The suppliers’ selection process through Extended Fuzzy Cognitive Maps and the Technique for Order of Preference by Similarity to Ideal Solution

Giovanni Mazzuto, Leonardo Postacchini, Filippo Emanuele Ciarapica, Maurizio Bevilacqua


In recent times, supplier selection has become one of the most important and crucial activities for companies. In this study, using the extended fuzzy cognitive maps (E-FCM) and technique for order of preference by similarity to ideal solution (TOPSIS), a decision-making support system is realised to assist managers in this activity. E-FCM expresses a causal relationship among criteria, computing linguistic variables to describe a complex situation. The proposed system allows managers to conduct an a priori evaluation regarding supplier suitability, according to both company and market requirements. A panel of experts was formed, according to their expertise areas, to cover the entire problem domain and model it. The problem was investigated in terms of the factors identified by the experts, such as costs, delivery quality, organisational capability, supplier flexibility, service quality and supplied product quality. These factors were analysed using the TOPSIS approach to rank the suppliers, and the use of TOPSIS allows for discrimination of the E-FCM. This decision-making support system was applied to a real case scenario to test its functionality; in particular, an Italian shoes and accessories company. The TOPSIS ideal solutions were defined from two different points of view: based on the standard TOPSIS procedure and on specifics fixed by the company managers. The two approaches resulted in considerably different outcomes, highlighting the need to consider concepts related to company expectations in the E-FCM.


Decision support systems; Extended fuzzy cognitive map; Supplier selection process; TOPSIS; Scenario analysis


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