{"title":"Hybrid model for evaluating the transformation of China’s resource-based cities","authors":"Song Pu , Chang Xia","doi":"10.1016/j.seps.2024.101947","DOIUrl":null,"url":null,"abstract":"<div><p>This paper constructs a new and proposes a novel hybrid model combining multi-criteria decision making (MCDM) model and variability for multi-periods as well as the approaches to select the best specific hybrid model. A case study based on 17 RBCs in three provinces of southwest of China for 2012–2020 indicates that the transformation efficiency of most RBCs is between 0.400 and 0.600. More specifically, 12 out of 17 RBCs have a positive variability direction with the biggest variability value less than 0.039. Sichuan has an obvious downward trend with a decreased rate of 9.13%, while Yunnan and Guizhou increase by 10.50% and 6.43%, respectively. The transformation efficiency of mature cities is the worst, while the only recession city is the best. The transformation efficiency of RBCs has the highest correlation with the freight volume, other indicators including unemployment rate, ratio of GDP growth, fiscal revenue, average annual population and unemployment rate are high correlation with the transformation efficiency.</p></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038012124001460","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper constructs a new and proposes a novel hybrid model combining multi-criteria decision making (MCDM) model and variability for multi-periods as well as the approaches to select the best specific hybrid model. A case study based on 17 RBCs in three provinces of southwest of China for 2012–2020 indicates that the transformation efficiency of most RBCs is between 0.400 and 0.600. More specifically, 12 out of 17 RBCs have a positive variability direction with the biggest variability value less than 0.039. Sichuan has an obvious downward trend with a decreased rate of 9.13%, while Yunnan and Guizhou increase by 10.50% and 6.43%, respectively. The transformation efficiency of mature cities is the worst, while the only recession city is the best. The transformation efficiency of RBCs has the highest correlation with the freight volume, other indicators including unemployment rate, ratio of GDP growth, fiscal revenue, average annual population and unemployment rate are high correlation with the transformation efficiency.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.