Abstract

PurposeOnline social networks (OSNs) provide users with mechanisms such as social circles and individual selection to define the audiences (i.e., privacy policy) of the shared information. This privacy decision-making process is a hard and tedious task for users because they have to assess the cost-benefit in a complex environment. Moreover, little is known about how users assess the cost-benefit of matching the elements of online communication and their interests. Therefore, the purpose of this paper is to develop and test a research model to understand the impact that the types of receivers and the sensitivity of messages have on privacy decisions.Design/methodology/approachA study was conducted to understand how users evaluate the cost-benefit of the disclosure action in online social networks for the different types of receivers identified and the sensitivity of the message. Data from 400 respondents was collected and analyzed using partial least squares modeling.FindingsThe findings of this study demonstrated a trade-off variance between the perceived cost-benefit and the disclosure of sensitive information with different receiver types. Disclosing personal information with trusted receivers, influencer receivers and receivers from the circle of coworkers had a positive significant effect on social capital building. Conversely, disclosing personal information with receivers from the circle of family or unknown receivers had a significant negative effect on social capital building and even a significant positive effect on privacy concerns.Originality/valueRecent literature has documented the increasing interest of the research community in understanding users' concerns and interests in making the most suitable privacy decisions. However, most researchers have worked on understanding the disclosure action from a user-centered perspective and have not considered all of the elements of online communication. This study puts the focus on all of the elements of communication during disclosure actions, taking into account the properties of the message and receivers and the impact on users' cost benefit value.

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