Abstract: In the era of digital economy, data as a factor of production intervenes in the economic system, and with the characteristics of almost zero marginal costs such as replicable, shareable, unlimited growth, and unlimited supply endowments, it has become a key production factor that connects innovation, activates funds, cultivates talents, and promotes industrial upgrading and economic growth. On the basis of analyzing the driving effect of data as a key production factor, a three-level model of data elements and other elements such as talents, capital, technology, and industry is proposed, and a "five-chain collaboration" mechanism of data elements and other production factors is constructed, that is, "around the industrial chain, integrated data chain, connected innovation chain, activated capital chain, cultivated talent chain" and other links, based on the fusion of multi-source heterogeneous data, the different subjects and different elements on the talent chain, capital chain and innovation chain are dynamically linked.
I. Introduction
In today's world, with the rapid development of emerging information technologies such as the Internet and the Internet of Things, the general trend of interconnection of all things and data ubiquity is becoming increasingly obvious, and data capabilities have become the core competitiveness of countries, regions and institutions. In July 2017, General Secretary Xi Jinping pointed out at the G20 Leaders' Summit in Hamburg: "95% of the world's industry and commerce are closely related to the Internet, and the world economy is moving towards digital transformation." [1] In the later stage of industrialization, with the basic completion of the industrialization process, economic and social operation began to enter a new stage in which the dynamic combination of factor chains and value chains was the main endogenous driving force, and the fourth scientific and technological revolution led by digital and intelligent technology triggered a new change in the way resources were allocated. According to statistics, at present, China's 4G users account for more than 40% of the world, optical fiber broadband users account for more than 60% of the world, and the number of cellular IoT M2M connections accounts for nearly 45% of the world. According to the Statistical Report on the Development of the Internet in China released in the second half of 2019, "As of June 2019, the scale of China's Internet users reached 854 million, mobile phone netizens reached 847 million, the Internet penetration rate exceeded 60%, and the important role of the Internet in economic and social development was more prominent." [2] China's huge group of netizens makes the speed and scale of data resources in the world maintain obvious advantages, is expected to become the world's first data resource power in 2025, the integration and application of data in all walks of life for the reconstruction and reform of production factors to create the basic conditions. To "promote the deep integration of the Internet, big data, artificial intelligence and the real economy" and "focus on accelerating the construction of an industrial system for the coordinated development of the real economy, scientific and technological innovation, modern finance, and human resources" is the direction pointed out by the 19th National Congress of the Communist Party of China for economic and social development, which means that the era of large-scale production of "dividends" of the digital economy has arrived. The Fourth Plenary Session of the Nineteenth Central Committee further proposed to add data as a new factor of production, and establish a mechanism for market evaluation contribution and remuneration according to contribution, which reflects the institutional advantages of the basic socialist economic system with Chinese characteristics that can adapt to the reality of the contemporary market to the greatest extent to liberate and develop social productive forces[3], is an important theoretical innovation of socialist political economy with Chinese characteristics, and marks the development of data production factors from the initial input stage of economic and social construction to a higher stage of economic output and social distribution. All countries in the world attach great importance to the strategic role of data elements in promoting economic and social transformation and linking other production factors. For example, the United States proposes a re-industrialization strategy, relying on high and new technologies such as data, using leverage such as finance and taxation to attract social capital and other elements to gather in emerging fields, supporting individual forces to invest in emerging industries, increasing incentives for scientific and technological innovation of private enterprises, continuously enhancing the innovation vitality of the United States, and improving the national economic growth rate. The German Industry 4.0 strategy takes "green" intelligent production as the goal, promotes the digital transformation and upgrading of the manufacturing industry, encourages manufacturing enterprises to actively apply a new generation of information and communication technology, Internet of Things technology, etc., and promotes the digital appearance of people, factories, products, etc. in the physical world; at the same time, through the accurate identification of big data analysis technology, promote the integration and development of the physical world and the virtual world such as data and network. British Industry 2050 strategy proposes that the low-cost mass production of personalized products will be the main trend of the future manufacturing industry, and should actively promote the redistribution of production resources, promote the integration of information and communication technologies, new materials and other technologies with products and production networks, change the way products are designed, manufactured, provided and even used, and improve the digital level of the production value chain. In the European Digital Agenda and the Industrial DigitalIzation Plan, the European Union highlighted that cloud computing and big data technologies will be embedded in the manufacturing production service process to improve the intelligence level of manufacturing enterprises. Based on the theoretical propositions put forward by the report of the 19th National Congress and the Fourth Plenary Session of the 19th Central Committee, this paper focuses on the case studies conducted by the research group in Fujian, Chongqing, Zhejiang, Guangdong and other places in the early stage, focusing on how to achieve linkage and collaborative innovation between data and other elements such as talents, capital, and technology as a new production factor. At the theoretical level, this paper summarizes the reconstruction model of data elements on other elements from the three levels of basic layer, support layer and integration layer; at the practical level, this paper analyzes the linkage mechanism between data and talents, capital, technology, industry and other elements from different levels such as digital industrialization, industrial digitalization and all-factor digitalization.
