Between crisis and reform: developing a causal mechanism of Indonesian healthcare reform with process tracing

Abstract

Purpose The article discusses social policy changes, connecting insights on successful reform in the Indonesian healthcare system with a causal mechanism through which the policy has been transformed. Design/methodology/approach The study employs modified Bayesian process tracing to examine how the Indonesian production regime and political bargains from 1998 to 2014 influenced these reforms. It commences with generating synthesized mechanisms based on previous studies, which are then tested using 25-elite interview data as a primary source. The analytical strategy then connects the theoretically expected causality with data, reconstructing a revised graph of causal mechanisms that links the crisis and reforms for theory-building. Findings A principal causal mechanism connecting crisis and reform was discovered, namely, policy entrepreneurs’ cooperation mechanism, which highlights the role of policy entrepreneurs, particularly welfare bureaucrats and Academic Administrative Entrepreneurs, in driving policy solutions that align with political interests, especially under conditions of uncertainty. In addition, based on the modularization analysis, an additional mechanism was identified, namely the policy learning-driven interest-interdependence mechanism. It illustrates how policy reform experiences from external contexts were assimilated domestically to address a domestic political concern. Originality/value The implication of the article to literature is outlined. Theoretically, a process-oriented analysis of Indonesian healthcare mitigates the bias of power-resources-based mechanisms in connecting crisis and reform, as illustrated in previous studies and general social policy scholarship in developing countries. Moreover, this article demonstrates that crises alone are insufficient drivers of systemic reform without endogenous changes that have already set in motion a cumulative process of divergence from the existing path. In the meantime, methodologically, this article shows broader relevance in enhancing the understanding of the complementary role of inductive reasoning within the Bayesian process-tracing model.