Decoding tourist satisfaction for sustainable economic development: a multi-method configuration framework using online reviews

    Yong Qin Info
    Chaoguang Luo Info
    Zeshui Xu Info
    Xinxin Wang Info
    Marinko Škare Info
DOI: https://doi.org/10.3846/tede.2025.23251

Abstract

Online reviews are crucial to understanding tourist satisfaction (TSA) in the digital tourism era. This study deconstructs the factors leading to high TSA performance in reviews, offering guidance for long-term economic benefits for destinations and businesses. Building on the three-factor theory, we create a framework utilizing text mining, affective distribution computing, and fuzzy-set qualitative comparative analysis (fsQCA) to identify patterns driving high TSA. We employ topic modeling to extract destination attributes from reviews, quantifying their performance through affective distribution computing. An enhanced Kano model classifies tourist needs based on emotional expressions in reviews. We investigate how basic, performance and excitement attributes interact and influence TSA. Additionally, we apply the coupling coordination degree model (CCDM) to analyze attribute interconnections within configurations. Our results show that no single attribute leads to specific outcomes; relatively, high TSA results from a combination of attributes. This study identifies three normative causal recipes and is the first to clarify the complex interactions in satisfaction management within the three-factor theory framework, addressing a significant knowledge gap. Ultimately, our operational guidelines aim to sustain the economic vitality of the tourism industry.

First published online 14 July 2025

Keywords:

tourism economy, tourist satisfaction, three-factor theory, FsQCA, online reviews

How to Cite

Qin, Y., Luo, C., Xu, Z., Wang, X., & Škare, M. (2025). Decoding tourist satisfaction for sustainable economic development: a multi-method configuration framework using online reviews. Technological and Economic Development of Economy, 1-39. https://doi.org/10.3846/tede.2025.23251

Share

Published in Issue
July 14, 2025
Abstract Views
90

References

Aliedan, M. M., Sobaih, A. E. E., & Elshaer, I. A. (2021). Influence of cities-based entertainment on tourist satisfaction: Mediating roles of destination image and experience quality. Sustainability, 13(19), Article 11086. https://doi.org/10.3390/su131911086

Anderson, E. W., & Mittal, V. (2000). Strengthening the satisfaction-profit chain. Journal of Service Research, 3(2), 107–120. https://doi.org/10.1177/109467050032001

Angelov, D. (2020). Top2vec: Distributed representations of topics. Arxiv. https://doi.org/10.48550/arXiv.2008.09470

Balazs, J. A., & Velásquez, J. D. (2016). Opinion mining and information fusion: A survey. Information Fusion, 27, 95–110. https://doi.org/10.1016/j.inffus.2015.06.002

Bi, J.-W., Liu, Y., Fan, Z.-P., & Cambria, E. (2019a). Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model. International Journal of Production Research, 57(22), 7068–7088. https://doi.org/10.1080/00207543.2019.1574989

Bi, J.-W., Liu, Y., Fan, Z.-P., & Zhang, J. (2019b). Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews. Tourism Management, 70, 460–478. https://doi.org/10.1016/j.tourman.2018.09.010

Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation Journal of Machine Learning Research, 3(2003), 993–1022.

Brunner-Sperdin, A., Peters, M., & Strobl, A. (2012). It is all about the emotional state: Managing tourists’ experiences. International Journal of Hospitality Management, 31(1), 23–30. https://doi.org/10.1016/j.ijhm.2011.03.004

Chang, R. M., Kauffman, R. J., & Kwon, Y. (2014). Understanding the paradigm shift to computational social science in the presence of big data. Decision Support Systems, 63, 67–80. https://doi.org/10.1016/j.dss.2013.08.008

Chen, J., Becken, S., & Stantic, B. (2022). Assessing destination satisfaction by social media: An innovative approach using importance-performance analysis. Annals of Tourism Research, 93, Article 103371. https://doi.org/10.1016/j.annals.2022.103371

Chen, C., Zhang, C., & Xu, Z. (2024). Online reviews-driven Kano-QFD method for service design. IEEE Transactions on Engineering Management, 71, 8153–8165. https://doi.org/10.1109/TEM.2024.3387579

Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., & Kuksa, P. (2011). Natural language processing (almost) from scratch. Journal of Machine Learning Research, 12(2011), 2493–2537.

