On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Communications of the ACM
What makes a Web site popular?
Communications of the ACM - Information cities
Group Buying on the Web: A Comparison of Price-Discovery Mechanisms
Management Science
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Classifying the segmentation of customer value via RFM model and RS theory
Expert Systems with Applications: An International Journal
Power-Law Distributions in Empirical Data
SIAM Review
Selecting a small number of products for effective user profiling in collaborative filtering
Expert Systems with Applications: An International Journal
Enterprise Information Systems
Repurchase intention in B2C e-commerce-A relationship quality perspective
Information and Management
Group Buying: A New Mechanism for Selling Through Social Interactions
Management Science
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In order to explain the formation of the business to customer e-commerce market structure, we introduce two concepts--market trading volume and user penetration into the analytical framework for e-commerce market. Based on the modification of Barabasi---Albert (BA) model, a new model which is added with fitness parameters and more reasonable growth mechanism is proposed. The model reveals a "bubble-stable" evolutionary process which is correspondent with real e-commerce market from an initial network to a scale-free one. The simulation results show that the number of websites a buyer chooses could affect the evolutionary process of user penetration distribution, but almost not affect the stable trend of the market. In addition, the initial network scale almost does not affect the nature of network, but causes market fluctuation. The model also reveals that unfair competition among websites is the reason for the formation of structure. Hence, a new method which is calculating numbers of overlap users between each pair of websites is developed to measure the competitive strength. Then, three distinct components are found in the competitive network: a small nucleus, a secondary core and a huge bulk body.