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Computational Simulation of the Correlations in a Port–Hinterland System from a Tourism Spatial Optimization Perspective

Autor(en): ORCID




ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 3, v. 13
Seite(n): 832
DOI: 10.3390/buildings13030832
Abstrakt:

From the perspective of tourism space optimization, the application of computer technology in creating computational simulations of correlation effects in tourism space systems is a core issue in research related to ports and hinterlands. Using a computer simulation analysis of the gray correlation, taking Mohan port–Yunnan economic hinterland as an example, the relationship between Mohan port and the Yunnan economic hinterland was quantitatively measured based on the indicators of cross-border tourism from 2006 to 2020. The study aimed to identify the driving mechanisms behind the synchronized development of Mohan port–Yunnan economic hinterland. The results are as follows: (1) due to the influence of administrative interventions and the competition of the neighboring ports, the correlation between the Mohan port and the Yunnan hinterland from 2006 to 2020 showed a rising–falling trend; (2) the correlation between the Mohan port and Xishuangbanna prefecture showed an obvious fluctuating trend, and the original port–city development relationship evolved to a competitive status; (3) the degree of spatial correlation of the Mohan port–Yunnan hinterland system evolved in a north–south-central–south direction, with “border zone–central region–northern region” distribution characteristics; (4) the natural conditions of the location, national policies, competition of nearby ports, infrastructure and traffic conditions, and economic strength are the main driving factors affecting the correlation change between Mohan port and the Yunnan hinterland. These findings can help enrich the theoretical research system of buildings economics, and expand the application of computational decision-making support in tourism spatial optimization.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10728436
  • Veröffentlicht am:
    30.05.2023
  • Geändert am:
    01.06.2023
 
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