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The future of TV-shopping: predicting user purchase intention through an extended technology acceptance model

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  • Rodríguez-López, María Eugenia
  • Higueras-Castillo, Elena
  • Rojas-Lamorena, Álvaro J.
  • Alcántara-Pilar, Juan Miguel

Abstract

The shoppable TV, which allows the purchase of products appearing in TV programmes directly, is a digital trend that is not implemented in most markets, but companies such as Amazon and NBC Universal have proposed the first sales systems. The aim of this research is to forecast the adoption intention of this technology by applying the Technology Acceptance Model. Structural equation modelling (PLS-SEM) has been applied to a sample of 283 participants. The results indicate that shopping enjoyment is particularly important in generating attitudes toward this type of consumption, and this increases the intention to use Shoppable TV.

Suggested Citation

  • Rodríguez-López, María Eugenia & Higueras-Castillo, Elena & Rojas-Lamorena, Álvaro J. & Alcántara-Pilar, Juan Miguel, 2024. "The future of TV-shopping: predicting user purchase intention through an extended technology acceptance model," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:tefoso:v:198:y:2024:i:c:s0040162523006716
    DOI: 10.1016/j.techfore.2023.122986
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    as
    1. Liu, Xiaohui & He, Xiaoyu & Wang, Mengmeng & Shen, Huizhang, 2022. "What influences patients' continuance intention to use AI-powered service robots at hospitals? The role of individual characteristics," Technology in Society, Elsevier, vol. 70(C).
    2. Niousha Shahidi & Vesselina Tossan & Stéphane Bourliataux-Lajoinie & Silvia Cacho-Elizondo, 2022. "Behavioural intention to use a contact tracing application: The case of StopCovid in France," Post-Print hal-03666263, HAL.
    3. Brusch, Ines & Rappel, Nina, 2020. "Exploring the acceptance of instant shopping – An empirical analysis of the determinants of user intention," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    4. Sánchez-Franco, Manuel J. & Arenas-Márquez, Francisco J. & Alonso-Dos-Santos, Manuel, 2021. "Using structural topic modelling to predict users’ sentiment towards intelligent personal agents. An application for Amazon’s echo and Google Home," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    5. Semila Fernandes & V.G. Venkatesh & Rajesh Panda & Yangyan Shi, 2021. "Measurement of factors influencing online shopper buying decisions: A scale development and validation," Post-Print hal-04455597, HAL.
    6. Driediger, Fabian & Bhatiasevi, Veera, 2019. "Online grocery shopping in Thailand: Consumer acceptance and usage behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 224-237.
    7. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    8. Yan, Li-Ya & Tan, Garry Wei-Han & Loh, Xiu-Ming & Hew, Jun-Jie & Ooi, Keng-Boon, 2021. "QR code and mobile payment: The disruptive forces in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    9. Rese, Alexandra & Ganster, Lena & Baier, Daniel, 2020. "Chatbots in retailers’ customer communication: How to measure their acceptance?," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    10. Kwak, Jooyoung & Zhang, Yue & Yu, Jiang, 2019. "Legitimacy building and e-commerce platform development in China: The experience of Alibaba," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 115-124.
    11. Pantano, Eleonora & Rese, Alexandra & Baier, Daniel, 2017. "Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 81-95.
    12. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
    13. Engström, Emma & Strimling, Pontus, 2020. "Deep learning diffusion by infusion into preexisting technologies – Implications for users and society at large," Technology in Society, Elsevier, vol. 63(C).
    14. Zhong, Yongping & Oh, Segu & Moon, Hee Cheol, 2021. "Service transformation under industry 4.0: Investigating acceptance of facial recognition payment through an extended technology acceptance model," Technology in Society, Elsevier, vol. 64(C).
    15. Hsin-Hui Lin, 2011. "Gender differences in the linkage of online patronage behavior with TV-and-online shopping values," Service Business, Springer;Pan-Pacific Business Association, vol. 5(4), pages 295-312, December.
    16. Christian Nitzl, 2016. "The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for future theory development," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 37(1), pages 19-35, October.
    17. Wagner, Gerhard & Schramm-Klein, Hanna & Steinmann, Sascha, 2017. "Consumers' attitudes and intentions toward Internet-enabled TV shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 278-286.
    18. Kim, Jiyeon & Forsythe, Sandra, 2008. "Adoption of Virtual Try-on technology for online apparel shopping," Journal of Interactive Marketing, Elsevier, vol. 22(2), pages 45-59.
    19. Natarajan, Thamaraiselvan & Balasubramanian, Senthil Arasu & Kasilingam, Dharun Lingam, 2017. "Understanding the intention to use mobile shopping applications and its influence on price sensitivity," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 8-22.
    20. Tseng, Shu-Mei, 2015. "Exploring the intention to continue using web-based self-service," Journal of Retailing and Consumer Services, Elsevier, vol. 24(C), pages 85-93.
    21. Fernandes, Semila & Venkatesh, V.G. & Panda, Rajesh & Shi, Yangyan, 2021. "Measurement of factors influencing online shopper buying decisions: A scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    22. Kautish, Pradeep & Purohit, Sonal & Filieri, Raffaele & Dwivedi, Yogesh K., 2023. "Examining the role of consumer motivations to use voice assistants for fashion shopping: The mediating role of awe experience and eWOM," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    23. Groß, Michael, 2018. "Heterogeneity in consumers’ mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segments," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 8-18.
    24. Swilley, Esther & Goldsmith, Ronald E., 2013. "Black Friday and Cyber Monday: Understanding consumer intentions on two major shopping days," Journal of Retailing and Consumer Services, Elsevier, vol. 20(1), pages 43-50.
    25. Li Hua & Shanyong Wang, 2019. "Antecedents of Consumers’ Intention to Purchase Energy-Efficient Appliances: An Empirical Study Based on the Technology Acceptance Model and Theory of Planned Behavior," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
    26. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    27. Umair Cheema & Muhammad Rizwan & Rizwan Jalal & Faiza Durrani & Nawal Sohail, 2013. "The Trend of Online Shopping in 21st Century: Impact of Enjoyment in Tam Model," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 3(2), pages 131-141, February.
    28. Reinartz, Werner & Haenlein, Michael & Henseler, Jörg, 2009. "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 332-344.
    29. Barari, Mojtaba & Ross, Mitchell & Surachartkumtonkun, Jiraporn, 2020. "Negative and positive customer shopping experience in an online context," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
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