Leveling the Playing Field China’s first e-commerce law takes effect in an effort to regulate the industry

Gao Difan,27,was overjoyed with the Givenchy lipstick she bought herself as a Christmas gift via a daigou.on Taobao,one of the most famous e-commerce platforms in China.A daigou is the name given to an intermediary who travels or lives abroad and buys products on behalf of people in China.

Impacts of agri-food e-commerce on traditional wholesale industry:Evidence from China

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.

Impact of BRICS Trade Facilitation on China's Exports Using Cross-Border E-Commerce

With the rapid growth of the global digital economy, cross-border e-commerce, as an emerging form of trade, has gradually become a powerful engine to promote the development of global trade. BRICS is an important force in the global economy, and the progress of the BRICS countries' trade facilitation level has an important impact on the global trade environment. This paper conducts an in-depth study of the dynamic changes in BRICS trade facilitation from 2013 to 2022, and uses an extended gravity model to analyze the specific impact of this change on China's exports using cross-border e-commerce. The results show that although the BRICS countries have made some progress in trade facilitation, the overall level still needs to be improved, and there are obvious differences among member countries. However, the improvement of trade facilitation among BRICS countries has undoubtedly brought significant positive effects to China's exports using cross-border e-commerce.

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.

Research on Current Situation and Legal Regulation of Cosmetics Live Streaming E-commerce in China

Analyze the compatibility between cosmetics and live streaming e-commerce from its own nature,marketing means and supply chain characteristics.According to the prominent problems,sort out the relationship between all parties in the cosmetics live e-commerce industry chain.Combined with the latest regulatory policies of live streaming e-commerce and cosmetics,the responsibilities of different subjects in cosmetics live streaming e-commerce are summarized,and relevant suggestions and countermeasures are put forward for the standardization and development of live streaming e-commerce.Cosmetics brand owners are the first responsible persons for product quality.Anchors,as a mixed identity between intermediary,advertising spokesperson and operator,should bear stricter joint and several liability when recommending products related to consumers’health.If anchors fail to clearly identify themselves in the recommendation process,thus causing consumers to mistake them for the operator of the cosmetics,they should assume the obligations of the operator.

How Does E-Commerce Policy Affect Consumption Disparities of Rural Households?-Evidence from China

In the context of China’s ongoing efforts to promote countryside revitalization and facilitate domestic economic circulation,it is of great significance to reduce the consumption disparity among rural households and unleash the consumption potential in the countryside.Based on data from China Family Panel Studies,this paper adopts a staggered difference-in-differences method to assess the impact of the e-commerce to enter rural areas on the consumption disparity among rural households.Findings:the comprehensive demonstration work of promoting e-commerce to enter rural areas has reduced the consumption disparity among rural households through the following mechanisms.Firstly,this policy initiative has mitigated the consumption-inhibiting effect on rural household consumption due to the local market size and external market accessibility by promoting the distribution of consumer goods to villages.Secondly,this policy initiative has also increased the agricultural income of rural households and reduced their consumption disparity by distributing farm produce to cities and enhancing the agricultural income of rural households.Moreover,the work is characterized by inclusive growth and is not susceptible to the“elite capture”phenomenon.

The Impact of E-Commerce Live Broadcasts on Consumers’Purchase Intention

E-commerce live broadcast has an important influence on consumers’purchase intention.The three dimensions of live broadcast content in the broadcast room are the number of comments,product quality,and live content as independent variables.A theoretical model is constructed with perceived value and risk as intermediaries and the consumers’purchase intention as the dependent variable,and corresponding hypotheses are put forward.We designed the scale,collected relevant data,and tested the model hypothesis using Statistical Package for Social Sciences(SPSS)and Analysis of Moment Structure(AMOS)software.The study found that the number of comments and product quality had a significant impact on perceived value,perceived risk,and consumers’purchase intention.From this conclusion,it is suggested that businesses should control the number of comments,strengthen the product quality of comments,and distinguish the repetition degree of the content of live broadcasts.

