While authentic leadership (AL) has seen a dramatic increase in scholarly attention over the last decade, its contribution relative to more established leadership constructs merits investigation. We ...employ meta-analytic techniques to compare AL and transformational leadership theories using 100 independent samples and 25,452 individuals. The findings reveal that (1) the relationship between authentic and transformational leadership is large in magnitude, suggesting construct redundancy (ρ=.72); (2) neither AL nor transformational leadership add noticeable incremental validity beyond the other construct; (3) AL has a lower relative weight than transformational leadership for the outcomes of follower satisfaction, follower satisfaction with the leader, task performance, and leader effectiveness; and (4) AL demonstrates dominance over transformational leadership when predicting group or organization performance and organizational citizenship behaviors. We recommend future research examine AL at the component level and its relationships with related ethical constructs to potentially differentiate it from transformational leadership.
We reviewed studies of the Dark Triad (DT) personality traits-Machiavellianism, narcissism, and psychopathy-and meta-analytically examined their implications for job performance and counterproductive ...work behavior (CWB). Relations among the DT traits and behaviors were extracted from original reports published between 1951 and 2011 of 245 independent samples (N = 43,907). We found that reductions in the quality of job performance were consistently associated with increases in Machiavellianism and psychopathy and that CWB was associated with increases in all 3 components of the DT, but that these associations were moderated by such contextual factors as authority and culture. Multivariate analyses demonstrated that the DT explains moderate amounts of the variance in counterproductivity, but not job performance. The results showed that the 3 traits are positively related to one another but are sufficiently distinctive to warrant theoretical and empirical partitioning.
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Methods and data innovations have served as catalysts for theory advancement and policy-making throughout the evolution of management and many other fields. However, new methods take a long time to ...be diffused and adopted. The most common contemporary methods used in management research are similar to those used decades ago. Drawing upon theories of knowledge diffusion and adoption, we identify four barriers to the slow propagation of methodological innovations: (a) insufficient knowledge or skills, (b) inadequate adoption of technology, (c) outdated norms, and (d) inefficient incentives as well as inapplicable journal and professional organization policies. Then, to show the usefulness of the four-barrier framework for understanding slow diffusion and adoption, we focus on three selective methods and data innovations: Collection of Web-based (aka big) data, utilization of video-based methods, and use of computer-aided text analysis techniques. Our aim is not to create a "gold rush" for new methods or accelerate methodological and theoretical speed for their own sake, but to expand our collective methodological toolkit to develop and test more robust, replicable, accurate, predictive, and credible theory that will result in better-informed and more effective policy-making.
In describing measures used in their research, authors frequently report having adapted a scale, indicating that they changed something about it. Although such changes can raise concerns about ...validity, there has been little discussion of this practice in our literature. To estimate the prevalence and identify key forms of scale adaptation, we conducted two studies of the literature. In Study 1, we reviewed the descriptions of all scales (N = 2,088) in four top journals over a 2-year period. We found that 46% of all scales were reported by authors as adapted and that evidence to support the validity of the adapted scales was presented in 23% of those cases. In Study 2, we chose six scales and examined their use across the literature, which allowed us to identify unreported adaptations. We found that 85% of the administrations of these scales had at least one form of adaptation and many had multiple adaptations. In Study 3, we surveyed editorial board members and a select group of psychometricians to evaluate the extent to which particular adaptations raised concerns about validity and the kinds of evidence needed to support the validity of the adapted scales. To provide guidance for authors who adapt scales and for reviewers and editors who evaluate papers with adapted scales, we present discussions of several forms of adaptations regarding potential threats to validity and recommendations for the kinds of evidence that might best support the validity of the adapted scale (including a reviewer checklist).
Access to data is a critical feature of an efficient, progressive and ultimately self-correcting scientific ecosystem. But the extent to which in-principle benefits of data sharing are realized in ...practice is unclear. Crucially, it is largely unknown whether published findings can be reproduced by repeating reported analyses upon shared data (‘analytic reproducibility’). To investigate this, we conducted an observational evaluation of a mandatory open data policy introduced at the journal Cognition. Interrupted time-series analyses indicated a substantial post-policy increase in data available statements (104/417, 25% pre-policy to 136/174, 78% post-policy), although not all data appeared reusable (23/104, 22% pre-policy to 85/136, 62%, post-policy). For 35 of the articles determined to have reusable data, we attempted to reproduce 1324 target values. Ultimately, 64 values could not be reproduced within a 10% margin of error. For 22 articles all target values were reproduced, but 11 of these required author assistance. For 13 articles at least one value could not be reproduced despite author assistance. Importantly, there were no clear indications that original conclusions were seriously impacted. Mandatory open data policies can increase the frequency and quality of data sharing. However, suboptimal data curation, unclear analysis specification and reporting errors can impede analytic reproducibility, undermining the utility of data sharing and the credibility of scientific findings.
