Embracing diversity through mixed methods research

European Journal of Information Systems (2013) 22, 251–256. doi:10.1057/ejis.2013.6 Mixed methods research – ‘the third methodological movement’ (Teddlie & Tashakkori, 2009) – appears to be one of those phenomena that attracts considerable interest but is rarely brought into practice, at least judging by the publications in major information systems (IS) outlets, where mixed methods studies represent only 3% of the published articles (Venkatesh et al, 2013). It is refreshing, however, to now see some increasing activity and acceptance of the approach vindicated by recent submissions to journals and conferences, in addition to recent publications (e.g. Venkatesh et al, 2013; Zachariadis et al, forthcoming). Mixed methods research is characterized by a combination of quantitative and qualitative methods within a single study. Johnson & Onwuegbuzie (2004, p. 17) define mixed methods research as ‘the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts or language into a single study’. The use of, and emphasis on, each of the two components may vary, although one often dominates. In the literature, a distinction is sometimes made between mixed methods research, which combines qualitative and quantitative methods, and multimethod research, which combines methods that may or may not share the same world-view (Venkatesh et al, 2013). A mixed method is therefore always a multimethod, but a multimethod is not necessarily a mixed method. The real strength of mixed methods is the possibility of developing meta-inferences based on a combination of qualitative and quantitative data and analysis (Venkatesh et al, 2013) – that is, developing an understanding of a phenomenon for which either approach in isolation would be insufficient. For example, a study of ‘opensourcing’ as a global sourcing strategy (Ågerfalk & Fitzgerald, 2008) developed a framework through a grounded analysis (based on qualitative interviews) followed by factor analysis (based on a quantitative survey). The framework comprised grounded categories corresponding to principal components. Parts of this framework could not be explained by the quantitative data alone but, by revisiting the qualitative analysis, a more complete understanding could be achieved. In the following, I outline an argument for mixed methods being potentially very useful in IS research, and indicate why you should consider sending your best mixed methods research to the European Journal of Information Systems (EJIS). In doing so, I will touch upon some of the philosophical and practical issues related to mixed methods and to our discipline. However, I do not go into detail about designing or conducting mixed methods studies; an up-to-date overview of and guidelines for conducting mixed methods research in IS are available elsewhere (Venkatesh et al, 2013).