Analysis of the Current Situation, Influential Factors, and Countermeasures of Rural E-commerce Development

The development of rural e-commerce is becoming an important driver for the transformation of China’s rural economy,and with the rapid development of information technology and the upgrading of the agricultural industry,rural e-commerce is showing a vigorous momentum of development.Traditionally,agricultural products are mainly sold through traditional farmers’markets,which are subjected to geography and channel limitations,resulting in inefficient circulation of agricultural products.This paper analyzes the definition,the status quo,as well as the influencing factors of rural e-commerce development.On this basis,countermeasures for the advancement of rural e-commerce development are put forward.

Research on Professional Teaching Reform of the E-Commerce Major in Vocational Colleges Under the Internet Era

With the rapid development of science and technology,the face of human society has undergone great changes;with the emergence of the Internet era,all kinds of educational technology,equipment,and software in vocational colleges have been widely used to carry out education and teaching,and has achieved remarkable results.Based on this,colleges and universities’electronic commerce(e-commerce)professional teachers should try to rely on the Internet to build information teaching classrooms,introduce advanced methods to build efficient classrooms by integrating teaching resources,and optimize the top-level design,so as to activate the classroom atmosphere,mobilize students’emotions,make them immersed in the teaching of electronic commerce courses.In view of this,this paper combines the existing theory and experience,first analyzes the dilemma faced by the current teaching of e-commerce in vocational colleges,then discusses the practical significance of teaching reform based on the Internet era,and lastly puts forward the specific practice path.

Optimization and Innovation of the Operation Model of Mobile Social E-commerce under AI Empowerment:Taking the Female Community Platform“Little Red Book”as an Example

This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Firstly,the relevant concepts were defined,and then the unique attributes of mobile community e-commerce were analyzed.As a typical representative of mobile community e-commerce,Little Red Book introduces the background and characteristics of its platform,analyzes its mobile community operation mode,and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology,to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.

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.

Transaction Frequency Based Trust for E-Commerce

Most traditional trust computing models in E-commerce do not take the transaction frequency among participating entities into consideration,which makes it easy for one party of the transaction to obtain a high trust value in a short time,and brings many disadvantages,uncertainties and even attacks.To solve this problem,a transaction frequency based trust is proposed in this study.The proposed method is composed of two parts.The first part is built on the classic Bayes analysis based trust modelswhich are ease of computing for the E-commerce system.The second part is the transaction frequency module which can mitigate the potential insecurity caused by one participating entity gaining trust in a short time.Simulations show that the proposed method can effectively mitigate the self-promoting attacks so as to maintain the function of E-commerce system.

Enhanced E-commerce Fraud Prediction Based on a Convolutional Neural Network Model

The rapidly escalating sophistication of e-commerce fraud in recent years has led to an increasing reliance on fraud detection methods based on machine learning.However,fraud detection methods based on conventional machine learning approaches suffer from several problems,including an excessively high number of network parameters,which decreases the efficiency and increases the difficulty of training the network,while simultaneously leading to network overfitting.In addition,the sparsity of positive fraud incidents relative to the overwhelming proportion of negative incidents leads to detection failures in trained networks.The present work addresses these issues by proposing a convolutional neural network(CNN)framework for detecting ecommerce fraud,where network training is conducted using historical market transaction data.The number of network parameters reduces via the local perception field and weight sharing inherent in the CNN framework.In addition,this deep learning framework enables the use of an algorithmiclevel approach to address dataset imbalance by focusing the CNN model on minority data classes.The proposed CNN model is trained and tested using a large public e-commerce service dataset from 2018,and the test results demonstrate that the model provides higher fraud prediction accuracy than existing state-of-the-art methods.

An Enhanced Intelligent Intrusion Detection System to Secure E-Commerce Communication Systems

Information and communication technologies are spreading rapidly due to their fast proliferation in many fields.The number of Internet users has led to a spike in cyber-attack incidents.E-commerce applications,such as online banking,marketing,trading,and other online businesses,play an integral role in our lives.Network Intrusion Detection System(NIDS)is essential to protect the network from unauthorized access and against other cyber-attacks.The existing NIDS systems are based on the Backward Oracle Matching(BOM)algorithm,which minimizes the false alarm rate and causes of high packet drop ratio.This paper discussed the existing NIDS systems and different used pattern-matching techniques regarding their weaknesses and limitations.To address the existing system issues,this paper proposes an enhanced version of the BOM algorithm by using multiple pattern-matching methods for the NIDS system to improve the network performance.The proposed solution is tested in simulation with existing solutions using the Snort and NSL-KDD datasets.The experimental results indicated that the proposed solution performed better than the existing solutions and achieved a 5.17%detection rate and a 0.22%lower false alarm rate than the existing solution.

