Adoption of AI-Enabled Decision Support Systems for Supply Chain Resilience – An Individual-Level Perspective

Abstract

In the context of supply chain management, Artificial Intelligence (AI) is contributing to increasingly performing Decision Support Systems (DSSs) that can support data-driven decision-making, leading to better supply chain resilience. As this is contingent on decision-makers adopting and using such systems, it remains unclear how various technology and individual-level factors interact to influence the adoption and usage of AI-enabled DSSs in the context of supply chain management. Using a 2 (AI vs. no AI) x 2 (confirmation vs. disconfirmation) scenario-based experiment, the study finds that employees with prior experience using AI exhibit a higher intention to adopt and use an AI-enabled DSS when it generally contradicts their opinion of the best course of action. Less experienced employees tend to prefer a non-AI-enabled DSS. Under the confirmation condition, and possibly fearing overreliance on the DSS, employees with more experience using AI prefer a non-AI-driven DSS.