Privacy Concerns, Perceived Privacy Control, and Trust in Google Digital Services: Evidence on Continued Use Intention among Young Users in Bangladesh

Abstract

The expansion of Google digital services and the growing integration of generative artificial intelligence have intensified the importance of privacy, user control, and trust in digital-service relationships. This study examines whether privacy concern and perceived privacy control are associated with trust in Google digital services and whether these perceptions, together with trust, explain users’ intention to continue using Google/Gemini services in Bangladesh. Drawing on Privacy Calculus Theory and Trust Theory, the study develops a model in which privacy concern is expected to reduce trust, perceived privacy control is expected to strengthen trust, and trust is expected to increase continued-use intention. A quantitative, cross-sectional survey design was applied to the Group 2 Google master dataset. After screening, 385 complete cases were retained, with all retained respondents satisfying the attention-check criterion. Three-item measures captured privacy concern, perceived privacy control, trust, and continued-use intention using a five-point Likert scale. Composite-score regressions with bootstrap inference were used to reproduce the planned SEM/PLSSEM-oriented structural assessment. The results indicate that perceived privacy control positively predicts trust (β = .167, p = .001), whereas privacy concern does not have a statistically significant effect on trust (β = .080, p = .114). Trust is a substantial positive predictor of continued-use intention (β = .347, p < .001), and perceived privacy control also has a positive direct association with continued use (β = .129, p = .007). Privacy concern does not significantly predict continued use (β = .058, p = .217). Bootstrap mediation indicates a significant indirect effect of perceived privacy control through trust, while the privacy-concern indirect effect is not statistically distinguishable from zero. The findings suggest that users’ perceived ability to understand and manage privacy settings may be more consequential for trust and continued use than generalized privacy concern alone. The study contributes Bangladesh-specific evidence to privacy-calculus and trust research and offers practical implications for Google and other digital-service providers seeking to strengthen transparency, user control, and durable trust in the generative-AI era.