ABSTRACT:
We discuss the cyclical nature of action research (AR) in information systems (IS) and contrast it with other research approaches commonly used in IS. Often those who conduct AR investigations build on their professional expertise to provide a valuable service to a client organization while at the same time furthering knowledge in their academic fields. AR is usually conducted using an interpretive research approach, but many doctoral IS students, as well as junior and senior IS researchers, are likely to be expected to conduct research in a predominantly positivist fashion, even as they are determined to conduct an AR study that builds on their professional expertise. We argue that these IS researchers can successfully employ AR in their investigations as long as they are aware of the methodological obstacles that they may face, and have the means to overcome them. The following key obstacles are discussed: low statistical power, common-method bias, and multilevel influences. We also discuss two important advantages of employing AR in positivist IS investigations, from a positivist perspective: AR’s support for the identification of omitted variables and J-curve relationships. The study’s contribution is expected to enhance our knowledge of AR and foster its practice.
Key words and phrases: action research, common-method bias, J-curve relationships omitted variables, positivist research, statistical power