AI CHATBOT ATTRIBUTES AND TRUST: DRIVING PURCHASE INTENTION IN MALAYSIAN B2C E-COMMERCE PLATFORMS
DOI:
https://doi.org/10.55197/qjssh.v7si4.1627Keywords:
perceived ease of use, perceived usefulness, social presence, Technology Acceptance ModelAbstract
The integration of artificial intelligence chatbots in business-to-consumer e-commerce platforms has transformed consumer-business interactions. Across Southeast Asia, platforms such as Shopee, Lazada, and TikTok Shop have increasingly adopted artificial intelligence chatbots to strengthen customer engagement. However, relying solely on functional efficiency often leads to consumer "bot frustration". This conceptual paper examines the influence of chatbot attributes and consumer trust on purchase intention within the Malaysian business-to-consumer e-commerce market. Anchored in the Technology Acceptance Model and social presence literature, the study proposes an extended framework illustrating how perceived ease of use, perceived usefulness, and social presence collectively influence purchase intention through the mediating role of trust. To empirically validate this model, a quantitative design utilizing a self-administered questionnaire and Partial Least Squares Structural Equation Modelling is proposed. Theoretically, this paper advances the Technology Acceptance Model by demonstrating that interactive artificial intelligence requires both functional and relational attributes to capture the psychological nuances of digital commerce. Practically, the framework provides actionable insights for managers to combat bot frustration by shifting toward relational bot designs that simulate empathy and warmth. Ultimately, enhancing these specific attributes builds the digital trust necessary to stimulate consumer purchase intentions and foster long-term commercial loyalty.
References
[1] Ashfaq, M., Yun, J., Yu, S., Loureiro, S.M.C. (2020): I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. – Telematics and Informatics 54: 18p.
[2] Aziz, A., Rahman, M.A., Rachman, P., Lestari, W. (2024): The effect of trust and social presence on consumer purchase interest in B2C e-commerce in Indonesia. – Edelweiss Applied Science and Technology 8(6): 1635-1649.
[3] Biswas, J., Mishra, S.N. (2019): Identifying drivers of m-commerce adoption by Indian youth using technology acceptance model. – Journal of Advanced Research in Dynamical and Control Systems 11(9 Special Issue): 423-430.
[4] Bulsara, H.P., Vaghela, P.S. (2023): Trust and online purchase intention: A systematic literature review through meta-analysis. – International Journal of Electronic Business 18(2): 148-164.
[5] Cao, W., Putit, L. (2024): Influence of effort expectancy on consumers’ purchase intention within a B2C imported cross-border e-commerce market: The mediating role of consumer trust. – International Journal of Innovative Research and Scientific Studies 7(3): 1330-1337.
[6] Chelvarayan, A., Jian Wee, B.C., Fern, Y.S. (2022): E-shopping during COVID-19 pandemic: Consumers' perception in Malaysia. – Proceedings of the 2022 International Conference on Digital Transformation and Intelligence (ICDI 2022), IEEE 6p.
[7] Chen, N., Yang, Y. (2023): The role of influencers in live streaming e-commerce: Influencer trust, attachment, and consumer purchase intention. – Journal of Theoretical and Applied Electronic Commerce Research 18(3): 1601-1618.
[8] Cheng, X., Bao, Y., Zarifis, A., Gong, W., Mou, J. (2022): Exploring consumers' response to text-based chatbots in e-commerce: The moderating role of task complexity and chatbot disclosure. – Internet Research 32(2): 496-517.
[9] Christopher, Y., Sundjaja, A.M., Mulvono. (2024): The role of AI chatbots on e-commerce platforms: Understanding its influence on customer trust and dependability. – Proceedings of the 2024 9th International Conference on Information Technology and Digital Applications (ICITDA), IEEE 6p.
[10] Davis, F.D. (1989): Perceived usefulness, perceived ease of use, and user acceptance of information technology. – MIS Quarterly 13(3): 319-340.
