{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T11:19:04Z","timestamp":1742383144216},"reference-count":26,"publisher":"World Scientific Pub Co Pte Ltd","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Info. Tech. Dec. Mak."],"published-print":{"date-parts":[[2004,12]]},"abstract":"<jats:p> Behavior analysis of credit cardholders is one of the main research topics in credit card portfolio management. Usually, the cardholder's behavior, especially bankruptcy, is measured by a score of aggregate attributes that describe cardholder's spending history. In real-life practice, statistics and neural networks are the major players to calculate such a score system for prediction. Recently, various multiple linear programming-based classification methods have been promoted for analyzing credit cardholders' behaviors. As a continuation of this research direction, this paper proposes a heuristic classification method by using the fuzzy linear programming (FLP) to discover the bankruptcy patterns of credit cardholders. Instead of identifying a compromise solution for the separation of credit cardholder behaviors, this approach classifies the credit cardholder behaviors by seeking a fuzzy (satisfying) solution obtained from a fuzzy linear program. In this paper, a real-life credit database from a major US bank is used for empirical study which is compared with the results of known multiple linear programming approaches. <\/jats:p>","DOI":"10.1142\/s021962200400129x","type":"journal-article","created":{"date-parts":[[2004,12,3]],"date-time":"2004-12-03T11:55:19Z","timestamp":1102074919000},"page":"633-650","source":"Crossref","is-referenced-by-count":52,"title":["CLASSIFICATIONS OF CREDIT CARDHOLDER BEHAVIOR BY USING FUZZY LINEAR PROGRAMMING"],"prefix":"10.1142","volume":"03","author":[{"given":"JING","family":"HE","sequence":"first","affiliation":[{"name":"Institute of Systems Science, Academy of Mathematics and Systems Science, The Chinese Academy of Sciences, Beijing 100080, China"}]},{"given":"XIANTAO","family":"LIU","sequence":"additional","affiliation":[{"name":"School of Business Administration, Southwest Petroleum Institute, Chengdu, Sichuan 610500, China"}]},{"given":"YONG","family":"SHI","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA"}]},{"given":"WEIXUAN","family":"XU","sequence":"additional","affiliation":[{"name":"Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100080, China"}]},{"given":"NIAN","family":"YAN","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf2","volume-title":"Management Models and Industrial Applications of Linear Programming","volume":"1","author":"Charnes A.","year":"1961"},{"key":"rf3","volume-title":"Practical Nonparametric Statistics","author":"Conover W. 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