Prediction of Promising Vacant Logistics Technology using Patent Data Analytics in Latin America

In recent years, the lack of relevant technological infrastructure for innovation in logistics technology in Latin American nations with significant economic expansion has been a factor impeding economic growth. In this case, even though Latin American nations are actively pursuing policies to revive technical innovation, there is an issue with the absence of objective data for policy formation. We suggests a strategy for revitalizing technical innovation through the utilization of promising vacant technologies predicted by patent data analysis. Using GTM, ARIMA, technology mapping, and decision tree analysis, promising vacant technology groups and technological keywords were identified from 670 logistics-related patents extracted between 2010 and 2020. As a result of the investigation, “Multimodal Transportation” and “Simulation-Based Distribution Optimization” derived based on important technology keywords, is perceived as a required technology to revitalize technological innovation in Latin American nations with large territories. The research results can be used as objective data for policymaking to stimulate technical innovation, contributing to more objective policymaking in Latin American countries.