Disclosure Determinants of Blockchain Crowdfunding Performance for Sustainable Smart City Financing: An Explainable Optuna-Optimized Machine Learning Approach

Abstract

Smart cities present a transformative paradigm for urban development, yet securing sustainable financing remains a critical challenge. While traditional funding mechanisms struggle with scalability limitations, FinTech innovations like Initial Coin Offerings (ICOs) have emerged as a viable alternative. Leveraging blockchain technology, ICOs enable decentralized capital raising through token sales, offering transparency and global investor access. However, their effectiveness is compromised by market volatility, information asymmetry, and the absence of reliable predictive frameworks. This study addresses these limitations by developing an explainable hybrid machine learning model that combines: (1) Light Gradient Boosting Machine (LGBM) for efficient feature selection through histogram-based learning, (2) Optuna-optimized Extremely Randomized Trees regression that mitigates overfitting via enhanced randomization while excelling with noisy financial data, and (3) interpretability tools including SHAP values and feature importance analysis. Optuna's automated hyperparameter optimization further enhances computational efficiency, enabling robust predictions of post-ICO returns. The proposed model demonstrates superior predictive performance (R²=0.814, MSE=0.005, MAE=0.051), significantly outperforming both linear regression and state-of-the-art ML models. Key findings identify token supply (63% predictive power) as negatively correlated with returns - reflecting dilution effects and investor perceptions of scarcity- while fundraising success (15%) and Bitcoin returns (8%) show positive influences. These results provide practical guidance for investors and regulators, while establishing ICOs as a potential sustainable financing mechanism for smart city initiatives. The study contributes both methodologically through its optimized hybrid architecture and practically by enhancing decision-making in blockchain-based urban development financing.