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A Decision Support Approach for Quality Management based on Artificial Intelligence Applications

Authors:
Nafissa Yussupova
Maxim Boyko
Diana Bogdanova
Andreas Hilbert

Keywords: quality management; decision support system; sentiment analysis

Abstract:
This paper describes the application of a novel domain-independent decision support approach for product quality management. It is based on customer satisfaction research through deep analysis of consumer reviews posted on the Internet in natural language. Artificial Intelligence (AI) techniques, such as Text Mining and Data Mining, are used for realization of consumer reviews analysis. In paper, specific Internet resources (such as yelp.com, tripadvisor.com, tophotels.ru) are used for accumulating customer reviews as a data source is considered. This is performed in accordance with the quality standard ISO 10004 proposed decision support approach, which allows for both qualitative and quantitative customer satisfaction surveys to be carried out. The output of the quantitative survey are values of customer satisfaction by product and each product’s aspect. The output of the qualitative survey are significance values of products aspect for customers and identified latent relations between satisfaction by product and satisfaction by products’ aspects. The proposed approach is performed as a prototype of a Decision Support System. To evaluate the efficacy of the proposed approach, an experiment on hotel’s customer satisfaction has been carried out. The obtained results prove the efficacy of the proposed decision support approach for quality management and the concept of using it instead of classical methods of qualitative and quantitative research of customer satisfaction.

Pages: 112 to 121

Copyright: Copyright (c) IARIA, 2014

Publication date: August 24, 2014

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-358-2

Location: Rome, Italy

Dates: from August 24, 2014 to August 28, 2013