智能制造对全要素能源效率的影响: Comparison
Please note this is a comparison between Version 1 by Pengfei Zhou and Version 4 by Lindsay Dong.

Intelligent technology is the core driving force of the fourth industrial revolution, which has an important impact on the high-quality economic development. First, the productivity effect, scale effect and resource allocation effect of intelligent manufacturing can significantly improve the energy efficiency of total factor, and the conclusion is still established after endogenous treatment and robustness test. Second, the results of the action mechanism show that labor price distortion and carbon emission trading policy are important mechanisms for intelligent manufacturing to improve total factor energy efficiency.智能技术是第四次工业革命的核心驱动力,对经济高质量发展产生重要影响。智能制造的生产力效应、规模效应和资源配置效应能够显着提高全要素能源效率,经过内生处理和稳健性检验后结论仍然成立。作用机制结果表明,劳动力价格扭曲和碳排放交易政策是智能制造提高全要素能源效率的重要机制。 

  • intelligent manufacturing
  • total-factor energy efficiency
  • TFEE

1. Introduction


Energy is an important cornerstone of economic and social development. Since the reform and opening-up, the China government has unswervingly pushed forward the energy revolution, and the method of energy production and utilization has undergone significant changes, basically forming an energy supply system driven by coal, oil, gas, electricity, nuclear energy, new energy and renewable energy and making historic achievements in the energy industry. Since the 19th National Congress of the Communist Party of China, the CPC Central Committee has paid more attention to the energy revolution and proposed adhering to the new development concept, building a clean, low-carbon, safe and efficient energy system, and taking firm steps in building a beautiful China. High-quality development is leading China’s economic development. When entering a new era, China’s economy faces the problem of achieving better development. After years of rapid development, the constraints of resources, environment and population on economic development are becoming increasingly obvious. The extensive development model of 能源是经济社会发展的重要基石。改革开放以来,中国政府坚定不移地推进能源革命,能源生产和利用方式发生重大变化,基本形成了以煤炭、石油、天然气、电力、核能为主导的能源供应体系、新能源和可再生能源,能源产业取得历史性成就。党的十九大以来,党中央更加关注能源革命,提出坚持新发展理念,构建清洁低碳、安全高效的能源体系,坚定不移推进能源革命。建设美丽中国的步伐。高质量发展引领中国经济发展。当进入新时代时,中国经济面临实现更好发展的问题。经过多年快速发展,资源、环境、人口对经济发展的制约日益明显。过去“三高一低”的粗放式发展模式已经过时,不利于经济持续健康发展。与此同时,“富煤、贫油、少气”的能源结构使中国陷入被动适应国际能源贸易和环境治理规则的困境。过去“三高一低”的粗放式发展模式已经过时,不利于经济持续健康发展。与此同时,“富煤、贫油、少气”的能源结构使中国陷入被动适应国际能源贸易和环境治理规则的困境。过去three highs and one low” in the past has been exhausted, which is not conducive to sustained and healthy economic development. At the same time, the energy structure of “rich in coal, poor in oil and less in gas”三高一低”的粗放式发展模式已经过时,不利于经济持续健康发展。与此同时,“富煤、贫油、少气”的能源结构使中国陷入被动适应国际能源贸易和环境治理规则的困境。1 makes]。经济发展面临环境污染和能源短缺的双重制约,能源安全容易受到威胁[ China fall into the dilemma of2 passively adapting to international energy trade and environmental governance rules. Economic development faces the dual constraints of environmental pollution and energy shortage, and3 energy]。能源作为经济发展的首要投入要素,发挥着至关重要的作用,被视为经济增长的重要助推器[ security4 is vulnerable to threats. As the primary input factor of economic development, energy5 plays]。中国是世界上最大的能源消费国[ a6]],特别是在煤炭价格优势显着的前提下,未来较长时期内煤炭消费结构难以扭转。 vital role and has been regarded as an essential economic growth booster. China is the world’s largest energy consumer, and especially under the premise of the significant price advantage of coal, it will be difficult to reverse the consumption structure of coal for a long time in the future. In 2020, China imported 303.99 million tons, up 1.5% yearly; crude oil imports were 542.39 million tons (including 28.35 million tons of refined oil products), up 7.3% year on year, and overall energy imports have shown an upward trend in recent years. This means that it is still difficult to address the short- and medium-term energy constraints by increasing the proportion of renewable and clean energy consumption. In this regard, the report of the 19th CPC National Congress pointed out that “improving total factor productivity is an important and reliable path to achieve high-quality economic development.” How to improve total-factor energy efficiency (TFEE), effectively control the total energy consumption and complete the “14th Five-year Plan” unit GDP energy consumption reduction target of 13.5% has become the urgent proposition of the present time.年中国进口30399万吨,同比增长1.5%;原油进口54239万吨(其中成品油2835万吨),同比增长7.3%,近年来能源进口总体呈上升趋势。这意味着通过提高可再生能源和清洁能源消费比重来解决中短期能源约束仍较困难。对此,党的十九大报告指出,“提高全要素生产率是实现经济高质量发展的重要而可靠的路径”。如何提高全要素能源效率(TFEE),有效控制能源消费总量,完成“十四五”单位GDP能耗下降13.5%的目标已成为当前的紧迫命题。
Wright first put forward the concept of 赖特首先提出了intelligent manufacturing,”智能制造”的概念,指出智能制造是智能机器人通过集成知识工程、制造软件系统和机器人视觉,在无需人工干预的情况下自行完成小批量生产的过程[7 pointing out that intelligent manufacturing is a process in which intelligent robots complete small batch production by themselves without human intervention by integrating knowledge engineering, manufacturing software systems, and robot vision [7]]. With the acceleration of the new wave of the digital and intelligent technological revolution, 。随着新一轮数字化、智能化技术革命的加速,IM的发展被赋予了新的内涵。随着近几十年来计算机集成制造、柔性制造、敏捷制造等相关先进制造理念的共同发展,IM has been endowed with new connotations in its development. With the joint development of its related advanced manufacturing concepts such as computer-integrated manufacturing, flexible manufacturing, and agile manufacturing in recent decades, the concept of “intelligent” in IM has been upgraded and broadened from the original narrow sense of “digital” to the current “digital,中的“智能”概念已从原来狭义的“数字化”升级和拓宽。当前的“数字化、网络化、智能化”[ networked8 and intelligent. In addition to automatic and unmanned production, the more profound role of 9]。除了自动化、无人化生产之外,IM lies in helping enterprises to realize mass production to customized production through its 更深刻的作用在于通过其Prosumption” mechanism, which not only improves production efficiency but also optimizes resource allocation. IM生产”机制帮助企业实现大规模生产到定制化生产,不仅提高了生产效率,而且优化了资源配置。 IM可以理解为新一代信息技术与先进的自动化、传感、控制、数字、管理技术以高度灵活、高度集成的方式结合在制造业的各个阶段。它还支持工厂和企业内部和之间以及产品的全生命周期(产品开发设计、生产加工、运营管理、维护服务、报废处理)的实时管理和优化[ can1011 be understood as combining the new generation of information technology with advanced automation, sensing, control, digital, and management technology in a highly flexible and highly integrated way at all stages of the manufacturing industry. It also supports the real-time management and optimization within and between factories and enterprises, as well as the whole life cycle of products (product development and design, production and processing, operation management, maintenance service, and scrap disposal). As there is no unified definition of IM, scholars draw lessons from the Development Plan of Intelligent Manufacturing (2016–2020). It holds that IM is a new mode of production with the functions of self-perception, self-learning, self-decision-making, self-execution, and self-adaptation based on the deep integration of the new generation of information and communication technology and advanced manufacturing technology, which runs through all aspects of manufacturing activities such as design, production, management, and service.]。
In在绿色低碳发展中,能源产业是主战场[ green12 and low-carbon development, the13 energy industry is the main battlefield. Improving ]。提高TFEE成为短期内实现绿色经济目标最可行、最现实的手段[ becomes the14 most feasible and realistic means of achieving green economy goals in the short term. However, the current single-terminal governance model has struggled to meet the demand for improving 15]。然而,目前的单一终端治理模式已经难以满足改进TFEE.的需求。数字技术与自然经济发展融合,正在成为重塑高质量发展竞争力的现实选择。智能系统依靠深度学习、自主决策、动态监测,能够有效、快速地提供应对措施,帮助原材料供应、中间品运输、能源生产等上游环节高效衔接,不仅节省能源,企业的时间成本、交易成本和运输成本,同时也在此基础上绘制更加合理的能源供应蓝图,提高全市能源综合利用效率[16 The integration of digital technology and natural economy development is becoming a realistic choice to reshape the competitiveness of high-quality development. The intelligent system relies on deep learning, independent decision-making, and dynamic monitoring, which can effectively and quickly provide countermeasures and help the upstream links such as raw material supply, intermediate goods transportation, and energy production to connect efficiently, which not only saves the time cost, transaction cost and transportation cost of enterprises, but also draws a more reasonable blueprint for energy supply on this basis, and improves the comprehensive utilization efficiency of energy in the whole city. According to the data of “World ]]。国际机器人联合会(IFRobots )发布的《世界机器人2021 Industrial Robots” released by the International Federation of Robotics (IFR), in 2020, nearly 168,000 industrial robots will have been newly installed in China, accounting for 43.8% of the world, and the level of automation and intelligence in the manufacturing industry is increasing day by day. The research report “Accelerating Energy Transformation by Using Artificial Intelligence,” released by the World Economic Forum in 2021, pointed out that artificial intelligence technology has great productivity in the process of energy decentralization, digitization, and decarbonization, and it has strong application in renewable energy generation capacity and demand forecasting, power grid operation and optimization, energy demand, and distributed resource management. The report “Digital Energy 2030” released by Huawei also pointed out that digital technology can make the intelligent evolution of energy systems and promote the maximization of energy value, which is the core “pry point” to drive the transformation of the energy industry. From the perspective of intelligent manufacturing, exploring its impact on TFEE is of great reference value for ensuring national energy security, achieving the goal of “double carbon,” and accelerating the construction of energy power.

