IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v62y2009i5p565-571.html
   My bibliography  Save this article

Consumer e-shopping acceptance: Antecedents in a technology acceptance model

Author

Listed:
  • Ha, Sejin
  • Stoel, Leslie

Abstract

This study integrates e-shopping quality, enjoyment, and trust into a technology acceptance model (TAM) to understand consumer acceptance of e-shopping. Online surveys with college students (n=298) were conducted. E-shopping quality for apparel products consists of four dimensions: web site design, customer service, privacy/security, and atmospheric/experiential. A structural equation model reveals that e-shopping quality determines perceptions of usefulness, trust, and enjoyment, which in turn influence consumers' attitudes toward e-shopping. Consumer perceptions of usefulness and attitude toward e-shopping influence intention to shop online, while perceived ease of use does not influence attitude toward e-shopping. Shopping enjoyment and trust play significant roles in consumers' adoption of e-shopping. This study provides important implications for e-tailers whose web site developers must keep in mind that customers are not only web users with trust/safety and information needs, but also shoppers with service and experiential needs.

Suggested Citation

  • Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
  • Handle: RePEc:eee:jbrese:v:62:y:2009:i:5:p:565-571
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148-2963(08)00172-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    3. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    4. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    5. Chen, Lei-Da & Tan, Justin, 2004. "Technology Adaptation in E-commerce:: Key Determinants of Virtual Stores Acceptance," European Management Journal, Elsevier, vol. 22(1), pages 74-86, February.
    6. Bauer, Hans H. & Falk, Tomas & Hammerschmidt, Maik, 2006. "eTransQual: A transaction process-based approach for capturing service quality in online shopping," Journal of Business Research, Elsevier, vol. 59(7), pages 866-875, July.
    7. Bruner, Gordon II & Kumar, Anand, 2005. "Explaining consumer acceptance of handheld Internet devices," Journal of Business Research, Elsevier, vol. 58(5), pages 553-558, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Domina, Tanya & Lee, Seung-Eun & MacGillivray, Maureen, 2012. "Understanding factors affecting consumer intention to shop in a virtual world," Journal of Retailing and Consumer Services, Elsevier, vol. 19(6), pages 613-620.
    2. Pando-Garcia, Julián & Periañez-Cañadillas, Iñaki & Charterina, Jon, 2016. "Business simulation games with and without supervision: An analysis based on the TAM model," Journal of Business Research, Elsevier, vol. 69(5), pages 1731-1736.
    3. 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).
    4. Schoenherr, Tobias, 2023. "Supply chain management professionals’ proficiency in big data analytics: Antecedents and impact on performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    5. Hsiao, Chun Hua & Yang, Chyan, 2011. "The intellectual development of the technology acceptance model: A co-citation analysis," International Journal of Information Management, Elsevier, vol. 31(2), pages 128-136.
    6. Mohammad Hasan Galib & Khalid Ait Hammou & Jennifer Steiger, 2018. "Predicting Consumer Behavior: An Extension of Technology Acceptance Model," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 10(3), pages 1-73, August.
    7. Dirsehan, Taşkın & Cankat, Ece, 2021. "Role of mobile food-ordering applications in developing restaurants’ brand satisfaction and loyalty in the pandemic period," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    8. Nastjuk, Ilja & Herrenkind, Bernd & Marrone, Mauricio & Brendel, Alfred Benedikt & Kolbe, Lutz M., 2020. "What drives the acceptance of autonomous driving? An investigation of acceptance factors from an end-user's perspective," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    9. Rizomyliotis, Ioannis & Kastanakis, Minas N. & Giovanis, Apostolos & Konstantoulaki, Kleopatra & Kostopoulos, Ioannis, 2022. "“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment," Journal of Business Research, Elsevier, vol. 153(C), pages 329-340.
    10. Nedra, Bahri-Ammari & Hadhri, Walid & Mezrani, Mariem, 2019. "Determinants of customers' intentions to use hedonic networks: The case of Instagram," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 21-32.
    11. Rese, Alexandra & Baier, Daniel & Geyer-Schulz, Andreas & Schreiber, Stefanie, 2017. "How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 306-319.
    12. Han, Sang-Lin & An, Myounga & Han, Jerry J. & Lee, Jiyoung, 2020. "Telepresence, time distortion, and consumer traits of virtual reality shopping," Journal of Business Research, Elsevier, vol. 118(C), pages 311-320.
    13. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    14. Adams, Peter & Farrell, Mark & Dalgarno, Barney & Oczkowski, Edward, 2017. "Household Adoption of Technology: The Case of High-Speed Broadband Adoption in Australia," Technology in Society, Elsevier, vol. 49(C), pages 37-47.
    15. Pallant, Jessica & Sands, Sean & Karpen, Ingo, 2020. "Product customization: A profile of consumer demand," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    16. Collier, Joel E. & Barnes, Donald C., 2015. "Self-service delight: Exploring the hedonic aspects of self-service," Journal of Business Research, Elsevier, vol. 68(5), pages 986-993.
    17. Julian M. Müller, 2019. "Comparing Technology Acceptance for Autonomous Vehicles, Battery Electric Vehicles, and Car Sharing—A Study across Europe, China, and North America," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    18. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    19. Hernández, Blanca & Jiménez, Julio & Martín, M. José, 2010. "Customer behavior in electronic commerce: The moderating effect of e-purchasing experience," Journal of Business Research, Elsevier, vol. 63(9-10), pages 964-971, September.
    20. Agrebi, Sinda & Jallais, Joël, 2015. "Explain the intention to use smartphones for mobile shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 16-23.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:62:y:2009:i:5:p:565-571. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.