Analysis of Public Administration Procurement and Expenditures Related to Energy Efficiency Improvements

Administrative law governs the interactions between public authorities and private entities, including the rules for awarding public contracts. Public procurement law, a subset of administrative law, regulates the procedures for public tenders to ensure transparency, competition, and equal treatment. Public tenders, as a core mechanism for resource allocation and procurement of goods and services by governments and public institutions, play a critical role in fostering transparency, efficiency, and fairness within procurement processes. In this context, ensuring and enhancing procurement processes’ transparency, efficiency, and compliance remains a significant challenge. Informatics in the legal domain offers promising solutions, addressing key aspects such as data management and transparency through data standardisation, interoperability, and protection; automation and AI for decision-making, including tools to evaluate bids or predict contract risks; fraud detection and compliance through data mining, machine learning and process mining to uncover irregularities or prevent corruption; and legal text analysis to automate the processing of legal documents. This thesis tackles these open research problems by proposing an integrated approach that leverages advanced computational techniques to address these challenges effectively. To investigate the analysis of the public administration procurement process and expenditures related to energy efficiency improvements, the thesis focuses on leveraging national datasets, such as those provided by the National Anti-Corruption Authority and the Italian Administrative Justice. By integrating these datasets, the thesis establishes a structured analytical approach that enables the application of machine learning techniques to identify patterns and factors associated with complaints. A relevant perspective concerns the construction of predictive models in the public procurement domain. The resulting models support proactive risk management and enhance transparency in public procurement processes, addressing critical challenges in this area. To investigate green and energy issues, it has been considered important to focus attention on the broader analysis of issues related to public tenders, among which relevant sustainability issues concern the areas of healthcare, renewable energy, and expenditures on services and works of public agencies. The thesis also employs process mining techniques to analyse procurement workflows, leveraging data from the Tenders Electronic Daily dataset alongside