1. Introduction
With the development of manufacturing, China is rapidly growing into the world’s second-largest economy. However, China’s economy still faces severe difficulties in sustainable development. In the past, this country mainly relied on the low-cost advantage of production factors such as capital, labor, and energy. These advantages are constantly weakening, and the resource problems are gradually becoming more prominent. According to China’s National Bureau of Statistics, the proportion of China’s working-age population has slowly declined since 2010; from 2015 to 2020, the total working-age population showed a downward trend, decreasing by nearly 16.99 million people. Based on the BP Statistical Review of World Energy 2022, China’s primary energy consumption has been on the rise without restraint since it surpassed the United States in 2009. By 2021, China’s energy consumption was equivalent to 63.06 million tons of hard coal. This is about 1.7 times that of the United States and accounts for 26.5% of global primary energy consumption, ranking first worldwide. Moreover, China’s energy mining has been unable to meet its own development needs, and it has begun to import many energy and mineral resources from overseas. Thus, the lack of labor and the overconsumption of natural resources are gradually restricting China’s economic development. In light of the move toward the high-quality development of China’s economy, China’s extensive economic growth mode is no longer sustainable, and it is urgent to shift from factor-driven to innovation-driven mechanisms to promote sustainable economic development.
In the light of the Global Innovation Index from the World Intellectual Property Organization, China’s overall ranking of innovation capacity rose to 11th in the world in 2021, up 23 places from 2012. This is thanks to the in-depth implementation of China’s innovation-driven development strategy. However, China, with the world’s most enormous energy consumption and a large population, is far less efficient at innovation than developed regions such as Switzerland and the United States. China’s innovation performance still needs to be improved. At the same time, manufacturing intelligentization has become an important driving force for upgrading China’s manufacturing industry, innovation, and sustainable development [
1]. “Made in China 2025” pointed out that intelligent manufacturing should be the main direction to promote the transformation and upgrading of the manufacturing industry. The 14th Five-Year Plan for Intelligent Manufacturing Development also indicated that the digital transformation, networking collaboration, and intelligent transformation of the manufacturing industry should be continuously promoted to provide strong support for the high-quality development of the manufacturing industry. Therefore, an in-depth study of the ability of intelligence to drive innovation is crucial to the high-quality and sustainable development of China’s economy.
Moreover, in implementing the Intelligent Manufacturing Strategy, in addition to the intelligent transformation of production, many large manufacturers are fundamentally changing their value creation strategies from product-centric to hybrid product–service providers [
2,
3]. Judging from international experience, the servitization of the economy is in line with the trend of a new round of technological revolution, industrial transformation, and consumption upgrading. Furthermore, it is also a practical choice for cultivating a new driving force for industrial development and a modern industrial system. In this context, enterprises are increasingly using services as intermediate inputs, resulting in the increasing externalization and marketization of producer services. Therefore, it is of great significance to the sustainable development of China’s economy to pay attention to the role of manufacturing intelligence and producer services in the innovation-driven strategy.
Recent research shows that implementing intelligent manufacturing is conducive to technological progress and regional innovation and is an essential measure for China’s innovation and development [
4,
5]. However, information technology in intelligent manufacturing has both an enabling effect and a squeezing effect on innovation, showing an inverted “U”-shaped curve relationship [
6]. Therefore, the impact of manufacturing intelligentization on innovation is still unclear. Manufacturing intelligence is a vertically integrated production model that introduces the concept of the Internet of Things and servitization [
7,
8]. Under the trend of servitization transformation, can manufacturing intelligentization effectively promote technological innovation, thereby promoting China’s innovation-driven development? This problem remains to be empirically verified. If confirmed, what is the mechanism behind it? This study attempts to demonstrate the issues mentioned above in depth.
