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.

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.

Paths for Upgrade and Transformation of E-commerce of China's Fresh Agricultural Products Based on Whole Industry Supply Chain

China's e-commerce market scale of fresh agricultural products has reached 1000 billion yuan,and the prospect is bright.However,in the face of such problems as quality control,storage and distribution,and consumption habits,the fresh product e-commerce has great difficulty in development.Internet generates large data,and data are the resources and the core of the Internet and the foundation for survival and development of Internet.This paper analyzed the current situation of the development of fresh agricultural products,and discussed the plight of fresh product e-commerce in scale,profit,non-standard,and network environment.On the basis of the whole industry supply chain,it came up with paths for upgrade and transformation of the fresh product e-commerce with the big data as the core in the context of Internet environment.

A Novel Named Entity Recognition Scheme for Steel E-Commerce Platforms Using a Lite BERT

In the era of big data,E-commerce plays an increasingly important role,and steel E-commerce certainly occupies a positive position.However,it is very difficult to choose satisfactory steel raw materials from diverse steel commodities online on steel E-commerce platforms in the purchase of staffs.In order to improve the efficiency of purchasers searching for commodities on the steel E-commerce platforms,we propose a novel deep learning-based loss function for named entity recognition(NER).Considering the impacts of small sample and imbalanced data,in our NER scheme,the focal loss,the label smoothing,and the cross entropy are incorporated into a lite bidirectional encoder representations from transformers(BERT)model to avoid the over-fitting.Moreover,through the analysis of different classic annotation techniques used to tag data,an ideal one is chosen for the training model in our proposed scheme.Experiments are conducted on Chinese steel E-commerce datasets.The experimental results show that the training time of a lite BERT(ALBERT)-based method is much shorter than that of BERT-based models,while achieving the similar computational performance in terms of metrics precision,recall,and F1 with BERT-based models.Meanwhile,our proposed approach performs much better than that of combining Word2Vec,bidirectional long short-term memory(Bi-LSTM),and conditional random field(CRF)models,in consideration of training time and F1.

Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning

With the continuous development of artificial intelligence technology,its application field has gradually expanded.To further apply the deep reinforcement learning technology to the field of dynamic pricing,we build an intelligent dynamic pricing system,introduce the reinforcement learning technology related to dynamic pricing,and introduce existing research on the number of suppliers(single supplier and multiple suppliers),environmental models,and selection algorithms.A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions.The first step is to analyze the pricing strategies of e-commerce platforms in mature markets,analyze the optimal pricing and profits of various enterprises under different strategy combinations,compare different market equilibriums and solve the Nash equilibrium.Then,assuming that all consumers are naive in the market,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.By comparing and analyzing the optimal pricing and total profit of each enterprise under different strategy combinations,the subgame refined Nash equilibrium is solved.Finally,assuming that the market includes all experienced consumers,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.

Effects of E-Commerce Platforms on Firm Export——Evidence from China’s Industrial Enterprises

With deepening digital technology applications in international trade, e-commerce platforms have become a major avenue for firm export. Based on a multicountry, multi-product heterogeneous firms trade theory model, this paper investigates the firm export effects of e-commerce platforms, and empirically tests the inferences from the model using data from Alibaba China Station, China industrial enterprises data, and China customs data from 2000 to 2009. Our estimation result shows that overall, e-commerce platforms significantly increase firm export probability and volume;e-commerce platforms enable firms to export products of different types to more countries by reducing the cost of information and export markets threshold while raising trade efficiency. Further analysis of enterprise heterogeneity reveals that SMEs, firms in China's eastern region, and general exporters benefit more from e-commerce platforms than other types of firms do.

Application of the E-commerce Platform in the International Trade

E-commerce is a new consumption mode, which develops rapidly and is welcomed by consumers. It also plays an important role in promoting the international trade. Through this analysis, we can understand that the influence of the e-commerce on the international market has both positive and negative aspects. We need to be aware of our shortcomings, understand the gap between them and the developed countries, and formulate the relevant policies. Let China's e-commerce continue to improve and innovate in the international trade, and find a suitable strategy for its own development. Relevant Chinese departments should actively and effectively participate in the construction of e-commerce. On the one hand, they can stabilize the status of e-commerce in the international trade, and on the other hand, they can expand the consumer groups and make the electronic goods better.

