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.

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.

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.

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.

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.

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.

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.

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.

数字平台自我优待的反垄断规制困境与优化进路

平台企业为开拓商业疆土,通过数据垄断、流量封锁等方式优待下游市场的自营业务,实现竞争优势乃至垄断地位的跨市场传导。从本质上来看,竞争优势的传导超越一定限度即可能构成滥用,不属于合法竞争的范围。平台自我优待由于符合杠杆理论对滥用行为的共同要求,应当被纳入反垄断法的规制范围。然而,鉴于我国当前该行为违法性统一认定标准缺失、反竞争效果难以判定、正当性抗辩理由滥用三项因素模糊了自我优待的反垄断规制边界,故在重塑分析框架基础上对其有针对性展开优化,明确平台自治的合理限度,以期为规制指明未来走向。

互联网平台企业滥用市场支配地位的认定与规制

数字平台现已成为互联网经济发展的重要基础,互联网平台所具有的潜在动力不仅拓宽了社会公众的消费渠道,也带动了平台企业的转型升级。因互联网平台企业自身的免费定价模式、动态竞争以及网络外部性特征区别于传统企业经济,进而出现了平台反垄断现象。互联网平台企业的属性构造、相关市场和行为类型都对滥用市场支配地位的认定有所影响。因此应遵循回应型规制方式,对互联网平台企业实施分类监管,不断完善认定思路,精准规制滥用行为,从而保障互联网平台企业的平稳运行。

网络平台不作为的刑事归责:理据、路径及限度

网络平台能够精确匹配供需,迅速提高社会资源的配置效率,对我国社会经济的发展作出了重要贡献。但一系列案件显示,网络平台不作为与重大法益侵害之间具有因果关系。不能以“中立帮助行为论”否定网络平台不作为的刑事不法性。具有作为义务是平台成立不作为犯的前提条件,作为义务在实质上来源于行为人对“结果发生原因的支配”。网络平台作为义务的内容在相关法律法规中已有明确体现,但形式上的义务必须接受实质义务论的检验。对于网络平台的故意不作为,存在正犯与共犯两种归责路径,正犯归责的法律门槛较高,在绝大多数情况下都应从共犯角度考察其刑事责任。帮助信息网络犯罪活动罪并非立法上对帮助行为的正犯化,按照该罪对网络平台不作为进行定性仍然是对共犯归责路径的延续。具有间接帮助性质的平台不作为也应被纳入刑法的打击范围。网络平台的过失不作为不可能成立刑事犯罪。

网络房地产经纪服务平台垄断行为规制进路

网络房地产经纪服务平台的经营模式高度依赖平台规则、算法技术、房源数据、用户数据等要素。一旦平台利用算法组织平台内经纪机构达成垄断协议,或是滥用市场支配地位,利用平台规则及数据分析、数据处理能力,收取高价经纪服务费用,滥用平台内经纪机构和消费者的数据,就会对网络房地产经纪服务市场的竞争秩序造成破坏。为此,应结合网络房地产经纪服务平台的模式与特点,审慎衡量平台行为对市场竞争产生的影响,着重关注平台是否合理利用算法、房源数据、客户数据等生产要素实施经营行为,考察网络平台行为是否违反《反垄断法》。

平台经济中优势地位滥用说之质疑——兼评《反不正当竞争法》修订草案第13条

滥用相对优势地位条款被引入反不正当竞争法的目的之一便是规制平台中不公平交易问题,但争议颇大。优势地位说是反垄断法中支配地位说的降格,同时剥离结构分析的前提,看似加大对优势平台的监管,实则会导致条文滥用和经营风险,伤害市场秩序的可预期性。优势地位依赖于企业市场力量,网络平台基于渠道资源自然形成规模经济与优势地位,是发展的必然结果,而平台上经营者为逐利依附于平台属自愿行为。平台合法利用优势地位扩大盈利能力与交易效率并无不当,对违法利用优势地位的规制必须回到滥用支配地位的反垄断监管框架中。若期待对损害公平竞争的滥用行为进行直接监管,法律应直接予以类型化,而非新设一般性专条。

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.

数字经济背景下互联网平台滥用市场支配地位行为的认定

在数字经济背景下,数据、算法、流量等因素成为市场竞争的核心要素。尽管传统相关市场界定方法仍有适用空间,但必须根据互联网平台的双边市场结构、网络效应、锁定效应等特征进行调整。面对市场份额弱化、新型市场壁垒等问题的冲击,判断市场支配地位需要在结合互联网平台特征的基础上做出相应的改变。随着算法与人工智能等新技术被广泛运用于市场经营中,滥用市场支配地位行为的表现形式更加多样,同时也更为隐蔽,其违法性判断的难度进一步加大。限制竞争效果应该从对市场竞争和消费者利益的影响两方面出发,在个案中予以界定。互联网平台天然具有一定程度的垄断特征,这并不必然具有违法性与可罚性。在包容审慎的执法理念下,应该从反垄断法价值追求的角度出发界定正当理由,且不能设立过于严格的适用标准。