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Decision Support in Car Leasing: A Forecasting Model for Residual Value Estimation

机译:汽车租赁中的决策支持:残值估计的预测模型

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The paper proposes a methodology to support pricing decisions in the car leasing industry. In particular, the price is given by the monthly fee to be paid by the lessee as compensation for using a car over some contract horizon. After contract expiration, lessors are obliged to take back the vehicle, which will then be sold in the used car market. Therefore, lessors require an accurate estimate of cars' residual values to manage the risk inherent to their business and determine profitable prices. We explore the organizational and technical requirements associated with this forecasting task and develop a prediction model that complies with identified application constraints. The model is rigorously tested within an empirical study and compared to established benchmarks. The results obtained in several experiments provide strong evidence for the proposed model being effective in generating accurate predictions of cars' residual values and efficient in requiring little user intervention.
机译:本文提出了一种方法来支持汽车租赁行业中的定价决策。特别是,价格由承租人支付的月租费来确定,作为在某些合同期限内使用汽车的补偿。合同到期后,出租人必须收回车辆,然后将其在二手车市场上出售。因此,出租人需要准确估计汽车的残值,以管理其业务固有的风险并确定可盈利的价格。我们探索与此预测任务相关的组织和技术要求,并开发符合已确定的应用程序约束的预测模型。该模型在经验研究中经过严格测试,并与已建立的基准进行了比较。在几次实验中获得的结果为所提出的模型有效地产生了汽车残值的准确预测,并且在几乎不需要用户干预的情况下有效提供了有力的证据。

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