引言数字化转型网szhzxw.cn
科技思考：中国制造业数字化转型的特征主要有哪些？总的来说，根据中国所有A股制造业上市公司的年报文本的数字化关键词词频的挖掘统计测算，获得中国制造业企业数字化指数值。数字化总指数从二〇一一年的1.283到二〇一九年的2.666，上升幅度较大，且呈现逐年递增之势。表明最近九年尤其二〇一五年后制造业数字化转型步伐明显提速。主要得益于近年来政策的科学指引和数字技术的日趋成熟。数字化转型网szhzxw.cn
一、制造业数字化转型的总体特征分析
在已经开展数字化转型的企业中，企业在人工智能技术应用方面成绩斐然，指数值增长了近2倍，大数据技术和商业模式转型紧随其后。但云计算技术的建设应用停滞不前，指数由二〇一一年的1.228上升到二〇一九年的1.305，上升幅度很小，仅为6.27%。数字化转型网szhzxw.cn
区块链技术应用指数在二〇一二年到达峰值后，出现较大幅度的波动。表明区块链技术仍然在发展初期，企业的实践应用停留在试水层面。指数中可以看出目前的制造业企业已逐渐步入数字化转型之路。正在形成以人工智能数字技术赋能企业运营为支撑，以重塑商业模式为核心的转型态势。但仍然存在着系统性成长滞后、全面转型水平及整体生态质量不高的困境。数字化转型网szhzxw.cn
二、不同区域制造企业数字化转型的特征分析
（一）省际制造业数字化转型指数测算结果
制造业数字化不同于以往经济开放中常出现的东中西“俱乐部效应”，各个地区都在从不同方向竞逐数字赋能的“新赛道”。
例如，在商业模式指数上，江西、湖北等内陆中部省份以及西部的重庆、内蒙古、西藏、云南、广西等地重视数字化商业模式的发展，商业化指数位于前列，分析认为这些中西部地区上市公司数量少，对数字化商业模式上更为偏重，所以指数值更高。数字化转型指数中处于第一阶梯是北京、广东、湖北、天津、辽宁省份，第二阶梯包括上海、福建、陕西、江苏。数字化转型网szhzxw.cn
第三阶梯依次为浙江、河南、内蒙古、江西、四川、山东、湖南、河北、甘肃、海南地区。第四阶段依次是安徽、贵州、宁夏、吉林、重庆、云南、山西、新疆、黑龙江、广西、青海、西藏的中西部省区。
因此，总体来说，制造业数字化转型呈现东部向中西部扩散的特征，而中西部地区制造业的数字化潜能正在释放，不断缩小与发达沿海地区的差异。从地区分布来看，在数字化转型新赛道上，中西部地区虽有短板，但也不乏亮点，为东西部数字协同发展提供了基础条件。数字化转型网szhzxw.cn
（二）省际制造业数字化转型指数横向比较
二〇一九年中国制造业数字化总指数及数字化结构构成。测算结果显示：首先，从数字化结构构成来看，在“ABCDE”五类数字化模块中，全国人工智能技术指数值最大为2.408，且除西藏外各省份指数值均大于1；
其次是云技术指数平均值为1.305，其中有18省份指数大于1，16省份指数小于1，且存在海南、西藏两省份指数监测为0；再次是大数据技术指数值为1.073，其中仅有9个省份指数大于1；另外区块链技术指数最小为0.539，且只在中国16省份制造业年报中监测到；再者，全国数字化商业模式指数值为1.650，在数字化结构构成中仅次于人工智能技术，且31省份指数值均大于1。数字化转型网szhzxw.cn
最后，从中国制造业数字化总指数来看，全国层面数字化总指数为2.666，其中北京、广东、上海、天津、四川、湖北、重庆、内蒙古、云南9个省份超过了全国均值，说明中国制造业数字化程度尚有进一步提升空间，也侧面反映制造业数字化存在省际差异。数字化转型网szhzxw.cn
（三）省际制造业数字化转型指数纵向比较
二〇一一年和二〇一九年中国制造业数字化程度主要指标前十省份｡通过对比可知，二〇一一-二〇一九年，中国制造业数字化省际排名差异较大，前十省份中北京、上海、广东、湖北、内蒙古五省区排名稳步提升。
辽宁、江西、陕西、陕西、河南落榜，重庆、云南、天津、四川、浙江上榜，前十榜单有新晋有旁落说明我国制造业数字化处于转型成长期。同时，数字化技术与商业模式的应用在制造业相对较弱的省份可以发挥出后发优势，说明数字化转型有助于打破传统制造业升级的路径依赖。
随着新一轮数字技术的推广和产业集聚效应的发挥，未来可能会出现数字化的制造业产业集聚和区域结构固化。具体来看，人工智能技术指数方面，二〇一九年相比二〇一一年，北京、广东、湖北、上海、江西、河南六省区稳坐前十，青海、辽宁、陕西、福建掉落前十榜单，取而代之的是制造业基础相对较好的天津、内蒙古、四川、浙江四省区。数字化转型网szhzxw.cn
说明制造业基础相对较好的省份更有可能实现制造业人工智能的技术升级，甚至技术跃迁；大数据技术指数方面，北京和广东坚挺前三，内蒙古制造业率先运用大数据技术，后期发展速度乏力，排名从第一跌落至第十，其他省份指数差距小，在数据是关键要素的认知上有齐头并进之势；
云技术指数方面，湖北、北京、广东、福建、四川一直保持前十，值得注意的是，宁夏在与北京合作的“前店后厂”的创新模式中崛起成为云计算新城，宁夏制造业数字化指数排名也从末端翻身至第一，说明云技术是东西地区制造业联动发展的重要手段；
区块链技术指数方面，广东和山东的制造业最早试点，排名一直位于前四，区块链技术在制造业基础较好的省份运用更为广泛；数字化商业模式方面，西部地区的云南、内蒙古一直位列前十，重庆、宁夏、西藏也表现突出，东中部在数字化商业模式运用的时序上呈现先东后中西阶梯态势。数字化转型网szhzxw.cn
（四）东、中、西部制造业数字化转型指数动态演进
通过对上述测算结果的观察和分析，判断二〇一一-二〇一九年我国各省制造企业数字化进程较为迅速｡并且，通过横向、纵向比对，初步了解到我国各个省份制造业数字化发展存有一定程度的不平衡性和省际差异，需要进一步刻画出各个省份制造业数字化发展的时空特征和演化趋势。
