Trans-Subsystem Dynamics: Policy Topography, Mass Opinion, and Policy Change

We argue that the treatment of trans-subsystem change, and particularly the role of public opinion in fostering such change, within the Advocacy Coalition Framework (ACF) has been underspecified. We propose a model of "policy topography" that combines the concepts of public opinion, clusters of linked subsystems, and policy issue venues. While the ACF has characterized subsystems as relatively self-contained, we argue that they are more usefully understood as operating in a relatively permeable fashion among evolving clusters of subsystems linked together by networked relations, strategically overlapping policy considerations, and public opinion disruptions. The "policy topography" model offers opportunities to assess the relationships across policy subsystems, and to better specify the critical relationship between public policy and mass opinions. We offer examples, and suggest hypotheses along with avenues for appropriate empirical analysis.     

Ideology,Power, and the Structure of Policy Networks

This article investigates the role of power and ideology in the endogenous formation of policy networks. According to the Advocacy Coalition Framework (ACF), shared ideology (conceptualized as a system of policy‐relevant beliefs and values) is the primary driver of collaboration within policy subsystems. On the other hand, Resource Dependency Theory suggests that power‐seeking is an important rationale behind network structure, and that collaborative ties are formed primarily on the basis of perceived influence. Hypotheses are tested using a new method of egocentric network correlation, based on survey data of policy networks in five regional planning subsystems in California (N = 506). Results suggest that ideology is an important force behind network cohesion: Not only do policy elites systematically avoid networking with ideologically dissimilar actors but collaborative ties are also systematically formed among actors with shared beliefs. Power‐seeking does not operate on a network‐wide scale but may drive network formation among coalitions of ideologically similar agents.     

Reconceptualizing Major Policy Change in the Advocacy Coalition Framework: A Discourse Network Analysis of German Pension Politics

How does major policy change come about? This article identifies and rectifies weaknesses in the conceptualization of innovative policy change in the Advocacy Coalition Framework. In a case study of policy belief change preceding an innovative reform in the German subsystem of old‐age security, important new aspects of major policy change are carved out. In particular, the analysis traces a transition from one single hegemonic advocacy coalition to another stable coalition, with a transition phase between the two equilibria. The transition phase is characterized (i) by a bipolarization of policy beliefs in the subsystem and (ii) by state actors with shifting coalition memberships due to policy learning across coalitions or due to executive turnover. Apparently, there are subsystems with specific characteristics (presumably redistributive rather than regulative subsystems) in which one hegemonic coalition is the default, or the “normal state.” In these subsystems, polarization and shifting coalition memberships seem to interact to produce coalition turnover and major policy change. The case study is based on discourse network analysis, a combination of qualitative content analysis and social network analysis, which provides an intertemporal measurement of advocacy coalition realignment at the level of policy beliefs in a subsystem.     

The Performance of Policy Networks: The Relation between Network Structure and Network Performance

The importance of policy networks has long been emphasized within the field of policy analysis. However, few attempts have been made to investigate the explanatory power of policy networks using the tools and theoretical concepts provided by social network analysis (SNA). This paper aims to address this need by determining if a relationship exists between the structural features of policy networks, their organizing capacities, and their performance. A comparative case study of four networks within the higher education policy sector confirms the assumption related to the existence of such a relation. It is proposed that an efficient and innovative policy network consists of a heterogeneous set of actors that are centrally and densely integrated. Furthermore, while the level of network heterogeneity is positively related to the function of resource mobilization in the process of policymaking, the level of centralized integration promotes the function of prioritizing. These findings are believed to contribute to our understanding of policymaking in contemporary society. The current paper indicates that a significant explanatory power exists in the concept of policy networks and that SNA is one way of advancing its possibilities.     

Network Dynamics in Natural Resource Governance: A Case Study of Swiss Landscape Management

Structural characteristics of social networks have been recognized as important factors of effective natural resource governance. However, network analyses of natural resource governance most often remain static, even though governance is an inherently dynamic process. In this article, we investigate the evolution of a social network of organizational actors involved in the governance of natural resources in a regional nature park project in Switzerland. We ask how the maturation of a governance network affects bonding social capital and centralization in the network. Applying separable temporal exponential random graph modeling (STERGM), we test two hypotheses based on the risk hypothesis by Berardo and Scholz (2010) in a longitudinal setting. Results show that network dynamics clearly follow the expected trend toward generating bonding social capital but do not imply a shift toward less hierarchical and more decentralized structures over time. We investigate how these structural processes may contribute to network effectiveness over time.     

