The Digital Economy’s Impact on the High-Quality Development of the Manufacturing Industry in China’s Yangtze River Economic Belt

Abstract

Based on the panel data of 108 cities in the Yangtze River Economic Belt from 2011 to 2021, this study constructs a fixed effect model, a mediating effect model, and a threshold effect model to verify the enabling role, conduction path, and nonlinear effect of the digital economy on the high-quality development of the manufacturing industry in the Economic Belt. It is found that the digital economy has remarkably enabled the high-quality development of the manufacturing industry in the Economic Belt, with an obviously stronger enabling effect in large-scale cities than in small ones; the digital economy can indirectly affect the high-quality development of the manufacturing industry in the Economic Belt through upgraded industrial structure, regional innovation, and residents’ consumption. Subject to environmental regulation, the digital economy’s impact on the high-quality development of the manufacturing industry in the Economic Belt has a double-threshold effect. With intensified urban environmental regulation, the digital economy’s promotion effect on the high-quality development of the manufacturing industry has demonstrated a trend of first enhancing and then weakening.

1. Introduction

Since the topic on the digital economy was listed in a separate chapter of the “14th Five-Year Plan” for the first time, China’s digital economy has ushered in an unprecedented opportunity for development. As a new economic form, the digital economy has, by taking digital technologies as its basis and using modern information networks as its main carrier, increasingly become a new engine to promote economic and social development. The 2020 Government Work Report pointed out that China should accelerate integration between the digital economy and the manufacturing industry, give full play to the role of the digital economy as a “new engine”, and further drive the deep integration of the digital economy and the manufacturing industry. This integration can make full use of digital technology and data resources to transform and upgrade all aspects and elements of the manufacturing industry through networking, intelligence, platform, and other methods, so as to boost the transformation of the manufacturing industry from traditional manufacturing to intelligent manufacturing, from production-oriented manufacturing to service-oriented manufacturing, from scale-based manufacturing to quality-based manufacturing, and from low-end manufacturing to high-end manufacturing, thus delivering the high-quality development of the manufacturing industry. So far (by 2024), China has cultivated more than 350 industrial Internet platforms with industrial characteristics and regional influences. These platforms have connected more than 80 million sets of industrial equipment, and the number of industrial APPs aggregated has continued to hike, providing strong support for enterprises’ digital transformation. According to statistics from the Ministry of Industry and Information Technology, currently, the utilization rate of R&D and design digitization tools in China’s industrial enterprises above the designated size has reached more than 60%. Additionally, the level of digitization of production equipment is also rising, with the rate of numerical control over key processes exceeding 75%. This shows that increasingly, more manufacturing enterprises are actively adopting digital tools to enhance their production efficiency and product quality.

The Yangtze River Economic Belt covers 11 provinces (or municipalities) in China. By relying on the golden waterway of the Yangtze River, the Economic Belt connects three major regions of eastern, middle-eastern, and western China, with its population and GDP accounting for more than 40% of the total of China, showing strong comprehensive strength and manifesting innovative vitality. As shown in the data for the first half of the year of 2023, the GDP of the region is up to RMB 27.59939 trillion, accounting for 46.8% of the total in China, highlighting the core position of the Yangtze River Economic Belt in China’s economic system. As the foundation of the real economy, the manufacturing industry provides a large number of employment opportunities, tax contributions, and economic growth points for the Yangtze River Economic Belt and even the whole country. Meanwhile, the manufacturing industry of the Yangtze River Economic Belt covers a wide range of industry sectors, ranging from traditional automobiles, iron and steel, and chemicals to emerging information technology, new materials, biomedicine, and so on, forming a complete industrial chain and supply chain system which has not only facilitated the synergistic development of upstream and downstream enterprises but has also boosted the industrial competitiveness and risk-resisting ability of the whole region. Despite the rapid development of the manufacturing industry in the Yangtze River Economic Belt, it still faces problems such as environmental pollution, monotonous industrial structures, unbalanced regional development, and serious industrial isomorphism. These problems limit the further development of the Yangtze River Economic Belt. Therefore, this study, by taking the Yangtze River Economic Belt as the main research subject, makes an in-depth investigation into the influence mechanism of the digital economy on the high-quality development of the manufacturing industry, aiming to provide theoretical support for promoting the high-quality development of the manufacturing industry in the Yangtze River Economic Belt and to offer a reference for the high-quality development of the economy of other regions and even the whole country of China.

By reviewing the past literature, we can find that the characteristics of high-quality development of the manufacturing industry are mainly demonstrated in the following aspects: improved innovation ability, regional synergy, optimized industrial structure, and deepened integration with digital technology, among others [1,2,3]. At present, the research on the high-quality development of the manufacturing industry is focused mainly on two dimensions. The first dimension is about the measurement of development levels, and there are two main methods of measurement: the first method is to use the total factor productivity of the manufacturing industry to represent the level of high-quality development of the manufacturing industry [4,5], and the other method is to construct an index system and then use the entropy value method and the principal component analysis method for calculation [6,7]. The second dimension is about the research of influencing factors. Currently, scholars are mainly conducting this research from the perspectives of technology, factors, the external environment, and others. The technology perspective mainly covers such factors as Internet technology [8,9] and technological innovation [10,11]; the factor perspective mainly covers such factors as labor cost [12] and factor quality [13,14]; and the external environment perspective mainly covers such factors as productive services [15], openness and demand-pull [16].

The digital economy is a new economic form that takes digital technology as the core, uses data as the key element, and promotes economic development through networking, intelligence, and other methods. Over recent years, many scholars have implemented in-depth research on the measurement of the digital economy as well as its enabling role for the high-quality development of the economy [17], the real industry [18], and high-level social construction [19]. Especially, how the digital economy boosts the high-quality development of the economy has become the focus of research in this field, including the impact on consumer demand [20], regional innovation input [21], ecological civilization construction [22], and other aspects.

The deep integration between the high-quality development of the manufacturing industry and the digital economy is not only an inherent requirement of the information technology era but also the key in promoting high-quality economic development. Some scholars have carried out theoretical research on the path for the digital economy to affect the high-quality development of the manufacturing industry. For example, He Wenbin [23] made an in-depth analysis of the impact of the digital economy on the development of China’s manufacturing industry from the global value chain perspective; Li Yingjie [24] explored the intrinsic mechanism of high-quality development of the manufacturing industry under the background of the digital economy from three perspectives: quality change, efficiency change, and power change. In terms of empirical research, scholars generally agree that the digital economy has a significant role in promoting the high-quality development of the manufacturing industry [25,26]. However, most of them have conducted empirical research at the provincial level, and only a few of them carried out research at the city level [27] or at the level of listed companies [28]. In terms of research on the influencing mechanism, the current research has found that the digital economy can promote the high-quality development of the manufacturing industry through human capital [26], industrial upgrading [26,29], dual innovation [28], industry-university-research combination [30], management efficiency [31], and other paths; some other scholars have indicated that the enabling role of the digital economy on the high-quality development of the manufacturing industry is subject to the population’s living standard and the economic development level [29], with an incremental marginal benefit manifested.