Cui, C., Wei, M., Che, L., Wu, S., & Wang, E. (2022). Hotel recommendation algorithms based on online reviews and probabilistic linguistic term sets. Expert Systems with Applications, 210, Article 118503. https://doi.org/10.1016/j.eswa.2022.118503

Das, R., Ahmed, W., Sharma, K., Hardey, M., Dwivedi, Y. K., Zhang, Z., Apostolidis, C., & Filieri, R. (2024). Towards the development of an explainable e-commerce fake review index: An attribute analytics approach. European Journal of Operational Research, 317(2), 382–400. https://doi.org/10.1016/j.ejor.2024.03.008

Dong, Q., Zhong, K., Liao, Y., Xiong, R., Wang, F., & Pang, M. (2023). Coupling coordination degree of environment, energy, and economic growth in resource-based provinces of China. Resources Policy, 81, Article 103308. https://doi.org/10.1016/j.resourpol.2023.103308

Dul, J. (2016a). Identifying single necessary conditions with NCA and fsQCA. Journal of Business Research, 69(4), 1516–1523. https://doi.org/10.1016/j.jbusres.2015.10.134

Dul, J. (2016b). Necessary condition analysis (NCA) logic and methodology of “necessary but not sufficient” causality. Organizational Research Methods, 19(1), 10–52. https://doi.org/10.1177/1094428115584005

Dul, J., van der Laan, E., & Kuik, R. (2020). A statistical significance test for necessary condition analysis. Organizational Research Methods, 23(2), 385–395. https://doi.org/10.1177/1094428118795272

Feng, Y., Gao, Y., Xia, X., Shi, K., Zhang, C., Yang, L., Yang, L., & Cifuentes-Faura, J. (2024). Identifying the path choice of digital economy to crack the “resource curse” in China from the perspective of configuration. Resources Policy, 91, Article 104912. https://doi.org/10.1016/j.resourpol.2024.104912

Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420. https://doi.org/10.5465/amj.2011.60263120

Fu, H., Xiao, Y., Mensah, I. K., & Wang, R. (2023). Exploring the configurations of learner satisfaction with moocs designed for computer science courses based on integrated LDA-QCA method. Education and Information Technologies, 29, 9883–9905. https://doi.org/10.1007/s10639-023-12185-7

Geremew, Y. M., Huang, W.-J., & Hung, K. (2024). Fuzzy-set qualitative comparative analysis as a mixed-method and analysis technique: A comprehensive systematic review. Journal of Travel Research, 63(1), 3–26. https://doi.org/10.1177/00472875231168619

Greckhamer, T. (2016). CEO compensation in relation to worker compensation across countries: The configurational impact of country-level institutions. Strategic Management Journal, 37(4), 793–815. https://doi.org/10.1002/smj.2370

Grootendorst, M. (2022). Bertopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv. https://doi.org/10.48550/arXiv.2203.05794

Gupta, S., Deodhar, S. J., Tiwari, A. A., Gupta, M., & Mariani, M. (2024). How consumers evaluate movies on online platforms? Investigating the role of consumer engagement and external engagement. Journal of Business Research, 176, Article 114613. https://doi.org/10.1016/j.jbusres.2024.114613

Han, X., Wang, Y., Yu, W., & Xia, X. (2023). Coupling and coordination between green finance and agricultural green development: Evidence from China. Finance Research Letters, 58, Article 104221. https://doi.org/10.1016/j.frl.2023.104221

Harkison, T. (2018). The use of co-creation within the luxury accommodation experience–myth or reality? International Journal of Hospitality Management, 71, 11–18. https://doi.org/10.1016/j.ijhm.2017.11.006

