Development Of E-commerce Industry Research Articles

Form Uncertainty to Sustainable Decision-Making: A Novel MIDAS–AM–DeepAR-Based Prediction Model for E-Commerce Industry Development

Global efforts to build sustainable e-commerce ecosystems through various prediction tools have suffered due to uncertainty in politics, the economy, and the environment. This paper proposes a new integrative prediction model to track the sustainable development of e-commerce. Using US e-commerce data, this study explores the prediction accuracy of the mixed data sampling (MIDAS) model in combination with the attention mechanism (AM) approach, analyzing the performance differences between the model’s before and after improvements. More so, the paper evaluates the performance of the new prediction approach against other competing models using the prediction accuracy metric, the probability interval test, and the Diebold and Mariann (DM) test methods. The results indicate that the introduction of the MIDAS and the AM approaches allows the prediction model to fully utilize the effective information of the mixed-frequency data while simultaneously capturing the differences in the importance of the variables in terms of their time series and the non-linear relationship of the learning variables, thereby positively influencing the economic prediction of the e-commerce industry. Second, the proposed prediction model combines the ability of long-term and short-term high-precision prediction and performs multi-step probability prediction on the development of the e-commerce industry. It can better track abnormal changes in macroeconomic indicators and fit their fluctuation trends. Third, based on the results of the three evaluation indicators, the MIDAS–AM–Deep autoregressive recurrent neural network (DeepAR) model achieves optimal prediction accuracy, allowing it to provide more timely, accurate, and comprehensive predictions for e-commerce management decisions when macroeconomic conditions are undergoing significant transformations.

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

Study on the effect of county e-commerce development on rural residents' income growth

Against the background of rural revitalization and the development of county-level e-commerce industry, based on the data of Caoxian County of Heze, Shandong Province from 2017 to 2021, this paper studies the promotion effect of county-level e-commerce industry development on urban and rural residents' income through grey relative correlation analysis. The results show that the impact of the development of county e-commerce industry on the operational income of urban and rural residents is similar, and the impact on the operational income of rural residents is partly greater than that of urban residents, and the effect is not obvious. The influence of the development of county e-commerce industry on the wage income of rural residents is greater than that on the wage income of urban residents.

Application of sensor-based speech data mining in E-commerce operations data analysis

With the rapid development of the e-commerce industry, enterprises need to effectively manage and analyze various operational data to support decision making and optimize business processes. Sensor technology is widely used in e-commerce environment, which can collect a lot of voice data and extract valuable information through data mining technology. The study presents the current background and trends of the e-commerce industry, with a focus on the importance and challenges of operational data analytics. A sensor-based voice data mining framework is proposed. Sensors are first used to collect voice data and turn it into a digital signal that can be used for analysis. Then the data mining algorithm is used to process and analyze the voice data, and a series of results about e-commerce operation are obtained. Analyze voice data to help companies develop effective marketing strategies, improve product quality, and optimize supply chain management. This study proves the role of sensor-based voice data mining in e-commerce operational data analysis. By harnessing the full potential of voice data, businesses can better understand and meet customer needs, improve competitiveness and performance. This research result has practical significance for the development of e-commerce industry, and provides guidance and reference for the research and practice in related fields.

Research on E-commerce Logistics Distribution Path Optimization Based on Ant Colony Algorithm

With the rapid development of e-commerce industry, the efficiency of logistics and distribution has become a key constraint to its further development. In this paper, we explore the optimization of e-commerce logistics and distribution paths through the ant colony algorithm, aiming to improve the distribution efficiency and reduce the cost. The study firstly analyzes the core elements and challenges of e-commerce logistics and distribution paths, and then describes in details about the ant colony algorithm and its application to path optimization. By constructing a model adapted to the characteristics of e-commerce distribution, we use the ant colony algorithm to optimize a variety of different sizes and complexities of distribution paths. By constructing a model adapted to the characteristics of e-commerce distribution, we use the ant colony algorithm to optimize a variety of distribution paths with different sizes and complexities, and the experimental results show that the algorithm can effectively reduce the total distribution distance and cost. In the test cases, we observe that the distribution paths are shortened by 15\% on average, and the distribution cost is reduced by about 20\%. These results prove the effectiveness and feasibility of the ant colony algorithm in the optimization of e-commerce logistics distribution paths. This study provides a new idea for e-commerce logistics distribution path optimization, which is of great significance for improving logistics efficiency and reducing operation cost.

