Identifying potential barriers to total quality management using principal component analysis and correspondence analysis

Most quality management researchers make inadequate use of statistical techniques, especially multivariate statistical methods. Applies two multivariate analysis techniques, principal component analysis (PCA) and correspondence analysis (CA), to analyse potential barriers to total quality management (TQM) implementation in Hong Kong’s service and manufacturing industries. Describes and demonstrates the applicability of these techniques as analysis tools for quality researchers and practitioners. Conducts PCA on a set of survey data and produces four orthogonal dimensions to potential barriers to TQM implementation, then applies CA in order to corroborate the findings of PCA. In addition, CA provides a simultaneous graphical representation of the data organized under different categories which shows how the potential barriers relate to one another and to the different types of industry.