He, S.-F., Pan, X.-H., Wang, Y.-M., Zamora, D. G., & Martínez, L. (2024). A novel multi-criteria decision making framework based on evidential reasoning dealing with missing information from online reviews. Information Fusion, 106, Article 102264. https://doi.org/10.1016/j.inffus.2024.102264

Hernández-Rojas, R. D., & Huete Alcocer, N. (2021). The role of traditional restaurants in tourist destination loyalty. PLoS ONE, 16(6), Article e0253088. https://doi.org/10.1371/journal.pone.0253088

Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9(2), 132–140. https://doi.org/10.1086/208906

Kano, N. (1984). Attractive quality and must-be quality. Journal of the Japanese Society for Quality Control, 31(4), 147–156.

Kirilenko, A. P., & Stepchenkova, S. (2025). Facilitating topic modeling in tourism research: Comprehensive comparison of new AI technologies. Tourism Management, 106, Article 105007. https://doi.org/10.1016/j.tourman.2024.105007

Klaus, P. G. (1985). Quality epiphenomenon: The conceptual understanding of quality in face-to-face service encounters. In J. A. Czepiel, M. R. Solomon, & C. F. Surprenant (Eds.), The service encounter: Managing employee/customer interaction in service business (pp. 17–33). Lexington Books.

Kratzwald, B., Ilić, S., Kraus, M., Feuerriegel, S., & Prendinger, H. (2018). Deep learning for affective computing: Text-based emotion recognition in decision support. Decision Support Systems, 115, 24–35. https://doi.org/10.1016/j.dss.2018.09.002

Kumar, S., Sahoo, S., Ali, F., & Cobanoglu, C. (2023). Rise of fsQCA in tourism and hospitality research: A systematic literature review. International Journal of Contemporary Hospitality Management, 36(7), 2165–2193. https://doi.org/10.1108/IJCHM-03-2023-0288

Lee, C. K. H. (2022). How guest-host interactions affect consumer experiences in the sharing economy: New evidence from a configurational analysis based on consumer reviews. Decision Support Systems, 152, Article 113634. https://doi.org/10.1016/j.dss.2021.113634

Lee, C. K. H., Tse, Y. K., Leung, E. K. H., & Wang, Y. (2024). Causal recipes of customer loyalty in a sharing economy: Integrating social media analytics and fsQCA. Journal of Business Research, 181, Article 114747. https://doi.org/10.1016/j.jbusres.2024.114747

Liu, P., Zhu, B., Yang, M., & De Baets, B. (2024). High-quality marine economic development in China from the perspective of green total factor productivity growth: Dynamic changes and improvement strategies. Technological and Economic Development of Economy, 30(6), 1572–1597. https://doi.org/10.3846/tede.2024.22018

López-Guzmán, T., Uribe Lotero, C. P., Pérez Gálvez, J. C., & Ríos Rivera, I. (2017). Gastronomic festivals: Attitude, motivation and satisfaction of the tourist. British Food Journal, 119(2), 267–283. https://doi.org/10.1108/BFJ-06-2016-0246

Luo, H., Wang, H., & Wu, Y. (2024). Digital financial inclusion and tourism development. International Review of Economics & Finance, 90, 207–219. https://doi.org/10.1016/j.iref.2023.12.001

Lv, S., Xiao, A., Qin, Y., Xu, Z., & Wang, X. (2024). A decision framework for improving the service quality of charging stations based on online reviews and evolutionary game theory. Transportation Research Part A: Policy and Practice, 187, Article 104168. https://doi.org/10.1016/j.tra.2024.104168

Mak, A. H. N. (2017). Online destination image: Comparing national tourism organisation’s and tourists’ perspectives. Tourism Management, 60, 280–297. https://doi.org/10.1016/j.tourman.2016.12.012

