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Will You Be Watching Me? A Conjoint-Based Study on Employee Attitudes Toward Personal Data Usage in Smart Factories.

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Title: Will You Be Watching Me? A Conjoint-Based Study on Employee Attitudes Toward Personal Data Usage in Smart Factories.
Authors: Keil, Maike (AUTHOR), Vervier, Luisa (AUTHOR), Brauner, Philipp (AUTHOR), Ziefle, Martina (AUTHOR)
Source: International Journal of Human-Computer Interaction. Aug2025, Vol. 41 Issue 16, p10024-10044. 21p.
Subjects: Employee attitudes, Data privacy, Communication strategies, Cyber physical systems, Conjoint analysis, Personally identifiable information
Abstract: The rapid transformation of the industrial sector requires strategies to integrate digitalization and monitoring. While these advancements promote data-driven optimization of manufacturing processes, they raise concerns regarding employee data privacy. This study shifts the focus from the prevalent technological perspective to the perspectives of employees, critically examining the factors influencing their willingness to share data. Employing a Choice-Based Conjoint Analysis with n = 132 participants, our research suggests a strong preference for exclusive control over access to personal data, particularly health-related information, indicating that privacy concerns typically eclipse the advantages offered by data sharing in the workplace. Using latent class analysis, we distinguish between two employee groups characterized by distinct privacy attitudes: "Data Protectors" and "Team Players." These findings underline the need to further investigate the influence of employee diversity, including demographics, attitudes, and job functions, to effectively optimize communication strategies and address diverse privacy expectations. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Will You Be Watching Me? A Conjoint-Based Study on Employee Attitudes Toward Personal Data Usage in Smart Factories.
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  Data: <searchLink fieldCode="AR" term="%22Keil%2C+Maike%22">Keil, Maike</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vervier%2C+Luisa%22">Vervier, Luisa</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Brauner%2C+Philipp%22">Brauner, Philipp</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ziefle%2C+Martina%22">Ziefle, Martina</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Aug2025, Vol. 41 Issue 16, p10024-10044. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Employee+attitudes%22">Employee attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Data+privacy%22">Data privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+strategies%22">Communication strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Cyber+physical+systems%22">Cyber physical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Conjoint+analysis%22">Conjoint analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Personally+identifiable+information%22">Personally identifiable information</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The rapid transformation of the industrial sector requires strategies to integrate digitalization and monitoring. While these advancements promote data-driven optimization of manufacturing processes, they raise concerns regarding employee data privacy. This study shifts the focus from the prevalent technological perspective to the perspectives of employees, critically examining the factors influencing their willingness to share data. Employing a Choice-Based Conjoint Analysis with n = 132 participants, our research suggests a strong preference for exclusive control over access to personal data, particularly health-related information, indicating that privacy concerns typically eclipse the advantages offered by data sharing in the workplace. Using latent class analysis, we distinguish between two employee groups characterized by distinct privacy attitudes: "Data Protectors" and "Team Players." These findings underline the need to further investigate the influence of employee diversity, including demographics, attitudes, and job functions, to effectively optimize communication strategies and address diverse privacy expectations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/10447318.2024.2430494
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        Text: English
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      – SubjectFull: Communication strategies
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              Text: Aug2025
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