Second, the three-level model of data elements linked with other elements
The factor of production is the basic concept of economic theory, which is an image summary of the input of resources in economic activities. From the evolution process of economic theory, it can be found that the factors of production have experienced different stages of development from dualism to five-dimensional theory, and are constantly changing with the characteristics of the era of economic development, such as in the era of agricultural economy, the core factor of production is land, and the core factor of production in the era of industrial economy is technology and capital. At present, thanks to the development of a new generation of information technology such as edge computing, cloud computing, big data, and artificial intelligence, the new scientific and technological revolution based on the interaction of physical, social and network three-dimensional space has completely changed how people and people, people and things, things and things are connected and the way and rules of interaction. From the typical characteristics of data elements, it is clear that they have "enabling technologies" and general purpose technologies (GPTs). The so-called enablability refers to the fact that after a data and its related technical elements are put into use, the existing technical capabilities can be improved and enhanced, and a gap between the "know-what" and the "know-how" (know-how) is set up for the user, and the users and attempters of the enabling technology save time familiar with the mechanism of the technology and can quickly adapt to the technology. [4] The concept of the so-called general purpose technology is T. Bresnahan F. Bresnahan et al. [5] argue that information technology with a general purpose feature has the potential for pervasive use potential in more sectors at any given time, and that the dynamism of such information technology is more active. Along with the evolution and advancement of such general purposeful technologies, more comprehensive productivity gains can be triggered across the industry and across society. Based on this, data and its related technologies can be said to be the current general purpose technology as a typical general purpose technology, with its development and evolution has a very broad application space, and its use is not constrained and guided by any personal preference, can be subordinated to the needs of all industries and activities. At present, the academic community rarely sees a special analysis of the linkage mechanism of data elements and other elements, but some researchers have put forward some relevant theoretical views. J. Delang B. Delong)[6] believes that compared with the previous industrial technology revolutions, the emerging information technology represented by big data and artificial intelligence strengthens and extends human intelligence, rather than the human function and organizational skills strengthened by general industrial technology. Therefore, the data element is not a substitute for each enterprise itself, but it is an important means to promote effective decision-making and improve labor efficiency [7]. Liu Yuqi and Wang Qiang believe that the role of data production factors needs to form general production technical conditions of "digitization of arbitrary objects and information", "universal connection of arbitrary information", and "storage and calculation of massive information", so it is necessary to use the digital world to link the physical world and the conscious world [8]. Wang Xin [9] In summarizing the role of information technology as a whole, including data, on economic growth, Wang Xin believes that it mainly includes three levels, namely, the deepening of IT capital, the improvement of total factor productivity in the information sector, and the growth of productivity in other sectors. The above research has some inspiration for the research of this paper, based on the collaborative linkage mechanism of data elements on other innovation elements such as technology and talents at different levels, this paper believes that it can be summarized as the three basic levels of the basic layer, the support layer and the integration layer (see Figure 1).