In summary, the existing literature mainly explores the mechanism for the digital economy to impact the high-quality development of the manufacturing industry, but no complete system has been formed on the enabling mechanism of the digital economy, and the research on the non-linear relationship between the two is insufficient. Given this context, this study selects the data of 108 cities at the prefecture level or above in the Yangtze River Economic Belt in 2011–2021 as its research object. The supply side, the external environment, and the demand side are the core elements of an economic system, and are also important factors affecting the high-quality development of the manufacturing industry. On the supply side, industrial upgrading is the core driving force for the high-quality development of the manufacturing industry. The digital economy promotes the transformation of the manufacturing industry from the traditional production mode to intelligent, green, and service-oriented manufacturing by providing advanced information technology, intelligent equipment, and data resources. In terms of the external environment, innovation-driven manufacturing is the key to high-quality development. The digital economy provides strong support for technological innovation, including data resources, cloud computing platforms, artificial intelligence algorithms, etc. These resources and technologies lower the threshold of innovation, accelerate the innovation process, and enable enterprises to launch new products, technologies, and services more quickly. On the demand side, consumption-driven manufacturing is the ultimate orientation of high-quality development of the manufacturing industry. The digital economy stimulates consumers’ purchase desire and ability by expanding the consumption boundary, improving consumption convenience, and meeting personalized needs. From the three aspects of the supply side, the external environment, and the demand side, the industrial upgrading drive, innovation drive, and consumption drive are selected as intermediary variables, which not only comprehensively cover the core elements of the economic system, but also deeply analyzes the interaction and relationship between them. From the supply side, the external environment, and the demand side, this study selects three driving factors, i.e., industrial upgrading, innovation, and consumption, to systematically demonstrate the specific mechanism of the digital economy’s impact on the high-quality development of the manufacturing industry. At the same time, the importance of environmental regulation for the high-quality development of the manufacturing industry is reflected in promoting green transformation, enhancing competitiveness, achieving a win–win situation between the economy and the environment, and promoting policy formulation and implementation. Therefore, this paper chooses environmental regulation as the threshold variable for research.

2. Materials and Methods

2.1. Theoretical Analysis and Research Hypotheses

The rising digital economy is profoundly leading and reshaping the development path of the traditional manufacturing industry based on its core characteristics, such as high growth, technological innovation, diffusion, and popularization. Through the extensive integration and implementation of advanced digital technologies such as big data, Internet-of-Things, 5G, etc., the manufacturing industry in the Yangtze River Economic Belt has been able to break through traditional spatiotemporal limitations to efficiently integrate and dynamically optimize production factors, significantly improving the overall production efficiency of the manufacturing industry and promoting the transformation and upgrading of the manufacturing industry. Specifically, the impact of the digital economy on the manufacturing industry in the Yangtze River Economic Belt is manifested in multiple aspects: firstly, driven by digital technology, the cost structure of the manufacturing industry has been substantially optimized, product quality has been significantly improved, and production processes have been continuously innovated [26]; secondly, as a new type of production factor, data have created unprecedented value-added spaces for the manufacturing industry, and while enhancing the value-creating capacity of enterprises, data have improved the efficiency of value capturing and transforming; finally, due to the extensive penetration of digital technology, the allocation of innovation resources in the manufacturing industry has been comprehensively optimized, and innovation efficiency and deliveries have been significantly boosted. Therefore, based on the above analysis, this study puts forward the following hypothesis:

Hypothesis 1. 

The digital economy significantly empowers the high-quality development of the manufacturing industry in the Yangtze River Economic Belt.

In the context of the digital economy, the traditional manufacturing industry is facing dual problems: value acquisition and value creation. Therefore, it has become the core focus of current academic research to explore the digital economy’s role in empowering production factors and then help the manufacturing industry break through its predicaments. Based on the understanding above, this study, starting from the definition and requirements of the high-quality development of the manufacturing industry, deeply analyzes the empowering path of the digital economy in the following three dimensions: driven by industrial upgrading, driven by innovation, and driven by consumption. With its unique technological advantages and strong integration capabilities, the digital economy has promoted the upgrading of the industrial structure of the Yangtze River Economic Belt, thus driving the high-quality development of the manufacturing industry. The digital economy empowers the upgrading of the industrial structure of the Yangtze River Economic Belt in multiple dimensions: Firstly, the digital economy can accurately collect and analyze market and resource information in real-time, thus helping enterprises make scientific decisions and then optimize the allocation of their resources, so that resources can flow to more efficient and promising industrial segments. Secondly, the digital economy has provided broad platforms and rich means for technological innovation. With the help of technologies such as big data and cloud computing, enterprises can identify market trends and technological directions in a more accurate manner, so as to accelerate the R&D and roll-out of new products and technologies, thus driving up the industrial structure. Finally, by breaking down information barriers, the digital economy has delivered an efficient synergy between all links of the industrial chain, thus enhancing overall operational efficiency while creating more opportunities for enterprises to cooperate and value growth. Driven by the digital economy, the industrial structure of the Yangtze River Economic Belt has gradually transformed from a labor-intensive pattern to a technology-intensive and knowledge-intensive pattern. Such a transformation means that the manufacturing industry can rely more on technological innovation and intelligent production, rather than on simple labor input. Therefore, the industrial structure’s upgrading can facilitate the manufacturing industry in the Yangtze River Economic Belt to develop in a more efficient, environmentally friendly, and sustainable direction, so as to realize high-quality growth. Based on the above analysis, this study puts forward the following hypothesis:

Hypothesis 2. 

The digital economy positively empowers the high-quality development of the manufacturing industry in the Yangtze River Economic Belt by facilitating the upgrading of its industrial structure.

The digital economy has effectively improved the regional innovation level of the Yangtze River Economic Belt and in turn, empowered the high-quality development of the manufacturing industry. By deeply analyzing this logical chain, it can be found that the digital economy can, with its unique technological advantages, significantly enhance the regional innovation level of the Yangtze River Economic Belt by facilitating the agglomeration and integration of innovation resources, driving the shift of innovation patterns, and improving the efficiency and quality of innovation. Specifically, by using cutting-edge technologies such as big data and cloud computing, the digital economy has delivered efficient allocation and optimization of innovation resources and promoted the in-depth integration of innovation factors in the region; meanwhile, by fostering new innovation modes, e.g., Internet-based makers and crowdsourcing, the digital economy has broken the limitations of traditional innovation and sparked a wider range of innovation potentials. Moreover, by relying on such advanced means as intelligent analysis, the digital economy has enhanced the precision and efficiency of innovation and strengthened the regional innovation level of the Yangtze River Economic Belt in an all-round way. With continuously enhanced innovation capacity, the manufacturing industry has made remarkable progress in technology R&D, product innovation, and process improvement and has effectively boosted the overall competitiveness of the manufacturing industry, while driving the manufacturing industry to develop in the green, intelligent, and efficient direction, so as to achieve the goal of high-quality growth. Based on the above analysis, this study puts forward the following hypothesis:

Hypothesis 3. 

The digital economy positively empowers the high-quality development of the manufacturing industry in the Yangtze River Economic Belt by improving regional innovation.

Under the influence of the digital economy, the consumption capacity of the residents in the Yangtze River Economic Belt has been significantly improved, which in turn promotes the high-quality development of the manufacturing industry. Firstly, by virtue of convenient and efficient consumption channels and services, such as mobile payment and e-commerce platforms, the digital economy has effectively broken the spatiotemporal limitations of consumption and enriched the choices of goods and services, thus stimulating the consumption potential of residents. Secondly, in the background of the digital economy, increasingly more new occupations and employment opportunities have emerged, providing residents with more sources of income. In addition, the popularization and deployment of digital technologies have improved the production efficiency of the labor force, so that residents can create more value during the same period of time, thereby increasing their disposable income and providing stronger support for consumption. Furthermore, the rising consumption ability of residents has played a positive role in promoting the high-quality development of the manufacturing industry in the Yangtze River Economic Belt: On the one hand, the growth of consumer demand has directly pulled up the production and sales of the manufacturing industry, thus providing the manufacturing industry with wider market space and more development opportunities; on the other hand, the upgrading of residents’ consumption structure and their diversified needs also promote the innovation, transformation, and upgrading of the manufacturing industry. In order to meet the ever-changing needs of consumers, manufacturing enterprises have to continuously develop new products while improving their product qualities and service levels, so as to drive the whole industry in the direction of higher quality. Based on the above analysis, this study puts forward the following hypothesis:

Hypothesis 4. 

