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Common prosperity level evaluation: A comprehensive method based on probabilistic linguistic ordered weighted distance measure, prospect theory, and TOPSIS.
Zhang, Erhua; Yu, Feifan; Jiang, Ting; Zeng, Shouzhen; Wang, Dandan.
Afiliación
  • Zhang E; School of Business, Ningbo University, Ningbo, China.
  • Yu F; School of Business, Ningbo University, Ningbo, China.
  • Jiang T; School of Business, Ningbo University, Ningbo, China.
  • Zeng S; School of Business, Ningbo University, Ningbo, China.
  • Wang D; School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China.
Front Psychol ; 14: 1152333, 2023.
Article en En | MEDLINE | ID: mdl-37008846
Introduction: Common prosperity is a major research project in China, and the scientific measurement and evaluation of common prosperity is very important. Methods: In this study, firstly, we construct a comprehensive evaluation index system for the common prosperity level (CPL). We then develop an evaluation model of CPL based on prospect theory, probabilistic linguistic ordered weighted distance measure, and the TOPSIS method, wherein we use a probabilistic linguistic term set (PLTS) to describe the uncertainty and complexity of the assessment process. Above all, we use prospect theory to reflect the preferences of experts to meet the unique needs for the evaluation of common prosperity. Moreover, we apply the proposed evaluation index system and model to evaluate the CPL of Zhejiang Province, China's first common prosperity demonstration zone, as an example to conduct relevant research. The advantages and effectiveness of the proposed method are verified by the sensitivity and comparative analysis. Results: The findings prove that the application of the new PLTS evaluation framework in CPL assessment is robust. Discussion: We propose specific suggestions for improving the development of common prosperity.
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Psychol Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Psychol Año: 2023 Tipo del documento: Article País de afiliación: China