An integrated framework for addressing urban challenges in smart cities: transitioning from the V-model to a knowledge-action approach

ABSTRACTDigital technologies and tools have been widely deployed in smart city initiatives to improve operations, resource allocation, and infrastructure management. Due to high complexity and diversity, however, numerous technologies have simultaneously created obstacles for practitioners when choosing appropriate tools for certain urban challenges. This study proposes a knowledge-action guiding framework (K-A framework), based on the classic V-model, useful for guiding practitioners to scan through appropriate digital technologies and tools for addressing urban challenges and societal issues. A toolbox was also developed to support the use of the framework. It outlines a comprehensive landscape of popular and emerging digital tools in digitalizing urban services. Essentially, the K-A framework provides a ‘how-to’ in terms of identifying potential tools, while the digital toolbox shows ‘what-are-the-options’ for the users of the framework. The case study underscores the usefulness of the framework and toolbox as effective practical guides for formulating action solutions. HighlightsWe propose a knowledge-action framework based on a classic systems engineering modelThis framework can guide practitioners to identify digital technologies and toolsA comprehensive toolbox was provided to support the use of the frameworkA case study of urban safety issues was applied to validate the framework and toolboxNonlinear thinking and professional competency are key for city planners and managersKEYWORDS: Urban challengedigital technologysmart citypolicymakingurban safety AcknowledgmentThis research is supported by (1) the Ove Arup Foundation (Digital Cities for Change project) (RG89525); (2) The Start-up Funding for New Faculty at Peking University Shenzhen Graduate School (1270110033); (3) Guangdong Basic and Applied Basic Research Foundation (2021A1515110537;2023A1515010979) and (4) the National Natural Science Foundation of China (42376213). We thank Miss Huali Lin for her initial assistance in the early stage of this paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research is supported by (1) the Ove Arup Foundation (Digital Cities for Change project) (RG89525); (2) The Start-up Funding for New Faculty at Peking University Shenzhen Graduate School (1270110033); (3) Guangdong Basic and Applied Basic Research Foundation (2021A1515110537;2023A1515010979) and (4) the National Natural Science Foundation of China (42376213).