Quantitizing Qualitative Data from Semi-Structured Interviews: A Methodological Contribution in the Context of Public Policy Decision-Making

Abstract

This paper presents a methodology involving the transformation and conversion of qualitative data gathered from open, semi-structured interviews into quantitative data—a process known as quantitizing. In the process of analysing the factors behind the different levels of success in the implementation of entrepreneurship education programs in two case studies, we came up with a challenge that became the research question for this paper: “How can we best extract, organize and communicate insights from a vast amount of qualitative information?” To answer it, we developed a methodology involving codifying, labelling, attributing a score and creating indicators/indexes and a matrix of influence. This allowed us to extract more insights than would be possible with a mere qualitative approach (e.g., we were able to rank 53 categories in two dimensions, which would have been impossible based only on the qualitative data, given the high number of pairwise comparisons: 1378). While any work in the social sciences will always keep some degree of subjectivity, by providing an example of quantitizing qualitative information from interviews, we hope to contribute to the expansion of the toolbox in mixed methods research, social sciences and mathematics and encourage further applications of this type of approach.

Keywords

• quantitizing
• qualitative data
• aggregation of information
• matrix of influence
• mixed methods research