|
| # | Reference title | Reference number | Implicit or explicit use of complex system | Type of contribution | Contribution | Formal modeling |
|
| 1 | Agenda dynamics and policy subsystems | [51] | Implicit | Theory | Conceptualize abrupt policy changes whose emergence happens from the interactions of multiple adaptive agents. Cite complex system literature [52] | NA |
| 2 | Agendas, alternatives, and public policies | [53] | Implicit | Theory | Conceptualize policymaking through multiple streams but discuss complexity theory in chapter 10 as a potential framework that can explain sudden, nonlinear change in policymaking | NA |
| 3 | Policy feedback theory | [54] | Implicit | Theory | Describe feedback loop between policy outcome and policy processes | NA |
| 4 | A river runs through it: a multiple streams metareview | [55] | Implicit | Theory; review | Describe interplay of actor and environment to explain policymaking; report 88% of studies are qualitative | NA |
| 5 | Policy learning and policy Change: theorizing their relations from different perspectives | [56] | Implicit | Theory; review | Describe adaptive behavior of individuals and groups | NA |
| 6 | Common approaches for studying advocacy: review of methods and model practices of the advocacy coalition framework | [57] | Implicit | Theory; review | Describe the use of coevolutionary coalitions to explain policy processes; report that 70 to 100% of analyses are qualitative | NA |
| 7 | Punctuated equilibrium theory: explaining stability and change in public policymaking | [3] | Implicit | Theory | Describe power-law in budget changes and theorize positive and negative feedback loops at the microlevel
| NA |
| 8 | Nonequilibrium theory and its implications for public administration | [58] | Explicit | Theory | Conceptualize policymaking and public administration through the lens of dynamic and nonequilibrium systems | NA |
| 9 | Managing uncertainties in networks a network approach to problem solving and decision making | [59] | Explicit | Theory | Conceptualize policymaking as set of networks and where policy change depends on the adaptation of networks to exogenous events | NA |
| 10 | Governance, complexity, and democratic participation | [60] | Explicit | Theory | Apply complexity theory to policymaking in urban environment, both understand processes and consequences | NA |
| 11 | Managing complex governance systems | [61] | Explicit | Theory | Collect frameworks that apply complexity theory to policymaking, notably nonlinear dynamics, self-organization, and coevolution | NA |
| 12 | Complexity theory and evolutionary public administration: a sceptical afterword | [18] | Explicit | Theory | Formulate a criticism of the current scholarship that applies complexity theory to policy processes and delineates avenues for further research | NA |
| 13 | Complexity and public policy: a new approach to twenty-first-century politics | [15] | Explicit | Theory | Map properties of complex systems on the characteristics of public policy processes and discuss implications | NA |
| 14 | Complexity, institutions, and public policy | [62] | Explicit | Theory | Apply complexity theory to institutionalism and discusses how this lens can help understand policy processes and as well as a policy evaluation | NA |
| 15 | Complexity theory in political science and public policy | [14] | Explicit | Theory | Discuss the use of complexity to understand policy processes and implications for the field | NA |
| 16 | What is evolutionary theory and how does it inform policy studies | [63] | Explicit | Theory | Discuss the use of evolutionary theory in policy process studies and present complexity theory as one approach | NA |
| 17 | A complexity theory for public policy | [16] | Explicit | Theory | Map properties of complex systems on the characteristics of public policy processes and discuss implications | NA |
| 18 | Complexity theory and its evolution in public administration and policy studies | [64] | Explicit | Theory | Survey the evolution of the application of complexity theory and proposes a four-stage model of such developments | NA |
| 19 | The emergence of complexity in the art and science of governance | [65] | Explicit | Theory | Discuss applications of complexity theory to governance and propose methods to put concepts to the test | NA |
| 20 | How the complexity sciences can inform public administration: an assessment | [66] | Explicit | Theory | Discuss major books published on complexity theory and public administration and public policy and delineate common themes | NA |
| 21 | Handbook of complexity and public policy | [67] | Explicit | Theory; review | Provide an overview of the use of complexity theory to explain policy processes, and describe the use of agent-based models | NA |
