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  • 标题:Spatial Analysis of the Empirical Behavior of Municipal Institutional Capacity for the Formulation of Sustainable Growth Management Strategies with a Regional Focus: State of Veracruz, Mexico
  • 本地全文:下载
  • 作者:Isabel Lagunes-Gómez ; María Graciela Hernández-Orduña ; Rene Murrieta-Galindo
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2022
  • 卷号:14
  • 期号:4
  • 页码:2000
  • DOI:10.3390/su14042000
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:As a governmental function, development for progress and welfare is a highly complex process that involves updating various attributes (such as a paradigm, critical or alternative, depending on of the way in which they are articulated regarding social aspects, environmental, and economic growth, as well as the institutional capacity of public and private actors). Regarding this, we are interested in the municipal institutional capacity (MIC) as a skill to carry out the functions and appropriate tasks that municipalities must fulfill in an effective, efficient, and sustainable way, and it varies considerably, depending on each local context. In order to analyze the relevance of the current official regionalization as a state government strategy for the centralized construction of MIC, an exploratory approach to its spatial behavior in the State of Veracruz, Mexico, was carried out. Given the nature of the study, a purely mixed approach, sequential exploratory design, subnational analysis methodology, and exploratory spatial data analysis (ESDA) were employed. The variable to be analyzed is the 2016 Municipal Functional Capacities Index (Índice de Capacidades Funcionales Municipales (ICFM)), with the Geostatistics Framework cartographic base of the 2020 Population and Housing Census. The analysis units are 212 municipalities in the 2014–2017 government period. As a result, it was confirmed that the current regionalization was irrelevant, owing to the absence of global spatial autocorrelation, and it was concluded that targeted interventions are necessary according to regional modeling techniques, based on scientific evidence.
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