%0 Journal Article
%T Artificial Intelligence (AI)-Enabled CRM Capability in Healthcare: The Impact on Service Innovation
%+ Laboratoire Charles Coulomb (L2C)
%+ Hawaii Institute of Geophysics and Planetology (HIGP)
%+ Métis Lab EM Normandie
%A Kumar, P.
%A Sharma, S.K.
%A Dutot, Vincent
%< avec comité de lecture
%@ 0268-4012
%J International Journal of Information Management
%I Elsevier
%V 69
%8 2023
%D 2023
%R 10.1016/j.ijinfomgt.2022.102598
%K Artificial intelligence,Artificial intelligence (AI),CRM,Customer relationship management,Customer relationship management systems,Customer service flexibility,Customer-service,Decision making,Health care,Healthcare,Management capabilities,Performance,Public relations,Sales,Service flexibility,Service innovation
%Z Humanities and Social Sciences/Business administrationJournal articles
%X Although AI-enabled customer relationship management (CRM) systems have gained momentum in healthcare to enhance performance, there is a striking dearth of knowledge on how such capabilities are formed and affect service innovation. The study adopted a mixed-method approach to investigate the underlying phenomena. This research infused resource-based theory, dynamic capability theory, and theory of productivity paradox to investigate how healthcare in India acquires AI-enabled CRM capabilities and enhances service innovation. We identified the facets of AI-enabled CRM capabilities using a case study and developed a framework for AI-enabled CRM capability and service innovation. This study noticed that customer service flexibility (CSF) is a missing link in this relationship. The findings of the quantitative study employing PLS-SEM reveal the linear relationships between AI-enabled CRM capability, CSF, and service innovation. This study explains the formation of AI-enabled CRM capabilities to fill the research gap and direct innovative performance in healthcare, which is an immediate need to sustain in a volatile environment. This study provides theoretical implications to enhance the research stream and practical implications for decision-makers. \textcopyright 2022 Elsevier Ltd
%G English
%L hal-04292614
%U https://hal.science/hal-04292614
%~ SHS
%~ EMNORMANDIE
%~ CNRS
%~ L2C
%~ METIS
%~ COMUE-NORMANDIE
%~ UNIV-MONTPELLIER
%~ UM-2015-2021
%~ UM-EPE