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This paper explores how global pandemic crises affect the financial vulnerability of municipalities.

This paper is developed from the relevant literature an analytical framework to examine municipal financial vulnerability before a global pandemic crisis and in its immediate aftermath by mapping and systematizing its dimensions and sources. To illustrate how it can be used and evaluate its robustness and flexibility, such a tool was applied to Portugal and Italy, two countries that particularly suffered from the Covid-19 crisis.

The application of the analytical framework has shown how financially vulnerable municipalities are to global pandemic crises. Financial vulnerability relates to issues ranging from institutional design to internal financial conditions and the perception of the capacity to cope with a crisis. Results further reveal that vulnerability has an inherent contingent nature in time and space and can lead to paradoxical outcomes.

This paper provides a tool that can be useful for both academic and public policy purposes, to further appreciate municipal financial vulnerability, especially during crises.

Municipalities can use the framework to better manage their financial vulnerability, strengthening their anticipatory and copying capacities, while oversight authorities can use it to help municipalities become less financially vulnerable or, at least, more aware of their financial vulnerability.

Municipal financial vulnerability to global shocks has not been explored extensively. Also, the Covid-19 pandemic is different from previous global crises as it affected society overnight with the implementation of lockdown and social distancing measures.

Learning as the way in which labor acquire new knowledge and skills has important strategic implications for the competitive advantage of an organization. The purpose of this paper is to present an agent-based modeling (ABM) approach to investigate the learning behavior of workers. The effect of interactions among different workers as well as the factors affecting the workers’ learning behavior is assessed using the proposed ABM approach.

For this purpose, the processes through which the competency value of worker is changed are understood and the workers’ learning behavior is modeled, taking account of various influencing factors such as knowledge flow, social ability to teach and forgetting factor.

The proposed model is implemented on a real steel structure project to evaluate its applicability and performance. The variation in the competency value of different workers involved in the project is simulated over time taking account of all the influencing factors using the proposed ABM approach.

In order to assess the effect of interactions among welders as well as the welders’ characteristics on their learning behavior, the competence value of different welders is evaluated.

This research presents an ABM approach to investigate the workers’ learning behavior. To evaluate the performance of the proposed ABM approach, it was implemented on a real steel structure project. The learning behavior of different welders (agents) was simulated taking account of their interactions as well as the factors affecting the welders’ learning behavior. The project involved the welding of a 240-ton steel structure. The initial project duration was estimated as 100 days. In this project, it has been planned to execute the welding process using three different welders namely welder A, B and C.