Crucial and fragile: a multi-methods and multi-disciplinary study of cooperation in the aftermath of the COVID-19 pandemic

Abstract

In addressing global pandemics, robust cooperation across nations, institutions, and individuals is paramount. However, navigating the complexities of individual versus collective interests, diverse group objectives, and varying societal norms and cultures makes fostering such cooperation challenging. This research delves deep into the dynamics of interpersonal cooperation during the COVID-19 pandemic in Canton Ticino, Switzerland, using an integrative approach that combines qualitative and experimental methodologies. Through a series of retrospective interviews and a lab-in-the-field experiment, we gained insights into the cooperation patterns of healthcare and manufacturing workers. Within healthcare, professionals grappled with escalating emergencies and deteriorating work conditions, resisting the "new normalcy" ushered in by the pandemic. Meanwhile, manufacturing workers adapted to the altered landscape, leveraging smart working strategies to carve out a fresh professional paradigm amidst novel challenges and opportunities. Across these contrasting narratives, the centrality of individual, institutional, and interpersonal factors in galvanizing cooperation was evident. Key drivers like established relational dynamics, mutual dependencies, and proactive leadership were particularly salient. Our experimental findings further reinforced some of these qualitative insights, underscoring the pivotal role of recognition and the detrimental effects of uncertainty on cooperative behaviors. While contextual and sample-related constraints exist, this study illuminates vital facets of cooperation during crises and lays the groundwork for future explorations into cooperative decision-making.

Keywords: COVID-19 pandemic; collaborative decision-making; crisis management; interpersonal cooperation; mixed methods.

Figure 1

Contributions in the PGG by treatment manipulation and across 10 rounds.

Figure 2

Variables in order of importance for the Random Forest model.