Abstract

This paper examines how learning has been treated, generally, in policy network theories and what questions have been posed, and answered, about this phenomenon to date. We examine to what extent network characteristics and especially the presence of various types of brokers impede or facilitate policy learning. Next, a case study of the policy network surrounding the sustainability of palm oil biodiesel in Indonesia over the past two decades is presented using social network analysis. This case study focuses on sustainability-oriented policy learning in the Indonesian biodiesel governance network and illustrates how network features and especially forms of brokerage influence learning.

Highlights

  • The policy universe or system can be thought of as an all-encompassing aggregation of all possible state, private and social actors at various levels working within the institutions that directly or indirectly affect a specific policy area

  • The actors active in each sector or issue area can be thought of as a subset of that universe, or a policy subsystem (Cater, 1964; Freeman, 1955; Freeman & Stevens, 1987; McCool, 1998). Such subsystems are forms of social networks which encompass the interrelationships existing between elements of the policy universe active in specific knowledge and political spaces so we can find, for example, a ‘health policy network’ or subsystem, an ‘energy policy subsystem’ and so on

  • Identifying key actors in policy subsystems or networks, what brings them together, how they interact, and what effect their interaction has on a policy, are questions which have attracted the attention of many students of public policy-making and form the core of policy network theory (Keast, Mandell, & Agranoff, 2014; Kickert, Klijn, & Koppenjan, 1997; Laumann & Knoke, 1989; Rhodes, 1990, 1997; Scharpf, 1978, 1997; Sørensen & Torfing, 2007; Timmermans & Bleiklie, 1999)

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Summary

Introduction

The policy universe or system can be thought of as an all-encompassing aggregation of all possible state, private and social actors at various levels (local, regional, national, international) working within the institutions that directly or indirectly affect a specific policy area. The dominant coalition was identified by highlighting actors with high centrality in the collaboration network – based on formal working relationships during biodiesel policy development – and testing which of these actors formed a cohesive sub-group (or ‘clique’) in the matrix defined by relationships of agreement regarding the prioritizing of sustainability in biodiesel policy formulation.

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