<p>The evolution mechanism of railway transportation network nodes driven by sea-rail intermodal transport (SRIT), a globally prevalent logistics method, has not been thoroughly investigated. From the perspective of SRIT, this study constructed a framework for understanding the evolution of railway container transport network nodes using Northeast China from 2013 to 2020 as a case study. It leverages proprietary data from 95306 Railway Freight E-commerce Platform. By employing the hybrid EWM-GA-TOPSIS model, complex network analysis, modified gravity model, and correlation and regression analyses, this study delves into the spatiotemporal patterns and dynamic transformations of railway container freight stations (RCFS). Finally, the long-term relationship between the RCFS and SRIT is explored. The results indicate that the spatial and temporal analysis of the RCFS in Northeast China from 2013 to 2020 revealed a clear polarisation trend, with the top-ranked stations mainly concentrated near ports and important transportation hubs. Additionally, the RCFS exhibited an expansionary trend; however, its development was uneven, and there was a significant increase in the number of new stations compared to abandoned stations, indicating an overall positive growth tendency. Moreover, the intensity of the SRIT at the RCFS in Northeast China notably increased. A significant positive linear relationship exists between SRIT and the freight capacity of all stations. A relatively pronounced correlation was observed for high-intensity stations, whereas a relatively weak correlation was observed for low-intensity stations. This study not only provides an effective framework for future research on RCFS within the context of SRIT but also serves as a scientific reference for promoting the implementation of the national strategy for multimodal transportation.</p>