From the Editors Publishing Laboratory Research in AMJ: A Question of When, Not If

Making a theoretical contribution is a core element of AMJ’s mission statement and its criteria for evaluating manuscripts. In describing what theory is and is not, Sutton and Staw (1995: 378) wrote, “Theory is about the connections among phenomena, a story about why acts, events, structure, and thoughts occur. Theory emphasizes the nature of causal relationships, identifying what comes first as well as the timing of such events” (1995: 378). The causal relationships aspect of theory is especially important in the applied sciences, where theories may eventually inspire interventions designed to improve some business outcome. For example, a scholar with expertise in motivation might advise an organization to use specific and difficult goals in its performance management system. That scholar would feel more comfortable making such a recommendation if he or she truly believed that specific and difficult goals cause increases in task performance (Locke & Latham, 1990). Unfortunately, inferring causality is one of the most difficult aspects of scientific research. Drawing on J. S. Mill, Cook and Campbell (1979) suggested that inferring causality depends on three criteria: (1) covariation between cause and effect, (2) temporal precedence of the cause, and (3) elimination of alternative explanations for the possible cause-effect connection. Consider a study in which employees were surveyed about the specificity and difficulty of their work goals in one time period, with their supervisors asked to rate their task performance in a subsequent time period. A correlation between those two measures would provide some support for the first two criteria for inferring causality, but what of the third? It may be that high task performance causes employees to be given more specific and difficult goals, meaning that the “effect” actually causes the “cause. ” It may also be that a third variable impacts both work goals and task performance, creating a spurious relationship between the two. For example, leaders high in “initiating structure” may assign specific and difficult goals more frequently while also engaging in behaviors that benefit employee performance. Alternatively, conscientious employees may seek out more challenging goals while also performing tasks in an organized and dilligent fashion because their perseverance and hard work has raised their performance on ordinary goals. Those two examples represent the classic unmeasured variables problem, a problem that occurs whenever an unmeasured variable is (1) correlated with a presumed cause, and (2) predictive of the presumed effect (James, 1980). Given the complexity of the phenomena studied in management research, the unmeasured variables problem is virtually unavoidable, with one exception. In laboratory research, the experimenter controls which units receive a particular level of the independent variable at a particular time. Such choices are made using random assignment, with assignment to conditions performed with the roll of a die, the use of a random number table, or some similar procedure. Because those choices will, by definition, lack any pattern, no unmeasured variable can be meaningfully correlated with the independent variable of interest. Thus, although there are still unmeasured variables, there is no longer an unmeasured variables problem (James, 1980). For this reason, random assignment has been termed “the great ceteris paribus” of causal inference (Cook & Campbell, 1979: 5; italic in original). Moreover, the fact that the experimenter controls the levels of the independent variable rules out the possibility that the outcome actually caused the predictor in a given study. For these reasons, and others described below, lab studies have been a vital component of the theory-centered research published in a number of journals. For the purposes of this review, lab studies are defined as studies involving undergraduate participants that occur in an environment that was created for research purposes. It is true that other combinations of samples and settings are possible. For example, what is often termed a “field experiment” places actual employees in an environment where randomly assigned conditions have been created. What might be termed a “student survey” examines undergraduates in an actual classroom environment. In practice, however, lab studies are much more common than either field experiments I would like to thank Duane Ireland, Mike Pratt, Dave Ketchen, Peter Bamberger, and Micki Kacmar for their helpful comments on a draft of this work. I would also like to thank Jessica Mueller for her assistance in the literature search. Academy of Management Journal 2008, Vol. 51, No. 4, 616–620.