Weber Law Based Approach for Multi-Class Image Forgery Detection

Today’s forensic science introduces a new research area for digital image analysis formultimedia security.So,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered images.Exiting forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing forgeries.However,an image can contain one or more types of forgeries.This study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial domain.Firstly,images are divided into equal blocks to get scale-invariant features.Weber law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing forgery.The proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and healthy.Benchmarked(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and testing.On average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

基于多尺度Laws纹理能量和低秩分解的织物疵点检测算法

为提高织物疵点检测算法对简单纹理织物、模式纹理织物及条纹纹理织物检测时的普适性和准确性,提出了一种基于多尺度Laws纹理能量和低秩分解的织物疵点检测算法。首先,对织物图像进行直方图均衡化并将处理后的图像均匀划分为子图像块;其次,对每个子图像块提取28个纹理能量特征(利用7个Laws滤波模板在4个尺度上提取),计算所有子图像块提取到的特征均值并组成特征矩阵;然后,利用特征矩阵构建低秩分解模型,通过方向交替方法(ADM)优化求解,得到低秩部分和稀疏部分;最后,由稀疏部分生成疵点显著图,采用迭代阈值分割法对其进行分割,得到织物疵点检测结果。为验证该算法的有效性,在织物图像数据集选取了包含错纬、断经、跳花、破洞等常见疵点的织物图像,并将实验结果与已有3种算法进行了对比。实验结果表明,该算法在简单纹理织物、模式纹理织物及条纹纹理织物检测上具有更好的普适性和准确性,且检测效率具有一定优势。

Analysis of the Development Environment and Trend of Cross-Border E-commerce in China

With the conclusion of the novel coronavirus pandemic and the increasingly complex market environment,China’s cross-border e-commerce has entered a new phase of development.The external landscape is evolving rapidly,and there is a gradual improvement in laws and regulations governing cross-border e-commerce,coupled with increased government support.Despite the impact of the COVID-19 pandemic on the market economy,overall development has been steadily improving.The Internet population is expanding,the online retail market is experiencing rapid growth,the consumption structure is undergoing transformation and upgrading,and the e-commerce market is demonstrating significant potential.The advancement of technologies such as big data,artificial intelligence,blockchain,and supply chain has provided more efficient operational support for the cross-border e-commerce industry.Against the backdrop of the emergence of new forms of cross-border e-commerce in China post-pandemic,this paper utilizes the PEST model to analyze the macro environment of cross-border e-commerce in China and project its future development trends.

Investigation and Countermeasures of the Development of Chinese Pharmaceutical E-commerce in the B2C Model Based on PEST-SWOT Analysis

Objective To analyze the problems of pharmaceutical e-commerce and provide strategies for its development in the future B2C mode since drug network management has great potential in China.Methods By collecting,identifying,and conducting literature research,PEST-SWOT identification and positioning of pharmaceutical e-commerce in the B2C mode were carried out.Results and Conclusion A PEST-SWOT analysis matrix was established to analyze the status of B2C pharmaceutical e-commerce,and to summarize its advantages,disadvantages,opportunities and threats from four perspectives of politics,economy,society and technology.Suggestions on cultivating compound talents proficient in medicine and e-commerce,exploring online payment methods for medical insurance,integration of upstream and downstream of the industrial chain and data sharing are put forward to promote the healthy and long-term development of pharmaceutical e-commerce under the background of big data.

Scaling Laws Behind Penetrative Turbulence:History and Perspectives

An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.

Nonuniform Dependence on the Initial Data for Solutions of Conservation Laws

In this paper,we study systems of conservation laws in one space dimension.We prove that for classical solutions in Sobolev spaces H^(s),with s>3/2,the data-to-solution map is not uniformly continuous.Our results apply to all nonlinear scalar conservation laws and to nonlinear hyperbolic systems of two equations.