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DATA PRIVACY IN A SMART HOME: A stated choice experiment on the trade-off between data privacy and the benefits of smart home appliances on energy consumption.



Last Updated: 10-2020


Data privacy in smart homes is becoming a more sensitive topic due to the increasing number of smart appliances that are present in our homes. Research has shown that there is a large discrepancy in how individuals think about data privacy instead of how they act. This is called the privacy paradox. Consequently, it is unknown how data privacy will influence to implementation of these smart home appliances. This study aims to determine the trade-offs that individuals are willing to make between sharing privacy-sensitive data and the benefits of smart home appliances. With the use of a survey including a stated choice experiment, it is tested which attributes are having the biggest influence on the choice of an individual. It is found out that the trade-off is mainly determined by three attributes, the type of data that is processed, the reason why this data is processed, and the financial benefit that can be obtained by the smart home appliance. Individuals are showing less interest in the actor that is processing the data, the frequency of data processing, and the retention time (when is the data removed). Furthermore, it was found that individuals care more about the content that is shared rather than with whom the data is shared and for how long indicating that individuals with high concerns are narrowing their perception of these concerns by sharing fewer data. Individuals are also demanding a (theoretical) financial compensation for the privacy harm they experience. This research also confirmed the existence of the privacy paradox. Individuals with high concern about data privacy are more likely to choose a smart home appliance that processes the least amount of data while demanding financial compensation for the privacy harm they experience. Also, women are showing more privacy-protective behavior. The results of this research can be used to improve the knowledge of privacy behavior in the built environment. This research should be seen as a startup for more (privacy-specific) research. It is recommended to collect more academic evidence to make the conclusions of this research more useful in practice.

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