Figure 1 Hierarchical model of data linkage with other production factors
(1) Basic layer: Digital industrialization is in the basic layer, data elements do not exist in an independent element form, but more are embedded in various digital infrastructures that support the operation of the real economy, and through hardware basic platforms such as data centers, networks, terminals, and software basic platforms such as databases and data services, we provide a basic environment for the integration of talents, capital, innovation and other elements in the real economy, and to a certain extent, solve the problem of insufficient or asymmetric information in the production and operation of enterprises. Promoting the improvement of production efficiency and operational efficiency is the added value of the information industry. It should be said that this is the lowest level at which data elements play a role in the linkage of factors, and its industrial added value and radiation driving effect are also minimal. In the initial period of informatization in the 1980s, although data was not used as an explicit production factor, it also existed in service industries such as information services and knowledge services, but the guiding role of the information industry in this period was not obvious. Even in the late 1980s, the "productivity paradox of information technology" was widely mentioned by a group of economists, represented by Steven Roach and others [10], who believed that information and related industries did not achieve the expected goals for improving the performance of various sectors of the national economy before the 1990s. However, this skepticism did not last long, and by the mid-1990s it had basically disappeared, the reason being that with the mature development of information technology and information industry, the development of digital industrialization brought about the beginning of all-factor digitization, and the correlation model between the two gradually formed and dominated.
(2) Support layer: Industrial digitalization In the stage of industrial digitalization, data begins to be fully integrated into the operation of the real economy as an independent production factor, and the results of digital technology being applied and output by the real industry can bring about the output and efficiency improvement of the original industry. T. Bowen S. Bowen[11], J. P. West et al. [12] argue that when data is integrated into business processes and becomes a basic management tool, it can provide enterprises with optimized production and management processes, allowing management knowledge to be shared and rationalized between different times and projects, fostering synergies and continued learning. As the earliest advocate of the industrial digitalization model, C. Shapiro (C. Shapiro) and V. Hal)[13] As early as the end of the 20th century, he forward-lookingly analyzed and discussed the impact of data on market structure and industrial organization, and put forward a series of theoretical views on differentiated products, complementary pricing, search costs and conversion costs, standard competition, path dependence and lock-in effects, as well as economies of scale, scope economies and network effects, precipitated capital growth and marginal capital investment reduction. At this stage, data plays a more important role than in previous periods, has become a strategic resource to drive industrial transformation and upgrading and coordinated regional development, is replacing labor and capital as factors leading production, and is dependent on efficient production and circulation and services in all aspects of the economic field. In the basic functional layer, the competitiveness of the real economy mainly comes from the cost reduction brought about by large-scale production and the industrial supporting scale effect of "supplementing the chain in groups", and the data only promotes the further reduction of costs and the further improvement of efficiency; and in the supporting functional layer, with the continuous advancement of industrial digitalization, the modern industrial economy will increasingly emphasize the dynamic formation of the industrial chain and the dynamic grouping effect, in which the data will become the core element of linking different organizations and different industrial clusters, traditional data flows, The situation in which the information flow is attached to the flow of materials has been subverted, and data has become the "brain" and "hub" that directs the operation of the real economy, and gives full play to the decisive role of the leading industrial operation. As a general-purpose technology, through extensive combination with all walks of life in the national economy, data makes the productivity of various fields continue to increase, and promotes the deep integration of formats between the primary, secondary and tertiary industries, thereby profoundly changing the production mode and organizational form of traditional industries, spawning new economic momentum, and forming new industrial models and formats.
(3) Integration layer: The digitization of all factors is in the support layer, and the role of data is mainly reflected in the digital transformation of the supply and demand side of the real economy to realize the transformation and upgrading of the commodity market in the traditional sense; in the integration layer, the role of data will be further reflected in the transformation and upgrading of the factor market, and realize the comprehensive digital and intelligent transformation of the flow of production factors such as talents, technology, capital, and management, so as to realize the digital transformation of all factors of the national economy. In this process, data and intelligent technology is not only an important foundation for industrial investment, talent training, technological innovation, and management change, but also an important basis for accelerating the rapid realization of chains, alliances, groups, network access, and deconstruction of different element chains in different industries and different regions, and data will become the glue for the smooth operation of a large and fine social production system. [14] It can be said that the process of digitization of all factors is the process of reconstructing the resource allocation status of the original industry, realizing the coordinated development and full integration of new technologies such as the Internet, big data, artificial intelligence, and blockchain with the real economy, scientific and technological innovation, modern finance, and human resources, and promoting the formation of an intelligent digital economic system. In summary, at the level of digital industrialization, the role of data elements for other elements is mainly embedded in the software and hardware information infrastructure services, and its operation rules are basically consistent with the operation rules of informatization and information industry. The following focuses on the basic path of multi-element linkage under industrial digitalization and the basic framework of all-factor digitalization based on "five-chain collaboration" from the perspective of support layer and integration layer.
