IDEAS home Printed from https://ideas.repec.org/p/zbw/itse22/265662.html
   My bibliography  Save this paper

Quantifying different psychological costs of user behavioral info for overcoming the 'take-it-or-leave-it' condition

Author

Listed:
  • Nam, Sangjun
  • Kwon, Youngsun

Abstract

Take-it-or-leave-it, in which users have to provide personal information as required by service providers, has been a dominant form of agreement between online service providers and users. The regulators recently began to prohibit dominant online platforms from collecting personal data based on the 'take-it-or-leave-it' basis because this clause is likely to harm consumer welfare without giving users choices for using the service. In order to improve regulatory efficiency, we need to devise more flexible alternative service provisions balancing privacy concerns and enhanced service based on personal preference. To accomplish this goal, we need to understand the users' attitudes related to personal behavioral data collection for both regulators and online platforms. In this context, we aim to estimate the psychological costs that users bear when they need to exchange personal data for service use. Quantifying the perceived cost of personal data collection with monetary reward was common. However, it is not easy to determine whether the perceived cost is high or not because the monetized value of personal data is not self-evident. To address this issue, we consider attention cost, one of the representative inconvenience costs of using free online services in the analysis. This study collects the data using a conjoint survey and estimates the psychological costs of personal data collection using the mixed logit model and latent-class logit model. Our results show that the respondents' perceived cost for overcoming the 'take-it-or-leave-it' condition is heterogeneous, and only one of four respondent segments (around 30% of respondents) perceived it as significant. Moreover, the results suggest that the perceived risks and benefits of personal data collection affect the psychological cost. It implies that privacy calculus theory can be a meaningful framework for understanding users' attitudes toward behavioral data collection on online platforms.

