E-commerce Logistics Research Articles

乡村振兴背景下生鲜农产品电商物流发展困境与优化

乡村振兴背景下生鲜农产品电商物流发展困境与优化

乡村振兴背景下农村电商物流发展存在的问题及对策研究

乡村振兴背景下农村电商物流发展存在的问题及对策研究

Research on optimization of e-commerce supply chain logistics service model based on multi-source data fusion

Abstract Inefficiencies in supply chain logistics management, particularly in certain regions, often result in “broken chain” incidents that significantly impact the efficiency of e-commerce operations and degrade consumer experiences. This paper addresses the necessity of optimizing the logistics service model by integrating 12 heterogeneous data sources related to warehousing, transportation, processing, and sorting. We propose a site selection-inventory-path e-commerce logistics optimization model. For the first time, the model incorporates the Dempster-Shafer (D-S) evidence algorithm to quantitatively evaluate the support relationships among various pieces of evidence by adjusting the weight coefficients accordingly. This adjustment is further refined through the application of the Nash equilibrium in the evidence combination process. The optimized logistics model is then solved using a fusion of the model and an intuitive fuzzy set approach. A case study demonstrates that the optimized logistic supply capacity consistently outperformed the non-optimized scenarios, with statistical increases of 1.64%, 1.72%, 2.15%, 3.73%, 2.71%, 2.46%, 3.59%, 2.17%, and 3.98%. Furthermore, by refining the logistics model, the gap in logistics performance was narrowed by at least 5.13% and by as much as 12.9% across successive evaluations, significantly alleviating issues related to enterprise capacity constraints. This study offers novel insights and methodologies for enhancing the efficiency of regional e-commerce supply chain logistics, boosting the competitiveness of logistics enterprises, and elevating the consumer experience in e-commerce settings.

Simulation and Optimization System of Automated E-Commerce Logistics Warehouse Allocation Network Based on Intelligent Algorithm

The prosperity of e-commerce has made our lives more convenient, but the logistics behind it has been silently paying. The e-commerce industry is expanding at an unprecedented rate, and with it comes explosive growth in logistics demand, especially in the warehouse distribution link. In order to meet this demand, the warehouse distribution system needs to be improved both in terms of technology and efficiency. This rapid development also brings a series of problems. First of all is the problem of logistics congestion. Due to the surge in orders, especially during peak shopping periods, logistics centers are often under great pressure. This not only affects the speed of delivery, but can also lead to damage or loss of goods. The purpose of this paper is to find an effective method to optimize the logistics warehouse allocation system of e-commerce, and to provide an efficient and reliable logistics optimization scheme for e-commerce enterprises. In this paper, data analysis and simulation methods are used to analyze. The experimental results show that PSO has the largest improvement in the order clerk operation efficiency (13%) and the smallest improvement in the order status (1%).

Intelligent E-commerce Logistics Supply Chain Management and Scheduling Optimisation

Abstract In the digital era, logistics supply chain scheduling has become the key to enhancing the competitiveness of e-commerce, and the fine management and scheduling optimization of the e-commerce logistics supply chain is particularly important. Based on the three-layer supply chain scheduling model, the study combines the production cost, transportation cost, and transportation time of each member of the supply chain with other influencing indexes. It establishes a multi-stage supply chain scheduling model (SCISM) with dual-objective. The rotational algorithm in linear programming is used to solve the model after it has been constructed. The effectiveness of the SCISM model for intelligent e-commerce logistics supply chains is explored through algorithmic and arithmetic validation of the SCISM model. The results show that the SCISM model algorithm determines the optimal solution σ∗ = (1,2,4,6,3,5) and the optimal objective generalized function value J(σ∗) = −49328 in only 0.95 seconds, which significantly improves the solution efficiency. Compared to Genetic Algorithm (GA) and Particle Swarm Algorithm (PSO), the SCISM algorithm quickly achieves the global optimal solution with the minimum number of iterations (100).

Development strategy of transnational e-commerce logistics and distribution based on artificial intelligence and big data

Development strategy of transnational e-commerce logistics and distribution based on artificial intelligence and big data

RubikCell: Toward Robotic Cellular Warehousing Systems for E-Commerce Logistics

RubikCell: Toward Robotic Cellular Warehousing Systems for E-Commerce Logistics

Cross-border E-commerce Logistics Distribution Optimization Based on Iot Artificial Intelligence Algorithm

Cross-border E-commerce Logistics Distribution Optimization Based on Iot Artificial Intelligence Algorithm

Cross-border e-commerce logistics distribution optimisation based on IoT artificial intelligence algorithm

Cross-border e-commerce logistics distribution optimisation based on IoT artificial intelligence algorithm

Effective Application of Smart Logistics Technology in Rural E-commerce Logistics Distribution

Abstract With the continuous development of smart logistics technology, the status of rural e-commerce logistics and distribution has also increased. This paper combines the intelligent logistics technology framework based on rural e-commerce logistics distribution situation, the selection of rural e-commerce distribution node sites, and distribution path optimization. Furthermore, construct a game model for the rural e-commerce logistics and distribution industry chain with the goal of generating synergy. We examine the traditional rural e-commerce logistics and distribution scheme, distribution node setting, and benefits game based on this basis. The results show that the total cost of the smart logistics distribution program is reduced by 200.7 compared with the traditional distribution program, and the total cost of the smart logistics distribution program saves 5% compared with the traditional distribution program. The average transportation time of smart logistics distribution is 11.22min, which is significantly reduced compared with traditional logistics distribution. The rural smart logistics distribution system for e-commerce that uses benefit sharing and cost sharing profit 1242 is the best program when comparing benefits. To sum up, smart logistics technology plays a significant role in rural e-commerce logistics distribution, which can effectively save logistics distribution costs and enhance distribution efficiency.

