Factors Affecting the Punctuality of Logistics Services Using Binary Logistic Regression

Abstract

The Indian logistics industry is in a period of rapid development. The purpose of this study is to analyze the factors affecting the punctuality of trucks for logistics distribution services in India based on data analysis. The data comes from 6880 pieces of data from the VTS data platform. A binary regression model was established for data analysis, and the model was tested to ensure statistical significance. Binary logistic regression was used to examine truck types, geographic locations, commodity types, order types, and suppliers for logistics services to examine significant differences between on-time and late. Binary logistic regression concluded that the shorter the distance, the signing of the perfect contract, and the selection of a specific type of vehicle, the better development of the logistics level is easier to be on time. This study provides suggestions for improving management strategies, which can be used as a reference for the development of logistics companies.