Research on the mechanism of residents’ data disclosure intention in the context of smart cities

Purpose This study investigates the factors influencing residents’ willingness to disclose personal data in the context of smart city services. While smart urban development has become essential for modern city governance, the issue of personal privacy leakage has intensified. Existing research has rarely examined users’ disclosure intentions systematically within this context. Design/methodology/approach Grounded in the stimulus-organism-response (S-O-R) theoretical framework, this study develops a structural equation model to explore how various external and internal factors affect users’ data disclosure intentions. A survey was conducted among residents of a representative smart city in China, and data were analyzed using covariance-based SEM. Findings The results reveal that perceived risk has no significant effect on users’ data disclosure intention, contrary to conventional assumptions. Instead, perceived social equity and perceived data value are the key predictors of disclosure willingness, with social equity being the most influential. Additionally, data-driven decision transparency does not affect perceived risk but significantly enhances perceived data value and social equity. Smart service quality positively influences all three organism-level variables, with the strongest effect on data value, while government support only impacts perceived risk. Originality/value This research offers novel insights by demonstrating that perceived risk may not be a decisive factor in smart city data disclosure contexts. It challenges prior assumptions and contributes to a more accurate understanding of user behavior. The findings provide actionable implications for the design and governance of smart city services, emphasizing the importance of promoting fairness and value perception rather than solely focusing on risk mitigation.