2. Literature Review
Research on the relationship between intelligence and innovation can be traced back to information technology and innovation literature. Information technology can improve the speed and efficiency of enterprise innovation through knowledge asset management, production support, and inter-organizational coordination [
9]. Some studies also use empirical evidence to show that information technology can promote the output, performance, and process of innovation and new product development [
9,
10,
11,
12,
13], or mitigate the diminishing returns to R & D [
14]. However, if information technology is inflexible in the use process, it may lock enterprises in the situation of limited external knowledge sources, thereby inhibiting innovation [
15]. Karhade and Dong (2021), based on the dynamic adjustment cost theory, found that with the increase in investment in information technology, the impact of information technology on innovation showed an inverted U-shaped relationship [
6].
In the intelligent manufacturing system, intelligent technology will gradually replace human and mental activities, accelerating knowledge iterative updating and creation, improving learning and absorption, and promoting technological innovation [
4]. Supported by big data, the development of deep learning technology will significantly reduce the cost of knowledge searching, prompting R & D departments to increase fixed capital investment in artificial intelligence. These investments may improve the performance of existing data-intensive research projects and open up new research ideas and development opportunities for studying social and physical phenomena previously outside systems science and empirical research [
16]. Kakatkar et al. (2020) found through case studies that AI can leverage large-scale data for highly scalable and reproducible deep analysis, helping innovation teams validate creative insights, reduce creative blind spots, and uncover new problems in complex relationships [
17]. Truong and Papagiannidis (2022) believe that artificial intelligence may acquire some creative ability by combining data in new ways to produce novel content, but whether it positively impacts disruptive innovation is unclear [
18]. Grashof and Kopka (2022) further found that large companies increase radical innovation from artificial intelligence applications, while small and medium-sized enterprises use artificial intelligence technology as a general-purpose technology to promote fundamental innovation [
19]. Rammer et al. (2022) also found the prominent role of AI in world-first innovations [
20]. Grounded in gestalt insight learning theory and organizational learning theory, Ghasemaghaei and Calic (2019) studied the influence of big-data characteristics on enterprise innovation from the perspectives of data volume, data speed, data diversity, and data accuracy and found that the accuracy, speed, and diversity of big-data analysis are the keys to promoting enterprise innovation [
21]. By increasing the scale and variety of information obtained by enterprises, reducing the cost of absorbing external knowledge, and promoting the integration of knowledge, big-data technology can improve effective results in the innovation process of enterprises [
22]. Yang et al. (2022) believed that intelligence could produce a “technology promotion effect” and a “cost reduction effect”, promoting the level of regional green innovation [
5].
Existing research has made some progress in the relationship between intelligent technology and innovation, which lays a theoretical foundation for subsequent research. However, there are still many problems to be further explored and solved. Firstly, the existing literature mainly studies the relationship between intelligent manufacturing and innovation performance with linear thinking, ignoring the potential negative impact on new knowledge acquisition caused by the excessive introduction of intelligent investment. It is necessary to explore the nonlinear relationship between manufacturing intelligence and innovation performance from a nonlinear perspective. Second, although the existing literature has recognized the trend of manufacturing servitization in the process of intelligent manufacturing, few scholars have included producer services in the study of the relationship between intelligence and innovation performance and have not investigated whether the change of producer service agglomeration exists in intelligence and innovation performance as a mediator. Therefore, the influence mechanism of manufacturing intelligence on innovation performance cannot be effectively revealed. Third, if there is a nonlinear influence of intelligence on innovation, few scholars discuss what measures can be taken to intervene in the extrusion effect of intelligence on innovation.
Based on this, the article uses the panel data of 30 provinces in China from 2008 to 2020 to conduct an empirical study on the impact of manufacturing intelligentization on innovation performance in a nonlinear way. In addition, from the perspective of diversified agglomeration of producer services, this study empirically adopts the mediation effect model to test the mechanism of manufacturing intelligentization on innovation performance. Thirdly, from the perspective of labor optimization, this paper uses the human capital variable to test its moderating influence on nonlinear effects.
