How Digital Twin Technology Promotes the Development of Smart Cities: Case Studies in China

How Digital Twin Technology Promotes the Development of Smart Cities: Case Studies in China

Poshan Yu, Zixuan Zhao, Michael Sampat
Copyright: © 2023 |Pages: 30
DOI: 10.4018/978-1-6684-3833-6.ch008
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Abstract

This chapter aims to study whether and how current practices based on digital twin technology can help the development of smart cities in China. This chapter will explore the roles of the government in promoting the application of digital twin technology in the development agenda of industrial infrastructure and smart cities through policies (i.e., institutions). How do these institutions promote the development of digital twin technology in various industries and how will these developments in turn affect stakeholders in various sectors? This chapter will investigate the impact of China's digital twin technology research and institutional changes on the sustainable development of smart cities. This chapter will use bibliometric analysis to perform statistical and correlation analysis on the digital twin/blockchain/AI/IoTs literature included in the Web of Science (WOS) database. Cases from China will be used for comparison. This chapter will provide suggestions for the development of digital twin technology-based ecosystems in emerging economies.
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Background

Analysis

The evolution of a new subject needs to build on the knowledge accumulation of relevant subjects. Similarly, no single research paper can be developed solely based on its content. The paper needs to draw on the past literature and research ðndings from its discipline or other relevant disciplines. Generally, research papers published in journals represent the frontiers of certain subjects, and the references cited in these papers provide the knowledge base of these papers. With the assistance of certain computer software, we could cluster references that are commonly cited in the smart city discipline and identify co-citation clusters. This step is important in identifying the foundation knowledge of smart city research and it could be achieved through visualizing the knowledge of smart city research using journal articles. To focus the subsequent research, we then used CiteSpace to search the existing literature in the WOS database to identify the core topics that are most closely related to smart cities today.

CiteSpace is one of the most popular tools for knowledge mapping (e.g., Chen, 2006; Chen et al., 2010). It is particularly designed to support the analytic process of visualizing and it can produce co-citation networks based on article citations to reveal the structure of a particular research field (Chen et al., 2010). Using CiteSpace to analyze existing smart city literature would help provide a clear picture of how knowledge and theories advanced and how to research topics evolved, therefore, this analysis is highly desirable.

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