进一步利用stata软件的Kernel密度估计处理方法，对中国各省及其三大经济带间的制造业数字化发展的非均衡性予以剖析｡描述了全国以及东部、中部和西部三大经济带制造业数字化在样本观测时间范围内的动态演变趋势。
共性之处在于：首先，从分布位置判断，全国层面以及三大经济带分布曲线中心和变化区间右移趋势均较为显著，说明样本时间范围内数字化水平总体上均呈上升趋势，这与前面各个指数的描述性统计与典型化事实保持一致。
其次，从时间分布形态判断，二〇一一-二〇一九年曲线高度明显下降，宽度明显变宽，表明随着时间的推移制造业数字化转型整体差距愈演愈烈。从极化分布来看，各个核密度估计曲线表现出不同程度的“双峰”、“三峰”甚至演变成“多峰”分布的趋势，表明我国的制造业数字化多峰形态明显，呈现数字服务多极分化现象，表明数字化蓬勃发展的大势下是存有显著区域差异的。数字化转型网szhzxw.cn
最后，从分布延展性来看，全国以及三大经济带分布曲线波形向右移动，存在显著的右拖尾状况，且其延展性呈现不同程度的拓宽趋势，这意味着全国范围内制造业数字化发展水平高的省与平均值差距在持续扩大。
不同之处在于：首先，东部区域各省制造业数字化与全国整体层面的核密度估计曲线较为相似，表明东部地区制造业数字化在全国整体层面中所起到的影响作用程度更大，东部地区Kernel密度曲线的“多峰”、“双峰”形态更加显著，表明制造业数字化在东部地区的极化现象比之全国更为严重。
其次，二〇一一-二〇一九年，中部和西部地区随着时间的推移，制造业数字化多极化状况逐步得到改善，已经逐步由多峰向双峰以及单峰过渡，分化现象在不断减弱，这表明这些省份的数字化开始不断发挥后发优势，区域内部差距在不断缩小。综合来看，东部地区的多极分化现象比中、西部更加严重，表明在制造业数字化过程中，东部地区虽有总量优势，但出现了均衡劣势。
翻译：数字化转型网szhzxw.cn
introduction
Scientific and technological thinking: What are the main characteristics of the digital transformation of China’s manufacturing industry? In general, the digitization index value of Chinese manufacturing enterprises is obtained according to the statistical calculation of digitization keyword frequency mining of the annual report text of all China’s A-share manufacturing listed companies. The digital total index increased from 1.283 in 2011 to 2.666 in 2020, and showed an increasing trend year by year. This indicates that the pace of digital transformation of manufacturing industry has accelerated significantly in the last nine years, especially after 2015. It is mainly due to the scientific guidance of policy in recent years and the increasing maturity of digital technology.
Analysis of the overall characteristics of the digital transformation of manufacturing industry
Among the enterprises that have carried out digital transformation, they have made remarkable achievements in the application of artificial intelligence technology, with the index value increasing nearly 2 times, followed by big data technology and business model transformation. However, the construction and application of cloud computing technology remained stagnant, and the index rose from 1.228 in 2011 to 1.305 in 1920, a small increase of 6.27%.
