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Factorial and discriminant analyses of the underlying factors that predict customer retention in the debt management plan.

In the past decades, the credit counseling industry has experienced steady growth due to the increased needs of consumers who are overwhelmed with debt (Christopher, Timmons and Cady, 2001). The services of credit counseling organizations focus on debt management plans (DMP), and they also provide other services such as financial education, budget counseling, and bankruptcy referrals (Hunt, 2005). Debt management plan is a schedule for repaying all of the borrower's debts over three to five years. Although DMP benefits directly to the debtors, many debtors dropped DMP, and only about 33% of DMP clients completed DMP (Hunt, 2005).

The low customer retention rate in the DMP has attracted increasingly attention from both credit counseling organizations and consumer researchers, since DMP is an important profit source for credit counseling organizations and retention rate in DMP directly influences their profitability and survival. On the other hand, without the help of DMP, consumers tend to involve serious financial problems and finally bankrupt. The purpose of this paper is to address this problem and empirically investigate whether consumers who successfully went through or stayed in the DMP without problems are different from those who have problems (e.g. payment delay or drop the program for personal reasons) to stay in the program, identify the factors that can predict customer retention, and furthermore evaluate the effects of these factors on customer retention in the DMP.

A survey was conducted on the clients of a national credit counseling agency and 210 subjects responded (response rate is 64%). An exploratory factor analysis was carried out first to identify the key factors that influence customer retention in the DMP including attitude toward retention, subjective norms, perceived control, and customer satisfaction. Then these factors along with self-regulation and demographic variables such as gender, education and incomes were applied in the subsequent discriminant analysis conducted to determine which factors discriminate between clients who stay in the program without any problem and those who have some problem (e.g. payment delay) to stay in the program. The result shows that three key factors: attitude, perceived control, and satisfaction successfully discriminate between customers who have problem and those who have no problem to stay in the program. 72.7% original cases were classified correctly. Furthermore, among these factors attitude has the greatest influence, followed by satisfaction and perceived control.

Above study is based on both the consumers who are in the DMP and those who have done with the program, but it seems more meaningful to check those have done with the DMP than to examine the customers who are still in the DMP. A further question is whether those who successfully went through the DMP and pay off all their debt are different from those who failed to go through the DMP and dropped for their personal reasons. However, the sample size for investigating this question is too small (sample size=41) to carry out a multivariate data analysis. Jackknife method (Fenwick, 1979) was used to solve the small-sample problem and provide a valid finding, and then a discriminant analysis was carried out to determine which factors discriminate between those two groups of clients. The findings of the discriminant analysis indicates that attitude, perceived control, satisfaction, and self regulation successfully discriminate between customers who successfully went through the DMP and paid off all their debt and those who failed to go through the DMP and dropped for their personal reasons. Attitude has the greatest influence, followed by satisfaction, perceived control and self regulation. Validation analysis performed shows that a genuine success rate of classification is 66%. The findings from this study will help researchers to better understand consumers' debt reduction behavior and the credit counseling agencies to better manage their customers.

Reference

Christopher H. S., Heather. T. and Cady, J. (2001). A Debt Trap for the Unwary. Business Week. Oct., 29.

Hunt, R. (2005). Whither consumer credit counseling? Business Review, Q4, 9-20.

Fenwick, I. (1979). Techniques in Market Measurement: The Jackknife. Journal of Marketing Research, 16(3): 410-414.

Chuanyi Tang (1) The University of Arizona

Jing Jian Xiao (2) The University of Arizona

Endnotes

(1) Doctoral student, Division of Retailing and Consumer Science, The University of Arizona

(2) TCA Professor and Director, Take Charge America Institute for Consumer Financial Education and Research, The University of Arizona
COPYRIGHT 2007 American Council on Consumer Interests
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Author:Tang, Chuanyi; Xiao, Jing Jian
Publication:Consumer Interests Annual
Geographic Code:1USA
Date:Jan 1, 2007
Words:715
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