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The upside of data privacy – delighting customers by implementing data privacy measures

Author

Listed:
  • Henner Gimpel

    (University of Augsburg)

  • Dominikus Kleindienst

    (University of Augsburg)

  • Niclas Nüske

    (University of Augsburg)

  • Daniel Rau

    (University of Augsburg)

  • Fabian Schmied

    (University of Augsburg)

Abstract

The targeted analysis of customer data becomes increasingly important for data-driven business models. At the same time, the customers’ concerns regarding data privacy have to be addressed properly. Existing research mostly describes data privacy as a necessary evil for compliance and risk management and does not propose specific data privacy measures which address the customers’ concerns. We therefore aim to shed light on the upside of data privacy. In this paper, we derive specific measures to deal with customers’ data privacy concerns based on academic literature, legislative texts, corporate privacy statements, and expert interviews. Next, we leverage the Kano model and data from two internet-based surveys to analyze the measures’ evaluation by customers. From a customer perspective, the implementation of the majority of measures is obligatory as those measures are considered as basic needs of must-be quality. However, delighting measures of attractive quality do exist and have the potential to create a competitive advantage. In this, we find some variation across different industries suggesting that corporations aiming to improve customer satisfaction by superior privacy protection should elicit the demands of their specific target customers.

Suggested Citation

  • Henner Gimpel & Dominikus Kleindienst & Niclas Nüske & Daniel Rau & Fabian Schmied, 2018. "The upside of data privacy – delighting customers by implementing data privacy measures," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(4), pages 437-452, November.
  • Handle: RePEc:spr:elmark:v:28:y:2018:i:4:d:10.1007_s12525-018-0296-3
    DOI: 10.1007/s12525-018-0296-3
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    References listed on IDEAS

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    Cited by:

    1. Trabucchi, Daniel & Patrucco, Andrea S. & Buganza, Tommaso & Marzi, Giacomo, 2023. "Is transparency the new green? How business model transparency influences digital service adoption," Technovation, Elsevier, vol. 126(C).
    2. Annette Wenninger & Daniel Rau & Maximilian Röglinger, 2022. "Improving customer satisfaction in proactive service design," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1399-1418, September.
    3. Jan Hendrik Betzing & Matthias Tietz & Jan Brocke & Jörg Becker, 2020. "The impact of transparency on mobile privacy decision making," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(3), pages 607-625, September.
    4. Pia Münster & Barbara Grabkowsky, 2023. "Kano Model Analysis of Digital On-Farm Technologies for Climate Adaptation and Mitigation in Livestock Farming," Sustainability, MDPI, vol. 16(1), pages 1-14, December.
    5. Barbara Dinter & Jan Krämer, 2018. "Data-driven innovations in electronic markets," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(4), pages 403-405, November.
    6. Wei Liu & Zongshui Wang & Hong Zhao, 2020. "Comparative study of customer relationship management research from East Asia, North America and Europe: A bibliometric overview," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 735-757, December.

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    More about this item

    Keywords

    Privacy concerns; Privacy measures; Customer data; Customer satisfaction; Survey research;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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