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From Words to Numbers: How to Transform Qualitative Data into Meaningful Quantitative Results

  • Content Analysis
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Schmalenbach Business Review Aims and scope

Abstract

In proposing a procedure for transforming qualitative data into quantitative results, we address the manifold requests for discovery-oriented research in the business disciplines. We present a systematic classification of combined qualitative-quantitative research designs and argue in favor of the generalization model. We give guidelines for its implementation and provide a blueprint for systematically converting respondents’ words into numbers that can be used for further (statistical) analyses. We delimit and discuss the stages of unitization, categorization, and coding. We also raise quality issues and propose relevant quality criteria in the transformation process. In particular, we suggest the intercoder consistency-matrix for determining the incisiveness of categories developed through content analysis. Finally, we demonstrate in an exemplary study how the blueprint can be applied and highlight the benefits of the proposed research design.

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Authors and Affiliations

  1. Faculty of Business, Economics, and Statistics, University of Vienna, Bruenner Str. 72, A-1210, Vienna, Austria

    Katharina J. Srnka (Associate Professor of Marketing) & Sabine T. Koeszegi (Associate Professor of Organization and Planning)

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  1. Katharina J. Srnka
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  2. Sabine T. Koeszegi
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Correspondence to Katharina J. Srnka.

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The authors thank two anonymous reviewers for their valuable feedback.

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Srnka, K.J., Koeszegi, S.T. From Words to Numbers: How to Transform Qualitative Data into Meaningful Quantitative Results. Schmalenbach Bus Rev 59, 29–57 (2007). https://doi.org/10.1007/BF03396741

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