Spatial Structure of China's E-commerce Express Logistics Network Based on Space of Flows

The intermediate link compression characteristics of e-commerce express logistics ne tworks influence the tradition al mode of circulation of goods and economic organization,and alter the city spatial pattern.Based on the theory of space of flows,this study adopts China Smart Logistics Network relational data to build China's e-commerce express logistics network and explore its spatial structure characteristics through social network analysis(SNA),the PageRank technique,and geospatial methods.The results are as follows:the network density is 0.9270,which is close to 1;hence,indicating that e-commerce express logistics lines between Chinese cities are nearly complete and they form a typical network structure,thereby eliminating fragmented spaces.Moreover,the average minimum number of edges is 1.1375,which indicates that the network has a small world effect and thus has a high flow efficiency of logistics elements.A significant hierarchical diffusion effect was observed in dominant flows with the highest edge weights.A diamond-structured network was formed with Shanghai,Guangzhou,Chongqing,and Beijing as the four core nodes.Other node cities with a large logistics scale and importance in the network are mainly located in the 19 city agglomerations of China,revealing the fact that the development of city agglomerations is essential for promoting the separation of experience space and changing the urban spatial pattern.This study enriches the theory of urban networks,reveals the flow laws of modern logistics elements,and encourages coordinated development of urban logistics.

Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

Impact of Ningbo Port Logistics on Regional Economic Development of Zhejiang Province

In related academic circles, the research on port logistics industry and regional economic development has become a hot topic in recent years, and there are already extensive studies about this topic. Taking Ningbo Port as an example, this paper analyzed its logistics development status, and discussed the existing problems. Besides, taking the time series data of Ningbo Port from 2007 to 2016 as sample data, and using the quantitative analysis methods such as correlation analysis and regression analysis, it systematically studied the interaction between the port development and regional economic development. Finally, on the basis of the problems, it came up with some recommendations.

Regional Logistics Demand Forecast Based on Least Square and Radial Basis Function

Regional logistics demand forecast is the basis for government departments to make logistics planning and logistics related policies.It has the characteristics of a small amount of data and being nonlinear,so the traditional prediction method can not guarantee the accuracy of prediction.Taking Xiamen City as an example,this paper selects the primary industry,the secondary industry,the tertiary industry,the total amount of investment in fixed assets,total import and export volume,per capita consumption expenditure,and the total retail sales of social consumer goods as the influencing factors,and uses a combining model least square and radial basis function(LS-RBF)neural network to analyze the related data from years 2000 to 2019,so as to predict the logistics demand from years 2020 to 2024.The model can well fit the training data,and the experimental results obtained from the comparison between the predicted value and the actual value in 2019 show that the error rate is very small.Therefore,the prediction results are reasonable and reliable.This method has high prediction accuracy,and it is suitable for irregular regional logistics demand forecast.

Analyzing Collaborative Development of E-Commerce and Logistics Based on DEA

In order to know the current collaborative development situation and relationship of E-commerce and logistics, the paper evaluates the whole collaborative development level of Chinese E-commerce and logistics from 2008 to 2014 using the DEA model. Fund, infrastructure, labor and collaborative development are evaluated and analyzed in this model. The research indicates that E-commerce facilitates the logistics development but logistics can’t support E-commerce development well due to the lag effect which leads to lower collaborative development level. So optimizing the ratio of logistics investment and output, promoting logistics service quality and accelerating logistics development have been the key factors for promoting the collaborative development of E-commerce and logistics.

Logistics Demand Forecast of Fresh Food E-Commerce Based on Bi-LSTM Model

Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales data of a fresh food e-commerce enterprise as the logistics demand, analyzes the influence of time and meteorological factors on the demand, extracts the characteristic factors with greater influence, and proposes a logistics demand forecast scheme of fresh food e-commerce based on the Bi-LSTM model. The scheme is compared with other schemes based on the BP neural network and LSTM neural network models. The experimental results show that the Bi-LSTM model has good prediction performance on the problem of logistics demand prediction. This facilitates further research on some supply chain issues, such as business decision-making, inventory control, and logistics capacity planning.

