Building an information system is a difficult task, partly due to the problem of ascertaining the requirements of the intended users, but also because of the complexity of the large number of human-machine interactions (Tatnall & Davey, 2005). This complexity is reflected in the difficulty of building these systems to operate free from error and to perform as intended. The dictionary defines innovation as “the alteration of what is established; something newly introduced” (Macquarie Library, 1981 p. 914). As the introduction or improvement of an information system in an organisation necessarily involves change, information systems research often involves research into technological innovation.
Background: Information Systems As A Socio-Technical Discipline
The discipline of information systems (IS) is concerned with the ways people build and use computer-based systems to produce useful information and so has to deal with issues involving both people and machines; with the multitude of human and non-human entities that comprise an information system (Tatnall, 2003). Information systems is neither merely a technical discipline nor a social one, but one that is truly socio-technical. Researchers in information systems face the problem of how to handle complexities due to interconnected combinations of computers, peripherals, procedures, operating systems, programming languages, software, data and many other inanimate objects; how they all relate to humans and human organisations, and how humans relate to them (Longenecker, Feinstein, Couger, Davis, & Gorgone, 1994).
This paper will outline a socio-technical approach, based on actor-network theory (ANT), to researching how people interact with and use information systems (Tatnall & Gilding, 1999; Tatnall 2003; Tatnall & Pliaskin, 2005). In actor-network theory the key is in using an approach that is neither purely social nor purely technical, but socio-technical.
Qualitative Research Traditions in Information Systems
Each field of academic inquiry is characterised by its own preferred and commonly used research approaches and traditions. In information systems research Myers (1997) outlines four qualitative traditions as being particularly significant: case study research, ethnography, grounded theory and action research.
Case study research is the most commonly used qualitative approach in information systems. As IS research topics commonly involve the study of organisational systems, a case study approach is often appropriate. Ethnography has grown in prominence as a suitable approach to information systems research after work such as that undertaken by Suchman (1987) and Zuboff (1988). It has been used especially in research where the emphasis is upon design, computer-supported cooperative work, studies of Internet and virtual communities, and information-related policies (Star, 1995). Grounded theory is an “an inductive, theory discovery methodology” (Martin & Turner, 1986) that seeks to develop theory that is grounded in data that is systematically gathered and analysed and involves “continuous interplay” between data and analysis (Myers, 1997). Orlikowski (1993) argues that in information systems research situations involving organisational change, a grounded theory approach can be useful as it allows a focus on “contextual and processual” elements as well as on the actions of key players.
Action research has been described as proceeding in a spiral of steps where each step consists of planning, action and evaluation of the result of the action. It is seen as aiming “... to contribute both to the practical concerns of people in an immediate problematic situation and to the goals of social science by joint collaboration within a mutually acceptable ethical framework.” (Rapoport, 1970, p. 499). A variant of action research that is slowly gaining acceptance in information systems is soft systems methodology (SSM), developed by Peter Checkland and his colleagues (Checkland & Scholes, 1991). SSM attempts to give due recognition to both the human and technological aspects of a system. It acknowledges both human and non-human aspects of IS, but considers these to be entirely separate types of entities.