E-commerce Logistics Research Articles

Cargo Volume Forecasting for Logistics Sorting Centers Based on Random Forest Model

With the rapid development of logistics industry, logistics sorting center, as a key node in e-commerce logistics network, its cargo volume prediction and personnel scheduling strategy are of great significance to improve operational efficiency and reduce costs. The purpose of this study is to deeply analyze the cargo volume data of 57 sorting centers through machine learning method, establish an accurate cargo volume prediction model, and optimize the personnel scheduling strategy based on the prediction results. In this study, we preprocess the historical cargo data, including missing value filling, time series conversion and feature construction. Then, the random forest model was used to carry out fitting analysis on the cargo volume data of different sorting centers. By comparing the evaluation indexes such as mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE), the superiority of random forest model compared with neural network, support vector regression and linear regression models was verified. This study not only improves the accuracy of cargo volume forecast, but also realizes the reasonable allocation of human resources, and provides scientific decision support for the operation and management of logistics sorting center.

A Study on Strategic Approaches to Efficient Sustainable Logistics

With the fast evolution of eCommerce, logistics is vitally involved in ensuring-with due efficiency-the movement of goods from the seller to the buyer. In an environmental sense, such efficiency would mean cost and time optimization, matching expectations of swift, timely product delivery. However, with growing environmental concerns, the need for sustainable logistics becomes no less critical. This research will dwell on strategic paths to balancing logistics efficiency with sustainability, leveraging state-of- the-art technologies such as Artificial Intelligence and automated route optimization. The study further proposes the integration of electric vehicles and green logistics practices in the sector of e-commerce, especially in the Delhi NCR region. It will quantify, through qualitative analysis, the effect that these techniques have on the environmental performance of sustainable logistics-such as carbon footprint reduction and general economic efficiency. Key Words eCommerce logistics, Sustainable logistics, Artificial intelligence (AI), Automation in logistics, Electric vehicles, Carbon emissions reduction, Route optimization, Eco-friendly packaging, Logistics efficiency, Environmental sustainability

Управление логистическими процессами в трансграничной электронной коммерции

In the context of the globalization of the economy and the development of cross-border e-commerce, the importance of cross-border logistics is increasing, allowing for an effective process of product distribution. The issues of organizing transport and logistics processes during the delivery of goods within the framework of the functioning of cross-border e-commerce are discussed. The main aspects of the development of e-commerce logistics and its impact on the trading business have been studied. An analysis of the cross-border e-commerce market in Russia is carried out. It is noted that currently the global logistics industry is in an unstable environment. The main directions and trends in the development of logistics services in modern conditions are considered and the specifics of adapting the process of goods distribution within the framework of cross-border e-commerce to changes in the external environment are investigated. The distinctive features of e-commerce logistics have been studied in the context of its impact on the trading business, which allows for increased efficiency of logistics processes such as procurement, transportation, order processing, inventory and warehouse management, packaging and labeling. It has been proven that with the development of information technology and telecommunication networks, as well as increasing demand in the field of online trading, the need for effective logistics support is significantly increasing, and delivery speed is becoming increasingly important to provide quality service to consumers. The advantages of e-commerce are substantiated from the perspective of subjects of trade and logistics activities, which include the global nature of customer coverage and the convenience of inter-subject interaction, reduction of operating costs of trade and logistics activities, expanded opportunities for marketing and advertising support, increased level of automation of e-commerce logistics management processes.

Enhancing Supply Chain Management Through Artificial Intelligence: A Case Study of JD Logistics

With the intensification of global economic competition, enterprises face the challenge of improving the supply chain management efficiency, and AI technology, as an emerging field in computer science, can provide effective solutions. As a leading e-commerce logistics service provider in China, JD Logistics has accumulated a wealth of logistics technology capabilities and digital transformation experience within and outside the JD Group. Using JD Logistics as a case study, this paper discusses the application of AI technology in supply chain management and its impact on enterprise responsiveness and operational efficiency. AI technology has significantly improved the supply chain operational efficiency and responsiveness of JD Logistics by applying intelligent supply chain planning, predictive analysis and intelligent decision-making. The study systematically summarizes the key role of AI technology in optimizing supply chain management through a literature review and specific case studies, providing an important reference and practical experience for enterprises to achieve digital transformation.

