IDEAS home Printed from https://ideas.repec.org/p/opa/wpaper/0044.html
   My bibliography  Save this paper

The Theoretical Framework for the Application of the TAM in Online Grocery Shopping

Author

Listed:
  • Radka Bauerová

    (Department of Business Economics and Management, School of Business Administration, Silesian University)

  • Martin Klepek

    (Department of Business Economics and Management, School of Business Administration, Silesian University)

Abstract

In today's world, the technology and internet reshaped the way products are ordered, delivered and consumed. More and more customers have internet connection thus opportunity to buy online. The products bought mostly online are mobile and IT, electronics, home and gardening equipment and fashion. On the other side of the spectrum is food. Thanks to high demands on logistics, companies entered the market in the Czech Republic gradually. One fourth of Czech customers tried buying food online and every tenth person buys groceries regularly. However, the relative turnover of online groceries to whole e-commerce market is low. Online retailers or e-retailers are therefore in constant search for understanding of consumer behaviour behind current situation. The aim of the paper is to formulate a theoretical model and formulate a hypothesis for consecutive model testing via structural equation modelling approach. The model will be suitable for online grocery shopping acceptance as a new technology in retail domain.

Suggested Citation

  • Radka Bauerová & Martin Klepek, 2017. "The Theoretical Framework for the Application of the TAM in Online Grocery Shopping," Working Papers 0044, Silesian University, School of Business Administration.
    • Handle: RePEc:opa:wpaper:0044
    as

    Download full text from publisher

    File URL: http://www.iivopf.cz/images/Working_papers/WPIEBRS2017/WPIEBRS_44_Bauerova_Klepek.pdf
    File Function: First version, 2017
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rohm, Andrew J. & Swaminathan, Vanitha, 2004. "A typology of online shoppers based on shopping motivations," Journal of Business Research, Elsevier, vol. 57(7), pages 748-757, July.
    2. 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.
    3. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michal Stoklasa & Eva Pitrunová, 2018. "Past and Future Research Trends of Regional Brands with Accent to Technology," Working Papers 0051, Silesian University, School of Business Administration.

    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. Sohn, Stefanie, 2017. "A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 22-33.
    2. Yang, Byunghwa & Kim, Youngchan & Yoo, Changjo, 2013. "The integrated mobile advertising model: The effects of technology- and emotion-based evaluations," Journal of Business Research, Elsevier, vol. 66(9), pages 1345-1352.
    3. Attié, Elodie & Meyer-Waarden, Lars, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    4. 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).
    5. 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.
    6. Wang, Shangrui & Cao, Anran & Wang, Guohua & Xiao, Yiming, 2022. "The Impact of energy poverty on the digital divide: The mediating effect of depression and Internet perception," Technology in Society, Elsevier, vol. 68(C).
    7. Fosso Wamba, Samuel & Bhattacharya, Mithu & Trinchera, Laura & Ngai, Eric W.T., 2017. "Role of intrinsic and extrinsic factors in user social media acceptance within workspace: Assessing unobserved heterogeneity," International Journal of Information Management, Elsevier, vol. 37(2), pages 1-13.
    8. Akram, Umair & Junaid, Muhammad & Zafar, Abaid Ullah & Li, Zhiwen & Fan, Mingyue, 2021. "Online purchase intention in Chinese social commerce platforms: Being emotional or rational?," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    9. Deepak Chawla & Himanshu Joshi, 2018. "The Moderating Effect of Demographic Variables on Mobile Banking Adoption: An Empirical Investigation," Global Business Review, International Management Institute, vol. 19(3_suppl), pages 90-113, June.
    10. Brenda Mak & Robert C. Nickerson & Henri Isaac, 2009. "A Model Of Attitudes Towards The Acceptance Of Mobile Phone Use In Public Places," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 305-326.
    11. 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.
    12. Mital, Monika & Chang, Victor & Choudhary, Praveen & Papa, Armando & Pani, Ashis K., 2018. "Adoption of Internet of Things in India: A test of competing models using a structured equation modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 339-346.
    13. Verhagen. T. & Feldberg, F. & Hooff, B. van den, 2008. "Explaining user adoption of virtual worlds: towards a multipurpose Explaining user adoption of virtual worlds: towards a multipurpose motivational model," Serie Research Memoranda 0006, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    14. Maria Tsourela & Dafni-Maria Nerantzaki, 2020. "An Internet of Things (IoT) Acceptance Model. Assessing Consumer’s Behavior toward IoT Products and Applications," Future Internet, MDPI, vol. 12(11), pages 1-23, November.
    15. Rajak, Manindra & Shaw, Krishnendu, 2021. "An extension of technology acceptance model for mHealth user adoption," Technology in Society, Elsevier, vol. 67(C).
    16. Kerstin Pezoldt & Jana Schliewe, 2012. "Akzeptanz von Self-Service-Technologien: State of the Art," Schmalenbach Journal of Business Research, Springer, vol. 64(2), pages 205-253, March.
    17. Nuno Calheiros-Lobo & José Vasconcelos Ferreira & Manuel Au-Yong-Oliveira, 2023. "SME Internationalization and Export Performance: A Systematic Review with Bibliometric Analysis," Sustainability, MDPI, vol. 15(11), pages 1-36, May.
    18. Baier, Daniel & Stüber, Eva, 2010. "Acceptance of recommendations to buy in online retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 17(3), pages 173-180.
    19. Yang, Chung-Shan, 2019. "Maritime shipping digitalization: Blockchain-based technology applications, future improvements, and intention to use," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 108-117.
    20. Weck, Marina & Afanassieva, Marianne, 2023. "Toward the adoption of digital assistive technology: Factors affecting older people's initial trust formation," Telecommunications Policy, Elsevier, vol. 47(2).

    More about this item

    Keywords

    Technology acceptance model; TAM modification; online sales; online shopping; online grocery shopping;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:opa:wpaper:0044. 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: David Jančar (email available below). General contact details of provider: https://edirc.repec.org/data/opfslcz.html .

    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.