Third, promote three major changes: realize the organic linkage of multiple elements with industrial digitalization
At present, the industry's definition of the digital economy generally recognizes the "G20 Digital Economy Development and Cooperation Initiative" released by the G20 at the Hangzhou Summit, which proposes: "The digital economy is a series of economic activities that use digital knowledge and information as key production factors, modern information networks as important carriers, and the effective use of information and communication technologies as an important driving force for efficiency improvement and economic structure optimization." [15] Industrial digitalization is a core component of the digital economy, and through the onlineization of resources and factors, the platform-led innovation ecosystem has realized the real-time online and sharing of data, and the automated, modeled, and continuously acquired data has become the "key production factor" driving economic growth. According to Freeman and Perez, "the change of key factors of production is the original variable driving economic growth, with the basic characteristics of falling production costs, unlimited supply capacity, and extensive application prospects" [16]. Although the generation of data requires higher cost inputs, its replication and dissemination costs are low, the marginal cost is almost zero, and the connection can generate data, and the role of wide application and data accumulation is mutually reinforcing, which is a typical "key production factor". Historically, every scientific and technological industrial revolution has brought about changes in core technologies, caused new industrial groups to arise, and led to changes in key production factors in the historical period. At present, under the general trend of the digital economy, "key factors of production will be integrated into all aspects of economic and social life as cheap input factors, and become the engine of economic growth and development at a specific stage" [17]. Under the industrial digitalization model, the endowment of data replicability, shareability, unlimited growth and supply has overcome the resource limits of traditional production factors and formed an economic development model with increasing scale and return, making sustained growth and sustainable development possible [18]. At present, China has entered a new era of high-quality economic and social development, and the "new economy" represented by the digital economy is undoubtedly an indispensable and important force to promote high-quality economic development [19], the key of which lies in the information support and transformation of data production factors to the real economy, especially the traditional manufacturing industry. Relying on the continuous innovation of Internet technology and creating a deep integration of the digital economy and the real economy, it is an all-round change to enhance the total factor productivity of the real economy, reshape the business structure, and cultivate new markets, new models and new growth points of the industry. In recent years, the development rate of China's digital economy has basically maintained an annual growth rate of more than 20%, and it has become the world's second largest digital economy after the United States, and the proportion of the digital economy in most provinces and cities in the GDP of their provinces and cities is also increasing year by year. Combined with the investigation of Guangdong, Fujian, Zhejiang and Chongqing, this paper finds that local governments in China attach great importance to the development of the digital economy, regard the digital economy as an overall move to promote high-quality development and the "bull nose" project, and explore many successful experiences in cultivating new kinetic energy with informatization and promoting new development with new kinetic energy.
(1) Promote quality change, improve the quality of the supply system of the real economy with digitalization, focus on the construction of a quality power, and build a fine management and quality control system based on new technologies such as the Internet of Things, big data, and artificial intelligence on the supply side, and promote the transformation and upgrading of traditional industries. Taking Chongqing As an example, in 2017, the city invested 30 million yuan in financial funds to support 22 manufacturing enterprises to carry out intelligent transformation, and the rate of defective products of transformed enterprises was reduced by an average of 21.8%. With the help of this intelligent transformation project, Chongqing Mag Home Furnishing Company has realized the customized intelligent production of furniture, including automatically reviewing each order, splitting orders, scheduling, and flexible production mode organized by batch, which not only realizes product zero inventory management, but also greatly improves the quality control effect of the whole process of products. Second, strengthen supervision during and after the event, build a cross-departmental, cross-industry, and cross-link product quality supervision system with big data as the main line, and promote social consumption to move towards safe, green and high-end consumption. Taking Zhejiang Province as an example, in 2017, the provincial quality supervision and inspection corps cooperated with e-commerce platform enterprises such as Ali to carry out two e-commerce product quality co-governance actions, using the problem product data found by the internal sampling of e-commerce platforms to rectify the quality of Internet e-commerce products from the source and achieve good results. Third, vigorously advance quality joint reward and punishment mechanisms based on social credit big data, and advance the sharing and connectivity of quality credit information through methods such as joint reward and punishment cases and joint reward and punishment memorandums. For example, since December 2019, multiple departments in Longgang District, Shenzhen, Guangdong Province, have joined forces to take a series of measures to jointly incentivize taxpayers with tax credit A. In November 2016, the former General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, together with the National Development and Reform Commission and 26 other departments, signed the Memorandum of Cooperation on Implementing Joint Disciplinary Action for Parties to Serious Quality Violations and Untrustworthy Acts, proposing 31 joint disciplinary action measures to jointly build a quality credit system, and more than 6,000 enterprises have issued the "Enterprise Quality Credit Report" and consciously accepted social supervision.
