With a long industrial chain and a powerful ability to drive other industries,the automobile manufacturing industry has a prominent strategic position in the national economy.In recent years,many countries have put on...With a long industrial chain and a powerful ability to drive other industries,the automobile manufacturing industry has a prominent strategic position in the national economy.In recent years,many countries have put on their agenda the digitalization of the automobile manufacturing industry,leading to an connected,autonomous,shared,and electric(also known as CASE)①development trend in the industry.As one of the six major automobile industry clusters in China,the Chengdu-Chongqing economic circle has achieved initial results in the digital transformation of the automobile manufacturing industry.However,the region is still faced with some constraints,such as insufficient digital infrastructure,relatively slow development of new automobile products,insufficient innovation ability of the automobile industry,and complex digital transformation of small and medium-sized automobile enterprises(automobile SMEs).This paper intends to construct a framework for the mechanism of action of the digital transformation in the automobile manufacturing industry,analyze the effects of the digital transformation of the automobile manufacturing industry in the Chengdu-Chongqing economic circle,and propose feasible paths for the digital transformation of the automobile manufacturing industry in the region by drawing on domestic and international experience in this regard.The specific paths include:(a)Smoothing the“dual-core”data chain to facilitate the digital transformation of the automobile manufacturing industry;(b)Developing the new energy vehicle(NEV)industry to upgrade the quality of automobile products;(c)Achieving corner overtaking in the digital transformation of the automobile manufacturing industry with digital technology;(d)Jointly building the automobile industrial park to promote the digital transformation of the industry;(e)Addressing problems facing automobile SMEs in digital transformation via targeted policy tools.展开更多
The average relative simulation and prediction percentage errors of the new model are only 0.092%and 3.023%,respectively.The simulation and prediction errors obtained from the classical GM(1,1)and the DGM(1,1)models a...The average relative simulation and prediction percentage errors of the new model are only 0.092%and 3.023%,respectively.The simulation and prediction errors obtained from the classical GM(1,1)and the DGM(1,1)models are,respectively,2.064%and 6.980%in the first case,and 1.942%and 7.360%in the second.The findings show that the GM(1,1,4)model has the best performance,which confirms the effectiveness of the structure improvement.The new model can enhance the smoothness of the background value and weaken the effects of extreme values in the raw sequence in the model’s performance.Therefore,the simulation and prediction performances of the GM(1,1,4)model are better than those of the traditional grey prediction models.The prediction show that the ownership for automobiles in China will grow rapidly in future.Findings could help the government in formulating adjustments to the industrial structures,and facilitate making rational yield plans for automobile firms.展开更多
文摘With a long industrial chain and a powerful ability to drive other industries,the automobile manufacturing industry has a prominent strategic position in the national economy.In recent years,many countries have put on their agenda the digitalization of the automobile manufacturing industry,leading to an connected,autonomous,shared,and electric(also known as CASE)①development trend in the industry.As one of the six major automobile industry clusters in China,the Chengdu-Chongqing economic circle has achieved initial results in the digital transformation of the automobile manufacturing industry.However,the region is still faced with some constraints,such as insufficient digital infrastructure,relatively slow development of new automobile products,insufficient innovation ability of the automobile industry,and complex digital transformation of small and medium-sized automobile enterprises(automobile SMEs).This paper intends to construct a framework for the mechanism of action of the digital transformation in the automobile manufacturing industry,analyze the effects of the digital transformation of the automobile manufacturing industry in the Chengdu-Chongqing economic circle,and propose feasible paths for the digital transformation of the automobile manufacturing industry in the region by drawing on domestic and international experience in this regard.The specific paths include:(a)Smoothing the“dual-core”data chain to facilitate the digital transformation of the automobile manufacturing industry;(b)Developing the new energy vehicle(NEV)industry to upgrade the quality of automobile products;(c)Achieving corner overtaking in the digital transformation of the automobile manufacturing industry with digital technology;(d)Jointly building the automobile industrial park to promote the digital transformation of the industry;(e)Addressing problems facing automobile SMEs in digital transformation via targeted policy tools.
基金supported by National Natural Science Foundation of China(71771033)Foundation Research and Frontier Exploration in Chongqing of China(cstc2019jcyjmsxm1385)+2 种基金the Ministry of Education Humanities and Social Sciences Planning Project of China(18XJC630003)Chongqing Municipal Educational Science for the 13th-Five Year Planning Project of China(2017-GX-304)Science and technology research project of Chongqing Education Commission(KJQN201800805).
文摘The average relative simulation and prediction percentage errors of the new model are only 0.092%and 3.023%,respectively.The simulation and prediction errors obtained from the classical GM(1,1)and the DGM(1,1)models are,respectively,2.064%and 6.980%in the first case,and 1.942%and 7.360%in the second.The findings show that the GM(1,1,4)model has the best performance,which confirms the effectiveness of the structure improvement.The new model can enhance the smoothness of the background value and weaken the effects of extreme values in the raw sequence in the model’s performance.Therefore,the simulation and prediction performances of the GM(1,1,4)model are better than those of the traditional grey prediction models.The prediction show that the ownership for automobiles in China will grow rapidly in future.Findings could help the government in formulating adjustments to the industrial structures,and facilitate making rational yield plans for automobile firms.
