Research on trusted closed loop management of the whole process of service evaluation based on blockchain

Abstract

Conventional service evaluation systems are increasingly plagued by data opacity, susceptibility to tampering, and delayed feedback loops, which erode stakeholder trust and hinder effective quality governance. To address these critical challenges, this study proposes and empirically validates a blockchain-enabled framework for trusted closed-loop management of the entire service evaluation process. The proposed architecture synergizes distributed ledger technology, autonomous smart contracts, and a dynamic Bayesian trust scoring model to achieve real-time data verification, automated corrective feedback, and adaptive trust computation. We analyzed a comprehensive dataset of 1,200 service interactions across the hospitality, healthcare, and e-commerce sectors, characterized by customer satisfaction scores ranging from 5.1 to 9.8, reliability indices between 0.72 and 0.96, and normalized positive interaction frequencies from 0.42 to 0.89. Empirical results demonstrate that the integration of the blockchain framework significantly elevated mean trust scores from 0.71 (± 0.12) to 0.88 (± 0.09), representing a statistically significant 23.7% improvement. Furthermore, the system reduced the variance in satisfaction ratings by 0.48 and lowered overall service discrepancy rates by up to 15.4%. Sector-specific dynamic weight adjustments yielded optimized outcomes, including a 7.4% increase in reliability for healthcare and a 6.3% improvement in consistency for hospitality. Comparative analysis reveals that while conventional digital evaluation systems typically achieve only 5–12% performance gains, our blockchain-based approach substantially enhances trust, accuracy, and process transparency. Crucially, the closed-loop mechanism facilitated timely interventions, reducing critical service deviations by 17.5% in healthcare and 15.4% in e-commerce. These findings offer robust theoretical validation and practical guidelines for deploying transparent, accountable, and adaptive service evaluation ecosystems in diverse industrial contexts.