engleski

A Critical Review of Techniques for Classifying Quality Attributes in the Kano Model

The purposes of this paper are: (i) to review the most commonly used approaches to the classification of quality attributes according to the Kano model ; (ii) to identify the theoretical/practical strengths and weaknesses of these techniques ; and (iii) to provide guidance for future research and managerial practice in this area. Based on an extensive review of the literature on the Kano model and the relevant marketing/management literature, five approaches (Kano’s method ; ‘penalty–reward contrast analysis’ ; ‘importance grid’ ; qualitative data methods ; and ‘direct classification’) are evaluated in terms of their validity and reliability for categorising attributes in the Kano model. Several illustrative examples provide empirical evidence for the theoretical arguments advanced in the study. Findings and implications: The Kano questionnaire and the direct- classification method are the only approaches that are capable of classifying Kano attributes in the design stage of a product/service. Penalty–reward contrast analysis (PRCA) is useful for assessing the impact of product/service attributes on overall satisfaction with a product/service, but its applicability to the classification of Kano attributes is questionable. The importance grid (IG) is not recommended for use with the Kano model. The critical incident technique and the analysis of complaints/compliments are valid for the Kano model, but have questionable reliability. The study also makes some important points about accurate semantic terminology in describing issues related to the Kano model. In particular, researchers should be aware that an attractive quality element (must-be quality element, respectively) might in fact be a dissatisfier (satisfier, respectively), due to significant conceptual differences between performance in terms of the Kano model (i.e. objective performance) and subjective performance perceptions.

Kano model; penalty–reward contrast analysis; importance grid; qualitative data methods; direct classification

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