An Analysis of the Potential Influence of Privacy Risk on Neuroheadset Usage

Frederik M. Mayer, Duc T. Nguyen and Claus-Peter H. Ernst ()
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Frederik M. Mayer: Frankfurt University of Applied Sciences
Duc T. Nguyen: Frankfurt University of Applied Sciences
Claus-Peter H. Ernst: Frankfurt University of Applied Sciences

A chapter in The Drivers of Wearable Device Usage, 2016, pp 37-47 from Springer

Abstract: Abstract Neuroheadsets use electroencephalography (EEG) to record cognitive activity and some neuroheadsets are even capable of deciphering basic mental commands. As a result, users might believe there are privacy risks associated with these devices, which can hinder their usage. In this article, we postulate that Perceived Privacy Risk has both a direct negative influence on the Behavioral Intention to Use neuroheadsets and an indirect negative influence on the Behavioral Intention to Use neuroheadsets through Perceived Usefulness. After collecting 107 completed online questionnaires and applying a structural equation modeling approach, our findings indicate that neuroheadsets are at least partly utilitarian technologies whose usage is influenced by Perceived Usefulness. However, we were not able to confirm a significant influence of Perceived Privacy Risk on either the Behavioral Intention to Use neuroheadsets or their Perceived Usefulness. These findings suggest that neuroheadset manufacturers need to emphasize the instrumental benefits of their devices, but that they do not currently need to address people’s potential negative perceptions of neuroheadsets in terms of privacy risks.

Keywords: Behavioral Intention; Wearable Device; Average Variance Extract; Privacy Risk; Structural Equation Modeling Approach (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-319-30376-5_4

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DOI: 10.1007/978-3-319-30376-5_4

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