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AI Technology and Online Purchase Intention: Structural Equation Model Based on Perceived Value

Author

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  • Jiwang Yin

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Xiaodong Qiu

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

Abstract

(1) Background: AI technology has been deeply applied to online shopping platforms to provide more accurate and personalized services for consumers. It is of great significance to study the different functional experiences of AI for consumers to improve the current application status of AI technology. (2) Method: Based on the “SOR” model, this study divides the AI technology experienced by the consumers of online shopping platforms into three dimensions: accuracy, insight, and interaction experience. The perceived value is taken as the mediating variable from the prospect of perceived utility value and perceived hedonic value. This article uses empirical research methods to analyze the effect of the three dimensions of online shopping AI experience to research the internal influence mechanism of consumers’ purchase intention. (3) Results: 1. The accuracy, insight, and interaction experience of AI marketing technology each have a significant positive impact on consumers’ perceived utility value and hedonic value; 2. Both the perceived utility value and perceived hedonic value obtained by an AI technology experience can promote the formation of consumers’ purchase intention; 3. The perceived hedonic value was better than perceived utility value at promoting the consumers’ purchase intention.

Suggested Citation

  • Jiwang Yin & Xiaodong Qiu, 2021. "AI Technology and Online Purchase Intention: Structural Equation Model Based on Perceived Value," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5671-:d:557316
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    3. Angga Febrian & Nabila Az-Zahra Najwa Amrizal & Rafika Indi Qut Ratuain, 2024. "The Role Of Artificial Intelligence: Increasing Ecommerce Purchase Intentions In Indonesia," Scientific Bulletin - Economic Sciences, University of Pitesti, vol. 23(1), pages 9-14.
    4. Miao Huang & Mohamad Saifudin Mohamad Saleh & Izzal Asnira Zolkepli, 2023. "The Moderating Effect of Green Advertising on the Relationship between Gamification and Sustainable Consumption Behavior: A Case Study of the Ant Forest Social Media App," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    5. Hasan Beyari & Hatem Garamoun, 2022. "The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework," Sustainability, MDPI, vol. 14(15), pages 1-17, August.
    6. Zhijie Song & Chang Liu & Rui Shi, 2022. "How Do Fresh Live Broadcast Impact Consumers’ Purchase Intention? Based on the SOR Theory," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    7. Md. Emam Hossain & Subarna Biswas, 2024. "Technology acceptance model for understanding consumer’s behavioral intention to use artificial intelligence based online shopping platforms in Bangladesh," SN Business & Economics, Springer, vol. 4(12), pages 1-61, December.
    8. Elizabeth Emperatriz García-Salirrosas & Ángel Acevedo-Duque & Viviana Marin Chaves & Paula Andrea Mejía Henao & Juan Carlos Olaya Molano, 2022. "Purchase Intention and Satisfaction of Online Shop Users in Developing Countries during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    9. Jinsoo Hwang & Heather Markham Kim & Kyuhyeon Joo & Muhammad Nawaz & Joonho Moon, 2022. "Travelers’ Perceived Value of Robot Services in the Airline Industry: Focusing on Demographic Characteristics," Sustainability, MDPI, vol. 14(23), pages 1-12, November.
    10. Nazir, Sajjad & Khadim, Sahar & Ali Asadullah, Muhammad & Syed, Nausheen, 2023. "Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach," Technology in Society, Elsevier, vol. 72(C).
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    12. Tao Zhou & Xiaoying Wu, 2024. "Examining user migration intention from social Q&A communities to generative AI," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
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