| 摘要(英) |
Recently, the dramatic raise of the oil price and economic recession result in the downturn of the automobile market. Under the situation of earning a little profit, those automobile manufacturers shift their target to the after-sales markets, which still have big demand. With the effort made at after-sales side makes the sales volume stable and brings the considerable turnover to the manufacturers. However, manufacturers often find that there are conflicts existing between strategies when planning the service activities.
This research analyzes the customers’ maintained data. Aiming at the known factors that effect the consumers’’ maintenance preference, we attempt to discriminate the importance and effect level of these factors in order to provide the management reference information for planning the service activities in the future.
We define four evaluation indices by using K-mean clustering to group the 4 known factors and industry standard. Further, we divide the maintenance data into six groups according to the car series and analyze with one of decision tree technique CART. The significant factors are determined and their importance and effects are discriminated.
The result of research shows: (1) The importance level of 4 factors for consumers’’ maintenance preference is that the first most important factor is frequency, the second is age, the third is oil price and the forth is the area. (2) The result of this research for six kinds of consumer’s maintenance feature can be a reference for further service activities planning.
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| 參考文獻 |
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