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Journal Article

Evidence Analysis using CAQDAS: Insights from a Qualitative Researcher  pp10-24

Marian Carcary

© Jan 2011 Volume 9 Issue 1, ECRM 2010 Special issue Part 2/Jan 2011, Editor: Ann Brown, David Douglas, Marian Carcary and Jose Esteves, pp1 - 87

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In data analysis the qualitative researcher seeks to produce a convincing explanation of the phenomena under investigation. Data analysis is an iterative process and requires reflection and interpretation on the researcher’s part on several levels. Interpretation suggests that there are no clear rules and that the researcher’s judgment, intuition and ability to highlight issues play an important part in the process. As a result, the issue as to how to analyse qualitative evidence is an area often poorly understood by researchers new to the interpretivist paradigm. The complexity of the data analysis process is increased due to the volume of evidence collected as part of a qualitative research study. The role of Computer Aided Qualitative Data Analysis Software (CAQDAS) in supporting this data analysis process is examined in this paper. It explores how CAQDAS can be used in facilitating the management of an extensive qualitative evidence base. CAQDAS enables researchers to manage qualitative data that would prove onerous through manual “pen and paper” methods. The paper examines the author’s use of the CAQDAS package N‑vivo in managing approximately 400 pages of single spaced interview transcripts resultant from a study on the evaluation of a new student ICT administrative system implementation in the Irish Institute of Technology (IoT) sector. This was an extensive empirical research study conducted across several case study sites and involved 49 informants and multiple sources of case study evidence. The objective was to develop a coherent cross‑case primary narrative of the system’s implementation from the evidence collected, reduce this to a set of key findings and ultimately develop a theoretical conjecture that provided fresh insights into the ICT investment evaluation process. The N‑vivo package served primarily as a support tool in managing the interview transcripts; in reflecting on the emerging themes; and in interpreting the body of evidence. It facilitated the identification of key points, the coding of key concepts that emerged from the body of evidence, and comparison between these concepts. It supported the later reclassification of concepts into a series of categories and sub categories; this helped to organise related concepts in relation to the overall research and facilitated greater understanding of the body of evidence. It supported the creation of memos to clarify emerging concepts and the categorisation of interview material to facilitate cross‑case analysis. Further, it facilitated analysis through for example relationship and model exploration. These features of N‑vivo played a vital role in producing a series of narrative accounts and ultimately the distillation of a new theoretical conjecture.


Keywords: qualitative data analysis, CAQDAS, N-vivo, coding, categorisation, memos, interpretivist research, research audit trail


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Journal Issue

Volume 9 Issue 1, ECRM 2010 Special issue Part 2/Jan 2011 / Jan 2011  pp1‑87

Editor: Ann Brown, David Douglas, Marian Carcary, Jose Esteves

View Contents Download PDF (free)


These papers dealt with the problems facing management researchers in a variety of ways. The keynote paper by Eileen Trauth discusses the issues that gender research raise for business. Three papers offer advice on qualitative data analysis, of which the paper by Carcary deals with methods of collection using IT, Ryan and Ogilvie identify an unusual data source and the third (Reiter et al) deals with the problem of choosing the appropriate research method. The two papers on research methodology address entirely different types of issue. The paper by Knowles and Michielsens gives all a fascinating insight into research methods that top journals apparently prefer. Iacono et al demonstrate how effective case study methods can be in developing theory. The two final papers address the subject of teaching research methods but again offer widely different views.


Keywords: autodriving, building theory from case studies, CAQDAS, case study research, categorisation, coding, critical theory, diversity, epistemology, feminism, gender and IT, gender differences, grounded theory, individual differences, interpretive research, interpretivist research, interviews, iterative process, marking rubrics, memos, N-vivo, phenomenology, photoelicitation, positivist research, primary data, projective prompts, qualitative, qualitative data analysis, qualitative research, quantitative, RAE 2008, REF 2013, research audit trail, research in large classes, research mentors, research method selection, research methodology, research methods, research outcomes, research training, social inclusion, teaching quantitative research, theory, theory of gender , Web 2, women and IT workforce,


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