| 22 | Agile actors on complex terrains: transformative realism and public policy | [68] | Explicit | Theory | Apply ideas from complexity theory to public policy, including both policy processes and policy consequences | NA |
| 23 | Complexity thinking in public administration’s theories-in-use | [69] | Explicit | Theory | Survey the use of complexity theory in public administration and how it is linked (or not) to established theories | NA |
| 24 | A critical discussion of complexity theory: how does “complexity thinking” improve our understanding of politics and policymaking? | [19] | Explicit | Theory | Survey applications of complexity theory and formulate a critique that they so far have are driven by hope rather than experience, and claim that complexity theory can serve as a bridge to communicate better between researchers and practitioners | NA |
| 25 | The new policy sciences: Combining the cognitive science of choice, multiple theories of context, and basic and applied analysis | [1] | Explicit | Theory | Cover briefly how complexity theory fits in the policy sciences | NA |
| 26 | Complexity theory in public administration | [70] | Explicit | Theory | Provide an overview of the latest discussions and applications of complexity theory to public administration, with content covering both policy processes and policy analysis. | NA |
| 27 | Adaptive parties in spatial elections | [71] | Explicit | Exploratory modeling | Model dynamic voting behavior between adaptive parties, with an unclear link with policy process theories | Agent-based model |
| 28 | Political complexity: nonlinear models of politics | [72] | Explicit | Review of models | Provide an overview of models of politics, with unclear links to policy process theories | Various |
| 29 | Abstention in dynamical models of spatial voting | [73] | Explicit | Exploratory modeling | Model dynamic voting behavior between adaptive parties, with an unclear link with policy process theories | Mathematical model |
| 30 | Mixing beliefs among interacting agents | [74] | Explicit | Exploratory modeling | Provide a model of opinion dynamics in networks of agents | Mathematical model |
| 31 | Policy and the dynamics of political competition | [75] | Explicit | Exploratory modeling | Conceptualize policymaking through an agent-based perspective on party competition where agents are adaptive and various processes are used to generate emergent policy change, with weak links to policy process theories | Agent-based model |
| 32 | Computational methods and models of politics | [76] | Explicit | Review of models | Review of models of politics, mostly focusing on electoral systems and institutional design | Agent-based model |
| 33 | A tournament of party decision rules | [77] | Explicit | Exploratory modeling | Conceptualize policymaking through repeated games with adaptive parties running for elections | Agent-based model |
| 34 | Sociophysics: a review of Galam models | [78] | Explicit | Review of models | Review 25 years of modeling attempts to understand democratic voting, decision-making fragmentation and coalition, and opinion dynamics | Mathematical models |
| 35 | MASON RebeLand : an agent-based model of politics, environment, and insurgency | [79] | Explicit | Exploratory modeling | Formalize a large-scale agent-based model with an unclear link to policy process theories | Agent-based model |
| 36 | Simulating political stability and change in The Netherlands (1998–2002) | [80] | Explicit | Emp.-validated modeling | Implement a version of Kollman et al. [71] model and test it empirically | Agent-based model |
| 37 | Understanding collective decision making: a fitness landscape model approach | [21] | Explicit | Emp.-validated modeling | Present a model of collective decision-making using fitness landscapes and apply the model to empirical cases; reconcile micro and macrodynamics of how groups agents interact to solve collective problems | Fitness landscapes |
| 38 | Deep learning and punctuated equilibrium theory | [22] | Explicit | Exploratory modeling | Model patterns of policy attention | Deep neural networks |
| 39 | Policy emergence: an agent-based approach | [23] | Explicit | Exploratory modeling | Formalize an agent-based model based on the combination of policy process theories | Agent-based model |
| 40 | Modeling contagion in policy systems | [35] | Explicit | Exploratory modeling | Model attention contagion in policy networks, with a clear link to policy process theories | Agent-based model |
| 41 | Association between decisions: experiments with coupled two-person games | [81] | Explicit | Exploratory modeling | Provide a game-theoretic model to explore decision-making between agents that meet in coevolving policy arenas | Game-theoretic model |
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