(2) Promote efficiency reform, promote the efficient circulation of real economic elements with digitalization, promote the gradual transformation and upgrading of the industrial system to the direction of advanced manufacturing, flexible production, precision service, and collaborative innovation, and continuously improve the level of total factor productivity and industry added value. In recent years, Chongqing has been at the forefront of using new technologies such as the Internet, big data, and artificial intelligence to reconstruct the value chain of enterprises. At present, more than 200 enterprises in the city have implemented intelligent transformation, an annual increase of more than 20%. Taking Chongqing MCC CCID as an example, its "CCID Cloud" product provides cloud-based ERP, MES, CAE analysis and other services, bringing together manufacturing communication, sharing and collaboration, connecting various tools, systems and services, and helping enterprises to gather and share the superior resources and capabilities of various fields and industries. According to statistics, after the completion of the current intelligent transformation project in Chongqing, the average production efficiency of enterprises has increased by 32.7%, the product research and development cycle has been shortened by an average of 12.5%, and the energy utilization rate has increased by an average of 8.4%. Second, with new technologies to promote the reform of "decentralization and management of services", optimize the business environment, break down the factor market circulation industry and regional barriers, fully stimulate the vitality of talents, capital, innovation and other factors, and improve total factor productivity. For example, Guangdong Province launched the People's Livelihood Service Mini Program "Guangdong Province" on the WeChat platform, and the public only needs to log in with a real name through the WeChat terminal entrance to handle high-frequency matters. Chongqing Liangjiang New Area deepened and expanded the functions of the online review platform, promoted the whole process of online processing, established a list of "no meeting" approval directories, realized the "paperless whole process electronic" processing of business licenses, and accelerated the time limit for enterprise registration and approval from the statutory 20 working days by 90%. Jiangsu Industrial Park has set up a "multi-planning" management platform to achieve unified collection, real-time update and collaborative sharing of public information in various cities, and compresses the commitment time limit for general industrial projects from project establishment to construction permit from 225 working days to 33 working days. Third, build a global data intelligence network around the layout of industrial globalization, transnational trade, and talent flow, realize the integration and aggregation of logistics, capital flow, and data flow, and improve the efficiency of opening up to the outside world and docking the global trading system. Taking Shanghai Customs as an example, in 2017, it launched the construction of a cross-border trade management big data platform, integrating enterprise data such as contracts, bookings, shipping, shipments, arrivals, tallying, etc., logistics data such as ships, routes, port arrival plans, bookings, cargo flows, and customs clearance status information, and carrying out real-time comparison and confirmation of real-time trade data of enterprises and enterprise declaration data, using digitization and cross-border information flow to promote trade and logistics security and transparency, and minimizing manual intervention. At the same time, it implements precision strikes and effective supervision of captured risk goods. (III) Promote dynamic change, accelerate the transformation of new and old kinetic energy of the real economy with digitalization, accelerate the integration of the digital economy and the real economy, and give birth to a number of new industrial digital formats and models characterized by consumption upgrading, service upgrading and industrial upgrading. Taking Qingdao Red Collar Group as an example, since 2003, it has explored the use of information technology to promote enterprise upgrading, established a customer-to-factory (C2M) business model, reduced the cost of intermediate links by about 30%, and transformed into an intelligent manufacturing enterprise based on an Internet platform. Another example is Hangzhou Ant Financial Services Group, which pioneered the "credit data service model", through the construction of a cloud computing platform for credit data sharing, through the big data analysis technology to analyze the relevant data of small and micro enterprises and individuals, to provide accurate service matching, providing a strong impetus for the upgrading of consumer service management. Second, the digital economy is closely integrated with the strategy of targeted poverty alleviation and rural revitalization, and has become a "glue" for the integration and cross-reorganization of the primary, secondary and tertiary industries in rural areas and a "catalyst" for winning the battle against poverty. Use modern information technology to promote the construction of rural information infrastructure, strengthen the interconnection of farmers and businessmen, and improve the rural industrial system. On the one hand, starting from the field, irrigating crops through Internet technology and exporting products of qualified quality, such as in the process of planting cotton, the agricultural department of the Xinjiang Production and Construction Corps applies Internet of Things technology to monitor the production status of cotton in real time, which greatly improves the quality of cotton. On the other hand, the integration and application of "Internet +" and rural e-commerce can be strengthened, and the sales channels of agricultural products can be broadened, such as in 2017, Zhangzhou City, Fujian Province, exploratorily applied "Internet +" and "Ecological +" to create a rural e-commerce poverty alleviation ecosystem model, helping 7664 poor farmers.
