Integrating Knowledge Management Into <scp>ERP</scp> Selection: A Fuzzy Multi‐Criteria Decision‐Making Model Based on Gray Theory in the Automotive Industry

ABSTRACT Enterprise Resource Planning (ERP) systems are integrated business management tools used by organizations to manage data and processes across various functions. While financial and technical considerations remain central to ERP selection, sustainable success also depends on the system's ability to support Knowledge Management (KM). This research employs a hybrid approach combining fuzzy decision‐making trial and evaluation laboratory (Fuzzy DEMATEL), fuzzy analytic network process (Fuzzy ANP), and Gray Theory to assess multiple ERP systems, identifying the best option for the automotive industry. The study has three primary objectives: first, to identify 19 key factors influencing ERP system selection; second, to analyze the relationships and interactions among these factors, particularly in terms of their implications for organizational memory, knowledge sharing, and collaborative learning; and third, to determine the relative importance of each factor in guiding ERP system selection within the automotive industry. The results indicate that Management factors are the strongest net causal drivers in the F.DEMATEL analysis, Organizational factors have the highest structural prominence, and Financial factors receive the highest priority weight in the F.ANP analysis. Among the evaluated systems, the “A2” ERP system emerged as the top choice and was selected for implementation at Mammut Industrial Company, the case study subject. Importantly, the finding reveals that ERP selection in this automotive industry extends beyond efficiency and cost, highlighting the strategic value of ERP as a knowledge‐oriented platform that strengthens decision‐making, fosters collaborations, and sustains long‐term competitiveness.