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.

Importance-Performance Analysis(IPA) holds the assumption that the degree of physical fulfilment of quality attributes and the satisfaction of that attribute is linear. Therefore, IPA can be applied to the traditional one-dimensional attributes, not to other quality elements such as attractive or must-be attributes. To overcome this problem, several articles introduced methods that integrate IPA into the concept of two-dimensional quality. However, these articles are rather conceptual focusing on the differentiation of quality attributes depend on quality elements in IPA. To provide empirical evidence of the dependent relationship between attribute importance and satisfaction in IPA, this study introduces a weighted importance approach and provides validation method using Bacon(2003)’s priority model, a regression model. For this, the current research investigates 23 quality attributes of TV set for the results of Kano’s model, which are adopted from Kim et al.(2013), and conducted a survey of 118 university students for the results of the importance/satisfaction and improvement priority. The result of the proposed approach shows better result than those using the conventional way, based on R-square of the regression model.

Determining relative importance among many quality attributes under financial constraints is an important task. The weighted value of an attribute particularly in QFD, will influence on engineering characteristics and this will eventually influence the whole manufacturing process such as parts deployment, process planning, and production planning. Several scholars have suggested weighting formulas using CSC (Customer Satisfaction Coefficient) in the Kano model. However, previous research shows that the validity of the CSC approaches has not been proved systematically. The aim of the present study is to address drawbacks of CSC and to develop APC (Average Potential Coefficient), a new approach for weighting of quality attributes. For this, the current study investigated 33 quality attributes of e-learning and conducted a survey of 375 university students for the results of APC, the Kano model, and the direct importance of the quality attributes. The results show that the proposed APC is better than other approaches based on the correlation analysis with the results of direct importance. An analysis of e-leaning’s quality perceptions using the Kano model and suggestions for improving e-learning’s service quality are also included in this study.

Importance-Performance Analysis(IPA) is a well-known methodology to find the area for improvement. However, the IPA uses different strategies depending on an attribute falls in either 'Concentrate', 'Keep up', 'Possible overkill', or Low priority' quadrant. Problems can occur when attributes locate near the demarcation lines. To solve this problem of IPA, I suggest a modified importance-satisfaction analysis which integrates the Slack(1994)'s diagonal approach and Kano's ASC(Jang et al., 2012) into Yang(2003)'s Importance-Satisfaction model. For this, I investigated 21 smartphone's quality attributes, which adopted from Song and Park(2012)'s study, and conducted a survey of 280 university students for the results of Kano' model and the importance and satisfaction of the quality attributes. The results show that the proposed model enables the business managers to prioritize the quality attributes for improvement through the interpretation on the continuous diagonal line using the Kano's questionnaire only, without acquiring any additional survey for importance of attributes. Accordingly, it is expected that the newly proposed method will diminish the limitation of the existing IPA. In addition, to test the validity of the ASC, this study conducts a comparative analysis between the Kano's ASC and Tontini(2007)'s method to determine the relative importance of quality attributes.

The theory of two-dimensional quality, in particular, the Kano model that is developed by the analogy with the M-H theory, has been applied in various industry fields for more than three decades. Importance-Performance Analysis (IPA) assumes that the degree of physical fulfilment of quality attributes and the satisfaction of that attribute is linear, and therefore, it is applicable to the traditional one-dimensional attribute, not other quality types defined in the Kano’s model such as attractive or must-be attribute. To solve this problem, the current study suggests a new importance-satisfaction analysis using a modified IPA in accordance with the three quality types and a diagonal method introduced by Slack (1999) to determine improvement priority. For this, I investigated 19 smartphone’s quality attributes and conducted a survey of 334 university students for the results of Kano’s model, which adopted from Song and Park (2012)’s study, and the importance/satisfaction of the quality attributes and the results of the priority for improvement of the 19 quality attributes. The results show that the proposed I-S priority model is better than the conventional IPA based on the comparison results of determination coefficient from the regression analysis of the two models.