Development Of E-commerce Platform Research Articles

Handling dynamic capacitated vehicle routing problems based on adaptive genetic algorithm with elastic strategy

With the development of e-commerce platforms, the logistics industry is also booming. The transportation process is at the core of the logistics industry, which influences the timeliness and rationality of logistics distribution. In the real world, there are many dynamic demands in logistics distribution, so logistics distribution should deal with dynamic demands quickly to realize more effective route planning. This paper proposes an adaptive genetic algorithm (AGA) with elastic strategy (AGA-ES) to solve the dynamic capacitated vehicle routing problems (DCVRPs). Firstly, AGA designs an adaptive local search operator, which can adaptively adjust the quantity of nodes that need local search, according to the fitness value of different individuals. At the same time, AGA develops adaptive crossover and mutation operators, which can automatically adjust the crossover and mutation probability based on the different fitness values. The experimental results verify the better performance of AGA on the traditional capacitated vehicle routing problems (CVRPs). After that, AGA combines elastic strategy (AGA-ES) to solve DCVRPs. This paper mainly concerns three types of actual demand information in DCVRPs: distribution nodes increase, distribution nodes decrease, and distribution road conditions change, according to the actual background. AGA-ES could interact with demand information and judge the types of different demands, and then adaptively plan new and reasonable routes after receiving one or more of the above demand information. The verification of benchmark data sets shows that AGA-ES can effectively deal with DCVRPs. Furthermore, this paper collects the longitude and latitude coordinates of 100 SF express stations in Xi’an, constructs the distribution information of these express stations, and verifies that AGA-ES can solve the DCVRPs under the actual background.

Determinants Of Intention To Use E-Commerce Based On The Technology Acceptance Model

Due to the development of e-commerce platforms in Indonesia, it is important to understand the factors that encourage user acceptance. This study explores the determinants of users' behavioral intention to use e-commerce platforms based on the Technology Acceptance Model (TAM). TAM is represented by perceived ease of use and perceived usefulness. This research is a quantitative study with data collection techniques through distributing questionnaires. The sample in this study was 100 respondents. The analysis technique used multiple linear regression analysis through SPSS 26. The results showed that perceived ease of use and perceived usefulness had a significant positive effect on behavioral intention to use. This provides actionable insights for businesses to conduct sales strategies by considering consumer perceptions of e-commerce users.

The Impact of Sales Promotion, User Interface and User Experience Design on Shopee App Users' Repurchase Intentions

By 2022, Gen Z and millennial consumers dominated Shopee usage in Indonesia. Similar e-commerce platforms are forced to constantly innovate to remain competitive in the market due to increasing competition. Therefore, the primary focus of e-commerce platform development should be on the user interface, user experience design, and promotions that are appealing and easy to access so that potential customers are inclined to repurchase. This research aims to determine the influence of UI design, UX design, and promotions on the repurchase intention of users of the Shopee application. The sampling method used was systematic sampling. Ninety-six respondents are included in the sample. This study uses descriptive analysis, classical assumption tests, multiple linear regression, and hypothesis testing for data analysis. SPSS Statistics 28.0 was used for data processing. The study found that user interface design, user experience design, and sales promotions statistically impact the repurchase intention of users of the Shopee application. The results demonstrate the effectiveness of repurchase intent in e-commerce.

Research on the Influencing Factors of the E-commerce Adoption Behavior of New Agricultural Business Entities under the TAM Model

<p>Based on the theoretical model of technology acceptance, this paper uses 372 questionnaire data to explore the influencing factors of the e-commerce adoption behavior of new agricultural business entities. The results show that: (1) Among the factors affecting the e-commerce adoption behavior of new agricultural business entities, perceived usefulness has the strongest impact, followed by perceived ease of use, and its standardized impact path coefficients are 0.81 and 0.20, respectively; (2) Perceived ease of use Usability not only positively affects the e-commerce adoption attitude of new agricultural business entities, but also positively affects the perceived usefulness of new agricultural business entities; (3) The e-commerce adoption attitude of new agricultural business entities positively affects their adoption behavior. Therefore, this paper puts forward relevant suggestions to improve the willingness of new agricultural business entities to adopt e-commerce, and then guide the sustainable development of e-commerce platforms.</p>

Differences Analysis Between China and the United States in the Development of E-commerce

Nowadays, online shopping has become a very common form of shopping in China. The sales of shopping carnivals such as 618 and single day also allow people to intuitively see the continuous development of e-commerce platforms. But in fact, the Internet only entered China in early 2000, and e-commerce has developed so rapidly in just a dozen years. However, looking back at the United States, a country where the Internet was first used and developed, why do U.S. e-commerce platforms not gain such a large market share as China's e-commerce platforms? This paper takes this as a premise, compares the e-commerce brands of Amazon, the most important e-commerce industry in the United States, and Alibaba, the famous e-commerce company in China, to explore the differences between Chinese and American e-commerce, and analyzes the possible reasons for these differences.

