An increasing number of research has provided insights for an understanding of network alliances among multiple social entities across sectors (i.e. public agencies, legislative offices, non-governmental organizations, and... [ view full abstract ]
An increasing number of research has provided insights for an understanding of network alliances among multiple social entities across sectors (i.e. public agencies, legislative offices, non-governmental organizations, and private sector organizations). The network system has limited the power of government in many ways, yet created new opportunities for social entities to solve complex social problems collaboratively in both policy-making and implementation processes (Salamon, 1995). However, little is known about the variance of structures and compositions of these networks across policy contexts, and all policy networks have been treated as if they are similar.
Thus, we will present comparative findings from three policy networks in different policy contexts: (1) a R&D policy network, (2) a broadcasting industry-related policy network, and (3) an ICT industry policy network. These three policy networks include key policy actors and stakeholders such as government agencies, legislative committees, industry associations, private sector organizations. Three social network datasets are being currently collected in the Ministry of Science, ICT, and Future Planning (MSIP), a Korean central government agency in charge of planning and evaluating science and technology-related policies, support scientific R&D projects. A noteworthy feature of this study is that three datasets deals with different policy areas governed by a same agency it is expected to obtain in-depth knowledge about factors affecting social network structure or governance structure in each policy area.
The social network data capture relationships among various policy actors in the policy area. At the same time, the data was also designed to measure the involving parties’ meta-cognition on given policies and how it differs depending on their sectoral membership. The data will be analyzed using UCINET to analyze and visualize the structure of three policy networks. The data will be further analyzed to see the level of congruence of meta-cognition among actors.
The initial interviews clearly show that each of these policy areas is governed by a different set of players and rules and that MSIP plays a different role in each policy area. For example, in the R&D policy network, MSIP governs other involved central government agencies and play a role as a coordinator and negotiator which intervene conflicts among different actors in a highly contentious policy environment. On the other hand, MSIP plays a role as a facilitator and director in the other two networks by both bringing as many players as possible at the table for discussion of important matters and regulating behavior of private sector organizations at the same time. We have also found that in a science and technology policy context, research and technical support organizations as well as industrial and professional associations play an important role in shaping the networks. The paper concludes with a discussion of propositions and implications for public managers about how to manage the governance system and their relationships with stakeholders.