After the blockchain technology application index reached the peak in 2012, there was a relatively large fluctuation. It shows that blockchain technology is still in the early stage of development, and the practical application of enterprises remains at the level of testing the water. It can be seen from the index that current manufacturing enterprises have gradually stepped into the road of digital transformation. It is forming a transformation situation that is supported by artificial intelligence digital technology enabling enterprise operation and centered on reshaping business model. However, there are still dilemmas such as systematic growth lag, overall transformation level and low ecological quality.
Analysis of characteristics of digital transformation of manufacturing enterprises in different regions数字化转型网szhzxw.cn
(1) Calculation results of the digital transformation index of provincial manufacturing industry
The digitalization of manufacturing industry is different from the “club effect” that often appears in the past economic opening. All regions are racing for the “new track” of digital empowerment from different directions.
For example, in terms of business model index, Jiangxi, Hubei and other inland central provinces as well as western Chongqing, Inner Mongolia, Xizang, Yunnan and Guangxi attach importance to the development of digital business model, and the commercialization index is at the forefront. It is analyzed that the number of listed companies in these central and western regions is small. And they attach more importance to digital business model, so the index value is higher. The first rung of the digital transformation index is Beijing, Guangdong, Hubei, Tianjin and Liaoning provinces. While the second rung includes Shanghai, Fujian, Shaanxi and Jiangsu.数字化转型网szhzxw.cn
The third step is Zhejiang, Henan, Inner Mongolia, Jiangxi, Sichuan, Shandong, Hunan, Hebei, Gansu and Hainan. The fourth stage is the central and western provinces of Anhui, Guizhou, Ningxia, Jilin, Chongqing, Yunnan, Shanxi, Xinjiang, Heilongjiang, Guangxi, Qinghai and Tibet.
Therefore, in general, the digital transformation of manufacturing industry shows the characteristics of spreading from the east to the central and western regions. And the digital potential of the manufacturing industry in the central and western regions is being released. Constantly narrowing the difference with the developed coastal areas. From the perspective of regional distribution, in the new track of digital transformation. Although the central and western regions have weaknesses, there are also some bright spots. Which provides the basic conditions for the coordinated development of digital between the east and the west.
