A Model for E-commerce Market Network with
Improved Evolution Mechanism
Zhihong TIAN1, Zhenji ZHANG1, Xiaolan GUAN2
1 Beijing Jiaotong University, Beijing, 100044, China
2 Beijing Institute of Graphic Communication,
Beijing, 102600, China
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.
Keywords: E-commerce; Market network; Evolution model; Complex network, Scale-free network.
CITE THIS PAPER AS:
Zhihong TIAN, Zhenji ZHANG, Xiaolan GUAN, A Model for E-commerce Market Network with Improved Evolution Mechanism, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (1), pp. 77-86, 2014.
Significant progress has been made in e-commerce applications so far, and e-commerce plays a very important role in national economy. Large numbers of buyers and sellers interact with each other through transactions on websites. These interactions promote the evolution and shape complex structures of e-commerce market. Going deeply insight into research of e-commerce market network has a profound and lasting significance.
Social and business networks are an increasingly important area of research attention in many disciplines [1-3]. However, stable equilibriums and models have been mainly focused on, while their dynamics and evolution have received limited research attention. One of the major challenges is to better understand, predict and control their dynamics, including how they form, evolve and shape their behaviors and performances . Networks of relationships, such as the nature, development and evolution of firms and markets, in all business disciplines have been drawn attention, rather than being attributed only to individual characteristics. In marketing, the research about B2B markets in the US, Europe and Australasia is a pioneer .
The market-as-networks (MAN) perspective is a theoretical framework that aims to describe and understand the functioning of industrial markets. It perceives industrial markets as a network of interdependent relationships between companies that cooperate, compete, compete to cooperate with each other and cooperate in order to compete more effectively . Some particular characteristics of e-commerce market have been studied. Maurer SM, et al.  present a static competition model of web site growth by establishing prey-predator equations. Their research shows that, in the long term, under competitive conditions, an efficient equilibrium structure will somehow emerge and, if conditions change leading to another equilibrium point, the network will move to that equilibrium in the long run. However, there are several troubles in the evolution process of e-commerce market network.
Firstly, we do not know how long the long run is, whether a network will ever get to such an equilibrium point. The evolution process is a black box for us. Secondly, we do not know what the network looks like. Namely, a clear and intuitive description of network structure has not been provided. Thirdly, we do not know how the network changes when its evolutionary rules or parameters change.
The aim of the paper is to propose a complex network analytical framework for e-commerce market networks, and to analyze the forming mechanisms. Then, a new evaluating model with growth-factor, select-order-factor, preferential attachment mechanism and global-local-factor is built. Our research reveals that the attraction mechanism impacts evolutionary trend and network structure to some extent. Contrast to the evolutionary trend of degree preferential attachment mechanism, the evolutionary trend with attraction preferential attachment mechanism reaches a smaller power-law exponent generally. Our research also reveals that the global-local-factor and select-order-factor impact the evolutionary structure of the network, and the smaller the probability is, the smaller the concentration of networks is, and the more obvious the randomness is. 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.
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