Poverty Alleviation From The Perspective Of New Public Governance: Multi-Actor Collaboration And Public Value Creation In Gorontalo City
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This study aims to analyze poverty alleviation from the perspective of New Public Governance through multi-actor collaboration, data governance, and its implications for public value creation in Gorontalo City. The study employed a qualitative approach using a case study design. Data were collected through in-depth interviews, observation, and document analysis of poverty alleviation policies and programs. Informants were selected using purposive sampling based on their direct involvement in the planning, implementation, coordination, and evaluation of poverty alleviation programs, consisting of local government institutions, sub-district authorities, social institutions, supporting agencies, and academics. Data were analyzed using the interactive model of (Matthew B. Miles et al., 2014), including data condensation, data display, and conclusion drawing and verification. The findings indicate that poverty in Gorontalo City is multidimensional, involving economic, social, educational, health, infrastructure, and economic opportunity dimensions. Multi-actor collaboration has involved government institutions, universities, social organizations, supporting agencies, and communities; however, the process remains government-centered, making co-production and co-creation suboptimal. The study also finds that sectoral ego, institutional interests, program fragmentation, and weak data integration are the main barriers to effective collaboration. The novelty of this study lies in its argument that data governance functions as a mediating mechanism linking multi-actor collaboration and public value creation. Collaboration does not automatically generate public value unless supported by valid targeting data, interoperability among actors, and transparent verification mechanisms. This study recommends strengthening permanent collaborative forums, integrating cross-sectoral poverty data, enhancing the role of sub-districts and urban villages as data validation nodes, and transforming policy orientation from social assistance toward sustainable economic empowerment.
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