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.

Current Trends in the Management of Distributed Transactions in Micro-Services Architectures: A Systematic Literature Review

In the evolving landscape of software engineering, Microservice Architecture (MSA) has emerged as a transformative approach, facilitating enhanced scalability, agility, and independent service deployment. This systematic literature review (SLR) explores the current state of distributed transaction management within MSA, focusing on the unique challenges, strategies, and technologies utilized in this domain. By synthesizing findings from 16 primary studies selected based on rigorous criteria, the review identifies key trends and best practices for maintaining data consistency and integrity across microservices. This SLR provides a comprehensive understanding of the complexities associated with distributed transactions in MSA, offering actionable insights and potential research directions for software architects, developers, and researchers.

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.

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.

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.

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 Optimized Method for Information System Transactions Based on Blockchain

Accounting Information System(AIS),which is the foundation of any enterprise resource planning(ERP)system,is often built as centralized system.The technologies that allow the Internet-of-Value,which is built onfive aspects that are network,algorithms,distributed ledger,transfers,and assets,are based on blockchain.Cryptography and consensus protocols boost the blockchain plat-form implementation,acting as a deterrent to cyber-attacks and hacks.Blockchain platforms foster innovation among supply chain participants,resulting in ecosys-tem development.Traditional business processes have been severely disrupted by blockchains since apps and transactions that previously required centralized struc-tures or trusted third-parties to authenticate them may now function in a decentra-lized manner with the same level of assurance.Because a blockchain split in AIS may easily lead to double-spending attacks,reducing the likelihood of a split has become a very important and difficult research subject.Reduced block relay time between the nodes can minimize the block propagation time of all nodes,resulting in better Bitcoin performance.In this paper,three problems were addressed on transaction and block propagation mechanisms in order to reduce the likelihood of a split.A novel algorithm for blockchain is proposed to reduce the total pro-pagation delay in AIS transactions.Numerical results reveal that,the proposed algorithm performs better and reduce the transaction delay in AIS as compared with existing methods.

An Interoperability Cross-Block Chain Framework for Secure Transactions in IoT

The purpose of this research is to deal with effective block chain framework for secure transactions.The rate of effective data transactions and the interoperability of the ledger are the two major obstacles involved in Blockchain and to tackle this issue,Cross-Chain based Transaction(CCT)is introduced.Traditional industries have been restructured by the introduction of Internet of Things(IoT)to become smart industries through the feature of data-driven decision-making.Still,there are a few limitations,like decentralization,security vulnerabilities,poor interoperability,as well as privacy concerns in IoTs.To overcome this limitation,Blockchain has been employed to assure a safer transaction process,especially in asset exchanges.In recent decades,scalable local ledgers implement Blockchains,simultaneously sustaining peer validations of transactions which can be at local or global levels.From the single Hyperledger-based blockchains system,the CCT takes the transaction amid various chains.In addition,the most significant factor for this registration processing strategy is the Signature to ensure security.The application of the Quantum cryptographic algorithm amplifies the proposed Hyperledger-based blockchains,to strengthen the safety of the process.The key has been determined by restricting the number of transactions that reach the global Blockchain using the quantum-based hash function and accomplished by scalable local ledgers,and peer validations of transactions at local and global levels without any issues.The rate of transaction processing for entire peers has enhanced with the ancillary aid of the proposed solution,as it includes the procedure of load distribution.Without any boosted enhancement,the recommended solution utilizes the current transaction strategy,and also,it’s aimed at scalability,resource conservation,and interoperability.The experimental results of the system have been evaluated using the metrics like block weight,ledger memory,the usage of the central processing unit,and the communication overhead.

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.

Securing Stock Transactions Using Blockchain Technology: Architecture for Identifying and Reducing Vulnerabilities Linked to the Web Applications Used (MAHV-BC)

This paper deals with the security of stock market transactions within financial markets, particularly that of the West African Economic and Monetary Union (UEMOA). The confidentiality and integrity of sensitive data in the stock market being crucial, the implementation of robust systems which guarantee trust between the different actors is essential. We therefore proposed, after analyzing the limits of several security approaches in the literature, an architecture based on blockchain technology making it possible to both identify and reduce the vulnerabilities linked to the design, implementation work or the use of web applications used for transactions. Our proposal makes it possible, thanks to two-factor authentication via the Blockchain, to strengthen the security of investors’ accounts and the automated recording of transactions in the Blockchain while guaranteeing the integrity of stock market operations. It also provides an application vulnerability report. To validate our approach, we compared our results to those of three other security tools, at the level of different metrics. Our approach achieved the best performance in each case.

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.

A Novel High-Efficiency Transaction Verification Scheme for Blockchain Systems

Blockchain can realize the reliable storage of a large amount of data that is chronologically related and verifiable within the system.This technology has been widely used and has developed rapidly in big data systems across various fields.An increasing number of users are participating in application systems that use blockchain as their underlying architecture.As the number of transactions and the capital involved in blockchain grow,ensuring information security becomes imperative.Addressing the verification of transactional information security and privacy has emerged as a critical challenge.Blockchain-based verification methods can effectively eliminate the need for centralized third-party organizations.However,the efficiency of nodes in storing and verifying blockchain data faces unprecedented challenges.To address this issue,this paper introduces an efficient verification scheme for transaction security.Initially,it presents a node evaluation module to estimate the activity level of user nodes participating in transactions,accompanied by a probabilistic analysis for all transactions.Subsequently,this paper optimizes the conventional transaction organization form,introduces a heterogeneous Merkle tree storage structure,and designs algorithms for constructing these heterogeneous trees.Theoretical analyses and simulation experiments conclusively demonstrate the superior performance of this scheme.When verifying the same number of transactions,the heterogeneous Merkle tree transmits less data and is more efficient than traditional methods.The findings indicate that the heterogeneous Merkle tree structure is suitable for various blockchain applications,including the Internet of Things.This scheme can markedly enhance the efficiency of information verification and bolster the security of distributed systems.

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.