2022
DOI: 10.1108/mrjiam-01-2022-1270
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Smart governance strategies and their relationships with SDGs in three Latin American cities

Abstract: Purpose The purpose of this paper is to identify and analyze the strategic decisions, especially those focused on smart governance, that have been implemented by the cities of Buenos Aires (Argentina), Medellín (Colombia) and Mexico City (Mexico) and how they have impacted the Sustainable Development Goals (SDGs). Design/methodology/approach Using a qualitative approach and a descriptive scope, this manuscript follows a multiple case study methodology that was primarily based on the analysis of archival reco… Show more

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Cited by 7 publications
(3 citation statements)
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References 68 publications
(117 reference statements)
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“…However, the resilience cultivated by some firms, governments and entrepreneurs that have devised solutions in challenging environments has been noteworthy (e.g. Flores et al , 2023; Jurado-Zambrano et al , 2023; Ramírez-Solís et al , 2021).…”
Section: Future Challenges and Research Opportunitiesmentioning
confidence: 99%
“…However, the resilience cultivated by some firms, governments and entrepreneurs that have devised solutions in challenging environments has been noteworthy (e.g. Flores et al , 2023; Jurado-Zambrano et al , 2023; Ramírez-Solís et al , 2021).…”
Section: Future Challenges and Research Opportunitiesmentioning
confidence: 99%
“…The research objective of Jurado-Zambrano et al (2023) is to describe the strategic decisions of smart city initiatives in Latin America related to SDG 16 (Peace, Justice and Strong Institutions). In doing so, the authors contribute to the debate about how smart cities from developing regions plan and implement sustainable smart governance structures.…”
Section: Special Section Contentmentioning
confidence: 99%
“…Typically, AI is designed around machine learning (ML) algorithms or techniques (such as decision trees and neural networks) that utilise numerical techniques to enable computers to learn and improve their performance using pre-imputed data (Pereira et al, 2020;Sánchez-Morales et al, 2020). Consequently, AI-based systems that can perform simple to complex tasks have soared with applications in various sectors such as transportation (Abduljabbar et al, 2019;Iyer, 2021), finance (Buckley et al, 2021;Cao, 2022), business (Enholm et al, 2022;Loureiro et al, 2021), manufacturing (Chien et al, 2020;Zeba et al, 2021), and others. In recent years, there have been growing calls for the application of AI in tackling socio-economic and environmental problems relating to sanitation, energy, healthcare, and housing, among other things.…”
Section: Introductionmentioning
confidence: 99%