利用市场人口统计数据预测陆军预备役部队编制

Q3 Decision Sciences
Nathan L. Parker
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引用次数: 0

摘要

本研究开发了一个数据驱动的统计模型,能够根据单位所在地的人口统计数据预测美国陆军预备役(USAR)单位的人员配备水平。该模型为决策者提供了一个评估,评估一个拟议的站点位置是否有能力支持一个单位对当地人口的人员需求。设计/方法/方法本研究首先开发了一种分配方法,以克服重叠单元边界造成的挑战,以防止人口的过度计数。一旦人口被准确地分配到每个地点,我们就会开发和比较统计模型的性能,以估计一个地点满足人员配备需求的可能性。这项研究发现,当地的人口因素对一个地区满足员工需求的能力至关重要。我们建议USAR和美国陆军招募司令部(USAREC)使用这里开发的逻辑回归模型来支持USAR单位驻扎决策;这将提高各单位达到所需员额水平的能力。独创性/价值本研究满足了USAREC与USAR的直接要求,协助开发模型,以帮助单位驻扎过程中的决策者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting army reserve unit manning using market demographics
Purpose This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides decision makers an assessment of a proposed station location’s ability to support a unit’s personnel requirements from the local population. Design/methodology/approach This research first develops an allocation method to overcome challenges caused by overlapping unit boundaries to prevent over-counting the population. Once populations are accurately allocated to each location, we then then develop and compare the performance of statistical models to estimate a location’s likelihood of meeting staffing requirements. Findings This research finds that local demographic factors prove essential to a location’s ability to meet staffing requirements. We recommend that the USAR and US Army Recruiting Command (USAREC) use the logistic regression model developed here to support USAR unit stationing decisions; this should improve the ability of units to achieve required staffing levels. Originality/value This research meets a direct request from the USAREC, in conjunction with the USAR, for assistance in developing models to aid decision makers during the unit stationing process.
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
5
审稿时长
12 weeks
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