A collective risk dilemma for tourism restrictions under the COVID-19 context

Abstract

The current COVID-19 pandemic has impacted millions of people and the global economy. Tourism has been one the most affected economic sectors because of the mobility restrictions established by governments and uncoordinated actions from origin and destination regions. The coordination of restrictions and reopening policies could help control the spread of virus and enhance economies, but this is not an easy endeavor since touristic companies, citizens, and local governments have conflicting interests. We propose an evolutionary game model that reflects a collective risk dilemma behind these decisions. To this aim, we represent regions as players, organized in groups; and consider the perceived risk as a strict lock-down and null economic activity. The costs for regions when restricting their mobility are heterogeneous, given that the dependence on tourism of each region is diverse. Our analysis shows that, for both large populations and the EU NUTS2 case study, the existence of heterogeneous costs enhances global agreements. Furthermore, the decision on how to group regions to maximize the regions’ agreement of the population is a relevant issue for decision makers to consider. We find out that a layout of groups based on similar costs of cooperation boosts the regions’ agreements and avoid the risk of having a total lock-down and a negligible tourism activity. These findings can guide policy makers to facilitate agreements among regions to maximize the tourism recovery.

Cooperation dynamics under pandemic risks and heterogeneous economic interdependence

“…As commented in the introduction, the income loss due to the implementation of pandemic control measures is not homogeneously distributed among countries. For example, tourism was one of the most affected sectors by the COVID-19 pandemic and tourism GDP contribution of the European regions is one example of the heterogeneity of the players involved, as discussed in [17] . The number of regions in the EU NUTS2 classification [35] is 312 and we use real data from this classification to compute the exposure of the regions to a lockdown and tourism activity halt.…”

“…Because of the heterogeneity in the costs, it is not possible to fully assess the overall dynamics through the mean-field analysis of the previous section. Thus, in the following, we resort to agent-based simulations to estimate the evolutionary dynamics of the model [17] , [29] . We have tested both log-normal and power law distributions of potential income losses without significant changes and therefore, the same conclusions apply for both distributions.…”

“…We resort to evolutionary game theory and stochastic population dynamics [21] , [22] , [23] , [24] , [25] , [26] , [27] when required, combined with agent-based computer simulations [28] , [29] . The inspiration for this model was found in previous CRD models for cooperative actions against climate change [9] , [14] and pandemic spread [17] .…”

“…Traditionally, cooperation to mitigate climate change by cutting carbon emissions has been one of the most important applications of CRDs [10] , [11] , [12] , [13] , [14] , [15] , [16] . More recently, CRDs have been proposed for the coordination of restrictions and reopen policies in the current context of the COVID-19 pandemic [17] .…”

Wisata di tengah Pandemi COVID-19: Melihat respon masyarakat setelah Satu tahun Pandemi Covid-19

“…Segala dampak tersebut bisa diminimalisir dan dipulihkan salah satunya oleh pemerintah (Yeh, 2020). Pemerintah baik pusat maupun daerah bisa membuat kebijakan dan bekerjasama terkait pembatasan aktivitas yang tentunya akan sangat berimbas pada aktivitas pariwisata (Chica, Hernández, & Bulchand-Gidumal, 2021).…”