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Issue 10, Volume 4, October 2007
ISSN: 1109-9526
E-ISSN: 2224-2899







Title of the Paper:  Improving Customer Satisfaction by the Expert System Using Artificial Neural Networks


Authors: Feng Qian and Linwen Xu

Abstract: CRM, which aims to enhance the effectiveness and performance of the businesses by improving the customer satisfaction and loyalty, has now become a leading business strategy in highly competitive business environment. The objective of this research is to improve customer satisfaction on product’s colors with the aid of the expert system developed by the authors by using artificial neural networks. The expert system’s role is to capture the knowledge of the experts and the data from the customer requirements, and then, process the collected data and form the appropriate rules for choosing product’s colors. In order to identify the hidden pattern of the customer’s needs, the artificial neural networks technique has been applied to classify the colors based upon a list of selected information. Moreover, the expert system has the capability to make decisions in ranking the scores of the colors presented in the selection. In addition, the expert system has been validated with a variety of customer types.

Keywords: Expert system; Artificial neural networks; Customer relationship management; Back propagation; Customer satisfaction; Decision support

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Title of the Paper: The Impact of ICT on the Development of Latvia as a New Member of the EU


Authors: J. Ulmanis and A. Kolyshkin

Abstract: The data from the Global Information Technology Reports (2004 – 2005 and 2006 – 2007), the International Benchmarking Study 2004 and similar report from Latvia are used in the present paper to analyze the factors that influence ICT adoption and usage. Relative strengths and weaknesses of Latvia with respect to the use and adoption of information and communication technologies are identified through detailed comparison with two EU countries – Ireland and Estonia.. Methods of analysis include regression analysis and hypotheses testing. 

Keywords: linear regression model, information and communication technology, hypothesis testing

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