Suggested Citation

  • Nam, Sangjun & Kwon, Youngsun, 2022. "Quantifying different psychological costs of user behavioral info for overcoming the 'take-it-or-leave-it' condition," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265662, International Telecommunications Society (ITS).
    • Handle: RePEc:zbw:itse22:265662
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/265662/1/Nam-and-Kwon.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Savage, Scott J. & Waldman, Donald M., 2015. "Privacy tradeoffs in smartphone applications," Economics Letters, Elsevier, vol. 137(C), pages 171-175.
    2. A. G. Winegar & C. R. Sunstein, 2019. "How Much Is Data Privacy Worth? A Preliminary Investigation," Journal of Consumer Policy, Springer, vol. 42(3), pages 425-440, September.
    3. Tiffany White & Debra Zahay & Helge Thorbjørnsen & Sharon Shavitt, 2008. "Getting too personal: Reactance to highly personalized email solicitations," Marketing Letters, Springer, vol. 19(1), pages 39-50, March.
    4. Hong Il Yoo, 2020. "lclogit2: An enhanced command to fit latent class conditional logit models," Stata Journal, StataCorp LP, vol. 20(2), pages 405-425, June.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    6. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    7. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    8. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
    9. Hayes, Jameson L. & Brinson, Nancy H. & Bott, Gregory J. & Moeller, Claire M., 2021. "The Influence of Consumer–Brand Relationship on the Personalized Advertising Privacy Calculus in Social Media," Journal of Interactive Marketing, Elsevier, vol. 55(C), pages 16-30.
    10. Tamara Dinev & Paul Hart, 2006. "An Extended Privacy Calculus Model for E-Commerce Transactions," Information Systems Research, INFORMS, vol. 17(1), pages 61-80, March.
    11. David S. Evans, 2013. "Attention Rivalry Among Online Platforms," Journal of Competition Law and Economics, Oxford University Press, vol. 9(2), pages 313-357.
    12. Costa-Cabral, Francisco & Lynskey, Orla, 2017. "Family ties: the intersection between data protection and competition in EU Law," LSE Research Online Documents on Economics 68470, London School of Economics and Political Science, LSE Library.
    13. Alfnes, Frode & Wasenden, Ole Christian, 2022. "Your privacy for a discount? Exploring the willingness to share personal data for personalized offers," Telecommunications Policy, Elsevier, vol. 46(7).
    14. Alison Munsch, 2021. "Millennial and generation Z digital marketing communication and advertising effectiveness: A qualitative exploration," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 31(1), pages 10-29, January.
    15. Alessandro Acquisti & Leslie K. John & George Loewenstein, 2013. "What Is Privacy Worth?," The Journal of Legal Studies, University of Chicago Press, vol. 42(2), pages 249-274.
    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. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    2. Carlos Barros, 2012. "Sustainable Tourism in Inhambane-Mozambique," CEsA Working Papers 105, CEsA - Centre for African and Development Studies.
    3. Caplan, Arthur J. & Akhundjanov, Sherzod B. & Toll, Kristopher, 2021. "Measuring heterogeneous preferences for residential amenities," Regional Science and Urban Economics, Elsevier, vol. 87(C).
    4. Galassi, Veronica & Madlener, Reinhard, 2017. "The Role of Environmental Concern and Comfort Expectations in Energy Retrofit Decisions," Ecological Economics, Elsevier, vol. 141(C), pages 53-65.
    5. Haile, Kaleab K. & Tirivayi, Nyasha & Tesfaye, Wondimagegn, 2019. "Farmers’ willingness to accept payments for ecosystem services on agricultural land: The case of climate-smart agroforestry in Ethiopia," Ecosystem Services, Elsevier, vol. 39(C).
    6. Tyllianakis, Emmanouil & Martin-Ortega, Julia & Ziv, Guy & Chapman, Pippa J. & Holden, Joseph & Cardwell, Michael & Fyfe, Duncan, 2023. "A window into land managers’ preferences for new forms of agri-environmental schemes: Evidence from a post-Brexit analysis," Land Use Policy, Elsevier, vol. 129(C).
    7. Natali, F. & Cacchiarelli, L. & Branca, G., 2022. "There are plenty more (sustainable) fish in the sea: A discrete choice experiment on discarded species in Italy," Ecological Economics, Elsevier, vol. 196(C).
    8. Paha, Johannes & Rompf, Dirk & Warnecke, Christiane, 2013. "Customer choice patterns in passenger rail competition," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 209-227.
    9. Feil, J.-H. & Anastassiadis, F. & Mußhoff, O. & Schilling, P., 2015. "Analysing Farmers’ Use of Price Hedging Instruments: An Experimental Approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 50, March.
    10. Aguilar, Francisco X. & Cai, Zhen & Mohebalian, Phillip & Thompson, Wyatt, 2015. "Exploring the drivers' side of the “blend wall”: U.S. consumer preferences for ethanol blend fuels," Energy Economics, Elsevier, vol. 49(C), pages 217-226.
    11. Alba J. Collart & Matthew G. Interis, 2018. "Consumer Imperfect Information in the Market for Expired and Nearly Expired Foods and Implications for Reducing Food Waste," Sustainability, MDPI, vol. 10(11), pages 1-17, October.
    12. Feil, J.-H. & Anastassiadis, F. & Mußhoff, O. & Kasten, P., 2016. "Analysing Farmers’ Preferences fo Collaborative Arrangements: An Experimental Approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 51, March.
    13. Maciej Sobolewski & Michał Paliński, 2017. "How much consumers value on-line privacy? Welfare assessment of new data protection regulation (GDPR)," Working Papers 2017-17, Faculty of Economic Sciences, University of Warsaw.
    14. Marco A. Palma & Dmitry V. Vedenov & David Bessler, 2020. "The order of variables, simulation noise, and accuracy of mixed logit estimates," Empirical Economics, Springer, vol. 58(5), pages 2049-2083, May.
    15. Gunnar Gutsche & Bernhard Zwergel, 2020. "Investment Barriers and Labeling Schemes for Socially Responsible Investments," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(2), pages 111-157, April.
    16. Yuanyuan Gu & Richard Norman & Rosalie Viney, 2014. "Estimating Health State Utility Values From Discrete Choice Experiments—A Qaly Space Model Approach," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 1098-1114, September.
    17. Martin Achtnicht & Daniel Osberghaus, 2019. "The Demand for Index‐Based Flood Insurance in a High‐Income Country," German Economic Review, Verein für Socialpolitik, vol. 20(2), pages 217-242, May.
    18. Schueftan, Alejandra & Aravena, Claudia & Reyes, René, 2021. "Financing energy efficiency retrofits in Chilean households: The role of financial instruments, savings and uncertainty in energy transition," Resource and Energy Economics, Elsevier, vol. 66(C).
    19. Gutsche, Gunnar & Ziegler, Andreas, 2019. "Which private investors are willing to pay for sustainable investments? Empirical evidence from stated choice experiments," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 193-214.
    20. Lea Skræp Svenningsen, 2017. "Distributive outcomes matter: Measuring social preferences for climate policy," IFRO Working Paper 2017/11, University of Copenhagen, Department of Food and Resource Economics.

    More about this item

    Keywords

    Personal data; Online platform; Privacy calculus theory; Information disclosure; Attention cost;
    All these keywords.

    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:zbw:itse22:265662. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: http://www.itseurope.org/ .

    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.