Supplier Scouting and Artificial Intelligence: An information processing theory approach

Purpose: The main objective of this paper is the study of the role of Artificial Intelligence in supporting the supplier scouting process run by a buyer firm, looking at the information and the capabilities required, together with the gains achieved in terms of procurement performance. Design/methodology/approach: Through the case study methodology, 12 IT and information providers involved in the design and development of AI-based scouting solutions have been studied. The unit of analysis is the AI-based scouting solution offered by the IT provider and the relationship that is resulted between the provider delivering the solution and the buyer firm implementing it. The Information Processing Theory is taken as the overarching research lens, addressing the Information Processing Needs and Capabilities underlying the adoption of Artificial Intelligence in supplier scouting. Findings: In the buyer firms, the Information Processing Needs in supplier scouting are high. IT and information provider can solve the requirement of the buyer firms through the proper information Processing Capabilities, enabled by AI-based solutions for supplier scouting. In this way, the Fit between Information Processing Needs and Capabilities is reached. Originality: The novelty of this study lies in the intersection between two research areas (i.e. purchasing and supply management and Artificial Intelligence), rarely investigated in conjunction. The application of Information Processing Theory is also novel in studying the impact of Artificial intelligence in the business process, such as the scouting for new suppliers. In this direction, this paper contributes structuring a phenomenon that is still unexplored by previous contribution and nonconsolidated in the business context.