<![CDATA[This empirical study calculated the network centralities of urban railway stations in Seoul using Social Network Analysis (SNA) and analyzed the effect of this value on the number of passengers and average travel distance at each station. Network centrality can be calculated using various methodologies. In this study, reach, betweenness, and closeness were used as network centrality indicators. A regression model was used with the characteristics of building use in the station catchment areas as control variables. This methodology was compared to previous studies’ methods for obtaining stations’ topology values. The adjusted R2 values increased by 0.272 and 0.220 for the respective models, explaining the number of passengers and the average travel distance, respectively; the number of significant variables also increased in both models. These results indicate that defining the network centrality obtained through SNA as the station’s topology could improve explanations of the number of passengers and the average travel distance by 27.2% and 22.0%, respectively, compared to previous studies. While this methodology is not new, this study demonstrated the advantages of using SNA to determine the centrality indices of urban railway stations.]]>
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