## 6 Conclusions
Second, in terms of empirical insights, it reveals how freight system structure emerges from the interplay of infrastructure dependency, cargo attributes, and regulatory constraints. Last, in terms of policy frameworks, it provides evidence for precision management strategies. For example, nighttime operation incentives are implemented to reduce tolls at night for closed-loop transportation hubs, leveraging the off-peak period to absorb the internal flow demand and relieve the pressure on the roads around the port area during the day. Notably, the policy recommendations are fundamentally anchored in the structural stability of freight-function relationships. This spatial pattern is not transient but reflects long-term dependencies on infrastructure and the structural stability of freight-function relationships, ensuring that policies targeting these linkages address systemic rather than short-term dynamics. Despite its contributions, the study has a few primary limitations. First, the reliance on trajectory-derived trip data may introduce biases compared to direct survey data, although this is a pragmatic compromise given the availability and representativeness of alternative datasets. Second, the absence of high-quality POI data limited our ability to validate micro-level activity purposes. While POI data theoretically capture land use functions, issues like missing records for SMEs and inconsistent categorization led to incomplete insights. For instance, unrecorded SME locations in POI datasets caused the underrepresentation of FT-driven peripheral market demands. Future research should leverage advancements in data governance to integrate refined POI datasets. Additionally, expanding the framework to other cities with diverse industrial structures would enhance its generalizability. Third, while the study provides critical insights for Shanghai's immediate policy needs, long-term data integration is essential to validate the stability of freight-function relationships over the years. Future work should explore how seasonal industrial fluctuations or infrastructure upgrades reconfigure these patterns. Fourth, due to the timeliness of the used data, the spatial interactions identified herein should be interpreted as estimates of the freight system's structure at the time of data collection. While the study's framework emphasizes structural stability, future research should incorporate more recent datasets to validate whether these spatial associations persist amid evolving urban landscapes. Last, the fixed grid resolution may not adapt to different urban areas. We plan to replace it with dynamic zones defined by road networks in future works, allowing the freight routes and functional boundaries to align more naturally. By addressing these gaps, and as more data become available, future studies can validate our findings across multiple cities with diverse urban layouts to further refine the understanding of how urban form and freight mobility co-evolve, supporting the development of adaptive, sustainable freight systems. Conceptualization, R.P. and Q.Y. ; Methodology, R.P. and C.L. ; Software, C.L. and J.C.; Validation, C.L. and J.C.; Investigation, R.P. and C.L. ; Writing--original draft, R.P. and C.L. ; Writing--review and editing, Q.Y. and X.L. ; Visualization, R.P. and J.C.; Project administration, Q.Y. and X.L. All authors have read and agreed to the published version of the manuscript. **Funding:** Shanghai Municipality Science and Technology Commission (Grant ID: 24692106600). **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The data presented in this study are available on request from the corresponding author. **Conflicts of Interest:** The authors declare no conflict of interest.