Qualitative data analysis, which will be referred in the latter contexts as QDA, is defined by Lewins et al. (2010) as a range of processes “whereby we move from the qualitative data that have been collected into some form of explanation, understanding or interpretation” of the people, phenomenon and the situations that have been investigated. Intending to assist the readers to have a deeper understanding of QDA, the author would firstly define qualitative research. Qualitative research, as oppose to quantitative research, is commonly seen as a naturalistic and interpretative approach that emphasises on words rather than numbers (Bryman and Bell, 2011), relies on textual data rather than numerical data (Schwandt, 2010, cited Tavalaei and Taib, 2010).
Aiming to explore the “deep meaning”, “inside view” and “initial causes” underneath the surface of human behaviours (Sechrest and Sidani, 1995, cited Velez, 2011), qualitative researchers do not believe in a universal truth (Newby, 2010). Accordingly, qualitative data are mainly being collected through the several predominant methods, including, in-depth interview, semi-structured interviews, focus groups, review of existing documents (Locke, Silverman and Spirduso, 2010; Creswell,2009; Marshall and Rossman,1999, cited in Thomas et al., 2011). Therefore, compared to quantitative data, qualitative data appears to be lengthy. Moreover, the process of its analysis demands intensive reading, understanding and interpretation that can only be carried out by human beings (Lewins et al., 2010). Due to its reliance on unstructured textual material that are mainly derived from interviews and participant observation in forms of transcripts and notes, qualitative data, are not straightforward to analyse (Bryman and Bell, 2011). Unlike quantitative data, no clear-cut rules have been developed so far to govern QDA (Marshall and Rossman, 2011). What enhances the difficulty of data analysis is that, collection of qualitative data usually leads to rapid accumulation of a sheer amount of cumbersome data.
Lewins et al. (2010) suggest that QDA in general is commonly considered as a procedure based on an interpretative philosophy. Nonetheless, in order to select the most appropriate and suitable analytical approach, which will eventually lead to a more rigorous research and a more effective way of communicating the findings; the author would stress the importance for researchers of understanding on what basis is each type of QDA is justified. It is necessary for the author to clarify that even though only one approach will be discussed and elaborated in greater details below, there are numerous sub-sets of various QDA methods, including analytic induction and grounded theory and more. However, to serve the purpose of this article, the author would emphasise on grounded theory as it is regarded by far as the most prominent and influential QDA approach.
Grounded theory is firstly developed by Strauss and Glaser (1967, cited Bryman and Bell, 2011). The approach has experienced several subtle changes, therefore, the author would explain it in its most recent incarnation. Grounded theory, according to Strauss and Corbin (1998, Bryman and Bell, 2011), is theory that is generated from the systematic process of data collection and data analysis. They highlight the crucial feature is that data collection, data analysis and generation of the ultimate theory stand in close relationship to each other (Ibid). In other words, what seperates grounded theory from other approaches are two significant characteristics. First of all, grounded theory approach is iterative. Thus, processes of data collection and analysis occur simultaneously. This statement has been further supported by Bryman and Bell (2011) saying that in grounded theory approach, “data collection and analysis proceed in tandem”. Secondly, emerging concepts, categories and eventual theories (as results are generated) are derived from data, meaning that results are inherent in the database itself, awaiting researchers to reveal these. However, an opposite opinion is proposed by Charmaz (2000). He defends that the developments of categories, concepts and “theoretical level of an analysis” is completed through the process of researchers questioning the data and interacting within the research field. As Strauss and Corbin (1990, cited Tavalaei and Taib, 2010) put it, coding is one of the most significant activity in grounded theory. It involves labelling the components that appear to be of vital theoretical significance during the revision of transcripts and documents (Fisher, 2010; Ritchie et al., 2013). Chairman (2000), therefore, stresses that researchers interpretations of data shapes the codes generated, which are highly relevant to the eventual outcome. In addition, he further criticises Strauss and Glaser (1967 cited Ritchie et al., 2013) and Strauss and Corbin (1998, cited Tavalaei and Taib, 2010) about the idea of isolating the influences of social actors implied on the results and revealing a reality on its own. Cited in Bryman and Bell (2011), it is certainly not unfair to propose that Strauss, Glaser and Corbin, have neglected researcher’s role and its influential impacts in the process of knowledge generation. Therefore, the author suggest that grounded theory could also be considered as based on interpretative philosophy. Nevertheless, Bummer (1979, cited Fisher et al., 2010), questions the feasibility of a generative theoretical approach to generate accurate results. Due to the fact that it is generally agreed that one’s view, one’s perception, one’s interpretation of the world, is filtered through various factors. For instance, life experience and social environment. He therefore registers several limitations as the outcome of such approach, which is highly dependent to how researchers interpret data.
Despite its prevalence of being the most widely spread and used general strategy in QDA, generated theory approach, as any other methods, has its flaws to be fixed and challenges to overcome. Regardless which approach is to be chosen, as a researcher, being able to identify the fundamental basis that justifies an approach enables the researcher to stay conscious and aware of the possible limitation of the chosen approach, to avoid or even compensate the weakness throughout the research process and to eventually accomplish a more comprehensive and accurate outcome.
References:
Bryman, A. (2012) Social Research Methods. 4th ed. Oxford: Oxford University Press.
Bryman, A. and Bell, E. (2011) Business Research Methods. 3rd ed. Oxford: Oxford University Press.
Fisher, C., Buglear, J., Lowry, D., Mutch, A. and Tansley, C. (2010). Researching and Writing a Dissertation: An essential guide for business students. 3rd ed. England: Prentice Hall.
Lewins, A. Taylor, C. and Gibbs, G. R. (2010).What is Qualitative Data Analysis (QDA)? http://onlineqda.hud.ac.uk/ [Accessed 01 November 2015].
Marshall, C. and Rossman, G. B. (1999) Designing Qualitative Research. 3rd ed. London: SAGE Publications.
Marshall, C. and Rossman, G. B. (2011) Designing Qualitative Research. 5th ed. Los Angeles: SAGE Publications.
Riley, M., Wood, R. C., Clark, M. A., Wilkie, E., and Szicas, E. (2004). Researching and Writing Dissertations in Business and Management. London: Thomson Learning.
Ritchie, J. and Lewis, J. ed. (2003) Qualitative Research Practice: A Guide for Social Science Students and Researchers. SAGE Publications Ltd. Available from: http://www.sagepub.in/[Accessed 02 November 2015].
Ritchie, J., Lewis, J., Nicholls, C. M. and Ormston, R. (2013) Qualitative Research Practice: A Guide for Social Science Students and Researchers. Los Angeles: SAGE Publications. Available from: http://www.sagepub.com [Accessed 03 November 2015].
Silverman, D. (2010) Doing Qualitative Research. 3rd ed. London: SAGE Publications.
Tavalaei, M. and Taib, M. (2010). A General Perspective on Role of Theory in Qualitative Research. The Journal of International Social Research, 3 (11), 570 – 577. Available from: http://www.sosyalarastirmalar.com [Accessed 03 November 2015].
Velez, A. M., (2015) Evaluating Research Methods: Assumptions, Strengths, and Weaknesses of Three Educational Research Paradigms. Available from: http://www.unco.edu [Accessed 03 November 2015].