Fourth, promote "five-chain coordination": the basic path to realize the digitization of all elements of the economy
Any factor of production does not exist alone, nor does it play an independent role, and it needs to be coordinated with other factors to jointly support value creation. If digital industrialization and industrial digitalization are the first and second levels of data elements playing the role of the "accelerator" of the national economy, then the digitization of all factors is the third level of the role of data elements, and it is also the most important institutional arrangement to support future economic and social operations. On the one hand, the accumulation of data can support technological innovation and promote product and industrial upgrading; on the other hand, technological progress can reduce the cost of data elements, and behind the technology is talent. At the same time, the guidance of intervention funds is conducive to better promoting the flow of data elements in multiple fields, thereby forming and expanding the multiplier effect, and creating more value at multiple levels and dimensions. The report of the Nineteenth National Congress proposes to "build an industrial system for the coordinated development of the real economy, scientific and technological innovation, modern finance and human resources"[20], the essence of which is to achieve the coordinated development of the industrial chain, innovation chain, capital chain and talent chain. The premise of the organic linkage and effective response of the above four chains depends on the interspersed linkage of the "data chain" based on the Internet, with big data as the main line and driven by artificial intelligence, so as to truly lead China's economic and social development to achieve all-factor digital transformation. Based on this, this paper combines the three-level model of data elements and other elements linkage, and constructs the "five-chain collaboration" theory of "five-chain collaboration" around the industrial chain and reconstructing the innovation chain, capital chain and talent chain with the data chain.
(I) The essence of the technical economy of five-chain collaboration From the perspective of innovation economy and technical economics, the essence of "five-chain collaboration" is to realize the organic linkage and dynamic combination management of multiple value chains in the era of digital economy. Driven by the new generation of information technology, the future economic and social operation will be further networked, thus breaking the existing social division of labor model, so that the new industrial operation mode shows the characteristics of functional compounding, role diversification and service process. The original real economic activities in the framework of a clear social division of labor, and the future digital economy era of division of labor will be destroyed or reconstructed to a large extent, the past economic functions are relatively clear and single various institutional settings, such as the government, scientific research institutions, enterprises and institutions, etc. must cross each other, mutual penetration, and have the functions of other social and economic subjects, thus breaking the social clear division of labor of the mixed, integrated development characteristics. The continuous occurrence of network integration, and finally reflected in the mode of enterprise operation through the fusion trend of human information behavior, will further blur the boundaries of enterprises that have been broken and blurred again and again since the emergence of modern information technology, and further promote the blurring trend of this boundary to industry and industry. In this case, the value chain linkage of innovative elements such as talent, technology, capital, and management in modern economic activities is difficult to rely entirely on single projects to achieve, but must rely on a highly digital and intelligent information environment to achieve multi-element chain linkage with data as the link. On the other hand, the traditional single-body or discrete project implementation and management model in the past will no longer be suitable for the future needs of the digital economy, and the comprehensive industrial innovation center that realizes collaborative innovation, collaborative education, collaborative venture capital and collaborative development with data as the core will become an indispensable hub for future digital economic activities. Therefore, in the future industrial management system, the traditional linear supply chain management will give way to a dynamic, data-driven value network management system. In essence, the basic mechanism of the implementation of "five-chain collaboration" can be summarized into three basic levels (see Figure 2):
Figure 2 Schematic of the three-layer fusion mechanism of "five-chain collaboration"
