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.

A Carbon Isotopic Stratigraphic Pattern of the Late Palaeozoic Coals in the North China Platform and Its Palaeoclimatic Implications

This paper gives the stable carbon isotopic data in coals from the Late Namurian to Kazanian stages in the Serteng Mt., Xishan and Huainan coalfields of the North China Platform. Its stratigraphic pattern shows that several isotopic shifts are apparent, and the large δ13C negative shifts (approximately 2.5 to 3.0 %%) occurred during the Stephanian, Artinskian and Kazanian are observed in three Permo-Carboniferous coalfields. Those negative shifts are neither related to the coal rank and coal macerals, nor caused by the variety of peat-forming plants. The general decrease in the δ13C values of the Stephanian, Artinskian and Kazanian coals is consistent with an overall decrease in the δ13C values of ambient atmospheric CO2 and/or a relative increase in atmospheric Pco2 during the coal-forming periods. Therefore the authors postulate that the oxidation of peat, and the δ13C-depleted CO2 flux into the atmosphere during the above stages may have contributed to coeval palaeoclimatic warming by way of the greenhouse effect.

The Relationship between the Distribution of Thick Coal Belts and the Late Carboniferous-Early Early Permian Marine Transgression-Regression in the North China Platform

Four great second-order transgressions occurred during the Late Carboniferous to early Early Permian and they came from both the eastern and western sea areas in the North China Platform. As time went on, depocentres, depositional extent, transgression directions, coastline position and distribution of minable coal seams were changing continuously. The third great second-order transgression occurring at the beginning of the early Early Permian marks the maximum transgression period and before its arrival, i.e. at the close of the late Late Carboniferous, there was the super-regional coal-forming environment. During the second, third and fourth transgressions, the northern North China Platform was all along situated on the transgressive margin of the epicontinental sea and became the major distribution area of thick coal belts because it maintained a coal-forming environment for a long period of time from the close of the late Late Carboniferous to the Early Permian.

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.

黑岱沟露天煤矿安全培训管理平台的设计构建

为了解决工学矛盾,减少传统安全培训方式对人力和物力造成的浪费,进一步提高安全培训的组织效率,提升安全培训效果;分析了我国相关法律法规对露天煤矿安全培训的要求,基于互联化+安全培训的模式构建了安全培训管理平台;安全培训管理平台实现了对培训计划、项目开展与档案管理情况的全过程管理,提升了教育培训和人才评价工作质量,更好地服务了高素质专业化人才队伍建设。

基于云平台的煤矿数据中心研究与应用

随着智能化矿山建设的逐步推进,应用系统数量逐渐增加,数据不能够完全统一、系统缺乏统筹管理、功能重复建设等问题逐渐凸显。为此,以伊敏露天煤矿数据中心为例,详细分析了煤矿数据中心的总体架构,结合工业私有云开发平台及大数据技术建立了开放式、持续集成和部署、支持高负载弹性伸缩、满足智能化露天煤矿管理理念的数据中心,基于数据中心多源数据存储架构解决了矿山领域数据采集难、数据无法统一存储、业务系统孤岛和采地测专业无法及时便捷共享数据等问题,同时综合利用已有设备及其采集的系统数据,采用数据共享和计算分析工具实现生产情况和设备状态的实时掌控,提升了管理决策能力和手段。

基于机器视觉的煤尘环境下掘进空间煤岩界面感知与精准识别

巷道掘进过程中煤岩识别技术是掘进机截割头自动调整的核心,同样是制约矿山智能化建设的关键难题之一。针对当前采掘失衡,掘进工作面缺乏成熟有效的煤岩识别方案,现有基于图像的煤岩识别模型存在分割精度差、无法灵活部署等问题,提出一种应用在掘进工作面下基于图像分割的煤岩截割界面感知与精准识别方法。该方法结合掘进工作面实际截割情况,采用Mobile-NetV2特征提取网络作为DeepLabV3+的主干网络,使模型更好地兼顾分割精度和模型复杂度;将空洞空间卷积池化金字塔模块输出的高级特征进行通道注意力(SE)操作,分配通道权重以强化对重点特征信息的训练;在主干网络输出的浅层特征引入通道空间注意力(CA)机制,使浅层特征图中的低级表征信息加权,从而设计出融合双注意力机制于DeepLabV3+的煤岩截割界面识别模型。同时搭建煤尘环境下煤岩识别实验平台模拟掘进机截割后形成的煤岩截割面,研发巷道掘进过程中煤岩截割界面采集方法,并以实际矿井的掘进工作面为工程背景,验证该煤岩识别模型的分割精度以及实际应用性。研究结果表明:SE-CA-DeepLabV3+模型的平均交并比和平均像素精度分别为97.15%和98.51%,相较于其他模型具有更优的分割性能。将所建立模型对来自陕北试验矿井掘进工作面的原始煤岩图像进行验证,平均误差为0.7%,每秒传输帧数为43 fps,满足井下现场应用部署条件。

安徽省关闭煤矿资源调查及其综合利用研究

【目的】在煤炭资源持续高强度开发与能源供给侧结构性改革的背景下,安徽省关闭了一批资源枯竭、产能落后的煤矿,而关闭煤矿仍赋存有地下空间、遗煤、瓦斯、矿井水、土地与基础设施设备等资源,开展关闭煤矿资源再利用具有现实的工程价值和经济效益。【方法】统计自2013年以来安徽省59座关闭煤矿基础信息和再利用现状,分析关闭煤矿分布特征、遗留资源与再利用潜力;构建安徽省关闭煤矿数据库与WebGIS云平台,实现关闭煤矿信息查询分析与可视化;以潘一矿与石台煤矿为例,分别介绍遗留瓦斯抽采与半地下抽水蓄能的关闭煤矿再利用方案。【结果和结论】结果表明:安徽省关闭煤矿主要集中分布在两淮矿区,部分关闭煤矿关闭时间较短、遗留资源丰富、产权隶属清晰,再利用潜力较大;潘一关闭煤矿综合使用封闭墙压管抽采、原抽采钻孔抽采和地面钻井抽采的立体化遗留瓦斯抽采技术,实施关闭煤矿采空区“排水-抽采-利用”的一体化工程,3年内累计抽采瓦斯量4 840万m^(3)、发电8 590万kW·h、直接经济效益5 120万元,同时保障了相邻矿井的安全生产;石台关闭煤矿拟建设半地下抽水蓄能电站,地下空间可提供有效库容30万m^(3)、装机容量35 MW。案例分析表明安徽省部分关闭煤矿资源再利用在技术经济上具有合理性,但仍需开展进一步深入研究。

矿区践行生态文明建设高质量发展总体设计及案例

科教融合、产教融合立体化平台已成为推动生态文明建设和高质量发展的重要途径,各地政府出台了一系列支持政策,鼓励企业与高校合作,加强人才培养和科技创新。本文采用文献资料法、案例分析法和比较研究法等,在对国内外科教融合、产教融合实践进行梳理和分析的基础上,以中煤平朔矿区黄土高原矿区土地复垦野外科学观测研究站为基础构建的数据观测-规律发现-技术转让-政策制定一体化产学研协同平台为案例,分析了科教融合、产教融合发展的历程和成效,系统设计了基地在科学研究、教育教学、科学普及和文化建设等功能方面提升的内容和路径,旨在为我国同类企业提质增效、高校复合型人才培养及资源型城市绿色转型提供本土化可借鉴模式。