[11] Deng, F., Chen, J., Liang, X. (2021): Research on the influencing factors of consumers’ purchase intention in Tmall Global based on TAM model. – Lecture Notes on Data Engineering and Communications Technologies 79: 696-705.
[12] Fei, T.L.K. (2023): The effects of consumers, competitors, and e-commerce intensity on business performance in Malaysia. – Malaysian Journal of Consumer and Family Economics 30: 72-98.
[13] Furner, C.P., Drake, J.R., Zinko, R., Kisling, E. (2022): Online review antecedents of trust, purchase, and recommendation intention: A simulation-based experiment for hotels and AirBnBs. – Journal of Internet Commerce 21(1): 79-103.
[14] Ghosh, M. (2024): Meta-analytic review of online purchase intention: Conceptualising the study variables. – Cogent Business & Management 11(1): 29p.
[15] Giri, A., Chatterjee, S., Biswas, S., Aich, A. (2020): Factors influencing consumer purchase intention of daily groceries through B2C websites in metro-cities of India. – International Journal of Scientific & Technology Research 9(1): 719-722.
[16] Jain, S. (2021): Examining the moderating role of perceived risk and web atmospherics in online luxury purchase intention. – Journal of Fashion Marketing and Management 25(4): 585-605.
[17] Kartawinata, S., Tovin, M., Christopher Lam, V., Limantara, N. (2024): The impact of live streaming on consumer engagement and purchase intentions towards fashion industry on e-commerce. – Proceedings of the 2024 International Conference on Information Management and Technology (ICIMTech 2024), IEEE 6p.
[18] Kurniawan, D., Budiyanto, S.R. (2025): The role of trust in the relationship between past interactions and buying intention in virtual organizations. – International Journal of Industrial Engineering and Production Research 36(1): 135-144.
[19] Lee, H.D., Sy, L.P., Minh, C.P.T. (2024): Impact of customer perception on FMCG products purchase intention through e-commerce platforms: The case in Vietnam. – In: Knowledge Transformation and Innovation in Global Society: Perspective in a Changing Asia, Springer Nature 21p.
[20] Malatji, W.R., van Eck, R., Zuva, T. (2020): Understanding the usage, modifications, limitations and criticisms of technology acceptance model (TAM). – Advances in Science, Technology and Engineering Systems 5(6): 113-117.
[21] Nila Febrianti, N.M., Darma, G.S. (2023): Millennials’ intention to invest through securities crowdfunding platform. – APTISI Transactions on Technopreneurship 5(1): 19-30.
[22] Nuanchaona, S., Siripipatthanakul, S., Nurittamont, W., Phayaphrom, B. (2021): Factors affecting consumers’ purchase intention of chatbot commerce in Thailand. – International Journal of Business, Marketing and Communication 1(3): 1-13.
[23] Pour, M.J., Moeini, H., Nejad, L.H. (2024): Understanding customer purchase intention in social media: An integration of TAM and DeLone and McLean's model. – International Journal of Business Information Systems 45(4): 519-541.
[24] Prihatna, K.A., Sasongko, A.H., Hariyatno, Barlian, E. (2024): Influence of information quality by recommendation system on purchase intention mediated by perceived ease of use and perceived usefulness. – Proceedings of the 2024 6th International Conference on Cybernetics and Intelligent System (ICORIS 2024), IEEE 6p.
[25] Qalati, S.A., Vela, E.G., Li, W., Dakhan, S.A., Truong Thi, H.T., Merani, S.H. (2021): Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping. – Cogent Business & Management 8(1): 20p.
[26] Ren, G., Wang, G., Huang, T. (2025): What influences potential users’ intentions to use hotel robots? – Sustainability 17(12): 24p.
[27] Rubiyanti, N., Abu Sujak, A.F., Madiawati, P.N., Nurutami, F., Bt Raja Razali, R.R., Syahputra. (2023): Perceived usefulness: A bibliometric visualization. – Proceedings of the 2023 International Conference on Digital Business and Technology Management (ICONDBTM 2023), IEEE 6p.