Mittal, V., Ross Jr, W. T., & Baldasare, P. M. (1998). The asymmetric impact of negative and positive attribute-level performance on overall satisfaction and repurchase intentions. Journal of Marketing, 62(1), 33–47. https://doi.org/10.1177/002224299806200104

Murphy, L., Moscardo, G., Benckendorff, P., & Pearce, P. (2011). Evaluating tourist satisfaction with the retail experience in a typical tourist shopping village. Journal of retailing and Consumer Services, 18(4), 302–310. https://doi.org/10.1016/j.jretconser.2011.02.004

Oliver, R. L., Rust, R. T., & Varki, S. (1997). Customer delight: Foundations, findings, and managerial insight. Journal of Retailing, 73(3), 311–336. https://doi.org/10.1016/S0022-4359(97)90021-X

Pan, M., Li, N., & Huang, X. (2022). Asymmetrical impact of service attribute performance on consumer satisfaction: An asymmetric impact-attention-performance analysis. Information Technology & Tourism, 24, 221–243. https://doi.org/10.1007/s40558-022-00226-9

Pang, Q., Wang, H., & Xu, Z. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Sciences, 369, 128–143. https://doi.org/10.1016/j.ins.2016.06.021

Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set qualitative comparative analysis (fsQCA): Guidelines for research practice in information systems and marketing. International Journal of Information Management, 58, Article 102310. https://doi.org/10.1016/j.ijinfomgt.2021.102310

Pappas, N. (2021). COVID19: Holiday intentions during a pandemic. Tourism Management, 84, Article 104287. https://doi.org/10.1016/j.tourman.2021.104287

Park, J., & Lee, B. K. (2021). An opinion-driven decision-support framework for benchmarking hotel service. Omega, 103, Article 102415. https://doi.org/10.1016/j.omega.2021.102415

Park, Y., Fiss, P. C., & El Sawy, O. A. (2020). Theorizing the multiplicity of digital phenomena: The ecology of configurations, causal recipes, and guidelines for applying QCA. Management of Information Systems Quarterly, 44, 1493–1520. https://doi.org/10.25300/MISQ/2020/13879

Peng, L., Cui, G., Chung, Y., & Li, C. (2019). A multi-facet item response theory approach to improve customer satisfaction using online product ratings. Journal of the Academy of Marketing Science, 47, 960–976. https://doi.org/10.1007/s11747-019-00662-w

Perdomo-Verdecia, V., Garrido-Vega, P., & Sacristán-Díaz, M. (2024). An fsQCA analysis of service quality for hotel customer satisfaction. International Journal of Hospitality Management, 122, Article 103793. https://doi.org/10.1016/j.ijhm.2024.103793

Pereira-Moliner, J., Villar-García, M., Molina-Azorín, J. F., Tarí, J. J., López-Gamero, M. D., & Pertusa-Ortega, E. M. (2024). Using tourism intelligence and big data to explain flight searches for tourist destinations: The case of the costa blanca (Spain). Tourism Management Perspectives, 51, Article 101243. https://doi.org/10.1016/j.tmp.2024.101243

Pocchiari, M., Proserpio, D., & Dover, Y. (2024). Online reviews: A literature review and roadmap for future research. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2024.08.009

Poria, S., Cambria, E., Bajpai, R., & Hussain, A. (2017). A review of affective computing: From unimodal analysis to multimodal fusion. Information Fusion, 37, 98–125. https://doi.org/10.1016/j.inffus.2017.02.003

Pu, Z., Zhang, C., Xu, Z., & Wang, X. (2023). A fuzzy decision support model for online review-driven hotel selection by considering risk attitudes of customers. Journal of the Operational Research Society, 75(7), 1407–1420. https://doi.org/10.1080/01605682.2023.2249938

Qin, X., Chen, Y., Rao, Y., Xie, H., Wong, M. L., & Wang, F. L. (2021). A constrained optimization approach for cross-domain emotion distribution learning. Knowledge-Based Systems, 227, Article 107160. https://doi.org/10.1016/j.knosys.2021.107160

