Abstract
Article history: Received October 23,2013 Received in revised format November 25, 2013 Accepted November 27, 2013 Available online November 27 2013 An innovative price plan monitoring and advisory system simulates subscriber usage consumption for offering suitable price plan. The aim of this paper is to develop the decision support system by using Statistical Process Control (SPC) to identify subscriber usage behavior and provide critical visibility into subscriber consumption to detect their inappropriate usage especially in exceeding usage. To explore subscriber usage behavior, a forecasting model and a regression is employed to identify related factors and predictive usage model. The innovative price plan monitoring and advisory system has been verified and validated with one of the largest telecommunication company in Thailand. Using decision support system with effective control chart and real subscriber behavior pattern help mobile network operator grow their revenues and profits by offering an appropriate price plan as well as improve subscriber experience with more flexible choice to meet their individual usage consumption needs. © 2014 Growing Science Ltd. All rights reserved.
Highlights
Subscriber churn is a fundamental driver of performance for mobile network operators
The aim of this paper is to develop the decision support system by using Statistical Process Control (SPC) to identify subscriber usage behavior and provide critical visibility into subscriber consumption to detect their inappropriate usage especially in exceeding usage
Evaluation of Innovative price plan monitoring and advisory system acceptance and adoption confirmed that Innovative price plan monitoring and advisory system has positively impact on their work performance and effectiveness
Summary
Subscriber churn is a fundamental driver of performance for mobile network operators. Understanding of subscribers and the ability to predict their behavior through continuous usage monitoring are vital to improve subscriber retention and performance. With increasing variety of services and evolving consumer behavior this paper aims to develop a decision support system to provide a more precise usage prediction with multiple regressions while control chart is adopted to identify usage pattern and provide warning signal for excessive usage. Such tool enables timely and proactive action for subscribers to avoid unexpected expenses. Mobile network operators can utilize these concepts to increase service usage, improve customer satisfaction and reduce churn
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