The first is data fusion, that is, around the different links of the industrial chain (basic research, prototype design, industrial development, market expansion), different subjects (management departments, manufacturing departments, research and development departments, colleges and universities, investment institutions, etc.), different objects (products, funds, technologies, talents, etc.) behavior information, to build a holographic data system that describes the basic situation of industrial operation. For example, the Big Data Center of the National Development and Reform Commission has jointly developed a dynamic ontology system for the macroeconomic field from the actual needs of macroeconomic monitoring and forecasting, and has jointly developed a dynamic ontology system for the macroeconomic field, which has realized the industrial and commercial registration, employment recruitment, bidding, investment and financing, patent soft, social credit, administrative approval, and industrial and commercial registration, employment recruitment, bidding, investment and financing, patent soft, social credit, administrative approval, etc. The court's judgment and other 78 categories and 1828 indicator items are uniformly related. The second is business integration, that is, on the basis of data integration, through accurate investment, customized development, targeted education, etc., to achieve accurate docking of technology, capital, talents and other elements with the real economy. The third is value integration, on the basis of data integration and business integration, enterprise innovation activities show a modular and component trend, which will make the boundaries of enterprise operations continue to blur, resulting in the cross-cutting and intertwining of the value chains between enterprises, forming an organic value network system. Regarding the integration and management of this networked value chain, many scholars at home and abroad have discussed it. Except for Slevowski (A. In addition to the concept of a "net of values" proposed by J. Slywotzky[21] et al., A. Muhren Mulholland also proposed the concept of "mesh collaboration" for enterprises. Fan Lee (R. van Lee et al. [23] attribute the innovative model of such a corporate organization to a "megacommunities" structure and make a more systematic argument. (II) The basic path to achieve five-chain collaboration Based on the above analysis, the basic framework of "five-chain collaboration" to realize the digitization of all elements in the era of digital economy is proposed, and its basic principle can be summarized into five sentences, namely, "around the industrial chain, integrated data chain, connected innovation chain, activated capital chain, and cultivated talent chain", that is, around the different links of the industrial chain, based on the fusion of multi-source heterogeneous data, dynamically link different subjects and different elements on the talent chain, capital chain and innovation chain (see Figure 3).
Figure 3 The "five-chain collaboration" model that realizes the digitization of all elements
1. Focusing on the industrial chain, connecting the innovation chain with the data link first, continuously deepening the cooperation between schools and enterprises, and forming a collaborative mechanism between industry, academia and research. Colleges and universities and scientific research institutes are the source of innovation and an important support for the rapid development of the Internet, big data, artificial intelligence and other fields. On the one hand, it is necessary to actively guide school-enterprise cooperation and promote the enthusiasm and sustainability of applied researchers to participate in cooperation through data resource sharing and win-win benefits; on the other hand, it is necessary to give full play to the amplification role of intermediary institutions in the transformation of innovative achievements, improve the incentive mechanism for technological innovation and the patent property rights protection system, encourage technology transfer incubation, patent transactions, etc., further expand technical service capabilities, and provide a solid guarantee for the smooth landing of research and innovation results. Second, continuously promote technological innovation of enterprises and build an innovation incubation platform. With the gradual penetration of the Internet and big data technology into the real economy, all walks of life have the ability to produce data and collect data, making data development and utilization possible. At this stage, it is necessary to reverse the current situation of heavy capital accumulation and light product innovation of enterprises in the real economy, actively play the leading role of enterprise innovation, and set up a physical research and development center, based on the internal and external data resources of enterprises, driven by market demand, with enterprise development and real economic growth as the goal, to provide innovative soil for the incubation and development of new technologies and new methods. Third, cultivate large-scale and large-scale leading enterprises with strong driving force, and promote the integration strategy of the innovation chain. In the development of the industry, leading enterprises are the organizers and integrators of key resources in the industry, and have a key role in leading and coordinating. Relying on the advantages of leading enterprises in terms of production scale and data accumulation, the government will take the lead in implementing the innovation chain integration strategy, establish a collaborative innovation center for the deep integration of the Internet, big data, artificial intelligence and the real economy, gather innovation forces to the greatest extent, improve the integration and development and utilization mechanism of data resources, ensure that data collection is more accurate and timely, data mining is more accurate and thorough, and finally realize the effective integration and utilization of industrial resources, forming a multi-enterprise, multi-field, multi-dimensional innovation chain ecosystem.
