ABSTRACT Online travel searches are important forms of travel virtual spaces. Previous studies have neglected to analyze the spatial features of the travel searches themselves, and the spatial heterogeneity of their influencing factors. In this study, a travel search index based on the Baidu index was established for analyzing travel searches. Meanwhile, a local spatial model was created for the linear features in order to discuss the spatiotemporal heterogeneity of the influencing factors. The results of this study indicated that travel searches have obvious spatial inequality, and economically developed regions had displayed advantages in the travel search network. The fitting results of the local model were found to be superior to global model. The number of attractions and the GDP of the origin were found to have promoting effects on the travel searches, whereas distances had shown inhibiting effects. These effects presented significant spatiotemporal heterogeneity. It was also found that within the travel search virtual space, the distance effects still existed, but the intensity was weaker than in the real space. The local spatial model for the linear features provided a new spatial analysis method for understanding the travel search network, as well as other types of networks (flow patterns).

中文翻译：

---

探索在线旅游搜索中的时空异质性：一种局部空间模型方法

摘要 在线旅游搜索是旅游虚拟空间的重要形式。以往的研究忽视了对旅游搜索本身的空间特征及其影响因素的空间异质性分析。本研究建立了基于百度指数的旅游搜索指数，用于分析旅游搜索。同时，为线性特征建立局部空间模型，以讨论影响因素的时空异质性。本研究结果表明，旅游搜索存在明显的空间不平等，经济发达地区在旅游搜索网络中表现出优势。发现局部模型的拟合结果优于全局模型。发现景点的数量和原产地的 GDP 对旅行搜索有促进作用，而距离则显示出抑制作用。这些影响呈现出显着的时空异质性。还发现在旅行搜索虚拟空间内，距离效应仍然存在，但强度比真实空间中要弱。线性特征的局部空间模型为理解旅行搜索网络以及其他类型的网络（流模式）提供了一种新的空间分析方法。