The paper investigates the determinants and discusses the consequences of the switch towards Italian high-tech firms’ teleworking due to the COVID-19 crisis. Teleworking is important to reduce traffic congestion and increase the sustainability of cities, and as such, it is important to understand what helps the successful transition of firms to telework. COVID-19 crisis represents a natural experiment that allows studying organizational ability to adapt to unexpected environmental changes rapidly. The study is based on a survey conducted in mid-April 2020 during the COVID-19 lockdown among Italian manufacturing firms’ managers in high-tech sectors. The final sample is composed of 179 observations. Using path analysis, we model the organizational e-readiness as a mediator of the firm’s technological and organizational characteristics in the rate of adoption of teleworking. Teleworking is also modeled as dependent on human resources and from the exogenous shock represented by COVID-19 lockdown. While teleworking has been imposed by COVID-19, organizational readiness plays a key role in shaping the rate of teleworking adoption during emergencies.

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In this paper, we present an agent-based, evolutionary, model of output- and labor-market dynamics. Firms produce a homogeneous, perishable good under constant returns to scale using labor only. Labor productivities are firm-specific and change stochastically due to technical progress. The key feature of the model resides in an explicit microfoundation of the processes of : (i) matching between firms and workers, (ii) job search, (iii) wage setting, (iv) endogenous formation of aggregate demand, and (v) endogenous price formation. Moreover, we allow for a competitive process entailing selection of firms on the basis of their revealed competitiveness. Simulations show that the model is able to robustly reproduce Beveridge, Wage and Okun curves under quite broad behavioral and institutional settings. The system generates endogenously an Okun coefficient greater than one even if individual firms employ production functions exhibiting constant returns to labor. Monte Carlo simulations also indicate that statistically detectable shifts in Okun and Beveridge curves emerge as the result of changes in institutional, behavioral, and technological parameters. Finally, the model generates sharp predictions about how system parameters affect aggregate performance (i.e. average GDP growth) and its volatility.

We investigate the role of search strategy in shaping firms' innovation performance. Firms use a wide range of external actors and sources to help them achieve and sustain innovation. In particular, the extension (breadth) and the relevance (depth) of such sources determine firms' ability to extract and exploit knowledge and new ideas and, thus, to be innovative. Using a sample of firms in a regional context active in R&D, we built separate measures of breadth and depth for local (on a regional scale) and global (outside the regional context) search. This allows us to investigate whether localized or global knowledge spillovers are in place. We find that a wider set of partners increases coordination costs, while greater depth in search strategies contributes to innovation. We find that a more diversified search strategy at the local level (greater breadth of search) results in significant payoffs in terms of innovation, while diversifying the partnership with Italian partners has a smaller, although still positive, effect. In contrast, the benefits of depth of innovation are greatest at the global level. In addition, a broader set of information sources for R&D projects has a significant positive effect on innovation. Finally, firms that resort to R&D subsidies are less innovative.