Risk aversion and risk seeking in multicriteria forest management: a Markov decision process approach
Risk aversion and risk seeking in multicriteria forest management: a Markov decision process approach
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多标准森林管理中的风险规避和风险寻求：马尔可夫决策过程方法
DOI：
10.1139/cjfr-2016-0502
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发表时间：
2017
影响因子：
2.2
通讯作者：
C. Johnston
中科院分区：
文献类型：
--
作者：
J. Buongiorno;Mo Zhou;C. Johnston
马尔可夫决策过程模型进行了扩展，以反映林业决策者的风险态度的一些后果。一种方法包括最大化的期望值的标准的方差上界，或对称地，最小化的方差下界的期望值。另一种方法使用确定性等效准则，即期望值和方差的加权平均值。这两种方法被应用到混合软木硬木森林在美国南部的数据与多个金融和生态标准。与风险中性或风险寻求相比，金融风险规避降低了预期的年度财务回报和产量，并导致较短的采伐周期，降低了预期的树种和大小，林分断面积，储存CO2e和老生长面积的多样性。
Markov decision process models were extended to reflect some consequences of the risk attitude of forestry decision makers. One approach consisted of maximizing the expected value of a criterion subject to an upper bound on the variance or, symmetrically, minimizing the variance subject to a lower bound on the expected value. The other method used the certainty equivalent criterion, a weighted average of the expected value and variance. The two approaches were applied to data for mixed softwood–hardwood forests in the southern United States with multiple financial and ecological criteria. Compared with risk neutrality or risk seeking, financial risk aversion reduced expected annual financial returns and production and led to shorter cutting cycles that lowered the expected diversity of tree species and size, stand basal area, stored CO2e, and old-growth area.