Situational Strength Interactions: Are Variance Patterns Consistent With the Theory?

• 成果类型: Article
• 署名作者: Keeler, Kathleen R.; Kong, Wenmo; Dalal, Reeshad S.; Cortina, Jose M.
• 署名单位: Virginia Commonwealth University; George Mason University
• 刊物名称: JOURNAL OF APPLIED PSYCHOLOGY
• ISSN/ISSBN: 0021-9010
• DOI: 10.1037/apl0000416
• 发表日期: 2019
• 页码: 1487-1513
• 关键词: situational strength; strong situation; Moderation; job characteristics model; SELF-DETERMINATION THEORY

摘要

Mischel's (1973, 1977) theory of situational strength has been used widely within the organizational sciences to help explain why contextual factors moderate predictor-criterion relationships. Situational strength interactions represent a particular type known as a restricted variance (RV) interaction (Cortina. Kohler, & Nielsen, 2015). The theory proposes that the strength of a given situation constrains or compresses the variance of the dependent variable, weakening its prediction from other variables. Other theories and models, such as self-determination theory and the job characteristics model, also make implicit references to variance compression based on the level of autonomy in a given situation and to the interactions that this compression creates. It is unclear, however, whether differences in strength (or degree of constraint) actually yield variance differences that are consistent with the theoretical framework. In this meta-analysis, we reviewed 132 articles that imply RV effects. 100 of which allowed for variance comparisons. We found that only a handful of authors explicitly connect their theoretical arguments and interaction hypotheses to changes in variance in the Introduction section of their articles. Moreover, our findings also reveal that, for the most part, variance differences between weak and strong situations are minimal. Where differences exist, they are often in the opposite of the expected direction (i.e., larger variance in strong situations). We discuss our findings and their theoretical and practical implications. We also provide recommendations for designing studies and testing for such interactions.