QCA and the harnessing of unstructured qualitative data

Rohit Nishant*, M.N. Ravishankar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
52 Downloads (Pure)


This paper proposes qualitative comparative analysis (QCA) as a novel method to harness unstructured data sets such as publicly available reports and news articles. It shows how QCA and conventional qualitative IS research can complement each other. In particular, it demonstrates how qualitative IS research can combine typical qualitative coding techniques with a specific type of QCA, namely crisp-set QCA (csQCA). The paper illustrates how QCA offers qualitative IS research an innovative approach to explicate the combination of conditions associated with particular outcomes. Drawing on an empirical study of green IS, it showcases the potential of QCA to harness large unstructured qualitative material and generate deeper insights about emerging IS phenomena. The paper also highlights how QCA can contribute to the data collection and analysis stages of qualitative IS research.

Original languageEnglish
Pages (from-to)845-865
JournalInformation Systems Journal
Issue number5
Early online date28 Feb 2020
Publication statusPublished - 01 Sept 2020
Externally publishedYes


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