(2) Horizontal comparison of provincial manufacturing digital transformation index
China manufacturing digitization index and digitization Structure in 1900. The calculation results show that: first, from the perspective of digital structure. Among the five categories of “ABCDE” digital modules, the maximum value of the national AI technology index is 2.408. And the index value of all provinces except Xizang is greater than 1;
Secondly, the average value of cloud technology index is 1.305. Among which 18 provinces’ index is greater than 1,16 provinces’ index is less than 1. And there are two provinces’ index monitoring is 0, Hainan and Xizang. Thirdly, the index value of big data technology is 1.073, among which only 9 provinces have an index greater than 1. In addition, the minimum blockchain technology index is 0.539, which is only monitored in the annual reports of manufacturing industries in 16 provinces of China. Moreover, the national digital business model index value is 1.650. Second only to artificial intelligence technology in the digital structure, and the index value of 31 provinces is greater than 1.数字化转型网szhzxw.cn
Finally, from the perspective of the overall index of Chinese manufacturing digitization. The total index of digitalization at the national level is 2.666. Among which nine provinces of Beijing, Guangdong, Shanghai, Tianjin, Sichuan, Hubei, Chongqing, Inner Mongolia and Yunnan exceed the national average, indicating that the digitalization degree of Chinese manufacturing industry still has room for further improvement. And also reflects the inter-provincial differences in manufacturing digitization.数字化转型网szhzxw.cn
(3) Longitudinal comparison of provincial manufacturing digital transformation index
Top 10 provinces in China in 2011 and 2020 by main index of digitization degree of manufacturing industry. It can be seen from the comparison that there was a big difference in the provincial ranking of China’s manufacturing digitization from 2011 to 2020. Among the top ten provinces, Beijing, Shanghai, Guangdong, Hubei, and Inner Mongolia steadily improved their ranking.
Liaoning, Jiangxi, Shaanxi, Shaanxi and Henan failed to make the list. While Chongqing, Yunnan, Tianjin, Sichuan and Zhejiang made the list. The fact that there are newcomers and omissions in the top 10 shows that the digitalization of Chinese manufacturing industry is in a period of transformation and growth. At the same time, the application of digital technology and business model can play a late mover advantage in provinces with relatively weak manufacturing industry. Indicating that digital transformation can help break the path dependence of traditional manufacturing industry upgrading.
With the promotion of a new round of digital technology and the play of industrial agglomeration effect. Digital manufacturing industry agglomeration and regional structure solidification may appear in the future. Specifically, in terms of AI technology index, Beijing, Guangdong, Hubei, Shanghai, Jiangxi and Henan remained in the top 10 compared with 211 in 1920, while Qinghai, Liaoning, Shaanxi and Fujian dropped out of the top 10, replaced by Tianjin, Inner Mongolia, Sichuan and Zhejiang, which have a relatively good manufacturing base.
It indicates that provinces with a relatively good manufacturing base are more likely to realize technological upgrading and even technological transition of manufacturing AI.
In terms of big data technology index, Beijing and Guangdong rank the top three. While Inner Mongolia takes the lead in the application of big data technology in the manufacturing industry. But its development speed is weak in the later period, and its ranking falls from the first to the 10th. Other provinces have a small gap in the index. And the recognition that data is the key factor shows a trend of parallel progress.
In terms of cloud technology index, Hubei, Beijing, Guangdong, Fujian and Sichuan have always been in the top ten. It is worth noting that Ningxia has emerged as a new city of cloud computing in the innovative mode of “front shop and back factory” in cooperation with Beijing. And the ranking of Ningxia manufacturing digitalization index has also risen from the end to the first place. Indicating that cloud technology is an important means for the combined development of manufacturing industry in the east and west regions.
