IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3362-d1066088.html
   My bibliography  Save this article

User Privacy Awareness, Incentive and Data Supply Chain Pricing Strategy

Author

Listed:
  • Haifei Yu

    (School of Business Administration, Northeastern University, Shenyang 110819, China)

  • Shanshan Zheng

    (School of Business Administration, Northeastern University, Shenyang 110819, China)

  • Hao Wu

    (Department of Science & Technology of Liaoning Province, Shenyang 110004, China)

Abstract

In recent years, the collection, mining, and utilization of data have become a new profit growth point for enterprises, and these events have also accelerated the pace of enterprises to collect users’ data. However, the relevance of personal data privacy and the frequent occurrence of data leakage events have increased users’ privacy awareness. The purpose of our study is to enhance the effective flow of data while protecting users’ data privacy. The data supply chain consists of the end user, data provider, and service provider, and involves the flow of the value-added process of data. Our study focuses on the pricing strategy of data products considering data incentive and data protection levels. We propose three models—centralized pricing, decentralized pricing, and revenue-sharing pricing—and solve them, and then we analyze the impact of users’ privacy awareness on data incentives, protection, and pricing of data products in the three models. We also analyze which pricing method works best for participants.

Suggested Citation

  • Haifei Yu & Shanshan Zheng & Hao Wu, 2023. "User Privacy Awareness, Incentive and Data Supply Chain Pricing Strategy," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3362-:d:1066088
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3362/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3362/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. I. Ooijen & Helena U. Vrabec, 2019. "Does the GDPR Enhance Consumers’ Control over Personal Data? An Analysis from a Behavioural Perspective," Journal of Consumer Policy, Springer, vol. 42(1), pages 91-107, March.
    2. Markus Spiekermann, 2019. "Data Marketplaces: Trends and Monetisation of Data Goods," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 54(4), pages 208-216, July.
    3. Ning Cai & Steven Kou, 2019. "Econometrics with Privacy Preservation," Operations Research, INFORMS, vol. 67(4), pages 905-926, July.
    4. Garrett A. Johnson & Scott K. Shriver & Shaoyin Du, 2020. "Consumer Privacy Choice in Online Advertising: Who Opts Out and at What Cost to Industry?," Marketing Science, INFORMS, vol. 39(1), pages 33-51, January.
    5. Philip Fei Wu & Jessica Vitak & Michael T. Zimmer, 2020. "A contextual approach to information privacy research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(4), pages 485-490, April.
    6. Frederik Zuiderveen Borgesius & Joost Poort, 2017. "Erratum to: Online Price Discrimination and EU Data Privacy Law," Journal of Consumer Policy, Springer, vol. 40(4), pages 521-521, December.
    7. Rajeev Kumar & Ram Gopal & Robert Garfinkel, 2010. "Freedom of Privacy: Anonymous Data Collection with Respondent-Defined Privacy Protection," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 471-481, August.
    8. Choi, Jay Pil & Jeon, Doh-Shin & Kim, Byung-Cheol, 2019. "Privacy and personal data collection with information externalities," Journal of Public Economics, Elsevier, vol. 173(C), pages 113-124.
    9. Velibor V. Miv{s}i'c & Georgia Perakis, 2019. "Data Analytics in Operations Management: A Review," Papers 1905.00556, arXiv.org.
    10. Ramon Casadesus-Masanell & Andres Hervas-Drane, 2015. "Competing with Privacy," Management Science, INFORMS, vol. 61(1), pages 229-246, January.
    11. Frederik Zuiderveen Borgesius & Joost Poort, 2017. "Online Price Discrimination and EU Data Privacy Law," Journal of Consumer Policy, Springer, vol. 40(3), pages 347-366, September.
    12. Shota Ichihashi, 2021. "Competing data intermediaries," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 515-537, September.
    13. Ghosh, Arpita & Roth, Aaron, 2015. "Selling privacy at auction," Games and Economic Behavior, Elsevier, vol. 91(C), pages 334-346.
    14. Inman, J. Jeffrey & Nikolova, Hristina, 2017. "Shopper-Facing Retail Technology: A Retailer Adoption Decision Framework Incorporating Shopper Attitudes and Privacy Concerns," Journal of Retailing, Elsevier, vol. 93(1), pages 7-28.
    15. Wu, Desheng & Baron, Opher & Berman, Oded, 2009. "Bargaining in competing supply chains with uncertainty," European Journal of Operational Research, Elsevier, vol. 197(2), pages 548-556, September.
