Computer-Assisted Qualitative Research: An Overview

  • Yanto Chandra
  • Liang Shang


Computer-assisted qualitative data analysis (CAQDAS)-based qualitative research is both an art and a science. It relies on creativity and disciplined imagination (Weick KE, Acad Manag Rev 14(4):516–531, 1989) plus systematic, accurate, reliable, and iterative approaches. The primary challenge in qualitative research is to transform “hundreds of pages of field notes to a final report” (Miles MB, Huberman AM, Qualitative data analysis: an expanded source book. 2nd ed. Sage, Thousand Oaks, 1994, p. 281) in a rigorous, defendable, and auditable process. Qualitative research is not “a disorganized stumble through a mass of data, full of ‘insightful’ observations of a mainly anecdotal nature” (Silverman D, Interpreting qualitative data: methods for analysing talk, text, and interaction. Sage, London, 1993, p. 43). Rather, it is a disciplined yet creative way to bring the messy, rich and thick data into discernible patterns, concepts, processes or mechanisms. To move from an anecdotal to a systematic approach in doing qualitative research, researchers can utilize the advances in computing technologies in the form of CAQDAS and adopt one of the dominant qualitative approach methodologies (see Chaps.  1 and  3). In this chapter, we describe the rationale for using CAQDAS in qualitative research as a strategy to professionalize and legitimize qualitative research. We also compare RQDA –– the R package for Qualitative Data Analysis –– the CAQDAS we introduce here, with three of the most well-known CAQDAS software (One of the earliest CAQDAS tools was NUDIST (Richards T, & Richards L, Qual Sociol 14(4):307–324, 1991). Other types of CAQDAS software, which are proprietary based (requires license fees), are MAXqda, QDA Miner, Dedoose, and webQDA. Open source (free) CAQDAS software includes Aquad, Coding Analysis Toolkit (CAT), Transana, and WeftQDA, among others) programs, NVivo, ATLAS.ti, and MaxQDA.