Taking existing literature into consideration, the contribution of the study is mainly reflected by the following three points: (1) This study innovatively explores the nonlinear relationship between manufacturing intelligentization and innovation performance; (2) in terms of the analysis of mediating factors, this paper chooses the perspective of diversified agglomeration of producer services under the background of servitization; (3) this article also emphasizes the moderating effect of human capital on the nonlinear relationship to alleviate the marginal diminishing phenomenon of the impact of intelligentization on innovation performance. The research results can provide reliable suggestions for driving economic innovation and sustainable development in the era of intelligent manufacturing. The rest of the paper is structured as follows:
Section 3 describes the research mechanism and the article’s hypotheses.
Section 4 introduces the selection of variables and data for the empirical study, the research method, and the regression results.
Section 5 discusses the results of the study.
Section 6 concludes the study.
5. Discussion
The arrival of the era of intelligent manufacturing marks the deep integration of informatization and industrialization and the beginning of manufacturing enterprises to move towards high-end value chains and service-oriented manufacturing. Manufacturing intelligentization can be a driving force for economic innovation and sustainable development. Nevertheless, from the empirical data, Chinese manufacturing companies have not fully realized the potential of intelligence in manufacturing to empower economic innovation and development. Although the relatively low intelligence of the manufacturing industry can improve China’s regional innovation performance, when the regional manufacturing industry overinvests in intelligent transformation, innovation will be squeezed. At the same time, in the process of service-oriented transformation of the manufacturing industry, the impact of manufacturing intelligentization on innovation performance of “promoting first and then inhibiting” has an intermediary channel of diversified agglomeration of producer services. This mechanism more clearly shows the action law and operation logic of intelligent manufacturing strategy on innovation, which is helpful to guide social practice better. In addition, the marginal diminishing impact of intelligentization on innovation can be significantly alleviated by optimizing human capital structure. To summarize, focusing on managing intelligent investment, the basic environment of producer services, and human capital structure are significant to the innovative and sustainable development driven by manufacturing intelligence.
5.1. Practical Implications
First of all, in the current environment where the manufacturing value of products is gradually decreasing and the economy has difficulties in sustainable development, Chinese manufacturers need to rely on intelligence to improve innovation performance. On the one hand, manufacturers can obtain a large amount of multi-source heterogeneous data by introducing intelligent technology, building physical information systems, and linking the entire product life cycle to build a “product–service” solution pattern. Through big-data analysis and prediction, a large amount of explicit knowledge is obtained, and the product development cycle is shortened to promote product innovation, value increase, and sustainable development. On the other hand, manufacturers have a threshold of investing in intelligence. Through physical information systems and service transformation, enterprises can link more physical equipment, manufacturers, and service providers in the supply chain, to obtain more explicit knowledge, form innovation potential, and improve product value and market competitiveness. However, due to the limited ability of people to obtain and analyze information, the excessive interconnection and concentration of information in high intelligence will lead to information overload and information barriers, raise the cost of innovation, and cause a technology lock. Therefore, manufacturers need to cultivate certain intelligent investment management capabilities, improve the innovation driving force of intelligent technology, and strengthen innovation results.
Secondly, manufacturers should pay attention to the match between intelligent investment in manufacturing and producer service environment. The influence of manufacturing intelligence on innovation performance has the internal mechanism of producer services’ diverse agglomeration. Manufacturers have a service-oriented trend when investing in intelligent technology, which shows that enterprises inject more and more productive service elements into the production process to extend the value of products. The service input caused by intelligence will attract diversified producer service enterprises to gather in intelligent areas, to adapt to the service needs of manufacturers in different stages of service transformation. However, the highly intelligent production environment will compress transportation costs and transaction costs to a minimum, thus inducing the producer service providers to transfer to the area with the highest factor endowment, which is not conducive to the diversification and agglomeration of service providers, thus inhibiting the innovation brought by diversification. Therefore, when manufacturers drive innovation development through intelligence, they should pay attention to the matching degree between the environment of producer service providers and the level of intelligence, to effectively enhance innovation output.