2. Impact of Intelligent Manufacturing on Total-Factor Energy Efficiency

2.1. The Mechanism Analysis of IM Affecting TFEE

Productivity effect: 工业机器人》数据显示,2020年,我国新增工业机器人近16.8万台,占全球的43.8%,制造业的自动化、智能化程度日益提高。世界经济论坛2021年发布的研究报告《利用人工智能加速能源转型》指出,人工智能技术在能源分散化、数字化、脱碳化过程中具有巨大生产力,在可再生能源领域具有强大应用能源发电能力和需求预测、电网运行和优化、能源需求和分布式资源管理。华为发布的《数字能源2030》报告也指出,数字技术可以让能源系统智能化演进,促进能源价值最大化,是驱动能源行业转型的核心“撬点”。从智能制造的角度探讨其对TFEE的影响对于保障国家能源安全、实现“双碳”目标、加快能源强国建设具有重要参考价值。探讨其对TFEE reflects the input–output efficiency of electric energy, coal, oil and natural gas in production and life. Technological progress means expanding the forefront of production through technological improvement, human capital accumulation and organizational management efficiency improvement, so as to improve the maximum output capacity under the established factor combination input. A typical example of the 的影响对于保障国家能源安全、实现digital intelligence” of the real economy is the rapid popularization and large-scale application of intelligent robots in the industrial sector. By introducing big data in the process of traditional production and modern digital technology such as artificial intelligence, “intellectualization” can effectively improve the operation efficiency of different factors of production configuration combination to realize the traditional factors of production of marginal output, help traditional enterprises “old tree sprout”, and fully promote the real economy sector to adapt to the new requirements of digital economy development. As the IM of neutral technology progress, it naturally carries the penetration, synergy, and substitution characteristics of digital technology, which can penetrate all fields of social life. On the one hand, the existence of Moore’s Law makes the chip-based, digital and information-based products constantly updated, and the prices of related products will also drop rapidly with the change and popularization of technology, which will help related manufacturers to gradually phase out production equipment with high energy consumption and low efficiency, thus reducing energy consumption and improving marginal energy productivity. On the other hand, related industry standards and customer demand will be improved with the improvement of labor productivity, process technology, and production process. More stringent factory standards and high-level market demand will lead to the derivative demand of enterprises for high efficiency, cleanliness, and high quality. 双碳”目标、加快能源强国建设具有重要参考价值。探讨其对TFEE的影响对于保障国家能源安全、实现“双碳”目标、加快能源强国建设具有重要参考价值。