A Study on Establishing a Cross-border E-commerce Logistics System for Agricultural Products in Sichuan Province in the Context of the Belt and Road Initiative

The rapid development of cross-border e-commerce,especially since Chengdu was listed as an Integrated Pilot Zone for Cross-Border E-Commerce in 2016,has led to a rising trade value of agricultural products in the metropolis.This upward trend is also attributed to the China-Europe Railway Express and the Chengdu International Aviation Hub Integrated Functional Area,two infrastructure systems that have opened more international logistics channels for agricultural products in Sichuan province.However,the development of cross-border logistics has failed to respond to the rapid growth of cross-border e-commerce for agricultural products.This problem has given rise to longer delivery cycles,higher costs,and reduced product quality,hindering the development of cross-border e-commerce for agricultural products.Currently,most research efforts are focused on selecting a logistics mode which has created an urgency is to establish a logistics system.To that end,we must utilize the opportunities and preferential policies brought about by the Belt and Road Initiative to advance the establishment of a cross-border logistics system for agricultural products,which will create more channels for selling Sichuan’s agricultural products overseas.This article analyzes the current situation of the cross-border logistics system for agricultural products produced by the province and studies the potential relationships between a logistics system and cross-border trade of agricultural products.It seeks to build a logistics system that meets the demands of cross-border transactions using economic theories focused on cross-border e-commerce and logistics.Such a logistic system will help shorten long delivery cycles,cut delivery costs,and guarantee the quality of agricultural products.Also,it can contribute to the rapid development of cross-border e-commerce of agricultural products and solve problems in developing the agricultural products logistics system of Sichuan province.

The Cooperation of Industrial Clusters and Regional Logistics of Shaanxi Province: An Evaluation Research

As a middle organization between enterprise organization which gains the competition advantage and eration of industrial clusters and regional logistics refers development of modern regional logistics. On the basis and market, industrial cluster is now the space industrial innovation advantage for a nation or a region. The coop- to improvement of industrial clusters＇ competitiveness and of reviewing the recent years＇ situation of Shaanxi Prov- ince＇s regional logistics and its industrial clusters, this paper analyzes positively about the supporting role of the regional logistics, builds gray relational model by choosing corresponding indicators, and carries out test of signif- icance. Finally it brings out strategic recommendations to and regional logistics enhance the level of cooperation of industrial clusters

Optimization of E-commerce Logistics Network in African Countries

The purpose of this research is to assist the Central African's logistics network authorities in making,evaluating,and realizing their decisions in regard to the development and management of e-commerce logistics network of companies・This article evaluated and used mathematical models which provided a descriptive analysis on the current situation of its'logistics network while applying the e-commerce logistics network optimization method in dealing with common issues of the logistics network in Central Africa,especially Chad.The suggested network in this study would promote the^from plant-to-from DC"ratio of 83%to 17%which conforms to the companies*objective in progressing towards direct plant shipments.In regard to that,it was proved that direct plant shipments could reduce the distribution costs from 12%to 3%of the net sales(approximately$135,000 in monthly savings).

Research of Order Allocation of E-commerce Logistics Service Supply Chain Considering Customer Evaluation

Based on the importance of customer evaluation for developing e-commerce enterprises,this paper analyzes the customer evaluation as a fuzzy variable and establishes a multi-objective mixed integer order allocation planning model by considering customer satisfaction,which maximizes customer praise and minimizes procurement cost.As the optimization goal,transaction cost is optimized for the order allocation of the secondary e-commerce logistics service supply chain.In order to defuzzify the customer evaluation,a fuzzy evaluation method is designed to transform the customer evaluation from fuzzy language evaluation to numerical measurement.Finally,the feasibility and effectiveness of the model are verified by using a specific example,and the order is made for the e-commerce enterprise.The allocation provides a theoretical reference.

Analyzing the Construction of the International Logistics Supply Chain Management Model from the Perspective of Cross-Border E-commerce

Cross-border e-commerce has progressively evolved with the deepening of economic globalization,and it now holds a significant place in the field of e-commerce.However,due to China’s late entry into the international logistics supply chain,there are issues such as complex environment,uneven information technology,and disagreements on standards,resulting in certain cross-border e-commerce disadvantages in China.Therefore,in this context,this study analyzes the construction of international logistics supply chain management model from the perspective of cross-border e-commerce,so as to provide some reference for the development of China’s international logistics supply chain.

Development of Agricultural Product Logistics in Tianjin in the Context of the Coordinated Development Strategy of Beijing-Tianjin-Hebei Region

Since February 26,2014,Chinese president Xi Jinping of the Central Committee of the Communist Party of China listened to the report on the coordinated development of Beijing-Tianjin-Hebei Region and delivered an important speech,and officially raised the coordinated development of Beijing-Tianjin-Hebei Region as a major national strategy,the integration of Beijing-Tianjin-Hebei Region has entered the"fast lane".Guided by accelerating the construction of agricultural product supply areas,agricultural high-tech industry demonstration areas,and agricultural product logistics center areas,Tianjin seizes the opportunity of coordinated development of Beijing-Tianjin-Hebei Region,brings into full play to the advantages of Tianjin s three-dimensional transportation network,perfect market system,high-quality port services,rapid growth of cold chain and e-commerce,to promote the faster and better development of Tianjin s agriculture.In addition,focusing on comprehensively improving Tianjin s regional agricultural product logistics service capabilities,Tianjin is establishing a distribution center for agricultural products,an e-commerce center,and a high-end agricultural product distribution center serving the Beijing-Tianjin-Hebei Region,to promote the construction of Tianjin agricultural product logistics center.

