Integrating LDA thematic model, FCE, and QFD methods for consumer-centered visual planning of the creative tourism destination: a macrosystem decision approach

Satisfying the consumer needs of tourism users is the key to the success of creative tourism destinations in landscape shaping, project design, and tourism operation. However, existing research on tourist needs mostly relies on expert experience and often stops at establishing evaluation results, lacking a systematic mechanism for translating user needs into implementation design. This study, however, synthesizes the perspectives of professionals and space users and innovatively proposes a macro-systematic decision-making approach that combines the LDA(Latent Dirichlet Allocation) thematic model, FCE(Fuzzy comprehensive evaluation), and QFD (Quality-function deployment) theory to ensure that the visual quality planning of tourism landscapes is closer to the aesthetic expectations of actual users. The feasibility of the research method was tested by analyzing 1056 social media comments and 237 questionnaires from a famous Chinese creative tourism venue (798 Art District) to determine the priority of design feature planning, thus improving the satisfaction of the tourist experience. The results show that more room for improvement is needed in terms of aesthetics, fun, creativity, and comfort of creative tourism venues in China. Relevant professionals should pay attention to attracting more potential consumers and enhancing their visual experience evaluation through the construction of features such as novelty, uniqueness, history, openness, and diversity in creative tourism destinations. The results of this study not only enrich the practical application of the theory of mass-functional configuration but also provide an important reference for how art can be involved in urban public space to enrich the evaluation of the tourism experience.

Text 117766.pdf - Accepted Version Restricted to Repository staff only until June 2027. Download (1MB) | Request a copy Official URL or Download Paper: https://www.sciencedirect.com/science/article/pii/...

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