A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change
The past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodolog...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/8210732 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832550784340852736 |
|---|---|
| author | Maxime Stauffer Isaak Mengesha Konrad Seifert Igor Krawczuk Jens Fischer Giovanna Di Marzo Serugendo |
| author_facet | Maxime Stauffer Isaak Mengesha Konrad Seifert Igor Krawczuk Jens Fischer Giovanna Di Marzo Serugendo |
| author_sort | Maxime Stauffer |
| collection | DOAJ |
| description | The past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodological counterparts to complexity theory, such as computational methods, are rarely used and, even if they are, they are often detached from established policy process theory. Building on a critical review of the application of complexity theory to policy process studies, we present and implement a baseline model of policy processes using the logic of coevolving networks. Our model suggests that an actor’s influence depends on their environment and on exogenous events facilitating dialogue and consensus-building. Our results validate previous opinion dynamics models and generate novel patterns. Our discussion provides ground for further research and outlines the path for the field to achieve a computational turn. |
| format | Article |
| id | doaj-art-297d4202e8e4416dafc8fed7204aaa0a |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-297d4202e8e4416dafc8fed7204aaa0a2025-02-03T06:05:51ZengWileyComplexity1099-05262022-01-01202210.1155/2022/8210732A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy ChangeMaxime Stauffer0Isaak Mengesha1Konrad Seifert2Igor Krawczuk3Jens Fischer4Giovanna Di Marzo Serugendo5Simon Institute for Longterm GovernanceSimon Institute for Longterm GovernanceSimon Institute for Longterm GovernanceEcole Polytechnique Fédérale de LausanneUniversité de Toulouse III - Paul SabatierComputer Science CenterThe past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodological counterparts to complexity theory, such as computational methods, are rarely used and, even if they are, they are often detached from established policy process theory. Building on a critical review of the application of complexity theory to policy process studies, we present and implement a baseline model of policy processes using the logic of coevolving networks. Our model suggests that an actor’s influence depends on their environment and on exogenous events facilitating dialogue and consensus-building. Our results validate previous opinion dynamics models and generate novel patterns. Our discussion provides ground for further research and outlines the path for the field to achieve a computational turn.http://dx.doi.org/10.1155/2022/8210732 |
| spellingShingle | Maxime Stauffer Isaak Mengesha Konrad Seifert Igor Krawczuk Jens Fischer Giovanna Di Marzo Serugendo A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change Complexity |
| title | A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change |
| title_full | A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change |
| title_fullStr | A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change |
| title_full_unstemmed | A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change |
| title_short | A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy Change |
| title_sort | computational turn in policy process studies coevolving network dynamics of policy change |
| url | http://dx.doi.org/10.1155/2022/8210732 |
| work_keys_str_mv | AT maximestauffer acomputationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT isaakmengesha acomputationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT konradseifert acomputationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT igorkrawczuk acomputationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT jensfischer acomputationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT giovannadimarzoserugendo acomputationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT maximestauffer computationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT isaakmengesha computationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT konradseifert computationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT igorkrawczuk computationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT jensfischer computationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange AT giovannadimarzoserugendo computationalturninpolicyprocessstudiescoevolvingnetworkdynamicsofpolicychange |