Extending TAM and UTAUT in the Context of Chatbot Commerce: An Empirical Study of Marketing Efforts and Moderating Role of Accuracy

Aftab Alam; Sultan Ahmad; Javed Naseem; Rafat Fatima; Niraj Kumar

doi:10.2991/978-2-38476-559-1_26

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Extending TAM and UTAUT in the Context of Chatbot Commerce: An Empirical Study of Marketing Efforts and Moderating Role of Accuracy

Authors

Aftab Alam¹^{, *}, Sultan Ahmad², Javed Naseem³, Rafat Fatima⁴, Niraj Kumar⁵^{, 6}

¹Assistance Professor, Department of Commerce, Faculty of Commerce, Integral University, Lucknow, Uttar Pradesh (UP), India, 226022

²Assistant Professor, Department of Commerce, Faculty of Commerce, Integral University, Lucknow, Uttar Pradesh (UP), India, 226022

³Research Scholar, Department of Commerce, Aligarh Muslim University, Aligarh, India, 846004

⁴Assistance Professor, Department of Economics, Faculty of Humanities and Social Sciences, Integral University, Lucknow, Uttar Pradesh (UP), India, 226022

⁵Assistant Professor, Department of Economics, C. M. College, Darbhanga, Bihar, India, 846004

⁶Lalit Narayan Mithila University, Darbhanga, Bihar, India, 846004

^*Corresponding author. Email: aaftab@iul.ac.in

Corresponding Author

Aftab Alam

Available Online 19 April 2026.

DOI: 10.2991/978-2-38476-559-1_26 How to use a DOI?
Keywords: Chatbots; Artificial Intelligence; Consumer Trust; Attitude; Chatbot Marketing Efforts; Mobile Commerce; Accuracy; TAM; UTAUT; Acceptance Intention
Abstract: Purpose: This study investigates how Chatbot Marketing Efforts (CMEs) influence consumer trust, attitudes, and acceptance intentions in mobile commerce environments. Despite the increasing deployment of chatbots in customer engagement, limited empirical research explores how different CME dimensions affect user behavior, particularly under the moderating influence of perceived chatbot accuracy.

Methodology: A conceptual framework grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) was developed. The model includes key constructs such as trust, attitude, acceptance intention, and CMEs (interaction, information, entertainment, accessibility, trendiness, customization, and problem-solving), along with accuracy as a moderator. A structured questionnaire using validated scales was distributed to 700 respondents, with 625 valid responses analyzed using descriptive and inferential statistics.

Results: Findings indicate that CMEs significantly and positively influence both trust and attitudes toward chatbot usage. Furthermore, trust and attitude both have a direct and positive impact on acceptance intention. Importantly, accuracy significantly moderates the relationship between CMEs and trust, as well as CMEs and attitude, amplifying their effect under high perceived accuracy conditions.

Conclusions: This study contributes to the growing literature on AI-driven marketing by providing empirical evidence on the psychological and behavioral mechanisms behind chatbot adoption. It offers practical insights for marketers and developers to enhance chatbot design and communication strategies, emphasizing the importance of personalization, accuracy, and entertainment to improve user engagement and brand trust in mobile commerce.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
Series: Advances in Social Science, Education and Humanities Research
Publication Date: 19 April 2026
ISBN: 978-2-38476-559-1
ISSN: 2352-5398
DOI: 10.2991/978-2-38476-559-1_26 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Aftab Alam
AU  - Sultan Ahmad
AU  - Javed Naseem
AU  - Rafat Fatima
AU  - Niraj Kumar
PY  - 2026
DA  - 2026/04/19
TI  - Extending TAM and UTAUT in the Context of Chatbot Commerce: An Empirical Study of Marketing Efforts and Moderating Role of Accuracy
BT  - Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
PB  - Atlantis Press
SP  - 375
EP  - 411
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-559-1_26
DO  - 10.2991/978-2-38476-559-1_26
ID  - Alam2026
ER  -

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