Factors Influencing Customer Purchase Decisions in AI-Driven Online Shopping: Systematic Review
DOI:
https://doi.org/10.54259/satesi.v6i1.7476Keywords:
Artificial Intelligence in E-commerce, Purchase Intention, Technology Acceptance Model, Stimulus-Organism-Response, Consumer BehaviorAbstract
This paper offers a PRISMA-guided systematic literature review to examine how Artificial Intelligence (AI) is applied in e-commerce. The focus is on identifying key factors that influence customer purchasing decisions in AI-driven online transactions. It examines Information Systems (IS) theories relevant to the integration of AI and e-commerce, offering insights into frameworks used to analyze the relationship between AI and consumer behavior. Additionally, the paper identifies gaps in current research and provides recommendations for future studies, particularly in areas requiring further exploration to understand the evolving impact of AI on e-commerce. Through a review of existing literature, the study identifies critical factors such as perceived enjoyment, perceived usefulness, perceived ease of use, interactivity, consumer engagement, AI technology, and information quality, which significantly affect consumer purchase intentions. This review finds that Stimulus-Organism-Response (SOR) and Technology Acceptance Model (TAM) are the most commonly adopted theories, while Media Richness Theory is used less frequently. The findings provide a robust foundation for future research, enabling the formulation of empirically testable hypotheses. Furthermore, this study offers a more integrated perspective by organizing identified constructs into a multi-dimensional framework and suggests directions for future empirical research, such as developing research models and validating them through survey-based approaches and Structural Equation Modeling (SEM-PLS), as well as qualitative methods. The study aims to offer insights to AI developers and e-commerce practitioners, helping them enhance AI-powered systems to better meet consumer needs and expectations, ultimately improving customer satisfaction and increasing purchase rates.
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Y. J. Lim, A. Osman, S. N. Salahuddin, A. R. Romle, and S. Abdullah, “Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention,” Procedia Economics and Finance, vol. 35, no. October 2015, pp. 401–410, 2016, doi: 10.1016/s2212-5671(16)00050-2.
C. V. Misischia, F. Poecze, and C. Strauss, “Chatbots in customer service: Their relevance and impact on service quality,” Procedia Comput. Sci., vol. 201, no. C, pp. 421–428, 2022, doi: 10.1016/j.procs.2022.03.055.
R. Fedorko, Š. Kráľ, and R. Bačík, “Artificial Intelligence in E-commerce: A Literature Review,” Lecture Notes on Data Engineering and Communications Technologies, vol. 111, no. July, pp. 677–689, 2022, doi: 10.1007/978-981-16-9113-3_50.
R. E. Bawack, S. F. Wamba, K. D. A. Carillo, and S. Akter, Artificial intelligence in E-Commerce: a bibliometric study and literature review, vol. 32, no. 1. Springer Berlin Heidelberg, 2022. doi: 10.1007/s12525-022-00537-z.
J. Y. S. Chang, J. H. Cheah, X. J. Lim, and A. M. Morrison, “One pie, many recipes: The role of artificial intelligence chatbots in influencing Malaysian solo traveler purchase intentions,” Tour. Manag. Perspect., vol. 49, no. October, p. 101191, 2023, doi: 10.1016/j.tmp.2023.101191.
S. Nazir, S. Khadim, M. Ali Asadullah, and N. Syed, “Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach,” Technol. Soc., vol. 72, no. December, 2023, doi: 10.1016/j.techsoc.2022.102190.
A. Casheekar, A. Lahiri, K. Rath, K. S. Prabhakar, and K. Srinivasan, “A contemporary review on chatbots, AI-powered virtual conversational agents, ChatGPT: Applications, open challenges and future research directions,” Comput. Sci. Rev., vol. 52, no. July 2023, p. 100632, 2024, doi: 10.1016/j.cosrev.2024.100632.
S. U. Singh and A. S. Namin, “A survey on chatbots and large language models: Testing and evaluation techniques,” Natural Language Processing Journal, vol. 10, no. January, p. 100128, 2025, doi: 10.1016/j.nlp.2025.100128.
