Time:10:00 - 11:30 AM,3 June, 2024

Speaker: Qi Yinan, Professor of Supply Chain and Operations Management at the School of International Business, University of International Business and Economics (UIBE), Director of Development Planning Department, and former President of the International Society of Supply Chain and Operations Management. His research areas include supply chain resilience, digital supply chain, supply chain innovation, supply chain collaboration and sustainable supply chain. Professor Qi has presided over and participated in more than 10 projects at national and provincial levels, served as the sub-topic leader of the key projects of the National Natural Science Foundation of China and the major special funds of the National Social Science Foundation, and presided over 4 horizontal projects. He has published more than 30 papers in well-known academic journals at home and abroad, including Journal of Operations Management, Decision Sciences, International Journal of Production Economics, Journal of Supply Chain Management, International Journal of Operations and Production Management, and International Journal of Production Management. Management, International Journal of Operations and Production Management, Technovation and so on. Professor Qi has published two teaching cases which have been included in the casebook of Ivy Business School, and one casebook has been published in collaboration with Ivy Business School.

Abstract:

While extensive literature highlights the benefits of artificial intelligence (AI), recent research suggests its side effects. The overall influence of AI application may vary across empirical contexts and the AI adoption intensity (the extent to which firms use AI in their specific business processes). This paper analyzes the impact of suppliers’ AI adoption in retailers’ procurement processes on product availability. Theoretically, adopting AI in the procurement process generates two conflicting effects on product availability: the efficiency enhancement that increases product availability and the expertise exclusion that decreases product availability. The overall impact of AI adoption depends on the tradeoff between them. Moreover, the tradeoff between these opposing effects may change over the AI adoption intensity, thus potentially leading to a nonlinear impact on product availability. We collected proprietary data from a leading online retailer to investigate how the supplier’s AI adoption intensity affects the retailer’s product availability. The empirical results suggest a significant and positive overall impact of AI adoption intensity. Our nonlinear analyses show that this impact follows an inverted U-shaped pattern when AI adoption intensity increases. This nonlinear impact suggests that more AI adoption does not necessarily result in better product availability. Too much AI adoption in procurement adversely hurts product availability. Furthermore, to disentangle these two conflicting effects, we investigate how product variety moderates the impact of AI adoption intensity since increased product variety is expected to magnify the expertise exclusion effect. Our results imply the importance of tailored AI adoption strategies for suppliers considering their product variety. Specifically, firms should develop their workforce with domain expertise to handle extensive product varieties. Our study thus provides theoretical contributions and practical implications for AI adoption in managerial decision-making tasks.