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.

Assumption of E-commerce Platform of Agricultural Products Based on F2C2B Mode

This paper proposes the assumption of E-commerce platform of the agricultural products based on the F2C2B mode. The whole e-commerce model is guided by the idea of the supply chain management from the perspective of the modern system, and the e-commerce integration model from customer to supplier is implemented, and the whole is optimized. E-commerce to cloud computing as the basic environment, the construction of public cloud services and private cloud resources, based on public cloud to the SaaS way to provide services to customers, focus on business search and business collaboration, make full use of the lnternet, modern communications technology to provide the real- service. The development of agricultural economy, no longer depends only on the number of some traditional agricultural resources, but also depends on the modern technology, information access and use. Through the development of basic network technology, by virtue of some modern electronic information technology and some other means that can improve the intelligence of agricultural use of the information resources, the proposed model provides the new methodology of the solution.

Financing Decisions Analysis of E-commerce Supply Chain Finance for Fresh Agricultural Products in China

The supply chain finance(SCF)solutions are becoming increasingly diversified with the continuous perfection of the economic system.However,financing for small and medium sized enterprises(SMEs)is still a difficult issue waiting to be solved by enterprises and the government in China.SCF solutions based on e-commerce platforms have developed rapidly in China that provide an alternative for SMEs when few studies have been conducted on e-commerce SCF solutions which focus on fresh agricultural products.Therefore,this research focuses on the SCF solutions applicable to e-commerce enterprises of fresh agricultural products.

Research on the Development Model ofE - commerce Finance： A Case Study of the Cross-border Cooperation in Finance between banks and E-commerce companies

This purpose of this article is to provide an overview of the research situation and the development model of the E-commerce finance. This article takes the cross-border cooperation in finance between banks and E-commerce companies. This paper introduces three development models of E-commerce finance. Banks set up their own E-commerce platform. The banks take advantage of E-commerce platform. The E-commerce companies run financial business. The theoretical findings reported in this paper pave the way for embarking on the promising and relevant future research.

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.

Digital Marketing and B2B Cross-Border E-Commerce: A Case Study of Alibaba International Station in China

The rapid development of the“Internet+”has ushered in a new era of global digital technology innovation.Concurrent with the deepening trends of economic globalization and integration,international trade is progressively undergoing extensive digitization,with cross-border e-commerce emerging as a significant manifestation of this transformation.Within this landscape,the cross-border e-commerce B2B platform is anticipated to become a pivotal driver for China’s cross-border trade growth,representing a strategic opportunity for trade transformation.This paper provides a comprehensive examination of the concepts,characteristics,and development status of cross-border e-commerce and B2B platforms,considering both global and Chinese perspectives.Focusing on a prominent case study,Alibaba International Station,a B2B cross-border e-commerce platform,the paper delves into its business model and core competencies,offering a thorough analysis of its role in the intricacies of international e-commerce and its contribution to the field.Drawing on insights gained,the paper concludes by presenting targeted recommendations from both the platform and government perspectives.These suggestions are informed by a nuanced understanding of the development opportunities and challenges facing China’s cross-border e-commerce B2B platforms.

Evolutionary game analysis of information service quality control of e-commerce platforms under information ecology

Due to the information asymmetry and imperfect supervision system,the problem of information service quality of e-commerce platforms is becoming increasingly prominent.Based on the perspective of information ecology,this paper constructs a three-party evolutionary game model including merchants,e-commerce platforms and governments,and analyzes the dynamic process of the threeparty game under bounded rationality,thereby characterizing the behavior and optimal strategies of information service quality control.We carry out numerical simulation using data of the Pinduoduo platform.The results show that the cost of each party,control strength of e-commerce platforms,proportion of margin deducted and other factors are important factors affecting the quality of information service;Only when the sum of the costs of passive management of e-commerce platforms,penalties for merchants,and the additional revenue generated from the active management exceeds the cost of the active management of the e-commerce platforms,it ensures effective control over the quality of information service in a stable market environment.Finally,some suggestions are put forward to optimize the e-commerce information service quality control.

