Section four discusses the experiences, challenges and critical reflections of Researchers A and B as they engaged with their particular approach to qualitative data analysis. Section three follows with a discussion of two qualitative PhD studies. In section two, we provide an overview of the problematic nature of qualitative research and a review of the manual and technological approaches of data analysis available to researchers. The remainder of the paper is structured as follows.
In so doing, we hope that the critical reflections and insights provided will assist qualitative researchers in making important decisions around their approach to data analysis. The paper contributes to the limited literature which explores the comparative experiences of those undertaking qualitative data analysis using different approaches. The paper aims to address this gap by reporting on the experiences of two recently qualified doctoral students as they reflect on how they each approached the task of analysing qualitative data, Researcher A (second author) choosing a technological approach (NVivo) while Researcher B (third author) opted for a manual approach. However, while a substantial literature exists to guide the researcher in undertaking qualitative data analysis and in providing an understanding of the problematic nature of such analyses, a dearth of research reports on the comparative experiences of those undertaking qualitative data analysis using different approaches. Moreover, in an accounting context, a critical literature has emerged which attempts to elucidate the messy and problematic nature of qualitative data analysis (Ahrens & Chapman, 2006 Lee & Humphrey, 2006 Modell & Humphrey, 2008 O’Dwyer, 2004 Parker, 2003). While earlier literature focuses on the manual approach to qualitative data analysis (Bogdan & Bilken, 1982 Lofland, 1971), more recent literature provides support in the application of a range of technological approaches (alternatively referred to as Computer Assisted Qualitative Data Analysis Software or CAQDAS): e.g., Excel (Meyer & Avery, 2009) NVivo (Jackson & Bazeley, 2019) and ATLAS.ti (Friese, 2019).
Reflecting this, a substantial literature has developed to guide the researcher through the process of qualitative data analysis (e.g. Qualitative data analysis has a long history in the social sciences.
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