This research identifies four challenges in the field of person–environment fit (PE fit): the multidimensionality of PE fit, the integration of fit theories, the simultaneous effects of the multiple dimensions, and the function of the dimensions. To address those challenges, we develop a theory‐driven and systematically validated multidimensional instrument, the Perceived Person–Environment Fit Scale (PPEFS), consisting of four measures: the Person–Job Fit Scale (PJFS), the Person–Organisation Fit Scale (POFS), the Person–Group Fit Scale (PGFS), and the Person–Supervisor Fit Scale (PSFS). Data are collected from 532 employees and 122 managers for two independent studies with multiple rater sources and multiple time points. A series of validation analyses and hypothesis tests reveals that the PPEFS measures have good psychometric properties (i.e. reliability, convergent validity, discriminant validity, and criterion‐related validity) and exhibit incremental validity above and beyond Cable and DeRue's (2002) fit measures. Furthermore, the measures are reflected by a superordinate (vs. aggregate) construct of PE fit. Overall, the four different types of fit significantly predict in‐role behavior, job satisfaction, intent to quit, and organisational citizenship behavior (OCB), each explaining the greatest amount of variance in different outcomes. The PPEFS should prove useful in future research regarding PE fit. 相似文献
This paper presents a dynamic tree-based item response (IRTree) model as a novel extension of the autoregressive generalized linear mixed effect model (dynamic GLMM). We illustrate the unique utility of the dynamic IRTree model in its capability of modeling differentiated processes indicated by intensive polytomous time-series eye-tracking data. The dynamic IRTree was inspired by but is distinct from the dynamic GLMM which was previously presented by Cho, Brown-Schmidt, and Lee (Psychometrika 83(3):751–771, 2018). Unlike the dynamic IRTree, the dynamic GLMM is suitable for modeling intensive binary time-series eye-tracking data to identify visual attention to a single interest area over all other possible fixation locations. The dynamic IRTree model is a general modeling framework which can be used to model change processes (trend and autocorrelation) and which allows for decomposing data into various sources of heterogeneity. The dynamic IRTree model was illustrated using an experimental study that employed the visual-world eye-tracking technique. The results of a simulation study showed that parameter recovery of the model was satisfactory and that ignoring trend and autoregressive effects resulted in biased estimates of experimental condition effects in the same conditions found in the empirical study.
The idea that influential factors for two subtypes of aggression (reactive and proactive aggression) should be different is popular, but the common influential factors have not been examined. Such an examination could help understand the influential factors of aggression from the perspective of multiple motivations affecting the development of aggressive motivations over time. The present study argued that angry rumination would be a common influential factor for both reactive and proactive aggression. In addition, consideration of future consequences (CFC) may moderate the longitudinal effect of angry rumination on proactive aggression. Two studies were conducted to test these hypotheses. In Study 1, a cross-lagged analysis with a 6-month interval was employed. A total of 505 undergraduate students (46% males) completed the questionnaires twice. Results indicated that after a 6-month period, angry rumination predicted reactive aggression but not proactive aggression. Furthermore, reactive aggression predicted angry rumination over time. In Study 2, a moderation analysis was performed with another 437 participants (130 males). The results partly supported our hypotheses, indicating that CFC-immediate (CFC-I) moderated the longitudinal effect of angry rumination on proactive aggression. The present results extended prior research regarding the predictors of proactive and reactive aggression and may contribute to a greater understanding of the development of aggressive motivation. In addition, our research suggested that high CFC-I may be an important factor for the motivation change from reactive aggression to proactive aggression. 相似文献