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<p>Based on the KANO model, this paper identifies 27 basic demand items of digital rural services under service design thinking and constructs a rural digital service quality evaluation index system. At the same time, to determine the size of the impact of different demand items on the user’s satisfaction, the weights of all demand items are calculated using the improved AHP hierarchical analysis method. Finally, an empirical analysis is carried out to estimate the overall satisfaction of users based on the evaluation system, on the basis of which the service quality expectations and perceptions are compared respectively. The service quality is evaluated by using the theory of difference in expectations. A regression analysis is also carried out on the relationship between service quality and user satisfaction to explore the degree of influence of service design thinking on digital rural services. The results show that the overall satisfaction is between (3.8 and 4.2), and the mean difference in perceived expectation for each dimension is between −0.46 and −0.276. None of the p-values are significant. This study enriches the research theories and research methods in the field of service design thinking and digital village services and provides theoretical references and methods for subsequent analyses.</p>
</abstract>

Based on the KANO model, this paper identifies 27 basic demand items of digital rural services under service design thinking and constructs a rural digital service quality evaluation index system. At the same time, to determine the size of the impact of different demand items on the user’s satisfaction, the weights of all demand items are calculated using the improved AHP hierarchical analysis method. Finally, an empirical analysis is carried out to estimate the overall satisfaction of users based on the evaluation system, on the basis of which the service quality expectations and perceptions are compared respectively. The service quality is evaluated by using the theory of difference in expectations. A regression analysis is also carried out on the relationship between service quality and user satisfaction to explore the degree of influence of service design thinking on digital rural services. The results show that the overall satisfaction is between (3.8 and 4.2), and the mean difference in perceived expectation for each dimension is between −0.46 and −0.276. None of the p-values are significant. This study enriches the research theories and research methods in the field of service design thinking and digital village services and provides theoretical references and methods for subsequent analyses.

A Study on the Application of Service Design Thinking in Enhancing User Experience in Digital Villages - Based on KANO-AHP Modeling

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Based on the KANO model, this paper identifies 27 basic demand items of digital rural services under service design thinking and constructs a rural digital...

A Study on the Application of Service Design Thinking in Enhancing User Experience in Digital Villages - Based on KANO-AHP Modeling

Published Online: Jun 03, 2024

Page range: -

Received: Feb 23, 2024

Accepted: Apr 30, 2024

DOI: https://doi.org/10.2478/amns-2024-1375

Keywords
KANO model, AHP hierarchical analysis, Expectancy difference theory, Regression analysis, Digital rural services

© 2024 Zehui Li, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Study on the Application of Service Design Thinking in Enhancing User Experience in Digital Villages - Based on KANO-AHP Modeling

Published Online: Jun 03, 2024

Page range: -

Received: Feb 23, 2024

Accepted: Apr 30, 2024

DOI: https://doi.org/10.2478/amns-2024-1375

KeywordsKANO model, AHP hierarchical analysis, Expectancy difference theory, Regression analysis, Digital rural services

© 2024 Zehui Li, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
KANO model, AHP hierarchical analysis, Expectancy difference theory, Regression analysis, Digital rural services