Leadership remains a popular and heavily researched area in the social sciences. Such popularity has led to a proliferation of new constructs within the leadership domain. Here, we argue that such ...construct proliferation without pruning is unhealthy and violates the principle of parsimony. Our purpose was to examine construct redundancy via a comprehensive review of task-oriented, relational, passive, and inspirational leader behaviors as well as values-based and moral leadership behaviors. Our findings, as indexed via meta-analytic correlations, reveal that construct redundancy remains problematic for the leadership literature. In addition, many of the values-based and moral behavior models correlated heavily with constructs traditionally examined as outcome variables (e.g., trust, LMX, justice). Implications for future research are discussed in regards to construct redundancy and how to avoid endogeneity bias in primary studies in the leadership literature.
Publication bias poses multiple threats to the accuracy of meta-analytically derived effect sizes and related statistics. Unfortunately, a review of the literature indicates that unlike meta-analytic ...reviews in medicine, research in the organizational sciences tends to pay little attention to this issue. In this article, the authors introduce advances in meta-analytic techniques from the medical and related sciences for a comprehensive assessment and evaluation of publication bias. The authors illustrate their use on a data set on employment interview validities. Using multiple methods, including contour-enhanced funnel plots, trim and fill, Egger’s test of the intercept, Begg and Mazumdar’s rank correlation, meta-regression, cumulative meta-analysis, and selection models, the authors find limited evidence of publication bias in the studied data.
The present research focuses on supervisor-subordinate guanxi (SSG) – a non-work or personal tie that reflects the relationship between a subordinate and their supervisor. Although SSG has received ...considerable attention, results are mixed. Further, how the Eastern conceptualization of SSG differs from the Western conceptualization of leader-member exchange (LMX) remains nebulous. We meta-analyzed 71 samples that contain 238 effect sizes. We found that: (1) SSG has a strong overlap with LMX (ρ̅̂ = 0.56); (2) SSG has small magnitude relations with its correlates (age, gender, education, and tenure); (3) SSG demonstrates smaller relative weights than LMX in predicting outcome variables (task performance, organizational citizenship behavior, job satisfaction, organizational commitment, turnover intention, subordinates' perceived distributive justice, subordinates' perceived procedural justice, and trust in supervisor); and (4) SSG contributes statistically significant, yet very small (ranging from 0.00 to 0.04), incremental validity above and beyond LMX in predicting all of the aforementioned outcome variables except for subordinates' perceived distributive justice. We conclude with a discussion of future directions for research on SSG.
•Supervisor-subordinate guanxi (SSG) overlaps with leader-member exchange (LMX).•SSG has small relations with its correlates (age, gender, education, and tenure).•SSG shows smaller relative weights than LMX in predicting outcome variables.•SSG shows very small incremental validities beyond LMX in predicting outcomes.
As growth mindset interventions increase in scope and popularity, scientists and policymakers are asking: Are these interventions effective? To answer this question properly, the field needs to ...understand the meaningful heterogeneity in effects. In the present systematic review and meta-analysis, we focused on two key moderators with adequate data to test: Subsamples expected to benefit most and implementation fidelity. We also specified a process model that can be generative for theory. We included articles published between 2002 (first mindset intervention) through the end of 2020 that reported an effect for a growth mindset intervention, used a randomized design, and featured at least one of the qualifying outcomes. Our search yielded 53 independent samples testing distinct interventions. We reported cumulative effect sizes for multiple outcomes (i.e., mindsets, motivation, behavior, end results), with a focus on three primary end results (i.e., improved academic achievement, mental health, or social functioning). Multilevel metaregression analyses with targeted subsamples and high fidelity for academic achievement yielded, d = 0.14, 95% CI .06, .22; for mental health, d = 0.32, 95% CI .10, .54. Results highlighted the extensive variation in effects to be expected from future interventions. Namely, 95% prediction intervals for focal effects ranged from −0.08 to 0.35 for academic achievement and from 0.07 to 0.57 for mental health. The literature is too nascent for moderators for social functioning, but average effects are d = 0.36, 95% CI .03, .68, 95% PI −.50, 1.22. We conclude with a discussion of heterogeneity and the limitations of meta-analyses.
Public Significance Statement
Growth mindset interventions are increasing in popularity in education and are being applied to improving other areas of functioning as well; however, there is debate about how well they work. Despite the large variation in effectiveness, we found positive effects on academic outcomes, mental health, and social functioning, especially when interventions are delivered to people expected to benefit the most.
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