패션산업 전자상거래에서 물류 서비스가 고객만족도에 미치는 영향

Purpose: A s t he c ommerce m arket r apidly c hanges d ue t o t echnological a dvancements and consumer preferences, the competitiveness of logistics services is highlighted. This study analyzes the factors of logistics in fashion industry e-commerce that affect customer satisfaction. The goal is to provide insights to fashion companies to develop logistics strategies. Research design, data, and methodology: In the research model for empirical analysis, the logistics service factors are reliability, economy, convenience, and speed. Data obtained via questionnaire were analyzed for multiple regression and moderating effects. Results: As a result of the analysis, the logistics service factors that provide economy, convenience, and speed had a significant impact on customer satisfaction. There were significant differences in customer satisfaction based on gender and age. Conclusions: Fashion companies must provide a variety of logistics services, and need to improve customer satisfaction through continuous service improvement.

Parcel-Locker-Sharing Model for E-Commerce Logistics Service Providers

In the e-commerce last-mile delivery process, the asset operators (logistics service providers who own parcel locker facilities) support their delivery service with parcel lockers, while the non-asset operators (logistics service providers without parcel lockers) perform door-to-door delivery. Due to demand fluctuation, asset operators’ parcel-locker slots may be left vacant, while non-asset operators are stuck with the high-cost door-to-door service. The exclusiveness of parcel-locker usage reduces resource utilization and service efficiency in last-mile delivery. Therefore, this paper proposes a parcel-locker-sharing model in which these two parties share the parcel-locker capacity in last-mile delivery. The asset operator rents the unused parcel lockers to the non-asset operator by charging a rental fee,while the non-asset operator rents the parcel lockers for delivery to save logistics costs. The motivation of this alliance is to increase the profits of both parties and that of the total supply chain. This study establishes the supply-chain profit model for the parcel-locker-sharing framework and finds that the profit or loss depends on the comparison of the operation cost savings and delivery-cost savings. A numerical analysis is conducted to validate the final result. The research further suggests the optimal rental quantity and price interval. This paper is the first to study the operational mechanism of sharing the parcel locker between two distinct types of logistics service providers and to offer recommendations for industrial application.

Assessing the spatial footprint of e-commerce logistics differentiating the types of warehouses: The case of Amazon in the United States

Assessing the spatial footprint of e-commerce logistics differentiating the types of warehouses: The case of Amazon in the United States

The Key Factors for Improving Returns Management in E-Commerce in Indonesia from Customers’ Perspectives—An Analytic Hierarchy Process Approach

The rapid growth of e-commerce has led to an increase in the number of product returns in supply chains, which is both environmentally and economically challenging. E-commerce companies need to effectively manage product returns, as this has a direct impact on their reputation and consumer experience. Reducing returns is key to maintaining sustainable practices for online product sales. A significant increase in e-commerce transactions is also evident in Indonesia, which is the fourth largest country in the world. Despite the very large size of the market, research on e-commerce in the business-to-customer (B2C) market in Indonesia is underrepresented in the literature. The purpose of this paper is to identify key factors from the customer perspective that influence product returns in reverse logistics in Indonesian e-commerce. The novelty of this study stems from the focus on the customer perspective on product returns in the B2C market when shopping online and the spatial scope. Due to the uncertainty inherent in multi-criteria decision making, the analytic hierarchy process (AHP) method was used to rank factors and potential solutions derived from a critical literature review. As a result, the study provides a ranking of factors and alternatives for managing e-commerce returns in Indonesia. The results show that among Indonesian e-commerce customers, product quality (QP) was rated the highest, while (Pu) was rated the lowest. In terms of the alternatives that are the most suitable for improving the customer experience of e-commerce product returns in Indonesia, a clear returns policy (CRP) scored the highest, while the merchandise catalog (Cat) was rated as the lowest priority.

