Putting the ‘theory’ back into grounded theory: guidelines for grounded theory studies in information systems

Abstract

Over the past decade, there has been increasing interest in the use of grounded theory in information systems research. Grounded theory is a qualitative research method that seeks to develop theory that is grounded in data systematically gathered and analysed. The purpose of this paper is to suggest guidelines for grounded theory studies in information systems. Our guidelines are based on a framework for theorizing in grounded theory studies that focuses on conceptualization and theory scope. Our hope is that the guidelines will help to raise the quality and aspirations of grounded theory studies in information systems.

Seeking Technical Debt in Critical Software Development Projects: An Exploratory Field Study

“…To build an understanding that is empirically grounded in the experience of professionals involved in software processes, a systematic data analysis process was conducted following the techniques suggested by the Glaserian Grounded Theory method (as cited in [37]). Using NVivo, we first performed a line-by-line open coding to closely examine fractures of data and to form categories of codes [37].…”

Cloud Computing: Adoption Issues for Sub‐Saharan African SMEs

“…The first definition of grounded theory as put forward by the proponents of the method Glaser and Strauss (1967) is -"the discovery of theory from data" (p. 1). It is a qualitative approach that has been has been variously described as positivist, interpretive or critical (Urquhart et al, 2010). Grounded theory has been used in the IS field; Orlikowski (1993), for example in investigating the use of Computer Aided Software Engineering tools in organizations.…”

“…Specifically, our research adopts the "Glaserian" or classical grounded theory approach with an interpretive viewpoint mainly because of its usefulness when studying relatively new areas (Stern, 1994) as is the case with cloud computing technology and its adoption in sub-Saharan Africa. More so, its coding procedure is simpler to use and closer to the original version (Urquhart et al, 2010). To determine an area of research in the broad topic of cloud computing, a literature review was conducted just enough to allow for the development of an interview guide for data collection and for interaction with participants in the study on the subject of cloud computing.…”

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

“…Third, interpretation of the data is prone to subjective interpretation bias, reducing the external validity of such research. While methodological guidelines have been offered to assist with these interpretative tasks (Urquhart et al, 2010), for example, by offering different types of codes (Miles & Huberman, 1994) or the use of coding teams (Fernandez, 2004), still, the subjective bias introduced by the researcher(s) cannot be fully alleviated.…”