A business process decision model for fresh-food supplier evaluation

Abstract

PurposeFrequent food safety incidents caused widespread consumer concerns. Even though food safety is one of the weakest links in the fresh food supply chain and influences consumer food choice in ways different from the quality dimension, this factor is hardly proposed as one of the key traditional supplier selection criteria (e.g. quality, delivery, and price) in the literature. The purpose of this paper is to develop a business process decision model to assess the non-compensating food safety sub-criteria in order to disqualify fresh food suppliers that cannot reach the minimum threshold for low probable food safety failure. The preferred fresh food suppliers can minimize the risk of food safety failure and the associated huge food safety failure costs spanning from private consumer anguish to social distress that cause unbearable costs of sales loss and damage to brand image in business.Design/methodology/approachThis study proposes a novel approach that combines several well-established multi-criteria decision making (MCDM) techniques, including fuzzy AHP (FAHP), TOPSIS, and ELECTRE, and innovatively apply to analyze supplier performance and prioritize potential fresh food suppliers. This hybrid business process model can enforce compliance to all the five non-compensatory sub-criteria of food safety. Since ELECTRE is a non-compensatory MCDM method, it is therefore particularly applicable for disqualifying high risk fresh food suppliers from further full scale supplier performance evaluation by FAHP and TOPSIS. This hybrid business process decision model is able to capitalize on the strengths of these MCDM methods and offset their deficiencies.FindingsThis study uses data of an international supermarket chain to validate feasibility of the proposed model. Results indicate that this model is able to assess the non-compensating food safety sub-criteria via the ELECTRE method in order to disqualify fresh food suppliers that cannot reach the minimum threshold for low probable food safety failure. Only the preferred suppliers with the required food safety capability can proceed to the second stage of the supplier selection process. Assessment via the TOPSIS method reveals the ranking order of those top performing suppliers according to their relative scores along all the supplier selection criteria. The TOPSIS ranking results with the selection of the suppliers C, E, A, and F are robust and consistent across all the different scenarios.Practical implicationsApplication to the fresh food industry is possible with the aid of the MCDM methods. The contribution to the body of knowledge in this teaching and research field demonstrates the importance of first identifying the order qualifier for disqualifying those suppliers that do not satisfy the food safety requirements via the ELECTRE method. The proposed assessment procedure complies with the regulatory policy on food safety, and would influence public policy in applying the best practice of food safety regulation. Without first qualifying the potential suppliers on the basis of food safety, wrong decision can be made to select those high food risk suppliers that have relatively higher overall scores in other supplier selection criteria. Using the assessment results has positive economic and commercial impact on the purchasing managers to formulate appropriate purchasing and supplier development strategy to enhance supplier’s food safety performance, whilst maximizing the overall supplier portfolio performance. The improved supplier’s food safety performance will certainly benefit the society’s quality of life as well.Originality/valueBased on the analytical MCDM methods of FAHP, TOPSIS, and ELECTRE, purchasing managers can operationalize the Hill’s framework of order qualifier and winner that has primarily been used in the literature and manufacturing industry. This study represents the first move to innovatively apply the FAHP, TOPSIS, and ELECTRE methods to operationalize the Hill’s framework of order qualifier and winner that has primarily been used in the literature and manufacturing industry. Application to the fresh food industry to validate the feasibility of the proposed model has been conceived and implemented in this study. Analysis of the data inputs of a supermarket chain via the three MCDM methods generate the results that fulfill the purpose of achieving the research objective of identifying and managing the supplier base that can deliver the best supplier performance, conditional on first passing the fresh food safety test.