Research on the spatial structure of tourism economic networks remains limited, whereas understanding how tourism economic components are interconnected and interact within a geographical area is crucial. This study aims to fill these limitations by analyzing the strength of interaction and the spatial structure of the tourism economic network in East Java, both now and in the future. This research employs a modified gravity model that integrates big data as a proxy for tourism economic variables. Spatial network analysis was conducted using Spatial Design Network Analysis (SDNA) with four centrality algorithms. The results showed that the main centers or hubs of the tourism economic network in East Java are Batu City, Malang Regency, and Surabaya City, based on the total number of nodes or variables. While the analysis per variable revealed differences in the main centers, indicating complexity and diversity in the interactions, connections, and clusters of the tourism economic network in East Java. Road network planning in the East Java Provincial RTRW until 2043 is predicted to have a significant impact on the connectivity, attractiveness, and accessibility of the road network, which in turn will affect tourism economic growth in East Java. However, the uneven improvement of accessibility, especially in Madura Island, is a challenge in itself. This research offers valuable insights into the spatial dynamics of the tourism economic network in East Java and its implications for regional economic development, providing policy recommendations to optimize the impact of road network planning on the tourism sector.
Handoko et al. (Tue,) studied this question.