In the age of digital connectivity, the impact of new technologies on cities is more pressing than ever. Digital twin is an emerging technology characterized by “living virtual models, connected digital representations of physical systems” (Ketzler et al., 2020). This technology has been widely deployed in various fields, including manufacturing (Liu et al., 2021), architecture (Harwood and Eaves, 2020), energy (Wang et al., 2022), and climate and earth systems (Voosen, 2020). It has been. , transportation infrastructure (Klar et al., 2023), and healthcare (Liu et al., 2019). Urban planning is no exception. Recently, national and local governments, together with leading technology companies, have been applying the so-called city-scale digital twin (CDT) technology to urban planning and the built environment.1(Ketzler et al., 2020).
A CDT is a virtual replica of a city's physical assets, landscape, and human activities created using data, analytics, and computational techniques. The process of creating a CDT involves encoding the semantic and geospatial properties of urban objects (Lei et al., 2023a). Unlike other digital twins, CDT allows two-way interaction with the physical city and enables analytical operations and simulations within the virtual environment (Lehtola et al., 2022; Lei et al., 2023a) . Because CDT includes not only the built environment but also human activities, it is useful for urban planners to assess the impact of various urban planning interventions and future changes, such as planned construction projects or emergency management in times of crisis. It has become an indispensable tool. These simulations and impact assessments allow decision makers to assess policy impacts and determine better solutions. CDT can improve many aspects of smart cities, including better urban planning through more involved citizen participation, integrated operations through interoperable systems, and greater public access to data. In practice, national governments (e.g. UK, Singapore, Japan), local governments (e.g. Zurich, New York, Chattanooga, Shanghai), private companies (e.g. PricewaterhouseCoopers, McKinsey), the European Union, and international organizations (e.g. For example, the World Bank) shows that there is a growing interest in this digital technology.
Urban planners have high expectations that CDT will help solve complex problems in smart cities (Hurtado and Gomez, 2021). Smart cities face accountability issues arising from a lack of transparency (Jacobs et al., 2020), citizen participation (Cardullo and Kitchin, 2019), and citizen-centric data governance (König, 2021). For example, a lack of citizen participation hinders the ability to imagine how smart cities can improve everyday life (Kogan and Lee, 2014; Komninos et al., 2013; Schuurman et al., 2012). CDT technology has the potential to enhance citizen participation in urban planning and implementation by providing visualization capabilities. It is important to conduct an in-depth analysis to explore the diverse pathways for CDT to address these challenges at different levels.
At the same time, CDT presents unique challenges due to the following differences from other digital twin technologies (Nochta et al., 2021): First, many of the data feeds to CDTs are not readily available or accessible due to decentralized data ownership, lack of data sharing schemes, and security and privacy concerns ( Nochta et al., 2021 ). Second, there is a lack of clear value propositions or benefits that can justify the necessary data collection and sharing across multiple stakeholders (Lei et al., 2023a; Nochta et al., 2021). Third, the social and economic aspects of how people and social systems should be engaged and represented are understudied compared to the technical aspects (Nochta et al., 2021; Tomko and Winter, 2019). CDT then faces unique challenges not encountered with other digital twin technologies. For example, there are some challenges in governance elements, such as public participation and inclusion. To analyze and address these challenges, we develop a maturity model, a framework that measures technology maturity such as quality, capability, sophistication, and progress toward goals (Becker et al., 2009; Warnecke et al., 2019). .
Specifically, this document aims to achieve three objectives. The first is to develop a CDT technology maturity framework. Second, we aim to use the developed maturity model to examine how CDTs can address long-standing challenges in smart cities. Finally, we analyze current obstacles to CDT from a governance perspective.
The remainder of the paper is organized as follows. Section 2 reviews the current literature on CDT governance and maturity models. Section 3 describes our method. Section 4 develops a CDT maturity model framework that can be used to assess the development status of CDT initiatives. Section 5 then assesses the governance perspectives: transparency, accountability, participation, and inclusion. Section 6 discusses how CDT can contribute to the challenges of smart city development. Section 7 discusses challenges in technology development, participation, and inclusion. Section 8 discusses policy implications and potential regulatory frameworks to address these challenges. Section 9 considers the promise and sustainability of CDT from the perspective of scalability and adaptability.
