Conducting credible and trustworthy research to inform managerial decisions is arguably the primary goal of business and management research. Research design, particularly the various types of experimental designs available, are important building blocks for advancing toward this goal. Key criteria for evaluating research studies are internal validity (the ability to demonstrate causality), statistical conclusion validity (drawing correct conclusions from data), construct validity (the extent to which a study captures the phenomenon of interest), and external validity (the generalizability of results to other contexts). Perhaps most important, internal validity depends on the research design’s ability to establish that the hypothesized cause and outcome are correlated, that variation in them occurs in the correct temporal order, and that alternative explanations of that relationship can be ruled out.
Research designs vary greatly, especially in their internal validity. Generally, experiments offer the strongest causal inference, because the causal variables of interest are manipulated by the researchers, and because random assignment makes subjects comparable, such that the sources of variation in the variables of interest can be well identified. Natural experiments can exhibit similar internal validity to the extent that researchers are able to exploit exogenous events creating (quasi-)randomized interventions. When randomization is not available, quasi-experiments aim at approximating experiments by making subjects as comparable as possible based on the best available information. Finally, non-experiments, which are often the only option in business and management research, can still offer useful insights, particularly when changes in the variables of interest can be modeled by adopting longitudinal designs.
Digital transformation in business and management research: An overview of the current status quo