The digital economy positively empowers the high-quality development of the manufacturing industry in the Yangtze River Economic Belt by enhancing the consumption capacity of residents.

The empowering effect of the digital economy on the high-quality development of the manufacturing industry in the Yangtze River Economic Belt would be subject to such external factors as trade, economy, technology, and regime [32]. In the process of empowerment by the digital economy, environmental regulation has, as an important policy instrument, delivered a non-negligible constraining effect on the development of the manufacturing industry. When environmental regulation is weak in the Yangtze River Economic Belt, manufacturing enterprises tend to adopt high-pollution and high-energy-consumption production methods in order to reduce costs; this practice may compromise the impact of the technological advantages of the digital economy. Conversely, with strengthened environmental regulations, manufacturing enterprises would, in order to meet environmental requirements, take the initiative to deploy smart manufacturing, IoT, and other technologies to improve productivity and reduce energy consumption, thus accelerating the integration between the digital economy and the manufacturing industry. However, the implementation of environmental regulations will also impose high compliance costs on manufacturing enterprises, and high investment in environmental protection will squeeze out enterprises’ investments in digital transformation, digital technology R&D, and its application. In summary, this study proposes the following hypothesis:

Hypothesis 5. 

There is a threshold effect of environmental regulation in the process of the digital economy which empowers the high-quality development of the manufacturing industry.

According to the above analysis, Figure 1 illustrates the influencing mechanism of the digital economy empowering the high-quality development of the manufacturing industry in the Yangtze River Economic Belt.

2.2. The Design of This Study

2.2.1. Model Construction

Based on the previous analysis, in order to test the direct effect of the digital economy on the high-quality development of the manufacturing industry in the Yangtze River Economic Belt, this study decided to construct a double fixed effect model for analysis. In the research of the digital economy’s influence on the high-quality development of the manufacturing industry, there may be inherent differences between different regions (individuals) in such dimensions as geographic location, resource endowment, industrial structure, etc.; in addition, there may also be a common effect of the macroeconomic environment, policy changes, etc. at different points in time (time effect). The double fixed effect model can effectively control these effects so that the analysis becomes more accurate. Therefore, this study constructed the following benchmark regression model:

$${HDM}_{it}={\beta }_0+{\beta }_1{DE}_{it}+{\beta }_2{X}_{it}+{\gamma }_i+{\sigma }_t+{\epsilon }_{it}$$

(1)

where ${\mathrm{H}\mathrm{D}\mathrm{M}}_{\mathrm{i}\mathrm{t}}$ denotes the high-quality development of the manufacturing industry; ${\mathrm{D}\mathrm{E}}_{\mathrm{i}\mathrm{t}}$ denotes the development level of the digital economy; ${\mathrm{X}}_{\mathrm{i}\mathrm{t}}$ denotes a series of control variables, mainly including the degree of government intervention (Gov), the foreign direct investment (Fdi), the level of economic development (Eco), and the transportation infrastructure (Tra); ${\mathsf{\gamma }}_{\mathrm{i}}$ denotes the individual fixed effect; ${\mathsf{\sigma }}_{\mathrm{t}}$ denotes the time-fixed effect; ${\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$ is the random error; and i and t denote cities and years, respectively.

In order to test the indirect effects of industrial structure upgrading, regional innovation level, and residents’ consumption capacity in the process of the digital economy empowering the high-quality development of the manufacturing industry in the Yangtze River Economic Belt, this study chose to construct a mediating effect model to make analysis. The mediating effect model can reveal the specific path of the impact of the digital economy on the high-quality development of the manufacturing industry. Under the context of the rapid development of the digital economy, the digital economy may affect the manufacturing industry through industrial upgrading, technological innovation, and other channels. The mediating effect model can test whether these channels really exist and quantify their respective roles, so as to build a more complete and systematic analytical framework. The mediating effect model below is constructed with reference to a research method from Wen Zhonglin et al. [33]:

$$Me{d}_{it}={\alpha }_0+{\alpha }_1{DE}_{it}+{\alpha }_3{X}_{it}+{\gamma }_i+{\sigma }_t+{\epsilon }_{it}$$

(2)

$${HDM}_{it}={\theta }_0+{\theta }_1{DE}_{it}+{\theta }_{2}Me{d}_{it}+{\theta }_3{X}_{it}+{\gamma }_i+{\sigma }_t+{\epsilon }_{it}$$

(3)

where $Me{d}_{it}$ is the mediating variable, specifically including industrial structure upgrading (Str), the regional innovation level (Inn), and residents’ consumption capacity (Con).

In order to deeply measure the threshold effect of how environmental regulations in the process of the digital economy empower the high-quality development of the manufacturing industry in the Yangtze River Economic Belt, this study constructed the following panel threshold effect model:

$$\begin{gathered} {HDM}_{it}={\mu }_0+{\mu }_1{DE}_{it}·I(thr{e}_{it}\le {\mathsf{\phi }}_1)+{\mu }_2{DE}_{it}·I({\mathsf{\phi }}_2\ge thr{e}_{it}>{\mathsf{\phi }}_1)+\cdots \cdots \\ +{\mu }_{n+1}{DE}_{it}·I(thr{e}_{it}>{\mathsf{\phi }}_{\mathrm{n}})+\rho X_{it}+{\gamma }_i+{\sigma }_t+{\epsilon }_{it} \end{gathered}$$

(4)

where $thr{e}_{it}$ denotes the threshold variable, which is the environmental regulation level (Env) in this study; $\mathsf{\phi }$ denotes the threshold value; n denotes the number of thresholds; and $I$ denotes an indicator function: 1 will be assigned as its value if the condition in the parentheses of the function is met, and 0 will be assigned if the condition is not met.

2.2.2. Selection of Variables

• Explained variable

The high-quality development of the manufacturing industry (HDM) is a multidimensional and multi-level concept involving a lot of aspects. The measurement method for high-quality development of the manufacturing industry has not yet been agreed on so far. Based on the reality of the manufacturing industry’s development in the Yangtze River Economic Belt, as well as the availability of data, this study constructed an index system in three levels, i.e., the development environment, the development scale, and the green development (see

Table 1. A comprehensive evaluation indicator system for the high-quality development of the manufacturing industry.

1st-Level Indicators	2nd-Level Indicators	3rd-Level Indicators
The manufacturing industry’s development environment	Governmental investment in science and technology	The percentage of local science and technology expenditure in local GDP (%)
	Urbanization level	Percentage of the local urban population in the total local population (%)
The manufacturing industry’s development scale	Value added to the manufacturing industry	Industrial added value (RMB ×10,000)
	The scale of manufacturing enterprises	The number of industrial enterprises above the designated size (unit)
The manufacturing industry’s green development	The energy input of the manufacturing industry	Total local energy consumption (×10,000 tons of standard coal)
	Industrial wastewater emission	Industrial wastewater emission (tons)/industrial output value (%)
	Industrial waste gas emission	Industrial sulfur dioxide emission (tons)/industrial output value (%)
	Industrial solid waste emission	Industrial smoke and dust emission (tons)/industrial output value (%)

). Then, the entropy method is utilized to obtain the high-quality development index of the manufacturing industry in each city of the Yangtze River Economic Belt. The government’s investment in science and technology is an important driving force for the high-quality development of the manufacturing industry. The increase in the level of urbanization means that more labor, capital, and other resources become concentrated in cities, thus providing a broader market and richer resources for the manufacturing industry; clearly, it is a key element for the high-quality development of the manufacturing industry. The added value of the manufacturing industry and the size of the manufacturing industry can reflect the expansion of the manufacturing industry’s production activities and the hiking of the economic efficiency in a certain region. Green development is an inevitable requirement for the high-quality development of the manufacturing industry, and the green development indicator of the manufacturing industry can reflect the extent of the impact of the manufacturing industry on the environment in its production process. Therefore, the indicator system established by this study is purposed to comprehensively and systematically demonstrate the high-quality development of the manufacturing industry.

