Research on World Agricultural Economy

The Impact of Artificial Intelligence on Generation Z Customer Experience in Agricultural E-Commerce: A Case Study of Shopee in Vietnam

Hien Thi Thu Hoang

Faculty of Banking, Banking Academy of Vietnam, Hanoi 100000, Vietnam

Ha Thi Thu Do

Faculty of Banking, Banking Academy of Vietnam, Hanoi 100000, Vietnam

Anh Phan

Faculty of Banking, Banking Academy of Vietnam, Hanoi 100000, Vietnam

DOI: https://doi.org/10.36956/rwae.v7i3.2908

Received: 13 November 2025 | Revised: 19 January 2026 | Accepted: 29 January 2026 | Published Online: 18 August 2026

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Abstract

The study aims to explore the impact of artificial intelligence on the online shopping experience of Generation Z consumers, focusing on the agricultural products offered on online shopping platforms such as Shopee in Vietnam. The study assesses the main features of artificial intelligence, including AI-based chatbots, AI-based price generation, AI-based recommendation systems, and AI-based image search, and their contributions to the shopping experience, personalization, and satisfaction, especially for products such as organic fruits, vegetables, and rice, which accounted for 20 percent of the sales of Shopee in Vietnam in 2024. The study is based on a quantitative analysis of behavioral patterns and perceptions and reveals the impact of artificial intelligence on the shopping experience of Generation Z consumers, thereby contributing to the development of the global agricultural economy and food security in developing countries. The study also reveals the impact of artificial intelligence on the shopping behavior and loyalty of young Vietnamese consumers in the digital agricultural economy, which is in line with the recent initiatives of the Food and Agriculture Organization on artificial intelligence-based agrifood systems.

Keywords: Artificial Intelligence; Agricultural E‑Commerce; Customer Experience; Generation Z; Technology Acceptance Model; Shopee; Vietnam Agriculture

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References

[1] Russell, S., Norvig, P., 2020. Artificial Intelligence: A Modern Approach, 4th ed. Pearson: London, UK.

[2] Grewal, D., Hulland, J., Kopalle, P.K., et al., 2020. The future of technology and marketing: a multidisciplinary perspective. Journal of the Academy of Marketing Science. 48(1), 1–8. DOI: https://doi.org/10.1007/s11747-019-00711-4

[3] Huang, M.-H., Rust, R.T., 2021. A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science. 49(1), 30–50. DOI: https://doi.org/10.1007/s11747-020-00749-9

[4] Wavemaker Impact, 2024. Seeding the Future: Transforming Smallholder Farms for a Sustainable Tomorrow. Wavemaker Impact: Singapore. Available from: https://wavemakerimpact.com/wp-content/uploads/2024/11/CIIP_WMi_PAA_Seeding-The-Future-Report.pdf

[5] Francis, T., Hoefel, F., 2018. ‘True Gen’: Generation Z and its implications for companies. Available from: https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/true-gen-generation-z-and-its-implications-for-companies (cited 10 November 2025).

[6] Khanh, N., 2023. Vietnamese Generation Z Online Purchasing Behavior toward Sustainability: Eco-Friendly Products on E-Commerce [Bachelor's Thesis]. Tampere University of Applied Sciences: Tampere, Finland. Available from: https://www.theseus.fi/bitstream/handle/10024/815085/Khanh_Nguyen.pdf?sequence=2&isAllowed=y

[7] Decision Lab, 2025. Vietnam Consumer AI market 2025: 78% of online population have engaged with AI, one-third turn it into a daily habit. Available from: https://www.decisionlab.co/blog/vietnam-consumer-ai-market-2025-78-of-online-population-have-engaged-with-ai-one-third-turn-it-into-a-daily-habit (cited 10 September 2025).

[8] Catană, Ștefan-A., Imbrișcă, C.-I., Veith, C., 2025. Understanding Generation Z′s Purchasing Behaviour on Online Marketplaces: A TAM-Based Approach. Journal of Theoretical and Applied Electronic Commerce Research. 20(4), 260. DOI: https://doi.org/10.3390/jtaer20040260

[9] Beyari, H., Garamoun, H., 2022. The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework. Sustainability. 14(15), 9637. DOI: https://doi.org/10.3390/su14159637

[10] Thi Mai Anh, N., Huong, P.T.T., 2019. Exploring the Vietnamese Consumer’s Trust in E-commerce. VNU Journal of Science: Economics and Business. 35(5E). DOI: https://doi.org/10.25073/2588-1108/vnueab.4299

[11] Food and Agriculture Organization (FAO), 2021. Digital Agriculture in Action. FAO: Rome, Italy. DOI: https://doi.org/10.4060/cb7142en

[12] Davis, F.D., 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly. 13(3), 319–340. DOI: https://doi.org/10.2307/249008

[13] Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 50(2), 179–211. DOI: https://doi.org/10.1016/0749-5978(91)90020-T

[14] Fishbein, M., Ajzen, I., 1975. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley: Reading, MA, USA.

[15] Venkatesh, V., Morris, M.G., Davis, G.B., et al., 2003. User Acceptance of Information Technology: Toward A Unified View. MIS Quarterly. 27(3), 425–478. DOI: https://doi.org/10.2307/30036540

[16] Jannach, D., Abdollahpouri, H., 2023. A survey on multi-objective recommender systems. Frontiers in Big Data. 6, 1157899. DOI: https://doi.org/10.3389/fdata.2023.1157899

[17] Ricci, F., Rokach, L., Shapira, B., 2015. Recommender Systems Handbook, 2nd ed. Springer: Singapore.

