The landscape is an essential resource for attracting tourists to a destination, but this resource has long been overused by tourism development. Tourists and scholars have begun noticing the interference of human structures in the natural environment and how this can change the meaning of a landscape. In this study, the impact of artificial elements on mountain landscapes was investigated by measuring the characteristics of visual perception and a landscape value assessment using eye-tracking analysis. Furthermore, this study includes socio-demographic features for testing whether they have an impact on landscape perception. The results show that human structures impact both visual perception and the perceived value of landscapes. Hotels and temples attract more visual attention than a purely natural landscape. Modern hotels appear to have a negative influence on mountain landscape valuation, while temples with unique culture have positive impacts. Socio-demographic groups differ significantly in how they observe landscape images and, to a degree, how they value the landscape therein. Our study should be of value to landscape planning and tourism policy making.

The coronavirus disease (COVID-19) has had a major impact on global tourism. We adopted social media data to quantify the change in Chinese consumers’ attitudes toward traveling during the pandemic, as no study has explored whether there is compensatory travel intention under the threat of infectious diseases. Using natural language processing technology and geographic information system technology, our analysis shows that Chinese consumers’ interest in tourism increased during the pandemic. Our results show that travel attitudes can be positively affected by compensatory consumption when travel is restricted by infectious diseases and has implications for tourism scholars, marketing managers, and stakeholders.

With the growing influence of media on tourism destination marketing, this research proposes a possible psychological process of music effect on place attachment, using the narrative transportation theory. Data were collected through an online survey in China (n = 531) and analyzed using SEM. Results indicate that (1) music transportation positively affects individuals’ attachment; (2) attitude plays a partial mediating role in the relationship between music transportation and place attachment; (3) previous visits have significant moderate effects on the attitude-attachment path rather than on the transportation-attachment path or the transportation-attitude path. Theoretical and practical implications for destination marketing are provided.

Abstract Transport is an integral part of the tourism industry. The tourist traveling patterns are highly dependent on the transport infrastructure in a tourism destinations. Based on the Social Network Theory, four centrality indicators and the transition possibility are adopted to explore the tourism flow network related to different modes of transportation and tourist transition capabilities in tourism destinations. A complex tourist itinerary visualization model uncovers the spatial structure of multi-layer tourist flows. Dunhuang, a rapidly growing tourist destination in Northwest China, reveals this patterning. Results show that: (1) The spatial structure and flow rate of the tourism flow network is significantly different when different transport modes are observed. (2) The tourists transition capability for different transport modes in the same region varies according to the geographic location and infrastructure level. (3) Tourists manifest different movement patterns among the available transport networks within a destination area. 交通是旅游系统中十分重要的一部分。旅游目的地交通基础设施的发展情况深刻影响着游客的出行模式。本文基于社会网络理论, 通过中心性分析方法和转移概率的计算, 以中国西北地区重要旅游目的地敦煌为案例地探究了不同交通方式下的旅游流网络, 并建立了一个多层交通下的旅游流网络可视化模型。本文拓展了交通与游客空间行为研究的方法, 并为旅游目的地规划与管理提供了科学依据。结果表明：（1）不同交通方式下的旅游流网络的流量和结构呈现出明显差异；（2）对于同一区域, 不同交通方式之间的转移概率会因为地理位置和交通基础设施水平的差异而不同；（3）游客出行行为模式在不同交通方式网络下表现出差异。

The spatial behavior of tourists is an important part of the research on congestion management and sustainable planning of tourism destinations. Combined with user-generated content (UGC) and site-based survey data, this study conducted an overlaying analysis between street network configurations that resulted from space syntax and tourist preferences. Based on space syntax, tourist movement is influenced by the distribution of scenic spots and the structure of tourist trails in scenic mountain areas. The results reveal that the distribution of scenic spots has a significant impact on tourist flow and visitors’ choices of entrance to the mountain; the volume of online sign-ins is highly correlated with landscape attention, axial control values and the local integration value of the trails; and tourists’ attention focuses on the entrance area and the few tourist-sight markers. This study advances the understanding of the spatial patterns of within-destination tourist behavior; this knowledge will be helpful in alleviating congestion in mountain scenic areas and providing effective guidance for tourists to plan an ideal tour route.