Prediction of the Logistics Demand Based on an Innovative Mixed Model: an Empirical Case from Nanping City,China

The research intends to make scientific prediction of the logistics demand of Nanping City based on mathematical model calculation so as to provide reasonable strategic guidance for the sustainable and healthy development of urban logistics industry.It constructs a comprehensive index system composed of freight volume and other eight relevant economic indices to form the foundation for the model construction.Combining forecasting models of principal component regression and GM(1,1)together,it makes mathematical calculation to predict the logistics demand of Nanping City from the years 2018 to 2022.The research makes systematical analyses of the indices influencing the precise prediction of logistics demand from a new perspective,which offers an innovative and practical option for urban logistics prediction.In line with the prediction,it offers some suggestions for the improvement of demand prediction and some strategies for the better development of the logistics industry in Nanping City.

Problems in Development of Rural E- commerce and Logistics and Recommendations

Rural e-commerce and logistics development is of great significance to promote rural economic development and increase farmers' income. This paper analyzed existing problems in development of rural e-commerce and logistics in China,mainly including objective restriction of rural e-commerce and logistics by economic level,relatively backward capital construction facilities,lack of logistics information service platform,and insufficient professional personnel,and shortage of rural logistics professional personnel,and weak financial support of government. On the basis of these problems,it came up with pertinent recommendations from government,enterprises,and rural areas.

SWOT Analysis of Agricultural Product Logistics Development——A Case Study of Shaanxi Province

SWOT method is used to analyze strengths and weaknesses in internal environment and opportunities and threats in external environment of development of agricultural product logistics in Shaanxi Province. The research indicates that the logistic development strategy of agricultural products in Shaanxi Province should bring into full play strengths in traffic, production, labor force, and science and technology. Besides, it is required to overcome weaknesses in information mechanism and management mode. Furthermore, we should take full advantage of domestic and international resources to develop famous, excellent and special products, to achieve high-efficient, rapid, and convenient development of logistics for agricultural products.

Accounting for the Effects of Climate Variability in Regional Flood Frequency Estimates in Western Nigeria

Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.

Enhancement of E-commerce Service by Designing Last Mile Delivery Platform

The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce.Last mile delivery,for which different app-based delivery services have recently emerged,is a new area of research that is not thoroughly addressed.Delivery ser-vice is one of the supporting platforms of e-commerce.One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service.This challenge is emphasized in this study which introduces a new system to facilitate communica-tion and coordination between customers and logistics companies by using one identity and one interface.This paper is a programming-based study,as the pro-posed system evaluates a website to serve logistics companies as well as designs an application(app)to serve the customers of logistics companies.Swift,a power-ful open-source and object-oriented programming language,and the mark-up language(HTML)were used to build the last mile delivery system.In addition,Firebase,a cloud-hosted real-time database built on Google infrastructure,were used to develop the system.By increasing the level of customer satisfaction and reducing delivery failure rates,this system will eventually increase the prosperity of e-commerce.

Using Statistical Learning Algorithms in Regional Landslide Susceptibility Zonation with Limited Landslide Field Data

Regional Landslide Susceptibility Zonation(LSZ) is always challenged by the available amount of field data, especially in southwestern China where large mountainous areas and limited field information coincide. Statistical learning algorithms are believed to be superior to traditional statistical algorithms for their data adaptability. The aim of the paper is to evaluate how statistical learning algorithms perform on regional LSZ with limited field data. The focus is on three statistical learning algorithms, Logistic Regression(LR), Artificial Neural Networks(ANN) and Support Vector Machine(SVM). Hanzhong city, a landslide prone area in southwestern China is taken as a study case. Nine environmental factors are selected as inputs. The accuracies of the resulting LSZ maps are evaluated through landslide density analysis(LDA), receiver operating characteristic(ROC) curves and Kappa index statistics. The dependence of the algorithm on the size of field samples is examined by varying the sizes of the training set. The SVM has proven to be the most accurate and the most stable algorithm at small training set sizes and on all known landslide sizes. The accuracy of SVM shows a steadilyincreasing trend and reaches a high level at a small size of the training set, while accuracies of LR and ANN algorithms show distinct fluctuations. The geomorphological interpretations confirm the strength of SVM on all landslide sizes. Our results show that the strengths of SVM in generalization capability and model robustness make it an appropriate and efficient tool for regional LSZ with limited landslide field samples.