In terms of blockchain technology index, the manufacturing industry in Guangdong and Shandong was the first to experiment, ranking the top four all the time. Blockchain technology is more widely used in provinces with a good manufacturing base. In terms of digital business model, Yunnan and Inner Mongolia in the western region have always been among the top ten. And Chongqing, Ningxia and Tibet have also been outstanding. In terms of the time sequence of digital business model application. The eastern and central regions show a ladder trend of first east and then East and West.
(4) Dynamic evolution of digital transformation index of manufacturing industries in eastern, central and western China
Based on the observation and analysis of the above calculation results. It can be concluded that the digitization process of manufacturing enterprises in various provinces was relatively rapid in 2019-2020. Moreover, through horizontal and vertical comparison. It is preliminatively understood that there is a certain degree of imbalance and inter-provincial differences in the digital development of manufacturing industry in each province, and it is necessary to further characterize the spatio-temporal characteristics and evolutionary trends of the digital development of manufacturing industry in each province.
Furthermore, the Kernel density estimation method of stata software is used to analyze the non-equilibrium of manufacturing digitization development among China’s provinces and its three economic belts. This paper describes the dynamic evolution trend of manufacturing digitization in the whole country and the eastern. Central and western economic belts within the sample observation time range.
The commonalities are as follows:
First of all, judging from the distribution location. The center of distribution curve and the change interval of the three economic belts at the national level and at the three economic belts have a relatively significant trend of right shift. Indicating that the digitalization level in the sample time range is generally on the rise. Which is consistent with the descriptive statistics and typical facts of each index above.数字化转型网szhzxw.cn
Secondly, judging from the time distribution pattern. The height of the curve decreased significantly and the width widened significantly from 2011-2020. Indicating that the overall gap in the digital transformation of manufacturing industry became more and more acute with the passage of time. From the perspective of polarization distribution. Each kernel density estimation curve shows different degrees of “double peak”, “triple peak” and even evolved into “multi-peak” distribution trend. Indicating that Chinese manufacturing industry has obvious multi-peak form. Showing the phenomenon of multi-polar differentiation of digital services. Indicating that there are significant regional differences under the general trend of booming digital development.
Finally, from the perspective of distribution ductility. The distribution curve waveform of the country and the three economic belts moves to the right. With a significant right trailing condition. And its ductility shows a widening trend to varying degrees. Which means that the gap between the provinces with high level of manufacturing digitization development and the average is continuously expanding.数字化转型网szhzxw.cn
The differences are:
Firstly, manufacturing digitization in the eastern region is similar to the Kernel density estimation curve of the whole country, indicating that manufacturing digitization in the eastern region has a greater impact on the whole country, nd the “multi-peak” and “double-peak” kernel density curve in the eastern region is more significant. It indicates that the polarization of manufacturing digitization in the eastern region is more serious than that in the whole country.
Secondly, from 2011-2020, as time went by, the digital multipolarization of manufacturing industry in the central and western regions gradually improved, gradually transitioning from multi-peak to double-peak and single-peak, and the differentiation phenomenon was weakening, which indicated that the digitalization of these provinces began to play a late mover advantage and the intra-regional gap was narrowing. On the whole, the eastern region is divided into multiple poles.数字化转型网szhzxw.cn
本文由数字化转型网（www.szhzxw.cn）转载而成，来源：科技X先生；编辑/翻译：数字化转型网宁檬树。
免责声明: 本网站(http://www.szhzxw.cn/)内容主要来自原创、合作媒体供稿和第三方投稿，凡在本网站出现的信息，均仅供参考。本网站将尽力确保所提供信息的准确性及可靠性，但不保证有关资料的准确性及可靠性，读者在使用前请进一步核实，并对任何自主决定的行为负责。本网站对有关资料所引致的错误、不确或遗漏，概不负任何法律责任。
本网站刊载的所有内容(包括但不仅限文字、图片、LOGO、音频、视频、软件、程序等) 版权归原作者所有。任何单位或个人认为本网站中的内容可能涉嫌侵犯其知识产权或存在不实内容时，请及时通知本站，予以删除。