Solving low-carbon last mile delivery problem using discrete marine predators algorithm

With the increasing concentration of greenhouse gases, carbon peaking and carbon neutrality have gradually become a global issue. As the last link of e-commerce logistics, the last mile delivery should not only focus on customer satisfaction and enterprise cost, but also reduce carbon emission and promote green development. In order to solve the last mile delivery problem, this paper builds the last mile delivery model for two common delivery vehicles, considering the impact of transportation cost, carbon emission and customer satisfaction on the last mile delivery path planning. The last mile delivery is an NP-hard problem, a novel Discrete Marine Predators Algorithm(DMPA) is proposed to solve the problem, which combines neighborhood search strategy and RS hybrid operator. Six different test examples are generated based on Solomon for simulation experiments, and the experimental results verify that the proposed algorithm is obviously superior to the marine predators algorithm, simulated annealing algorithm and genetic algorithm. DMPA obtains significantly higher customer satisfaction than other algorithms. The customer satisfaction of C101 and C201 is as high as 0.99, which is close to the optimal value of 1. DMPA can achieve lower transportation costs and less carbon emissions compared with other algorithms. DMPA reduces the transportation cost by at least 61.12$ and the carbon emission by at least 1033.64 kg for C101 by minivan delivery. DMPA reduces the transportation cost by at least 28.89$ and the carbon emission by at least 210.9 kg for C101 by electric tricycle delivery. It can effectively reduce carbon emission, lower transportation cost, improve service level, and promote the integration of the dual carbon target with the internal requirements of national development.

The death of language barriers? An empirical study based on China’s cross-border e-commerce

ABSTRACT Based on China’s cross-border e-commerce (CBEC) logistics order data from 2017 to 2019, we examine the impact of language barriers on CBEC. By constructing a comprehensive language barrier index, we find that, unlike offline trade, China exhibits higher CBEC exports to countries with greater language barriers. Mechanism analysis indicates that this positive correlation arises from CBEC effectively overcoming phonological linguistic disparities and compensating for the offline trade gap caused by language barriers. Our study contributes to understanding the evolution of the gravity model in the context of CBEC and provides new insights into international business activities.

The Improvement of Logistics Management in China: A Study of the Risk Perspective

This paper identifies and empirically validates the potential risks in overseas third-party logistics services that support sustainable cross-border e-commerce logistics in China. This research addresses a significant gap in the current literature by conducting a comprehensive literature review and case study, primarily focusing on third-party logistics services’ benefits without adequately discussing the associated risks. Our study highlights the medium and high risks in forwarding and contracting processes, such as cost uncertainty, quality issues, and cultural and language differences. The findings contribute to academic research and practical applications by providing a theoretical foundation and practical guidance for enhancing logistics management in China’s sustainable cross-border e-commerce. This research promotes the resilience and sustainability of cross-border e-commerce supply chains and offers valuable insights for overseas 3PL service providers looking to expand their operations in China.

Cross-Border E-commerce Logistics System Optimization Analysis

Cross-border e-commerce is a rapidly growing market segment that means high-quality logistic support for long-term growth. This paper investigates the peculiarities of present cross-border e-commerce logistics conditions, defines existing challenges, and suggests improvement ideas. In this case, the study reviews literature and case studies to examine the issues affecting cross-border logistics, including long transit times, high freight costs, and bureaucratic formalities in accessing various customs. This research is designed to help readers understand the specific forces that affect logistics configuration and suggest methods to improve the performance and quality of the logistics services being delivered to customers. Through the realization of these optimization measures, the study will aim to play a significant role in enhancing the sustainable growth of the cross-border e-commerce sector and preventing it from being out-competed in the world market. The findings of this research highlight the critical strategies and technological innovations necessary to address these challenges and demonstrate their potential to improve logistics efficiency and reduce costs significantly.