Qin, Y., Wang, X., & Xu, Z. (2022). Ranking tourist attractions through online reviews: A novel method with intuitionistic and hesitant fuzzy information based on sentiment analysis. International Journal of Fuzzy Systems, 24, 755–777. https://doi.org/10.1007/s40815-021-01131-9

Ragin, C. C. (2014). The comparative method: Moving beyond qualitative and quantitative strategies. University of California Press. https://doi.org/10.1525/9780520957350

Rassal, C., Correia, A., & Serra, F. (2023). Understanding online reviews in all-inclusive hotels servicescape: A fuzzy set approach. Journal of Quality Assurance in Hospitality & Tourism, 25(6), 1607–1634. https://doi.org/10.1080/1528008X.2023.2167761

Rihoux, B., & Ragin, C. C. (2009). Configurational comparative methods: Qualitative comparative analysis (QCA) and related techniques. Sage Publications. https://doi.org/10.4135/9781452226569

Roelen-Blasberg, T., Habel, J., & Klarmann, M. (2023). Automated inference of product attributes and their importance from user-generated content: Can we replace traditional market research? International Journal of Research in Marketing, 40(1), 164–188. https://doi.org/10.1016/j.ijresmar.2022.04.004

Sánchez-Franco, M. J., & Aramendia-Muneta, M. E. (2023). Why do guests stay at Airbnb versus hotels? An empirical analysis of necessary and sufficient conditions. Journal of Innovation & Knowledge, 8(3), Article 100380. https://doi.org/10.1016/j.jik.2023.100380

Scarpi, D., Confente, I., & Russo, I. (2022). The impact of tourism on residents’ intention to stay. A qualitative comparative analysis. Annals of Tourism Research, 97, Article 103472. https://doi.org/10.1016/j.annals.2022.103472

Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic methods for the social sciences: A guide to qualitative comparative analysis. Cambridge University Press. https://doi.org/10.1017/CBO9781139004244

Shin, S., & Nicolau, J. L. (2022). Identifying attributes of wineries that increase visitor satisfaction and dissatisfaction: Applying an aspect extraction approach to online reviews. Tourism Management, 91, Article 104528. https://doi.org/10.1016/j.tourman.2022.104528

Singh, J. P., Irani, S., Rana, N. P., Dwivedi, Y. K., Saumya, S., & Roy, P. K. (2017). Predicting the “helpfulness” of online consumer reviews. Journal of Business Research, 70, 346–355. https://doi.org/10.1016/j.jbusres.2016.08.008

Slevitch, L., & Oh, H. (2010). Asymmetric relationship between attribute performance and customer satisfaction: A new perspective. International Journal of Hospitality Management, 29(4), 559–569. https://doi.org/10.1016/j.ijhm.2009.09.004

Socher, R., Perelygin, A., Wu, J., Chuang, J., Manning, C. D., Ng, A. Y., & Potts, C. (2013). Recursive deep models for semantic compositionality over a sentiment treebank. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (pp. 1631–1642). Seattle, Washington, USA. Association for Computational Linguistics. https://doi.org/10.18653/v1/D13-1170

Steriopoulos, E., Khoo, C., Wong, H. Y., Hall, J., & Steel, M. (2024). Heritage tourism brand experiences: The influence of emotions and emotional engagement. Journal of Vacation Marketing, 30(3), 489–504. https://doi.org/10.1177/13567667231152930

Subramanian, A. M., Nishant, R., Van De Vrande, V., & Hang, C. C. (2022). Technology transfer from public research institutes to SME: A configurational approach to studying reverse knowledge flow benefits. Research Policy, 51(10), Article 104602. https://doi.org/10.1016/j.respol.2022.104602

Sun, M., Ryan, C., & Pan, S. (2015). Using Chinese travel blogs to examine perceived destination image: The case of New Zealand. Journal of Travel Research, 54(4), 543–555. https://doi.org/10.1177/0047287514522882

