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.
Highlights
Reasonable spatial organization of the tourism industry can improve the utilization efficiency of regional tourism industry elements
In order to build a reasonable spatial organization mode for the tourism industry and improve the efficiency of tourism resource and facility utilization by connecting series of tourism enterprises through tourism nodes and tourism channels, tourism nodes, channels, and areas must be optimized in order to classify them according to their scales and functions and determine the organization levels and development orders of tourism industry elements
The existing studies lack quantitative research on spatial organization nodes and organization mode of the tourism industry based on the collection of various types of tourism industry data and the comprehensive consideration of the interactions among tourism resources, service facilities, transportation, tourist towns, and other tourism industry elements. e existing studies lack quantitative research on service scopes and scales of tourism nodes
Summary
2.1. e Model of Minimizing Facility Points. is model is applied to determine the number and locations of tourism nodes (i.e., facility points). e unbalanced space of tourism industry elements makes it difficult to determine the number and location of tourism nodes, and the service radius of different levels of tourism nodes is different. Is model is applied to determine the number and locations of tourism nodes (i.e., facility points). E unbalanced space of tourism industry elements makes it difficult to determine the number and location of tourism nodes, and the service radius of different levels of tourism nodes is different Using this model to set the impedance cutoff value of tourism nodes, the tourism nodes that meet the requirements according to the distribution of tourism enterprises (i.e., request points) will be selected, and the tourism enterprises located in the tourism nodes impedance cutoff will allocate all of their request weights to the tourism nodes, so that as many tourism enterprises as possible are located within the impedance radius of tourism nodes, minimizing the number of tourism nodes covering tourism enterprises. E spatial organization mode of the tourism industry is constructed on this basis, and its essential elements are scientifically organized to provide reference for development planning and policy formulation for Dalian’s tourism industry
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