A common practice in applications of structural equation modeling techniques is to create composite measures from individual items. The purpose of this article was to provide an empirical comparison of several composite formation methods on model fit. Data from 1, 177 public school teachers were used to test a model of union commitment in which alternative composite formation methods were used to specify the measurement components of the model. Bootstrapping procedures were used to generate data for two additional sample sizes. Results indicated that the use of composites, in general, resulted in improved overall model fit as compared to treating all items as individual indicators. Lambda values and explained criterion variance indicated that this improved model fit was due to the creation of strong measurement models. Implications of these results for researchers using composites are discussed.

We used psychological contract theory as a framework to meta-analytically review subjective and objective predictors of employees' perceived job insecurity. Seventy-six samples from 68 studies were included in our review. Results revealed that lower levels of job insecurity are associated with having an internal locus of control, lower amounts of role ambiguity and role conflict, greater amounts of organizational communication, less organizational change, younger employees, and white-collar and permanent work. Moderator analyses further revealed that relations between job insecurity and age, gender, education, and formal contracts are moderated by unemployment rates, countries of origin, and type of job insecurity measure. We discuss theoretical and practical implications for psychological contract theory and occupational health, and offer directions for future research.

Purpose Questionable research or reporting practices (QRPs) contribute to a growing concern regarding the credibility of research in the organizational sciences and related fields. Such practices include design, analytic, or reporting practices that may introduce biased evidence, which can have harmful implications for evidence-based practice, theory development, and perceptions of the rigor of science. Design/Methodology/Approach To assess the extent to which QRPs are actually a concern, we conducted a systematic review to consider the evidence on QRPs. Using a triangulation approach (e.g., by reviewing data from observations, sensitivity analyses, and surveys), we identified the good, the bad, and the ugly. Findings Of the 64 studies that fit our criteria, 6 appeared to find little to no evidence of engagement in QRPs and the other 58 found more severe evidence (91 %). Implications Drawing upon the findings, we provide recommendations for future research related to publication practices and academic training. Originality/value We report findings from studies that suggest that QRPs are not a problem, that QRPs are used at a suboptimal rate, and that QRPs present a threat to the viability of organizational science research.

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A meta‐analytic path analysis with k = 52 studies and sample size of roughly 17,000 showed that enhanced perceptions of organizational honesty is the primary mechanism by which realistic job previews (RJPs) influence voluntary turnover. This suggests revisions to RJP theory to incorporate social exchange and the way RJPs lead individuals to feel about the organization. Results assessing several new potential moderators of relationships between RJPs and turnover found that the most effective RJP design may be an oral or written RJP delivered posthire and designed to signal organizational honesty. We discuss several key theoretical and practical implications of the results based on a novel signaling theory perspective on RJPs.

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The world is awash in data. Data is being created and stored at ever-increasing rates through a variety of new methods and technologies. Data is accumulating in all sorts of accessible places. Much of that data is of great interest to industrial–organizational (I-O) psychologists, often in ways never anticipated by those who develop technologies and processes that generate and store that data. I-O psychologists also generate data in the course of research and practice in ways that, especially if joined with data originating from other sources, create giant datasets. This abundance of data—variables, measurements, observations, facts—can be used to inform a vast number of issues in research and practice. This is the new “big data” world, and beyond opportunities, this new world also presents challenges and potential hazards.