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• Main Authors: Yu-Jiun Cheng, 鄭聿均
• Other Authors: 王啟泰
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/rq82qe

碩士 === 國立中央大學 === 工業管理研究所在職專班 === 107 === After-sales service is the key factor that influencing consumer’s notebook purchase decisions. According to the annual list of notebook brand ranking by Laptop Mag, after-sales service and warranty accounted for 20% in the evaluation. Most of the notebook brands and manufacturers launched fast repair service to improve after-sales service quality and customer satisfaction. And for the fast repair service requirement, the accuracy of the preparation of spare parts will be the most important key factor. The results of this study is to use Regression Analysis to construct a main reference index. This study analyzed the notebook repair database of a notebook manufacturer as the case study, and select the spare parts suitable for the prediction of this research by demand and feature of the spare parts. And also find the shipment quantity, and repair quantity data to finish the analysis. The results of this study shows that for the notebooks within warranty, the prediction accuracy of Regression Analysis is better than Moving Average Period or Exponential Smoothing. But for the notebooks which already out of warranty, the prediction accuracy of Moving Average Period is better than Regression Analysis and Exponential Smoothing. And the management can rivise the demand for spare parts according to the results of this study.