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.

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.

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.

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.

Plants: The Future Pharmaceutical Factory

The main objective of this study was to identify prospects, advantages and challenges of plant molecular farming. Plant-made pharmaceuticals (PMPs) and plant made vaccines (PMVs) were intended to be used for human consumption. A broad range of plants, including crops, vegetables and fruits have been investigated for their applicability in production of pharmaceuticals over the last two decades. At present, mainly maize, rice, tobacco and safflower are used in open field production. Contained bioreactor-type systems focus on moss, algae and plant organ culture. Expression systems include stable transformation of plant genomes—both nuclear and plastid, which are also used in the generation of genetically modified crops, plant-viruses and transient expressions. Each expression system (production platform) offers different advantages and disadvantages. Production platform choice is perceptive and depends on a broad range of criterion. This study is based on literature reviews, document analysis and internet database browsing.

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.

罕见病寻医找药多功能智慧化药学服务平台的建立与应用

目的加强罕见病患者合理用药管理,提高用药综合保障水平,以解决罕见病用药痛点问题。方法借助移动信息化技术,开发广东短缺药品咨询平台应用程序,并建立罕见病患者智慧化多功能的药学信息服务。结果作为中国首个整合省级罕见病医药资源的大数据平台,通过建立完善、专业的罕见病移动式药学服务体系,创新性实现线上线下“医+药+患”三方闭环。结论该药学服务平台为罕见病患者搭建起寻医找药的桥梁,助力健康中国高质量发展。

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.

基于西部儿科发展联盟的儿科药学服务云平台构建

目的探索构建基于西部儿科发展联盟的儿科药学服务云平台,以期为缩小西部地区间、医疗机构间儿科药学服务的差异提供参考。方法以西部儿科发展联盟为基础,依托联盟远程医疗服务网络构建“1+3+3”儿科药学服务云平台,即以重庆医科大学附属儿童医院为1个中心,通过对资源信息、服务流程及组件接口3个方面进行标准化管理,在联盟内开展处方调剂、药学指导、健康宣教3个药学核心服务。结果与结论基于西部儿科发展联盟远程服务网络构建的“1+3+3”儿科药学服务云平台自运营以来,注册人数共计120.8万人,完成在线处方11.2万张、流转处方4.4万张,用药咨询总计10694例次,在线培训人数超1.5万人次。但在运行过程中,该平台存在临床用药数据量少、覆盖区域范围还不够广等问题。随着平台临床用药数据的累积,本项目组将借助人工智能技术提取患者处方信息、用药行为及用药后身体指标等数据,对区域内不同地理环境、不同年龄段、不同身高体重等条件下的儿童药学数据进行关联分析,获取区域内儿童临床用药特征,为进一步指导儿科临床合理安全用药提供决策支持。

“互联网+”药学门诊用药管理体系的建立

目的提高医院药学门诊的药学服务质量。方法制订及完善药学门诊的工作基本流程,统计患者就诊原因,并针对重点人群设计规范化药学服务流程,进行药学门诊用药管理体系的信息化建设,构建智能药学平台(简称平台)并与医院信息系统对接,建立患者用药管理数据库,同时开发平台知识库,构建“互联网+”药学门诊用药管理体系,据此分析2021年1月至2022年12月的医院药学门诊数据;并进一步设计监管统计功能,以客观分析门诊工作情况。结果共纳入医院药学门诊患者2276例,就诊原因以吸入装置(981例,43.10%),慢性病用药(573例,25.18%),妊娠期/哺乳期用药(249例,10.94%)为主;患者就诊时咨询问题以(药物的)用法用量为主(1474例),涉及药物以吸入类药物(1079例,73.20%)为主,其次为注射类降糖药(58例,3.93%),再次为眼/耳鼻喉外用药物(30例,2.04%)。结论该院已初步建立“互联网+”药学门诊用药管理体系,可更快地适应医药卫生体制改革政策下药学服务发展的需求,但仍需在实践中不断完善。

线上线下相结合的药用植物学野外实习模式探究

药用植物学是药学、中药学、中药资源与开发及相关专业的基础学科,而野外实习是药用植物学教学中必不可少的环节。借助药用植物实践网络学习平台,方便学生线上了解野外实习的各个环节,提前开展准备工作以及后期实习成果的展示;利用微信雨课堂平台线上发布实习安排、参考资料、作业、标本识别试题等。线下实践是实习工作的重点,以标本的采集、制作、拍照、路线设计、物种鉴别、总结汇报等方面的考察进行综合评价。以甘肃省徽县麻沿实习基地为例,利用设计规划实习路线,记录药用植物图片及位置;制作《实习区域药用植物实习手册(电子版)》,供预习及实习过程的更新。经过近五年不同实习基地的实践,这种线上线下相结合的实习模式增强了师生互动效率,缩短了信息反馈时间,提高了实习工作效率,提高了学生动手动脑能力,提高了药用植物野外鉴别能力,增强了学生环境保护意识,达到了实习目的。

大都市推动人工智能制药新赛道高质量发展的路径探索

借鉴全球AI制药平台探索经验,通过打造基于临床前数据和临床数据的高质量生物大数据平等方式,打通创新药数据壁垒,有利于国内药企在短期赶上甚至超越跨国药企长期数据积累、变更跟随式创新和安全无效药物发展趋势,找到“干湿结合”的未来生物经济发展路径,引导药企以数据为抓手、以创新策源为方向开展高质量创新研究。

基于“用药管家”服务平台的用药咨询实践及分析

目的探讨“用药管家”服务平台的用药咨询实践,为智能化、个体化互联网用药咨询提供参考。方法收集十堰市人民医院2019年7月至2022年10月“用药管家”服务平台用药咨询中759例药师问答记录,对药师、咨询者和咨询内容相关信息进行统计、分析。结果主任药师、副主任药师和主管药师人均咨询例数分别为110、82.5和74.8例;咨询者年龄主要分布在0~10、>20~30和>30~40岁,其中女性病人占64.16%(487/759);主要涉及泌尿生殖系统、呼吸系统、皮肤和皮下组织、消化系统疾病;咨询内容主要为用法用量、药物不良反应、药物相互作用和特殊人群用药;药品种类主要为中药饮片及中成药、抗感染药物、内分泌系统药物和呼吸系统药物。结论“用药管家”服务平台通过合理配置咨询药师,规范服务流程,为病人提供了智能化、个体化的用药咨询服务,满足了多元化药学服务需求,得到了病人的认可。

基于微信平台的药学服务模式在2型糖尿病合并高血压患者健康管理中的应用效果

目的:探讨基于微信平台药学服务模式在2型糖尿病合并高血压患者健康管理中的应用效果。方法:选取2022年7月—2023年8月佛山市禅城区人民医院收治的2型糖尿病合并高血压患者100例作为研究对象,按照随机数字表法分为观察组和对照组,各50例。对照组采用常规药学服务管理,观察组在对照组基础上采用基于微信平台药学服务模式。比较两组健康知识掌握度、血糖和血压水平、用药依从性。结果:观察组健康知识掌握度高于对照组,差异有统计学意义(P=0.021);干预后,两组空腹血糖、餐后2 h血糖、收缩压、舒张压水平均低于治疗前,且观察组低于对照组,差异有统计学意义(P<0.05);观察组用药依从性优良率高于对照组,差异有统计学意义(P=0.029)。结论:2型糖尿病合并高血压患者采用基于微信平台药学服务模式干预,可以显著提升其自身健康知识知晓率及用药依从性,有利于控制血压和血糖。