Use of the Principal Component Analysis (PCA) to Reduce Data Complexity in Qualitative Research: An Electro-Electronics Case Study

The objective of this paper was to show that the Principal Component Analysis (PCA) quantitative technique is capable of grouping complex variables in correlation groups from qualitative research. Thus, the study proposes a set of indicators for evaluating the production area in electro-electronic transformation industries in the city of Curitiba and Metropolitan Region, under aspects of environmental, social and economic sustainability. By employing the technique, it was observed that the questions were well formulated and truly measured what was proposed by the researchers. However, the way the variables were grouped needs adjustments to facilitate application of the questionnaire and the tabulation and analysis of data.