Indonesia’s production network is organized around multiple Java-centered rich cores

Indonesia’s national economy is not stitched together by a single dominant production hub, according to a new network analysis of the country’s internal trade flows. Using the 2016 Interregional Input–Output table, researchers mapped intermediate transactions between provinces and economic sectors as a weighted, directed network of 578 province–sector nodes, then applied a combination of community detection, rich-club analysis, rich-node enrichment testing, and backbone extraction to reveal how the network is organized at the mesoscale.

The analysis, published in Applied Network Science, shows that production communities in the network are predominantly geographic rather than sectoral. Communities align strongly with provinces and island groupings rather than with sector labels, meaning that Indonesia’s internal production blocs are spatially cohesive but multi-sector. Within each community, particular sector groups dominate internal value added and the channels linking the community to the rest of the network, giving each regional bloc a distinct production profile.

At the center of the structure, the rich-club and enrichment analyses point to a pattern of multiple spatially grounded rich-core communities rather than a single dominant production community absorbing all economic centrality. This multiple rich-core structure is Java-centered at the national mesoscale: the study identifies Java-based manufacturing production cores, a service-intermediation role for Jakarta, a hybrid service–manufacturing role for East Java, and resource-processing or resource-supplying interfaces outside Java. An island-constrained test gave the strongest support to the Jakarta-centered community as the network’s most central rich core.

The analysis also examined the network at finer spatial resolutions. Selected communities outside Java, especially in resource-producing regions, showed supplier-side concentrations of rich nodes when the network was examined at finer resolution, suggesting that economic centrality in Indonesia is not exclusively concentrated on Java but is distributed in spatially specific ways across the archipelago.

Between the communities, the inter-community backbone revealed a Java-centered strongest-corridor structure linking western, central, and eastern Indonesia through Jakarta and East Java. A redundancy-preserving comparison using a PMFG network, which retains additional high-weight routes beyond a simple backbone, showed that the Jakarta-centered and East Java communities remain structurally important gateway positions even when alternative connections are taken into account. This points to a corridor dependence in how value flows between the western, central, and eastern parts of the country.

The authors emphasize that the findings, based on the 2016 input–output table, offer a structural snapshot of flow concentration and corridor dependence rather than a dynamic picture. They position the mesoscale framework as a basis for future analysis of how shocks might propagate through the network, and as a systematic way to understand how spatial production communities, rich-node concentration, and interregional gateway corridors jointly shape Indonesia’s economy, with implications for spatial inequality, national integration, and structural dependence.

Subject of Research: Mesoscale community structure and rich-core organization of Indonesia's intranational production network

Article Title: Community detection reveals multiple rich cores in Indonesia’s intranational production network

Article References: Maulana, A., Pradono, P., Aritenang, A. F., & Situngkir, H. (2026). Community detection reveals multiple rich cores in Indonesia’s intranational production network. Applied Network Science. https://doi.org/10.1007/s41109-026-00828-w

Image Credits: AI Generated

DOI: 10.1007/s41109-026-00828-w

Keywords: Indonesia, production network, input-output analysis, community detection, rich-club, economic geography, Java, Jakarta, interregional trade, network science, spatial inequality, Community