2017
DOI: 10.3390/su9040666
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Urban Competitiveness Measurement of Chinese Cities Based on a Structural Equation Model

Abstract: In the current era, competition among countries and regions is in fact among cities. Thus, how to measure urban competitiveness precisely is a basic and important question. The two main approaches to this are comprehensive evaluation based on a set of indicators and network analysis based on inter-city relations. However, both have shortcomings. In this study, we introduced structural equation model (SEM) into urban competitiveness measurement to integrate the two approaches. We built a partial least squares s… Show more

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Cited by 9 publications
(3 citation statements)
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“…The model fit indices of distinct categories can be measured for model complexity, sample size, relativity, and absoluteness. Therefore, the following seven commonly used indicators were selected (Yuan et al, 2017).…”
Section: Model Fitting and Assessmentmentioning
confidence: 99%
“…The model fit indices of distinct categories can be measured for model complexity, sample size, relativity, and absoluteness. Therefore, the following seven commonly used indicators were selected (Yuan et al, 2017).…”
Section: Model Fitting and Assessmentmentioning
confidence: 99%
“…The aggregated fuzzy values can be calculated in several ways, for example, Eqs. ( 6) and (7). In this study, geometric mean operations are applied to aggregate group decisions as following Eq.…”
Section: Fahp Approachmentioning
confidence: 99%
“…According to the above context, exporting enterprises' competitiveness needs to pay more attention to numerous dimensions, including quality, traceability standards, and food safety requirements. Prior research on competitiveness was reported using linear relations such as Structural Equation Modeling (SEM) approach between variables [7,8]. Additionally, Hair [9] provided an overview of emerging prediction assessment tools for composite-based Partial Least Squares-Structural Equation Modeling (PLS-SEM), notably proposed out-of-sample prediction methodologies.…”
Section: Introductionmentioning
confidence: 99%