The Privacy Calculus under Positive and Negative Mood States

Tawfiq Alashoor, Nader Al-Maidani, Ibrahim Al-Jabri

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


The privacy calculus has gained wide acceptance in the privacy literature. It is a parsimonious economic model that explains and predicts privacy-related decisions based on users' subjective calculus of the perceived privacy risks and perceived benefits. In this study, we focus on affect (i.e., positive and negative mood states) and its role in interrupting the privacy calculus. Based on a scenario-based experiment conducted among social media users, the results show that users' privacy calculus is biased depending on the mood state they exhibited. The positive effect of perceived benefits on disclosure likelihood was amplified (trivial) under a positive (negative) mood state, whereas the negative effect of perceived privacy risks on disclosure likelihood was trivial (amplified) under a positive (negative) mood state. Also, the construct of privacy concerns was incapable of predicting disclosure likelihood under both positive and negative mood states. We discuss the theoretical and practical implications of these findings.

Original languageEnglish
Title of host publicationProceedings of the 39th International Conference on Information Systems (ICIS)
Number of pages17
Place of PublicationAtlanta, GA
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Publication date2018
Article number1186
ISBN (Electronic)9780996683173
Publication statusPublished - 2018
Externally publishedYes
Event39th International Conference on Information Systems, ICIS 2018: Bridging the Internet of People, Data, and Things - San Francisco, United States
Duration: 13 Dec 201816 Dec 2018
Conference number: 39


Conference39th International Conference on Information Systems, ICIS 2018
Country/TerritoryUnited States
CitySan Francisco
Internet address
SeriesProceedings of the International Conference on Information Systems


  • Information privacy
  • Privacy calculus
  • Privacy paradox
  • Privacy concerns
  • Disclosure
  • Enhanced APCO model
  • Affect
  • Mood induction
  • Experiment
  • Social media

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