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Perception of Privacy and Willingness to Share Personal Data in the Smart Factory

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HCI for Cybersecurity, Privacy and Trust (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14045))

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Abstract

By optimising data-driven processes and improving automation, the digital transformation in production aims to increase effectiveness, efficiency and improve the working conditions of employees. In such a networked working environment, the performance and actions of workers need to be captured in form of digital data. However, the collection of personal data is a sensitive issue. More research, not only from a techno-centric but also from a human-centric perspective, is needed. Using a multi-method approach, this study examines the motives, barriers and acceptance of technologies that use personal data in a production context. A qualitative pre-study (\(n = 7\)) identified motives (e.g. data offering personal benefit) and barriers (e.g. privacy concerns) of personal data disclosure. In the subsequent quantitative main study (\(n = 152\)), these key elements were operationalised in a scenario-based online survey, and two different working scenarios – cobot and chatbot – were additionally assessed using the Technology Acceptance Model (TAM and UTAUT2). The results show: The more fun it is to use and the higher the expected performance, the higher the acceptance of technology using personal data. Trust in automation followed by expected effort were important. Views on the disclosure of personal data and the expected benefit to the organisation varied widely. Out of seven categories, work-related and demographic data were considered to be disclosable, while five categories were considered important to the organisation. The article concludes with actionable recommendations on how the collection and use of personal data can be well aligned with stakeholder interests.

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Acknowledgments

The authors would like to thank all the participants for sharing their personal views. We would also like to thank Lena Herrmann and Tim Schmeckel for their valuable research assistance. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC-2023 Internet of Production - 390621612.

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Authors and Affiliations

  1. Chair of Communication Science, RWTH Aachen University, Aachen, Germany

    Luisa Vervier, Philipp Brauner & Martina Ziefle

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  1. Luisa Vervier
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  2. Philipp Brauner
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  3. Martina Ziefle
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Correspondence to Philipp Brauner or Martina Ziefle .

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  1. San Jose State University, San Jose, CA, USA

    Abbas Moallem

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Vervier, L., Brauner, P., Ziefle, M. (2023). Perception of Privacy and Willingness to Share Personal Data in the Smart Factory. In: Moallem, A. (eds) HCI for Cybersecurity, Privacy and Trust. HCII 2023. Lecture Notes in Computer Science, vol 14045. Springer, Cham. https://doi.org/10.1007/978-3-031-35822-7_15

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  • DOI: https://doi.org/10.1007/978-3-031-35822-7_15

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