In order to exhaustively explore the spatial distribution and evolution of the high-quality development of the manufacturing industry in the cities of the Yangtze River Economic Belt, this study used ArcGIS 10.7 software to render spatial distribution maps (Figure 2 and Figure 3) for the levels of high-quality development of the manufacturing industry of these based on the data from 2011 and 2021. These maps visually demonstrate the development stages of the manufacturing industry from low-quality to high-quality by dividing them into five levels in different color shades. By comparing the spatial distribution of these points in time, it is possible to observe the dynamic changes in the manufacturing industry’s high-quality development in the Yangtze River Economic Belt. As seen, in the initial stage of the study, i.e., in 2011, although the clustering trend of high-quality development appeared, it was still at a low level overall. However, by 2016 and 2021, the quality of the manufacturing industry’s development had been significantly improved, and the regions with medium-high and high levels of development began to concentrate and appear in continuous areas. By analyzing the data in 2021 in detail, this study found significant differences in the quality of manufacturing development between regions. A high level of manufacturing development was generally reached in downstream cities, while relatively few cities in the midstream region reached this level.

2.

Explanatory variable

Digital economy (DE): As an emerging industry form, the digital economy has so far not obtained a unified and standardized definition, resulting in diversified measurement methods. In reference to research by Zhao Tao et al. [34], this study took the development of the Internet as the core of measurement, plus the three major indexes of digital inclusive finance, to construct an index system which takes into account both the connotation of the digital economy and data availability. The penetration degrees of the Internet and mobile Internet directly reflect the popularization and implementation of digital infrastructure, which is the basis for the development of the digital economy. The Internet-related outputs and employees can measure the contribution and employment-driven capacity of the Internet industry in the digital economy. The development of digital inclusive finance, as an important part of the digital economy, directly showcases the overall level of development of the digital economy; therefore, the inclusion of digital inclusive finance into the digital economy indicator system can more comprehensively reflect the connotation and denotation of the digital economy. As a result, on the basis of data availability, the indicator system established by this study can comprehensively and systematically measure the overall development of the digital economy and provide a scientific basis for policymakers. The indicators are shown in

Table 2. A comprehensive evaluation indicator system for the development level of the digital economy.

1st-Level Indicators	2nd-Level Indicators	3rd-Level Indicators
Internet development	Internet penetration	Internet users per 100 people (users/100 people)
	Mobile Internet penetration	Mobile phone users per 100 people (users/100 people)
	Internet-related output	Total telecommunication services per capita (RMB/person)
	Internet-related employees	Percentage of employees in computer services and software
Digital-inclusive finance	Development level of digital inclusive finance	Coverage breadth indicator of digital finance
		Usage depth indicator of digital finance
		Digitization degree of digital finance

in detail.

Figure 4 and Figure 5 illustrate the spatial distribution patterns of the digital economy’s development levels in the Yangtze River Economic Belt in 2011 and 2021, respectively. The results of the analysis show that the spatial layout of the digital economy in the Yangtze River Economic Belt changed significantly over time: the original pattern dominated by primary and low-intermediate levels of development gradually gave way to intermediate and high levels of development. In addition, it can also be observed that high-level development areas gradually converged into more concentrated areas from their original fragmented states. This change maps out the growingly prominent trend of convergence in the development of the digital economy. Further exploration of the 2021 data reveals that the digital economy development in the Yangtze River Economic Belt exhibited a remarkable geographic gradient. In particular, the downstream regions, especially the Yangtze River Delta urban agglomeration, had risen to become leaders in the digital economy’s development. Although the development of the digital economy in the midstream regions also showed a certain degree of vitality, there is still a certain gap compared to the prosperity of the downstream regions. Undoubtedly, such an unbalanced development between regions reveals the existence of a “digital divide” phenomenon.

3.

Mediating variables

①

Upgrading of industrial structure (Str): The upgrading of industrial structures is the inevitable result of regional economic transformation. According to the Clark Theorem, the upgrading of industrial structures is usually measured by the proportion of non-agricultural output value. However, in the context of the digital economy, the growth rate of the secondary industry is lower than that of the tertiary industry, and this trend has become a basic feature of current industrial development [26]. Therefore, this study adopted the ratio of the value added of the tertiary industry to the local GDP to demonstrate the industrial structure upgrading.

②

Regional innovation level (Inn): The granting of patents implies that certain progress with originality and practicality has been made in relevant technology fields, and such progress is an important manifestation of innovation output. Thus, the number of patents granted, as a key indicator to measure technological innovation and invention activities, can directly reflect the innovation capacity of a region. Therefore, this study adopted the number of patents per capita in a city as an indicator of regional innovation level.

③

Consumption capacity of residents (Con): By referring to the research of Zhou Zheng et al. [35], this study adopted the total social consumer goods per capita, i.e., the ratio of total retail sales of social consumer goods to the number of permanent resident population in a city.

4.

Threshold variable

Environmental regulation (Env): This study drew on the research method of Chen Shiyi et al. [36] to count the frequency of “environmental protection”-related terms in local government work reports of different regions, and then calculated the proportion of these terms in the full text of such reports, so as to measure the intensity of environmental regulation across regions.

5.

Control variables

① The degree of government intervention (Gov), as expressed by the ratio of local general budget expenditures to local GDP: the degree of government intervention can help accurately identify the net effect of the digital economy on the development of the manufacturing industry and exclude the interference of other factors, such as government intervention. ② The level of foreign direct investment (Fdi), as expressed by the ratio of foreign direct investment to local GDP: firstly, FDI may bring advanced technology and management experience, which can deliver a positive impact on technological innovation and productivity enhancement in the manufacturing industry; secondly, FDI may also promote market competition and drive local manufacturing enterprises to continuously improve their competitiveness. ③ The transportation infrastructure (Tra), as expressed by the ratio of the mileage of highways to the area of a city: In the Yangtze River Economic Belt, highways are one of the most important modes of transportation, so their development level would have a direct impact on the manufacturing industry’s raw material procurement, product transportation, market expansion, and other key links. ④ The level of economic development (Eco), as expressed by per capita regional GDP is directly related to the development environment and potential of the manufacturing industry. In addition, this study controlled the city-fixed effect (City) and the year-fixed effect (Year).

2.2.3. Data Sources and Descriptive Statistics

Based on the availability and integrity of data, this study took 108 cities in the Yangtze River Economic Belt as the research sample. By selecting the panel data from 2011 to 2021, this study explored the effect of the digital economy empowering the high-quality development of the manufacturing industry in the Yangtze River Economic Belt. The data relating to the high-quality development of the manufacturing industry came from the China Urban Statistical Yearbook, China Industrial Statistical Yearbook, and the statistical yearbooks of provinces and cities in the Yangtze River Economic Belt; the data related to the digital economy came from the China Urban Statistical Yearbook, Peking University’s Center for Digital Finance Research, and the statistical yearbooks of provinces and cities in the Yangtze River Economic Belt; the data for the mediating variables and control variables mainly ame from the China Urban Statistical Yearbook; and the data for the threshold variables were mainly derived from the government work reports of cities. The financial expenditure data of Chizhou City, Pu’er City, and Jingmen City in 2011 were missing, and the environmental regulation data of Ya’an and Ziyang cities in 2020 were missing. The interpolation method can maintain the original structures and distribution characteristics of data, making the processed dataset more in line with the actual situation, thus conducive to the subsequent data analysis and modeling. At the same time, it should be noted that interpolation for filling in the missing values may change the distribution characteristics of the original data; especially when there are a lot of missing data or large distribution differences, this effect may be more significant, and changes in data distribution may compromise the subsequent data analysis and modeling. In this study, the amount of missing data was small; therefore, in order to maintain the integrity of the data and the coherence of the analysis, the interpolation method was used to supplement the missing data. The data were mainly derived from provincial and municipal statistical yearbooks and the China Urban Statistical Yearbook. Some missing data were supplemented with the interpolation method. The descriptive statistics of the variables are shown in

Table 3. Descriptive statistics of the explained variables, explanatory variables, mediating variables, threshold variables, and control variables.

