusion of diverse subjective and objective factors. There is, therefore, the need for a reliable methodology to provide higher accuracy in predictions of anticipated supplier performance, and this article makes contributions in that direction. The model was applied in the retail end of a fast-moving consumer goods (FMCG) industry to select the best possible suppliers using the sustainability criteria of the triple-bottom-line. Available data from the FMCG retail sector was fed into the TOPSIS and ANFIS model to rank the suppliers. Results indicated that the most dominant sustainability factors in the Nigerian FMCG retail sector are advanced technology, cost, reliability, on-time delivery, and environmental competencies. The finding should encourage companies in the retail sector to explore sustainability opportunities in order to improve their competitiveness for selection during bidding processes. The novelty of this study is the application of ANFIS to sustainable supplier selection problem in the context of a developing economy like Nigeria. It should also assist managers in the FMCG retail sector to highlight areas of possible sustainability improvements.
Highlights
The retail industry serves as the intersection between production and consumption of goods and is subject to particular attention among academic and stakeholder audiences.[1]
Contrary to Fallapour et al.[28] and Azimifard et al.,[24] our results indicate that the safety and rights of employees do not necessarily exert a huge influence on improving sustainable performance in the fast-moving consumer goods (FMCG) retail sector
We propose a predictive intelligent-based technique, Adaptive neuro-fuzzy inference systems (ANFIS), for sustainable supplier selection in the Nigerian FMCG retail sector
Summary
The retail industry serves as the intersection between production and consumption of goods and is subject to particular attention among academic and stakeholder audiences.[1] To increase competitive advantage, retail firms must endeavor to align their business strategies, activities, and operations along their supply chains. The supply chain has to do with the selection of best possible supplier ensuring an effective network of product interaction. Brun and Castelli[2] proposed a segmentation tree model for supply chain strategy segmentation based on three drivers: brand, product, and retail channel. Managing supply chains emphasizes the importance of buyer–supplier relationships, thereby strategizing the purchasing function which is considered a primary driver of the profitability of the firm, since it represents a 50–60% of a particular firm’s total turnover.[3] Previous studies available in extant literature affirm to supplier selection being an extremely important operation within the purchasing function.[4,5,6,7] There exist
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