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Are global north smart city models capable to assess Latin American cities? A model and indicators for a new context

机译:全球北部智慧城市模型是否能够评估拉丁美洲城市?新环境的模型和指标

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摘要

Most of the methodologies available in the scientific literature for measuring ongoing sustainable efforts at municipal levels are from affluent regions (Europe, US, and Canada). Due to context idiosyncrasies, the models available to measure ongoing sustainable efforts in affluent cities are not suitable for cities in Latin America. Issues related to the lack of infrastructure, the absence of primary and sustainable services, and the problems derived from economic, social, and political environment constraints, which are remarkable in some Latin American cities, have been mostly overcome in the western global north cities. A mere reproduction of successful technological solutions adopted by some cities of the Global North does not mean that the results achieved there will be equally obtained in Latin America. Latin American cities are unevenly developed and in need of different and customized solutions. In the absence of a conceptual and widely accepted methodology to evaluate the smartness of a city considering the Latin America context and in accordance to the literature, this research proposes an innovative model and indicators, levelling up the importance of dimensions less remarkable in previous models. Latin American cities must use their own model to measure their ongoing sustainable efforts that consider the idiosyncrasies of the region while not being tempted to use models from affluent regions, avoiding the risk of reiterating a top-bottom approach and thus using an inappropriate tool.
机译:科学文献中可用的大多数用于衡量市政当局正在进行的可持续努力的方法均来自富裕地区(欧洲,美国和加拿大)。由于上下文的特殊性,可用于测量富裕城市中正在进行的可持续发展努力的模型不适用于拉丁美洲的城市。与基础设施不足,缺乏基本服务和可持续服务以及经济,社会和政治环境制约所引起的问题有关的问题在拉丁美洲一些城市尤为突出,而这些问题已在全球西部的北方城市中得到了解决。仅复制全球北部某些城市采用的成功技术解决方案,并不意味着在拉丁美洲获得的成果将得到同等的回报。拉丁美洲的城市发展不平衡,需要不同的定制解决方案。在缺乏考虑拉丁美洲背景并根据文献评估城市智能性的概念性和广泛接受的方法的情况下,本研究提出了一种创新的模型和指标,从而提高了先前模型中规模较小的维度的重要性。拉丁美洲城市必须使用自己的模型来衡量他们正在进行的可持续发展努力,这些努力考虑了该地区的特殊性,同时又不倾向于使用富裕地区的模型,从而避免了重申自上而下的方法并因此使用不合适的工具的风险。

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