Analyzing Traceability Models in E-Commerce Logistics: A Multi- Channel Approach

Analyzing Traceability Models in E-Commerce Logistics: A Multi- Channel Approach

IDEAL LOCATION SELECTION FOR CONTACTLESS PARCEL PICK-UP POINTS

The post-Covid era has witnessed the adoption of various new habits in our daily lives, particularly in relation to the ubiquitous e-commerce platforms that have become essential for urban populations. The surge in e-commerce activities and the intensified volume in delivery of packages during the pandemic sparked innovative ideas. This study explores one such creative concept: parcel pick-up points. We conducted a pioneering research endeavor to determine the optimal locations for these pick-up points in Istanbul, Turkey. Our methodology employed a novel hybrid approach, combining the Spherical Fuzzy Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The evaluation of criteria importance was facilitated by a literature review and experienced high-level managers in the cargo industry, who determined the criteria weights using the Spherical Fuzzy AHP method. Subsequently, the TOPSIS method was employed to identify the most ideal locations, leading to the selection of Kadikoy, Umraniye, and Atasehir. This study provides valuable insights into the selection of the optimal locations for parcel pick-up points in Istanbul, Turkey, which can inform policymakers, e-commerce companies, and logistics stakeholders. The proposed hybrid approach demonstrates the integration of modern smart technologies with fuzzy decision-making techniques, offering a robust framework for decision support in the field of e-commerce logistics. Future research can further explore the implementation and effectiveness of these pick-up points to enhance the efficiency and convenience of last-mile deliveries in urban areas.

Development of Cold Chain Logistics for China's Fresh E-commerce in Post-Epidemic Era

The emergence of the COVID-19 pandemic presented both unprecedented challenges and remarkable opportunities for China’s fresh food e-commerce industry. This dynamic landscape has underscored the critical importance of advancing cold chain logistics within this industry. Drawing upon established supply chain management theories, this paper identifies key areas for enhancement in the realm of cold chain logistics for fresh e-commerce. Through a comprehensive review of existing literature and current research findings, this study delves into the current state of cold chain logistics for fresh e-commerce, scrutinizing prevalent issues and deriving significant insights. The paper advocates for enterprises to prioritize the integration of cutting-edge technologies, enabling the creation of intelligent logistics systems. Additionally, it emphasizes the implementation of lean supply chain management practices to drive holistic regional development. Furthermore, leveraging policy support for the expeditious establishment of industry standards and protocols is crucial. The conclusions drawn from this research hold tangible implications for understanding the present landscape of cold chain logistics in fresh e-commerce, offering a theoretical and practical foundation to propel its future development.

Commitment or rent-seeking? Government incentive policies for ESG reporting in sustainable e-commerce logistics

In the sphere of e-commerce logistics industry, the credibility of Environment, Social, and Governance (ESG) reports by e-commerce logistics service providers (ELSPs) is critical for accurately conveying sustainability initiatives with transparency. Nonetheless, the actions of ESG rating stakeholders can significantly affect the truthfulness and authenticity of these ESG reports. Therefore, it becomes essential to develop comprehensive analytical methods and incentives policies to forestall any rent-seeking behavior that might emerge from potential collusion between ELSPs and ESG rating agencies (ERAs). This study presents a tripartite evolutionary game model to inspect the enduring strategic interplay among ELSPs, ERAs, and government regulators. The model illuminates the collective supervision outcomes molded by these stakeholder interactions. Choices available include ELSPs' decision to offer ESG-committed or basic services, ERAs' consideration to accept or decline rent-seeking requests from ELSPs, and regulators' options for either stringent or lenient supervision. The analysis also explores the influence of government incentives, such as rewards or penalties, in promoting ELSPs' provision of ESG-committed transportation services. Evolutionary stable strategies and conditions are then derived to capture the feature of incentive policies. The findings show that high ESG commitment transportation costs often deter ELSPs due to unpredictable future revenues, leading them to prefer a conservative strategy of providing basic services. Government regulations and incentives, however, can encourage in ESG transport, especially when ERAs’ rent-seeking charges are high. Despite the potential for relaxed supervision as ESG transport services become more widespread, strict government regulation remains crucial in motivating ELSPs to enhance their ESG commitment and adopt ESG transportation services.