Analysis of the key influencing factors of China's cross-border e-commerce ecosystem based on the DEMATEL-ISM method.

Systematically analysing the relative importance and hierarchical relationships among the influencing factors of the cross-border e-commerce ecosystem holds rich theoretical value and practical significance for the development of this ecosystem. A total of 19 influencing factors covering four aspects affecting the cross-border e-commerce ecosystem are identified by means of the relevant literature, web pages, research, and discussions with relevant experts and scholars, and the decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling (ISM) method is used to analyse the cause-effect correlation of each factor and to obtain a cause-effect diagram and a multi-level recursive structure model. The results show that three factors, i.e., the e-commerce platform development level, cross-border e-commerce competitiveness, and the cross-border e-commerce transaction scale, have a greater degree of influence on the other influencing factors. Additionally, three factors, i.e., the information development level, GDP, and cross-border online shopping demand, are vulnerable to the influence of the other factors. The level of cross-border e-commerce platform development, cross-border e-commerce competitiveness, and inter-firm competition are the root factors and occupy an important position in the cross-border e-commerce ecosystem as influencing factors and influence the stability of the cross-border e-commerce ecosystem by affecting the other factors.

Analisis Perkembangan Platform E-commerce Terhadap Minat Transaksi Digital Menggunakan Metode Chi Square

Online-based business and market behavior has become a trend due to the Covid-19 pandemic where some people, especially among students, use e-commerce to meet their needs and lifestyle. The development of science and technology is the main thing in supporting the convenience of the community to carry out online activities. People use smartphones to get the products they need, make transactions and pay online. This study analyzes the relationship between the development of various e-commerce platforms and interest in digital transactions in society, especially among students. The results of data analysis from this study become a reference for e-commerce platforms in developing their services according to market tastes. The research method used for sampling was purposive sampling methods, for data analysis using the Chi Square method from the Statistical Product and Service Solution software (SPSS version 25). From the results of the analysis of the research data, it concludes that there is a significant relationship between the development of e-commerce platforms and people's interest in conducting digital transactions.

Proposal to Improve the E-Commerce Platform Development Process with an Exploratory Case Study in Chile

Electronic commerce (e-commerce) is the buying and selling of goods and/or services over the internet. In recent years, e-commerce has experienced tremendous growth due to the popularity of and access to the internet throughout the world. Many companies have seen an opportunity in this market, starting to offer their products and/or services online. However, developing electronic commerce platforms can be complex and requires technical skills and specialized knowledge, which has become a problem due to the need to comply with the standards and requirements of customers who request to join these channels. Microenterprises in particular often need more resources and experience building e-commerce platforms. This is an exploratory case study, the objective of which is to design a proposal to improve an e-commerce platform development process for a computer enterprise from Valdivia, Chile, based on the international standard ISO 10008. Therefore, a solution is proposed for microenterprises to standardize their processes and improve their competitiveness in an increasingly demanding market, incorporating a methodology based on a review of quality management and customer satisfaction guidelines for e-commerce that allow the identification of internal and external failures, to prevent problems and achieve acceptable results. The proposal includes suggestions on how to improve the user experience on platforms, make the purchase and payment process more efficient, develop a support section for the computer microenterprise, and improve the security and privacy of customer data. The study of this quality regulation is one of the first at the national level, paving the way for developing proposals for other microenterprises in the country and, in turn, for the study and implementation of guidelines for business-to-consumer electronic commerce transactions (B2C ETC).

