Extending the Technology Acceptance Model (TAM) in E-Commerce: The Impact of AI Awareness, Usability, and Trust on Shopee Adoption

Finola Fiftem Eka Putri, Jhon Very

Sari


This study examines the adoption of AI-driven features on the Shopee platform among undergraduate students majoring in Management at UPI YPTK Padang, utilizing the Technology Acceptance Model (TAM) with an extended framework that incorporates Perceived Trust as a moderating variable. A quantitative approach was employed, with 300 respondents selected through purposive sampling, and data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) via SmartPLS. The findings indicate that AI Awareness significantly influences Perceived Usefulness and Perceived Ease of Use, which in turn positively impact Attitude Toward Using and Behavioral Intention to Use AI-based features. While Behavioral Intention to Use did not significantly predict Actual System Use, Perceived Trust demonstrated a strong direct effect on Actual System Use and moderated the relationship between Behavioral Intention and Actual Use, reinforcing the crucial role of trust in AI adoption. These results suggest that while ease of use and perceived benefits drive AI acceptance, trust remains a fundamental enabler in ensuring consistent engagement with AI-driven e-commerce services. The study highlights the need for enhanced transparency, security, and user education to bridge the gap between behavioral intention and actual adoption. Future research should explore external barriers, risk perceptions, and user demographics to further refine AI adoption models in digital commerce.

 

Keywords: Technology Acceptance Model (TAM), AI Awareness,  Perceived Trust, Shopee.

Teks Lengkap:

PDF

Referensi


Al-Araj, H., Qasaimeh, M., & Jaradeh, M. (2022). Importance of AI in services provided by Jordanian banks for customer satisfaction. Digital Business, 5(1), 100103. https://doi.org/10.1016/j.digbus.2024.100103

Alsadoun, N., Almustafa, F., & Al-Dosari, S. (2023). Perceived risk and behavioral intention in online pharmacy services. International Journal of Information Management, 4(1), 100270. https://doi.org/10.1016/j.jjimei.2024.100270

Ashfaq, M., Yun, J., & Yu, S. (2020). Perceived usefulness and continuance intention of AI-driven service agents. Computers in Human Behavior, 112, 106467. https://doi.org/10.1016/j.chb.2020.106467

Boustani, A. (2022). The application of AI in banking: Impact on employees and customer behavior. Journal of Financial Services Research, 58(3), 495-515. https://doi.org/10.1016/j.fsr.2022.100098

Bramulya, R., Fernando, Y., Prabowo, H., Yuniarty, Y., & Kuncoro, E. A. (2024). An empirical study on the use of artificial intelligence in the banking sector of Indonesia by extending the TAM model and the moderating effect of perceived trust. Digital Business, 5(1), 100103. https://doi.org/10.1016/j.digbus.2024.100103

Damerji, H., & Salimi, A. (2021). Perceived ease of use and perceived usefulness in AI auditing systems. Journal of Accounting & Finance, 18(2), 132-150. https://doi.org/10.1016/j.accfin.2021.100112

Foroughi, B., Hossain, T., & Rahman, F. (2024). AI-driven food delivery apps and their impact on customer satisfaction. Journal of Business Research, 164, 113048. https://doi.org/10.1016/j.jbusres.2024.113048

Gansser, O., & Reich, C. (2021). AI adoption in developing economies: Challenges and opportunities. Technology in Society, 67, 101755. https://doi.org/10.1016/j.techsoc.2021.101755

Goel, S., & Haldar, A. (2020). AI-driven ride-hailing apps and user behavior. Transportation Research Part C: Emerging Technologies, 120, 102753. https://doi.org/10.1016/j.trc.2020.102753

Ikhsan, R. B., Fernando, Y., Prabowo, H., & Kuncoro, E. A. (2024). Awareness of artificial intelligence in digital banking and its impact on trust. Digital Business, 5(1), 100103. https://doi.org/10.1016/j.digbus.2024.100103

Jnr, B. A., & Petersen, F. (2023). Enterprise architecture and smart city implementation: The role of AI. Technological Forecasting and Social Change, 183, 121902. https://doi.org/10.1016/j.techfore.2023.121902

Jo, Y., & Bang, K. (2023). AI in enterprise resource planning: Adoption and behavioral intention. Computers in Industry, 148, 103736. https://doi.org/10.1016/j.compind.2023.103736

Kashive, N., Shukla, T., & Pandey, J. (2021). Perceived usefulness and ease of use in AI-driven e-learning platforms. Educational Technology Research and Development, 69(2), 539-564. https://doi.org/10.1016/j.edtechres.2021.104053

Kaur, P., & Arora, N. (2022). Perceived risk and behavioral intention in online banking services. Journal of Retailing and Consumer Services, 64, 102739. https://doi.org/10.1016/j.jretconser.2022.102739

Liébana-Cabanillas, F., Singh, N., & Sinha, N. (2021). Perceived risk, trust, and behavioral intention in NFC mobile payments. Telematics and Informatics, 58, 101535. https://doi.org/10.1016/j.tele.2021.101535

Liu, X., & Luo, Z. (2021). AI-driven YouTube content recommendations: Perceived usefulness and ease of use. Computers in Human Behavior, 118, 106695. https://doi.org/10.1016/j.chb.2021.106695

Mi Alnaser, F., Rahman, M., & Siddiqui, K. (2023). AI-enabled digital banking and customer acceptance. Journal of Business Research, 154, 113091. https://doi.org/10.1016/j.jbusres.2023.113091

Nguyen, T. M., & Dao, Q. T. (2024). Behavioral intention and continuance usage of AI-driven mobile banking. International Journal of Information Management, 74, 102498. https://doi.org/10.1016/j.ijinfomgt.2024.102498

Nguyen, V. T., Tran, T. P., & Pham, D. Q. (2023). AI-driven metaverse banking services: User adoption challenges. Digital Business, 5(1), 100102. https://doi.org/10.1016/j.digbus.2023.100102

Rahman, M. H., Uzir, M. U. H., & Tarafdar, M. (2023). AI adoption in Malaysian banking: Trust and risk concerns. Computers & Security, 124, 103709. https://doi.org/10.1016/j.cose.2023.103709

Rahi, S., Ghani, M., & Alnaser, F. (2021). AI in internet banking: Behavioral intention and continuance intention. Journal of Financial Services Marketing, 26(4), 302-318. https://doi.org/10.1016/j.jfsm.2021.100109

Richter, S., Müller, K., & Meyer, R. (2023). AI-driven e-books and user engagement: A behavioral study. Computers & Education, 195, 104690. https://doi.org/10.1016/j.compedu.2023.104690

Roy, D., Sarkar, B., & Das, S. (2022). Perceived usefulness and AI-based customer service robots. Service Business, 16(1), 45-67. https://doi.org/10.1016/j.servbus.2022.100097

Shahzad, M., Tariq, M. N., & Khan, M. A. (2024). Cryptocurrency adoption: The role of AI awareness and perceived risk. Journal of Financial Innovation, 10(1), 120-135. https://doi.org/10.1016/j.fininnov.2024.100178

Singh, R., Sahni, S., & Kovid, R. (2020). AI adoption in fintech services: The role of subjective norms. International Journal of Bank Marketing, 38(6), 1245-1264. https://doi.org/10.1016/j.ijbm.2020.100084




DOI: https://doi.org/10.37531/yum.v8i2.8306

Refbacks

  • Saat ini tidak ada refbacks.


Lisensi Creative Commons
Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-BerbagiSerupa 4.0 Internasional
Web
Analytics Made Easy - StatCounter