Work

How can the natural background and ecological & environment promote the green and sustainable development of Chinese tourist attractions?

Year: 2024

Type: article

Abstract: In the context of global carbon peak and carbon neutrality initiatives and post-pandemic, studying the green and sustainable development of tourist attractions is of great significance for the sustainable utilization of tourism resources. This study focuses on tourist attractions in 30 provinces in China from 2001 to 2019, establishes an input-output indicator system for economic efficiency and eco-efficiency, and uses the Super-SBM model in Data Envelopment Analysis to calculate the economic efficiency and eco-efficiency of tourist attractions in China. To analyze the natural background and environmental driving factors that affect the eco-efficiency, as well as the interaction between these factors, using a geographic detector model, and propose a green and sustainable development path for tourist attractions. The research results indicate: the eco-efficiency of Chinese tourist attractions was higher than the economic efficiency, and both showed a downward trend; The proportion of altitude and nature reserve area to the area under the jurisdiction, as well as the total investment in environmental pollution control, have a significant impact on the eco-efficiency; The interaction between temperature, precipitation, and NDVI, and the proportion of nature reserves in the jurisdiction and the total investment in environmental pollution control, is significantly enhanced, indirectly affecting the eco-efficiency of Chinese tourist attractions. Among the natural factors, temperature, precipitation, and NDVI all promote the improvement of eco-efficiency in Chinese tourist attractions through a significantly enhanced interaction with altitude. The research aims to provide a Chinese solution for the development of tourist attractions in developing countries similar to China.

Source: Ecological Indicators

DOI: 10.1016/j.ecolind.2024.112813

Authors: Ning Yan, Jing Zhang, Bing Xia, Shihua Li, Wen Yang

Institutions: Xiamen University, Imperial College London, Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, Inner Mongolia Normal University

Language: English

Topic: Efficiency Analysis Using DEA

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $2,970