We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal relationships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control independent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substantive domains and topics that can benefit from implementing EVM, address knowledge gaps regarding EVM such as the need to increase realism and the number and diversity of participants, and address ways to overcome some of the negative perceptions about EVM by pointing to exemplary articles that have used EVM successfully.

We clarify differences among moderation, partial mediation, and full mediation and identify methodological problems related to moderation and mediation from a review of articles in Strategic Management Journal and Organization Science published from 2005 to 2014. Regarding moderation, we discuss measurement error, range restriction, and unequal sample sizes across moderator-based subgroups; insufficient statistical power; the artificial categorization of continuous variables; assumed negative consequences of correlations between product terms and its components (i.e., multicollinearity); and interpretation of first-order effects based on models excluding product terms. Regarding mediation, we discuss problems with the causal-steps procedure, inferences about mediation based on cross-sectional designs, whether a relation between the antecedent and the outcome is necessary for testing mediation, the routine inclusion of a direct path from the antecedent to the outcome, and consequences of measurement error. We also explain how integrating moderation and mediation can lead to important and useful insights for strategic management theory and practice. Finally, we offer specific and actionable recommendations for improving the appropriateness and accuracy of tests of moderation and mediation in strategic management research. Our recommendations can also be used as a checklist for editors and reviewers who evaluate manuscripts reporting tests of moderation and mediation.

We conducted a quantitative and a qualitative study to assess the extent to which industrial and organizational (I–O) psychology has moved to business schools, understand the nature of this move, and offer a balanced discussion of positive and negative consequences of this phenomenon. In quantitative Study 1, we provide evidence that I–O psychologists affiliated with business schools currently constitute a majority of editorial board members and authors of articles published in Journal of Applied Psychology and Personnel Psychology but that I–O psychology, as a field, is growing. These results suggest that it is not the field of I–O psychology but some of the most active and influential I–O psychology researchers who are moving to business schools. In qualitative Study 2, we gathered perspectives from 144 SIOP Fellows and 27 SIOP presidents suggesting different views on Study 1's results ranging from very negative (i.e., “brain drain”) to very positive (i.e., “eye opener”) depending on the affiliation of the respondent. On the basis of these results, we offer 10 admittedly provocative predictions to stimulate follow‐up research and serve as a catalyst for an important conversation, as well as the development of action plans, regarding the future of I–O psychology as a field.

We offer a four-category taxonomy of individual output distributions (i.e., distributions of cumulative results): (1) pure power law; (2) lognormal; (3) exponential tail (including exponential and power law with an exponential cutoff); and (4) symmetric or potentially symmetric (including normal, Poisson, and Weibull). The four categories are uniquely associated with mutually exclusive generative mechanisms: self-organized criticality, proportionate differentiation, incremental differentiation, and homogenization. We then introduce distribution pitting, a falsification-based method for comparing distributions to assess how well each one fits a given data set. In doing so, we also introduce decision rules to determine the likely dominant shape and generative mechanism among many that may operate concurrently. Next, we implement distribution pitting using 229 samples of individual output for several occupations (e.g., movie directors, writers, musicians, athletes, bank tellers, call center employees, grocery checkers, electrical fixture assemblers, and wirers). Results suggest that for 75% of our samples, exponential tail distributions and their generative mechanism (i.e., incremental differentiation) likely constitute the dominant distribution shape and explanation of nonnormally distributed individual output. This finding challenges past conclusions indicating the pervasiveness of other types of distributions and their generative mechanisms. Our results further contribute to theory by offering premises about the link between past and future individual output. For future research, our taxonomy and methodology can be used to pit distributions of other variables (e.g., organizational citizenship behaviors). Finally, we offer practical insights on how to increase overall individual output and produce more top performers. (PsycINFO Database Record

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