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首页> 外文期刊>Journal of Forest Economics >Annual use, economic life and residual value of cut-to-length harvesting machines.
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Annual use, economic life and residual value of cut-to-length harvesting machines.

机译:定尺收获机的年度使用量,经济寿命和残值。

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摘要

Recognizing the absence of up-to-date empirical data on the economic life, the annual use and the residual value of dedicated cut-to-length (CTL) harvesting machinery, the authors gathered a large database of second-hand machine sale offers containing over 1000 records, coming from Europe and North America. The statistical analysis of these data pointed at an economic life in the vicinity of 18,000 h for both harvesters and forwarders, which confirms previous assumptions. The average annual use for the machines in the database is 1424 and 1581 h year-1, respectively for the harvesters and the forwarders. Nordic users achieve a higher annual use than central European users, and the difference is statistically significant. Nevertheless, the average annual use recorded for both groups falls below the levels commonly adopted in current estimates, which may therefore represent ideal reference figures rather than actual averages. Residual value is strongly related to machine age, and the authors calculated some simple functions for estimating it. The study points at a better retention of the original value, compared to the figures reported in previous literature. At 5 years of age the harvesters and forwarders in the study keep respectively 38% and 44% of the new value. The information contained in the study is crucial to machine rate calculation, which has often been based on rule-of-thumb assumptions, in the absence of empirical data.
机译:认识到缺乏有关专用定尺(CTL)收获机械的经济寿命,年度使用和残值的最新经验数据,作者收集了一个庞大的二手机器销售报价数据库,其中包括来自欧洲和北美的1000多个记录。对这些数据的统计分析表明,收割机和货运代理的经济寿命均在18,000小时左右,这证实了先前的假设。数据库中机器的平均年使用量分别为1424和1581 h year -1 。北欧用户的年使用量比中欧用户高,差异在统计上是显着的。不过,两组记录的年平均使用量均低于当前估计数通常采用的水平,因此,这可能是理想的参考数字,而不是实际的平均值。残留值与机器寿命密切相关,作者计算了一些简单函数来估算它。与先前文献中报道的数字相比,该研究指出保留了原始值更好。在5岁时,研究中的收割机和货运代理分别保持新值的38%和44%。该研究中包含的信息对于机器速率的计算至关重要,而机器速率通常是基于经验法则的假设而缺乏经验数据。

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