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Dainty, A R J, Bagilhole, B M and Neale, R H (1997) Analytical strategies for dealing with qualitative data in construction management research. In: Stephenson, P (Ed.), Proceedings 13th Annual ARCOM Conference, 15-17 September 1997, Cambridge, UK. Association of Researchers in Construction Management, Vol. 2, 484–93.

  • Type: Conference Proceedings
  • Keywords: data analysis; qualitative methodology; software
  • ISBN/ISSN: 0 86 339 759 X
  • URL: http://www.arcom.ac.uk/-docs/proceedings/ar1997-484-493_Dainty_Bagilhole_and_Neale.pdf
  • Abstract:
    There have been many recent calls for greater use of qualitative methods in construction management research, or at least for greater consideration to be given to the use of these methods if appropriate. However, for many researchers, particularly those using methods involving a very thorough, in depth data gathering exercise, and a fairly free-form approach to the collection instrument, this can lead to practical analytical problems through the generation of overwhelming amounts of qualitative data, and potential difficulties of working with a number of complex data sets. Increasingly, qualitative data is becoming far more diverse than simple transcribed information from interviews, and now encompasses a wide range of data from different sources, such as participant and non-participant observation field notes, video recordings and other graphical media. Whilst the combination of such data can greatly enhance qualitative and compliment quantitative studies, making sense of the emerging issues is difficult in terms of remaining organised, rigorous and systematic in the analysis. This paper discusses the problems inherent with qualitative data analysis, and describes the authors' experience of dealing with such data using the most popular computer package currently available to qualitative researchers; NUDIST TM. The research used NUDIST as part of an analytical strategy which combined several distinct data sets, including a substantial amount of semi-structured interview data. The paper concludes by discussing the particular relevance of such packages for construction management researchers, and other issues concerning qualitative data analysis.