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Zhang, M., Wang, R., Xie, Z., He, H., Li, S., Cen, Y., Wu, H., & Chu, C. C. (2022). Evaluation of the Level of Smart City Construction Based on Guangfo- Shenzhen-Dongguan in the Context of Guangdong-Hong Kong Macao Greater Bay Area. Advances in Social Sciences Research Journal, 9(5). 436-
454.
URL: http://dx.doi.org/10.14738/assrj.95.12439
Greater Bay Area. This study focuses on the development needs, future
development trends and construction strategies of smart cities in four city clusters
in the Guangdong-Hong Kong-Macao Greater Bay Area from four development
perspectives: smart water conservancy, smart cultural tourism, smart
transportation and smart healthcare, using data related to the development of
smart cities in Guangzhou-Foshan-Shenzhen-Dongguan in recent years, the entropy
weighting method is used to determine the weights of 40 indicators, and the TOPSIS
evaluation model is applied to evaluate the level of smart city construction in each
city. The evaluation of the level of smart city construction in each city was carried
out by using the TOPSIS evaluation model, and it was concluded that there were
large differences among the cities, and there was a need for city-specific policies and
reasonable improvements. The evaluation of the level of smart city development in
each city was carried out using the TOPSIS evaluation model.
Keywords: Guangdong Hong Kong -Macao Greater Bay Area, Smart Water, Smart Culture
and Tourism, Smart Transportation, Smart Healthcare, Smart City Construction Level
Evaluation1
INTRODUCTION
As a national reform and opening-up early zone and an important engine of economic
development, Guangdong-Hong Kong-Macao Greater Bay Area is ahead of the rest of the
country in building technology and industrial innovation centers and bases for advanced
manufacturing and modern service industries, reaching the organic integration of Internet,
Internet of Things, communication networks and cable TV networks, and forming a strong
infrastructure network. The government actively promotes the development of smart cities,
and from 2014 "Guidance on Promoting the Healthy Development of Smart Cities" there are
constantly active policies to promote the reform of wisdom around the world, trying to solve a
series of problems encountered in the development of urbanization from another side. Some
local governments have adopted the attitude of blindly following the trend, without an in-depth
analysis of the construction of their smart cities, copying the construction plans of other cities
into their construction, which eventually makes the construction of smart cities around the
world more or less the same.
In the process of promoting the "people-oriented, user-oriented" smart city construction, the
quality of the simultaneous construction of a smart society will directly affect the quality of life
and experience of residents. As one of the regions with the highest degree of openness and
economic vitality in China, the Guangdong-Hong Kong-Macao Greater Bay Area has an
important strategic position in the country’s overall development. The Guangzhou-Foshan and
Shenzhen-Dongguan city pairs ranked first and second respectively in the "2020 Third Quarter
National City Linkage" ranking, and their economic development and urban influence is the
"leading city in the Bay Area". However, the unbalanced development of urban clusters within
the region of Guangdong-Hong Kong-Macao Greater Bay Area is one of the important challenges
faced in the process of building a smart society in the region. Facing the problems of
administrative division management, cultural differences, and unbalanced economic
development in Guangdong-Hong Kong-Macao Greater Bay Area, political enterprises are
needed to solve the challenges and problems in the construction of a smart society in a more
1 Student Academic Fund project of Foshan University of Science and Technology in 2021(xsjj202114zsb21)
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Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 5, May-2022
Services for Science and Education – United Kingdom
intelligent way. How to improve the smart city construction of the leading cities in the Bay Area
and create a benchmark city to drive other cities to improve the level of smart city construction
has become an urgent problem to be solved in Guangdong-Hong Kong-Macao Greater Bay Area.
There are many analyses about the connotations of smart cities at present, but no unanimous
consensus has been formed. The research on smart city construction by domestic and foreign
scholars can be broadly divided into two aspects: one is to study the construction mode of smart
cities, and the other is to study the evaluation system of smart cities. As for the research on the
mode of smart city construction, Wang Juan (2014) proposed that the mode of smart city
construction should be driven by innovation, with smart industry as the forerunner and
technology as the basis, and the government as the leading gradually guiding enterprises and
public participation from the demand of city characteristics. After comparing and analyzing the
typical development models of smart cities at home and abroad, Zhang Hong et al. (2014)
concluded that the construction model of smart cities should be divided into four categories:
government independent investment in network construction, operator-independent
investment in network construction, government planning guiding operator investment in
network construction, and the model of government partially funding and entrusting operator
network construction. In the study of the smart city assessment system, the concept of "smart
city" was first proposed by IBM in 2008, and there is no authoritative index and system for the
assessment of the level of urban wisdom. Deng Xianfeng (2010) constructed a wisdom city
evaluation index system from four dimensions: network interconnection, wisdom industry,
wisdom service, and wisdom humanity, and analyzed the data of Nanjing city to summarize 21
indexes. Qu Yan (2017) argues that city construction is a dynamic process, and the assessment
of smart city construction level needs to be based on five dimensions: smart technology
infrastructure construction, management system construction, economic investment, social
risk governance, and sustainable development strategy, and the regional characteristics
presented by the construction level among cities are divided into three types of smart city
construction: leading, catching up and developing. The research at home and abroad is still in
the exploratory stage, and the research is scattered and has not yet formed a system, and each
assessment system focuses on different contents and has different advantages and
disadvantages.
The problems faced are mainly: more qualitative research, not enough quantitative analysis of
the research. Most of the studies focus on the proposed and construction of the smart city index
system, and relatively little research on the construction method of the index system and the
evaluation method and measurement model of the smart city construction level, which will
inevitably affect the reliability of the index system and the scientificity of the evaluation results.
And there are a few research scholars through quantitative analysis methods and the
establishment of models to carry out systematic analysis, but the regional relevance of the study
is not strong, and the significance of the reference to the development of the city cluster driven
by Guangzhou-Foshan-Shenzhen- Dongguan in the context of the current Guangdong-Hong
Kong-Macao Greater Bay Area is not high, and the application of realistic significance is not high.
In a comprehensive view, the overall evaluation index system of smart city construction level
is lacking, and a more systematic and complete policy framework system has not yet been
formed. The article intends to take Guangzhou-Foshan-Shenzhen-Dongguan as an example,
evaluate the differences in the appropriate consumption level of each city within the city
cluster, and study the possibility and policy guidelines for taking the lead in building a smart
city cluster in the Guangdong-Hong Kong-Macao Greater Bay Area.