Institutional Communication Revisited: Preferences, Opportunity Structures and Scientific Expertise in Policy Networks (original) (raw)
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Journal of Theoretical Politics, 1998
This article attempts to explain why actors form policy networks of information and exchange contacts, and how the institutional settings of public decision-making affect policy network formation. In their empirical analysis of the formation of four different policy networks in the German labourpolicy domain, the authors examine actors' choice of mutual contacts resting on similarity of preferences on political events and test the importance of either formal procedural settings or common sector membership for information and exchange network formation. The choice of policy network contacts is shown to be primarily determined by the similarity of actors' preferences. However, this is qualified by institutional settings.
The Politics of Connections: Assessing the Determinants of Social Structure in Policy Networks
Journal of Public Administration Research and Theory, 2012
This article investigates the role of resource dependence in explaining the social structure of policy networks while controlling for the effects of microstructure, such as the tendency for networks to display reciprocity and/or transitive closure. While previous studies have analyzed resource dependence as a factor in decision making in policy networks, surprisingly little is known about the effects of these social factors on the structure of policy networks due, in part, to the statistical challenges in modeling them precisely. However, the recent development of the exponential random graph model technique, a stochastic method for studying social structure, has made it possible to overcome the statistical hurdles. This study draws on longitudinal data collected from an adult basic education policy network during 1998 and 2005 in a state to which we gave the pseudonym "Newstatia. " The findings suggest that decreased resource munificence may cause network segmentation and change the composition and nature of relationships among policy network members. These findings confirm our prior expectation that policy network activity and structure is animated by a desire to control resources. In addition, the observed policy network structure is greatly influenced by balancing operations undertaken by resource holders (e.g., legislators and state agencies) and resource seekers (e.g., service providers) and the generic social pressures for reciprocity and transitivity. INTroDuCTIoN For decades, scholars have recognized that public organizations with an enduring interest in a particular substantive policy area and their senior public managers are enmeshed in informal webs of relationships. More recently termed "policy networks," these webs are an alternate forum for policy deliberation and policy making. Policy networks provide a structure within which senior public managers play a role in guiding decision processes. Numerous studies on policy networks have suggested that resource We would like to acknowledge the contribution of Deneen M. Hatmaker (University of Connecticut) to the original collection and collation of the data used for this study. An abridged, early version of the paper was published in the 2009 Academy of Management Annual Meeting Proceedings. We also would like to thank the anonymous reviewers and the editors of JPART for their invaluable comments.
The roles actors play in policy networks: Central positions in strongly institutionalized fields
Network Science, 2021
Centralities are a widely studied phenomenon in network science. In policy networks, central actors are of interest because they are assumed to control information flows, to link opposing coalitions and to directly impact decision-making. First, we study what type of actor (e.g., state authorities or interest groups) is able to occupy central positions in the highly institutionalized context of policy networks. Second, we then ask whether bonding or bridging centralities prove to be more stable over time. Third, we investigate how these types of centrality influence actors’ positions in a network over time. We therefore adopt a longitudinal perspective and run exponential random graph models, including lagged central network positions at t1 as the main independent variable for actors’ activity and popularity at t2. Results confirm that very few actors are able to maintain central positions over time.
Policy Networks: Empirical Evidence and Theoretical Considerations
The American Political Science Review, 1993
Although network thinking will have considerable impact on future social theory building in general, this chapter is certainly not the place for a general "philosophical" discussion. Based on the assumption that the network perspective will be, indeed, also fruitful for political analysis, we will focus our discussion on the specific use of network concepts in policy analysis. We will try to show that an important advantage of the network concept in this discipline is that it helps us to understand not only formal institutional arrangements but also highly complex informal relationships in the policy process. From a network point of view. modern political decision making cannot adequately be understood by the exclusive focus on formal politico-institutional anangements. Policies are formulated to an increasing degree in informal political infrastructures outside conventional channels such as legislative, executive and administrative organizations. Contemporary policy processes emerge from complex actor constellations and resource interdependencies, and decisions are often made in a highly decentralized and informal manner. example, the policy sector (Benson 1982), the policy domain (Laumann/ Knoke 1987), the policy topic's organization set (see for this concept Olsen 1982), the policy (actor) system (see, for instance, Sabatier 1987), the policy community (Jordan/ Richardson 1983, Mdny 1989), the policy game, the policy arena and also the policy regime. The network concept and all these other policy concepts are variations of a basic theme: the idea of public policies which are not explained by the intentions of one or two central actors, but which are generated within multiple actor-sets in which the individual actors are interrelated in a more or less systematic way. However, each of the different policy concepts emphasizes a special aspect: for example, the institutional structures in decision making processes are highlighted by the arena and regime perspective; the conflictual nature of policy processes, again, is emphasized by the game perspective. The arena concept, in contrast, concentrates on conflict and institutional integration, and the community, system and sector perspec-9 For a more detailed overview of British works with the network concept see also the recent article of Rhodes (1990). l0 Other examples in the application of the network concept in policy making are Zijlstra (1918179:359-389); Rainey/ Milward (1983: 133-146); Trasher/ Dunkerley (1982: 349' 382); Trasher (1983: 375-391). For an overview see also Windhoff-Hdritier (1985: 85-2t2). Cltapter 2 Butt, R. S./ M. J. Minor, 1982: Applied Nenuork Analysis-A Methodological Introduction Beverly Hills/ London: Sage. Callon, Michel, 1986: The Sociology of an Actor-Network: The Case of the Electric Vehicle. In: M. Callon/ H. Law/ A. Rip, Mapping the Dynamics of Science and Technology. Sociology of Science in the Real World. Houndmills: Macmillan, 19-34.
