When WhatsApp changed its privacy policy: explaining WhatsApp discontinuation using an enablers-inhibitors' perspective

Abstract

PurposeThe purpose of this paper is to understand the factors that enable and inhibit WhatsApp users' discontinuance intention (DI) following the change in WhatsApp's privacy policy.Design/methodology/approachUsing the enabler-inhibitor model as a framework, a research model consisting of discontinuation enabler distrust (DT) and the DT's antecedents [(negative electronic word of mouth (NEWOM), negative offline word of mouth (NOWOM) and privacy invasion (PI)], discontinuation inhibitor inertia (INR) and INR's antecedents (affective commitment, switching cost and use habit) and moderator structural assurance was proposed and tested with data from 624 WhatsApp users using partial least square structure equational modeling (PLS-SEM).FindingsThe results show that DT created due to NEWOM and a sense of PI significantly impact DI. However, INR has no significant impact on DI. Structural assurance significantly moderates the relationship between DT and DI.Originality/valueThe paper collected data when many WhatsApp users switched to other platforms due to the change in WhatsApp's terms of service. The timing of data collection allowed for collecting the real impact of the sense of PI compared to other studies where the effect is hypothetically induced. Further, the authors acknowledge social media providers' efforts to address privacy criticism and regain users’ trust, an area that has received little attention in prior literature.

The effect of job and personal demands and resources on healthcare workers’ wellbeing: A cross-sectional study

“…Indicators were removed if the variance inflation factor was more than five, indicating collinearity or if the weight and the loading were insignificant. This analysis approach has been used extensively in healthcare [11,65] and other disciplines, such as information systems [66], tourism [67], education [68], and cybersecurity [69].…”