Sun, X., Lin, B., Chen, Y., Tseng, S., & Gao, J. (2019). Can commercialization reduce tourists’ experience quality? Evidence from Xijiang Miao village in Guizhou, China. Journal of Hospitality & Tourism Research, 43(1), 120–140. https://doi.org/10.1177/1096348017736569

Tuo, G., Feng, Y., & Sarpong, S. (2019). A configurational model of reward-based crowdfunding project characteristics and operational approaches to delivery performance. Decision Support Systems, 120, 60–71. https://doi.org/10.1016/j.dss.2019.03.013

Vayansky, I., & Kumar, S. A. P. (2020). A review of topic modeling methods. Information Systems, 94, Article 101582. https://doi.org/10.1016/j.is.2020.101582

Velikova, N., Slevitch, L., & Mathe-Soulek, K. (2017). Application of Kano model to identification of wine festival satisfaction drivers. International Journal of Contemporary Hospitality Management, 29(10), 2708–2726. https://doi.org/10.1108/IJCHM-03-2016-0177

Vu, H. Q., Li, G., & Law, R. (2019). Discovering implicit activity preferences in travel itineraries by topic modeling. Tourism Management, 75, 435–446. https://doi.org/10.1016/j.tourman.2019.06.011

Wang, F., Liu, Z., Shang, S., Qin, Y., & Wu, B. (2019). Vitality continuation or over-commercialization? Spatial structure characteristics of commercial services and population agglomeration in historic and cultural areas. Tourism Economics, 25(8), 1302–1326. https://doi.org/10.1177/1354816619837129

Wang, X., Dong, Q., & Zhang, B. (2022). Analytical framework and empirical study of user needs for online reviews based on Kano model. Information Studies:Theory & Application, 45(02), 160–167.

Wang, R., Wu, C., Wang, X., Xu, F., & Yuan, Q. (2023). E-tourism information literacy and its role in driving tourist satisfaction with online travel information: A qualitative comparative analysis. Journal of Travel Research, 63(4), 904–922. https://doi.org/10.1177/00472875231177229

Wang, M. M., & Jia, Z. Y. (2024). Investigating the correlation between building fasade design elements and tourist satisfaction – Cases study of Italy and the Netherlands. Habitat International, 144, Article 103001. https://doi.org/10.1016/j.habitatint.2024.103001

Wattanacharoensil, W., Fakfare, P., Manosuthi, N., Lee, J.-S., Chi, X., & Heesup, H. (2024). Determinants of traveler intention toward animal ethics in tourism: Developing a causal recipe combining cognition, affect, and norm factors. Tourism Management, 100, Article 104823. https://doi.org/10.1016/j.tourman.2023.104823

Wu, X., Liao, H., Xu, Z., Hafezalkotob, A., & Herrera, F. (2018). Probabilistic linguistic multimoora: A multicriteria decision making method based on the probabilistic linguistic expectation function and the improved borda rule. IEEE Transactions on Fuzzy Systems, 26(6), 3688–3702. https://doi.org/10.1109/TFUZZ.2018.2843330

Wu, X., & Liao, H. (2021). Modeling personalized cognition of customers in online shopping. Omega, 104, Article 102471. https://doi.org/10.1016/j.omega.2021.102471

Wu, J., Chen, J., Yang, T., & Zhao, N. (2024a). How to stay competitive: An innovative concept to assess the business competitiveness using online restaurant reviews. International Journal of Hospitality Management, 122, Article 103836. https://doi.org/10.1016/j.ijhm.2024.103836

Wu, J., Zhao, N., & Yang, T. (2024b). Wisdom of crowds: Swot analysis based on hybrid text mining methods using online reviews. Journal of Business Research, 171, Article 114378. https://doi.org/10.1016/j.jbusres.2023.114378

Xiao, R., Yu, X., Xiang, T., Zhang, Z., Wang, X., & Wu, J. (2021). Exploring the coordination between physical space expansion and social space growth of China’s urban agglomerations based on hierarchical analysis. Land Use Policy, 109, Article 105700. https://doi.org/10.1016/j.landusepol.2021.105700

