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.

Research on the Legal Framework of Content Regulations for Network Platforms

In the era of the Internet,various network platforms have evolved into new hubs for information dissemination.Currently,China has established a platform-centered content regulation framework,wherein platforms proactively enforce content regulations in accordance with legal censorship obligations.Additionally,platform policies and user agreements augment their authority in content regulation.The platforms can achieve cost-effective and highly efficient content regulation by leveraging their strategic advantages enabled by their own technical capabilities and extensive coverage.The platform self-regulation model,however,still faces challenges.First,accurately evaluating content remains a formidable task;second,ensuring effective platform publicity through self-regulation poses difficulties;third,users may potentially face disadvantages due to the platform’s right of self-regulation;and fourth,digital copyright owners face challenges when defending digital copyright disputes under the safe harbor rule.Therefore,it is imperative to establish,review,and revise the legal framework for content regulation of network platforms in order to enhance the efficiency of their governance systems.The formulation of the legal framework for content regulation of network platforms may encompass the following aspects:rationalizing obligations pertaining to platform content regulations,enhancing supervision over platform self-regulation,and establishing a dual-track responsibility system for digital copyright content regulation.This will ensure a harmonious balance among public interests,users’personal rights and interests,and commercial benefits through regulating the content on network platforms.

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.

An Empirical Study on E-commerce Service in the Western China’s Tourism Industry

With the rapid development of China’s tourism industry, e-commerce will bring about new opportunity and challenge to tourism. Hotels and travel agencies play very important roles in tourism industry and their level of application of IT prominently shows the management level and information process of whole tourism. This study uses content analysis to evaluate the web sites service of travel agencies and hotels in the Western China. Moreover, this paper puts forward strategic suggestion for the future development of tourism e-commerce in the Western China.

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.

考虑同侧和跨侧网络效应的UGC平台广告投放和内容创作补贴策略

UGC平台连接着内容创作者和消费者,双边用户间存在的同侧和跨侧网络效应吸引着他们进入一个或多个平台,从而形成不同的部分多归属结构。基于Hotelling模型,通过构建UGC平台的竞争模型,研究了双方均单归属(SS)、仅消费者边部分多归属(MS)和仅内容创作者部分多归属(SM)3种部分多归属结构下同侧和跨侧网络效应影响下的平台广告投放与内容创作补贴决策,以及其对市场份额和平台利润的影响。研究发现:当消费者边单归属(SS或SM)时,平台的广告投放随同侧网络效应单调递减;当消费者边多归属(MS)时,平台的内容创作补贴和消费者规模会随同侧网络效应单调递增,而同侧网络效应对平台的广告投放水平的影响是非单调的,其受到消费者对广告厌恶水平的影响。当消费者边多归属(MS)时,随着消费者边的跨侧网络效应的增加,平台会采取提高广告投放水平和内容创作者补贴,即从消费者处获得更多的广告收入以补贴内容创作者的策略;而随着内容创作者边的跨侧网络效应的增加,平台会降低广告水平并提高内容创作者补贴,即采取同时向两边用户让利的策略。当内容创作者边多归属(SM)时,随着消费者边的跨侧网络效应的增加,平台会同时向两边用户让利;而随着内容创作者边的跨侧网络效应的增加,平台会降低广告投放和内容创作者补贴水平,即降低对内容创作者的补贴而让消费者观看更少的广告。当某一边用户选择多归属时,该边用户的规模会随跨侧网络效应的提升而增长。通过对不同情形下均衡结果的横向比较,还发现双边用户中存在多归属的前提是较强的跨侧网络效应,而内容创作者多归属时,平台更容易对内容创作者提供补贴。

基于虚拟仿真实验教学平台的网络安全实践教学体系研究与构建

基于CC2020胜任力模型,从实现网络安全核心知识的学习、攻防技能的提高、品行的培养出发,对网络安全实验教学体系进行了构建及研究。虚拟仿真实验教学平台和雨课堂平台,为实践开展提供了信息化教学的基础,同时提升了实践教学的可行性和创新性。结合学生现状,从教学内容设计、实验资源建设、教学方法策略、考核评价机制,多角度、多方位地提出了详细建设举措。实践课程的实施对培养网络安全创新型、实战型人才培养具有实际意义和参考价值。

企业社交媒体平台印象管理策略——基于新浪微博数据的内容分析

互联网时代,企业使用社交媒体平台进行印象管理能够改变受众认知,树立良好的企业形象。探讨企业在社交媒体平台上印象管理策略分类,利用数据爬虫软件搜集新浪微博品牌排行榜前10名的企业微博推文,通过内容分析法得出企业在社交媒体平台上经常使用的具体策略有四种:自我呈现、企业社会责任、道歉声明、辩解对抗。此外,还发现企业在道歉声明中还会结合自我呈现或者辩解进行策略地组合应用。

基于知乎平台内容挖掘的元宇宙公众感知研究

[目的/意义]通过分析公众对元宇宙中个体、业界、政府3方面内容的感知,针对性地为个体、企业、政府参与元宇宙生态建设提供建议。[方法/过程]参考三螺旋模型,构建基于个体—业界—政府维度的元宇宙公众感知分析框架,采用改进LDA和BERT算法,基于知乎问答分析公众对元宇宙中个体、业界、政府3方面内容的感知主题,主题的热度、情感及相关演化。[结果/结论]公众在个体、业界、政府维度上的感知既有差异又有联系。演化上,公众关注点逐渐细化深入,态度受体验、舆论影响显著,但趋于理性。通过挖掘不同维度的热点、潜力点及问题,能针对性地为不同主体提供建议。

一流专业建设背景下数字教材建设研究

数字教材是一种新形态的教材形式,它能很好地适应当前高等教育多媒体教学方式的发展需求。在设计数字教材架构体系和编写制作要求的基础上,借助超星学习通平台,以《村镇供水工程》数字教材为例,提出编写制作数字教材的结构体系和内容体系,并将其运用于教学实践,为推动专业课程群建设和发展、促进专业教学改革提供示范支持。