Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model
Understanding customer needs is of great significance to enhance service quality and competitive advantage. However, for the tourism industry, it is still unclear how to mine service improvement strategies from tourist-generated online reviews. This paper aims to develop a data-driven approach to co...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-07-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/11/7/345 |
| _version_ | 1797587392879656960 |
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| author | Kailin Zhou Zhong Yao |
| author_facet | Kailin Zhou Zhong Yao |
| author_sort | Kailin Zhou |
| collection | DOAJ |
| description | Understanding customer needs is of great significance to enhance service quality and competitive advantage. However, for the tourism industry, it is still unclear how to mine service improvement strategies from tourist-generated online reviews. This paper aims to develop a data-driven approach to conduct a fine-grained dimension analysis of customer satisfaction with tourism services. First, this paper uses Latent Dirichlet Allocation to explore the key dimensions of tourist satisfaction from online reviews. Next, based on the Chinese sentiment dictionary, tourists’ emotional attitudes towards each service dimension can be identified. Then, the backpropagation neural network is used to measure the complex relationship between tourists’ sentiment orientations towards different dimensions and their satisfaction. Finally, according to the improved Kano model, multi-dimensional attribute classification is realized to support the strategic analysis of tourism service quality improvement. The proposed method is empirically verified through a real tourism review dataset. The results exhibit the theoretical and practical implications of our method. |
| first_indexed | 2024-03-11T00:36:25Z |
| format | Article |
| id | doaj.art-a6e7ac6aa6794b89a91549493bb168c4 |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-11T00:36:25Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-a6e7ac6aa6794b89a91549493bb168c42023-11-18T21:35:55ZengMDPI AGSystems2079-89542023-07-0111734510.3390/systems11070345Analysis of Customer Satisfaction in Tourism Services Based on the Kano ModelKailin Zhou0Zhong Yao1School of Economics and Management, Beihang University, Beijing 100191, ChinaSchool of Economics and Management, Beihang University, Beijing 100191, ChinaUnderstanding customer needs is of great significance to enhance service quality and competitive advantage. However, for the tourism industry, it is still unclear how to mine service improvement strategies from tourist-generated online reviews. This paper aims to develop a data-driven approach to conduct a fine-grained dimension analysis of customer satisfaction with tourism services. First, this paper uses Latent Dirichlet Allocation to explore the key dimensions of tourist satisfaction from online reviews. Next, based on the Chinese sentiment dictionary, tourists’ emotional attitudes towards each service dimension can be identified. Then, the backpropagation neural network is used to measure the complex relationship between tourists’ sentiment orientations towards different dimensions and their satisfaction. Finally, according to the improved Kano model, multi-dimensional attribute classification is realized to support the strategic analysis of tourism service quality improvement. The proposed method is empirically verified through a real tourism review dataset. The results exhibit the theoretical and practical implications of our method.https://www.mdpi.com/2079-8954/11/7/345customer satisfactionKano modelonline reviewbackpropagation neural networkonline reviews |
| spellingShingle | Kailin Zhou Zhong Yao Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model Systems customer satisfaction Kano model online review backpropagation neural network online reviews |
| title | Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model |
| title_full | Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model |
| title_fullStr | Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model |
| title_full_unstemmed | Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model |
| title_short | Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model |
| title_sort | analysis of customer satisfaction in tourism services based on the kano model |
| topic | customer satisfaction Kano model online review backpropagation neural network online reviews |
| url | https://www.mdpi.com/2079-8954/11/7/345 |
| work_keys_str_mv | AT kailinzhou analysisofcustomersatisfactionintourismservicesbasedonthekanomodel AT zhongyao analysisofcustomersatisfactionintourismservicesbasedonthekanomodel |