E-commerce Industry Supply Chain: Status, Problems and Countermeasures

In recent years, the e-commerce industry has been developing rapidly, and at the same time, the quality level of e-commerce industry development is limited by the level of supply chain technology development. As a result, the development of supply chain technology has become the core of the driving force for various enterprises to pursue development. This paper analyses the supply chain status quo of e-commerce industry, finds the problems of excess inventory leading to backlogs, high loss rate of goods leading to waste of resources, and negative impacts caused by failure to deliver on time, and proposes the establishment of perfect supply chain management norms, the establishment of incentives, and the establishment of a research department; the use of cold chain transport, multi-modal transport, the use of automated systems, the establishment of inventory systems, the upgrading of technology, the enhancement of training, regular inspection and maintenance of equipment; the enhancement of management and management of equipment. Regular inspection and maintenance of equipment; strengthening management, improving risk control, establishing a supply network, optimizing routes, and improving service quality are some of the solutions.

Research on the Impact of ChatGPT on The Economic Development of E-commerce Industry

This article summarizes the impact of the new artificial intelligence technology ChatGPT on the economic development of the e-commerce industry and provides an analysis of two main aspects. Firstly, this paper studies the application mechanism of ChatGPT in the e-commerce industry. By investigating the specific application of ChatGPT on the e-commerce platform, including fine recommendation, intelligent customer service and consumer insight, the potential of ChatGPT in improving the operational efficiency of e-commerce enterprises is revealed. The research results show that ChatGPT can provide personalized services and suggestions, help improve the quality and efficiency of customer service, and reduce the workload of manual customer service. Secondly, we predict the impact of ChatGPT on the future development of the e-commerce industry by mining the characteristics of Amazon's financial data. The results show that ChatGPT is expected to meet these challenges and have a positive impact on the e-commerce market. For example, the introduction of ChatGPT technology may change the competitive landscape of the e-commerce market and increase market concentration ; at the same time, ChatGPT's personalized recommendations and suggestions can improve consumers' shopping satisfaction and purchase rate, and promote the development of the e-commerce industry. In summary, this paper reveals the potential positive impact of ChatGPT on the economic development of the e-commerce industry by analyzing the application mechanism of ChatGPT in the e-commerce industry and predicting its impact on the future development of the e-commerce industry. These research results have important reference value for decision makers and practitioners in the e-commerce industry, and can help them better understand and respond to the challenges and opportunities of new artificial intelligence technologies for the industry.

A Study on Identifying the eCommercePlayers and Business Model

The aim of the paper is to analyze the eCommerce industry development in order to create the theoretical base for the business valuation process, in the case of the eCommerce industry (particularly refer to the online retail industry). Considering this research approach, the most important part of a valuation base and drivers analysis is to identify the relevant companies and by a detailed understanding of their business model, to recognize which companies can be compared to each other. The presented study’s conclusions will underline important issues for the companies’ valuation process.

A Study of Growth of E-Commerce Business of India in Post Pandemic Era: An Overview

Nowadays, e-commerce industry in India, emerges one of the largest growing retail industries in India, during the period of pandemic almost all the sectors or business operations remain closed, but e-commerce industry providing all essential goods and services to the people of India by following COVID related guidelines. Therefore, people of India relying on e-commerce industry instead of local retail market and outcomes of that, e-commerce industry in India increased by 21.5% in 2022 and reaching US $ 74.8 billion. It is also expected that e-commerce industry will grow 84% to $ 111 billion by 2024 as well as US $ 350 billion by 2030. This is the sign of growing and development of e-commerce industry in India. About 830 million (2021) of people using smartphones in India and e-commerce industry is also mainly driven by mobile shopping, social media, etc. So, it is predicted that mobile shopping is increase by 21% annually in next four years. As per the data available 40% of people using mobile wallets, 15% Credit Cards, 15% Debit cards and remaining using other payment system for shopping, this payment mode is also playing vital role in the growth of e-commerce industry in India. Because currently e-commerce industry is not limited up to traditional website, e-commerce players or retailers develops their smartphone-based applications to ease of access and shopping, this system helps to grow number of users of application and it will be converted in to end user or consumer. Therefore, it is become necessary to study the growth and development of e-commerce industry in post pandemic era in India.