Customer Satisfaction and Repurchase Intention in Terms of E-Commerce Logistics Service Quality and Recovery Service

Abstract The shift from traditional markets to digital markets makes the community's need for expedition services very high. The increasing number of business competitors in electronic services requires companies to always pay attention to consumer needs and try to meet consumer expectations by providing quality electronic services that can create customer satisfaction. This study aims to determine the effect of E-Service Quality and E-Recovery Service on Repurchase Intention through Customer Satisfaction as a mediating variable. The type of research used is explanatory research with a quantitative approach. The sample is 100 respondents who are J&T Express Indonesia customers who have submitted complaints to the X @jntexpressid. Data analysis used is PLS- SEM analysis with mediating effect. The results showed that: the E-Service Quality had a significant direct and indirect effect on Repurchase Intention through Customer Satisfaction;variable E-Recovery Service is not a significant direct effect on Repurchase Intention but an indirect significant effect on Repurchase Intention through Customer Satisfaction; Customer Satisfaction as a mediating variable significant effect on Repurchase Intention. Abstrak Pergeseran pasar tradisional ke pasar digital menjadikan kebutuhan masyarakat akan jasa ekspedisi sangat tinggi. Meningkatnya jumlah pesaing bisnis dalam layanan elektronik menuntut perusahaan untuk selalu memperhatikan kebutuhan konsumen serta berusaha memenuhi harapan konsumen dengan memberikan kualitas pelayanan elektronik yang dapat menciptakan kepuasan konsumen. Penelitian ini bertujuan untuk mengetahui pengaruh E-Service Quality dan E-Recovery Service terhadap Repurchase Intention melalui Customer Satisfaction sebagai variabel mediasi. Jenis penelitian yang digunakan adalah explanatory research dengan pendekatan kuantitatif. Sampel sebanyak 100 responden yang merupakan pelanggan J&T Express Indonesia yang pernah mengajukan keluhan kepada akun X @jntexpressid. Analisis data yang digunakan adalah analisis PLS-SEM dengan efek mediasi. Hasil penelitian menunjukkan bahwa: variabel E-Service Quality berpengaruh signifikan secara langsung dan tidak langsung terhadap Repurchase Intention melalui Customer Satisfaction; variabel E-Recovery Service tidak berpengaruh signifikan secara langsung terhadap Repurchase Intention namun berpengaruh signifikan secara tidak langsung terhadap Repurchase Intention melalui Customer Satisfaction; Customer Satisfaction sebagai variabel mediasi berpengaruh signifikan terhadap Repurchase Intention.

E-commerce logistics management cargo volume prediction research: a cargo volume prediction system constructed based on LSTM models

E-commerce logistics management cargo volume prediction research: a cargo volume prediction system constructed based on LSTM models

Transforming E-Commerce Logistics: Sustainable Practices through Autonomous Maritime and Last-Mile Transportation Solutions

The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the maritime industry’s digital transformation, the study identifies key features and proposes a forward-looking autonomous maritime and last-mile transportation system. Emphasizing the role of geospatial technologies, the proposed system employs GIS-based electronic route optimization for efficient goods delivery, integrating onboard and ashore GIS-based sensors for enhanced location precision. A case study was built to analyze the implementation of autonomous means of transport along the route of a product from factory to customer. The integration of autonomous systems shows substantial improvements in logistics performance. Synchromodal logistics and smart steaming techniques can be utilized to optimize transportation routes, resulting in reduced fuel consumption and emissions. The findings reveal that autonomous maritime and last-mile transport systems can significantly enhance the efficiency, flexibility and sustainability of e-commerce logistics. The study emphasizes the need for advanced technological integration and provides a comprehensive framework for future research and practical applications in the logistics industry.

Delivering Goods Sustainably: A Fuzzy Nonlinear Multi-Objective Programming Approach for E-Commerce Logistics in Taiwan

With the booming development of e-commerce, the importance of controlling carbon emissions has become increasingly prominent in Taiwan. This study explores the trade-offs among time, cost, quality, and carbon emissions (TCQCE) in e-commerce logistics. Will carbon emissions mitigation lead to decreased logistics efficiency and increased costs? This article differs from other studies that use precise numbers and linear model situations. This study adopts fuzzy theory, nonlinear methods, and multi-objective programming models closer to the actual situation to study the decision-making between delayed logistics delivery times and reduced carbon emissions. This article also uses Project D as a case to enhance readers’ understanding of decision-making methods in real-life e-commerce logistics cases. The results show that extended delivery times could significantly reduce carbon emissions, ranging from 5259.31 to 419,199.60 tons, and reduce delivery quality under the 90.00% threshold and even under 75.25%. Extending delivery times is a viable business strategy, particularly by extending delivery to push carbon reduction policies to minimize environmental impact. However, consumer acceptance is crucial, as consumers willing to embrace longer wait times can significantly contribute to emission mitigation and support businesses committed to sustainability. This research uses a fuzzy nonlinear multi-objective programming model (FNMOPM) to contribute novel time management to mitigate carbon emissions. Moreover, this study uses a fuzzy and nonlinear approach to fill in the gaps of previous research to balance the efficiency and carbon emission mitigation goals of ESG (environmental, social, and governance) principles. The framework presented in this article solves the complex trade-off situations in the TCQCE issues. This article provides practical, actionable guidance for decision-making regarding sustainable e-commerce logistics, instilling confidence in its implementation.

