For several decades, attribute classification methods using the asymmetrical relationship between an attribute performance and the satisfaction of that attribute have been explored by numerous researchers. In particular, the Kano model, which classifies quality attributes into 5 elements using simple questionnaire and two-dimensional evaluation table, has gained popularity: Attractive, One-dimensional, Must-be, Indifferent, and Reverse quality. As Kano's model is well accepted, many literatures have introduced categorization methods using the Kano's evaluation table at attribute level. However, they applied different terminologies and classification criteria and this causes confusion and misunderstanding. Therefore, a criterion for quality classification at attribute level is necessary. This study is aimed to suggest a new attribute classification method that sub-categorizes quality attributes using 5-point ordinal point and Kano's two-dimensional evaluation table through an extensive literature review. For this, the current study examines the intrinsic and extrinsic problems of the well-recognized Kano model that have been used for measuring customer satisfaction of products and services. For empirical study, the author conducted a comparative study between the results of Kano's model and the proposed method for an e-learning case (33 attributes). Results show that the proposed method is better in terms of ease of use and understanding of kano's results and this result will contribute to the further development of the attractive quality theory that enables to understand both the customers explicit and implicit needs.

The two-way quality theory has been widely used as a method for classifying quality attributes for several decades. In particular, the Kano model that classifies attributes into not just conventional one-dimensional but must-be and attractive has gained popularity due to its applicability and ease of use. However, the wordings of the five alternatives in the Kano's questionnaire has been criticised for unclear meanings. This study proposes a new two-way model to classify attributes using 5-point Likert scale alternatives. For this, the current paper investigated a case of TV sets to examine how the proposed model works in comparison with the Kano model. The application results of the proposed model are different from the original one. The two-way model classifies quality attributes in more detail such as the “one-dimensional with an attractive tendency” attribute, which has a greater influence on satisfaction than dissatisfaction, the opposite “one-dimensional with a must-be tendency” attribute, and “highly one-dimensional” and “less one-dimensional” attributes. In this study, a potential satisfaction coefficient (PSC), a potential dissatisfaction coefficient (PDC), and an average potential coefficient (APC) to manage quality attributes are proposed and discussed for their utilization.