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Unpacking the intention-behavior gap in privacy decision making for the internet of things (IoT) using aspect listing

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Abstract

Previous studies have observed an intention-behavior gap that has been labeled the “privacy paradox”: people disclose personal information (behavior) despite expressing negative sharing intentions (in surveys). However, this phenomenon has not been studied in the Internet of Things (IoT) in which users’ personal information sharing is crucial for the functionality of the technology. We explore this phenomenon by comparing participants’ intentions (via a survey) with their actual behavior (via a privacy-setting interface) and controlling the data sharing device and storage. Furthermore, we explore the decision processes underlying these privacy decisions by measuring and manipulating these processes using an aspect listing task. We find a reversed intention-behavior gap in IoT: participants disclosed less (rather than more) information in the behavior condition than in the intention condition, an effect that was associated with fewer benefits than risk aspects listed in the behavior condition. The number and type of aspects listed fully mediated the effect of decision type (intention versus behavior) on the decision, which suggests that a risk-benefit calculation guided the privacy decision-making. Moreover, this reversed intention-behavior gap vanishes if we specifically ask participants to think about positive and negative aspects of the decision, as this allows them to consider both risks and benefits, irrespective of decision type.
Original languageEnglish
Article number101924
Number of pages18
JournalComputers and Security
Volume97
DOIs
Publication statusPublished - Oct 2020

Funding

This work was supported by the Netherlands Organization for Scientific Research (NWO) project 628.001.027, the US National Science Foundation (NSF) award no. 1640664 “Using Process Tracing to Improve Household IoT Users’ Privacy Decisions”, and Samsung Research America. We thank Paritosh Bahirat and Yangyang He for the discussion on the paper. We thank Lars Middel, Pepijn Schnitzeler, Ken Geelhoed, Juliët van Gent, Anouk van Kasteren and Raghav Mohan for their help in setting up to the studies and data collection. This work was supported by the Netherlands Organization for Scientific Research ( NWO ) project 628.001.027 , the US National Science Foundation (NSF) award no. 1640664 “Using Process Tracing to Improve Household IoT Users’ Privacy Decisions”, and Samsung Research America. We thank Paritosh Bahirat and Yangyang He for the discussion on the paper. We thank Lars Middel, Pepijn Schnitzeler, Ken Geelhoed, Juliët van Gent, Anouk van Kasteren and Raghav Mohan for their help in setting up to the studies and data collection.

FundersFunder number
Samsung Research America
National Science Foundation1640664
Nederlandse Organisatie voor Wetenschappelijk Onderzoek628.001.027

    Keywords

    • Decision-making
    • Internet of things
    • Privacy paradox
    • Process-tracing
    • Risk-benefit calculation

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