[18] Gilleski, S., Linh, N., 2022. Vietnam Issues Sustainable Agriculture and Rural Development Strategy 2021–2030 Vision to 2050. U.S. Department of Agriculture, Foreign Agricultural Service: Washington, DC, USA. Available from: https://gain.fas.usda.gov/Download.aspx?p=1597&q=18130cdc-c239-4fe3-a9cc-c7f43c575c6e

[19] IMARC Group, 2024. Vietnam AI in Agriculture Market Size, Share, Trends and Forecast by Offering, Technology, Application, and Region, 2026–2034. Available from: https://www.imarcgroup.com/vietnam-ai-in-agriculture-market (cited 10 November 2025).

[20] Thao, N.T.T., 2023. The Impact of E-Commerce on Consumer Behavior in Vietnam [Bachelor’s Thesis]. Savonia University of Applied Sciences: Kuopio, Finland. Available from: https://urn.fi/URN:NBN:fi:amk-2023120434106

[21] Liakos, K., Busato, P., Moshou, D., et al., 2018. Machine Learning in Agriculture: A Review. Sensors. 18(8), 2674. DOI: https://doi.org/10.3390/s18082674

[22] Adamopoulou, E., Moussiades, L., 2020. Chatbots: History, technology, and applications. Machine Learning with Applications. 2, 100006. DOI: https://doi.org/10.1016/j.mlwa.2020.100006

[23] Statista, 2024. Market share of e-commerce platforms based on gross merchandise value in Vietnam in 1st quarter 2024. Available from: https://www.statista.com/statistics/1487682/vietnam-market-share-of-e-commerce-platforms/ (cited 10 November 2025).

[24] Banerjee, P., 2025. Impact of Dynamic Pricing on Consumer Loyalty in E-Commerce. Journal of Informatics Education and Research. 5(1). DOI: https://doi.org/10.52783/jier.v5i1.2316

[25] Guo, Y., Liu, Y., Oerlemans, A., et al., 2016. Deep learning for visual understanding: A review. Neurocomputing. 187, 27–48. DOI: https://doi.org/10.1016/j.neucom.2015.09.116

[26] Hameed, I.M., Abdulhussain, S.H., Mahmmod, B.M., 2021. Content-based image retrieval: A review of recent trends. Cogent Engineering. 8(1), 1927469. DOI: https://doi.org/10.1080/23311916.2021.1927469

[27] World Bank, 2017. Vietnam—Sustainable Agriculture Transformation Project. World Bank: Washington, DC, USA. Available from: http://documents.worldbank.org/curated/en/783441467998463415

[28] Dale, R., 2016. The return of the chatbots. Natural Language Engineering. 22(5), 811–817. DOI: https://doi.org/10.1017/S1351324916000243

[29] Rita, P., Vong, C., Correia, C., 2026. How AI-driven chatbots shape customer satisfaction and loyalty to chatbot usage in digital service experience. Computers in Human Behavior Reports. 22, 101017. DOI: https://doi.org/10.1016/j.chbr.2026.101017

[30] Kikani, D., Ramchandani, S.M., 2025. The impact of AI chatbots on customer service: Efficiency vs. human touch: A comparative analysis of automation and human interaction in customer support. International Journal for Research Trends and Innovation. 10(3). Available from: https://www.ijrti.org/papers/IJRTI2503134.pdf

[31] Elmaghraby, W., Keskinocak, P., 2003. Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions. Management Science. 49(10), 1287–1309. DOI: https://doi.org/10.1287/mnsc.49.10.1287.17315

[32] AI for Good, 2025. AI for food systems. Available from: https://aiforgood.itu.int/ai-for-food-systems/ (cited 10 September 2025).

[33] Bhardwaj, P., 2019. Types of sampling in research. Journal of the Practice of Cardiovascular Sciences. 5(3), 157. DOI: https://doi.org/10.4103/jpcs.jpcs_62_19

[34] Pires, P.B., Perestrelo, B.M., Santos, J.D., 2025. Measuring Customer Experience in E-Retail. Administrative Sciences. 15(11), 434. DOI: https://doi.org/10.3390/admsci15110434

[35] Hair, J.F., Black, W.C., Babin, B.J., et al., 2010. Multivariate Data Analysis, 7th ed. Pearson: New York, NY, USA.

[36] Williams, B., Onsman, A., Brown, T., 2010. Exploratory Factor Analysis: A Five-Step Guide for Novices. Australasian Journal of Paramedicine. 8, 1–13. DOI: https://doi.org/10.33151/ajp.8.3.93

[37] Musa, S.F.P.D., 2020. A Study on Youth Aspiration and Perception of Agriculture and Its Policy Implications. In: Jean Vasile, A., Subic, J., Grubor, A., et al. (Eds.). Advances in Environmental Engineering and Green Technologies. IGI Global: New York, NY, USA. pp. 441–453. DOI: https://doi.org/10.4018/978-1-5225-9837-4.ch022

[38] Thang, B., 2025. AI and e-commerce drive Vietnamese farm produce past export barriers. Available from: https://van.nongnghiepmoitruong.vn/ai-and-e-commerce-drive-vietnamese-farm-produce-past-export-barriers-d771967.html (cited 10 September 2025).