An Assessment of Consumer Awareness and Coverage of Digital Television Services in Uganda

Nowadays, e-commerce industry in India, emerges one of the largest growing retail industries in India, during the period of pandemic almost all the sectors or business operations remain closed, but e-commerce industry providing all essential goods and services to the people of India by following COVID related guidelines. Therefore, people of India relying on e-commerce industry instead of local retail market and outcomes of that, e-commerce industry in India increased by 21.5% in 2022 and reaching US $ 74.8 billion. It is also expected that e-commerce industry will grow 84% to $ 111 billion by 2024 as well as US $ 350 billion by 2030. This is the sign of growing and development of e-commerce industry in India. About 830 million (2021) of people using smartphones in India and e-commerce industry is also mainly driven by mobile shopping, social media, etc. So, it is predicted that mobile shopping is increase by 21% annually in next four years. As per the data available 40% of people using mobile wallets, 15% Credit Cards, 15% Debit cards and remaining using other payment system for shopping, this payment mode is also playing vital role in the growth of e-commerce industry in India. Because currently e-commerce industry is not limited up to traditional website, e-commerce players or retailers develops their smartphone-based applications to ease of access and shopping, this system helps to grow number of users of application and it will be converted in to end user or consumer. Therefore, it is become necessary to study the growth and development of e-commerce industry in post pandemic era in India.

Research on the impact of artificial intelligence-based e-commerce personalization on traditional accounting methods

With the development of artificial intelligence technology in various fields, the traditional accounting method is no longer applicable to the personalized development of e-commerce industry; Therefore, it is essential to improve the accounting method and construct a personalized recommendation model for e-commerce. Based on this background, this study firstly reconstructs the steps of accounting element recognition in the traditional accounting system and constructs an automated accounting recognition mechanism using BP neural network algorithm, aiming to improve the accuracy and efficiency of accounting element recognition; Secondly, a personalized e-commerce recommendation model based on multiple intelligence is built, which uses intelligent Q-learning algorithm to optimize the recommendation module, aiming to improve the accuracy of personalized recommendation. By comparing the performance of different accounting models under different personalized e-commerce systems, the accounting model proposed in this paper can predict the accounting entries well under the three-layer BP neural network, and the error between the maximum predicted value and the actual value is 0.23%. The recommendation model proposed in the study outperforms the traditional recommendation model and the recommendation model under collaborative filtering algorithm in predicting customers' personal preferences, whose predicted value is closer to the real situation. In summary, both the accounting method and the personalized recommendation model for e-commerce proposed in this study can achieve better application results, thus providing a new idea for the development of the e-commerce industry.

Value chain analysis of cross border e-commerce foreign trade driven by networked manufacturing mechanism

With the rapid rise of the Internet and the rapid development of e-commerce industry, the concept and research of cross-border e-commerce foreign trade oriented to networked manufacturing mechanism are deepening. Based on the continuous progress of modern information technology and the corresponding network sharing technology, it is inevitable to analyze the value chain of cross-border e-commerce foreign trade under networked manufacturing mechanism. This paper will model the corresponding foreign trade value chain of cross-border e-commerce based on the networked manufacturing mechanism, and based on the current economic environment of small and medium-sized cross-border e-commerce, analyze the internal advantages, external advantages, external opportunities and internal opportunities and challenges of current small and medium-sized enterprises' foreign trade e-commerce based on SWOT analysis method, and give the corresponding cross-border e-commerce value chain of small and medium-sized enterprises The corresponding value chain relationship and social status of e-commerce. In the end, this paper gives the development strategy of cross-border e-commerce of SMEs and the corresponding development model.

Introduction to the Development of China's E-Commerce Industry

In recent years, with the popularity of the Internet and the upgrading of technology, China's e-commerce industry has experienced explosive growth. E-commerce is becoming an inseparable part of people's life. With the development of the e-commerce industry, behind the prosperity of Internet e-commerce, it is also bound to face the problems of industry development, such as the scarcity of talents, imperfect construction of the rule of law, logistics services do not match. This paper analyzes and discusses the difficulties of e-commerce development from the characteristics of the current situation of e-commerce development in China, and puts forward corresponding countermeasures. E-commerce may encounter different problems and difficulties in the process of development, but it is believed that through the joint efforts of the government and all parties, it will be continuously improved and eventually provide more convenient services for people's lives.

