A Text Mining Approach to Identify and Analyse Freight Logistics Service Demands

Abstract

Abstract The pandemic COVID-19 has caused significant impacts on the freight supply chain, based on the data from the traffic service hotline, the time and space characteristics of calls from drivers were described, and a 2-stage LDA model was built to quickly identify the demand for freight logistics services. The results showed as follows: 1) Hotline records fluctuated significantly with pandemic policy changes; 2) The top 4 demands for freight logistics services are road conditions consultation, applying the permit for vehicles carrying essential goods and materials, refueling and gas service consultation, and traffic control complaint; 3) 10 expressways, including G45, G10 and G59, as well as the three cities of Hohhot, Ordos and Wuhai, are under great pressure to ensure the stability of supply chains; 4) Information disclosure mechanism, driver service guarantee and hotline operation mechanism need to be improved. The research results verify the effectiveness of text mining technology in describing and identifying transport service demands. The proposed technical framework promotes the transformation of transport service from extensive governance to precise governance, which can provide a reference for promoting the stability of the logistics supply chain and exploring a participative approach to managing the industry.