Development Opportunities of Taiwan’s Smart Cities from the Viewpoint of Smart Manufacturing

Wu, Yung Chang; Wu, Yenchun Jim; Wu, Shiann Ming

doi:10.1007/978-3-030-62066-0_7

Cited by 1 publication

(1 citation statement)

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“…However, Zhen [29] emphasized that the development of smart manufacturing in China should start from the transformation and upgrading of traditional industries to improve industrial competitiveness. Smart manufacturing could be implemented in not only high-end manufacturing but also in various industries [30]. Meng et al [31] investigated the factors influencing the development of traditional manufacturing to smart manufacturing and concluded that factors, such as technological innovation, policy development, and integrated interconnection, have a positive impact on the development level of smart manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Evaluation and Spatial Characteristics of Smart Manufacturing Capability in China

Xue

Wang

et al. 2022

Sustainability

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Smart manufacturing is an important development mode in the transition of China’s industry from weak to strong, and the realization of comprehensive smart manufacturing demands the coordinated efforts of all regions in China. Based on the panel data of 30 provincial administrative regions in China from 2014 to 2019, this paper constructs an index system for the development environment, infrastructure facilities, and industrial development. This paper uses methods of entropy weight TOPSIS and the dynamic comprehensive evaluation based on the time ordered weighted averaging (TOWA) operator to evaluate the smart manufacturing capability in China and analyze its characteristics of spatial difference for exploring the appropriate paths for development. The result shows that there are only two provinces, Guangdong and Jiangsu, with the values of dynamic comprehensive evaluation greater than 0.5, seven provinces with values between 0.25 and 0.5, and 21 provinces with values less than 0.25. This reflects the fact that the gradient difference in provincial smart manufacturing capability in China is obvious and most provinces are not good. The decline in the Theil index from 0.17 to 0.15 indicates that the difference in capability between provinces is narrowing, which is a good phenomenon. The increase in the Global Moran’s index from 0.1156 to 0.1478 shows that the capability in each province has a significant positive spatial correlation, and the correlation is strengthening. Moreover, during the six years, the spatial aggregation models of most provinces have not changed. The smart manufacturing capability of the Yangtze River Delta constitutes a stable high-high aggregation region. Guangdong and Chongqing have been in high-low aggregation regions for a long time, while most of the low-low aggregation regions are in the west.

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Section: Introductionmentioning

confidence: 99%