An evaluation system based on the self-organizing system framework of smart cities: A case study of smart transportation systems in China

Jianghui Yan, Jinping Liu and Fang-Mei Tseng

Technological Forecasting and Social Change, 2020, vol. 153, issue C

Abstract: Smart cities have been developing aggressively around the globe, especially in China. As of 2017, more than 1000 cities in the world have commenced smart city developments, half of which are in China. However, there is not a uniform and clear understanding of smart city systems; this may affect their evaluation/planning and lead to misguided construction. Smart cities are characterized by complex self-organizing systems, and thus their sustainable and healthy development may require following the evolutionary patterns of such systems. Hence, self-organizing system theory may be useful in explaining such cities. Therefore, this paper first performs secondary qualitative data analyses of previous attempts at characterizing smart city development to identify the most robust aspects tested in previous work. Then, incorporating the results, self-organization theory is used to develop an overall, comprehensive system framework of smart cities. In this framework, all types of smart devices are the basic units of development (defined as “smart cells”). Meanwhile, Information and Communications Technology (ICT) and developmental mechanisms offer technical support and regulatory mechanisms in the spontaneous operation of smart cities. These three dimensions (smart cells, ICT, and developmental mechanisms) are combined into a scalable and distributed smart city evaluation system. Finally, smart transportation systems and the current state of these in China are used as a case study for discussion.

Keywords: Smart cities; Self-organizing systems; CA model; Smart cells (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:153:y:2020:i:c:s0040162518301021

DOI: 10.1016/j.techfore.2018.07.009

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