While other applied sciences systematically distinguish between manipulation designs, organizational research does not. Herein, we disentangle distinct applications that differ in how the manipulation is deployed, analyzed, and interpreted in support of hypotheses. First, we define two archetypes: treatments, experimental designs that expose participants to different levels/types of a manipulation of theoretical interest, and primes, manipulations that are not of theoretical interest but generate variance in a state that is. We position these and creative derivations (e.g., interventions and invariant prompts) as specialized tools in our methodological kit. Second, we review 450 manipulations published in leading organizational journals to identify each type's prevalence and application in our field. From this we derive our guiding thesis that while treatments offer unique advantages (foremost establishing causality), they are not always possible, nor the best fit for a research question; in these cases, a non-causal but accurate test of theory, such as a prime design, may prove superior to a causal but inaccurate test. We conclude by outlining best practices for selection, execution, and evaluation by researchers, reviewers, and readers.

中文翻译：

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组织研究中的操作：关于执行和解释从治疗到引物的设计


虽然其他应用科学系统地区分了操作设计，但组织研究却没有。在本文中，我们解开了不同的应用程序，这些应用程序在部署、分析和解释操作以支持假设的方式上有所不同。首先，我们定义了两种原型：治疗，使参与者暴露于不同层次/类型的理论兴趣操纵的实验设计，以及引物，不具有理论兴趣但在某种状态下产生差异的操作。我们将这些和创造性的推导（例如，干预和不变提示）定位为我们方法论工具包中的专用工具。其次，我们回顾了发表在领先组织期刊上的 450 种操作，以确定每种类型在我们领域的普遍性和应用。由此我们得出我们的指导论点，虽然治疗提供了独特的优势（首先确定因果关系），但它们并不总是可能的，也不是最适合研究问题的地方;在这些情况下，非因果但准确的理论检验（例如素数设计）可能优于因果但不准确的检验。最后，我们概述了研究人员、审稿人和读者选择、执行和评估的最佳实践。