Fake review detection system for online E-commerce platforms: A supervised general mixed probability approach

Online consumer reviews play an important role in helping consumers judge the quality and authenticity of products on e-commerce platforms. However, the constant presence of fake reviews on these platforms has significantly impacted the operation and development of e-commerce platforms. In this study, we develop a novel supervised probabilistic method to detect fake reviews by utilizing the difference in the distribution of non-fraudulent reviews and that of fake reviews. Specifically, we first derive the univariate distributions of several unique features (linguistic, behavioral, and interrelationship features). We then integrate these distributions into two mixed distributions according to their labels to represent the overall difference between non-fraudulent reviews and fake reviews. Next, we randomly generate synthetic review data points with different labels from the above mixed distributions. Finally, we train a Multilayer Perceptron model by using these synthetic review data to obtain a classifier. We conducted several experiments to test the model using several original real-world review datasets. Numerical results indicated that the proposed supervised method outperformed some well-known sampling models and fake review detection methods, in terms of classification accuracy. Moreover, we extend the proposed method to handle the scenarios with small samples of raw review data. This study contributes to the literature by exploiting the difference in the distribution of non-fraudulent reviews and that of fraudulent reviews, which can improve the accuracy of fake review detection for online platforms.

Research on the Regulation of Algorithmic Price Discrimination Behaviour of E-Commerce Platform Based on Tripartite Evolutionary Game

With the development of the digital economy, the algorithms and big data technologies of e-commerce platforms have gradually turned into double-edged swords. While realising personalised recommendations, they also provide information technology support for the use of algorithmic prices to discriminate and extract residual value from consumers. Consumers frequently use Black Cat and third-party media to complain, resulting in a significant negative impact. Therefore, in order to regulate algorithmic price discrimination, using e-commerce platforms, local governments and consumers act as game subjects, taking an evolutionary game approach. We analyse the impact of different situations and factors on the system’s evolutionary stability strategy and conduct its verification via simulation experiments. This study shows that several measures, such as increasing cooperation with the media; establishing clear regulatory rules to reduce the extent of algorithmic price discrimination and the grey revenue of e-commerce platforms; establishing a long-term mechanism for consumer feedback; improving rewards and punishments to increase the probability of successful regulation and penalties by local governments; sharing information to reduce the cost of consumer regulation; and setting reasonable bonus thresholds based on government revenue and consumer regulation costs, can effectively regulate algorithmic price discrimination and promote the sustainable development of e-commerce platforms.

Response Methods and Optimization Measures for Natural Disasters in The Context of Block Chain and E-commerce Platform Development

In recent years, the frequent occurrence of natural disasters has aroused people's attention all over the country, such as the recent rainstorm in Zhengzhou. We plan to design an emergency management mini program based on blockchain to cope with natural disasters, open up production, transportation and distribution channels of materials, achieve accurate distribution of materials, better meet people's needs, and shorten the period of post-disaster reconstruction.

The Impact of Covid-19 on E-Commerce Platforms and The Opportunities and Challenges They Face

Since the outbreak of Covid-19 in 2019, many countries set policies to deal with Covid-19. Because of these policies, many people were restricted from going out. Hence, E-commerce platforms are the preferred way of shopping for many people during Covid-19. The aim of this paper is to examine the impact of Covid-19 on E-commerce platforms and how they can be improved in response to the epidemic. According to the financial status of several E-commerce platforms, sales and revenue increased during the Covid-19 period compared to the past. Furthermore, essential goods are the items that most people preferred to buy during the epidemic time. Mounika Veeragandham’s research shows that 50% of respondents chose to buy essential goods during the epidemic time, which is the highest compared to other purchases. And more people prefer to shop on E-commerce platforms than on traditional ways. To better respond to Covid-19, many E-commerce platforms have taken some measures such as shared employees and online consultation. Based on the above phenomenon and its analysis, this paper hopes to provide some reference for the development of E-commerce platforms in the epidemic situation.

Identification of Usefulness for Online Reviews Based on Grounded Theory and Multilayer Perceptron Neural Network

In the context of the continuous development of e-commerce platforms and consumer shopping patterns, online reviews of goods are increasing. At the same time, its commercial value is self-evident, and many merchants and consumers manipulate online reviews for profit purposes. Therefore, a method based on Grounded theory and Multi-Layer Perceptron (MLP) neural network is proposed to identify the usefulness of online reviews. Firstly, the Grounded theory is used to collect and analyze the product purchasing experiences of 35 consumers, and the characteristics of the usefulness of online reviews in each stage of purchase decision-making are extracted. Secondly, the MLP neural network classifier is used to identify the usefulness of online reviews. Finally, relevant comments are captured as the subject and compared with the traditional classifier algorithm to verify the effectiveness of the proposed method. The experimental results show that the feature extraction method considering consumers’ purchase decisions can improve the classification effect to a certain extent and provide some guidance and suggestions for enterprises in the practice of operating online stores.

