• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• International Commerce and Information Review
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• v.9 no.1
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• pp.149-168
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• 2007

e-Trade Payment system has been transformed by quickly and effectively. The e-trade Payment system such as TradeCard System, Bolero Surf, Identrus Eleanor and e-Escrow and e-letter of Credit issued by SWIFT System enable partly sellers, buyers and service providers. This paper studies for SWIFT, Surf, TradeCard, Eleanor, e-Escrow as international trade payment, As reason following : The First, Bolero is a neutral secure platform enabling paperless trading between exporter, importer, and their logistics service and bank partners, insurance company. The Second, TradeCard is to manage procurement-to-payment worldwide, that is exporter, importer and connected partners, paperless platform. The Third, Identrus is the global leader in trusted identity solutions, recognized by global financial institutions, commercial organizations and bank partners around the world. The Forth, Escrow payment have effect to L/C issue and enter into electronic contracts in internet bank. Trader practice use Escrow Bank as the same bank that rules to Issuing Bank and Advising Bank and payment, acceptance. This paper of these electronic payment have studies new international trade payment to approach such as eUCP rules and TradeCard System, Surf of bolero, eleanor of Identrus, SWIFT.

• International Commerce and Information Review
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• v.9 no.2
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• pp.327-350
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• 2007

A single window platform must be successfully established by implementing CDM/UCR in WCO and UNeDocs in UN/CEFACT, which is part of the framework of standards for secure and facilitate global trade. Core success factors in single window platform for international trade depend on political innovative capacity, advanced leadership of high ranking officials and departments in charge, effective collaborations between the ministries and offices concerned which are supported by supreme executives, self-controlled coordinations between users, convenience and access availability to users, promotion and marketing, identification on predictive impediments, financial raising and revenue model payable, communication's strategy, valid legal basis etc. To settle a stable ubiquitous e-trade platform, firstly, procedures and practices of customs clearance which different from one another mutually must be standardized globally. Secondly, the international standard electronic data exchanges must be introduced to facilitate and simplify customs clearing procedures by holding administrative informations in common between public institutions. thirdly, cooperative work model must be accepted with enhancing outsourcing business between reference groups (export-import firms and IT service providers).

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.71-83
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• 2003

Nowadays on-line services based on Internet are being popularized and there are lots of E-Commerce applications using Internet. So we can use lots of information on anytime. To maximize the convenience of the network, the platform of the service is moving from E-Commerce to M-Commerce. In this paper we developed the application system for mobile environment. Therefore applicants can apply their applications and see the competition rate of the applying departments anytime and anywhere even if in the network disconnection regions. And we can manage more economically the application system because we use the network only the time when we syncronize the mobile device to mobile server.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.53-58
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• 2023

The trend of satisfying consumer needs (payment for mobile communication, music services, cab ordering, banking products, and food delivery) on a unified online platform has shaped a digital ecosystem, an instrument creating a unified space of economic interaction. Representatives of e-commerce are major stakeholders in the development of such tools. In particular, subscription services (multiservice subscriptions) allow users to create their own ecosystems based on their personal preferences. The rate of subscription service use is growing around the world, yet understanding of the peculiarities of development of this e-commerce sphere is limited due to insufficient research.The study aims to determine the motives and barriers to the use of subscription services (multiservice subscriptions) by consumers and their relationship with consumer characteristics.Proceeding from an online survey of 200 users, the study determines the relationship between the gender and income of consumers and their use of subscription services, motives and motivators for using subscription services, and barriers to the choice of a particular subscription service. The obtained results may serve as a basis for managerial decisions in e-commerce and for improving the effectiveness of marketing solutions.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.138-154
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• 2021

'Live commerce', a brand new format of online shopping, is actively promoted in China recently. This research focused on 'Taobao-live', China's largest live commerce platform to investigate the relationships among para-social interaction, source characteristics (e.g., trustworthiness, attractiveness, and expertise), perceived ease of use, perceived usefulness, and shopping intention based on Technology Acceptance Model. A total of 536 Taobao live users were recruited through the Chinese research platform. The results showed that para-social interactivity positively affected perceived ease of use and usefulness, whereas the source characteristics had no significant effect on consumers' perceptions. Furthermore, higher perceived ease of use generated higher perceived usefulness, and both perceived ease of use and usefulness positively influenced consumers' intention to shop through Taobao live. This research can provide theoretical background for understanding the potential of live commerce platforms and help brands come up with effective online shopping strategies using live commerce platforms.

