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Inventory Model for Auto Service Parts Considering Vehicle Warranty Period and Return rate
Service parts,Warranty period,Return rate,Service level,Demand forecasting,Parts inventory management,
|Publication Year :||2021|
In recent year owing to the increasing percentage of cost to price ratio, the extension of average vehicle age and the consideration of car purchase, many car manufacturers have more strategies on aftersales that has higher profits and gradually expanding scale. Improving the return rate is one of the most important issue of aftersales considering limitations of the workshop equipment, time, manpower and other factors. Most of the consumers will still return to the dealers’ workshop within the warranty period limited by the warranty terms. In addition to the incentives of marketing, service level will also affect willingness to return to the dealers’ workshop. To meet the customer's parts needs, subsequent visits may be affected. If the parts demand aren’t satisfied within warranty period, then the willingness to return would be impacted.
Therefore, this research takes the vehicle within warranty period as the research object, compares the difference in return rate of different models, revises the demand forecasting model, and combines it to the case company's current periodic inventory system to construct a more accurate inventory management model. At last, it compares the cost difference between the research result and the current practice at the case company's target service level and proposes practical management implications for the case company's reference in inventory management strategy.
The analysis results show that the combination of the return rate and the regression equation are the basis for demand forecasting which can better grasp the fluctuated parts demand and moving average method of the case company that is more suitable for the mature period of parts with less fluctuation in demand. The standard of classification is one of the factors that affects the parts demand forecasting and the efficiency of the inventory model. If the part categories are used as parameter setting and applied to specific parts, the results would be biased due to lack of individual heterogeneity. But if by using parts demand as the classification criteria, the results of the model building would be more accurate. At last, if it has to achieve target service level, it will increase parts inventory and cost, but back order situation will be improved. However, if the inventory is reduced in order to reduce costs, the shortage will be greatly improved, affecting the service level and customer satisfaction.
|Appears in Collections:||商學研究所|
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