Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kumar, Nishant; Garg, Pratibha; Gupta, Neha; Upreti, Kamal Title A name given to the resource Examining humanized bot interaction for the retail revenue growth Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Journal of Revenue and Pricing Management;Volume;25;Issue;1;pp.25-40 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1057/s41272-025-00549-2" target="_blank" rel="noreferrer noopener">https://doi.org/10.1057/s41272-025-00549-2</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105012379316?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105012379316?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kumar N., School of Business and Management, CHRIST University, Bangalore, India; Garg P., Amity School of Business, Amity University, Noida, India; Gupta N., Amity School of Business, Amity University, Noida, India; Upreti K., Department of Computer Science, CHRIST University, Delhi NCR, Ghaziabad, India Description An account of the resource The increasing popularity of conversational artificial intelligence (chatbot) in retail has fuelled consumer purchase decisions. The present study measures humanbot interaction through anthropomorphism, social presence, personalization, media richness, and its role in customer engagement and continuous purchase intention for retail revenue growth. Data were collected from 366 respondents and analyzed using PLS-SEM-ANN integrated approach. To overcome the limitation of establishing only the linear relationship among variables for prediction, the study deploys nonlinear complex artificial neural network (ANN) models to determine the relative importance of the significant predictors identified through structural equation modeling (PLS-SEM). The findings of the study confirm the role of anthropomorphism, personalization, and media richness in customer engagement and customer engagement leading to continuous purchase intention. Furthermore, Chatbots in the electronic commerce space strengthen involvement, but trust and price fairness also play a positive moderating influence in shaping consumer purchase intentions. Study implications highlight the role of anthropomorphic design in the desired social presence for sustained engagement and its contribution to revenue. This study enriches the AI literature and guides organizations leveraging chatbots to create more natural and personalized interactions so retailers can better meet customer needs, foster loyalty, and stay competitive in an increasingly digital marketplace. The Author(s), under exclusive licence to Springer Nature Limited 2025. Subject The topic of the resource Chatbot; Continuous purchase; Price; Revenue; Trust Publisher An entity responsible for making the resource available Palgrave Macmillan Relation A related resource ISSN: 14766930; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online