The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Are CRM systems ready for AI integration?: A conceptual framework of organizational readiness for effective AI-CRM integration
Open accessAbstract
Purpose: The purpose of this paper is to develop a conceptual framework to check if an organization is ready to adopt an AI-integrated CRM system. The study also analyzes different situations which can provide a comprehensive check list in the form of indicators that could provide a signal indicating whether the organization is ready to adopt an AI-integrated CRM system by capturing actionable and appropriate data. Design/methodology/approach: The paper is a general review, and appropriate literature has been used to support the conceptual framework. Findings: The key findings of this study are the different indicators that make up the conceptual framework. This framework can help organizations to check at a glance whether they are ready to adopt AI-integrated CRM system in their organizations. Specifically, it has been identified that different approaches are needed to tackle various types of customer data so that those may be made fit and actionable for appropriate utilization of AI algorithms to facilitate business success of an organization. Practical implications: The paper has elaborately discussed the different approaches to be undertaken to calibrate and reorient the various kinds of actionable data and the contemplated challenges one would face in doing so. This would help the practitioners that how the data so captured can be made fit for action and utilization toward application of AI technologies integrated with existing CRM system in an organization. Originality/value: This study is claimed to be a unique study to provide a conceptual framework which could help arranging and rearranging of captured data by an organization for making the data fit and ready for use with the help of AI technologies. This successful integration of AI with CRM system can help organizations toward taking quick and automated decision-making without much intervention of human beings.
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Cites
Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers?
de Kerviler, G., Demoulin, N. T. M., & Zidda, P. (2016) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.04.011 · Cited by 374
Alshare, K. A., & Lane, P. L. (2011) · Communications of the Association for Information Systems · doi:10.17705/1cais.02834 · Cited by 102
E-business value creation in Small and Medium Enterprises: a US study using the TOE framework
Wen, K. W., & Chen, Y. (2010) · International Journal of Electronic Business · doi:10.1504/ijeb.2010.030717 · Cited by 88
Analysis of the determinants of consumers’m-commerce usage activities
Chan, F. T. S., & Yee‐Loong Chong, A. (2013) · Online Information Review · doi:10.1108/oir-01-2012-0012 · Cited by 77
Cited by
AI-powered marketing: What, where, and how?
Kumar, V., Ashraf, A. R., & Nadeem, W. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102783 · Cited by 509
Does data-driven culture impact innovation and performance of a firm? An empirical examination
Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2024) · Annals of Operations Research · doi:10.1007/s10479-020-03887-z · Cited by 274
Self-citationLedro, C., Nosella, A., & Vinelli, A. (2022) · Journal of Business & Industrial Marketing · doi:10.1108/jbim-07-2021-0332 · Cited by 216
Integration of AI in CRM: Challenges and Guidelines
Ledro, C., Nosella, A., & Dalla Pozza, I. (2023) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.1016/j.joitmc.2023.100151 · Cited by 108
Chatterjee, S., Chaudhuri, R., Thrassou, A., & Sakka, G. (2022) · Journal of Intellectual Capital · doi:10.1108/jic-12-2020-0378 · Cited by 67
Self-citationLedro, C., Nosella, A., Vinelli, A., Dalla Pozza, I., & Souverain, T. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2025.115531 · Cited by 33
Nilashi, M., Abumalloh, R. A., Ahmadi, H., Samad, S., Alrizq, M., Abosaq, H., & Alghamdi, A. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e21828 · Cited by 30
Metadata
- Authors
- Chatterjee, S., Ghosh, S. K., Chaudhuri, R., & Nguyen, B.
- Venue
- The Bottom Line
- Publisher
- Emerald
- Published
- 2019-05-30
- Volume
- 32
- Issue
- 2
- Pages
- 144-157
- ISSN
- 0888-045X (ISSN-L)
- OpenAlex
- W2956609189
- Cited by
- 159
- References
- 4
- FWCI
- 8.94
- Type
- journal article
- Language
- en
- Open access
- green
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