Social Processes in Lobbyist Agenda Development: A Longitudinal Network Analysis of Interest Groups and Legislation

How are lobbying agendas formed? While individual interest matters, a social process may also affect why lobbyists choose legislation on which to lobby. In a crowded environment, looking at what credible others do may help lobbyists lower their search and information costs with regard to an issue. Using longitudinal network data on lobbyists' legislative choices, I analyze the choices of organizations using an actor‐based dynamic model of network change that conditions agenda changes on the choices made by other organizations. The results suggest both a “bandwagon” process in which organizations converge on “popular” bills and an influence process in which lobbying organizations influence each other when their lobbying agendas overlap. In support of the quantitative findings, interviews with lobbyists show that the policy domain is a social community that consists of ongoing relationships, trust, and information sharing.     

Impacts of Market Liberalization on Regulatory Network: A Longitudinal Analysis of the Swiss Telecommunications Sector

This article looks at the reconfiguration of the regulatory actors' network, as induced by the liberalization and reregulation processes in utility sectors. It investigates the changes in governance structures and patterns of collaborative ties between actors resulting from these processes. Applying stochastic actor‐oriented modeling (SAOM) to data on the liberalization of the Swiss telecommunications sector over two decades, we test whether and to what extent structural changes driven by liberalization and reregulation express themselves through network effects, that is, through changing patterns of interactions between political authorities, regulators, regulatees, and interest groups. Our empirical tests highlight a rearrangement of the regulatory network and a reorganization of relational patterns around new actors, such as the sector‐specific regulatory agency, coregulators, and new operators.     

The Advocacy Coalition Index: A new approach for identifying advocacy coalitions

Policy scholars have increasingly focused on collaborative and competitive relationships between stakeholder coalitions. The Advocacy Coalition Framework (ACF) in particular has directed scholarly attention toward such relationships. The ACF defines advocacy coalitions as groups of actors who share beliefs and coordinate their action. However, previous research has been inconsistent in defining and measuring coalitions, which has hampered comparative research and theory building. We present a method called the Advocacy Coalition Index, which measures belief similarity and the coordination of action in a manner that makes it possible to assess the extent to which advocacy coalitions are found in policy subsystems, whether subgroups resemble coalitions, and how individual actors contribute to coalition formation. The index provides a standardized method for identifying coalitions that can be applied to comparative research. To illustrate the effectiveness of the index, we analyze two climate change policy subsystems, namely Finland and Sweden, which have been shown to differ in terms of the association of belief similarity with coordination. We demonstrate that the index performs well in identifying the different types of subsystems, coalitions, and actors that contribute the most to coalition formation, as well as those involved in cross-coalition brokerage.     

Policy Networks in Complex Governance Subsystems: Observing and Comparing Hyperlink,Media, and Partnership Networks

Methods for observing policy networks have not kept up with the development of new network analytic techniques required to understand governance in complex settings. We compare three unobtrusive methods for observing policy networks based on hyperlinks between policy actor web sites, on media reports, and on public policy partnerships. Observations of one complex local water policy arena with all three methods provide a comparison of the general as well as actor‐specific network characteristics in the three observed networks. The core network of actors observed by all methods has similar network level statistics, highly correlated relationships measured by Quadratic Assignment Procedures models, and the same significant network microstructures as measured by Exponential Random Graph Models. The full networks including actors observed by any method also exhibit similar actor‐level characteristics, although the correlations across networks are stronger for bridging capital measures than for bonding capital measures, and each method has different apparent biases. Once biases are accounted for, similarities suggest that these methods may provide useful proxies for each other and for other relationships that are more difficult or impossible to measure, particularly when combined to offset each method's biases. If so, they can extend the range of policy networks observable with limited resources across space and time.     

Punishment Policy in the American States from 1890 to 2008: Convergence,Divergence, Synchronous Change,and Feed‐Forward Effects

This analysis of the patterns of change in the use of incarceration by the American states from 1890 through 2008 focuses on multiple themes particularly relevant to an understanding of policy arenas in which the social constructions of target populations play an important role. Specifically, the study examines whether the states have adopted more similar incarceration levels over time (converged), whether they tend to change in the same direction at the same time (synchronous change), and whether they tend to stay in the same relative positions vis‐à‐vis one another, such that the historical policy position has long‐term implications for later policy positions (“feed‐forward” effects). The results indicate that, in spite of a century of social, political, and economic integration, the policy positions of the states have not exhibited a sustained convergence toward a common level of incarceration, but have undergone cycles, with some periods of convergence followed by periods of divergence. Change has generally been synchronous—as states tend to move in the same direction at the same time as if propelled by national forces even though incarceration levels are determined by state and local policy and the use of discretion by criminal justice officials. The results also indicate a profound “feed‐forward” effect in that the position of the states vis‐à‐vis one another historically has substantial predictive power for their position in subsequent years.