Structural Equation Model in Landscape Performance Research: Dimensions, Methodologies, and Recommendations

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Publicat a:Land vol. 14, no. 3 (2025), p. 646
Autor principal: Han, Xiao
Altres autors: Li, Zhe, Chen, Haini, Yu, Mengyao, Shi, Yi
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MDPI AG
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022 |a 2073-445X 
024 7 |a 10.3390/land14030646  |2 doi 
035 |a 3181561306 
045 2 |b d20250101  |b d20251231 
084 |a 231528  |2 nlm 
100 1 |a Han, Xiao 
245 1 |a Structural Equation Model in Landscape Performance Research: Dimensions, Methodologies, and Recommendations 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a The scientific evaluation of landscape performance has become a critical focus in promoting landscape architecture and urban quality research. Structural equation modeling (SEM) is widely applied in digital assessments and performance studies, offering robust analytical capabilities. However, further progress requires a systematic review to synthesize past findings and identify emerging opportunities. This study reviews 245 articles that utilize SEM in landscape performance research, analyzing publication trends, research dimensions, methodologies, and data sources. The results indicate that SEM-based studies are predominantly focused on cognitive environmental performance based on subjective evaluation data. SEM can be applied to analyze the correlation mechanisms between landscape performance and influencing factors, examine the mediating effects among multiple factors, and conduct comparative analyses across different sample groups. Future research should prioritize integrating subjective and objective assessments, developing open-source databases, and promoting practical applications of SEM technologies. These efforts will enhance policy-making and improve the precision of performance evaluations, strengthening the scientific foundation of landscape architecture and quality enhancement research. 
653 |a Landscape architecture 
653 |a Research methodology 
653 |a Comparative analysis 
653 |a Assessments 
653 |a Performance evaluation 
653 |a Environmental performance 
653 |a Perceptions 
653 |a Sustainable development 
653 |a Discriminant analysis 
653 |a Structural equation modeling 
653 |a Data processing 
653 |a Variables 
653 |a Design 
653 |a Parameter estimation 
700 1 |a Li, Zhe 
700 1 |a Chen, Haini 
700 1 |a Yu, Mengyao 
700 1 |a Shi, Yi 
773 0 |t Land  |g vol. 14, no. 3 (2025), p. 646 
786 0 |d ProQuest  |t Publicly Available Content Database 
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856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3181561306/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3181561306/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch