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QCA and the harnessing of unstructured qualitative data

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journal contribution
posted on 14.01.2020, 13:27 authored by R Nishant, M.N. Ravishankar
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.

History

School

  • Business and Economics

Department

  • Business

Published in

Information Systems Journal

Volume

30

Issue

5

Pages

845-865

Publisher

Wiley

Version

AM (Accepted Manuscript)

Rights holder

© John Wiley & Sons Ltd

Publisher statement

This is the peer reviewed version of the following article: NISHANT, R. and RAVISHANKAR, M.N., 2020. QCA and the harnessing of unstructured qualitative data. Information Systems Journal, 30(5), pp. 845-865, which has been published in final form at https://doi.org/10.1111/isj.12281. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Acceptance date

14/01/2020

Publication date

2020-02-28

Copyright date

2020

ISSN

1350-1917

eISSN

1365-2575

Language

en

Depositor

Prof Ravishankar Mayasandra Nagaraja. Deposit date: 14 January 2020

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