Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications

Meier, Andreas; Donze, Laurent

ISBN 10: 1466600950 / ISBN 13: 9781466600959

Published by Business Science Reference, 2011

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnInformation overload has made it increasingly difficult to analyze large amounts of data and generate appropriate management decisions. Furthermore, data is often imprecise and will include both quantitative and qualitative elemen.

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Bibliographic Details

• Title: Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications
• Publisher: Business Science Reference
• Publication Date: 2011
• Language: English
• ISBN 10: 1466600950
• ISBN 13: 9781466600959
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Information overload has made it increasingly difficult to analyze large amounts of data and generate appropriate management decisions. Furthermore, data is often imprecise and will include both quantitative and qualitative elements. For these reasons, it is important to extend traditional decision making processes by adding intuitive reasoning, human subjectivity, and imprecision. Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies. This book covers a variety of possible fuzzy logic approaches to customer relationship management and marketing, making it a valuable resource for not only students and researchers but also executives, managers, marketing experts, and project leaders who are interested in applying fuzzy classification to managerial decisions.

About the Author

Andreas Meier is professor at the University of Fribourg (Switzerland) and head of the research center for Fuzzy Marketing Methods. His research interests include electronic business and government, information management, and data mining. He is a member of GI Europe, IEEE, and ACM. After studies at the Music Academy of Vienna he received a diploma in mathematics and a PhD in computer science from the Swiss Federal Institute of Technology (ETH) in Zurich. He was a system engineer at IBM, a researcher at the IBM research lab in California USA, a director at the international bank UBS, and a member of the executive board of the CSS insurance company before he joined the University of Fribourg.

Laurent Donzé is professor of statistics at the University of Fribourg (Switzerland). After his PhD in econometrics at the University of Fribourg, he worked several years as research fellow on different projects in the field of applied statistics and econometrics. During this time, he completed his formation by studies in mathematics. In 1996, he was engaged as research fellow at the Swiss Federal Institute of Technology in Zurich (KOF ETH Zurich) and since 2002, he is teaching statistics and applied econometrics at the University of Fribourg. His main research interests are in survey statistics, in measuring economic inequality and the impact of economic policy programs.