Identifying temporal patterns of multilateral spatial interactions: Using international trades as an example

Abstract

AbstractGravity models, popular for estimating spatial interactions, assume independent spatial interactions from locations to all other locations and, therefore, overlook potential latent multilateral influences in play. This research combines self‐organizing map (SOM) and trajectory analysis to classify patterns of spatial interactions and trace changes in the patterns simultaneously across all locations and decipher the development and dependence of multilateral interactions in space and time. We use international trading among 207 countries from 1900 to 2014 to demonstrate the proposed SOM–trajectory analysis. We create SOMs of annual international trade for all countries, trace each country's changes in trading patterns over 115 years, and compare the trajectories for countries. The combined SOM–trajectory analysis elicits the hidden trading development and geographic influences brought into play. The proposed method is adaptable to other domains of spatial interactions (e.g., immigration) to characterize the temporal patterns of multilateral spatial interactions at locations individually or contextually.