Assessing Organizational Users’ Intentions and Behavior to AI Integrated CRM Systems: a Meta-UTAUT Approach

Sheshadri Chatterjee (), Nripendra P. Rana (), Sangeeta Khorana, Patrick Mikalef () and Anuj Sharma ()
Additional contact information
Sheshadri Chatterjee: Indian Institute of Technology Kharagpur
Nripendra P. Rana: Qatar University
Patrick Mikalef: Norwegian University of Science and Technology
Anuj Sharma: Chandragupt Institute of Management Patna Mithapur Institutional Area

Information Systems Frontiers, 2023, vol. 25, issue 4, No 2, 1299-1313

Abstract: Abstract This paper tests the meta-analysis based unified theory of acceptance and use of technology (meta-UTAUT) model to predict the behavioral intentions of organizational users and their use behavior to artificial intelligence (AI) integrated customer relationship management (CRM) systems. Data was collected from 315 organizational users in India. The hypotheses draw on the theoretical underpinnings which have been statistically validated. Results show that CRM quality and satisfaction significantly influences an organization’s employees attitudes and intentions to use AI integrated CRM systems. The compatibility of CRM systems has, however, a limited impact on employees attitudes. The findings, which are aligned with the extended UTAUT model, provide useful insights into organizations and decision-makers for designing AI integrated CRM systems.

Keywords: AI-CRM; CRM Quality; CRM satisfaction; User behavior; Meta-UTAUT (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10796-021-10181-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:25:y:2023:i:4:d:10.1007_s10796-021-10181-1

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-021-10181-1

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().