Xu, X. (2022). A growing or depreciating love? Linking time with customer satisfaction through online reviews. Information & Management, 59(2), Article 103605. https://doi.org/10.1016/j.im.2022.103605

Xu, X., & Li, Y. (2016). The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text mining approach. International Journal of Hospitality Management, 55, 57–69. https://doi.org/10.1016/j.ijhm.2016.03.003

Yan, X., Guo, J., Lan, Y., & Cheng, X. (2013). A biterm topic model for short texts. Proceedings of the 22nd International Conference on World Wide Web, 1445–1456. ACM Digital Library. https://doi.org/10.1145/2488388.2488514

Yang, G., Bai, X., & Yang, S. (2023a). Analysis strategy configurations in risk taking using fuzzy set qualitative comparative analysis model. Technological and Economic Development of Economy, 29(3), 981–1004. https://doi.org/10.3846/tede.2023.18779

Yang, T., Wu, J., & Zhang, J. (2023b). Knowing how satisfied/dissatisfied is far from enough: A comprehensive customer satisfaction analysis framework based on hybrid text mining techniques. International Journal of Contemporary Hospitality Management, 36(3), 873­–892. https://doi.org/10.1108/IJCHM-10-2022-1319

Zhang, C., Xu, Z., Gou, X., & Chen, S. (2021a). An online reviews-driven method for the prioritization of improvements in hotel services. Tourism Management, 87, Article 104382. https://doi.org/10.1016/j.tourman.2021.104382

Zhang, T., Yin, P., & Peng, Y. (2021b). Effect of commercialization on tourists’ perceived authenticity and satisfaction in the cultural heritage tourism context: Case study of Langzhong ancient city. Sustainability, 13(12), Article 6847. https://doi.org/10.3390/su13126847

Zhang, M., Zhao, L., Zhang, Y., Liu, Y., & Luo, N. (2021c). Effects of destination resource combination on tourist perceived value: In the context of Chinese ancient towns. Tourism Management Perspectives, 40, Article 100899. https://doi.org/10.1016/j.tmp.2021.100899

Zhang, F., Wang, F., Yao, S., & Fu, F. (2023). High-speed rail and tourism expansion in China: A spatial spillover effect perspective. Technological and Economic Development of Economy, 29(6), 1753–1775. https://doi.org/10.3846/tede.2023.19813

Zhang, C., Cheng, X., Li, K., & Li, B. (2024). Hotel recommendation mechanism based on online reviews considering multi-attribute cooperative and interactive characteristics. Omega, 130, Article 103173. https://doi.org/10.1016/j.omega.2024.103173

Zhao, M., Zhang, C., Hu, Y., Xu, Z., & Liu, H. (2021). Modelling consumer satisfaction based on online reviews using the improved Kano model from the perspective of risk attitude and aspiration. Technological and Economic Development of Economy, 27(3), 550–582. https://doi.org/10.3846/tede.2021.14223

Zhao, M., Liu, M., Xu, C., & Zhang, C. (2023). Classifying travellers’ requirements from online reviews: An improved Kano model. International Journal of Contemporary Hospitality Management, 36, 91–112. https://doi.org/10.1108/IJCHM-06-2022-0726

Zhou, Y., Xue, H., & Geng, X. (2015). Emotion distribution recognition from facial expressions. Proceedings of the 23rd ACM International Conference on Multimedia, 1247–1250. ACM Digital Library. https://doi.org/10.1145/2733373.2806328

View article in other formats

CrossMark check

CrossMark logo

Published

2025-07-14

Issue

Section

Articles

How to Cite

Qin, Y., Luo, C., Xu, Z., Wang, X., & Škare, M. (2025). Decoding tourist satisfaction for sustainable economic development: a multi-method configuration framework using online reviews. Technological and Economic Development of Economy, 1-39. https://doi.org/10.3846/tede.2025.23251

Share