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Adding versus averaging: Evaluability theory applied to job choice decisions
Journal of Behavioral Decision Making ( IF 2.508 ) Pub Date : 2020-05-15 , DOI: 10.1002/bdm.2186
Yalcin Acikgoz 1
Affiliation  

While the unique roles of individual job attributes (e.g., salary and benefits) in job and organizational attraction have received extensive research attention, research examining the mechanisms through which an overall evaluation of a job option is made by combining evaluations of individual attributes is scarce. The current study examined the process through which job choice decisions are made under three conditions: when evaluating a single job offer, when comparing two job offers, and when evaluating more than two job offers. In Study 1, it was found that when a single job offer is evaluated, the average of perceived values of attributes in an offer (e.g., the perceived attractiveness of a salary) drives the choice, whereas the difference between jobs is what matters when two jobs are evaluated simultaneously, potentially leading to a preference reversal between conditions when the same two jobs are evaluated. In Study 2, it was found that average values of attributes across options (e.g., average salary in all job offers received) influence job choice when more than two job offers are evaluated simultaneously. These findings indicate that in all three conditions, job choice decisions are influenced by the evaluability of the choice set, which becomes low when a single job offer is evaluated without any context, or when more than two job offers are evaluated simultaneously, and becomes high when two jobs are compared with each other. When evaluability is low, candidates resort to averaging as the decision rule, whereas adding is used when evaluability is high.

中文翻译:

加法与平均法:可评估性理论应用于工作选择决策

尽管个体工作属性(例如,薪水和福利)在工作和组织吸引力中的独特作用已受到广泛的研究关注,但尚缺乏研究通过结合对个体属性的评估对工作选择进行总体评估的机制的研究。当前的研究检查了在以下三个条件下做出工作选择决定的过程:评估单个工作机会时,比较两个工作机会时,以及评估两个以上工作机会时。在研究1中,发现对单个工作机会进行评估时,工作机会中属性的感知价值的平均值(例如,工资的吸引力)驱动选择,而两个工作之间的差异就很重要同时评估工作 当评估相同的两个作业时,可能导致条件之间的偏好反转。在研究2中,发现当同时评估两个以上的工作机会时,跨选项的属性平均值(例如,收到的所有工作机会的平均薪水)会影响工作选择。这些发现表明,在所有三种情况下,工作选择决定都会受到选择集的可评估性的影响;当在没有任何上下文的情况下评估单个工作机会时,或者同时评估两个以上的工作机会时,工作机会选择就变得很低。当两个工作相互比较时。当可评估性较低时,候选人求助于求平均值作为决策规则,而当可评估性较高时则使用加法。我们发现,当同时评估两个以上的工作机会时,各个选项的属性平均值(例如,收到的所有工作机会的平均薪水)都会影响工作选择。这些发现表明,在所有三种情况下,工作选择决定都会受到选择集的可评估性的影响;当在没有任何上下文的情况下评估单个工作机会时,或者同时评估两个以上的工作机会时,工作机会选择就变得很低。当两个工作相互比较时。当可评估性较低时,候选人求助于求平均值作为决策规则,而当可评估性较高时则使用加法。我们发现,当同时评估两个以上的工作机会时,各个选项的属性平均值(例如,收到的所有工作机会的平均薪水)都会影响工作选择。这些发现表明,在所有三种情况下,工作选择决定都会受到选择集的可评估性的影响;当在没有任何上下文的情况下评估单个工作机会时,或者同时评估两个以上的工作机会时,工作机会选择就变得很低。当两个工作相互比较时。当可评估性较低时,候选人求助于求平均值作为决策规则,而当可评估性较高时则使用加法。这些发现表明,在所有三种情况下,工作选择决定都会受到选择集的可评估性的影响;当在没有任何上下文的情况下评估单个工作机会时,或者同时评估两个以上的工作机会时,工作机会选择就变得很低。当两个工作相互比较时。当可评估性较低时,候选人求助于求平均值作为决策规则,而当可评估性较高时则使用加法。这些发现表明,在所有三种情况下,工作选择决定都会受到选择集的可评估性的影响;当在没有任何上下文的情况下评估单个工作机会时,或者同时评估两个以上的工作机会时,工作机会选择就变得很低。当两个工作相互比较时。当可评估性较低时,候选人求助于求平均值作为决策规则,而当可评估性较高时则使用加法。
更新日期:2020-05-15
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