Bruna Bruno

1. Public sector organisations are widely affected by the technological change brought about by the data-driven revolution (Javaid et al. 2025). Nevertheless, there remain many barriers and challen...

This study analyzes how blockchain technology can be interpreted through an economic perspective, viewing network nodes as rational agents whose strategic behavior affects the efficiency and sustainability of decentralized systems. Using a multi-player non-cooperative game with complete but imperfect information, we model validators’ decisions in voting-based consensus mechanisms and compare alternative incentive configurations through simulation results. The analysis shows how variations in reward schemes influence validators’ behavior and consensus reliability. Extending the framework to Decentralized Autonomous Organizations (DAOs), the study explores how blockchain-based incentives can enhance participation, accountability, and decentralized governance. The findings highlight that incentive design plays a decisive role in aligning individual motivations with collective goals, ensuring both network integrity and long-term sustainability. Overall, this study connects economic theory with blockchain governance, extending its relevance to business and organizational contexts beyond cryptocurrencies.

This study presents an agent based model with two sectors differing for their location in the economy and workers sequentially searching for a job. In this framework we test the effects on workers’ disposable income of teleworking introduction, with different intensity by sectors, to verify if working organizational features may exacerbate the negative effects post-pandemic asymmetric shocks. Results show that workers employed in central locations of the economy gain a wage advantage compared to those finding job in peripheral positions. The differential in disposable income for the first group increases if in the central sector teleworking is introduced at higher intensity compared to the peripheral one. Sectors already penalized by closures and social distancing measures can face further inequalities in terms of disposable income for organizational and technological bounds.

This study presents an agent-based model where individuals employ simple heuristics to assess their satisfaction for specific life satisfaction domains and for life satisfaction as a whole, considering reference groups of different dimensions. The objective is to reconcile the evidence on the negative correlation between the income measures and self-reported happiness at the country level with the individuals’ attitude toward happiness. Results from simulations show that the relationship between life satisfaction and income has opposite signs when individuals perform their comparisons basing judgments on the mean or on the median income of their reference groups, and that the extension of the reference groups matters. A role for inequality emerges in determining the relationship between aggregate measures of income and life satisfaction. Results from simulations are validated through data from Eurobarometer for 24 European countries in the period 2008–2020, suggesting that people employ positional evaluations of satisfaction for the income domain by using the median income of the reference group as reference parameter.

This paper deals with the relationship between individual preferences and the use of cash. Building on insights from economic and psychological literature, we present an agent-based model simulating consumers’ behaviour when choosing which mean of payment to use, according the value of the transaction. Assuming heterogeneous preferences for mean of payment, results show that the number of cash transactions and their value strongly depend on both the consumption and the preference structure. Results are validated with EU countries’ data, considering different national policies adopted on the cash usage.

The main objectives of this study are to take into account the effects of COVID-19 on labor market functioning, and to evaluate the effects of policies regarding working time reduction, in terms of both containing the spread of infection and economic activity. Accordingly, we describe a macroeconomic model wherein we test the effects of reducing working hours in the Keynesian unemployment framework, which comprises a fixed prices and wages regime, and a consumption demand that is dependent on salaries and autonomous demand components. Moreover, we also describe a neoclassical unemployment framework, wherein the labor market is only governed by dynamic demand forces. Theoretical results show that, according to the epidemiological phase, a reduction in working hours may be a good policy for containing the virus and improving employment in the Keynesian framework when established conditions are maintained. In the neoclassical framework, a work sharing policy will fail if some conditions do not occur, and it could cause an increase in the spread of the virus when a reduction of epidemic containment measures occurs. Employment will increase when the pandemic ends. A numerical simulation confirms that a reduction in working hours could reduce virus diffusion, but only under established, constrained parameters in both frameworks.

The transition from the linear economy to the circular economy exhibits some criticalities that can be solved through the identification of factors pushing and pulling the transition itself. By adopting a public good perspective in analysing the main features of the circular business models, this study underlines how the sharing economy business models are well integrated and complementary to some features of the circular economy, representing a strong pulling factor. Other loops of the circular economy need an explicit push factor, individuated in a strong impulse to eco-efficiency, to be reached through consistent incentives to invest in R&D for eco-innovations. Seven case studies are investigated in their aims, feasibility and implementation to support the interpretative framework.