Developing an E-commerce trust model in crowdfunding by integrating blockchain and edge computing using fuzzy technique
نویسندگان
1 Faculty of Business Administration, Memorial University of Newfoundland, St. John’s, NL, Canada.
2 Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran.
3 Department of Mathematics, Semnan University, Semnan, Iran.
4 Department of Entrepreneurship, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
doi
10.22105/jfea.2025.481202.1654چکیده
This study investigates the integration of blockchain and edge computing technologies to enhance E-commerce trust in crowdfunding platforms using fuzzy techniques. The research focuses on five key dimensions of trust: Security, Transparency, Efficiency, Social Trust, and Technical Capabilities. By applying Multi-Criteria Decision-Making (MCDM) methodologies, including FUCOM, IDOCRIW, and F-CoCoSo, the study evaluates solutions designed to address trust-related challenges in crowdfunding. A comprehensive case study of Iranian crowdfunding platforms was conducted to empirically validate these solutions using fuzzy logic and advanced MCDM techniques. The study's key innovation lies in the development of a novel trust framework that combines blockchain and edge computing technologies with advanced fuzzy-based MCDM methods. This framework uniquely addresses the challenges of transparency, fraud prevention, and real-time auditing in crowdfunding ecosystems while providing a scalable and decentralized approach to enhancing trust. The findings highlight three primary solutions for reinforcing trust: S4 (Implementing a Blockchain-Based Auditing and Monitoring System), S2 (Implementing a Decentralized User Verification System), and S6 (Enhanced Security with Blockchain and Edge Computing Synergy). These solutions provide significant improvements in real-time auditing, user verification, and system security, ensuring enhanced transparency, fraud prevention, and performance. Additionally, the study incorporates sensitivity analysis using techniques such as F-MARCOS, F-SECA, F-KEMIRA, and F-MABAC to evaluate the robustness of the findings. The analysis demonstrates that the proposed solutions remain stable across varying decision-making scenarios, confirming their reliability and effectiveness. This research advances the theoretical understanding of trust in E-commerce by integrating blockchain and edge computing, offering a scalable, efficient, and secure model for crowdfunding platforms. The results suggest that these solutions are crucial for fostering a more transparent, reliable, and trustworthy digital financial environment, contributing to the sustainable growth of the crowdfunding industry. The study's implications extend to both academic theory and practical applications, providing a roadmap for future developments in digital trust frameworks.