Variable Name	Data Volume	Minimum Value	Maximum Value	Mean Value	Median Value	Standard Deviation
HDM	1188	0.018	0.809	0.119	0.082	0.111
DE	1188	0.058	0.956	0.411	0.411	0.139
Str	1188	0.272	5.072	0.968	0.905	0.443
Inn	1188	0.001	1.441	0.139	0.069	0.176
Con	1188	0.141	8.396	2.170	1.869	1.305
Env	1188	0.0003	0.012	0.003	0.003	0.001
Gov	1188	0.071	5.087	0.536	0.393	0.449
Fdi	1188	0.0001	0.839	0.051	0.034	0.061
Tra	1188	0.004	5.144	0.274	0.139	0.402
Eco	1188	9.091	12.201	10.766	10.755	0.594

.

3. Results

3.1. Benchmark Regression Results

This study used the F-test and Hausmann test to determine the applicability of models. The results showed that the fixed effect model should be adopted. Therefore, this study used the double fixed effect model to conduct the benchmark regression. The double fixed effect model is a kind of model that considers both individual fixed effects and time fixed effects in panel data analysis, and it aims to eliminate the effects on dependent variables of the individual-specific factors that do not vary over time as well as the time-specific factors that do not vary with individuals. The results are shown in

Table 4. Results of the benchmark regression for the digital economy’s effect on the high-quality development of the manufacturing industry in the Yangtze River Economic Belt.

	(1)	(2)	(3)	(4)
	HDM	HDM	HDM	HDM
	Full Sample	Full Sample	Small-Sized Cities	Large-Sized Cities
DE	0.188 ***	0.138 ***	0.058 **	0.125 **
	(4.846)	(4.608)	(2.563)	(2.401)
Gov		0.013 ***	0.018 ***	0.026 *
		(3.897)	(7.752)	(1.775)
Fdi		0.030	0.059	−0.095
		(0.679)	(1.546)	(−1.188)
Tra		0.034 **	0.016	0.017
		(2.007)	(1.002)	(1.489)
Eco		−0.005	0.028 ***	−0.056 **
		(−0.371)	(3.516)	(−2.434)
cons	0.047 ***	0.097	−0.257 ***	0.727 ***
	(4.956)	(0.668)	(−2.951)	(2.935)
City	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes
N	1188	1188	757	431
R2	0.539	0.573	0.611	0.024

Note: The content in parentheses is t-statistics; * p < 0.1, ** p < 0.05, and *** p < 0.01.

. Column (1) shows that the impact coefficient of the digital economy is 0.188 and passes the significance test at 1% level, indicating that digital economy can remarkably empower the high-quality development of the manufacturing industry in the Yangtze River Economic Belt. On the basis of Column (1), control variables such as the degree of government intervention, the level of foreign direct investment, the transportation infrastructure, the level of economic development, and others were added for regression, with the results shown in Column (2). As seen, the impact coefficient of the digital economy is 0.138 and remains significant. Thus, Hypothesis 1 is verified. The reason for these results is that the key for the digital economy to promote the high-quality development of the manufacturing industry lies in data driving; the development of digital technology facilitates the digitization of the manufacturing process, with a close connection between the manufacturing industry chain’s upstream and downstream sections, the real-time exchange of information can be delivered, resulting in a massive amount of data, which fully infiltrate into the manufacturing process and the manufacturing environment. After the data are collected, sorted out, and mined, certain laws can be identified, so as to provide a basis for production and management, optimize resource allocation and production process, and boost the quality and efficiency of the manufacturing industry.

The coefficients of the control variables indicate that only the government intervention and the transportation infrastructure significantly affect the high-quality development of the manufacturing industry in the Yangtze River Economic Belt, and both of them make a positive contribution. On the one hand, by adjusting the proportion of fiscal expenditure to GDP, the government is able to accurately guide the flow of social resources, optimize the construction of the market environment, and provide necessary public services and policy support for the manufacturing industry. On the other hand, the Yangtze River Economic Belt spans a number of provinces, so the interconnection of transportation infrastructure helps to break down geographical barriers and drive the flow and agglomeration of labor, capital, and many other factors along the river. This would not only expand the market space of manufacturing enterprises and reduce the cost of transportation but would also help to deliver the effect of economies of scale and drive the high-quality development of the manufacturing industry. The impact of FDI on the high-quality development of the manufacturing industry is not significantly correlated. This result may stem from a combination of multiple factors’ actions. Factors such as the policy environment, the degree of market openness, and the method of cooperation with foreign-funded firms in the Yangtze River Economic Belt may affect the role of FDI in the high-quality development of the manufacturing industry. In addition, it is necessary to take into account the possible negative impacts delivered by FDI. For instance, foreign-funded firms may compete with local enterprises for market shares and resources, leading to increased competition; meanwhile, foreign-funded enterprises may also pose a threat to local ones in terms of technological innovation and brand forging. Additionally, the coefficient of the impact of economic development level is negative, and the result is insignificant. The reason is that the manufacturing industry in the Yangtze River Economic Belt still is yet to be enhanced in terms of innovation ability. With the core and key technologies controlled by others, its manufacturing industry lacks core competitiveness in the process of high-quality development; thus, it is difficult to make full use of the improved level of economic development to drive up the upgrading and transformation of the industry.

Columns (3) and (4) present the regression results of city size sub-samples. The sub-sample test can deeply reveal the differences in the empowerment role of the digital economy for cities of different sizes, so as to provide an important reference basis for cities to formulate specific policies and measures. In reference to the relevant regulations, this study classifies the cities in the Yangtze River Economic Belt into megacities, supercities, large cities, and medium-sized cities based on their population in related years. According to the Notice of the State Council on Adjusting the Criteria for the Division of City Sizes, cities with a permanent resident population of less than 500,000 in urban areas are small cities; specifically, those with a resident population of more than 200,000 and less than 500,000 are Type-I small cities, and those with a resident population of less than 200,000 are Type-II small cities. Cities with a permanent resident population of more than 500,000 and less than 1 million in urban areas are medium-sized cities. Cities with a permanent resident population of more than 1 million and less than 5 million in urban areas are large cities; specifically, cities with a resident population of more than 3 million and less than 5 million in urban areas are Type-I large cities, and those with a resident population of more than 1 million and less than 3 million are Type-II large cities. Cities with a permanent resident population of more than 5 million and less than 10 million in urban areas are supercities. Cities with a permanent resident population of more than 10 million in urban areas are megacities. Due to the small sample of megacities and medium-sized cities, this study consolidated large cities and medium-sized cities into the small-sized city group, while consolidating megacities and supercities into the large-sized city group. As shown in Table 4, for cities of different sizes, the digital economy can empower the high-quality development of the manufacturing industry. The regression coefficients of the digital economy for the large-sized cities and small-sized cities are 0.125 and 0.058, respectively, indicating that the larger the city size, the stronger the empowering role of the digital economy. The reason for this result may be that large cities enjoy advantages in terms of talent, technology, market, infrastructure, etc., and such advantages provide favorable conditions for the deep integration between the digital economy and the manufacturing industry. Moreover, in small-scale cities, economic development can significantly promote the high-quality development of the manufacturing industry; in larger cities, however, economic development may inhibit the high-quality development of the manufacturing industry. The reason is that smaller cities tend to own relatively concentrated resources and offer more policy support for the manufacturing industry, with relatively weak market competition; their level of economic development can effectively promote the high-quality development of the manufacturing industry. On the other hand, due to dense population and concentration industries, larger cities often face heavy pressure in terms of resources and environments, leading to the result that the manufacturing industry enterprises in large cities often encounter such high production costs and environmental protection pressures that they cannot achieve high-quality development. In addition, large cities often own a more complete industrial system, so it is difficult for their traditional manufacturing enterprises to quickly transform and upgrade themselves to high-end manufacturing ones due to historical reasons and path dependence.

