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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

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  • Bilal, Muhammad
  • Zhang, Yunfeng
  • Cai, Shukai
  • Akram, Umair
  • Halibas, Alrence

Abstract

Artificial intelligence (AI) is revolutionizing consumer–provider interactions by changing the nature of online purchases. This study uses the social support theory to investigate consumer purchase intentions by combining AI technology, consumer social media engagement, and consumer experience. Online surveys are conducted with 467 Chinese social media users who had experience with online purchasing and AI technology. Partial Least Squares Structural Equation Modelling (PLS-SEM) is used to examine the data and proposed hypothesis. This study finds that AI positively affects consumer experience and consumer engagement on social media. Similarly, a positive relationship exists between social media engagement and consumer experience, leading to a more satisfied consumer and amplified purchase intentions. Additionally, affective attachment moderates the relationship between consumer satisfaction and purchase intention. The results reveal that AI can be used on social media to improve consumer experience and increase customer satisfaction levels and purchase intention. We also provide tips for developing flawless service business models. Marketers should explore making social media posts more engaging by using vibrant images and videos to attract customers and prompt them to create, circulate, and share said content on various social media networks.

Suggested Citation

  • Bilal, Muhammad & Zhang, Yunfeng & Cai, Shukai & Akram, Umair & Halibas, Alrence, 2024. "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 attach," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:joreco:v:77:y:2024:i:c:s0969698923004253
    DOI: 10.1016/j.jretconser.2023.103674
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    1. De Silva, Muthu & Wang, Pengji & Kuah, Adrian T.H., 2021. "Why wouldn’t green appeal drive purchase intention? Moderation effects of consumption values in the UK and China," Journal of Business Research, Elsevier, vol. 122(C), pages 713-724.
    2. Reinartz, Werner & Wiegand, Nico & Imschloss, Monika, 2019. "The impact of digital transformation on the retailing value chain," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 350-366.
    3. Yuksel, Atila & Yuksel, Fisun & Bilim, Yasin, 2010. "Destination attachment: Effects on customer satisfaction and cognitive, affective and conative loyalty," Tourism Management, Elsevier, vol. 31(2), pages 274-284.
    4. Chaouali, Walid & Ben Yahia, Imene & Souiden, Nizar, 2016. "The interplay of counter-conformity motivation, social influence, and trust in customers' intention to adopt Internet banking services: The case of an emerging country," Journal of Retailing and Consumer Services, Elsevier, vol. 28(C), pages 209-218.
    5. Leong, Lai-Ying & Hew, Teck-Soon & Ooi, Keng-Boon & Wei, June, 2020. "Predicting mobile wallet resistance: A two-staged structural equation modeling-artificial neural network approach," International Journal of Information Management, Elsevier, vol. 51(C).
    6. Moon, Sangkil & Jalali, Nima & Erevelles, Sunil, 2021. "Segmentation of both reviewers and businesses on social media," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    7. Ahmad, Wasim & Kim, Woo Gon & Choi, Hyung-Min & Haq, Junaid Ul, 2021. "Modeling behavioral intention to use travel reservation apps: A cross-cultural examination between US and China," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    8. 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.
    9. Sarkar, Subhro & Chauhan, Sumedha & Khare, Arpita, 2020. "A meta-analysis of antecedents and consequences of trust in mobile commerce," International Journal of Information Management, Elsevier, vol. 50(C), pages 286-301.
    10. Nadeem, Waqar & Tan, Teck Ming & Tajvidi, Mina & Hajli, Nick, 2021. "How do experiences enhance brand relationship performance and value co-creation in social commerce? The role of consumer engagement and self brand-connection," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    11. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 300-301, July.