D. Gao et al., “LLMs-based machine translation for E-commerce,” Expert Syst. Appl., vol. 258, no. June, p. 125087, 2024, doi: 10.1016/j.eswa.2024.125087.
A. Valencia-Arias, H. Uribe-Bedoya, J. D. González-Ruiz, G. S. Santos, E. C. Ramírez, and E. M. Rojas, “Artificial intelligence and recommender systems in e-commerce. Trends and research agenda,” Intelligent Systems with Applications, vol. 24, no. September, 2024, doi: 10.1016/j.iswa.2024.200435.
C. Dorogan, “Why 68% of AI Ecommerce Projects Fail — And How to Fix It.” Accessed: Apr. 23, 2026. [Online]. Available: https://bintime.com/artificial-intelligence/why-ai-ecommerce-projects-fail/
D. Moher, A. Liberati, J. Tetzlaff, and D. G. Altman, “Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement,” International Journal of Surgery, vol. 8, no. 5, pp. 336–341, 2010, doi: 10.1016/j.ijsu.2010.02.007.
M. C. Han, “The Impact of Anthropomorphism on Consumers’ Purchase Decision in Chatbot Commerce,” Journal of Internet Commerce, vol. 20, no. 1, pp. 46–65, 2021, doi: 10.1080/15332861.2020.1863022.
N. Fang, “Exploring the Influence of AI on Purchase Intention of Electric Vehicle among Consumers in China,” vol. 23, pp. 263–270, 2023.
Y. Zhu, R. (Renata) Zhang, Y. Zou, and D. Jin, “Investigating customers’ responses to artificial intelligence chatbots in online travel agencies: the moderating role of product familiarity,” Journal of Hospitality and Tourism Technology, vol. 14, no. 2, pp. 208–224, 2023, doi: 10.1108/JHTT-02-2022-0041.
M. G. Elmashhara, R. De Cicco, S. C. Silva, M. Hammerschmidt, and M. L. Silva, “How gamifying AI shapes customer motivation, engagement, and purchase behavior,” Psychol. Mark., vol. 41, no. 1, pp. 134–150, 2024, doi: 10.1002/mar.21912.
X. C. Le, “Inducing AI-powered chatbot use for customer purchase: the role of information value and innovative technology,” Journal of Systems and Information Technology, vol. 25, no. 2, pp. 219–241, 2023, doi: 10.1108/JSIT-09-2021-0206.
Y. Zhu, H. Shi, H. Bin Azam Hashmi, and Q. Wu, “Bridging artificial intelligence-based services and online impulse buying in E-retailing context,” Electron. Commer. Res. Appl., vol. 62, no. October, p. 101333, 2023, doi: 10.1016/j.elerap.2023.101333.
S. Chen, X. Li, K. Liu, and X. Wang, “Chatbot or human? The impact of online customer service on consumers’ purchase intentions,” Psychol. Mark., vol. 40, no. 11, pp. 2186–2200, 2023, doi: 10.1002/mar.21862.
M. Qin, W. Zhu, S. Zhao, and Y. Zhao, “Is Artificial Intelligence Better than Manpower? The Effects of Different Types of Online Customer Services on Customer Purchase Intentions,” Sustainability (Switzerland), vol. 14, no. 7, 2022, doi: 10.3390/su14073974.
Y. Liang, S. H. Lee, and J. E. Workman, “Implementation of Artificial Intelligence in Fashion: Are Consumers Ready?,” Clothing and Textiles Research Journal, vol. 38, no. 1, pp. 3–18, 2020, doi: 10.1177/0887302X19873437.
H. A. D. M. Arachchi and G. D. Samarasinghe, “Impact of embedded AI mobile smart speech recognition on consumer attitudes towards AI and purchase intention across Generations X and Y,” European Journal of Management Studies, pp. 2635–2648, 2023, doi: 10.1108/ejms-03-2023-0019.
