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.

Ecology-oriented development (EOD) projects integrate ecological governance with revenue-generating industries, but their financial feasibility evaluation and resource balancing depend heavily on expert judgment. This study develops a decision-support method combining case-based reasoning (CBR) and machine learning (ML) to support the systematic reuse of historical project experience. A standardized case representation framework and an EOD case database were established. Gradient boosting decision trees (GBDT) were then used to determine predictive-importance weights, support weighted similarity calculation, and predict key financial indicators, while CBR linked retrieved case information to project-specific recommendations through experience transfer and adaptation. The method was applied to the Xibei Canal EOD project in Wuxi, China. The three most similar historical cases achieved similarities of 91.02%, 90.26%, and 89.52%, respectively, providing complementary references for financing arrangements and industrial cross-subsidization of the Xibei Canal EOD project. GBDT achieved R² values of approximately 0.87, 0.97, 0.93, and 0.97 for predicting financial internal rate of return (FIRR), financial net present value (FNPV), payback time (Pt), and debt service coverage ratio (DSCR), respectively, providing quantitative support for scheme evaluation. Threshold sensitivity analysis further clarified the scope of reuse-eligible cases and the corresponding adaptation requirements under different screening conditions. The proposed method provides structured, quantitative, and traceable support for EOD project screening, preliminary financial assessment, resource balancing, and scheme comparison.