Kano's model is a very useful tool to classify customer needs into different categories. It completely uses self-stated evaluations to classify the service quality. The disadvantages of self-stated evaluation are respondents often find it difficult to differentiate and respondents' answers may be influenced by social norms or political correctness. The derived evaluation approach uses a less direct way of uncovering the evaluations that are most reliable to reflect the respondents' view from the survey. The major drawback of the derived importance computed by multiple regression, structural equation modeling, or partial correlation is all based on linear assumption between each item and overall satisfaction. However, a non-linear effect between each item and overall satisfaction is often incurred in practice. To overcome this major drawback, a dual importance diagram based on generalized correlation is proposed to classify items into appropriate satisfaction factors by considering both linear and non-linear effects between items and overall satisfaction. A case of evaluating the service quality of a particular hospital is illustrated to show how this proposed dual importance diagram works to classify the service items into different types of Kano's categories. The result shows that using the generalized correction-based dual importance diagram is more practical in our case study.
All Science Journal Classification (ASJC) codes
- Computer Science (miscellaneous)