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Wang, Guang-Xu
Languages: English
Types: Unknown
Subjects:
Taiwan adopted its National Health Insurance (NHI) scheme in 1995. Presently, the scheme covers virtually all of the island’s citizens. However, it is under the threat of a serious imbalance between expenditure and revenue. As spending has become unsustainable, everyone has realised the need for financial reform. However, the reform process itself is beset by political confrontations. There is a need to deepen the understanding of the relationships and dependencies among the policy actors. With a view to helping address this problem, this study empirically examines the multiple types of ties prevailing between the policy actors and the resulting power distribution while the DPP government was working earnestly towards reforming the NHI’s financial system in the period 2000-2008. Apart from official documents, data are drawn from a network survey coupled with semi-structural interviews of 62 policy actors including government officials and related unofficial policy participants. Measures such as the in-degree centrality index and core/periphery model, betweenness centrality, structural hole index (effective size), density index, E-I index and CONOOR procedure (Blockmodeling and multidimensional scaling - MDS) are used to identify the major participants and network structures in the NHI domain and assess their relative influence-powers on the basis of information transmission patterns, resource exchanges, action-set coalition relationships and reputational attributions. It is shown that, although the public sector and the medical associations were at the helm of the NHI reform, financial reform remained unfulfilled mainly because of poor communications among societal actors. We then performed a social network analysis and systematically mapped the prevailing political conflicts among diverse policy stakeholders. We confirm that SNA is an effective research tool for political feasibility evaluation; it can facilitate smoother policy adoption by enhancing better interactions within networks.
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