Proceedings of ICLT 2023

EXPLAINABLE AI APPROACH FOR IDENTIFYING CRITICAL FACTORS AFFECTING ON-TIME ARRIVAL OF TRUCKS IN LOGISTICS

Panupong Wanjantuk; Ruth Banomyong

Department of Computer Engineering, Khon Kaen University, Thailand; Department of International Business, Logistics and Transport, Thammasat University, Thailand

International Conference on Logistics & Transport 2023, Helsinki, Finland, pp. 108-117

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Abstract

Purpose: Effective supply chain management depends on on-time delivery, and knowing what influences on-time arrival can help logistics organizations optimize their processes and improve customer satisfaction. This study explores the key factors that affect the on-time arrival of trucks in logistics operations using an explainable AI technique. Design/methodology/approach: This study identifies the key factors that have a significant impact on the on-time arrival of trucks using explainable AI techniques and a large dataset made up of historical delivery records, current location, transportation distance, vehicle type, supplier, material shipped, vehicle state, destination state, and other relevant factors. Findings: The research's conclusions provided clear understandings into the causes of delivery delays by shedding light on the relative significance and interplay of these factors. Research limitations: The research may face limitations due to the availability and quality of data. Access to comprehensive and up-to-date datasets containing information on various factors that influence on-time arrival of trucks in logistics might be challenging. Insufficient or biased data can affect the accuracy and generalizability of the findings. Practical implications The logistics sector will be significantly impacted by the results of the study. Logistics organizations may enhance their delivery schedules, manage resources more wisely, and put plans in place to reduce risks by developing a thorough grasp of the essential elements influencing on-time arrival. Cost reductions, increased operational effectiveness, and an overall improvement in logistics performance can result from this. Originality/value: By particularly applying explainable AI techniques to the logistics context and concentrating on the on-time arrival of trucks, this research makes a contribution to the area. The proposed technique stands out for its transparency and interpretability, guaranteeing that stakeho

Keywords

Explainable AI; On-Time Arrival; Trucks; Logistics; Delivery Delays; Transparent Insights; Operational Efficiency

Citation

Panupong Wanjantuk; Ruth Banomyong (2023). EXPLAINABLE AI APPROACH FOR IDENTIFYING CRITICAL FACTORS AFFECTING ON-TIME ARRIVAL OF TRUCKS IN LOGISTICS. Proceedings of the International Conference on Logistics & Transport (ICLT 2023), Helsinki, Finland, pp. 108-117.