Military maximizers: Examining the effect of individual differences in maximization on military decision-making
Military maximizers: Examining the effect of individual differences in maximization on military decision-making
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军事最大化者：检验最大化中的个体差异对军事决策的影响
DOI：
10.1016/j.paid.2020.110051
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发表时间：
2020
影响因子：
4.3
通讯作者：
Lisa Thompson
中科院分区：
文献类型：
--
作者：
N. Shortland;Laurence Alison;Lisa Thompson
本研究调查了最大化在解释高不确定性情况下决策中的个体差异方面所发挥的作用。有大量证据表明最大化会影响决策，但所研究的决策类型都是以消费者为中心的。尽管最大化的重要性众所周知，但最大化的边界尚未被探索。本研究通过证明军事人员样本（n = 287）在做出军事（特定领域）和非军事（一般领域）决策时，最大化的个体差异会影响决策，从而扩展了最大化的研究。此外，分类分析使研究人员能够探索最大化的潜在结构，发现它也可以被概念化为分类（而不是传统的连续）变量。总体而言，高度最大化者发现决策更加困难，选择选项和做出决定的速度也更慢。这些发现与之前关于最大化影响的大量研究一致，但表明最大化的影响延伸到了应用决策，其中应用样本在高度不确定性的情况下做出决策。这些发现对于最大化研究和不确定性下的决策研究具有重要的理论意义，也对人员选择等问题具有应用意义。
The present study investigates the role maximization plays in explaining individual differences in decisionmaking in high-uncertainty situations. There is a wealth of evidence that maximization affects decision-making, yet the types of decisions that have been studied have been consumer-focused. Despite the known importance of maximization, the boundaries of maximization have not been explored. This research extends the study of maximization by evidencing that individual differences in maximization influence decision-making with a sample of military personnel (n= 287) when they make both military (domain specific) and non-military (domain general) decisions. Furthermore, taxometric analysis allowed the researchers to explore the latent structure of maximization, identifying that it can also be conceptualized as a categorical (rather than a traditionally continuous) variable. Overall, high maximizers found decisions more difficult, were slower to choose an option and decide. These findings are in accord with a wealth of previous research on the effects of maximization, but demonstrate that the effect of maximization extends to applied decision-making with applied samples who make decisions in high-uncertainty situations. These findings have important theoretical implications for the study of maximization and the study of decision-making under uncertainty, as well as applied implications for issues such as personnel selection.