3.2. Test of the Mediating Effect

In the Benchmark Model (1), the impact coefficient of the digital economy is significantly positive, and this result satisfies the prerequisite of the mediating effect test.

Table 5. The test results of the mediating effect of industrial structure upgrading, regional innovation level, and residents’ consumption capacity.

	(1)	(2)	(3)	(4)	(5)	(6)
	Str	HDM	Inn	HDM	Con	HDM
DE	0.365 *** (18.759)	0.051 ** (2.144)	0.077 ** (2.444)	0.087 *** (4.427)	1.975 *** (13.521)	0.058 *** (2.636)
Str		0.149 *** (4.798)
Inn				0.236 *** (13.092)
Con						0.024 *** (5.719)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
cons	0.080 (1.291)	−0.681 *** (−10.315)	−1.895 *** (−18.871)	−0.221 *** (−3.110)	−13.874 *** (−29.853)	−0.342 *** (−3.928)
N	1188	1188	1188	1188	1188	1188
R2	0.482	0.583	0.616	0.629	0.851	0.586

Note: The content in parentheses is t-statistics; ** p < 0.05 and *** p < 0.01.

illustrates the results of the mediating effect test. As shown in Columns (1) and (2), the impact coefficient of the digital economy on industrial structure upgrading is 0.365, and the impact coefficient of industrial structure upgrading on the high-quality development of the manufacturing industry is 0.149, both passing the significance test at the 1% level. The above results indicate that the digital economy can effectively drive the upgrading of the industrial structure of the Yangtze River Economic Belt, and the chain effect generated by the upgrading of the industrial structure can, in turn, promote the further enhancement of the manufacturing industry effectively. Thus, a benign mutual promotion and synergistic development relationship is formed between the digital economy, the upgrading of the industrial structure, and the high-quality development of the manufacturing industry. Therefore, Hypothesis 2 is valid.

As can be observed in Columns (3) and (4) in Table 5, the impact coefficient of the digital economy on the regional innovation level is 0.077, and the impact coefficient of the regional innovation level on the high-quality development of the manufacturing industry is 0.236, both passing the significance test at the 1% level. These results indicate that the application of digital technology has facilitated the efficient flow of information as well as the optimal allocation of resources, accelerated the generation and dissemination of new knowledge and new technology, created favorable conditions for the improvement of the regional innovation level, and boosted the agglomeration of innovation resources as well as innovation activities. Furthermore, the feedback mechanism formed by the regional innovation level of the Yangtze River Economic Belt has offered a core driving force for the transformation and upgrading of the manufacturing industry. Therefore, Hypothesis 3 is established.

As seen in Columns (5) and (6) in Table 5, the impact coefficient of the digital economy on residents’ consumption capacity is 1.975, and the impact coefficient of residents’ consumption capacity on the high-quality development of the manufacturing industry is 0.024, both passing the significance test at the 1% level. These results indicate that the digital economy can remarkably boost the consumption level of the residents in the Yangtze River Economic Belt by improving the residents’ incomes and enriching the supply of commodities and services. On the other hand, the residents’ growing demands for high-quality, high-value-added products and services have facilitated the quality upgrading and structural adjustment of the manufacturing industry in the Yangtze River Economic Belt. Therefore, Hypothesis 4 is valid.

3.3. Test of the Threshold Effect

This study adopted the self-sampling method to verify whether the threshold effect exists in the process of the digital economy influencing the high-quality development of the manufacturing industry, while further determining the threshold value and the corresponding model form. In order to ensure the reliability of the results, this study has chosen a sufficient bootstrap sample size, and an appropriate sample size is determined based on data characteristics and research needs. Meanwhile, when conducting the threshold effect test, this study explicitly sets up the null hypothesis and alternative hypothesis, while conducting rigorous hypothesis testing based on the bootstrap samples. According to the test results in

Table 6. Test of threshold effect.

Model	F-Value	p-Value	Self-Sampling Times	Critical Value
				1%	5%	10%
Single threshold	4.609 *	0.100	100	11.996	7.082	4.646
Double threshold	12.808 ***	0.000	100	8.981	3.591	1.897
Triple threshold	1.992	0.140	100	9.101	4.840	2.758

Note: The content in parentheses is t-statistics; * p < 0.1 and *** p < 0.01.

, this study adopts a double threshold model for analysis. The specific threshold estimates of environmental regulation are shown in

Table 7. Test of threshold estimates for environmental regulation.

	Threshold Estimate	95% Confidence Interval
Ito1	0.002	[0.001, 0.008]
Ito2	0.004	[0.004, 0.005]

, which are 0.002 and 0.004. The double-threshold effect threshold of environmental regulation implies that in the process of boosting the high-quality development of the manufacturing industry in the Yangtze River Economic Belt, the effect of the digital economy’s function is significantly compromised by the intensity of environmental regulations in different stages. This effect is not linear but with two key turning points (i.e., thresholds). As a result, under different levels of environmental regulation, the promotion of the digital economy on the high-quality development of the manufacturing industry demonstrates different strengths and directions.

Table 8. The test results of the double threshold effect of environmental regulation.

	HDM
DE (Env < 0.002)	0.163 ***
	(12.310)
DE (0.002 ≤ Env < 0.004)	0.189 ***
	(12.350)
DE (0.004 ≤ Env)	0.157 ***
	(11.500)
Gov	0.013 ***
	(4.010)
Fdi	0.034
	(1.840)
Tra	0.036 ***
	(7.870)
Eco	0.008
	(1.530)
_cons	−0.049
	(−0.980)
City	Yes
YEAR	Yes
N	1188
R2	0.548

Note: The content in parentheses is t-statistics; *** p < 0.01.

illustrates the regression results of the threshold effect test when environmental regulation is used as the threshold variable. As can be seen, the impact coefficient of the digital economy varies with environmental regulation, but it is always positive, while passing the significance test at the 1% level. When the value of environmental regulation is below the threshold value of 0.002, the impact coefficient of the digital economy is 0.163; when the intensity goes across the first threshold, the impact coefficient of the digital economy increases significantly; when the intensity goes across the second threshold, the impact coefficient of the digital economy decreases significantly and becomes lower than the coefficient when the intensity of environmental regulation is at the first threshold value. It can be seen that under the constraint of environmental regulation, the digital economy has a significant empowering effect on the high-quality development of the manufacturing industry in the Yangtze River Economic Belt, and this empowering effect rises up and then goes down with the enhanced intensity of environmental regulation.

