From chatbots to conversational commerce: The role of AI in shaping consumer purchase decisions

Dadah Muliansyah; Rika Nurhidayah

doi:10.31004/riggs.v3i2.1068

Authors

Dadah Muliansyah Universitas Tangerang Raya
Rika Nurhidayah Universitas Tangerang Raya

DOI:

https://doi.org/10.31004/riggs.v3i2.1068

Keywords:

conversational AI, consumer trust, perceived empathy, chatbot engagement

Abstract

As conversational artificial intelligence (AI) continues to transform digital commerce, understanding how chatbot-mediated interactions shape consumer decision-making is essential. This study investigates the role of AI-based chatbots in influencing consumer purchase behavior through real-time, natural language communication. Focusing on the emerging dimensions of perceived empathy and trust, the research employs a mixed-methods approach combining a quantitative survey (n = 420) and qualitative text mining of chatbot dialogues collected from the used car sales sector in the Tangerang region, Indonesia. Findings reveal four key insights: (1) perceived empathy strongly predicts consumer trust, (2) trust in AI significantly drives behavioral intention to purchase, (3) empathy also directly influences intention, and (4) empathetic language triggers engagement during chatbot interactions. These results demonstrate that affective communication by AI agents is a critical driver of consumer responses in digital transactions. The study extends the Technology Acceptance Model by integrating emotional constructs and contributes to human resource and marketing strategy by showing how emotional intelligence, when encoded into AI systems, affects relational and behavioral outcomes. Despite the geographic and sectoral limitations of the sample, the findings underscore the growing need to humanize AI communication in commerce. Future research should explore cross-cultural validations and assess AI–human interaction in broader organizational contexts.

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References

C. Gu, Y. Zhang, and L. Zeng, “Exploring the mechanism of sustained consumer trust in AI chatbots after service failures: a perspective based on attribution and CASA theories,” Humanit Soc Sci Commun, vol. 11, no. 1, p. 1400, Oct. 2024, doi: 10.1057/s41599-024-03879-5.

J. Sidlauskiene, Y. Joye, and V. Auruskeviciene, “AI-based chatbots in conversational commerce and their effects on product and price perceptions,” Electronic Markets, vol. 33, no. 1, p. 24, Dec. 2023, doi: 10.1007/s12525-023-00633-8.

J. Balakrishnan and Y. K. Dwivedi, “Conversational commerce: entering the next stage of AI-powered digital assistants,” Ann Oper Res, vol. 333, no. 2–3, pp. 653–687, Feb. 2024, doi: 10.1007/s10479-021-04049-5.

A. I. Suroso and D. Krisnatuti, “The Effect of Marketing Mix Toward Used Car Marketplace Purchase Intentions with the Mediating Factors of Brand Awareness and Perceived Quality,” International Journal of Research and Review, vol. 11, no. 3, pp. 94–104, Mar. 2024, doi: 10.52403/ijrr.20240313.

S. Gomes, J. M. Lopes, and E. Nogueira, “Anthropomorphism in artificial intelligence: a game-changer for brand marketing,” Future Business Journal, vol. 11, no. 1, p. 2, Jan. 2025, doi: 10.1186/s43093-025-00423-y.

A. Mari, A. Mandelli, and R. Algesheimer, “Empathic voice assistants: Enhancing consumer responses in voice commerce,” J Bus Res, vol. 175, p. 114566, Mar. 2024, doi: 10.1016/j.jbusres.2024.114566.

A. Juquelier, I. Poncin, and S. Hazée, “Empathic chatbots: A double-edged sword in customer experiences,” J Bus Res, vol. 188, p. 115074, Feb. 2025, doi: 10.1016/j.jbusres.2024.115074.

H. Y. Panjaitan and R. Risqiani, “Antecedents of Customer Satisfaction Towards Chatbot on Used Car Buying and Selling Platforms in Indonesia,” Asia Pacific Management and Business Application, vol. 12, no. 3, pp. 315–334, Apr. 2024, doi: 10.21776/ub.apmba.2024.012.03.6.

F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, vol. 13, no. 3, p. 319, Sep. 1989, doi: 10.2307/249008.

C. Nass and Y. Moon, “Machines and Mindlessness: Social Responses to Computers,” Journal of Social Issues, vol. 56, no. 1, pp. 81–103, Jan. 2000, doi: 10.1111/0022-4537.00153.