2. Focus on the industrial chain, activate the capital chain first with the data link, optimize the financial policy, and give play to the guiding role of the government. The government can formulate targeted policy loans or innovation project support funds through financial subsidies or tax reductions and exemptions, support real economy enterprises to carry out information construction and big data analysis business; support forward-looking technology research and development through the establishment of special scientific research funds to promote the application of big data and artificial intelligence in the industry; through the formulation of key industry digital upgrading plans, build industrial upgrading platforms, promote and introduce key technologies, key institutions, and key projects, and promote the gradient allocation of data and industry-related resources. Second, set up an industrial fund to build a diversified investment channel. Through industrial mergers and acquisition funds, intellectual property funds and collaborative innovation funds, etc., we will build diversified investment and financing channels, make good use of the stimulating and guiding role of funds, innovate financing forms, grasp the diversified needs of private small and medium-sized enterprises with innovative needs, and promote the transformation of innovative achievements and industrialization development. At the same time, we will actively mobilize social venture capital funds, focus on the layout of the capital chain, and promote a number of social big data research institutions with strong research and development capabilities to directly provide data support and information services to enterprises in specific industries. Third, encourage data transactions and release corporate data dividends. Attract investment from real economy enterprises, establish a national industrial big data trading center, carry out operations through the joint-stock system, and mainly undertake functions such as promoting commercial data circulation transactions and the integration and application of public data and commercial data. As an industrial hub project, the data trading center can effectively promote the circulation and sharing of multi-source data and help enterprise development and economic growth.
3. Focus on the industrial chain, cultivate the talent chain first with the data link, do a good job in the reform and innovation of the talent development system, and play a good talent "first hand chess". Promoting the deep integration of the Internet, big data, artificial intelligence and the real economy is inseparable from the construction of the talent team, and talent is not only the biggest driving force for promoting industrial development, but also the biggest bottleneck restricting industrial development. On the one hand, it is necessary to combine the characteristics of high-tech development, accelerate the reform of the human resources system, accelerate the formation of a talent training system with comparative advantages, and promote the vitality of various elements of the data chain to burst forth. On the other hand, it is necessary to rely on the advantages of data clusters in key industries to build a national-level big data and real economy deep integration training platform, build a "reservoir" for data link applications, and prepare the "engine" for the development of the industrial chain. Second, create a "national data university" to create a "new magnetic field" for talents. With the organic linkage of "industrial chain - data chain - talent chain" as the goal, to create a world-class "national data university" from a global perspective, to define the deep integration of the Internet, big data, artificial intelligence and the real economy as a national key discipline, strengthen the level of basic theoretical research, increase the research and development of technology in the fields of high-end consumption, innovation leadership, green and low-carbon, sharing economy, modern supply chain, human capital services, etc., to create a fair, just and conducive to the ecological environment of scientific and technological innovation for scientific research talents. Attract talents from all over the world. Third, improve the service mechanism and stimulate the creativity of talents. Use data links to find and discover practical contradictions and prominent problems that restrict talents to play a role, take the sound service mechanism as the entry point and focus point, provide "agency-style", "one-stop" and "all-weather" services for talents at all levels, and deeply promote mechanisms and measures such as enterprise equity and dividend incentives, so that talents can inject new momentum into the deep integration of the Internet, big data, artificial intelligence and the real economy, maximize the stimulation and release of talents' innovation power and creative vitality, and continuously promote the resonance of the industrial chain, data chain and talent chain at the same frequency.
5. Summary
Starting from the basic theory of building a modern industrial system proposed in the report of the Nineteenth National Congress and the basic theory of building a data element market system proposed by the Fourth Plenary Session of the Nineteenth Central Committee, combined with local research and theoretical discussion, from the perspective of industrial economics and technological innovation economics, the synergistic linkage mechanism of data elements and other industrial elements is summarized into three levels: digital industrialization, industrial digitalization and all-factor data, respectively, the linkage mechanism and realization path at different levels are elaborated, and corresponding countermeasures are proposed. It is hoped that this study can provide useful reference for the relevant work of the industrial sector and academia.
(Author: Wang Jiandong and Tong Nannan, Department of Big Data Development, State Information Center, published in E-Government, No. 3, 2020)