Study on the conservation and renewal of traditional rural tourism spaces: A perspective based on tourists' revisit intention

被引:0
|
作者
Tang, Huanchen [1 ]
Liu, Xiaodong [1 ]
Li, Junjie [1 ]
Wang, Hanyu [1 ]
机构
[1] Donghua Univ, Coll Fash & Design, Shanghai, Peoples R China
关键词
Traditional village; Revisit intention; Spatial planning; Structural equation modeling; Artificial neural network; DESTINATION IMAGE; PLACE ATTACHMENT; SATISFACTION; ANTECEDENTS; EXPERIENCE; BEHAVIOR; HERITAGE; MODEL;
D O I
10.1016/j.jclepro.2025.145184
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Traditional villages serve as a fundamental vehicle for rural tourism development in China. Understanding tourists' revisit intentions to traditional villages and their influencing factors is of great significance for the scientific planning of rural spaces and the sustainable development of rural tourism. This study innovatively constructs a novel hybrid analytical approach that integrates Latent Dirichlet Allocation (LDA), Structural Equation Modeling (SEM), and deep learning-based Artificial Neural Networks (ANN). This approach overcomes the explanatory limitations of traditional methods and, for the first time, enables the synergistic application of text sentiment analysis, latent variable relationship validation, and nonlinear pattern interpretation. The study proposes a four-dimensional driving mechanism for traditional villages: "spatial layout-architectural characteristics-architectural aesthetics-cultural experience." Based on a tourist survey conducted in three representative villages in Suzhou, China, the results from SEM and ANN indicate that village layout pattern (LP), architectural characteristics (AC), architectural aesthetics (AA), and cultural experience (CE) exert significant positive effects on tourists' revisit intention (RI). Moreover, tourists' positive attitude (PA) plays a mediating role in shaping their revisit intention. Furthermore, according to the standardized importance derived from the multilayer perceptron analysis, AC was identified as the most critical predictor (100%), followed by PA (71.207%), AA (52.632%), LP (43.963%), and CE (42.105%). Based on these findings, the study proposes three strategic recommendations: coordinating spatial layout, optimizing architectural characteristics, and enhancing tourists' positive attitudes. These strategies aim to improve land use efficiency in villages, foster deeper tourist engagement with traditional villages, and enhance cultural experiences and revisit intentions. Ultimately, these measures contribute to optimizing the landscape of tourism-oriented traditional villages, addressing contemporary challenges in sustainable rural development. This research not only provides a novel theoretical perspective for rural tourism development but also offers practical guidance for the adaptive reuse and revitalization of traditional villages.
引用
收藏
页数:15
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