Price Masking Strategy of Cross-Border E-Commerce Platform Financing

E-commerce platform financing is a new service pattern of supply chain finance.However,this pattern may bring some new issues when considering the problem of cash flow shortage and financing difficulties of small and medium-sized enterprises.When enterprises use this service,they worry about the leakage of preferential wholesale price when applying the full loan amount and providing the true transaction information.Based on the model consisting of a supplier,a retailer and a cross-border e-commerce platform,the authors design a price masking strategy to prevent the retailer’s preferential wholesale price information from leakage.The authors analyze the profit of the retailer and the platform before and after adopting the price masking strategy.The authors find that the price masking strategy always benefits the retailer.Besides,the optimal profit of the retailer and the platform are both affected by the loan interest rate.Moreover,there exists a range of loan interest rates that can benefit both the retailer and the platform if the price masking strategy is adopted.The research emphasizes that platform can expand the total business volume by allowing retailers to use price masking strategy.In other words,there will be more and more retailers attracted by the strategy,which benefits the long-term growth of cross-border e-commerce platform financing.

Study on the Tort Liability of Electronic Commerce Platform

Today,the rapid development of electronic commerce(E-commerce)has added a new driving force for China’s economic development.However,all kinds of legal problems have followed,such as uncontrolled production and sale of fake goods,frequent malicious complaints,endless unfair competition,and illegal infringement,which have harmed the legitimate interests of consumers and seriously damaged the market order and fair competition.In order to provide some theoretical and realistic reference for the development of China’s E-commerce industry,this paper focuses on the relevant problems in the field of“infringement”of E-commerce platforms for in-depth thinking,and puts forward suggestions for solving the existing problems based on the development status of E-commerce platforms.

Study on Tourism Electronic Platform based on Large Data Background

A big scale data poses a great challenge to data storage, management and data analysis. This article analyzes the basic concepts of large data, and mainly used on large data makes the simple contrast. And paper put forward a platform of regional characteristics based on electronic business information publishing system. Finally the paper gives general model and the realization of the platform structure, key technology and process. The platform uses conversion technology of StrutsCX framework based on J2EE platform and the XSLT parsing template of XML document tree that generates and provide automation platform construction features site for the user, it can quickly set up a tourism industry application component with plug-in manner.

生鲜电商平台消费者购菜意愿多元提升路径及适配组态研究

基于南昌市519份调查数据,运用技术接受模型3和期望确认理论模型,采用fsQCA方法对生鲜电商平台消费者购菜意愿进行组态分析,探讨消费者购菜意愿适配组态的要素构成条件及提升策略。结果表明:单一条件变量均不是生鲜电商平台消费者购菜意愿的必要条件,说明变量间可能存在替代作用;存在乐趣性与顾客认可型路径、适应性与情感导向型路径、体验感与顾客评价型路径、个性化与挑战导向型路径、影响力与便利导向型路径等5条产生高购菜意愿的路径;其中,高主观规范和高满意度作为核心条件存在于4条路径中,对生鲜电商平台消费者产生购菜意愿发挥着更普适的作用。基于此,建议整合多元路径,根据组态效应调整购菜意愿提升策略;确保产品质量,提升售后服务,重视满意度的普适性作用;建立良好口碑,发挥社交圈的积极作用,以实现平台发展的良性循环。

Comparative Analysis of the Effects of False Low-Price Marketing Strategy on Multiple Platforms

In order to make full use of the characteristics of commodity prices,merchants on e-commerce platforms have adopted the low-price marketing strategy.Regular promotional discounts can bring new vitality to the commodity sales market,but extreme discount marketing methods would lead to serious impacts on the sales of competing products,thus affecting the stable development of the online shopping market.The sales data of four electrical products using the false low-price marketing strategy on three e-commerce platforms(Taobao,JD,and Amazon)were used in this study.The sales data from different e-commerce platforms and different time periods were analyzed,and one-way ANOVA was used on the factors affecting the effect of marketing strategy.The results showed that there is a significant difference between the direct marketing of high-priced products and low-priced products on Taobao;the difference between the marketing effects of high-priced products and mid-priced products on JD and Amazon is significant.This analysis would help businesses formulate reasonable marketing strategies and promote the stable development of the online shopping market.