CAQDAS Qualitative research RQDA ATLAS.ti NVivo MaxQDA 


  1. Babbie, E. (2002). The basics of social research (2nd ed.). Belmont: Thomson Learning.Google Scholar
  2. Bazeley, P. (2007). Qualitative data analysis with NVivo. London: Sage.Google Scholar
  3. Brown, W. A., & Guo, C. (2010). Exploring the key roles for nonprofit boards. Nonprofit and Voluntary Sector Quarterly, 39(3), 536–546.CrossRefGoogle Scholar
  4. Chandra, Y., & Shang, L. (2017). Unpacking the biographical antecedents of the emergence of social enterprises: A narrative perspective. Voluntas: International Journal of Voluntary and Nonprofit Organizations, 28(6), 2498–2529.CrossRefGoogle Scholar
  5. Colgrove, J., Abiola, S., & Mello, M. M. (2010). HPV vaccination mandates—Lawmaking amid political and scientific controversy. New England Journal of Medicine, 363(8), 785–791.CrossRefGoogle Scholar
  6. Creswell, J. W. (1998). Qualitative inquiry and research design: Choosing among five traditions. London: Sage.Google Scholar
  7. Denzin, N. K., & Lincoln, Y. S. (2005). Introduction: The discipline and practice of qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (3rd ed., pp. 1–32). Thousand Oaks: Sage.Google Scholar
  8. Fisher, D. R. (2013). Understanding the relationship between subnational and national climate change politics in the United States: Toward a theory of boomerang federalism. Environment and Planning C: Government and Policy, 31(5), 769–784.CrossRefGoogle Scholar
  9. Gilbert, L. S. (2002). Going the distance: ‘Closeness’ in qualitative data analysis software. International Journal of Social Research Methodology, 5(3), 215–228.CrossRefGoogle Scholar
  10. Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013). Seeking qualitative rigor in inductive research: Notes on the Gioia methodology. Organizational Research Methods, 16(1), 15–31.CrossRefGoogle Scholar
  11. Håkanson, C., Sahlberg-Blom, E., & Ternestedt, B. M. (2010). Being in the patient position: Experiences of health care among people with irritable bowel syndrome. Qualitative Health Research, 20(8), 1116–1127.CrossRefGoogle Scholar
  12. Lozano, R., & Huisingh, D. (2011). Inter-linking issues and dimensions in sustainability reporting. Journal of Cleaner Production, 19(2), 99–107.CrossRefGoogle Scholar
  13. MacMillan, K. (2005). More than just coding? Evaluating CAQDAS in a discourse analysis of news texts. Forum: Qualitative Social Research, 6(3), Art. 25. Retrieved from
  14. Micheli, P., & Neely, A. (2010). Performance measurement in the public sector in England: Searching for the golden thread. Public Administration Review, 70(4), 591–600.CrossRefGoogle Scholar
  15. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded source book (2nd ed.). Thousand Oaks: Sage.Google Scholar
  16. Molecke, G., & Pinkse, J. (2017). Accountability for social impact: A bricolage perspective on impact measurement in social enterprises. Journal of Business Venturing, 32(5), 550–568.CrossRefGoogle Scholar
  17. Moore, K. S. (2009). Gentrification in Black face?: The return of the Black middle class to urban neighborhoods. Urban Geography, 30(2), 118–142.CrossRefGoogle Scholar
  18. Morse, J. M., & Richards, L. (2002). Read me first for a user’s guide to qualitative methods. Thousand Oaks: Sage.Google Scholar
  19. Norgaard, M. (2011). Descriptions of improvisational thinking by artist-level jazz musicians. Journal of Research in Music Education, 59(2), 109–127.CrossRefGoogle Scholar
  20. Oswald, A. G. (2017). Improving outcomes with qualitative data analysis software: A reflective journey. Qualitative Social Work, 1473325017744860.
  21. Paulus, T. M., & Lester, J. N. (2016). ATLAS.ti for conversation and discourse analysis studies. International Journal of Social Research Methodology, 19(4), 405–428.CrossRefGoogle Scholar
  22. Richards, T., & Richards, L. (1991). The NUDIST qualitative data analysis system. Qualitative Sociology, 14(4), 307–324.CrossRefGoogle Scholar
  23. Roberts, K. A., & Wilson, R. W. (2002). ICT and the research process: Issues around the compatibility of technology with qualitative data analysis. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 3(2), Art. 23. Accessed 8 Jan 2013.Google Scholar
  24. Rodik, P., & Primorac, J. (2015, January). To use or not to use: Computer-assisted qualitative data analysis software usage among early-career sociologists in Croatia. In Forum: Qualitative social research (Vol. 16, No. 1). Berlin: Freie UniversitätGoogle Scholar
  25. Saillard, E. K. (2011). Systematic versus interpretive analysis with two CAQDAS packages: NVivo and MAXQDA. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 12(1).
  26. Silverman, D. (1993). Interpreting qualitative data: Methods for analysing talk, text, and interaction. London: Sage.Google Scholar
  27. Sinkovics, R. R., & Alfoldi, E. A. (2012). Progressive focusing and trustworthiness in qualitative research. Management International Review, 52(6), 817–845.CrossRefGoogle Scholar
  28. Sotiriadou, P., Brouwers, J., & Le, T. A. (2014). Choosing a qualitative data analysis tool: A comparison of NVivo and Leximancer. Annals of Leisure Research, 17(2), 218–234.CrossRefGoogle Scholar
  29. Strauss, A., & Corbin, J. M. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park: CA, Sage.Google Scholar
  30. Weber, P. R. (1985). Basic content analysis. Beverly Hills: Sage.Google Scholar
  31. Weick, K. E. (1989). Theory construction as disciplined imagination. Academy of Management Review, 14(4), 516–531.CrossRefGoogle Scholar
  32. Wickham, M., & Woods, M. (2005). Reflecting on the strategic use of CAQDAS to manage and report on the qualitative research process. The Qualitative Report, 10(4), 687–702.Google Scholar
  33. Woods, M., Paulus, T., Atkins, D. P., & Macklin, R. (2015). Advancing qualitative research using qualitative data analysis software (QDAS)? Reviewing potential versus practice in published studies using ATLAS.ti and NVivo, 1994–2013. Social Science Computer Review, 0894439315596311.Google Scholar
  34. Woods, M., Macklin, R., & Lewis, G. K. (2016). Researcher reflexivity: Exploring the impacts of CAQDAS use. International Journal of Social Research Methodology, 19(4), 385–403.CrossRefGoogle Scholar
  35. Wright, C., & Nyberg, D. (2017). An inconvenient truth: How organizations translate climate change into business as usual. Academy of Management Journal, 60(5), 1633–1661.CrossRefGoogle Scholar
  36. Yin, R. (1994). Case study research design and method. Beverly Hills: Sage.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yanto Chandra
    • 1
  • Liang Shang
    • 2
  1. 1.The Hong Kong Polytechnic UniversityHong KongHong Kong
  2. 2.City University of Hong KongHong KongHong Kong

Personalised recommendations