Submission Deadline: 31 October 2020 (closed)
Prof. Dr. Jung Yoon Kim, Gachon University, South Korea
Prof. Yuyu Yin, Hangzhou Dianzi University, China
In recent years, there is an increasing interest in new business models and strategies from both practitioners and researchers. The significant market transformation has been accomplished by leading E-commerce vendors such as Alibaba and Amazon through their innovative and highly scalable E-Commerce eco-systems. In the context of E-Commerce eco-system, there are hundreds of millions of consumers, thousands of businesses and shops, and hundreds of delivery people. Alibaba Group, as one of the main E-Commerce providers, cooperates with tens of thousands of software vendors to provide all necessary software services to support the business. With the booming of eco-business, more ecological roles in E-Commerce businesses emerge. For instance, Alibaba Group has expanded its business scale from Taobao Software to several business units, with 10000 plus technical staff. Large E-Commerce businesses such as Alibaba Group need to support a large number of applications and business modules, and cater for hundreds of business requirements and independent changes on a daily basis. Another new commercial mode, the sharing economy, such as Airbnb, Instacart, and Uber, has already operated on the basis of E-commerce eco-systems and information technologies. The intersection of these information technologies and business models provides ample research opportunities in intelligent processing of data, information and knowledge.
• Knowledge management for E-commerce;
• Date management for E-commerce;
• Literature review on emerging issues of new business models and strategies;
• New information technology for E-commerce, AI technology, Blockchain, Edge computing, service computing, etc;
• Business process management for E-commerce;
• Big data management and application in E-commerce;
• Demand analysis in E-commerce companies;
• Implementation risk and benefit of adopting digital technologies in E-commerce;
• Innovative mode in E-commerce;
• Consumer information sharing in E-commerce;
• The use of internet platform in E-commerce;
• Empirical studies of business practices and performance.
- OPEN ACCESS ARTICLE
- A User-Transformer Relation Identification Method Based on QPSO and Kernel Fuzzy Clustering
- CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1293-1313, 2021, DOI:10.32604/cmes.2021.012562
- （This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
- Abstract User-transformer relations are significant to electric power marketing, power supply safety, and line loss calculations. To get accurate user-transformer relations, this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization (QPSO) and Fuzzy C-Means Clustering. The main idea is: as energy meters at different transformer areas exhibit different zero-crossing shift features, we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations. The proposed method contributes in three main ways. First, based on the fuzzy C-means clustering algorithm (FCM),… More
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- OPEN ACCESS ARTICLE
- A Novel Collaborative Filtering Algorithm and Its Application for Recommendations in E-Commerce
- CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1275-1291, 2021, DOI:10.32604/cmes.2021.012112
- （This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
- Abstract With the rapid development of the Internet, the amount of data recorded on the Internet has increased dramatically. It is becoming more and more urgent to effectively obtain the specific information we need from the vast ocean of data. In this study, we propose a novel collaborative filtering algorithm for generating recommendations in e-commerce. This study has two main innovations. First, we propose a mechanism that embeds temporal behavior information to find a neighbor set in which each neighbor has a very significant impact on the current user or item. Second, we propose a novel collaborative filtering algorithm by injecting… More
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Downloads:148
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- OPEN ACCESS ARTICLE
- E-Commerce Supply Chain Process Optimization Based on Whole-Process Sharing of Internet of Things Identification Technology
- CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 843-854, 2021, DOI:10.32604/cmes.2021.014265
- （This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
- Abstract With in-depth development of the Internet of Things (IoT) in various industries, the informatization process of various industries has also entered the fast lane. This article aims to solve the supply chain process problem in e-commerce, focusing on the specific application of Internet of Things technology in e-commerce. Warehousing logistics is an important link in today’s e-commerce transactions. This article proposes a distributed analysis method for RFID-based e-commerce warehousing process optimization and an e-commerce supply chain management process based on Internet of Things technology. This article first introduces the advantages and disadvantages of shared IoT identification technology and the IoT… More
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Downloads:305
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