Forecasting time-varying logistics distribution flows in the One Belt-One Road strategic context

This work presents a multi-methodological approach to address the dynamic and stochastic challenges that underlie the problem of international logistic network reconfiguration induced by the One Belt-One Road initiative. A spatial-temporal logistics interaction model integrated with Markov chain is proposed to forecast time-varying logistic distribution flows for a three-layer supply chain framework. Further, numerical forecasts based on two cases of Chinese oil supply chain is carried out to account for the effectiveness of the proposed model. Analytical results suggest various development strategies for the practitioners and the policy makers in optimizing their logistics and transportation decisions in the OBOR context.