测量和评估 TFEE

现有文献构建的Therefore, enterprises can hedge the negative effects of increasing production costs and intensifying market competition by reducing total energy consumption, using intensity, and improving energy utilization efficiency.
FEE评价指标体系分为单因素能效(Scale effect: FEE)和The most striking feature of emerging technologies is to replace low-skilled labor and supplement high-skilled labor. This will relieve the dependence of enterprises on labor factors through digitalization, informatization, and intelligence, quickly complete the repetitive tasks of packaging, sorting, and transit that human labor cannot complete in a short time, and use the same energy consumption and labor to obtain greater economic output, to improve the total factor productivity of enterprises. IM, in the process of intelligent activities, involves the collaborative interaction and cooperation of people and intelligent machines and uses the concept of automation for flexible, intelligent and highly integrated working, so as to realize traditional factory to digital factory transformation, which makes manufacturing enterprises, through digital development, improve product quality and management efficiency. A mature, intelligent manufacturing factory or enterprise often does not simply transform its production equipment intelligently but integrates market demands and consumer demands into production processes and product design. All aspects of product production are connected in series with the help of intelligent products, intelligent design, intelligent production, and intelligent management. Enterprise managersFEE。但随着研究的深入,SFEE指标也存在一些缺陷;也就是说,只考虑了能源投入因素,没有考虑资本、劳动力等因素,而TFEE指数可以极大地补偿能源消耗、劳动力、资本等因素对产出的影响。李等人。 [ use technologies such as the Internet and the Internet of 18]通过比较单因素法和全因素法计算了中国各地区的Things to realize horizontal integration and vertical expansion of intelligent production, and then use mobile communication technology and intelligent equipment to realize digital transformation of the whole intelligent production value chain, thus forming and smoothing the whole intelligent management system. FEEnterprises also introduce industrial robots and high-tech talents, expand production scale, promote the continuous improvement and extension of related industrial chains and supply chains through economies of scale, and improve resource utilization efficiency.
Resource allocation effect: IIM can reduce energy consumption per unit output and improve comprehensive ,指出全因素法在评价区域要素禀赋影响方面具有单因素法无法替代的优势其 TFEE. A typical example is that the traditional energy industry only pays attention to watt flow, and the nodes of power generation, transmission, distribution, storage, and use are isolated, making it cooperate, resulting in low operating efficiency of the energy system. Moreover, there are many “dumb devices” in the full link, and the operation and maintenance efficiency are low with manual maintenance. IM digitally processes energy by introducing digital technologies such as 5G, AI, and big data, innovatively integrates power electronics technology with digital technology, adds bit streams based on watt flow, and manages watts with bits to realize complete link interconnection, digitization, and intelligent collaboration and to maximize power production efficiency, equipment operation and maintenance efficiency and TFEE. In addition, at the present stage, the world’s energy system is undergoing structural restructuring and map reconstruction: centralized and decentralized variable renewable energy is incorporated into the power grid, the electrification trend of energy consumption is becoming increasingly prominent, and consumers involved in production activities are emerging. Energy demand flexibility features increasingly emphasize the timeliness and efficiency of the energy supply. Energy digitization enables intelligent buildings, transport, vehicles, and industrial facilities to provide new flexible load sources for energy systems, helping suppliers cut energy supplies and supporting communities to better consume the energy they produce. By improving the use efficiency of end users and system efficiency, the entire energy system will benefit from avoiding repeated investments in energy facilities, reducing ineffective losses in production and distribution, optimizing the combination of renewable resources, and enhancing energy security. As a general progression in technology, IM itself represents typical non-competitive public goods. When it performs innovation activities in a certain area, it will often produce “energy上的结构。 TFEE的测量主要基于非参数估计方法中的DEA方法。例如,Hu和Wang[ technology19 diffusion” and “energy technology spillover”, that is, the unconscious outflow of technological innovation and the unconscious acceptance of relevant subjects. The spillover effect of IM is specifically manifested in the embedding of the automation technology of machinery and equipment into the application department, realizing the interaction between factor input and science and technology in the production link, and then promoting the production, transportation, storage and consumption to form a new enterprise production mode and the new energy technology and equipment, energy conservation and environmental protection awareness. At the same time, the artificial intelligence platform contributes to the sharing of data elements. With the help of factor circulation and knowledge technology spillover, it builds an intelligent management system of energy interconnection and global energy allocation network and integrates traditional chimney independent system architecture and remote island management into a unified architecture, unified management, and comprehensive application to realize overall planning, coordination, and optimization of the whole link, thereby promoting low-carbon development of the whole society and improving energy utilization efficiency. The combination of artificial intelligence technology and traditional factors of production can effectively improve the allocation quality and combination efficiency of the original factors of production by expanding the application scenarios of digital energy and upgrading digital management, thus enhancing the coordination of organization and management of production enterprises and the overall efficiency of factors. For example, ]基于输入Datang Group Co., Ltd. (Beijing, China), China realizes a 3D virtual power plant through advanced communication technology and software architecture and realizes the aggregation, coordination, and optimization of spatial and geographical dispersion. Its intelligent control system controls the power production process in real-time and completes energy storage and rational allocation. Accordingly, The productivity effect, scale effect and resource allocation effect of IM carrying can improve the TFEE.

