Liu Zihan, Hoff Kevin A, Chu Chu, Oswald Frederick L, Rounds James
Department of Management, Marketing and Operations, College of Business and Management, University of Illinois, Springfield.
Department of Psychology, Michigan State University.
J Appl Psychol. 2025 May;110(5):623-647. doi: 10.1037/apl0001232. Epub 2024 Sep 9.
Measuring person-occupation fit serves many important purposes, from helping young people explore majors and careers to helping jobseekers assess fit with available jobs. However, most existing fit measures are limited in that they focus on single individual difference domains without considering how fit may differ across multiple domains. For example, a jobseeker might be highly in a job, yet not possess the requisite to perform the job well. The current research addresses this issue by evaluating an integrative set of person-occupation fit assessments that measure 88 fit dimensions across five domains: and . These measures were either newly developed or adapted from existing assessments to directly correspond with occupational variables from the Occupational Information Network database. Across three studies with diverse samples, we obtained extensive reliability and validity evidence to evaluate the fit assessments. Results consistently showed that integrating across fit domains led to practical improvements in predictions of relevant outcomes, including career choice and subjective and objective career success. However, some fit measures (i.e., interests and knowledge) were generally more predictive of outcomes than others (i.e., personality), thus warranting greater consideration for use in research and applied contexts. We discuss how our results advance theoretical and practical knowledge concerning the measurement of person-occupation fit in the modern labor market. Moreover, to inspire additional research and applications involving whole-person fit measurement, we made all newly developed fit assessments publicly available, providing guidance for using them with the Occupational Information Network database. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
衡量人与职业的匹配度有许多重要目的,从帮助年轻人探索专业和职业,到帮助求职者评估与现有工作的匹配度。然而,大多数现有的匹配度测量方法存在局限性,因为它们只关注单一的个体差异领域,而没有考虑到匹配度在多个领域可能存在的差异。例如,一名求职者可能在某项工作中具备很高的[此处原文缺失相关内容],但却不具备出色完成该工作所需的[此处原文缺失相关内容]。当前的研究通过评估一套综合的人与职业匹配度评估方法来解决这个问题,该方法测量了五个领域的88个匹配度维度:[此处原文缺失相关内容]和[此处原文缺失相关内容]。这些测量方法要么是新开发的,要么是从现有评估中改编而来,以直接对应职业信息网络数据库中的职业变量。在三项针对不同样本的研究中,我们获得了广泛的信度和效度证据来评估这些匹配度评估方法。结果一致表明,整合各个匹配度领域能够在预测相关结果方面带来实际的改进,包括职业选择以及主观和客观的职业成功。然而,一些匹配度测量方法(即兴趣和知识)通常比其他方法(即个性)更能预测结果,因此在研究和应用场景中更值得考虑使用。我们讨论了我们的研究结果如何推进了关于现代劳动力市场中人与职业匹配度测量的理论和实践知识。此外,为了激发更多涉及全人匹配度测量的研究和应用,我们将所有新开发的匹配度评估方法公开,为将它们与职业信息网络数据库一起使用提供指导。(PsycInfo数据库记录(c)2025美国心理学会,保留所有权利)