The ICIR of Beijing Jiaotong University

Achievements

1.A Model for E-commerce Market Network with Improved Evolution Mechanism
Abstract:In order to investigate the formation of e-commerce market network, this paper describes an analytical framework from a complex network point of view which contains three steps—definition of network, analysis of network topology and analysis of network environment. Then, an innovative model for explaining the evolutionary process is proposed, with several original factors—growth-factor, select-order-factor, preferential attachment mechanism and global-local-factor. Our research reveals that the attraction mechanism impacts evolutionary trend and network structure to some extent, and also reveals that the global-local-factor and select-order-factor impact the evolutionary structure of the network, the smaller the probability, the smaller the concentration of networks and the more obvious the randomness are. In order to analyze the impact of edge-increasing mechanism on network evolutionary trend, a contrast test is designed with two models. The test reveals that the edge-increasing mechanism makes the network become a small world with a lower average distance and a higher clustering coefficient, and makes it be like a scale-free network with a lower power-law exponent and a higher centralization.
Studies in Informatics and Control, ISSN 1220-1766, 2014, vol. 23 (1), pp. 77-86.(SCI Index)
2.A Study of Short-term Effect Measurement for Information Publication in Government Microblog
Abstract:From the microcosmic point of view, based on AISAS model, aiming at real cased and data of government microblog information publication, this article makes a quantitative empirical research using correlation analysis and regression analysis and construct a quantitative model to measure the short-term effect of government microblog information publication. The measurement model lay a theoretical basis for improving effect of government microblog information.
International Journal of Hybrid Information Technology, 2014, 7(1), pp.57-66. (EI Index)
3.A New Structural Analysis Model for E-commerce Ecosystem Network
Abstract:The paper establishes a new theoretical and methodological analysis model based on ecosystem theory and network science for researching on e-commerce market structure. The model considers three steps to answer the questions for explaining the structure—element identification, relationship analysis and formation mechanism analysis. Then, several suggestive applications based on the analysis model are shown. The systematic analysis framework provided by the model will lead to further research that will reveal the hidden mechanism of Web economic and Internet social system.
International Journal of Hybrid Information Technology, 2014, 7(1): 43-56. (EI Index)
4.A New Evolution Model for B2C Ecommerce Market
Abstract: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.
Information Technology and Management, 2013, 14(3): 205-215. (SSCI Index)
5.Modelling the Emergence and Evolution of e-Business Ecosystems from a Network Perspective
Abstract:In recent years, we notice that the cooperation and competition among enterprises become much more complicated. Managers have to pay more attention to external cooperation from an ecological view. As e-business adoption becomes more pervasive, business ecosystems are shifting to e-business ecosystems. Because the situation is becoming more serious, in order to control the e-business ecosystem and earn profit from it, it is necessary for us to learn its structure and evolution. From the perspective of network science, this paper tries to connect complex network theories with e-business ecosystem research. We firstly analyse network structure of e-business ecosystem. Then an evolutionary model is proposed to describe the emergence and evolution of it. We finally use simulation and empirical methods to valid the theory we proposed.
Studies in Informatics and Control, 2013, 22(4). (SCI Index)
6.Operation Mechanism of the Driving Force System of Ecosystem of Cyber-society Based on the System Dynamics
Abstract:Operation of the driving force system of Ecosystem of Cyber-society needs a scientific mechanism of intervention and regulation to solve the integration problem of a variety of organizations and forces within the Ecosystem of Cyber-society, shorten the process from uncoordination to coordination, promote the orderly operation of the driving force system of Ecosystem of Cyber-society, make the system play a strong force, in order to promote the formation and rapid development of Ecosystem of Cyber-society. We analyze the driving force system of Ecosystem of Cyber-society using the theory of System Dynamics and propose a theoretical framework, and then present its operation mechanism systematically.
International Journal of Computers, Communications & Control, 2013, 6(6): 812-824. (SCI Index)
7.A New Evolution Mechanism Model for B2B E-Commerce Network
Abstract:In order to study the structure and evolution mechanism of B2B e-commerce network, we propose a network with several layers description of B2B e-commerce market. The empirical analysis from Alibaba.com shows that degree distribution of the network structure follows power-law. Based on modified BA (Barabasi-Albert) model, a new model is proposed with adding layers, fitness parameters and more reasonable growth mechanism. The model reveals that, the structure of the network is stable, and the average path length and clustering coefficient are small. We also find that the impact of parameters is not decisive, and the emergence of scale-free nature depends on the mechanism itself.
Journal of Electronic Commerce in Organizations, 2013, 11(2): 12-22. (EI Index)
8.Research on the Mechanism and Optimization of Knowledge –sharing Network of Research Teams based on Social Network Analysis
Abstract:We study the knowledge-sharing network of research teams by using the social network analysis methods, under the conceptual framework of social network theory. We analyze the mechanisms which influence the effect of knowledge sharing from the aspect of the network structure, and apply the mechanisms to propose the suggestion of network optimization, with a specific case of a research team.
Advances in Information Sciences and Service Sciences, 2011, 3(6). (EI Index)
9.Study on the Knowledge-sharing Network of Innovation Teams Using Social Network Analysis.
Abstract:Under the conceptual framework of social network theory, we research the knowledge-sharing network of innovation teams by using the social network analysis methods. This paper puts particular emphasis on how does the structure of knowledge-sharing network impact on the knowledge flows at the overall level. We expect to find the key man and small groups in knowledge-sharing activities. Comparing with the actual organizational structure, we could improve the efficiency of knowledge flows within the organization.
ICEIS 2011 - 13th International Conference on Enterprise Information Systems, 2011, 6(2): 438-443. (EI Index)