2.2. The Intermediary Path of Labor Price Distortion

InEA方法测算了中国各省份的TFEE。此类研究通常将全要素衡量效率分解为纯技术效率和规模效率[ the20]。同时,还有一小部分文献致力于根据生产函数建立包含能源要素的单部门生产模型,属于参数估计[ neoclassical21 economic growth theory, the primary source of total factor productivity improvement lies in technological progress and resource allocation efficiency. ]。在The price mechanism is the essential reflection of the allocation of resources in the market economy. However, the distorted factor price cannot truly reflect the scarcity degree and the relationship between the supply and demand of resources in the factor market. Factors of production are the starting point of the economic cycle, and the distortion of factor price will affect the macroeconomic variables such as consumption, investment, total output and total factor productivity by affecting the efficiency of resource allocation. The loss of production efficiency caused by ineffective factor allocation or overcrowding is considered an essential factor in reducing the efficiency of resource allocation and even the welfare of residents in a country. Moreover, existing studies find that the contribution of the improvement of factor allocation efficiency to the improvement of total factor productivity is improved. The labor factor has strong initiative and adsorption and is an important link to other factors of production, knowledge, technology, management, and data elements attached to the labor itself and through the labor bridge to achieve activation and operation. However, the distorted labor market not only may make the resource allocation imbalanced between enterprises but will also stop the efficient enterprises entering the market, therefore producing greater efficiency loss.
Currently, China’s labor price is mainly manifested as low price distortion, the remuneration of labor suppliers is lower than the marginal contribution, and the price distortion in less developed areas is severe. Underestimated labor remuneration will enable enterprises with low production efficiency to use many tangible low-cost factors to obtain more profits. The arbitrage space formed by it will lead to a large number of laborers flowing to extensive production projects with quick results and low uncertainty, which will make economic growth stand out as factor-driven epitaxial growth, aggravate the low-end lock-in of industrial structure, and is not conducive to the improvement of TFEE测量方法中,能源使用过程中造成的环境污染问题并未纳入测量范围,因此有可能高估TFEE。因此,为了填补这一空白,一些研究将 inSO the2、废水、固体废物或碳排放纳入 production process . DEAs far as labor price distortion is concerned, negative price distortion causes enterprises to have the illusion that labor elements are vibrant, and then they will hire cheaper labor. This price 模型中,以测量包含非期望输出的 TFEE [ advantage22 of low-cost labor reduces the demand of enterprises for capital factors and technological innovation attached to capital goods, which makes managers stay in low-end production links for a long time, resulting in a low contribution of technological progress to 23]。此外,有研究将能源枯竭、生态环境恶化等非预期产出纳入效率测度模型,测算省级TFEE.,发现存在“东部高、东部低”的空间差异。西”[ In24 addition, the distortion degree of labor factors is different in different regions, and there is regional heterogeneity in the distortion degree of factor prices. ]。为了获得更准确的ThisFEE数据信息,相关统计模型和评估体系不断更新和扩展[ difference25 will cause the price of labor factors in some areas to be seriously underestimated, which will enable those enterprises that should have been eliminated by the market to continue their production and business by moving and transferring to lower-cost areas. ]。