Variable neighborhood genetic algorithm for multi-order multi-bin open packing optimization

In the rapidly evolving e-commerce landscape, efficient packaging and logistics reduce costs and enhance customer satisfaction. This study addresses the problem of dynamic bin size optimization in e-commerce logistics by proposing a series of intelligent algorithms. Considering real-world constraints such as item separation requirements, a Mixed Integer Programming Model for Multi-Order Multi-Box Open-Dimension Rectangular Packing (MOMB-ODRPP) is formulated. The Stacked Clustering Algorithm (SCA) series, One-Dimensional Fixed Stacked Clustering Algorithm (ODF-SCA), Two-Dimensional Fixed Stacked Clustering Algorithm (TDF-SCA), and Variable Neighborhood Descent Spatial Ordering Algorithm (VND-SOA) series are employed to solve the MOMB-ODRPP model and improve order packing rates and optimize bin sizes. Computational experiments using real-world data from JD’s e-commerce operations reveal that the TDF-SCA algorithm series outperforms the ODF-SCA series by approximately 5% in Case 4. In contrast, the VND-SOA-S1 and VND-SOA-S2 algorithms achieve improvements of 0.83% and 0.76%, respectively, over the TDF-SCA-P2 algorithm in Cases 4 and 11. The comparative analysis highlights the practical implications of bin size optimization, with Case 11 providing a more viable option for standardizing bin sizes in e-commerce logistics.

Mapping the Research Landscape of Reverse Logistics in E-Commerce: A Bibliometric Analysis from 2003 to 2023

Mapping the Research Landscape of Reverse Logistics in E-Commerce: A Bibliometric Analysis from 2003 to 2023

Cross-border E-commerce Logistics Optimization Algorithm for Collaboration between the Internet of Things and Logistics

This paper proposes the shortest path optimization algorithm for domestic and overseas e-commerce logistics based on a bilateral search method. This paper uses the logistics distribution route optimization algorithm based on the shortest path to set the collaborative parameters. Then, it builds an adaptive optimization model for the grid planning of domestic and overseas e-commerce logistics path. The route is optimized. Then, the PSO and genetic algorithm are integrated to establish the logistics path planning model of domestic and overseas e-commerce. The superiority of the proposed route optimization algorithm in domestic and overseas e-commerce logistics distribution is verified through simulation experiments. This algorithm has high spatial positioning efficiency and high transportation efficiency.

Routing protocols for B2B e-commerce logistics in cyber-physical internet (CPI)

Currently, the boom in B2B e-commerce logistics and the fragmentation of logistics networks have put tremendous pressure on the efficient and economical routing of packages. The idea of the cyber-physical internet (CPI) in logistics is to establish a new paradigm for sending and receiving goods, similar to how sending and receiving instant messages over the internet might be a solution. This work focuses on the routing process in B2B e-commerce logistics driven by the CPI. A framework of B2B e-commerce logistics in CPI networks is proposed to integrate logistics networks with components such as CPI routers, routing tables, and autonomous logistics systems (ALSs). Routing protocols within and among ALSs are proposed for making routing decisions based on information in routing tables for efficient and economical routing. Finally, two B2B e-commerce logistics scenarios are utilized to simulate the routing protocols in CPI networks to prove their feasibility, and their sensitivity is analysed. This work may support the improvement of B2B e-commerce logistics networks and intelligent logistics in Industry 4.0.