Research on Consumer Trust Mechanism in China’s B2C E-Commerce Platform for Second-Hand Cars

The rapid development of China’s e-commerce industry has led to the rise of China’s second-hand car e-commerce. With the increasingly rich trust theory and the rapid development of e-commerce platforms, the issue of online consumer trust has attracted more and more scholars’ attention. This paper takes China’s B2C second-hand car e-commerce platforms as an example, combines the second-hand car research conclusions and consumer trust theory, and conducts a systematic study on the formation of consumer trust in second-hand car e-commerce platforms. Based on the trust of individual consumers, system environment, website/APP and platform companies, this paper explores the influencing factors of consumer trust and constructs the influencing factors model of trust formation. The empirical study was conducted by using the structural equation model and multiple regression to verify the degree of fitting of the theoretical hypothesis and the model. The research results have a certain reference value for the development of second-hand car e-commerce platforms.

Application of Game Theory Analysis in E-commerce Platform Pricing

The impact of pricing strategy on the profitability of e-commerce platform is studied. First of all, based on the e-commerce platform, considering the interests of the platform, the seller and the buyer in the transaction process, it is of practical and theoretical significance to explore the strategic choice of e-commerce platform pricing from the perspective of game theory. Then, through research, it is found that the operation of the e-commerce platform has distinct life cycle characteristics, that is, the initial use of various subsidy strategies to attract the entry of sellers and buyers, and the medium-term use of asymmetric pricing strategies combined with external response and demand elasticity to ensure the effectiveness of the platform. Finally, when formulating pricing strategies, e-commerce platforms should actively implement the strategy of market-oriented operation, reduce the intervention of sellers and buyers, and ensure the stable development of e-commerce platforms.

АВТОМАТИЗАЦІЯ МАРКЕТИНГОВОЇ ДІЯЛЬНОСТІ ЯК НАСЛІДОК ІНФОРМАТИЗАЦІЇ СУСПІЛЬСТВА

The article is devoted to a modern problem - the development of marketing under the conditions of informatization of the economy. The conducted analysis showed that the automation of marketing activity became possible, including thanks to the large-scale system program for the development of the economy of the new technological generation, the so-called digital economy. The use of automation tools in marketing activities allows you to significantly reduce transaction costs associated with the search, exchange and storage of information, optimize the processes associated with the creation of goods and services, and also allows you to provide constant feedback and the development of individual offers. Іncrease consumer interest in marketing programs and reduce the number of contacts with consumers, which radically improves marketing results, increases profitability. However, the transition to digital rails is not possible without leveling up digital literacy of the population, elimination of the lack of modern technologies and equipment, development of e-commerce platforms, modernization of information security standards at the state level and introduction of monitoring of their implementation. Therefore, the development of the era of automated marketing involves the development of digitalization of the economy in general, and the improvement of marketing tools. Thanks to this, companies can effectively monitor and analyze consumer data, develop more accurate and personalized marketing strategies, increase customer loyalty and increase profitability. However, companies should also be careful not to rely too heavily on automation and maintain a personal touch with their customers. The main disadvantages of marketing automation are cost, marketing automation requires large financial investments, especially for small businesses. The costs of acquiring, installing, configuring, and maintaining this technology can be high. And the risk of errors is also very high: marketing automation can lead to errors. Conclusions are drawn and prospects for further research are defined.

Analysis of The Transformation in Pinduoduo Based on SWOT Model and 4C Marketing Theory

With the rapid development of the Internet in China, the competition in the field of e-commerce is becoming more and more fierce. Under the impact of economic expansion and COVID-19, it is no longer feasible for e-commerce platforms maintain their original competitive strategies. In this context, how to fully grasp the advantages of existing competitive strategies and take advantage of the opportunities brought by the external environment has become an important task for the sustainable development of e-commerce platforms. Under this background, Pinduoduo actively responds to the impact of the epidemic and changes in the economic environment, makes full use of its advantages in the low-end market and unique social marketing strategies, and gradually puts its marketing focus on the investment in agricultural scientific research to adapt to the changes in the e-commerce market and consumer behaviour at the present stage. Guided by the 4C marketing theory, this paper studies consumer habits from the four directions of consumer, cost, convenience and communication. Then the SWOT analysis was applied to study the internal and external environment of Pinduoduo agriculture and community group buying business transformation. The analysis results showed that Pinduoduo has some deficiencies in its transformation. Next, in view of the shortcomings in the transformation, combined with the existing literature and relevant materials, this study put forward optimization suggestions from the four directions of consumer, cost, convenience and communication.

