| dc.description.abstract | Nowadays airlines are facing increasingly severe competition. In order to effectively control costs and focus on the development of core capabilities, airlines are showing more and more interest in joining so-called “Total Care” engine maintenance management program, such as Fleet Management Program (FMP), Material Management Program (MMP), Inventory Logistics Program (ILP) etc. For those professional engine shops or repair stations, this is obviously a great opportunity. However, different engine failure mode or part distress severity will require very different repair workscopes. How to standardize the maintenance work is another hard task to handle. As a consequence, the repiar cost becomes very difficult to predict and control in advance. Without the accurate cost information, engine shops or repair stations have to find out an effective pricing mode to make sure price is reasonably set. Pricing too high is not competitive, too low may compromise profits, not to mention the increase of operational risk.
The study attempts to find a convenient way to resolve such an issue by grouping the customer’s parts with similar property per correspondence analysis and cluster analysis first. And then, through the Data Envelopment Analysis (DEA) method as well as one of its extensions, Revenue Efficiency model analysis, we can identify the price range of DMUs with relative revenue efficiency. Data collection covers the past three-year detail repair and price information of the case study company. Based on the results, we can obtain an objective and practical mode for pricing adjustment reference. This is also the basis for management team to review pricing and negotiate with customers in future.
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