With the development of science and technology, digital economy has penetrated into traditional manufacturing industry extensively and deeply, which has motivated the progress of the digital transformation for traditional manufacturing industry. Through comparative analysis of theoretical mechanism of synergetic development, this paper researches the order degree model and the synergy degree model based on the social shaping of technology theory to evaluate the synergetic degree of the digital transformation for China's traditional manufacturing industry. An empirical study is presented based on the proposed models and the spatial analysis method by using the statistical data of Yangtze River Delta in China from 2014 to 2019. The results were consistent with the actual situation and indicated that the model fully reflect the dynamic interaction between systems, which is a sound basis for scientific judgment and effective decision-making when seeking to the digital transformation of traditional manufacturing industry.
Citation: Yi Liu, Xuan Zhao, Feng Mao. The synergy degree measurement and transformation path of China's traditional manufacturing industry enabled by digital economy[J]. Mathematical Biosciences and Engineering, 2022, 19(6): 5738-5753. doi: 10.3934/mbe.2022268
With the development of science and technology, digital economy has penetrated into traditional manufacturing industry extensively and deeply, which has motivated the progress of the digital transformation for traditional manufacturing industry. Through comparative analysis of theoretical mechanism of synergetic development, this paper researches the order degree model and the synergy degree model based on the social shaping of technology theory to evaluate the synergetic degree of the digital transformation for China's traditional manufacturing industry. An empirical study is presented based on the proposed models and the spatial analysis method by using the statistical data of Yangtze River Delta in China from 2014 to 2019. The results were consistent with the actual situation and indicated that the model fully reflect the dynamic interaction between systems, which is a sound basis for scientific judgment and effective decision-making when seeking to the digital transformation of traditional manufacturing industry.
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