Arnulf Jan Ketil, Nimon Kim, Larsen Kai Rune, Hovland Christiane V, Arnesen Merethe
Department of Leadership and Organizational Behaviour, BI Norwegian Business School, Oslo, Norway.
Department of Human Resource Development, The University of Texas at Tyler, Tyler, TX, United States.
Front Psychol. 2020 Jun 19;11:1321. doi: 10.3389/fpsyg.2020.01321. eCollection 2020.
This study uses latent semantic analysis (LSA) to explore how prevalent measures of motivation are interpreted across very diverse job types. Building on the Semantic Theory of Survey Response (STSR), we calculate "semantic compliance" as the degree to which an individual's responses follow a semantically predictable pattern. This allows us to examine how context, in the form of job type, influences respondent interpretations of items. In total, 399 respondents from 18 widely different job types (from CEOs through lawyers, priests and artists to sex workers and professional soldiers) self-rated their work motivation on eight commonly applied scales from research on motivation. A second sample served as an external evaluation panel ( = 30) and rated the 18 job types across eight job characteristics. Independent measures of the job types' salary levels were obtained from national statistics. The findings indicate that while job type predicts motivational score levels significantly, semantic compliance as moderated by job type job also predicts motivational score levels usually at a lesser but significant magnitude. Combined, semantic compliance and job type explained up to 41% of the differences in motional score levels. The variation in semantic compliance was also significantly related to job characteristics as rated by an external panel, and to national income levels. Our findings indicate that people in different contexts interpret items differently to a degree that substantially affects their score levels. We discuss how future measurements of motivation may improve by taking semantic compliance and the STSR perspective into consideration.
本研究运用潜在语义分析（LSA）来探究在极为多样的工作类型中，动机的普遍衡量标准是如何被解读的。基于调查反应语义理论（STSR），我们将“语义一致性”计算为个体回答遵循语义可预测模式的程度。这使我们能够考察工作类型形式的背景如何影响受访者对项目的解读。共有来自18种差异极大的工作类型（从首席执行官到律师、牧师、艺术家，再到性工作者和职业军人）的399名受访者，根据动机研究中常用的八个量表对自己的工作动机进行了自评。第二个样本作为外部评估小组（n = 30），对18种工作类型的八个工作特征进行了评分。工作类型的薪资水平独立测量值取自国家统计数据。研究结果表明，虽然工作类型能显著预测动机得分水平，但由工作类型调节的语义一致性通常也能以较小但显著的幅度预测动机得分水平。综合来看，语义一致性和工作类型解释了动机得分水平差异的41%。语义一致性的变化也与外部评估小组评定的工作特征以及国家收入水平显著相关。我们的研究结果表明，处于不同背景下的人对项目的解读存在差异，且这种差异在很大程度上影响了他们的得分水平。我们讨论了未来动机测量如何通过考虑语义一致性和STSR视角来改进。
