Harnessing the decision tree technique to the customer churn analysis for automobile repairs

• Main Authors: LIU,YUN-SHOU, 劉允守
• Other Authors: Huang, Zheng-Kui
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/m7ar85

碩士 === 國立中正大學 === 企業管理學系碩士在職專班 === 106 === The work of Taiwan’s automotive after-sales service is belonging to a technical service-oriented industry; this is a high-labor-intensive industry as well. Due to the industry’s uniqueness, the degree of automation is quite low. In this study, our research subject is the service maintenance of authorized operations for the domestic brand automobile manufacturers. Since the number of new cars for Taiwan’s new car sales is declining year by year, the industry of aftermarket service is more difficult to be operated so that the sales price of new cars is fiercely competitive. As such, the revenue and profit generated by the after-sales service for the company are declined; the operation management is obviously turning into more important. We need to pay attention to the retention and churn of customers, which are particularly important for the business operations. How to maintain the customer’s turnover rate is one of the most important management issues. The technical level of maintenance personnel and the consumption of customers experience in the maintenance of after-sales service has the inseparable relationship. In addition, we also are able to find out the potential factors of the churn of service personnel and customer experience through the maintenance history records. According to the argument above, this study employs the C5.0 decision tree in data mining to find relevant factors and build models through building decision trees to address the issue − reducing customer churn.