Exploring the Effects of the Privacy‐Handling Management Styles of Social Networking Sites on User Satisfaction: A Conflict Management Perspective

Abstract

The issue of consumer information privacy, arguably the most substantial and persistent problem confronting e‐commerce companies in general and online social networking service providers in particular, often results in unsatisfied customers. Researchers have investigated privacy from various perspectives and in a multitude of settings, yet there have been few attempts to understand privacy versus satisfaction, particularly from the perspective of conflict management. Because users’ privacy can be negatively affected by social networking sites (SNSs), this study focuses on the privacy conflicts between SNSs and their users. Drawing on conflict management theory, this article investigates the effects of different conflict management styles exhibited by an SNS on users’ satisfaction with its privacy practices, which then affects their intention to disclose personal information. The SNS examined in this study is Facebook, the most popular SNS with the largest number of users. Data were collected using an online survey and were analyzed using structural equation modeling. The results suggest that the two cooperative conflict management styles demonstrated by the SNS—accommodating and problem‐solving—positively affect users’ satisfaction with the privacy practices of the SNS both directly and indirectly through perceived privacy risk control. With regard to uncooperative styles, an avoiding style negatively affects user satisfaction directly, whereas an asserting style negatively affects user satisfaction indirectly through perceived privacy risk. The results also support that satisfaction is positively related to intention; users who are satisfied with the privacy practices of SNSs are more willing to disclose personal information than unsatisfied ones.

Understanding employees' adoption of the Bring-Your-Own-Device (BYOD): the roles of information security-related conflict and fatigue

“…Future studies could further explore the strategies for conflict resolution. For example, Zhang et al (2017) proposed four types of conflict management strategies: problem-solving, accommodating, asserting and avoiding. The authors confirmed the effects of these strategies on privacy issues in the context of SNS.…”

“…In this research, information security–related conflicts are defined as the stimuli that affect internal states. “Conflict” describes a process in which one party perceives that its interests are being opposed or negatively affected by another party (Zhang et al , 2017). Conflict arises among interdependent parties that perceive incompatible interests or goals when they interact.…”

E-waste information security protection motivation: the role of optimism bias

“…financial, social, performance and prosecution risks) to be lower. Zhang et al (2018) also suggested that people with high optimism bias may believe they have greater control over the outcome, therefore, they perceive low privacy risks. Applied here we postulate that e-waste owners high in optimism bias may under-weigh information risks; even if the risk is judged to be high, it will not influence coping intentions as the risk will only marginally be integrated into one's mental calculus.…”

Analyzing Social Media Research: A Data Quality and Research Reproducibility Perspective

“…Nowadays, both primary survey data and secondary data directly crawled from social networking sites have been used by the researchers. Both Chakraborty et al (2013) and Zhang et al (2017) studied social media users’ behavioral responses related to privacy issues of the users. Chakraborty et al (2013) used data from Facebook pages of profiles of elderly adults to study their privacy-preserving actions.…”

“…Chakraborty et al (2013) used data from Facebook pages of profiles of elderly adults to study their privacy-preserving actions. Zhang et al (2017), on the other hand, used data from the online surveys of respondents who use social networking sites. Amazon Mechanical Turk was used to recruit respondents (social media users).…”