A novel framework for investigating organizational adoption of AI-integrated CRM systems in the healthcare sector; using a hybrid fuzzy decision-making approach

Abstract

CRMS (Customer Relationship Management system) is a brand-new technology that assists hospitals in managing their relationship with patients. Organizations’ analysis methods of huge customer-related data have been subjected to a massive change because of the Artificial Intelligence (AI) integrated CRMS. This integration enables healthcare institutes to quickly and precisely analyze the tremendous volume of patient-related data in order to make accurate, and automated decisions. On the contrary to prior surveys in the healthcare domain, which mainly focused on the individual acceptance of innovation, this study tries to consider both organizational and human-related factors to provide a better understanding of the CRMS adoption in hospitals. This paper will be the first of its kind to analyze and categorize parameters contributing to CRMS adoption in healthcare by introducing an integrated framework, including Human, Technology, Organization, Environment, and Cost (HTOEC) dimensions. The fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is applied to find the interdependence among adoption dimensions and variables. The Maximum Mean de-Entropy (MMDE) algorithm is exploited to choose the optimum threshold value in the DEMATEL method. The fuzzy Analytic Network Process (ANP) is deployed to prioritize adoption parameters. Based on the results, Environment and Human dimensions are the most crucial determinants of CRMS adoption in Iranian hospitals.