Exploring the Academic–Industry Collaboration in Knowledge Sharing for Supplier Selection: Digitalizing the OEM

Abstract

Increasing reliance on digital technologies has led to a significant shift in how businesses operate, with many now relying heavily on digital platforms for effective planning, communication, sales, marketing, supply chain, and logistics management. In this context, knowledge sharing platforms enable academic–industry collaboration in which exchange of ideas, opinions, experience, and expertise brings collective intelligence in cooperative learning ecosystem thereby expediting decision making. However, establishing long-term commitment among the partners, allocation of time and resources for sharing tacit knowledge, collaboration among partners with different strategic priorities, and real-time knowledge sharing capabilities are essential for effective and rapid learning in knowledge sharing platforms. The present article will examine these benefits and challenges in knowledge sharing and its impact on supplier selection platforms in Asian automakers. The findings of this article will be helpful for researchers and practitioners intending to explore the role of cooperation in knowledge sharing and digital transformation amid competitive environment prevalent in the automotive industry. The potential supplier database is first examined for qualifying the capability requirements put forth in this article and further prioritized using a multicriteria decision-making technique and analytic hierarchy process. The article results reveal that the manufacturer has highly prioritized firms’ financial transparency for supplier evaluation followed by the suppliers’ cost control, quality control, and manufacturing capabilities. The article has significant theoretical and practical implications for developing robust supplier evaluation criteria for automobile industry and a digital ecosystem for original equipment manufacturers in making supplier related decisions.