Application of the Hungarian Method for Reducing Shipping Delays in Online Retail Logistics

Abstract

The expansion of electronic commerce has transformed retail markets worldwide, making efficient logistics management a critical factor for business success. Among the various operational challenges faced by online retailers, shipping delays remain one of the most significant issues affecting customer experience and organizational performance. Delayed deliveries not only increase operational costs but also reduce customer trust and loyalty. The present study explores the applicability of the Hungarian Method as an optimization tool for minimizing shipping delays in online retail logistics through efficient assignment of delivery resources. The research adopted an empirical and analytical approach using shipment data collected from five regional distribution centers and five delivery partners serving customers across different districts of Jharkhand, India. A dataset comprising 300 customer orders was analyzed. Delivery times between warehouses and customer locations were arranged in the form of a cost matrix, where the Hungarian Algorithm was employed to determine the optimal assignment of delivery resources. The optimized allocation model was subsequently compared with the conventional allocation strategy currently used in logistics operations. The results demonstrated a substantial improvement in delivery performance after implementing the Hungarian Method. The average order fulfillment time was reduced from 6.2 days to 4.3 days, representing a decrease of approximately 30.6%. The total delay hours associated with the sample orders declined from 1,620 hours to 1,085 hours, resulting in a reduction of 33.0%. In addition, vehicle and delivery personnel utilization improved from 74% to 89%, indicating more efficient use of available logistics resources. A customer feedback survey conducted among 200 respondents revealed that satisfaction levels increased from a mean score of 3.5 to 4.4 on a five-point scale following the implementation of the optimized delivery schedule. Statistical testing confirmed that the observed improvements were significant at the 0.05 level.

Introduction

The text examines the use of the Hungarian Method (Hungarian Algorithm) for reducing shipping delays and improving delivery efficiency in e-commerce logistics. The rapid growth of online shopping has increased customer expectations for faster deliveries, real-time tracking, and reliable service. Since logistics operations, especially last-mile delivery, strongly influence customer satisfaction, efficient resource allocation has become essential.

Shipping delays occur due to several factors such as poor resource allocation, traffic issues, warehouse bottlenecks, demand variations, weather conditions, and transportation disruptions. The study highlights that Operations Research (OR) techniques, particularly assignment optimization, can help solve these logistics challenges by allocating delivery resources effectively.

The research focuses on applying the Hungarian Method to assign delivery resources (vehicles, drivers, and routes) optimally to minimize delivery time and delays. The study is conducted in Jharkhand, India, using data from five regional distribution centers, five delivery partners, and 300 customer orders.

Objectives of the study:

• Analyze the impact of optimized delivery resource allocation.
• Compare conventional allocation methods with the Hungarian Method.
• Reduce delivery delays and improve logistics performance.
• Evaluate effects on customer satisfaction and resource utilization.

Methodology:
The study uses a quantitative and analytical approach:

• Data collected from delivery records and customer surveys.
• A cost matrix was developed based on delivery times between delivery partners and destinations.
• The Hungarian Algorithm was applied to find the optimal assignment.
• Results were compared using performance indicators such as delivery time, delay hours, vehicle utilization, and customer satisfaction.
• Statistical validation was performed using a paired-sample t-test.

Results after applying the Hungarian Method:

• Average delivery time reduced from 6.2 days to 4.3 days (30.65% improvement).
• Total delay hours reduced from 1,620 to 1,085 hours (33.02% reduction).
• On-time deliveries increased from 68% to 87%.
• Vehicle utilization improved from 74% to 89%.
• Delivery personnel utilization increased from 76% to 91%.
• Customer satisfaction improved from 3.5 to 4.4 out of 5.

The optimized system also increased faster deliveries:

• Orders delivered within 1–3 days increased from 42 to 96.
• Orders taking more than 7 days reduced from 68 to 20.

Customer feedback showed improvements in:

• Delivery speed.
• Reliability.
• Tracking accuracy.
• Overall service quality.

The statistical analysis confirmed that improvements from the Hungarian Method were significant (p < 0.001), proving that optimized assignment improves logistics performance.

Conclusion

The present study investigated the application of the Hungarian Method as an optimization tool for minimizing shipping delays in online retail logistics. The findings clearly demonstrate that assignment-based optimization significantly improves logistics performance by enabling the efficient allocation of delivery resources. By applying the Hungarian Algorithm to delivery assignment decisions, the study achieved substantial reductions in average delivery time and total delay hours while simultaneously improving on-time delivery rates, customer satisfaction, and resource utilization. The optimized logistics model reduced the average delivery time from 6.2 days to 4.3 days and decreased total delay hours by approximately 33%, indicating that mathematical optimization can effectively address inefficiencies in delivery operations. Furthermore, improvements in vehicle and delivery personnel utilization revealed that higher operational performance can be achieved without increasing the number of available resources. These findings highlight the economic benefits of optimization-based decision-making in logistics management. Customer satisfaction analysis further demonstrated that faster and more reliable deliveries positively influence customer perceptions of service quality. As customer expectations continue to rise in the rapidly expanding e-commerce sector, organizations must adopt efficient and data-driven logistics strategies to maintain competitiveness and ensure long-term sustainability. The statistical significance of the results confirms that the Hungarian Method is a reliable and practical decision-support tool for logistics managers. The study contributes to the growing application of Operations Research techniques in e-commerce logistics and provides empirical evidence that optimized resource allocation can enhance delivery performance while reducing operational inefficiencies. Overall, the research concludes that the Hungarian Algorithm offers a cost-effective, scalable, and scientifically sound approach for improving logistics operations. Its adoption can help online retailers reduce shipping delays, increase customer satisfaction, maximize resource utilization, and strengthen their competitive advantage in the dynamic e-commerce marketplace.

References

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Copyright

Copyright © 2026 Mithilesh Kumar Choudhary, Dr. Ziaul Hoque. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.