Volume 9 Number 5 (May 2014)
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JSW 2014 Vol.9(5): 1275-1280 ISSN: 1796-217X
doi: 10.4304/jsw.9.5.1275-1280

A Method for Determining the Importance of Customer Demand Based on Rough Set and DEA

Xiuli Sang1, Song Gao1, Jianxin Xu1, Hua Wang2
1Quality Development Institute, Kunming University of Science and Technology, Kunming, P. R. China
2Engineering Research Center of Metallurgical Energy Conservation and Emission Reduction Ministry of Education, Kunming University of Science and Technology, Kunming, P.R. China


Abstract—Affected by customers’ lack of experiences and personal preferences, the importance of customer demand as 0 by only using Rough Set method frequently occurs. Existing methods could not determine this importance of indicators, so it is usually deleted. A new method combining Rough Set and Data Envelopment Analysis (DEA) to determine importance of customer demand in Quality Function Deployment (QFD) is proposed. Based on Rough Set theory, we modify the importance as 0 to determine the fundamental importance of customer demand by combining customers’ preferences and experts’ experiences. Let customer demand be decision-making unit, competitive differences and other factors the input and output indicators, which give full play to DEA’s advantages of avoiding subjective factors and reducing errors to obtain relative efficiency of pure technical indicators. Final importance of customer demand is confirmed by combing fundamental importance with relative efficiency in QFD. Lastly, an application example is to illustrate the effectiveness of this method.

Index Terms—quality function deployment, rough set, data envelopment analysis, importance

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Cite: Xiuli Sang, Song Gao, Jianxin Xu, Hua Wang, "A Method for Determining the Importance of Customer Demand Based on Rough Set and DEA," Journal of Software vol. 9, no. 5, pp. 1275-1280, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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