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Artificial Intelligence (AI)-Enabled CRM Capability in Healthcare: The Impact on Service Innovation

Author

Listed:
  • P. Kumar

    (L2C - Laboratoire Charles Coulomb - CNRS - Centre National de la Recherche Scientifique - UM - Université de Montpellier)

  • S.K. Sharma

    (HIGP - Hawaii Institute of Geophysics and Planetology - UHM - University of Hawai‘i [Mānoa])

  • Vincent Dutot

    (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie)

Abstract

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

Suggested Citation

  • P. Kumar & S.K. Sharma & Vincent Dutot, 2023. "Artificial Intelligence (AI)-Enabled CRM Capability in Healthcare: The Impact on Service Innovation," Post-Print hal-04292614, HAL.
    • Handle: RePEc:hal:journl:hal-04292614
    DOI: 10.1016/j.ijinfomgt.2022.102598
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    Cited by:

    1. Zhou, Shuai & Yi, Ni & Rasiah, Rajah & Zhao, Haipeng & Mo, Zile, 2024. "An empirical study on the dark side of service employees’ AI awareness: Behavioral responses, emotional mechanisms, and mitigating factors," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    2. Talaei-Khoei, Amir & Yang, Alan T. & Masialeti, Masialeti, 2024. "How does incorporating ChatGPT within a firm reinforce agility-mediated performance? The moderating role of innovation infusion and firms’ ethical identity," Technovation, Elsevier, vol. 132(C).

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