A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
How to Promote a Smart City Effectively? An Evaluation Model and Efficiency Analysis of Smart Cities in China
With the rapid development of smart cities, smart city evaluation is receiving an increasing amount of attention. However, the link between the evaluation results of smart cities and the decision making of urban construction roadmap is still relatively lacking. Therefore, it is necessary to quantitatively analyze the evaluation results, to support cities to formulate specific measures for effectively improving their smartness construction. The era of big data gives us the opportunity to evaluate and improve the development of smart cities with urban data. This paper proposes a Capability–Performance–Experience (CPE) evaluation model. An empirical study was conducted with 275 Chinese cities as samples. Principal component analysis and k-means clustering were adopted to classify cities according to their infrastructure readiness level. For each category, multi-linear regression and sensitivity analysis were adopted to analyze the impact of each input factors on each output factors. The results contribute to reasonably design or adjust strategies for smart cities based on their own development stages. Some policy implications are proposed to better prioritize investment in smart cities and to maximize the return on citizens’ experience.
How to Promote a Smart City Effectively? An Evaluation Model and Efficiency Analysis of Smart Cities in China
With the rapid development of smart cities, smart city evaluation is receiving an increasing amount of attention. However, the link between the evaluation results of smart cities and the decision making of urban construction roadmap is still relatively lacking. Therefore, it is necessary to quantitatively analyze the evaluation results, to support cities to formulate specific measures for effectively improving their smartness construction. The era of big data gives us the opportunity to evaluate and improve the development of smart cities with urban data. This paper proposes a Capability–Performance–Experience (CPE) evaluation model. An empirical study was conducted with 275 Chinese cities as samples. Principal component analysis and k-means clustering were adopted to classify cities according to their infrastructure readiness level. For each category, multi-linear regression and sensitivity analysis were adopted to analyze the impact of each input factors on each output factors. The results contribute to reasonably design or adjust strategies for smart cities based on their own development stages. Some policy implications are proposed to better prioritize investment in smart cities and to maximize the return on citizens’ experience.
How to Promote a Smart City Effectively? An Evaluation Model and Efficiency Analysis of Smart Cities in China
Yufei Fang (author) / Zhiguang Shan (author)
2022
Article (Journal)
Electronic Resource
Unknown
smart city evaluation , CPE evaluation model , return on investment (ROI) , quality of experience (QoE) , principal component analysis (PCA) , multi-linear regression (MLR) , Environmental effects of industries and plants , TD194-195 , Renewable energy sources , TJ807-830 , Environmental sciences , GE1-350
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