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Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy Topsis

A Case Study from 30 Provinces, China

Bibliographic Data

ID15465160
AuthorsXuedong Liang (0009-0004-9013-5626, Sichuan University), Canmian Liu (0000-0002-6309-5612, Sichuan University), Zhi Li (0000-0002-6039-1045, Sichuan University, corresponding author)
Year2017
Volume15
Issue1
Pages10-10
Publication date2017-12-22
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph15010010
PMID29271947
OpenAlexW2777729964
LanguageEN
Citations received5
References cited21

In connection with the sustainable development of scenic spots, this paper, with consideration of resource conditions, economic benefits, auxiliary industry scale and ecological environment, establishes a comprehensive measurement model of the sustainable capacity of scenic spots; optimizes the index system by principal components analysis to extract principal components; assigns the weight of principal components by entropy method; analyzes the sustainable capacity of scenic spots in each province of China comprehensively in combination with TOPSIS method and finally puts forward suggestions aid decision-making. According to the study, this method provides an effective reference for the study of the sustainable development of scenic spots and is very significant for considering the sustainable development of scenic spots and auxiliary industries to establish specific and scientific countermeasures for improvement

Business · China · Economics · Entropy (arrow of time · Environmental economics · Environmental resource management · Geography · Index (typography · Operations research · Principal (computer security · Principal component analysis · Sustainable development · TOPSIS · Computer Science · Cruise Tourism Development and Management · Diverse Aspects of Tourism Research · Engineering · Environmental Science · Artificial Intelligence

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Unique citing works5
Citations per year0,71
Citation span2019 - 2022 (4)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 4

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