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Your privacy for a discount? Exploring the willingness to share personal data for personalized offers

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  • Alfnes, Frode
  • Wasenden, Ole Christian

Abstract

This paper explores how willing consumers are to share personal data to receive personalized offers on their mobile (cell in the US) phones using nationwide surveys of mobile users, 16–35 years old, in Norway, Serbia, Malaysia, and Pakistan. We ask respondents about the likelihood they would use three types of personalized advertising services delivered through their mobile operator, with services varying with respect to the level of personal data collected and whether shared with third parties. In all four countries, respondents state that their likelihood of using a personalized ad service decreases when the service uses more personal data or shares the data with third parties. Using a split sample design, we find that introducing a 10% discount on mobile subscriptions for those using the ad service increases the stated likelihood of using the service. We find significant differences in willingness to share personal data attitudes between countries, with respondents in high-income Norway being least willing and those in low-income Pakistan most willing to share personal data. We identify only minor differences between respondents in Serbia and Malaysia, middle-income countries in Europe and Asia. The study contributes to the literature on the willingness to share personal data by including young adult respondents from countries in both Europe and Asia. Furthermore, framing the survey questions in a mobile service context is appreciably closer to telecom reality than most existing experimental studies on sharing of personal data.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:telpol:v:46:y:2022:i:7:s030859612200012x
    DOI: 10.1016/j.telpol.2022.102308
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    References listed on IDEAS

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    Cited by:

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    2. Hyojin Park & Hyeontaek Oh & Jun Kyun Choi, 2023. "A Profit Maximization Model for Data Consumers with Data Providers’ Incentives in Personal Data Trading Market," Data, MDPI, vol. 9(1), pages 1-21, December.
    3. Urbonavicius, Sigitas, 2023. "Relative power of online buyers in regard to a store: How it encourages them to disclose their personal data?," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    4. 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).

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    More about this item

    Keywords

    Personal data; Preference elicitation; Data privacy; Mobile (cell) phone services;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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