Self-organizing maps for categorical data: Application to an ISO 9000 accreditation assessment

Abstract

Self-Organizing Maps (SOM) usually deal with quantitative inputs, but an algorithm for handling qualitative variables as inputs, using a Multiple Correspondence Analysis (MCA) framework, has already been proposed (the KMCA). This work suggests an alternative approach, also using the MCA framework, but calculating the category profiles of a complete disjunctive table (in MCA nomenclature, the Indicator Matrix). An illustrative example of the method is shown, concerning the assessment of an ISO 9000 standard adoption in a general hospital in Rio de Janeiro, Brazil. Questionnaires of 369 respondents pertaining to this implementation were analyzed. From a 9x9 hexagonal SOM's grid, the main results suggested an indifferent and slightly positive perception of quality improvement between employees. Further studies repeating the strategy in the same institution should be carried out to evaluate the present state of the standard implantation.