2.1. IM影响TFEE的机制分析

生产力效应:This aggravates the dilemma of low-end locking of industrial structure in those areas where labor-intensive industries are the leading industries, and it is difficult to develop the rationalization and upgrading of industrial structure, which is not conducive to technological progress and the improvement of TFEE.
Guiding反映了生产生活中电能、煤炭、石油、天然气的投入产出效率。技术进步是指通过技术改进、人力资本积累和组织管理效率提高,扩大生产前沿,提高既定要素组合投入下的最大产出能力。实体经济“数字化智能化”的典型例子就是智能机器人在工业领域的快速普及和规模化应用。通过在传统生产过程中引入大数据和人工智能等现代数字技术,“智能化”可以有效提高不同生产要素配置组合的运行效率,实现传统生产要素的边际产出,帮助传统企业“老树发芽”,全面促进实体经济领域适应新要求。数字经济发展[44 the labor force with higher human capital to flow to the regions, departments, and industries with advanced productive forces will help to improve the total factor productivity. ]。随着中立技术进步的IM,天然承载着数字技术的渗透性、协同性、替代性特征,可以渗透到社会生活的各个领域[ has45]]。一方面,摩尔定律的存在使得芯片化、数字化、信息化的产品不断更新,相关产品的价格也会随着技术的变革和普及而迅速下降,这将有助于相关厂商逐步淘汰能耗高、效率低的生产设备,降低能源消耗,提高能源边际生产率。另一方面,相关行业标准和客户需求将随着劳动生产率、工艺技术、生产工艺的提高而提高。更严格的工厂标准和高水平的市场需求,将引发企业对高效、清洁、高质量的衍生需求。所以,企业可以通过降低能源消耗总量、使用强度、提高能源利用效率来对冲生产成本增加和市场竞争加剧的负面影响。 规模效应:新兴技术最显着的特点是替代低技能劳动力、补充高技能劳动力。这将通过数字化、信息化、智能化缓解企业对劳动力要素的依赖,快速完成人力短时间内无法完成的包装、分拣、中转等重复性任务,用相同的能耗和劳动力获得更大的经济产出,提高企业全要素生产率[ substantial46]]。 advantages in correcting the distortion of the labor factor market, unimpeded factor channel, and strengthening the efficiency of resource allocation. First, the rapid development of intelligent technology with the underlying logic of IM在智能化活动过程中,涉及人与智能机器的协同交互与配合,利用自动化的理念进行柔性化、智能化、高度集成化的工作,从而实现传统工厂向数字化工厂的转变,使制造企业、通过数字化开发,提高产品质量和管理效率。一个成熟的智能制造工厂或企业往往不是简单地对生产设备进行智能化改造,而是将市场需求和消费者需求融入到生产流程和产品设计中。产品生产的各个环节借助智能产品、智能设计、智能生产、智能管理串联起来。企业管理者利用互联网、物联网等技术,实现智能生产的横向整合和纵向拓展,再利用移动通信技术和智能设备,实现整个智能生产价值链的数字化转型,从而形成和打通全程智能管理系统[47 helps to reduce the cost of information search and simplify the collection path. With the help of ]。企业还引进工业机器人和高新技术人才,扩大生产规模,通过规模经济推动相关产业链、供应链不断完善和延伸,提高资源利用效率。 资源配置效应:Internet technology, workers can collect, sort out, compare and analyze information such as job salary, skill demand, and labor demand to form accurate information about the rationality of labor remuneration and help reduce market information asymmetry. At the same time, they can simplify the market transaction business process and improve the information transparency of the transaction process to form a nationwide network transaction system, to a certain extent, to reduce the market segmentation formed by local protectionism and administrative barriers and to reduce price distortion. Second, the Internet technology-derived network platform has weakened the physical barriers of distance and time, information can be spread more quickly across regions and across time, cross-sectoral transmission and sharing can occur, element demanders and labor suppliers can combine their expectations in broader market-accurate matching, saving transaction cost time, thus opening free flow channels for labor elements, and the level of factor–market integration can be improved. New online working methods, such as telecommuting, online meetings, and remote services, enable workers to participate in the division of labor in the whole of society without changing their residence and workspace, forming invisible mobile labor, and following the trajectory of a low rate of return to a high rate of return, therefore reducing price distortion. Third, the market impact of IMM可以降低单位产出能耗,提高综合TFEE。一个典型的例子是,传统能源行业只关注瓦特流量,发电、输电、配电、存储、使用等节点相互孤立,使其相互配合,导致能源系统运行效率低下。而且全链路“哑设备”较多,人工维护运维效率低。 IM通过引入5G、AI、大数据等数字技术对能源进行数字化处理,创新性地将电力电子技术与数字技术融合,基于瓦流添加比特流,用比特管理瓦特,实现全链路互联、数字化、和智能协作,最大限度地提高电力生产效率、设备运维效率和TFEE。此外,现阶段世界能源体系正在进行结构调整和版图重构:集中式和分散式可变可再生能源并入电网,能源消费电气化趋势日益凸显,消费者参与生产活动正在涌现。能源需求的灵活性特征越来越强调能源供应的及时性和效率。能源数字化使智能建筑、交通、车辆和工业设施能够为能源系统提供新的灵活负载源,帮助供应商减少能源供应并支持社区更好地消耗他们生产的能源。通过提高终端用户的使用效率和系统效率,整个能源系统将受益于避免能源设施的重复投资,减少生产和分配中的无效损失,优化可再生资源的组合,增强能源安全。作为一种普遍的技术进步,即时通讯本身就代表了典型的非竞争性公共产品。当其在某一领域进行创新活动时,往往会产生“能源技术扩散”和“能源技术溢出”,即技术创新的无意识流出和相关主体的无意识接受。避免能源设施的重复投资、减少生产和分配的无效损失、优化可再生资源组合、增强能源安全,将使整个能源系统受益。作为一种普遍的技术进步,即时通讯本身就代表了典型的非竞争性公共产品。当其在某一领域进行创新活动时,往往会产生“能源技术扩散”和“能源技术溢出”,即技术创新的无意识流出和相关主体的无意识接受。避免能源设施的重复投资、减少生产和分配的无效损失、优化可再生资源组合、增强能源安全,将使整个能源系统受益。作为一种普遍的技术进步,即时通讯本身就代表了典型的非竞争性公共产品。当其在某一领域进行创新活动时,往往会产生“能源技术扩散”和“能源技术溢出”,即技术创新的无意识流出和相关主体的无意识接受。作为一种普遍的技术进步,即时通讯本身就代表了典型的非竞争性公共产品。当其在某一领域进行创新活动时,往往会产生“能源技术扩散”和“能源技术溢出”,即技术创新的无意识流出和相关主体的无意识接受。作为一种普遍的技术进步,即时通讯本身就代表了典型的非竞争性公共产品。当其在某一领域进行创新活动时,往往会产生“能源技术扩散”和“能源技术溢出”,即技术创新的无意识流出和相关主体的无意识接受。48]。 on employment is mainly produced through productivity efficiency, compensation effects, and destructive effects. IM的溢出效应具体表现在将机械设备自动化技术嵌入到应用部门,实现生产环节要素投入与科学技术的互动,进而促进生产、运输、储存和消费形成新的企业生产模式和新能源技术装备、节能环保意识。同时,人工智能平台有助于数据要素的共享。借助要素流通和知识技术溢出,构建能源互联和全球能源配置网络的智能管理系统,将传统烟囱独立系统架构和孤岛管理整合为统一架构、统一管理、综合应用,实现全链路统筹协调、优化,从而促进全社会低碳发展,提高能源利用效率。人工智能技术与传统生产要素的结合,通过拓展数字能源的应用场景、升级数字化管理,可以有效提高原有生产要素的配置质量和组合效率,从而提高生产企业组织管理的协调性和要素的整体效率。例如,中国大唐集团有限公司(中国北京)通过先进的通信技术和软件架构实现了3D虚拟电厂,实现了空间和地理分散的聚合、协调和优化。其智能控制系统实时控制电力生产过程,完成能量储存和合理分配。其智能控制系统实时控制电力生产过程,完成能量储存和合理分配。其智能控制系统实时控制电力生产过程,完成能量储存和合理分配。


在新古典经济增长理论中,全要素生产率提高的首要源泉在于技术进步和资源配置效率[ technology49 uses]。价格机制是市场经济条件下资源配置的本质体现。然而,扭曲的要素价格并不能真实反映要素市场资源的稀缺程度和供求关系。生产要素是经济周期的起点,要素价格扭曲会通过影响资源配置效率,影响消费、投资、总产出、全要素生产率等宏观经济变量[50 technological]]。要素配置无效或过度拥挤造成的生产效率损失被认为是降低一国资源配置效率乃至居民福利的重要因素。而且,现有研究发现,要素配置效率的提高对全要素生产率提高的贡献度提高[ advantages51 and capital advantages to replace conventional, programmable52 ]]。劳动力要素具有较强的能动性和吸附性,是连接其他生产要素的重要纽带,知识、技术、管理、数据要素依附于劳动力本身并通过劳动力桥梁实现激活和运行。然而,扭曲的劳动力市场不仅可能使企业之间的资源配置失衡,而且会阻碍有效率的企业进入市场,从而产生更大的效率损失[ rules of labor53, and human labor has the comparative advantage of new tasks,54,55 economic] 目前,我国劳动力价格主要表现为低价扭曲,劳动力供给者报酬低于边际贡献,欠发达地区价格扭曲严重[ activities, and work forms56 being constantly created; different skills of workers in the digital technology leads to the higher efficiency of the digital industry and needs to be implemented in emerging jobs to achieve efficient matching and obtain more reasonable labor remuneration. Accordingly, IM57 can improve ]。低估的劳动报酬将使生产效率低下的企业利用许多有形的低成本要素来获取更多的利润。其形成的套利空间将导致大量劳动力流向见效快、不确定性低的粗放型生产项目,使经济增长突出为要素驱动的外延式增长,加剧工业低端锁定。结构,不利于生产过程中TFEE的提高[ by mitigating labor price distortions.