    16. Zhang, Zhiming & Ren, Da & Lan, Yanfei & Yang, Shanxue, 2022. "Price competition and blockchain adoption in retailing markets," European Journal of Operational Research, Elsevier, vol. 300(2), pages 647-660.
    17. Tommaso Valletti & Jiahua Wu, 2020. "Consumer Profiling with Data Requirements: Structure and Policy Implications," Production and Operations Management, Production and Operations Management Society, vol. 29(2), pages 309-329, February.
    18. Florian Hoffmann & Roman Inderst & Marco Ottaviani, 2020. "Persuasion Through Selective Disclosure: Implications for Marketing, Campaigning, and Privacy Regulation," Management Science, INFORMS, vol. 66(11), pages 4958-4979, November.
    19. Vincent Conitzer & Curtis R. Taylor & Liad Wagman, 2012. "Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases," Marketing Science, INFORMS, vol. 31(2), pages 277-292, March.
    20. Rômy Bergman & Antragama Ewa Abbas & Sven Jung & Claudia Werker & Mark de Reuver, 2022. "Business model archetypes for data marketplaces in the automotive industry," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 747-765, June.
    21. Xu Guan & Ying-Ju Chen, 2017. "The Interplay between Information Acquisition and Quality Disclosure," Production and Operations Management, Production and Operations Management Society, vol. 26(3), pages 389-408, March.
    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. Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2022. "Data brokers co-opetition [The impact of big data on firm performance: an empirical investigation]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 820-839.
    2. Duan, Yongrui & Liu, Peng & Feng, Yixuan, 2022. "Pricing strategies of two-sided platforms considering privacy concerns," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    3. DELBONO Flavio & REGGIANI Carlo & SANDRINI Luca, 2021. "Strategic data sales to competing firms," JRC Working Papers on Digital Economy 2021-05, Joint Research Centre.
    4. Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
    5. Ichihashi, Shota, 2021. "The economics of data externalities," Journal of Economic Theory, Elsevier, vol. 196(C).
    6. Hufnagel, Gerrit & Schwaiger, Manfred & Weritz, Louisa, 2022. "Seeking the perfect price: Consumer responses to personalized price discrimination in e-commerce," Journal of Business Research, Elsevier, vol. 143(C), pages 346-365.
    7. Shuaicheng Liu, 2024. "Privacy regulation in asymmetric environments," Journal of Regulatory Economics, Springer, vol. 66(2), pages 157-173, December.
    8. Masuyama, Ryo, 2023. "Endogenous privacy and heterogeneous price sensitivity," MPRA Paper 117316, University Library of Munich, Germany.
    9. Conti, Chiara & Reverberi, Pierfrancesco, 2021. "Price discrimination and product quality under opt-in privacy regulation," Information Economics and Policy, Elsevier, vol. 55(C).
    10. Martin, Kelly D. & Kim, Jisu J. & Palmatier, Robert W. & Steinhoff, Lena & Stewart, David W. & Walker, Beth A. & Wang, Yonggui & Weaven, Scott K., 2020. "Data Privacy in Retail," Journal of Retailing, Elsevier, vol. 96(4), pages 474-489.
    11. Itay P. Fainmesser & Andrea Galeotti & Ruslan Momot, 2023. "Digital Privacy," Management Science, INFORMS, vol. 69(6), pages 3157-3173, June.
    12. Christian Niemeier & Richard Pospisil, 2021. "The Effects of User Tracking and Behavioral Management on Online Prices: A Theoretical Approach," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 386-398.
    13. Chongwoo Choe & Noriaki Matsushima & Shiva Shekhar, 2023. "The Bright Side of the GDPR: Welfare-Improving Privacy Management," CESifo Working Paper Series 10617, CESifo.
    14. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    15. Yassine Lefouili & Leonardo Madio & Ying Lei Toh, 2024. "Privacy Regulation and Quality‐Enhancing Innovation," Journal of Industrial Economics, Wiley Blackwell, vol. 72(2), pages 662-684, June.
    16. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    17. Lagerlöf, Johan N.M., 2023. "Surfing incognito: Welfare effects of anonymous shopping," International Journal of Industrial Organization, Elsevier, vol. 87(C).
    18. de Streel, Alexandre & Jacques, Florian, 2019. "Personalised pricing and EU law," 30th European Regional ITS Conference, Helsinki 2019 205221, International Telecommunications Society (ITS).
    19. Didier Laussel & Ngo Van Long & Joana Resende, 2023. "Profit Effects of Consumers’ Identity Management: A Dynamic Model," Management Science, INFORMS, vol. 69(6), pages 3602-3615, June.
    20. Andrei Hagiu & Julian Wright, 2023. "Data‐enabled learning, network effects, and competitive advantage," RAND Journal of Economics, RAND Corporation, vol. 54(4), pages 638-667, December.

    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:15:y:2023:i:4:p:3362-:d:1066088. 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.