[28] Sawaftah, D. (2020): The effectiveness of electronic integrated marketing communications on customer purchase intention of mobile service providers: The mediating role of customer trust. – Journal of Sustainable Marketing 1(1): 43-56.
[29] Shahzad, M.F., Xu, S., An, X., Javed, I. (2024): Assessing the impact of AI-chatbot service quality on user e-brand loyalty through chatbot user trust, experience and electronic word of mouth. – Journal of Retailing and Consumer Services 79: 13p.
[30] Sharma, B.K., Jain, P., Gautam, O., Mishra, S. (2024): Determinants of trust on social networking sites and its impact on purchase intention through the mediation effect of customer experience. – International Journal of Public Sector Performance Management 13(3): 313-330.
[31] Shih, H.P. (2011): Mr. Risk! Please trust me: Website acceptance of e-vendor websites in Taiwan. – Journal of Internet Banking and Commerce 16(2): 12p.
[32] Short, J., Williams, E., Christie, B. (1976): The Social Psychology of Telecommunications. – John Wiley & Sons, London 195p.
[33] Siagian, H., Tarigan, Z.J.H., Basana, S.R., Basuki, R. (2022): The effect of perceived security, perceived ease of use, and perceived usefulness on consumer behavioral intention through trust in digital payment platform. – International Journal of Data and Network Science 6(3): 861-874.
[34] Siautama, K., Rudy, R., Syahchari, D.H. (2024): A comparison study on logistic services between Indonesia, Malaysia, and Singapore for support e-commerce. – Proceedings of the 2nd International Conference on Cyber Resilience (ICCR 2024), IEEE 5p.
[35] Soares, A.M., Camacho, C., Elmashhara, M.G. (2022): Understanding the impact of chatbots on purchase intention. – In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (Eds.): Proceedings of the 10th World Conference on Information Systems and Technologies, WorldCIST 2022. Lecture Notes in Networks and Systems 470, Springer 11p.
[36] Swilley, E., Goldsmith, R.E. (2007): Assessing the impact of corporate credibility and technology acceptance on online shopping. – International Journal of Electronic Marketing and Retailing 1(3): 199-216.
[37] Teh, Z.H., Lim, C.Y., Chen, S.Y. (2021): An exploratory review of Malaysian e-commerce merchants and their readiness in adopting business analytics models for assessment of business KPIs. – Proceedings of the 6th International Forum on Research and Technology for Society and Industry (RTSI 2021), IEEE 5p.
[38] Tu, N., Cui, Z., Itoh, M. (2024): Distinct technology acceptance models for unfamiliar systems in Japan and the United States during the COVID-19 pandemic. – Proceedings of the 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE 2024), IEEE 2p.
[39] Varma, M., Kumar, V., Sangvikar, B., Pawar, A. (2020): Impact of social media, security risks and reputation of e-retailer on consumer buying intentions through trust in online buying: A structural equation modeling approach. – Journal of Critical Reviews 7(1): 119-127.
[40] Wang, X., Xu, A. (2022): Chinese consumers’ intention to purchase tourism financial products. – Journal of Teaching in Travel & Tourism 22(3): 325-336.
[41] Wut, T.M., Lee, S.W., Xu, J., Kwok, M.L.J. (2025): Do trusting belief and social presence matter? Service satisfaction in using AI chatbots: Necessary condition analysis and importance–performance map analysis. – Informatics 12(3): 20p.
[42] Zhao, Y., Cormican, K., Sampaio, S. (2024): Clicks vs. bricks: Exploring the critical success factors for consumer purchase intention in e-commerce. – Procedia Computer Science 239: 590-597.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 MOHAMAD FARIZ ABDULLAH, LENNORA PUTIT, NORAFIFA MOHD ARIFFIN, PUSPO DEWI DIRGANTARI, YUSUF MURTADLO HIDAYAT
This work is licensed under a Creative Commons Attribution 4.0 International License.
