A Guide for Novice Researchers on Experimental and Quasi-Experimental Studies in Information Systems Research

The main focus of this informative article is to bring attention to experimental research in the field of information systems, especially for novice researchers such as doctoral students. In the past three decades, information systems research has been heavily focused on theoretical model development and testing using survey-based methodology. However, criticism on such an approach has been prevalent. Experimental research has been used extensively in the ‘hard’ sciences and has provided a solid foundation for advancement in those fields. Incorporating a greater emphasis on experimental studies in information systems research is a route to similar advancements in that domain. Although this paper presents little new information, it attempts to make the wealth of existing information on experiments and quasi-experiments usable by the novice researcher. As such, we start by defining the term experiment and argue for its importance in the context of information systems research. We then discuss three key categories of experimental design: lab-experiments, quasi-experiments, and factorial design experiments. In each of the key experimental categories, we provide examples of common type(s) of design. Within the lab-experiment, we explore pretest-posttest with control group and Solomon fourgroup designs. In the quasi-experiment, we discuss nonrandomized pretest-posttest control group design, control-group time series design, and multiple baseline design. We examine factorial design with a discussion of the ex-post facto type of experiment. We conclude the paper with discussions about importance of increased use of experimental research in information systems and it’s relevancy to practice and advancement of knowledge.