J. W. Creswell and V. L. Plano Clark, Designing and conducting mixed methods research , 3rd ed. SAGE, 2018.

V. Venkatesh, S. A. Brown, and H. Bala, “Bridging the Qualitative-Quantitative Divide: Guidelines for Conducting Mixed Methods Research in Information Systems,” MIS Quarterly, vol. 37, no. 1, pp. 21–54, Jan. 2013, doi: 10.25300/MISQ/2013/37.1.02.

J. F. Hair, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A primer on partial least squares structural equation modeling, 3rd ed. SAGE, 2022.

M. Juquelier, I. Poncin, and S. Hazée, “Chatbot empathy and customer trust: A dual-path model in conversational commerce,” Journal of Retailing and Consumer Services, vol. 77, 2025.

J. R. McColl‐Kennedy and T. White, “Service provider training programs at odds with customer requirements in five‐star hotels,” Journal of Services Marketing, vol. 11, no. 4, pp. 249–264, Aug. 1997, doi: 10.1108/08876049710171713.

Pavlou and Fygenson, “Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior,” MIS Quarterly, vol. 30, no. 1, p. 115, 2006, doi: 10.2307/25148720.

Kominfo, Peraturan Menteri Komunikasi dan Informatika Republik Indonesia tentang Perlindungan Data Pribadi dalam Sistem Elektronik. Jakarta: Kementerian Kominfo, 2023.

Gefen, Karahanna, and Straub, “Trust and TAM in Online Shopping: An Integrated Model,” MIS Quarterly, vol. 27, no. 1, p. 51, 2003, doi: 10.2307/30036519.

S. Martínez Puertas, M. D. Illescas Manzano, C. Segovia López, and P. Ribeiro-Cardoso, “Purchase intentions in a chatbot environment: An examination of the effects of customer experience,” Oeconomia Copernicana, vol. 15, no. 1, pp. 145–194, Mar. 2024, doi: 10.24136/oc.2914.

H. Choung, P. David, and A. Ross, “Trust in AI and Its Role in the Acceptance of AI Technologies,” Int J Hum Comput Interact, vol. 39, no. 9, pp. 1727–1739, May 2023, doi: 10.1080/10447318.2022.2050543.

I. Ajzen, “The theory of planned behavior,” Organ Behav Hum Decis Process, vol. 50, no. 2, pp. 179–211, Dec. 1991, doi: 10.1016/0749-5978(91)90020-T.

R. E. Petty and J. T. Cacioppo, Communication and persuasion: Central and peripheral routes to attitude change. Springer, 1986.

R. E. Petty, P. Briñol, and Z. L. Tormala, “Thought confidence as a determinant of persuasion: The self-validation hypothesis.,” J Pers Soc Psychol, vol. 82, no. 5, pp. 722–741, May 2002, doi: 10.1037/0022-3514.82.5.722.

L. Qiu and I. Benbasat, “Evaluating Anthropomorphic Product Recommendation Agents: A Social Relationship Perspective to Designing Information Systems,” Journal of Management Information Systems, vol. 25, no. 4, pp. 145–182, Apr. 2009, doi: 10.2753/MIS0742-1222250405.

Z. Gong and L. Y.-F. Su, “Exploring the Influence of Interactive and Empathetic Chatbots on Health Misinformation Correction and Vaccination Intentions,” Sci Commun, vol. 47, no. 2, pp. 276–308, Apr. 2025, doi: 10.1177/10755470241280986.

J. Short, E. Williams, and B. Christie, The social psychology of telecommunications. John Wiley, 1976.

N. Cai, S. Gao, and J. Yan, “How the communication style of chatbots influences consumers’ satisfaction, trust, and engagement in the context of service failure,” Humanit Soc Sci Commun, vol. 11, no. 1, p. 687, May 2024, doi: 10.1057/s41599-024-03212-0.

J. Yun and J. Park, “The Effects of Chatbot Service Recovery With Emotion Words on Customer Satisfaction, Repurchase Intention, and Positive Word-Of-Mouth,” Front Psychol, vol. 13, May 2022, doi: 10.3389/fpsyg.2022.922503.

N. Saffaryazdi, T. S. Gunasekaran, K. Loveys, E. Broadbent, and M. Billinghurst, “Empathetic Conversational Agents: Utilizing Neural and Physiological Signals for Enhanced Empathetic Interactions,” Preprint arXiv, 2025.