Training Strategies of E-Commerce Professionals Serving Regional Economic Development

With the advent of the Internet economy era, many e-commerce enterprises have sprung up in China, which drive the regional economy. The emergence of e-commerce enterprises in regional economy makes the e-commerce market face a shortage of talents, so there are great employment opportunities for students majoring in e-commerce. However, there is still a certain gap in the training of e-commerce students in China, and the lack of enterprise practice opportunities for e-commerce professionals is not conducive to the vigorous development of e-commerce industry in the future. This paper analyzes the current situation of the training of e-commerce professionals serving the regional economic development, and puts forward the training strategies of e-commerce professionals.

The change of supply chain in the transformation of traditional retail enterprises to new retail enterprises: A case study of Chinese RT-Mart

With the development of e-commerce industry and the arrival of the new retail era, traditional retail enterprises have to step into the field of e-commerce, change the sales model and redesign the complete new supply chain. This paper mainly introduces the market competition environment and internal reform pressure faced by traditional retail enterprises, taking Ruentex-Mart as an example, analyzes the advantages and problems of supply chain reform, and puts forward corresponding solutions for other traditional retail enterprises.

Big Data-Based E-Commerce Transaction Information Collection Method

With the rapid development of e-commerce industry, online shopping has become a craze. With the rapid growth of transaction volume on e-commerce platforms, a large amount of transaction data has been accumulated. From the transaction information of these users, a lot of very valuable information can be mined, such as the defects of products and the actual needs of users. In view of the existing e-commerce transaction information collection method is not mature, in this paper, the electric business platform system architecture planning and design increases the function management module. In this paper, a new Naive Bayes model is established by using HBase distributed database instead of traditional database. Based on the optimization and extraction of the important transaction information in the product, the dataset of e-commerce transaction information is updated. Through the efficiency test of the collection method, the information scalability ability test, and the accuracy test, the important context was sorted out after integration, the sources of trading information were sorted out, and the data analysis of the collected information was conducted to optimize the information collection method and verify the feasibility of the method.

The Impact and Empirical Analysis of the Development Level of E-commerce Industry on China’s Export Trade

With its advantages of low cost and high efficiency, e-commerce is not only favored by ordinary consumers, but also effectively promotes SMEs to find business opportunities and win the market. This article starts with the development scale of China’s e-commerce industry and the status quo of export trade, and measures the overall index of China’s e-commerce industry development level from 2008 to 2018 through empirical methods to analyze its impact on China’s export trade. The results show that the development level of the e-commerce industry has a significant positive impact on China’s export trade. Finally, it analyzes the existing problems in the development of China’s e-commerce industry.

Policy Analyses on Promoting the Recycling of Express Packages

With the development of e-commerce industry, the express enterprises are growing up rapidly. At the same time, they produce a large amount of express packaging garbage. The recycling of express packages has become an important issue for environment protection. In this paper, three types of possible policies are discussed for consideration: subsidy, penalty, and tax reduction. We analyze the efficiency of each policy and find the conditions under which the express packaging manufacturers prefer to recycle and reprocess the used products. A two-stage model is established from the perspective of manufacturers to discuss the production and recycling strategies under the three policies. Besides, we suggest an optimal choice between subsidy and tax reduction for the government when the budget is fixed. This paper provides guidelines for the government to improve related policies on promoting the recycling of express packages.

Research on Cross-border E-commerce Platform Supplier Credit Evaluation Based on Big Data Interconnection

This paper first analyzes credit assessment of cross-border E-commerce platform suppliers based on big data from two aspects: credit evaluation index system and credit evaluation model. On this basis, this paper summarizes the recommendations of supplier credit assessment for cross-border E-commerce platform based on big data, in order to provide reference for the work of supplier credit assessment for cross-border E-commerce platform from the perspective of big data, hoping that this study can help promote the cross-border E-commerce platform construction and cross-border E-commerce industry development.

Research on Fresh Products for Fresh E-commerce

At present, opportunities and challenges coexist in the development of e-commerce industry, which develops rapidly, but there are also many problems. Among them, the offline cold chain logistics that puzzles fresh e-commerce has not been a good solution, the key reason is that there are too many uncontrollable factors of logistics distribution, storage and fresh, and lack of high quality cold storage to meet the needs of e-commerce. This paper analyzes a series of problems of cold storage from the aspects of temperature, space location, packaging design and distribution. Finally, we can solve these problems through temperature control technology, bar code technology and advanced cold chain technology.