2.3. The Moderating Effect of the Carbon Emission Trading Policy

Coase Property Rights 58]。就劳动力价格扭曲而言,负的价格扭曲会让企业产生劳动力要素活跃的错觉,从而雇佣更便宜的劳动力。这种低成本劳动力的价格优势,降低了企业对资本要素的需求以及依附于资本品的技术创新,使得管理者长期停留在低端生产环节,导致技术进步对TheoryFEE的贡献较低。此外,不同地区劳动力要素扭曲程度不同,要素价格扭曲程度也存在地区异质性。这种差异会导致部分地区劳动力要素价格被严重低估,使那些本应被市场淘汰的企业,通过向成本较低的地区转移、转移,继续生产经营。这加剧了以劳动密集型产业为主导产业的地区产业结构低端锁定的困境,产业结构合理化和升级难以开展,不利于技术进步和生产力水平的提高。 shows that under the premise that property rights can be clearly defined, spontaneous market transactions can realize the Pareto optimal resource allocation. TheTFEE。 引导人力资本较高的劳动力向生产力先进的地区、部门、行业流动,有利于提高全要素生产率。 profoundIM在纠正劳动力要素市场扭曲、畅通要素通道、强化资源配置效率等方面具有显着优势。首先,以IM为底层逻辑的智能技术的快速发展,有助于降低信息搜索成本、简化采集路径。借助互联网技术,劳动者可以对岗位薪资、技能需求、劳动力需求等信息进行收集、整理、比较和分析,形成劳动报酬合理性的准确信息,有利于减少市场信息不对称。同时,可以简化市场交易业务流程,提高交易过程的信息透明度,形成覆盖全国的网络交易体系,在一定程度上减少地方保护主义和行政壁垒形成的市场分割,减少价格扭曲。51 logic of carbon emission trading policy is the commercialization, asset,59]。其次,互联网技术衍生的网络平台弱化了距离和时间的物理障碍,信息可以更快速地跨地域、跨时间传播,可以实现跨部门的传输和共享,要素需求者和劳动力供给者可以将各自的期望结合起来。更广泛的市场精准匹配,节省交易成本时间,从而打通劳动力要素自由流动渠道,提高要素市场一体化水平。远程办公、在线会议、远程服务等新型线上工作方式,使劳动者在不改变居住地、工作场所的情况下,参与全社会分工,形成隐形流动劳动力,走上低费率轨迹。回报率达到高回报率,从而减少价格扭曲。第三,IM对就业的市场影响主要通过生产力效率、补偿效应和破坏效应产生。 andIM技术利用技术优势和资本优势取代传统的、可编程的劳动规则,人类劳动具有不断创造新任务、经济活动和工作形式的比较优势;数字技术中劳动者的不同技能导致数字产业的效率更高,需要落实到新兴岗位上,实现高效匹配,获得更合理的劳动报酬。劳动规则可编程,人类劳动具有不断创造新任务、经济活动、工作形式的比较优势;数字技术中劳动者的不同技能导致数字产业的效率更高,需要落实到新兴岗位上,实现高效匹配,获得更合理的劳动报酬。劳动规则可编程,人类劳动具有不断创造新任务、经济活动、工作形式的比较优势;数字技术中劳动者的不同技能导致数字产业的效率更高,需要落实到新兴岗位上,实现高效匹配,获得更合理的劳动报酬。


