The role of policy learning in explaining Covid-19 policy changes
Bibliographic Data
| ID | 4823169 |
|---|---|
| Authors | Chan Wang (0000-0002-1442-8484, Jacksonville State University, corresponding author) |
| Year | 2025 |
| Volume | 42 |
| Issue | 4 |
| Pages | 929-948 |
| Publication date | 2025-07-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Review of Policy Research (JOURNAL) |
| Journal identifiers | ISSN: 1541-132X • E-ISSN: 1541-1338 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/ropr.12578 |
| OpenAlex | W4387957452 |
| Language | EN |
| Citations received | 3 |
| References cited | 43 |
The ongoing fight against the COVID-19 pandemic has highlighted the importance of adaptive policy change and the critical role of policy learning in responding to public health crises. This study utilizes policy change and policy learning theories to investigate how instrumental and political learning intertwined to explain the policy change decisions made by six U.S. states from May to December 2020. By employing a multi-value Qualitative Comparative Analysis, this study finds that the decision to impose stricter public gathering restrictions is primarily driven by instrumental learning, which is a response to the deteriorating pandemic situation. On the contrary, the decision to relax gathering restrictions is not only driven by the policymakers' perception of the improving pandemic situation but also influenced by the political motivations, such as the desire to suppress protests and address concerns for the decreased approval for the governor's handling of the crisis. The findings highlight the varied utilization of different policy learning types in response to different directions of policy change. Additionally, this study underscores the joint impact of instrumental and political learning in explaining changes in policy stringency. Overall, these findings contribute to a deeper understanding of policy change through learning activities in a complex and rapidly evolving policy landscape
Disease · Economic growth · Economics · Pandemic · Perception · Policy analysis · Policy learning · Policy studies · Political science · Politics · Public economics · Public policy · Public relations · Computer Science · Law · Medicine · Policy Transfer and Learning · Political Influence and Corporate Strategies · Psychology · Public Administration · Qualitative Comparative Analysis Research
Theories of the Policy Process
Adaptive policies, policy analysis, and policy-making
Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?
Learning from the Covid-19 crisis
The Multiple Streams Framework
Policy change and learning
Lessons of Disaster
Set-Theoretic Methods for the Social Sciences
During Disaster
Policy learning type shifts during creeping crises
Policy Learning in Comparative Policy Analysis
EU economic governance and Covid-19
From Uncoordinated Patchworks to a Coordinated System
How different forms of policy learning influence each other
Fighting Covid ‐19 with Agility, Transparency, and Participation
Crisis Decision‐Making on a Global Scale
Organizing for Crisis Management
Explaining science-led policy-making
The lessons of learning
High-stakes crisis management in the Low Countries
A comparative study of Covid-19 responses in South Korea and Japan
Local Response to Water Crisis
Set Relations in Social Research
A global panel database of pandemic policies (Oxford Covid-19 Government Response Tracker)
Crisis, learning and policy change in the European Union
Policy learning and change during crisis
States Divided
Policy Learning and Information Processing
Of Barriers to Entry for Medium and Large n Multiple Streams Applications
Evidence translation
How does policy learning take place across a multilevel governance architecture during crises
Policy Learning and Failure
Three strategies to track configurations over time with Qualitative Comparative Analysis
Researching Covid-19
Systematising Policy Learning
Policy Paradigms, Social Learning, and the State
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2025 (2) |
| Highly cited | No |