Abstract
A novel method is proposed in this paper to find the promotive relationship of products from a network point of view. Firstly, a product network is built based on the dataset of handsets’ sale information collected from all outlets of a telecom operator of one province of China, with a period from Jan. 2006 to Jul. 2008. Then the edge enhanced model is applied on product network to divide all the products into several groups, according to which each outlet is assigned to class A or class B for a certain handset. Class A is defined as the outlet which sell the certain handset and contains all of handsets of its group, while other situation for class B which sell the certain handset too. It’s shown from the result of analysis on these two kinds of outlets that many handsets are sold better in outlets of class A than that of class B, even though the sales revenue of all these outlets in the time period is close. That is to say the handsets within a group would promote the sale for each other. Furthermore, a method proposed in this paper gives a way to find out the important attributes of the handsets which lead them to br divided into the same group, and it also explains how to add a new handset to an existing group and where would the new handset be sold best.
This work is supported by the National Natural Science Foundation of China under Grant 60402011 and National Eleven Five-Year Scientific and Technical Support Program under Grant 2006BAH03B05.
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References
Bass, F.M.: A new product growth model for consumer durables. Management Science 15(5), 215–227 (1969)
Hidalgo, C.A., Klinger, B., Barabási, A.-L., et al.: The Product Space Conditions the Development of Nations. Science 317, 482–487 (2007)
Borgs, C., Chayes, J., Mahdian, M., Saberi, A.: Exploring the community structure of newsgroups. In: Proc. 10th ACM SIGKDD Intl. Conf. Knowledge Discovery and Data Mining (2004)
Newman, M.: Detecting community structure in networks. The European Physical Journal B 38, 321–330 (2004)
Jianmei, L.M.Y., Weiliang, T.: Research on features of product competition network based on complex network. Electronic measurement technology 30 (2007)
Radicchi, F., Castellano, C., Cecconi, F., et al.: Defining and identifying communities in networks. Proc. Natl. Acad. Sci. 101(9), 2658–2663 (2004)
Du, N., Wu, B., Pei, X., Wang, B., Xu, L.: Community Detection in Large-Scale Social Network. In: KDD workshop (2007)
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking:Bringing order to the web. Technical report, Stanford University, Stanford, CA (1998)
Barabási, A.L., Albert, R.: Emergence of Scaling in Random Networks. Science 286(5439), 509–512 (1999)
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Huang, Y., Tan, J., Wu, B. (2009). Finding Sales Promotion and Making Decision for New Product Based on Group Analysis of Edge-Enhanced Product Networks. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_44
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DOI: https://doi.org/10.1007/978-3-642-02469-6_44
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