a comparative analysis of traditional and blockchain-based process mining: a food supply chain case study

This paper investigates the integration of blockchain technology into process mining, a powerful data analysis technique. by applying the design science research methodology, we compared traditional process mining methods with blockchain-based approaches, focusing on a food supply chain case study. the goal was to assess the efficiency and effectiveness of both methods in improving supply chain transparency, security, and data integrity. we implemented a process on the ethereum blockchain platform and conducted process mining both with and without blockchain data. the results revealed that blockchain-based process mining yielded a higher matching rate with the initial model (85% vs. 74%), indicating improved data quality and process accuracy. this enhancement is attributed to blockchain s inherent immutability and security features. our findings suggest that blockchain can be effectively employed to store and analyze process data, leading to more reliable and trustworthy process models. this integration offers the potential to revolutionize process mining by providing a robust and secure framework for data-driven decision-making in various industries.