The structure of policy networks
European Journal of Political Research, 1992
In this study the formation of policy networks is analysed. Theoretically the policy network is seen as a tool for actors to advance their goals in order to ensure that the policy decisions correspond as closely as possible with their own policy preferences. The possession of information has a major role in this process. The empirical analysis shows that the tendency towards mutual relations in the policy network is strong. Network ties are also more likely to be directed to those actors with similar overall policy preferences. Thus, relations in the policy network can be seen mainly as attempts to create a reasonable level of trust (or "political capital") among pairs of actors. Once the trust relationship is established influence is used in specific instances when the two actors disagree. On the whole, political decision-makers are more willing to accept "one-sided" incoming information contacts. However, they are also likely to engage in "bolstering" i.e. listening mostly to information from actors sharing the decisionmakers' own preferences.
1997
Abstract Theory: The political information that lobbyists seek is distributed in a communications network. Individual lobbyists must therefore choose their contacts carefully. We wed rational choice theory to network analysis in a combinatorial optimization model of lobbyists' choice of contacts in a network. The model demonstrates the growing importance of political" friends" relative to acquaintances as contacts when the competition for information among groups rises.
Connections, 2005
This article aims at presenting advantages and weaknesses of complete network analysis in policy analysis and research of organized interests. Indicators (actor-and network-related factors) that have proven to be significant for power dimensions (trust, incentive giving and irreplaceability) will be presented. These have been derived from a policy research project in 2002. Advantages of a complete analysis of policy networks are the disclosure of latent structures, the operationalisation of power in policy arena, the measurement of policy impact of subjective factors (attitudes like radicalism, trustworthiness etc), and the "objective" bounding of the network. Challenges for future improvement are the relative "small size" of a network as a sample, the weakness of telephone queries, and the selfselection which characterizes the snowball sampling. Further questions could concern research on information, financial incentives, oligarchy and corruption. of the results as example, but not the policy content of these issue networks. We only make clear that these are of environmental interest. Briefly, we mention these as follows: 1. Denmark: Certification of sustainable management of natural resources, 2. Finland: Certification of sustainable management of natural resources, 3. Spain: Certification of sustainable management of natural resources, 4. Germany-Bavaria: Eco-account, 5. Germany-Bavaria: Mapping of biotopes, 6. Sweden: Key biotopes, 7. Greece: Revision of constitution regarding environmental policy, 8. Sweden: Governmental forestry strategy, 9. UK-Scotland: Scottish forestry strategy, 10. UK-Scotland: Loch Lomond and Trossachs National Park, 11. Ireland: Provisional marketing services in natural resources, 12. Spain: Research project castanea. 3 The initial hypothesis was that the power status of an organisation depends both on its own characteristics and on the characteristics of the policy network in which it is involved Our conclusions are based on experience derived from a survey that was carried out in 2002 2 . General aim of this research was to find out actor-and network-related factors that influence the power status of an interest group in a network 3 . We will briefly present the network-related factors as well as certain actor-related factors which are not internal structures (e.g. multidisciplinary team) but rather depend on the network in which an actor participates (e.g. communication properties of an actor, behavioral aspects, partners). We are going to argue that the advantages of the complete analysis of policy networks are the potential of disclosing latent structures (e.g. oligarchy), the operationalisation of power in political arena, the measurement of policy impact of subjective factors (attitudes like radicalism, trustworthiness, information "importance"), and the "objective" bounding of the network. Challenges for future improvement are the relative "small size" of a network as a sample, the weakness of telephone queries (which usually is the only cost-effective technique), and the self-selection which characterizes the snowball sampling (complete network). Further questions and applications could concern research on information, financial incentives and corruption.
