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Smart city maturity models: A multidimensional synthesized approach
WIREs Data Mining and Knowledge Discovery ( IF 6.4 ) Pub Date : 2023-09-15 , DOI: 10.1002/widm.1516 Sepehr Ghazinoory 1 , Jinus Roshandel 1 , Fatemeh Parvin 1 , Shohreh Nasri 2 , Mehdi Fatemi 1
WIREs Data Mining and Knowledge Discovery ( IF 6.4 ) Pub Date : 2023-09-15 , DOI: 10.1002/widm.1516 Sepehr Ghazinoory 1 , Jinus Roshandel 1 , Fatemeh Parvin 1 , Shohreh Nasri 2 , Mehdi Fatemi 1
Affiliation
Smart cities are one of the consequences of digital transformation, and there have been many attempts to assess the smartness of cities with various frameworks. Among these frameworks, smart city maturity models (SCMMs) evaluate the existing conditions of cities and provide guidelines for progressing through the subsequent stages of maturity. However, most maturity models follow the instructions of the first model, published by the International Data Corporation, and there are many similarities across the models. These maturity models have advantages and disadvantages, while previous studies have not addressed the differences. Therefore, this article fills this knowledge gap by systematically reviewing the existing SCMMs. The findings suggest that some trending topics, such as resiliency concerning global pandemics and cultural aspects are neglected in SCMMs. Moreover, the validation techniques of the models are not rational. Finally, given the theoretical nature of most models, they cannot be applied to multiple regions.
中文翻译:
智慧城市成熟度模型:多维综合方法
智慧城市是数字化转型的后果之一,人们已经进行了许多尝试用各种框架来评估城市的智慧程度。在这些框架中,智慧城市成熟度模型(SCMM)评估城市的现有条件,并为后续成熟阶段的进展提供指导。然而,大多数成熟度模型都遵循国际数据公司发布的第一个模型的说明,并且这些模型之间有许多相似之处。这些成熟度模型各有优缺点,而之前的研究尚未解决这些差异。因此,本文通过系统回顾现有的 SCMM 来填补这一知识空白。研究结果表明,一些热门话题,例如,SCMM 忽视了全球流行病和文化方面的弹性。此外,模型的验证技术也不合理。最后,考虑到大多数模型的理论性质,它们不能应用于多个区域。
更新日期:2023-09-18
中文翻译:
智慧城市成熟度模型:多维综合方法
智慧城市是数字化转型的后果之一,人们已经进行了许多尝试用各种框架来评估城市的智慧程度。在这些框架中,智慧城市成熟度模型(SCMM)评估城市的现有条件,并为后续成熟阶段的进展提供指导。然而,大多数成熟度模型都遵循国际数据公司发布的第一个模型的说明,并且这些模型之间有许多相似之处。这些成熟度模型各有优缺点,而之前的研究尚未解决这些差异。因此,本文通过系统回顾现有的 SCMM 来填补这一知识空白。研究结果表明,一些热门话题,例如,SCMM 忽视了全球流行病和文化方面的弹性。此外,模型的验证技术也不合理。最后,考虑到大多数模型的理论性质,它们不能应用于多个区域。