Mian Zhang

Ms. Mian Zhang


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 January 2024 in Social Indicators Research
Verified
Journal Article
Closed access
PDF file
Dezhi LiDezhi Li
Dezhi Li
XSXuyan Shang
Xuyan Shang
GHGuanying Huang
Guanying Huang
Shenghua ZhouShenghua Zhou
Shenghua Zhou
MZMian Zhang
Mian Zhang
Haibo FengHaibo Feng
Haibo Feng

7 January 2026 in Systems
Verified
Journal Article
Open access
PDF file
GHGuanying Huang
Guanying Huang
Dezhi LiDezhi Li
Dezhi Li
YWYang Wang
Yang Wang
LWLingxiao Wang
Lingxiao Wang
MZMian Zhang
Mian Zhang
HYHongzhe Yue
Hongzhe Yue
Citizen-centric smart city construction (SCC) has been the crucial mode for enhancing citizens’ well-being with rapid urbanization. While smart cities are constructed to improve urban operational safety, the concomitant low resilience of infrastructure, data breaches, and other issues also lead to physical, financial, and legal consequences, which therefore have the complicated the impact on citizens’ security perception of smart city construction (CSPSCC). To achieve sustainable smart city construction, it is important to clarify the influencing factors on CSPSCC. Although the enhancement of CSPSCC needs the joint efforts of citizens, government, and social organizations, the previous studies mostly focus on influencing factors from the single stakeholder. To address this gap, the theory of planned behavior was expanded to examine factors influencing CSPSCC from the perspective of participatory governance. Taking Nanjing as a case, hypotheses testing, mediating testing, and heterogeneity analysis were carried out for this theoretical model. The results show that the security governance of citizens, the government, and social organizations all had a positive impact on CSPSCC, with citizens’ behavioral intention being the most significant influencing factor. In addition, CSPSCC is also significantly affected by the citizens’ age, educational level, and usage frequency of smart city services.