• Smart Media Journal
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• v.10 no.4
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• pp.54-62
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• 2021

As the volume of online e-commerce transactions increases, items diversify and the classification becomes complicated. E-commerce platforms that specialize in dealing only in one area are emerging, and the area is diversifying. Three problems were identified by researching the craft online e-commerce platform, one of the various types of professional e-commerce platforms. First of all, although craft materials are diversified and complex on the platform, the existing craft e-commerce system is fragmented in structure to categorize complex crafts, making it difficult to accurately present search results that meet various criteria. Second, although appearance is the main reason for purchasing artifacts, it is rare for users to categorize them according to appearance, so they have to judge and filter each work directly. Finally, the language entered when searching for artifacts by non-technical experts is not reflected in the language used to categorize artifacts in the taxonomic system, so the language used for searching is highly accurate. Therefore, the purpose of this study is to add and consider complex attributes in the field of technology to meet the search criteria. Properties to be added must include the main appearance in the search for artifacts. In addition, the government aims to develop a taxonomic system that can reflect non-experts' search languages in the search of works through artificial intelligence natural language processing technology.

• Journal of Arbitration Studies
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• v.23 no.1
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• pp.107-131
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• 2013

Online-ADR (Alternative Dispute Resolution) has been receiving attention from the international community as a means of alternative dispute resolution for consumer disputes in both small and mass international e-commerce. The EU Parliament and the Council proposed the Online Dispute Resolution Regulation for Consumer Disputes (hereafter, "EU Consumer ODR Regulation") and the Directive on Alternative Dispute Resolution of Consumer Disputes (hereafter, "EU Consumer ADR Directive") as a legislative package, now scheduled to be adopted. Those efforts strengthen consumer protection by enhancing ODR in international e-commerce and improving of the functions of the e-commerce market. The EU Consumer ADR and ODR regulation package will operate in conjunction with the ODR platform as a single point across Europe, abandoning the ADR system of each member. Consumers and traders who need dispute resolution apply on the EU ODR platform linked website, and the applications are distributed to individual ADR institutions in accordance with the Rules and Procedure of ADR institutions in the respective country. Although there has been partial progress in Korea for ODR programs such as the establishment of the Online Administrative Trial and the procedures of individual ADR agencies operating through the website, existing norms do not fully support the system. At this point, we see many implications of the EU Consumer ADR and ODR regulation package on the direction chosen for domestic ADR and ODR policy and legislation. This study introduces the main features and content of the EU Consumer ADR Directive (draft) and ODR Regulation provisions, and describes the direction of domestic policy and legislation regarding Online-ADR.

• The Journal of Bigdata
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• v.8 no.2
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• pp.201-222
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• 2023

As the e-Commerce gets increased based on the platform, a lot of small and medium sized sellers have tried to develop the more effective strategies to maximize the profit. In order to increase the profitability, it is quite important to make the strategic decisions based on the range of promotion, discount rate and categories of products. This research aims to develop the business intelligence application which can help sellers of e-Commerce platform make better decisions. To decide whether or not to promote, it is needed to predict the level of increase in sales after promotion. I n this research, we have applied the various machine learning algorithm such as MLP(Multi Layer Perceptron), Gradient Boosting Regression, Random Forest, and Linear Regression. Because of the complexity of data structure and distinctive characteristics of product categories, Random Forest and MLP showed the best performance. It seems possible to apply the proposed approach in this research in support the small and medium sized sellers to react on the market changes and to make the reasonable decisions based on the data, not their own experience.

• ETRI Journal
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• v.46 no.4
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• pp.633-647
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• 2024

In e-commerce platforms, sentiment analysis on an enormous number of user reviews efficiently enhances user satisfaction. In this article, an automated product recommendation system is developed based on machine and deep-learning models. In the initial step, the text data are acquired from the Amazon Product Reviews dataset, which includes 60 000 customer reviews with 14 806 neutral reviews, 19 567 negative reviews, and 25 627 positive reviews. Further, the text data denoising is carried out using techniques such as stop word removal, stemming, segregation, lemmatization, and tokenization. Removing stop-words (duplicate and inconsistent text) and other denoising techniques improves the classification performance and decreases the training time of the model. Next, vectorization is accomplished utilizing the term frequency-inverse document frequency technique, which converts denoised text to numerical vectors for faster code execution. The obtained feature vectors are given to the modified convolutional neural network model for sentiment analysis on e-commerce platforms. The empirical result shows that the proposed model obtained a mean accuracy of 97.40% on the APR dataset.