This article examines how Italian manufacturing firms align with the United Nations Sustainable Development Goals (SDGs) in their online communication. We analyze a novel dataset that combines financial information from 9464 Italian firms with website content archived by the Wayback Machine (2018–2023), applying natural language processing techniques to identify and measure SDG-related discourse. Using fixed-effects regression and propensity score matching, we estimate the relationship between SDG-related website discourse and firm performance. Findings are mixed: discourse related to gender equality (SDG 5) is consistently positively correlated with sales, while other relationships are not robust to alternative model specifications. The study contributes to corporate sustainability research by introducing a web-based approach to track firms’ alignment with global sustainability priorities as expressed in online communication. Overall, the evidence indicates that Italian manufacturers increasingly incorporate SDG-related language into their website communication, but the estimated associations between this online disclosure and firm performance vary considerably across specific goals and firm characteristics.
This paper investigates the transformative potential of AI-based real-time crowding information in shaping travel behaviour, passenger well-being, and environmentally sustainable choices in rail transport—addressing both technological innovation and its socio-economic impacts. Drawing on original stated-preference data from the capacity-constrained “Cinque Terre” railway corridor in Italy, we integrate behavioural indicators with a discrete choice experiment to examine how passengers respond to AI-generated predictions of crowding, delays, fares, and information sources. Our results demonstrate that exposure to such AI-driven information significantly increases passengers’ propensity to adjust departure times and opt for less crowded, lower-emission services. The analysis reveals a substantial willingness to incur delays or monetary costs to avoid severe crowding, highlighting the critical disutility of peak-period congestion. These findings suggest that AI-based information systems can serve as effective demand management tools, delivering well-being gains while supporting sustainable mobility and decarbonisation strategies.
Geopolitical uncertainty has become an increasingly important driver of financial market dynamics. This study examines the relationship between the Geopolitical Risk Index (GPR) and sectoral stock market volatility in Italy over the period 2008–2024 using a two-stage empirical approach. Wavelet coherence analysis is employed to investigate time- and frequency-varying co-movements between geopolitical risk and sectoral volatility, while a Time-Varying Parameter Vector Autoregression (TVP-VAR) model is used to assess dynamic spillover effects between the GPR and major Italian stock market sectors. The results show substantial heterogeneity across sectors and periods. Overall, the evidence suggests that geopolitical uncertainty is associated with changes in sectoral interconnectedness and volatility transmission, with the industrial and financial sectors emerging as net transmitters and the energy and automotive sectors as net receivers of spillovers. These findings provide useful insights for risk management, portfolio allocation, and investment decision-making under conditions of geopolitical instability.
This paper examines the association between voluntary municipal amalgamations and observable dimensions of public procurement quality in Italy from 2010 to 2022. Using contract-level data from the Italian National Anti-Corruption Authority (ANAC), we analyse 58,144 contracts, including 1532 awarded by amalgamated municipalities. Procurement performance is measured by winning rebate, total saving, normalised delay and cost overrun. Our empirical strategy employs the staggered difference-in-differences estimator of Callaway and Sant’Anna (2021), using inverse probability weighting and not-yet-treated and never-treated authorities as comparison groups. A two-way fixed-effects model provides a benchmark. Under conditional parallel trends and no anticipation, we estimate that amalgamated municipalities experience winning rebates and total savings that are approximately 6.8 and 8.5 percentage points higher, respectively. Estimates for normalised delay and cost overrun are not statistically significant, while the dynamic results show no persistent deterioration in execution-stage performance. The rebate association is stronger for higher-value contracts, awards based on the most economically advantageous tender, and municipalities with lower pre-merger staff qualifications. We interpret these findings as evidence of a downstream procurement-related channel of the Italian merger policy package—which combines administrative consolidation, fiscal incentives, and increased tendering activity—rather than as a general test of amalgamation effectiveness. An exploratory analysis of pre-merger referendum support finds no robust association with post-merger procurement outcomes once institutional controls are included.
Traditional macroeconomic models often abstract from the temporal structure of production, treating the transformation of inputs into outputs as instantaneous, and largely overlooking micro-level production frictions. We develop an agent-based model that explicitly incorporates time-to-build constraints, heterogeneous production durations, and the possibility of production failures to investigate how the temporal organization of production shapes the interaction between supply and demand. The model features a central-planner-like mechanism that generates production orders and allocates investment goods, allowing us to examine how mismatches between firms’ orders and production capabilities propagate through the economy. We show that temporal rigidities and resource constraints can become endogenous drivers of aggregate dynamics and, ultimately, of distinct patterns of macroeconomic stability. By moving beyond static production functions and equilibrium assumptions, the framework highlights how production time, firm heterogeneity, and supply-side frictions interact to shape the stability properties of the economy.