The reason for this is that when the intensity of environmental regulation is at a low level, the environmental protection pressure on manufacturing enterprises is weak, so digital technology can be applied mainly to improving production efficiency and reducing costs, with less consideration for energy saving, emission reduction, and green development. With gradually strengthened environmental regulation, manufacturing enterprises have to ensure technological innovation and process optimization to meet environmental standards, and such innovations are often closely combined with digital technology. For example, production lines are intelligentized to reduce resource waste or data analysis is deployed to hike energy efficiency. At this stage, environmental regulation becomes a “catalyst” to facilitate the manufacturing industry to actively adopt digital technology and realize green transformation. The flexibility, efficiency, and innovation of the digital economy can be better brought into play under the condition of environmental regulation, thus delivering enhanced promotion for the manufacturing industry. However, when the intensity of environmental regulation is too high, enterprises may not invest enough in technological innovation and green transformation, due to excessive environmental pressure and cost burden, thus inhibiting the positive facilitating effect of the digital economy to a certain extent.

3.4. Robustness Test

In order to verify the robustness of the above findings, this study conducted the following tests: ① Replacing the models: Given that the explanatory variables in this study are non-negative, a left-truncated panel Tobit model was constructed, with the test results showcased in Column (1) of

Table 9. Robustness test.

	(1)	(2)	(3)	(4)
	HDM	HDM	HDM	HDM
DE	0.174 ***	0.142 ***	0.118 **
	(6.695)	(4.645)	(4.282)
LDE				0.104 ***
				(3.270)
Gov	0.013 ***	0.017 ***	0.014 **	0.004
	(3.806)	(7.131)	(4.604)	(1.030)
Fdi	0.038 **	−0.098	0.042	0.070 ***
	(2.057)	(−1.636)	(1.174)	(4.440)
Tra	0.039 ***	0.086 ***	0.102 **	0.022 ***
	(8.827)	(3.404)	(3.721)	(5.040)
Eco	0.009	0.015 *	0.001	−0.014 *
	(1.494)	(1.660)	(0.070)	(−1.940)
_cons	−0.059	−0.124	0.017
	(−0.929)	(−1.343)	(0.139)
City	Yes	Yes	Yes	Yes
YEAR	Yes	Yes	Yes	Yes
N	1188	972	1161	1080
R2	/	0.611	0.577	0.944

Note: The content in parentheses is t-statistics; * p < 0.1, ** p < 0.05, and *** p < 0.01.

. It can be seen that the results are consistent with the results acquired above. ② Changing the research scope: In terms of time dimension, this study intercepted the data of the Yangtze River Economic Belt in 2019 and earlier for the regression analysis, so as to eliminate the interference of the pandemic; in terms of individual dimension, two municipalities, i.e., Shanghai and Chongqing, were excluded, and then regression analysis was carried out for the remaining 106 cities, so as to remove the interference of extreme values. The test results are shown in Columns (2) and (3) in Table 9, which are consistent with the findings acquired above. ③ Control over endogeneity: In view of the possible correlation between the explanatory variables and the error term, this study used the one-phase lagged variable of the digital economy (DE) (i.e., LDE) as an instrumental variable to conduct the endogeneity test. Column (4) demonstrates the endogeneity test results, which are consistent with the findings acquired above.

4. Discussion

Based on the summary of the existing literature, the following deficiencies are found: First, the current research on the Yangtze River Economic Belt is more about high-quality economic development or total factor productivity, but less about the high-quality development of the manufacturing industry. Second, the research on the enabling mechanism of the digital economy for the high-quality development of the manufacturing industry has not yet formed a complete system. Third, the current research on the nonlinear relationship between the digital economy and the high-quality development of the manufacturing industry is not enough, and the heterogeneity analysis is mainly from the research perspective of the upper middle and lower reaches, ignoring the differences of individual cities. On the basis of previous studies, this paper attempted to carry out a more systematic study on the digital economy enabling the high-quality development of the manufacturing industry in the Yangtze River Economic Belt. Therefore, the innovation of this paper is mainly reflected in the following aspects: First, the innovation of the research perspective. This study has a certain practical guiding value for the high-quality development of the manufacturing industry in the Yangtze River Economic Belt and even the high-quality economic development of the Yangtze River Economic Belt. Most current heterogeneity studies are divided by region, ignoring the individual differences between cities. Therefore, this paper analyzed heterogeneity by city size division, which provided certain data support for the government to develop the digital economy according to local conditions and promote the transformation and upgrading of the manufacturing industry. Second, the innovation of research content. Starting from the internal mechanism of high-quality development of the manufacturing industry, namely the supply side, the external environment, and the demand side, this paper systematically examined the impact path of the digital economy on the high-quality development of the manufacturing industry, enriching the research on enabling mechanism of the digital economy. Environmental regulation is an important link in the green development and even high-quality development of the Yangtze River Economic Belt and is closely related to the high-quality development of the manufacturing industry in the Yangtze River Economic Belt. This paper innovatively incorporated environmental regulation into the research framework and supplemented the non-line of the digital economy to the high-quality development of the manufacturing industry.

There are still several areas that can be further improved: First, the sample time should be extended and the study sample should be increased. This study took 108 prefecture-level cities and above covered by the Yangtze River Economic Belt from 2011 to 2021 as the research object. Since the data on the dimension of digital inclusive finance start from 2011, this paper adopted the data from 2011 to 2021, and the time span of the selected sample data was relatively short. At the same time, due to the limitations of data sources and data integrity, this paper did not cover the ethnic minority autonomous prefectures in the Yangtze River Economic Belt and the newly established prefecture-level cities od 2011 and later, which may have led to insufficient insight into the development process and characteristics of some specific regions. Based on the data availability and the comprehensiveness of the research, future studies can expand the sample data interval and further improve the research scope, so as to reveal the overall picture of the development of the Yangtze River Economic Belt in a more comprehensive and in-depth way. Second, the index system should be enriched. Due to the complexity and difficulty in obtaining relevant data on the digital economy and the manufacturing industry in prefecture-level cities, this study may have failed to cover all key elements when constructing an evaluation index system, resulting in a lack of comprehensiveness of the index system. Future studies can further improve the definition of the digital economy and high-quality development of the manufacturing industry and try to add more indicators to build a more scientific and comprehensive digital economy development indicator system and high-quality development indicator system of the manufacturing industry, so as to more accurately and comprehensively reflect the real situation of the Yangtze River Economic Belt.

5. Conclusions

Based on the panel data of 108 cities in the Yangtze River Economic Belt from 2011 to 2021, this study delivers an in-depth exploration of the specific mechanism for the digital economy to empower the high-quality development of the manufacturing industry, while further discussing the mediating effects of the upgrading of the industrial structure, the regional innovation level, the residents’ consumption capacity, as well as the threshold effect of environmental regulation. The following conclusions are found: ① The digital economy has significantly promoted the high-quality development of the manufacturing industry in the Yangtze River Economic Belt. The larger the city size, the stronger the empowering effect of the digital economy. ② As shown in the analysis of the mediating effect, the digital economy can effectively drive the high-quality development of the manufacturing industry in the Yangtze River Economic Belt by boosting the upgrading of the industrial structure, enhancing the level of regional innovation, and strengthening the consumption capacity of residents. ③ With gradually intensified urban environmental regulation, the enabling role of the digital economy has demonstrated a trend of rising first and then declining; in other words, there is a threshold effect of environmental regulation in the process of the digital economy empowering the high-quality development of the manufacturing industry.

6. Policy Recommendations

Currently, the fast development of the digital economy is ushering in a major transformation in the mode of social production as well as a profound change in the way of life of human beings, while providing a new impetus for the high-quality development of the manufacturing industry. Therefore, based on the theoretical and empirical research results as previously discussed, in order to give better play to the enabling effect of the digital economy, to facilitate the manufacturing industry of the Yangtze River Economic Belt to get rid of its difficulties in a faster manner, and to deliver high-quality development, this study puts forward the corresponding policy recommendations in three dimensions: to develop the digital economy in accordance with the local conditions, to continuously promote the double-end drive from both supply and demand sides, and to fully improve the external development environment.