Retracted: A Cloud Computing-Based Intelligent Forecasting Method for Cross-Border E-Commerce Logistics Costs

Retracted: A Cloud Computing-Based Intelligent Forecasting Method for Cross-Border E-Commerce Logistics Costs

Exploring the cross-border e-commerce of agricultural exports and its logistics supply chain innovation and development strategy under digital technology

Abstract This paper constructs a cross-border e-commerce supply chain information synergy platform for agricultural products, which screens and processes data of relevant business information and finally outputs information that helps cross-border e-commerce business of agricultural products. Through in-depth analysis of the structural characteristics of cross-border e-commerce maritime and air transport international logistics network under the mode of overseas warehouse, we first describe this type of problem and the basic assumptions of the model, set the model parameters, take a set of optimal solutions of Pareto, and model the cross-border e-commerce logistics network under the mode of overseas warehouse under the mode of maritime and air transport, respectively. According to different objectives, the multi-objective model of the international logistics network of cross-border e-commerce sea transportation mode and the multi-objective model of the international logistics network of cross-border e-commerce air transportation mode are established, respectively. After the optimization of the logistics supply chain, the turnover days of accounts receivable are 20 days faster than in the past, which is still 5 days less than the specified target value. The inventory stock days have been decreased from 150 days to 110 days. In other aspects, although there is still a small gap between the actual situation and the target value, most of the score values are close to the established value, and there is a significant improvement compared with the original operational value after improvement through the method of this paper cross-border e-commerce enterprises’ procurement cycle time and order fulfillment cycle time are reduced by 10 days compared with the past and reach the target values.

Research on cross-border e-commerce logistics under the sharing economy model

As an important part of cross-border e-commerce, cross-border e-commerce logistics occupies a very important position in cross-border e-commerce, but its development in China is relatively lagging behind that of cross-border e-commerce, and this situation needs to be resolved urgently. The emergence of the sharing economy model provides possible solutions to the problems in cross-border e-commerce logistics. This article analyzes the current development status of cross-border e-commerce logistics in China, defines and analyzes the feasibility of the “sharing economy + cross-border e-commerce logistics” model, and finally proposes the “sharing economy + cross-border e-commerce logistics” model corresponding policy recommendations to better support cross-border e-commerce to achieve a high level of sustainable development.

RAIL TRANSPORT IN E-COMMERCE: AN OVERVIEW OF THE OPPORTUNITIES

The e-commerce market is constantly growing and attracting new entrants, but some developing trends are controversial.
 The study presents the results of a comparative analysis of logistics development strategies in the e-commerce market in the Russian Federation and the Republic of Indonesia. The analysis shows that while technological solutions are more general and they can be disseminated as best practices, the structure of transportation depends on local characteristics. 
 In Russia rail transport has an important place in the overall transport volume, but in order to be integrated into the e-commerce market, railway companies have to change their existing logistics significantly. This study presents an analysis of strategic documents, examining the prospects for Russian Railways to enter the e-commerce market and the challenges encountered along the way. Rail logistics is a rather conservative industry but nowadays it ready to embrace new technologies, cloud-based solutions and services, such as track and wagon sensors, intelligent video analytics and so on. In Indonesia, as an island nation, rail transport is not that important. The country faces the challenge of developing land transportation by different modes of transport.
 The article not only identifies general trends in the use of logistic instruments for small-scale shipments but reveals possible obstacles and ways to improve logistics. Some recommendations are made, as E-commerce logistics systems seek improved communication, transparency in the supply chain, improved customer satisfaction, distribution and logistics optimization, cost reduction, improvement in efficiency and on-time delivery. The land transportation industry is crucial for the growth of national connectivity and contributes significantly to national development.

Retracted: E-Commerce Logistics Inspection System Based on Artificial Intelligence Technology in the Context of Big Data

Retracted: E-Commerce Logistics Inspection System Based on Artificial Intelligence Technology in the Context of Big Data

A bi-criteria approach to the truck-multidrone routing problem

In the rapidly expanding field of e-commerce logistics, the optimisation of last-mile delivery solutions is paramount. This paper introduces a novel methodology that addresses this challenge by generating approximate Pareto fronts in a hybrid truck-drone delivery system. Specifically, we examine a generalized single truck multi-drone problem that allows multi-visit flight missions and rendezvous points distinct from launch locations. Our goal is providing decision-makers with a portfolio of optimal routing solutions that balance service time and environmental impact, criteria that are increasingly shaping decision-making in this domain. To achieve this, we introduce a bivector coding scheme inspired by flow-shop scheduling problems and implement a Simulated Annealing algorithm. This algorithm features an advanced stopping mechanism, negating the need for manual adjustments by utilizing a distinctive blend of a domination rate and a Kalman filter. Importantly, our framework employs an iterated greedy search algorithm to evolve from initial solutions towards identifying non-dominated solutions sets, which are then ranked using a hypervolume coefficient. To validate our methodology, we conduct a sensitivity analysis on two different size instances using a full factorial design of experiments. Our analysis reveals crucial insights into the impact of the number of drones, their autonomy, and their flight speed settings. From it, we conclude that it is a robust and adaptable framework for its practical application for obtaining Pareto fronts solutions among which picking the ultimate routing to be implemented.