S. Bag, G. Srivastava, M. M. Al Bashir, S. Kumari, M. Giannakis, and A. H. Chowdhury, “Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion,” Benchmarking, vol. 29, no. 7, pp. 2074–2098, 2022, doi: 10.1108/BIJ-07-2021-0415.
S. F. Yeo, C. L. Tan, A. Kumar, K. H. Tan, and J. K. Wong, “Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry,” Technol. Forecast. Soc. Change, vol. 177, 2022, doi: 10.1016/j.techfore.2022.121551.
M. Bilal, Y. Zhang, S. Cai, U. Akram, and A. Halibas, “Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment,” Journal of Retailing and Consumer Services, vol. 77, no. December 2023, p. 103674, 2024, doi: 10.1016/j.jretconser.2023.103674.
R. Pillai, B. Sivathanu, and Y. K. Dwivedi, “Shopping intention at AI-powered automated retail stores (AIPARS),” Journal of Retailing and Consumer Services, vol. 57, no. June, p. 102207, 2020, doi: 10.1016/j.jretconser.2020.102207.
H. A. D. M. Arachchi and G. D. Samarasinghe, “Impulse Purchase Intention in an AI-mediated Retail Environment: Extending the TAM with Attitudes Towards Technology and Innovativeness,” Global Business Review, no. December, 2023, doi: 10.1177/09721509231197721.
R. Bhagat, V. Chauhan, and P. Bhagat, “Investigating the impact of arti fi cial intelligence on consumer ’ s purchase intention in e-retailing,” vol. 25, no. 2, pp. 249–263, 2023, doi: 10.1108/FS-10-2021-0218.
S. Jain and A. V. Gandhi, “Impact of artificial intelligence on impulse buying behaviour of Indian shoppers in fashion retail outlets,” International Journal of Innovation Science, vol. 13, no. 2, pp. 193–204, 2021, doi: 10.1108/IJIS-10-2020-0181.
G. Malhotra, “Perceived anthropomorphism and purchase intention using artificial intelligence technology : examining the moderated effect of trust,” 2023, doi: 10.1108/JEIM-09-2022-0316.
C. Yen and M. C. Chiang, “Trust me, if you can: a study on the factors that influence consumers’ purchase intention triggered by chatbots based on brain image evidence and self-reported assessments,” Behaviour and Information Technology, vol. 40, no. 11, pp. 1177–1194, 2021, doi: 10.1080/0144929X.2020.1743362.
H. Beyari and H. Garamoun, “The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework,” Sustainability (Switzerland), vol. 14, no. 15, 2022, doi: 10.3390/su14159637.
J. Jan, K. A. Alshare, and P. L. Lane, “Hofstede’s cultural dimensions in technology acceptance models: a meta-analysis,” Univers. Access Inf. Soc., vol. 23, no. 2, pp. 717–741, 2024, doi: 10.1007/s10209-022-00930-7.
M. Żemojtel-Piotrowska and J. Piotrowski, “Hofstede’s Cultural Dimensions Theory,” in Encyclopedia of Sexual Psychology and Behavior, Springer International Publishing, 2023, pp. 1–4. doi: 10.1007/978-3-031-08956-5_1124-1.
N. Peña-García, I. Gil-Saura, A. Rodríguez-Orejuela, and J. R. Siqueira-Junior, “Purchase intention and purchase behavior online: A cross-cultural approach,” Heliyon, vol. 6, no. 6, 2020, doi: 10.1016/j.heliyon.2020.e04284.
F. Pratesi, L. Hu, R. Rialti, L. Zollo, and M. Faraoni, “Cultural dimensions in online purchase behavior: Evidence from a cross-cultural study,” Italian Journal of Marketing, vol. 2021, no. 3, pp. 227–247, 2021, doi: 10.1007/s43039-021-00022-z.
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Copyright (c) 2026 Arnold Aribowo, Hery Hery, Andree Emmanuel Widjaja, Calandra Alencia Haryani
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