IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p10110-d1524763.html
   My bibliography  Save this article

Personal Data Management in Smart Product-Service Systems: Preliminary Design Strategies to Avoid User Manipulation in Democratic Processes

Author

Listed:
  • Alessandra C. Canfield Petrecca

    (LeNSlab Polimi, Department of Design, Politecnico di Milano, 20158 Milan, Italy
    Design for Sustainability Research Group, Brunel Design School, College of Engineering, Design and Physical Sciences, Brunel University of London, London UB8 3PH, UK)

  • Carlo Vezzoli

    (LeNSlab Polimi, Department of Design, Politecnico di Milano, 20158 Milan, Italy)

  • Fabrizio Ceschin

    (Design for Sustainability Research Group, Brunel Design School, College of Engineering, Design and Physical Sciences, Brunel University of London, London UB8 3PH, UK)

Abstract

The use of digital technologies in Product Service Systems (PSSs) has increased in recent years. More and more smart devices are used in these models, collecting significant amounts of data to provide personalized and responsive products and services. However, data extraction has been causing disruptions in the social sphere, manipulating users, threatening democratic processes, and harming the social dimension of sustainability. To mitigate these problems associated with user data, some solutions on the market claim to take a more ethical approach. This article presents the preliminary results of a study aiming to understand what features in these solutions may favour the resilience of democratic processes and reduction in user manipulation due to personal data extraction and personalized activity. It also examines how designers can use them to develop smart PSSs that incorporate these elements and features in their process. Based on a literature review, three key elements relevant to personal data and democracy were assessed and applied to analyze 30 cases. The results provided a preliminary list of 46 features and 15 strategies for designers to embed these elements in the design of smart PSSs, as well as a conceptual framework. The study concludes with recommendations for future research.

Suggested Citation

  • Alessandra C. Canfield Petrecca & Carlo Vezzoli & Fabrizio Ceschin, 2024. "Personal Data Management in Smart Product-Service Systems: Preliminary Design Strategies to Avoid User Manipulation in Democratic Processes," Sustainability, MDPI, vol. 16(22), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:10110-:d:1524763
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/10110/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/22/10110/
    Download Restriction: no
    ---><---

    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:16:y:2024:i:22:p:10110-:d:1524763. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.