Study on City-Level Optimization of Tourism Industry Spatial Organization Nodes and Organization Mode for Tourist Destinations. (17th August 2020)

• Record Type: Journal Article
• Authors: Hao, Jinlian; Liu, Haolong; Chen, Jie; Sun, Fankai
• Other Names: Yang Jun Guest Editor.
• Is Part Of: Complexity. Volume 2020(2020)
• Publication Date: 2020-08-17
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2020/2807817
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Reasonable spatial organization of the tourism industry can improve the utilization efficiency of regional tourism industry elements. Taking Dalian City in China as an example, this paper collects various types of tourism industry data and introduces GIS network analysis technology into tourism studies to determine the location, scale, and number of tourism nodes in Dalian and optimize the spatial organization nodes and organization models of the tourism industry. This will help ease the pressure on tourism reception in the southern area of Dalian and promote better development and utilization of tourism resources and tourism facilities in the central and northern regions. The results show that (1) when using the "minimizing facility points" model, a total of 17 second-level tourism nodes and 5 first-level tourism nodes are obtained after optimization. The location of these nodes is highly correlated with the level of tourist scenic spots, while tourist scenic spots play a significant role in leading and driving tourism nodes. (2) Using the "maximum coverage" model for optimization, 3138 tourism enterprises are connected with tourism nodes, thus realizing the shortest traffic path between tourism enterprises and tourism nodes, which minimizes the total cost of network services. Compared with suburban areas, enterprises in urban tourism areas are densely distributed, meaning that a smaller service radius of tourism nodes can cover more enterprises. (3) A total of 10 first-level tourism channels and 12 second-level tourism channels are optimized using the "nearest facility" model. The first-level tourism channels are mainly distributed in the central and southern areas of Dalian. These channels connect nodes mainly through national and provincial roads. The second-level tourism channels are mainly distributed in the central and northern areas of Dalian. (4) This study aims to analyze the evolution process of the spatial organization mode of Dalian's tourism industry and construct a hub-spoke network tourism industry spatial organization mode composed of 17 hubs, 22 spokes, and 22 tourism domains. The analysis and construction are designed according to the optimization results of tourism nodes and tourism channels. The research results enrich the theories and technical means of tourism industry spatial organization and provide references and suggestions for local governments or tourism planning decision-makers; they also provide a scientific basis for the rational allocation of tourism industry elements and promote the rational distribution of tourism industry.