USE OF IRAMUTEQ FOR CONTENT ANALYSIS BASED ON DESCENDING HIERARCHICAL CLASSIFICATION AND CORRESPONDENCE FACTOR ANALYSIS

Abstract

Objective: To present content analysis based on descending hierarchical classification and factorial correspondence analysis as complementary and sequential techniques, with possible application in the area of innovation management. Method: Content analysis based on Computer-Aided Text Analysis (CATA) techniques using the IRAMUTEQ software Originality/Relevance: The research paradigm usually influences the researcher's own knowledge bases and domain methodologies. Manual text analysis can eventually be attributed to the interpretivist paradigm and CATA techniques can eventually be attributed to the post-positivist paradigm, however, there seems to be no reason to make this distinction. Results: Presentation of a framework that demonstrates the technological choices of the most innovative companies in the world (Google, Apple and Amazon), common and different choices, among them. Theoretical/methodological contributions: Development of a method for analyzing the technological choices of the most innovative companies in the world, applying content analysis based on descending hierarchical classification and factorial analysis of correspondence in a sequential and complementary way. Social / management contributions: Decision-making for innovation management can be revised according to the technological choices presented. Competitive advantage has distinctiveness by nature. We demonstrate that it is not a problem to master the same technologies, that is, companies can have similar technological domains and still have different marketing approaches.