The Integration Model of Kano Model and Importance-Performance and Gap Analysis—Application of Mutual Information

Service quality research has traditionally focused either on identifying Kano two-dimensional quality categories or detecting service quality deficiencies. However, integrating these perspectives remains a challenge due to the Kano model’s nonlinear characteristics and the importance-performance and gap analysis (IPGA) model’s linear approach. This study proposes the Kano-IPGA (KIPGA) model, incorporating mutual information (MI) to bridge the gap between these two models. The KIPGA model first employs moderated regression analysis to classify service attributes into Kano’s quality categories. MI is then used to calculate the relative importance (RI), while relative performance (RP) is determined using the original IPGA approach. The results are mapped into the KIPGA strategic matrix, categorizing service attributes into eight management strategies. An empirical analysis of Taiwan’s online insurance systems demonstrates the model’s effectiveness in simultaneously identifying Kano categories and prioritizing service quality improvements. The findings reveal that critical improvement and enhanced improvement regions require immediate attention. The proposed KIPGA model offers a systematic approach for service quality management, providing decision-makers with a structured framework to allocate resources effectively and enhance customer satisfaction. This study contributes to service quality research by offering an integrated model that accounts for both linear and nonlinear quality assessment perspectives.

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Publication Details

Journal
Mathematics
Published
2025-05-28
DOI
https://doi.org/10.3390/math13111794
Citations
1
Primary Topic
Customer Service Quality and Loyalty
Type
article
Field-Weighted Citation Impact
2.76
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article

The Integration Model of Kano Model and Importance-Performance and Gap Analysis—Application of Mutual Information

Shu-Ping Lin, Ming-Chun Tsai
1 citations
Mathematics
Customer Service Quality and Loyalty
2.76
article

The Integration Model of Kano Model and Importance-Performance and Gap Analysis—Application of Mutual Information

Shu-Ping Lin, Ming-Chun Tsai
article en
1 citations

Abstract

Service quality research has traditionally focused either on identifying Kano two-dimensional quality categories or detecting service quality deficiencies. However, integrating these perspectives remains a challenge due to the Kano model’s nonlinear characteristics and the importance-performance and gap analysis (IPGA) model’s linear approach. This study proposes the Kano-IPGA (KIPGA) model, incorporating mutual information (MI) to bridge the gap between these two models. The KIPGA model first employs moderated regression analysis to classify service attributes into Kano’s quality categories. MI is then used to calculate the relative importance (RI), while relative performance (RP) is determined using the original IPGA approach. The results are mapped into the KIPGA strategic matrix, categorizing service attributes into eight management strategies. An empirical analysis of Taiwan’s online insurance systems demonstrates the model’s effectiveness in simultaneously identifying Kano categories and prioritizing service quality improvements. The findings reveal that critical improvement and enhanced improvement regions require immediate attention. The proposed KIPGA model offers a systematic approach for service quality management, providing decision-makers with a structured framework to allocate resources effectively and enhance customer satisfaction. This study contributes to service quality research by offering an integrated model that accounts for both linear and nonlinear quality assessment perspectives.

MathematicsVol. 13(11)
CTBC Business School (TW)
Openalex Percentile: Top 10%
Customer Service Quality and Loyalty
2.76
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The Integration Model of Kano Model and Importance-Performance and Gap Analysis—Application of Mutual Information — Shu-Ping Lin, Ming-Chun Tsai · Mathematics (2025) | TGRS Research Map | TGRS