2004
This work is based on a doctoral research. Our main question is: who can be powerful and when. We assume that power is a function of network and organizational characteristics and thus not every actor can be powerful in every network. Power and institutional theories will be operationalized, completed and specified by the results. Five types of power factors will be proposed, which are combinations of organizational and network characteristics that combine to produce high power synergy and low inconsistency. The first dimension of power is trust: the trustee leads the one who trusts. The second dimension is financial incentive: the gift giver influences the gift receiver. The third dimension is irreplaceability. This is an operationalization of general system theory which operationalizes the exchange power model. Although the dependent variable (power) will be calculated by the systemic approach, the independent variables will be culled from New Institutionalism. For this purpose, a combination of the Theory of Organized Interests and Network Theory is necessary. These theories will be specified throughout our results. The typology of power factors (organizational and network characteristics) was derived from both inductive and deductive processes. The organizational factors have been deduced from certain theories: the "lawful" type from contingency theory and mobilization of bias, the "trustworthy" from the resource dependence model, the "little brother" from the transaction-cost and resource dependence model, the "omniscient" type from decisionmaking theory, and the "re-distributor" type from decision-making theory and hypotheses on the role of monitoring information. Afterwards, the deduced organizational factors of each type have functioned as a basis for the induction of network factors, which proved to reach highest power synergy with the organizational factors through stepwise regression. Our methodology is a statistics-based vector algebra. We measured 108 indicators in 234 cases from 12 environmental policy networks in 8 European countries. In general, 'trust' makes up 82% of the power composition, while 'financial incentive' is only 8% and 'irreplaceability' only 10%. Not all the network characteristics and organized interest models proposed until now have proven relevant to power, rather only some of them in certain combinations. We classified these combinations into five types: The "lawful" type: An actor with a multidisciplinary team that is lawful but not state-controlled has optimal chances in 'non crowded' and mono-sectoral networks with intensive state contacts, where the state does not play any important role. The "trustworthy" type: A trustworthy actor with a multidisciplinary team has optimal chances in a 'non-crowded' network with intensive state contacts and low importance of state. The "little brother" type: An actor who has powerful partners and various financing resources has optimal chances in a monosectoral network with 'equal chances', where many possible contacts remain unexplored. The "omniscient" type: A powerful actor who implements its power by imposing general or scientific information as "important" on a network with little material needs. The "redistributor" type: A powerful actor who receives occasional general information and reconstructs it in order to provide 'important' general and scientific information. It has optimal chances in a network with no scientific links. The equilibrium between the advantages and disadvantages of the method of complete network analysis has motivated thoughts about future research questions regarding the quality of regression and the insights of Heckman on the weakness of self-selection. A combined strategy of qualitative and quantitative research is necessary in order to make policy consulting applicable to politics and further theorizing more accurate. Contents 1 Introduction 1.1 Questions and aims 1.2 Concept, design and output 2 Theoretical framework 2.1 A concise form of our research concept 2.2 Power: our dependent variable 2.3 Operationalization of power for political networks: trust, incentive, irreplaceability 2.3.1Trust as a dimension of power 2.3.2 Incentive as a dimension of power 2.3.3 Irreplaceability as a dimension of power 2.4 System theory and the exchange model: applying our power dimensions 2.5 New Institutionalism: trying to find relevant independent variables 2.5.1 Theory of Organized Interests 2.5.2 The deficit of network models: rather descriptive than explanatory 2.5.2.1 Understanding the logic of the institutionalists 2.5.2.2 Empirical institutionalist models: searching for definitions with properties 2.6 Five types of power factors: How they emerged and why they are necessary 2.6.1 Building typology 2.6.2 Why a typology is necessary 2.6.3 Theoretical bases of the types 3 Methodology and illustrative examples 3.1 Applying quantitative network analysis 3.2 Advantages and disadvantages of a complete network analysis: our strategy for improvement 3.2.1 Advantages of a complete network analysis 3.2.2 Disadvantages of complete network analysis 3.2.3 The strategy of "many" indicators 3.3 Operationalization of variables 3.4 Measurement of power 3.5 Measurement of information-related variables 3.6 Measurement of organization-related and network variables 3.6.1 Organization-related variables 3.6.2 Network variables 3.7 Data 4 Presentation and qualitative analysis of the results: Anatomy of power and the five power types 4.1 Anatomy of power 4.2 The five power types 4.2.1 The three types of power accumulation factors (or structure-related factors) 4.2.1.1 The "lawful" type 4.2.1.1.1 Analysis of organizational factors 4.