Effective use of artificial intelligence in healthcare supply chain resilience using fuzzy decision-making model

Abstract

AI technologies are absolutely changing the rules of the game all around the world. However, the diffusion rate of AI is widely ranging across countries. This study aims to fulfill a research gap regarding multidimensional comprehensive studies which could provide academic information to the policy makers, technology producers, adopters of technology and the workforce. Friction against the use of new technologies has been existing since the beginning of industrial revolution. This study examines the possible factors behind the friction in AI adoption process. The subject of the course in this study is the supply chain resilience which is a keystone in healthcare sector especially after the recent pandemics. Studies promise the efficiency improvements and cost reductions in healthcare when AI technologies are implemented in supply chain management of the industry. This paper proposes a fuzzy Aczel–Alsina-based decision-making model to analyze the factors that enhance the diffusion of AI technologies in healthcare supply chain management. The model is tested for the case of Turkish healthcare industry. Fuzzy decision-making model is used to solve the complexities in unveiling success factors in the implementation and diffusion phases. Results show that among many other factors tested, technology intensity, trialability and government support and policies are the most important AI success factors. The results are discussed to reveal potential policy recommendations.