    12. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    13. Capatina, Alexandru & Kachour, Maher & Lichy, Jessica & Micu, Adrian & Micu, Angela-Eliza & Codignola, Federica, 2020. "Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users’ expectations," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    14. Crittenden, Andrew B. & Crittenden, Victoria L. & Crittenden, William F., 2019. "The digitalization triumvirate: How incumbents survive," Business Horizons, Elsevier, vol. 62(2), pages 259-266.
    15. Pandita, Shailesh & Mishra, Hari Govind & Chib, Shagun, 2021. "Psychological impact of covid-19 crises on students through the lens of Stimulus-Organism-Response (SOR) model," Children and Youth Services Review, Elsevier, vol. 120(C).
    16. Paschen, Jeannette & Wilson, Matthew & Ferreira, João J., 2020. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel," Business Horizons, Elsevier, vol. 63(3), pages 403-414.
    17. Muhammad Bilal & Zeng Jianqiu & Umair Akram & Yasir Tanveer & Taiba Sardar & Hassan Rasool, 2020. "Understanding the Effects of Internet Usage Behavior on eWOM," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 12(3), pages 93-113, July.
    18. Thakur, Rakhi, 2018. "Customer engagement and online reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 48-59.
    19. Liu, Linlin & Lee, Matthew K.O. & Liu, Renjing & Chen, Jiawen, 2018. "Trust transfer in social media brand communities: The role of consumer engagement," International Journal of Information Management, Elsevier, vol. 41(C), pages 1-13.
    20. Yueling Xu & Wenyu Zhang & Haijun Bao & Shuai Zhang & Ying Xiang, 2019. "A SEM–Neural Network Approach to Predict Customers’ Intention to Purchase Battery Electric Vehicles in China’s Zhejiang Province," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    21. Borges, Aline F.S. & Laurindo, Fernando J.B. & Spínola, Mauro M. & Gonçalves, Rodrigo F. & Mattos, Claudia A., 2021. "The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions," International Journal of Information Management, Elsevier, vol. 57(C).
    22. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    23. Li Yang & Tony L. Henthorne & Babu George, 2020. "Artificial Intelligence and Robotics Technology in the Hospitality Industry: Current Applications and Future Trends," Springer Books, in: Babu George & Justin Paul (ed.), Digital Transformation in Business and Society, chapter 0, pages 211-228, Springer.
    24. Baabdullah, Abdullah Mohammed, 2018. "Consumer adoption of Mobile Social Network Games (M-SNGs) in Saudi Arabia: The role of social influence, hedonic motivation and trust," Technology in Society, Elsevier, vol. 53(C), pages 91-102.
    25. Mohammed Majeed & Charles Asare & Alhassan Fatawu & Aidatu Abubakari, 2022. "An analysis of the effects of customer satisfaction and engagement on social media on repurchase intention in the hospitality industry," Cogent Business & Management, Taylor & Francis Journals, vol. 9(1), pages 2028331-202, December.
    26. Singh, Nidhi & Sinha, Neena & Liébana-Cabanillas, Francisco J., 2020. "Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence," International Journal of Information Management, Elsevier, vol. 50(C), pages 191-205.
    27. Su, Lujun & Swanson, Scott R. & Chinchanachokchai, Sydney & Hsu, Maxwell K. & Chen, Xiaohong, 2016. "Reputation and intentions: The role of satisfaction, identification, and commitment," Journal of Business Research, Elsevier, vol. 69(9), pages 3261-3269.
    28. Vishal V. Agrawal & Atalay Atasu & Koert van Ittersum, 2015. "Remanufacturing, Third-Party Competition, and Consumers' Perceived Value of New Products," Management Science, INFORMS, vol. 61(1), pages 60-72, January.
    29. Upadhyay, Nitin & Kamble, Aakash, 2023. "Examining Indian consumer pro-environment purchase intention of electric vehicles: Perspective of stimulus-organism-response," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    30. Chiu, Yi-Te & Zhu, Yu-Qian & Corbett, Jacqueline, 2021. "In the hearts and minds of employees: A model of pre-adoptive appraisal toward artificial intelligence in organizations," International Journal of Information Management, Elsevier, vol. 60(C).
    31. Raouf Ahmad Rather, 2021. "Monitoring the impacts of tourism-based social media, risk perception and fear on tourist’s attitude and revisiting behaviour in the wake of COVID-19 pandemic," Current Issues in Tourism, Taylor & Francis Journals, vol. 24(23), pages 3275-3283, December.
    32. Bisbe, Josep & Batista-Foguet, Joan-Manuel & Chenhall, Robert, 2007. "Defining management accounting constructs: A methodological note on the risks of conceptual misspecification," Accounting, Organizations and Society, Elsevier, vol. 32(7-8), pages 789-820.
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