科斯产权理论表明,在产权能够明确的前提下,自发的市场交易可以实现帕累托最优的资源配置。碳排放交易政策的深刻逻辑是碳排放权的商品化、资产化、数据化。通过限制控制企业温室气体排放和排放配额,借助市场机制将环境负外部成本转化为企业内部生产成本,反向传导控制完成绩效条件,推动碳市场达到帕累托最优局面,最终实现整个经济社会的能源利用质量和效率、节能减排[ data6061 of]。适当合理设计的环境规制政策将促进受限个体在有限条件下激发技术创新意识,动态整合要素投入组合,提高绿色全要素生产率[ carbon emission rights. By limiting control of enterprise greenhouse gas emissions and emission quotas, with the help of market mechanisms to transform environment negative external cost into enterprise internal production costs, this reverses transmission control to complete the performance conditions, promotes the carbon market to reach the Pareto optimal situation, and finally realizes the quality and efficiency of energy utilization, energy conservation and emission reduction of the whole economy and society. An appropriate and reasonably designed environmental regulation policy will promote the constrained individuals to stimulate the consciousness of technological innovation under limited conditions, dynamically integrate the factor input combination, and improve the green total factor productivity. The carbon emission trading policy releases the guiding signal of environmental regulation, and the diffusion of its policy influence can not only promote energy reform, consumption revolution, and the green industrial system through the 62]]。碳排放交易政策释放了环境监管的引导信号,其政策影响力的扩散不仅可以通过上级行政指令下的pilot diffusion试点扩散 under superior administrative instruction and promote the improvement of the green low-carbon cycle development economic system, but it can also guide and encourage scientific research and development and technological innovation, expand the application scenarios of advanced green technology, and promote the “active diffusion” self-organization after learning推动能源改革、消费革命和绿色产业体系,还可以促进环境治理的改善。绿色低碳循环发展经济体系的同时,还可以引导和鼓励科研开发和技术创新,拓展先进绿色技术的应用场景,促进非领域学习模仿后的“主动扩散”自组织。 - 试点地区 [ and imitation in non-pilot areas . As a means of market-oriented environmental regulation, carbon emission trading policy impacts 63]。作为市场化环境监管手段,碳排放交易政策从成本压力、政策引导和利益激励三个方面对TFEE in three ways: cost pressure, policy guidance, and interest incentive. Specifically, according to the requirements of carbon emission intensity regulation, the government issues a certain free emission quota to each market participant with the carrier of the 产生影响。具体来说,政府根据碳排放强度监管要求,以carbon emission permit” system. Regulators who exceed the quota need to buy carbon emission quotas in the trading market, and enterprises with carbon reduction advantages can sell carbon emission rights or transfer green technologies as profits. Based on the consideration of controlling emission costs and removing fossil energy consumption dependence, the original energy-intensive enterprises will independently carry out energy conservation and emission reduction, increase green technology research and development, continuously optimize the production process, improve production technology, and replace and eliminate backward equipment, thus bringing higher TFEE. At碳排放许可证”制度为载体,向各市场主体发放一定的免费排放配额。超过配额的监管机构需要在交易市场购买碳排放配额,具有碳减排优势的企业可以出售碳排放权或转让绿色技术作为利润。基于控制排放成本、消除化石能源消费依赖的考虑,原有高耗能企业自主开展节能减排,加大绿色技术研发,不断优化生产工艺,改进生产技术,更换和淘汰落后设备,从而带来更高的TFEE[64 the same time, policy instructions’ long-term, mandatory, and supportive characteristics will optimize the distribution mode and correlation of production factors among industries. Carbon trading policy released green market signals to guide capital, technology, talent, energy, and other elements to the low-carbon industry. 65]。同时,政策指令的长期性、强制性、支持性特征将优化产业间生产要素的配置方式和关联性。碳交易政策释放绿色市场信号,引导资金、技术、人才、能源等要素向低碳产业发展。原来的高耗能、高碳排放的老产业,迫于环境约束压力,被迫向绿色、高效、低碳的新产业转变。直接影响是一个地区最终将经历先进的产业结构变革,同时减少碳排放并提高The original energy-intensive, high-carbon-emission old industry, due to pressure from environmental constraint pressure, has been forced to change into a green, high-efficiency, low-carbon new industry. The direct impact is that a region will eventually undergo advanced industrial structure change, while reducing carbon emissions and improving TFEE. As an essential booster of low-carbon transformation, with deep integration among the digital network, “Metcalfe Law”, advanced intellectualization technology and traditional power, energy, and transportation industries, can effectively assign enterprises green IM and energy management, lead the green industry and process reengineering, promote the critical carbon industry’s whole lifecycle of energy consumption, and realize TFEE and the production efficiency of double promotion. Moreover, digital technology helps administrative departments to find out the “carbon background”, carry out “carbon investigation” and “carbon planning” under the background of carbon emission regulation, and significantly enhance the government departments to monitor urban carbon emissions and low-carbon governance capacity. Therefore, in improving TFEE by IM, carbon emission trading policy mainly forces industrial upgrading and low-carbon transformation by imposing environmental pressure on “three high” enterprises to further weaken enterprises’ dependence on energy consumption and ultimately improve TFEE.。作为低碳转型的重要助推器,与数字网络深度融合的“梅特卡夫定律”,先进的智能化技术与传统电力、能源、交通行业相结合,可以有效赋能企业绿色IM和能源管理,引领绿色产业和流程再造,推动关键碳产业能源消耗全生命周期,实现TFEE和生产效率的提升。双重促销。而且,数字技术帮助行政部门摸清“碳背景”,在碳排放监管背景下开展“碳排查”和“碳规划”,显着增强政府部门对城市碳排放和低碳的监管。治理能力[推动关键碳素产业能源消费全生命周期,实现TFEE和生产效率的双提升。而且,数字技术帮助行政部门摸清“碳背景”,在碳排放监管背景下开展“碳排查”和“碳规划”,显着增强政府部门对城市碳排放和低碳的监管。治理能力[推动关键碳素产业能源消费全生命周期,实现TFEE和生产效率的双提升。而且,数字技术帮助行政部门摸清“碳背景”,在碳排放监管背景下开展“碳排查”和“碳规划”,显着增强政府部门对城市碳排放和低碳的监管。治理能力[大幅提升政府部门对城市碳排放的监测和低碳治理能力[大幅提升政府部门对城市碳排放的监测和低碳治理能力[66 Based on this, the carbon emission trading policy will strengthen the positive effect of ]。因此,碳排放交易政策在通过IM on improving TFEE.

3. Conclusions and Policy Implications

With the accelerated innovation of digital technologies such as big data, cloud computing, blockchain, and automation, the free flow of various production factors and the deep integration of various market entities have been promoted in recent years. 提高TFEE的过程中,主要通过对“三高”企业施加环境压力来倒逼产业升级和低碳转型,进一步削弱企业对能源消耗的依赖,最终提高The application of industrial robots is a concrete reflection of the integration of artificial intelligence technology and industry. Its extensive promotion and popularization in the manufacturing field not only bring about a change in production mode but also significantly impact the method of resource combination and energy utilization efficiency.

(1) The productivity effect, scale effect and resource allocation effect produced by IM technology can significantly improve the TFEE, and the conclusion is still valid after the robustness test and dealing with endogenous problems.

(2) LPD and CEPT are important mechanisms for IM to improve TFEE. On the one hand, IM helps to eliminate workers’ information search costs and search process, promote labor factors in a broader market configuration, more efficiently match labor supply and job demanders, and ease labor price distortion, and corrected LPD can strengthen the enterprise research and development and innovation and crack regional industrial structure low-end locking, ultimately improving the TFEE. On the other hand, CEPT, by imposing cost pressure on enterprises and supplemented by policy guidance and interest incentive, can strengthen enterprises’ willingness to develop green technology research and development, optimize the process, and replace backward equipment, so as to positively regulate IM and improve TFEE.

