On the taxonomy of smart city indicators and their alignment with sustainability and resilience

As interest in smart city initiatives continues to grow rapidly, various involved actors and stakeholders increasingly rely on assessment frameworks or indicator sets for different purposes such as monitoring and benchmarking performance, identifying strengths and weaknesses, and determining priority intervention areas. Accordingly, many smart city assessment frameworks and/or indicator sets have been developed in the last decade. To guide actors and stakeholders in their selection of the most suitable frameworks, several studies have examined contents and structure of smart city assessment frameworks or indicator sets. Such studies have significantly improved our understanding of the thematic focus of assessment tools and their methodological approaches. However, there is still a lack of knowledge on the taxonomy of smart city indicators. In addition, since other concepts such as sustainability and resilience are increasingly recognized to be connected to the smart city concept, more clarity on how different assessment frameworks or indicator sets are aligned with sustainability and resilience dimensions and characteristics is needed. To fill these gaps, we developed a taxonomy and examined 33 assessment frameworks or indicator sets in terms of indicator type, sectoral linkages, and alignment with sustainability and resilience dimensions and characteristics. In terms of indicator type, results show that output indicators are dominant but limited attention has been paid to impact indicators. In terms of sectoral focus, existing indicators are mainly related to information and communication technologies, economy, and governance. Regarding resilience abilities, indicators are mainly related to planning abilities and limited attention has been paid to recovery and adaptation. As for resilience characteristics, reasonable levels of alignment with resourcefulness and efficiency were observed, but indicators are not well-aligned with other important characteristics such as redundancy and diversity. Finally, in terms of sustainability, limited alignment with the environmental dimension was found, which raises concerns regarding the suitability of smart city indicators for guiding environmental sustainability and informing efforts aimed at addressing climate change issues. Results of this study can support interested stakeholders in their efforts to select the most suitable assessment frameworks or indicator sets for promoting resilient, smart, and sustainable communities.