DECODING CUSTOMER INTENTION TO USE CHATBOT SERVICES: A SYSTEMATIC REVIEW AND RESEARCH AGENDA
Keywords:
Bibliometric, ChatBot Services, Customer Intention, Literature Review, TCCM
Abstract
In consumer psychology and information and communication technology research, studies regarding the utilization of innovation in technology-based interventions, and in particular, the effect of Chabot services on customer usage intention are growing while remaining dispersed and multi-faceted. Consistent with this, our study epistemologically reviews the extant literature on chatbot services for customer intention by utilizing a systematic literature review approach. This study further offers a future research agenda by analyzing the theoretical contribution, methodological evolution, and inter-relationships and interactions among the distinct constructs within different contexts concerning the prior research on chatbot services with respect to customer intention. In particular, we systematically recognized and evaluated the publication trends, the article distribution, methodological classification, analysis of constructs, and contexts utilized in existing research. Overall, our synthesis based on systematic literature review offers practical benefits for scholars, management thinkers, and practitioners of consumers’ psychology and marketing decision making research.
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References
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34.Liu, I., Norman, W. C., & Pennington-Gray, L. (2013). A flash of culinary tourism: Understanding the influences of online food photography on people's travel planning process on flickr. Tourism Culture & Communication, 13(1), 5-18.
35.Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2023). Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. ACM Computing Surveys, 55(9), 1-35.
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38.Luo, B., Lau, R. Y., & Li, C. (2023). Emotion-regulatory chatbots for enhancing consumer servicing: An interpersonal emotion management approach. Information & Management, 60(5), 103794.
39.Malik, R., Shrama, A., Trivedi, S., & Mishra, R. (2021). Adoption of chatbots for learning among university students: Role of perceived convenience and enhanced performance. International Journal of Emerging Technologies in Learning (iJET), 16(18), 200-212.
40.Mäntymäki, M., & Islam, A. N. (2016). The Janus face of Facebook: Positive and negative sides of social networking site use. Computers in Human Behavior, 61, 14-26.
41.Mäntymäki, M., & Riemer, K. (2014). Digital natives in social virtual worlds: A multi-method study of gratifications and social influences in Habbo Hotel. International journal of information management, 34(2), 210-220.
42.Mazzei, A., Anselma, L., Sanguinetti, M., Rapp, A., Mana, D., Hossain, M. M., ... & Longo, L. (2022). Anticipating user intentions in customer care dialogue systems. IEEE Transactions on Human-Machine Systems, 52(5), 973-983.
43.Moon, Y. (2000). Intimate exchanges: Using computers to elicit self-disclosure from consumers. Journal of Consumer Research, 26, 323–339.
44.Morsi, S. (2023). Artificial intelligence in electronic commerce: investigating the customers’ acceptance of using chatbots. Journal of System and Management Sciences, 13(3), 156-176.
45.Murtarelli, G., Collina, C., & Romenti, S. (2023). “Hi! How can I help you today?”: investigating the quality of chatbots–millennials relationship within the fashion industry. The TQM Journal, 35(3), 719-733.
46.Naqvi, M. H. A., Hongyu, Z., Naqvi, M. H., & Kun, L. (2023). Impact of service agents on customer satisfaction and loyalty: mediating role of Chatbots. Journal of Modelling in Management, 19(2), 470-491.
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48.Nguyen, T., & Nguyen, D. M. (2024). What will make Generation Y and Generation Z to continue to use online food delivery services: a uses and gratifications theory perspective. Journal of Hospitality Marketing & Management, 33(4), 415-442.
49.Paul, J., & Rosado-Serrano, A. (2019). Gradual internationalization vs born-global/international new venture models: A review and research agenda. International Marketing Review, 36(6), 830-858.
50.Paul, J., Khatri, P., & Kaur Duggal, H. (2023). Frameworks for developing impactful systematic literature reviews and theory building: What, Why and How?. Journal of Decision Systems, 1-14.
51.Pavone, G., Meyer-Waarden, L., & Munzel, A. (2023). Rage against the machine: experimental insights into customers’ negative emotional responses, attributions of responsibility, and coping strategies in artificial intelligence–based service failures. Journal of Interactive Marketing, 58(1), 52-71.
52.Pawlik, Ł., Płaza, M., Deniziak, S., & Boksa, E. (2022). A method for improving bot effectiveness by recognising implicit customer intent in contact centre conversations. Speech Communication, 143, 33-45.
53.Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226.
54.Pizzi, G., Vannucci, V., Mazzoli, V., & Donvito, R. (2023). I, chatbot! the impact of anthropomorphism and gaze direction on willingness to disclose personal information and behavioral intentions. Psychology & Marketing, 40(7), 1372-1387.
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Published
2026-06-30
How to Cite
Rakesh Sharma, Dr Nikhil Dogra, & Dr. Mohit Jamwal. (2026). DECODING CUSTOMER INTENTION TO USE CHATBOT SERVICES: A SYSTEMATIC REVIEW AND RESEARCH AGENDA. IJRDO - Journal of Business Management, 12(1), 63-77. https://doi.org/10.69980/bm.v12i1.6733
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Articles
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