Analysis of Multiple Linear Regression Algorithm for High Quality Development Factors of Cross-Border E-Commerce

With the in-depth development of Internet technology as well as information technology, the continuous popularization of computers in China, and the increasingly obvious economic globalization, the world’s economies are becoming more and more closely connected. Cross-border e-commerce has been developed better. In China, with the deep and continuous development of China’s reform and opening up, as well as the continuous improvement of our country’s science and technology level, the continuous improvement of people’s living standards and the internationalization of our country’s enterprises are getting stronger. E-commerce in China has also been developed significantly. According to the statistics of China’s National Bureau of Statistics and relevant scientific research institutions, since China entered the modernization, China’s cross-border e-commerce are multiplying the high-speed growth state, especially after China’s entry into the WTO, China’s cross-border e-commerce business is growing rapidly, in the process of China’s cross-border e-commerce development, compared with imports, exports are taking the absolute dominant position. Therefore, the quality of goods in China, the implementation of standards and related laws and regulations and policies, then become a relatively core part of cross-border e-commerce. Among all the core parts, the quality of goods is undoubtedly the most core part. Under the supervision of our national departments and law-making and other factors, the regulator of the e-commerce platform is the main body of commodity quality supervision. Therefore, the managers of e-commerce platforms are of vital importance to promote the development of e-commerce platforms. In this paper, in line with the principle of promoting the high-quality development of cross-border e-commerce in the prospect of high-quality development of China’s e-commerce platform, a series of multivariate linear models on the development of e-commerce platform carry out the analysis of China’s high-quality development of e-commerce. The main body of China’s e-commerce, the country, as well as consumers, producers, and other optimization analysis is from the overall analysis of China’s e-commerce platform development status. The current problems of China’s e-commerce platform, according to this to carry out the overall planning, put forward the countermeasure suggestions studied in this paper.

Channel Competition and Coordination of E-Commerce Platforms under Low-Carbon Environment: A Cooperative Game Approach

The objective of “low-carbon supply chain” and the development of e-commerce platforms (as e-platform) has boosted the production and sales of low-carbon products. Although the e-platform’s involvement promotes the efficiency of low-carbon products circulation, it leads to channel competition and double marginalization. To mitigate these negative effects, in the context of low-carbon production, a three-player supply chain that contains a low-carbon manufacturer, an e-platform, and a retailer are investigated. By introducing the Stackelberg game and cooperative game theory, the supply chain is coordinated under a cooperative framework considering the commission rate of e-platforms. Subsequently, Mathematica is used for numerical simulation. The results show that intensified channel competition and excessive commission rates will lead to malicious price cuts by supply chain members, which is not conducive to the low-carbon production of manufacturers. Appropriate cooperation strategies can improve the value and identity of low-carbon products and optimize the supply chain system. For coordination of supply chain, three cooperative game-theoretic mechanisms can coordinate low-carbon dual-channel supply chain of the e-commerce platform (LCDESC) well under different situations. These findings provide managerial insights for managers of LCDESC.

Optimal channel selection of remanufacturing firms with considering asymmetric information in platform economy

With the rapid development of e-commerce platforms, and considering that online return rate is relatively high and third-party stores on e-commerce platforms need to adopt third-party logistics, thus remanufacturing firms face the challenge of deciding whether to enter e-commerce platforms. To address this challenge, our paper considers a remanufacturing firm, an e-commerce platform, and a third-party logistics provider. Moreover, according to whether the remanufacturing firm enters the platform and whether the information is symmetrical, we develop three theoretical models: Model NP (the firm doesn’t enter platform), Model YP (the firm enters platform with symmetric information) and Model YA (the firm enters platform with asymmetric information). Some main insights are obtained. We find that whether remanufacturing firms should enter the platform depends not only on the annual service fee charged by the platform but also on the carbon tax price set by the government. Interestingly, improved consumers’ satisfaction with online remanufactured products is not necessarily conducive to enhancing the willingness of remanufacturing firms to enter e-commerce platforms. Finally, we find that when the production quantity constraint of the remanufactured products is not binding, if the actual production cost of remanufactured products is high and consumers’ satisfaction with offline remanufactured products is relatively low, information disclosure will benefit remanufacturing firms, however, when the production quantity constraint of the remanufactured products is binding, information disclosure has no impact on the remanufacturing firms’ profits and operational decisions.