Earticle

초록

영어

RFM model is an important method in customer clustering. Some past studies have proposed fuzzy RFMs model to overcome the shortcomings of traditional RFM models. However, there are some problems unsolved in these approaches. To deal with these problems and to enhance the flexibility in customer clustering, the traditional fuzzy c-means (FCM) method is fuzzified to deal with R, F, and M scores that are expressed in fuzzy values. A fuzzified RFM model is then established by incorporating the fuzzified FCM approach, which is based on the inherent structure of the data itself. The number of customer clusters can be arbitrarily specified in advance, considering the scarcity of marketing resources and the diversification of marketing strategies. Besides, exploring the content of each customer cluster provides the business with many meaningful suggestions that could be usefully employed to establish target marketing programs. An example is adopted to demonstrate the application of the proposed methodology and to make some comparisons.

목차

Abstract
 1. Introduction
 2. Methodology
 3. A Demonstrative Example
 4. Conclusions
 Acknowledgements
 References

키워드

저자

• Toly Chen [ Department of Industrial Engineering and Systems Management ]
• Yu-Cheng Wang [ Department of Industrial Engineering and Systems Management ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605