Customer Churn in telecommunication: An application of Multivariable Adaptive Regression Splines

سال انتشار: 1400
محل انتشار: دومین کنفرانس بین المللی چالش ها و راهکارهای نوین در مهندسی صنایع و مدیریت و حسابداری
کد COI اختصاصی: CSIEM02_360
زبان مقاله: انگلیسی
تعداد مشاهده: 262

نویسندگان

Department of Industrial Engineering, Alzahra Universtiy, Tehran, Iran

چکیده

The profit resulting from customer relationship is essential to ensure companies viability, so an improvement in customer retention is crucial for competitiveness. As such, companies have recognized the importance of customer centered strategies and consequently customer relationship management (CRM) is often at the core of their strategic plans. In this context, customer churn is an important subject. A churn consumer can be defined as a customer who transfers from one service provider to another service provider. Recently, business operators have investigated many techniques that identify the customer churn since churn rates leads to serious business loss. This article investigates the use of Multivariable Adaptive Regression Splines (MARS) together with logistic regression in the context of modeling customer churn prediction. Specifically, our goal is to assess the relative effectiveness of MARS model vis-a-vis logistic regression with original predictor variables in modeling customer churn. Based on our results, the values of specificity and sensitivity for logistic regression are ۸۵% and ۹۰% while these amounts for MARS are ۹۰% and ۹۵% respectively. By considering these values one can conclude that MARS outperforms the logistic regression model.

کلیدواژه ها

Customer relationship management, Customer churn, Logistic Regression, Multivariable Adaptive Regression Splines

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