For governments and policymakers, it is necessary to strengthen the in-depth application of information technology in manufacturing and guide qualified small and medium-sized manufacturing enterprises to carry out the digital and intelligent transformation, to avoid duplication or excessive investment. The infrastructure of various types of productive services should be further improved. A market business environment with fair competition and a transparent legal environment should be established. These will provide basic conditions for the agglomeration of producer services, expand market size, and cultivate a variety of producer service suppliers. Furthermore, it is necessary to improve the adaptability between the skill structure of labor supply and the intelligence level of manufacturing through the policy system. Further, the coordinated development of intelligent manufacturing and higher education should be promoted by improving the popularity and quality of higher education.
5.2. Theoretical Implications
Firstly, this study reveals that manufacturing intelligence is a key nonlinear factor affecting innovation performance growth, which enriches the existing research framework on the relationship between intelligent technology and innovation. Existing literature mainly studies the positive relationship between intelligent technology and innovation from a linear perspective [
4,
5], without paying attention to the potential negative impact of excessive investment in intelligent technology on product innovation and new knowledge output. This paper complements related research from a nonlinear perspective and verifies the inverted U-shaped relationship between manufacturing intelligence and innovation performance.
Secondly, the diversified agglomeration of producer services was taken as the key intermediary factor, enriching the research on intelligence’s influence on innovation performance. The existing literature mainly focuses on the linear direct impact of intelligence on innovation [
4] and studies the intermediary mechanism from the perspective of innovation ability [
5], while there are few studies on the diversification and agglomeration of producer services as a nonlinear potential mechanism. Under the background of economic service, this paper reveals the nonlinear effect path of intelligence on innovation performance from the perspective of diversification and agglomeration of producer services. It not only expands the research on the nonlinear influence channels of intelligence on innovation but also enriches the literature on innovation development under the trend of servitization.
Thirdly, to alleviate the marginal diminishing constraint of the impact of manufacturing intelligence on innovation performance, this paper uses the level of human capital to verify its moderating effect on the inverted U-shaped impact from the perspective of labor structure optimization. To some extent, this reveals how to promote the sustainable development of innovation strategy driven by intelligence.
6. Conclusions
In the era of intelligent manufacturing, intelligent technology will be embedded in all links of the innovation chain to promote innovation and sustainable development in the manufacturing industry. The article mainly analyzes the nonlinear impact of manufacturing intelligentization on innovation performance and examines the mediating role of the diversified agglomeration of producer services. The study found that the impact of manufacturing intelligentization on innovation performance presents a significant inverted “U”-shaped relationship; at the same time, this impact has a nonlinear channel of diversified agglomeration of producer services. Further tests point out that, to a certain extent, the improvement of the human capital level can restrain the diminishing marginal effect of intelligentization on innovation. That is, it can alleviate the negative effect of higher intelligence levels on regional innovation.
This study has some limitations. First, this study only used the individual and time fixed-effects model for testing and did not consider the interaction between regions. Second, due to the COVID-19 epidemic in 2020, China’s economic development was affected to a certain extent, and the article included the data for 2020 in the study without corresponding consideration. Therefore, the reliability of empirical predictions in the article may be reduced.
For future research, intelligent manufacturing is undoubtedly a means to improve the value of China’s manufacturing industry chain and a significant driving force for China’s economic innovation and sustainable development. However, in the process of servitization, intelligent manufacturers may face a contradiction between innovation and efficiency [
36]. For example, intelligent enterprises can quickly respond to and customize the needs of the consumer market. So, should the technology development within an intelligent enterprise be customer-oriented, or should it be based on engineering thinking? Customer orientation is necessary when customizing solutions and advanced services for a client’s business, but engineering thinking is critical to maintaining a culture that supports the development of highly innovative products and solutions. Customized solutions have low reusability and production efficiency of related products, which is different from efficient incremental innovation under engineering thinking. In other words, manufacturers may face the paradox of customized innovation and production efficiency in intelligentization. This paradox is also a pivotal point to be considered in future research on the relationship between intelligence and innovation.