IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i11p2041-d117977.html
   My bibliography  Save this article

Assessing the User Resistance to Recommender Systems in Exhibition

Author

Listed:
  • Chulmo Koo

    (College of Hotel & Tourism Management, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 02447, Korea)

  • Namho Chung

    (College of Hotel & Tourism Management, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 02447, Korea)

  • Juyeon Ham

    (College of Hotel & Tourism Management, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 02447, Korea)

Abstract

Under the paradigm shift toward smart tourism, the exhibition industry is making efforts to introduce innovative technologies that can provide more diverse and valuable experiences to attendees. However, various new information technologies have failed in a market in practice due to the user’s resistance against it. Since innovative technology, such as booth recommender systems (BRS), is changing, creating uncertainty among consumers, consumer’s resistance to innovative technology can be considered a normal reaction. Therefore, it is important for a company to understand the psychological aspect of the consumer’s resistance and make measures to overcome the resistance. Accordingly, based on the model of Kim and Kankanhalli (2009), by applying the perceived value, the technology acceptance model, and the status quo bias theory, this study focused on the importance of self-efficacy and technical support in the context of using BRS. To do this purpose, a total of 455 survey data that was collected from “Korea franchise exhibition” attendees were used to analyze the proposed model. Structural equation modeling was applied for data analysis. The result shows that perceived value was affected by relative advantage and switching cost, also switching cost reduced the perceived value. However, self-efficacy reduced the switching cost, thereby decreasing the resistance of exhibition attendees. In addition, technical support increased the relative advantage switching cost and the perceived value. Exhibition attendee’s resistance was significantly negatively affected by perceived value, and positively affected by switching cost. The results will provide balanced viewpoints between the relative advantage and switching cost for exhibition marketers, helping to strengthen the competitiveness in terms of sustainable tourism of exhibition.

Suggested Citation

  • Chulmo Koo & Namho Chung & Juyeon Ham, 2017. "Assessing the User Resistance to Recommender Systems in Exhibition," Sustainability, MDPI, vol. 9(11), pages 1-16, November.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:11:p:2041-:d:117977
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/11/2041/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/11/2041/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. Samuelson, William & Zeckhauser, Richard, 1988. "Status Quo Bias in Decision Making," Journal of Risk and Uncertainty, Springer, vol. 1(1), pages 7-59, March.
    5. James C. Anderson & David W. Gerbing, 1992. "Assumptions and Comparative Strengths of the Two-Step Approach," Sociological Methods & Research, , vol. 20(3), pages 321-333, 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. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

    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. Hsieh, Pi-Jung, 2021. "Understanding medical consumers’ intentions to switch from cash payment to medical mobile payment: A perspective of technology migration," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    2. Wang, Yu-Yin & Wang, Yi-Shun & Lin, Tung-Ching, 2018. "Developing and validating a technology upgrade model," International Journal of Information Management, Elsevier, vol. 38(1), pages 7-26.
    3. Roemer, Ellen & Henseler, Jörg, 2022. "The dynamics of electric vehicle acceptance in corporate fleets: Evidence from Germany," Technology in Society, Elsevier, vol. 68(C).
    4. Zied Mani & Inès Chouk, 2018. "Consumer Resistance to Innovation in Services," Post-Print hal-03700875, HAL.
    5. Jacques Nel & Christo Boshoff, 2023. "Unraveling the link between status quo satisfaction and the rejection of digital-only banks," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 189-207, March.
    6. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    7. Philippe Fevrier & Sebastien Gay, 2005. "Informed Consent Versus Presumed Consent The Role of the Family in Organ Donations," HEW 0509007, University Library of Munich, Germany.
    8. Jose Apesteguia & Miguel Ballester, 2009. "A theory of reference-dependent behavior," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 40(3), pages 427-455, September.
    9. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    10. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. Karle, Heiko & Schumacher, Heiner & Vølund, Rune, 2023. "Consumer loss aversion and scale-dependent psychological switching costs," Games and Economic Behavior, Elsevier, vol. 138(C), pages 214-237.
    12. Louis Lévy-Garboua & Claude Montmarquette, 1996. "Cognition In Seemingly Riskless Choices And Judgments," Rationality and Society, , vol. 8(2), pages 167-185, May.
    13. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    14. Erica Mina Okada, 2010. "Uncertainty, Risk Aversion, and WTA vs. WTP," Marketing Science, INFORMS, vol. 29(1), pages 75-84, 01-02.
    15. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    16. Jidong Zhou, 2011. "Reference Dependence and Market Competition," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(4), pages 1073-1097, December.
    17. Jae‐Do Song, 2023. "Excessive banking preference in emissions trading," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 448-458, January.
    18. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    19. Alex Imas & Sally Sadoff & Anya Samek, 2017. "Do People Anticipate Loss Aversion?," Management Science, INFORMS, vol. 63(5), pages 1271-1284, May.
    20. Hajiheydari, Nastaran & Delgosha, Mohammad Soltani & Olya, Hossein, 2021. "Scepticism and resistance to IoMT in healthcare: Application of behavioural reasoning theory with configurational perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).

    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:gam:jsusta:v:9:y:2017:i:11:p:2041-:d:117977. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.