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Impact of privacy concerns on resistance to smart services: does the ‘Big Brother effect’ matter?

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  • Zied Mani

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

  • Inès Chouk

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

Abstract

The aim of this study is to provide a better understanding of the factors that explain consumer resistance to smart services from a privacy perspective. To this end, an exploratory qualitative study and a quantitative study were carried out. 653 French consumers answered an online questionnaire regarding smart services in the banking sector. Structural equation modelling was used to test the conceptual model. The findings show that information privacy, the unauthorised secondary use of personal information and perceived intrusion have an impact on consumer resistance to smart services. Moreover, our research highlights the major role of the ‘Big Brother effect' as an antecedent to these various privacy concerns.

Suggested Citation

  • Zied Mani & Inès Chouk, 2019. "Impact of privacy concerns on resistance to smart services: does the ‘Big Brother effect’ matter?," Post-Print hal-03217977, HAL.
    • Handle: RePEc:hal:journl:hal-03217977
    DOI: 10.1080/0267257X.2019.1667856
    Note: View the original document on HAL open archive server: https://hal.science/hal-03217977
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    References listed on IDEAS

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    1. Ellen M. Hufnagel & Christopher Conca, 1994. "User Response Data: The Potential for Errors and Biases," Information Systems Research, INFORMS, vol. 5(1), pages 48-73, March.
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    Cited by:

    1. Sanjit K. Roy & Gaganpreet Singh & Corey Hatton & Bidit Dey & Nisreen Ameen & Satish Kumar, 2023. "Customers’ motives to co-create in smart services interactions," Electronic Commerce Research, Springer, vol. 23(3), pages 1367-1400, September.
    2. Yuho Shimizu & Aimi Ishizuna & Shin Osaki & Takaaki Hashimoto & Mitsuharu Tai & Tetsushi Tanibe & Kaori Karasawa, 2022. "The Social Acceptance of Smart Health Services in Japan," IJERPH, MDPI, vol. 19(3), pages 1-11, January.
    3. Liu, Yu-li & Yan, Wenjia & Hu, Bo, 2021. "Resistance to facial recognition payment in China: The influence of privacy-related factors," Telecommunications Policy, Elsevier, vol. 45(5).
    4. Fu, Shihui & Xue, Kunkun & Yang, Mengya & Wang, Xiaona, 2023. "An exploratory study on users' resistance to mobile app updates: Using netnography and fsQCA," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    5. Querci, Ilaria & Monsurrò, Luigi & Peverini, Paolo, 2024. "When anthropomorphism backfires: Anticipation of negative social roles as a source of resistance to smart object adoption," Technovation, Elsevier, vol. 132(C).
    6. Lucia-Palacios, Laura & Pérez-López, Raúl, 2021. "Effects of Home Voice Assistants' Autonomy on Instrusiveness and Usefulness: Direct, Indirect, and Moderating Effects of Interactivity," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 41-54.
    7. Souka, Mohamed & Bilstein, Nicola & Decker, Reinhold, 2024. "Give me your data and I’ll dress you: A two-sided messaging approach to address privacy concerns surrounding in-store technologies," Journal of Business Research, Elsevier, vol. 172(C).

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