Building Transparency and Trustworthiness in Inductive Research Through Computer-Aided Qualitative Data Analysis Software. (January 2021)

• Record Type: Journal Article
• Authors: O'Kane, Paula; Smith, Anne; Lerman, Michael P.
• Is Part Of: Organizational research methods. Volume 24:Number 1(2021)
• Page Start: 104
• Page End: 139
• Publication Date: 2021-01
• Subjects: inductive research -- text coding -- Computer Aided Qualitative Data Analysis Software (CAQDAS) -- NVivo -- QDA Miner; Organization -- Research -- Methodology -- Periodicals; Organizational sociology -- Research -- Methodology -- Periodicals; Management -- Research -- Methodology -- Periodicals; 302.350721
• DOI: 10.1177/1094428119865016
• Languages: English
• ISSNs: 1094-4281

Abstract

Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in mystery. We suggest that computer-aided/assisted qualitative data analysis software (CAQDAS) can support qualitative researchers in their efforts to present their analysis and findings in a transparent way, thus enhancing trustworthiness. To this end, we propose, describe, and illustrate working examples of six CAQDAS building blocks, three combined CAQDAS techniques, and two coder consistency checks. We argue that these techniques give researchers the language to write about their methods and findings in a transparent manner and that their appropriate use enhances a research project's trustworthiness. Specific CAQDAS techniques are rarely discussed across an array of inductive research processes. Thus, we see this article as the beginning of a conversation about the utility of CAQDAS to support inductive qualitative research.