This work aims to offer a contribution in the analysis and management, from an economic and financial point of view, of the flood risk, and extended to the hydrogeological risk, from the perspective of a public administration. As main responsible actor for containing the phenomenon through the maintenance of the territory, public administration is responsible for the cost of restoring of the services that have been damaged by this type of phenomenon. The assets of which the public administration must ensure the restoration are all public infrastructures (i.e. transportation, energy and water supply system, communication) together with the damage suffered by private property, if these affect services to be guaranteed to the population. In this work, the authors propose possible strategies that a public administration can put in place to deal with flood risk. Three main strategies are analysed: an absolute passivity that provides for the payment of damages as they occur (i.e. business-as-usual scenario), a classic insurance scheme, a resilient and innovative insurance scheme. The economic–financial profiles of these strategies proposed in this work put an emphasis on how the assumption of a time horizon can change the convenience of one strategy compared to the others. This study highlights the key role of the quantification of flood risk mitigation measure from an engineering perspective, and their potential issues to pursue these objectives in connection to the regulatory framework of the public administrations. This synergy is supported by the potential use of Blockchain-based tools. Within the paper is highlighted the key role that such platform IT data management platform could have within risk analysis and management schemes, both as a data collection tool and as certification of the various steps necessary to complete the process.

This study explores how the System Dynamics modeling approach can help deal with the problem of conventional insurance mechanisms by studying the feedback loops governing complex systems connected to the disaster insurance mechanism. Instead of addressing the disaster’s underlying risk, the traditional disaster insurance strategy largely focuses on providing financial security for asset recovery after a disaster. This constraint becomes especially concerning as the threat of climate-related disasters grows since it may result in rising long-term damage expenditures. A new insurance mechanism is suggested as a solution to this problem to lower damage costs while safeguarding insured assets and luring new assets to be protected. A local case study utilizing a System Dynamics stock and flow model is created and validated by examining the model’s structure, sensitivity analysis, and extreme value test. The results of the case study performed on a city in Latvia highlight the significance of effective disaster risk reduction strategies applied within the innovative insurance mechanism in lowering overall disaster costs. The logical coherence seen throughout the analysis of simulated scenario results strengthens the established model’s plausibility. The case study’s findings support the innovative insurance mechanism’s dynamic hypothesis and show the main influencing factors on the dynamics within the proposed innovative insurance mechanism. The information this study can help insurance firms, policy planners, and disaster risk managers make decisions that will benefit local communities and other stakeholders regarding climate-related disaster risk mitigation.

There is a widespread interest among institutions and economic agents for a reduction of the environmental impact of the production system. An important role seems to be played by the ability of public institutions to push the transition toward a green economy also through the application of fiscal policies that envisage a system of rewards and penalties, respectively, for those companies which adopt green strategies and those which do not. It is clear that readjusting older production systems to new pollution regulations can lead in the short term to profitability reductions for the companies implementing them, even though it is possible to assume increases in profitability over medium-long time horizons. One possible approach to this issue is the classical econometric one, which analyzes the effect of different parameters of multivariate models, that influence the level of pollution due to production systems with different propensity for environmental protection. Optimal control models have been also considered with control variables relating to the technologies of production systems and public incentive policies for the green economy: see for example (Tan et al. in J Syst Sci Inf 9(1):61–73, 2021). In recent years, many scholars have studied the relationship between environmental regulation and enterprise technological innovation using evolutionary games, involving mainly economic incentives and fiscal strategies (see see Suyong et al. in Appl Math Comput 355(15):343–355, 2019; Zhang and Li in Appl Math Model 63:577–590, 2018). In our article, we propose a dynamical model where the public administration uses pollution penalties as a control variable in order to push a production sector toward better performances concerning two targets, pollution level and profitability. To this end, we consider the effects of competitiveness among firms and technology innovation.