Impact of Accessibility and Network Attention Coupling Coordination on Operating Benefits of Scenic Spots

-- Empirical Research based on BP Neural Network

Authors

  • Fan Xu

DOI:

https://doi.org/10.54097/ajmss.v2i3.8717

Keywords:

Accessibility, Network Attention, Tourist Attractions, Operational Benefits

Abstract

This paper takes the scenic spots in the outskirts of Beijing as the research area and uses a BP neural network model based on the perspective of coupling relationship to study the impact of accessibility, network attention, and their coupled coordination relationship on operational efficiency of scenic spots in the outskirts of Beijing between November 27, 2018 and January 20, 2020. The results show that the coupled coordination relationship between accessibility and network attention has a significant positive impact on operational efficiency. Under the situation of coupled coordination, there is a positive impact between accessibility and operational efficiency as well as between network attention and operational efficiency; however, under the situation of mismatching, there is a negative non-linear relationship between accessibility and operational efficiency, and between network attention and operational efficiency, respectively.

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References

Zeng, C. (2016). From "Isolated Island" to City: Spatial design strategy under the background of architectural urbanization. Beauty and Time: Cities, (5), 23-24.

Li, X. (2018). Analysis of network attention degree and SVR passenger flow prediction in Jiuzhaigou. Nanchang University.

Zhang, Y. (2012). Graph theory Reachability. Chinese Journal of Architecture, (09), 71-76.

Yegnanarayana, B. (2009). Artificial neural networks. PHI Learning Pvt. Ltd.

Abraham, A. (2005). Artificial neural networks. Handbook of measuring system design.

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Published

21-05-2023

Issue

Section

Articles

How to Cite

Xu, F. (2023). Impact of Accessibility and Network Attention Coupling Coordination on Operating Benefits of Scenic Spots: -- Empirical Research based on BP Neural Network. Academic Journal of Management and Social Sciences, 2(3), 61-67. https://doi.org/10.54097/ajmss.v2i3.8717