<p>Recent crises such as the COVID-19 pandemic and geopolitical tensions around the world have highlighted the need to incorporate resilience as a key objective of public policy. However, existing literature in resilience is highly fragmented, and cannot successfully provide an answer to key pressing policy issues. In this paper, we analyze how resilience is understood and analyzed in the sustainability, economics, and management literatures. We highlight similarities and differences in resilience studies across the three fields, and some limitations which may arise when trying to use such studies to inform policymaking. We propose a research agenda for future policy-oriented resilience studies which aims to tackle some of the gaps of current work. We argue that the ultimate goal should be to create large-scale simulation models which are able to integrate economic, environmental, and societal considerations. To reach that goal, more interdisciplinary work is needed to understand the interdependencies among systems, and to create a robust data infrastructure which can support policymaking.</p>

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Resilience: The Need for an Interdisciplinary Research Agenda for Policymaking

  • Tongle Si,
  • Pedro Senna,
  • Jaime Bonnin Roca

摘要

Recent crises such as the COVID-19 pandemic and geopolitical tensions around the world have highlighted the need to incorporate resilience as a key objective of public policy. However, existing literature in resilience is highly fragmented, and cannot successfully provide an answer to key pressing policy issues. In this paper, we analyze how resilience is understood and analyzed in the sustainability, economics, and management literatures. We highlight similarities and differences in resilience studies across the three fields, and some limitations which may arise when trying to use such studies to inform policymaking. We propose a research agenda for future policy-oriented resilience studies which aims to tackle some of the gaps of current work. We argue that the ultimate goal should be to create large-scale simulation models which are able to integrate economic, environmental, and societal considerations. To reach that goal, more interdisciplinary work is needed to understand the interdependencies among systems, and to create a robust data infrastructure which can support policymaking.