Complexity, Governance & Networks

Aims & Scope

CGN contributes to philosophical, theoretical, methodological, and empirical developments in complexity, network, and governance studies in public administration, public policy, and politics, and non-governmental organizations. We also aim to establish a bridge between the worlds of academics and practitioners. Therefore, we welcome contributions by both. We publish content on a diverse array of topics to enhance understanding on complex, and often multifaceted issues reflected in the world today. Authors are encouraged to submit manuscripts written from a variety of theoretical perspectives, including, but not limited to: rational choice theory, game theory, advocacy coalition framework, Marxist theory, critical theory. Listed below are examples of issues that theoretical and/or empirical manuscripts have covered in the past; however, authors are not limited to this list: Definitional and conceptual issues in studying nonlinearity, emergence, self-organization, and (co-)evolution in complex political, policy, and governance systems and networks Applications of agent-based (multi-agent) simulations and systems dynamics modeling in studying complex political, policy, and governance systems and networks and methodological issues in these applications Applications of social network analyses in studying complex political, policy, and governance systems and networks and methodological issues in these applications Applications of qualitative case studies and mixed methods in studying complex political, policy, and governance systems and networks and methodological issues in these applications Case studies focusing on examples of complex behavior and network interactions in public service settings Reflective pieces on the practical value of emerging theories Theoretical essays and empirical studies are encouraged, and should employ at least one of the following: quantitative methods (e.g., agent-based simulations, system dynamics, social network analyses) qualitative methods (e.g., single and multiple case studies, content analyses) mixed methods (e.g. qualitative comparative analysis, process analysis).

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Subject Classification