Policy Enlightenment

In order to give full play to the driving role of intelligent manufacturing in improving TFEE as much as possible, combined with the research perspective and conclusion of this paper, the following policy suggestions are put forward:

(1) Government departments should deepen the reform of IM systems and continuously improve the business environment of the digital economy. First, scholars will give full play to the role of the government in the top-level design and deepen the reform of the government management system. Starting from the perspective of industrial integration systems, scholars will expand the coverage space of intelligent manufacturing policy support, plan intelligent manufacturing production, equipment, technology, management, and other fields, and improve the policy system of intelligent manufacturing. At the same time, the government’s policy preference for intelligent manufacturing should be based on the principle of “market leading, government guidance”, give full play to the decisive role of the market in the allocation of intelligent manufacturing resources, and promote the rapid development of intelligent manufacturing industry. Second, scholars should increase the financial support for the development of intelligent manufacturing and deepen the reform of the financial system. scholars should implement the particular policy of preferential tax treatment for intelligent manufacturing enterprises, including the R&D expenditure of intelligent manufacturing technology in the list of VAT deductions to encourage intelligent manufacturing enterprises to strengthen independent innovation and carry out deep cooperation with the government in capital and technology, so that enterprises can reasonably enjoy the policy dividend. Third, scholars will optimize the talent supply and training structure, deepen the reform of the talent system, and alleviate the mismatch between labor industries and regions. On the basis of improving the supporting policies for talent introduction, the government builds a training platform for intelligent manufacturing talents and attracts foreign high-tech talents to reflux by improving economic treatment, politics, treatment, family treatment, and other forms. At the same time, scholars will support institutions of higher learning and vocational colleges to set up intelligent-manufacturing-related majors or practical courses, promote the construction of this discipline at different levels, and reserve sufficient professional talents for intelligent manufacturing enterprises and scientific research institutes. Fourth, scholars will promote the construction of a digital government to release the information dividend. With the implementation of e-government and the construction of a smart city as the starting point, scholars must integrate digital government into the digital transformation of the whole city, jointly promote the construction of a digital government and an innovative city, digital community, and digital countryside, and build the construction of a coordinated linkage represented by “three integration and five spans.” Using digital intelligence to drive the system remodeling, scholars must actively explore data governance and government function reform, restore the “business flow” with departmental “data flow,” promote the integration of government service links and process optimization of government services, realizing the “one network” of government services and leading the digital development with the construction of digital government. Fifth, scholars should accelerate the establishment of a multi-functional and integrated national carbon trading market data-sharing platform. The scholars will continue to pilot carbon trading in parallel with the national carbon market and give full play to the positive regulatory role of carbon emission trading policies. It is necessary to make full use of intelligent manufacturing, artificial intelligence, and blockchain advanced information technology, and optimize and integrate Guangdong carbon trading, China carbon city, Shenyang Carbon trading, and other local carbon trading user terminal information platforms, building a national-integrated, multi-functional carbon trading user terminal and data analysis platform and striving to eliminate information barriers.

(2) Governments must make breakthroughs in the core technologies of intelligent manufacturing and strengthen the strategic layout. First, they must strengthen basic industrial research to seize the advantages of intelligent manufacturing technology. With the industrial and supply chains as the main lines, scholars will make significant breakthroughs in the “five new types of infrastructure” engineering, industrial production, and application in essential fields such as intelligent equipment and new materials and constantly improve the essential capacity of intelligent manufacturing. scholars must strengthen the construction of industrial Internet infrastructure in public places and intelligent manufacturing industrial agglomeration parks, strengthen information security control, and promote the integration and interaction of manufacturing technology and information technology in all links of industrial manufacturing. Second, scholars will strengthen our strategic layout and give full play to its exemplary and leading role. Administrative departments can build regions and industrial parks with a good foundation of intelligent manufacturing into intelligent manufacturing demonstration bases and adopt the “reveal the list and take the lead” approach to concentrate high-end national resources, taking the lead in breaking through the key core technologies that restrict the development of intelligent manufacturing, to give full play to the positive leading role of pilot demonstration projects. At the same time, the leading enterprises of intelligent manufacturing should accelerate the cooperation of domestic and foreign universities and scientific research institutions, build an industrial innovation platform, and drive the upstream and downstream linkage and cooperation of the industrial chain and innovation chain. Third, scholars must learn lessons from advanced foreign experience to develop intelligent manufacturing essential software. For the weak link of the intelligent manufacturing essential software industry in China, a software development-related support policy encourages industrial enterprises and software development park building technology demand communication platform, real-time tracking enterprise demand to jointly develop intelligent manufacturing basic software and operating system, solve the problem of software system development lags behind the intellectual level of China.

(3) Enterprise must build “intelligent” employees in the digital era and build a community of interests. First, scholars must reshape the corporate culture of the digital age through thinking. Intelligent manufacturing enterprises should give up the traditional top-down, inside-out planning and control mechanism, break the status quo of hierarchical decision-making, and change the enterprise development from “controlling employees” to “trusting employees.” At the same time, all levels embed the thinking mode of risk-taking and innovative development to cultivate a corporate culture with digital vision and genes. Second, scholars should carry out “online + offline” digital training and create a scientific training evaluation system. Intelligent manufacturing enterprises should drive data-driven enterprise learning and set up personalized and specific training courses. At the same time, using various management software and data analysis functions, these enterprises should establish a scientific training evaluation system, link the training content with employee performance, and fully mobilize employees’ enthusiasm to integrate into the digital age. Third, scholars should pay attention to individual value and realize the symbiosis of enterprise and employee value. Intelligent manufacturing enterprises should pay attention to organizational performance goals and consider the value of employees in the organization. Enterprises should establish a value platform shared by employees and organizations, constantly strengthen the communication between employees and other high-tech enterprises, improve the cognitive level of employees, and achieve the goal of matching the development speed of enterprises and employees.

(4) Considering the role of carbon emission trading in promoting TFEE, it is necessary to continue to speed up the construction of the carbon emissions trading market in pilot areas and improve the national unified carbon trading market system. When the government provides a good platform for trading subjects, it should also handle the relationship between the government and the market. Based on emphasizing fairness, scholars should give play to the role of the market mechanism, not interfere with the implementation of the carbon emission trading system, give play to the dominant position of enterprises in the market, use the market mechanism to guide the rational allocation of factors, save energy and improve energy utilization efficiency. To implement a carbon emission trading system, scholars should not only fully consider each region’s historical cumulative carbon emissions but also fully measure each region’s natural endowment and economic development to improve TFEE effectively. A differentiation strategy can be implemented.

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