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A Neuro-Fuzzy Partner Selection System for Business Social Networks
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Author(s): T. T. Wong (The Hong Kong Polytechnic University, Hong Kong)and Loretta K.W. Sze (The Hong Kong Polytechnic University, Hong Kong)
Copyright: 2012
Pages: 21
Source title:
Handbook of Research on Business Social Networking: Organizational, Managerial, and Technological Dimensions
Source Author(s)/Editor(s): Maria Manuela Cruz-Cunha (Polytechnic Institute of Cavado and Ave, Portugal), Patricia Gonçalves (School of Technology at the Polytechnic Institute of Cavado and Ave, Portugal), Nuno Lopes (Polytechnic Institute of Cávado and Ave, Portugal), Eva Maria Miranda (Polytechnic Institute of Cávado and Ave, Portugal)and Goran D. Putnik (University of Minho, Portugal)
DOI: 10.4018/978-1-61350-168-9.ch006
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Abstract
Enterprises are now facing growing global competition and the continual success in the marketplace depends very much on how efficient and effective companies are able to respond to customer demands. Business social network sites (BSNS) have provided a powerful tool to link up manufacturers, suppliers, distributors, and customers. Among the emerging business social networks, decision support functionality addressing the issue of selecting business partners is an important domain to be studied, and it is the objective of this chapter to propose a practical partner selection decision support system. Essentially, a neural-network data mining system is used to generate information for subsequent fuzzy multi-objective analysis. It demonstrates the benefits of integrating information technology, artificial intelligence, and multi-objective decision making to form a practical aid that capitalizes on the merits of BSNS. A special feature is that the trust among companies can be incorporated as an evaluation criterion.
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