DIGITAL TRANSFORMATION AND QUALITY GOVERNANCE IN AUTOMOTIVE SUPPLY CHAINS: A FUZZY AHP-BASED PRIORITIZATION OF TQM CAPABILITIES

Abstract

Intense competition in the Automotive Supply Chain Ecosystem and the necessity to produce high-quality products have driven companies toward implementing Total Quality Governance (TQM) systems. However, the diversity and complexity of TQM Capabilities, coupled with resource constraints, have made the identification and prioritization of critical success factors essential. This study aims to prioritize the critical TQM Capabilities supporting quality governance in the Automotive Supply Chain Ecosystem using the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method.. The research adopts a descriptive-applied approach, where key TQM Capabilities were first identified through a literature review and then evaluated by 27 automotive industry experts. Data were collected using a fuzzy pairwise comparison questionnaire, and the analysis was conducted using Fuzzy AHP method. The findings indicate that among the four main TQM Capabilities-leadership and management, processes and operations, strategic planning, and human resources-leadership and management, with a weight of 0.362, was identified as the highest priority, while top management commitment, with a weight of 0.109, was recognized as the most critical sub-component. Quality vision and strategy (0.098) and process management (0.080) ranked next in importance. The results of this study provide a practical framework for Automotive Supply Chain Ecosystem managers to focus on critical factors and adopt more effective TQM implementation strategies. The study provides a capability-based prioritization framework that can support decision-making in digitally transforming automotive ecosystems.