6.1. To Develop the Digital Economy in Accordance with Local Conditions

①

To accelerate the deep integration between the digital economy and the manufacturing industry

In order to accelerate the in-depth integration between the digital economy and the manufacturing industry in the Yangtze River Economic Zone, and thus drive the high-quality development of the manufacturing industry, the government should adopt a series of comprehensive strategies. Firstly, the government should strengthen top-level design and policy guidance, clarify the strategic planning for the integration between the digital economy and the manufacturing industry, and formulate specific implementation programs and timetables. On the basis of the above work, the government should provide strong policy support and financial guarantees for the integrated development of the digital economy and the manufacturing industry through financial, tax, and other policy measurements. In the meantime, the government should increase its investment in the development of the digital economy, especially in the fields of infrastructure construction and technical R&D, so as to lay a solid foundation for the digital transformation of the manufacturing industry.

Additionally, the government should actively guide enterprises to participate in the process of integration between the digital economy and the manufacturing industry. By setting up a platform for cooperation between industries, universities, research institutes, and users, the government would encourage enterprises to boost cooperation with universities and research institutes, so as to jointly develop new technologies and products, while promoting the transformation and upgrading of the manufacturing industry in the intelligence-, green- and service-based direction. Furthermore, the government should also strengthen quality supervision and drive the manufacturing industry to high-quality and high-end levels. By improving the quality management system, the government could improve the quality control ability of enterprises, so as to ensure the stability of product quality and performance.

②

To implement differentiated development strategies

In the process of promoting the development of the digital economy, governmental agencies should attach great importance to the differences in the digital economy’s empowerment for high-quality development of the manufacturing industry in different regions. These differences are not only reflected in the size of cities but also involve the industrial structure, resource endowment, innovation capacity, and other aspects of each region. Therefore, when formulating digital economy development strategies, local governments should take these differences into full consideration, so as to design differentiated strategies that can meet the characteristics of their respective regions according to their local conditions.

For megacities and supercities, given that they have solid economic foundations, strong technological innovation capacity, and abundant human resources, the government should focus on supporting the high-end technology R&D and industrial upgrading of these cities in the digital economy. For example, by building high-level digital economy industrial parks, they can attract top technology enterprises in China and foreign nations, while boosting the R&D and deployment of cutting-edge technologies, such as cloud computing, big data, and artificial intelligence. Moreover, by virtue of their strong radiation-driven capabilities, these cities can establish close digital economy partnerships with neighboring cities, so as to jointly create a regional digital economy ecosystem. For large and medium-sized cities, the government should pay more attention to the digital transformation and intelligent upgrading of industries in the development of the digital economy. These cities tend to have a certain industrial base, but possibly with relatively weak technological innovation capabilities and human resources. Therefore, the government can, by providing policy support and financial assistance, help enterprises adopt advanced digital technology and equipment, so as to improve their productivity and product quality. At the same time, the government can encourage enterprises to carry out industry–university–research cooperation with universities and research institutes, so as to jointly drive the digital transformation of industries. In addition, the government should actively promote cross-city cooperation in the digital economy by breaking down the constraints of administrative divisions, so as to deliver the efficient use of resources and complementarity of advantages. For example, a cross-city digital economy cooperation platform can be established to boost information exchange, resource sharing, and project cooperation among different cities. In this way, not only the efficiency of resource utilization can be improved, but the problems of vicious competition and duplicative construction can also be effectively avoided.

6.2. To Continuously Promote the Double-End Drive from Both Supply and Demand Sides

①

Driven by industrial upgrading

Government agencies should clarify the central position of digital technology in promoting the transformation and upgrading of the manufacturing industry and take the digital economy as an important hand in facilitating the upgrading of the industrial structure of the Yangtze River Economic Belt. By formulating and implementing a series of policy measures, the government can guide and encourage enterprises to enhance the R&D and implementation of digital technology. For example, special funds can be set up to support enterprises in carrying out digital transformation, deploying advanced intelligent manufacturing equipment and technology, and raising the level of automated and intelligent production. At the same time, government agencies should also actively promote the construction and usage of industrial Internet platforms, so as to promote information sharing and collaborative cooperation between upstream and downstream enterprises in the industrial chain. Through the industrial Internet platform, enterprises can implement a visualized, controllable, and intelligent production process, thus further hiking production efficiency and product quality. Further, the industrial Internet platform can also promote the connection between enterprises for supply and demand, optimize resource allocation, reduce operating costs, and enhance the competitiveness of the entire industrial chain. While promoting the application of digital technologies, government agencies should focus on the promotion and practice of green manufacturing ideas. Through environmentally friendly and energy-saving digital technologies, traditional manufacturing industries can be transformed into green manufacturing. For example, big data and artificial intelligence technologies can be used to monitor and optimize energy consumption and pollutant emissions in the production process in real-time, so as to reduce environmental pollution and resource waste. In addition, government agencies should strengthen their cooperation with universities and research institutions to pursue integrated industry–university–research development. Through attracting and training high-end talents, as well as strengthening the R&D and innovation of digital technology, a steady stream of technical support and talent guarantee can be provided for the transformation and upgrading of the manufacturing industry. Meanwhile, government agencies should also forge a perfect intellectual property protection system, so as to safeguard the technological innovation achievements of enterprises and ignite the innovation vitality and motivation of enterprises.

②

Driven by consumption

In the Yangtze River Economic Belt, by improving the social security system and raising the income of residents, the government can effectively bolster the confidence and ability of residents to consume, thereby expanding the domestic demand market for manufactured products and offering solid support for the high-quality development of the manufacturing industry. Firstly, the government can make use of big data and cloud computing technology to comprehensively analyze and optimize the social security system, so as to ensure the coverage and protection level of social security, thus stabilizing residents’ consumption expectations. At the same time, it should facilitate the digital transformation of social security services, so as to drive up the service efficiency and convenience and enhance residents’ trust in the social security system. Secondly, the government should actively push the digital transformation of industries and encourage enterprises to deploy advanced digital technologies for higher productivity, thereby creating more jobs and increasing residents’ wage income. Additionally, through such policy instruments as tax incentives and financial subsidies, the government can incentivize residents to participate in digital economy activities and further broaden their sources of income. In order to optimize the consumption environment, the government should strengthen market supervision, protect consumers’ rights and interests, and crack down on counterfeiting and online fraud, so as to create a safe and honest consumption atmosphere. At the same time, it should, by utilizing big data and artificial intelligence technologies, gain precise insights into residents’ consumption demands while guiding manufacturing enterprises to develop new products and services in line with market trends, so as to effectively stimulateconsumption potentials. Finally, the government should make heavy investment into digital infrastructure, boost network coverage and data transmission speeds, lower the threshold for residents to access the digital economy, and ensure the inclusion of the digital economy. This move will help to further enhance residents’ consumption capacity and offer a sustained demand momentum for the high-quality development of the manufacturing industry.

6.3. To Fully Improve the External Development Environment

①

To raise the level of regional innovation

By bolstering investments in scientific research, encouraging industry–university–institute cooperation, and strengthening supervision and evaluation, it is possible to effectively enhance the regional innovation level and in turn to promote the high-quality development of the manufacturing industry in the Yangtze River Economic Belt. Driven by the digital economy, these measures will inject a powerful impetus into the transformation and upgrading of the manufacturing industry in the Yangtze River Economic Belt, so as to help it deliver higher-quality development in a more sustainable manner. Government agencies should understand the key role of research investment in promoting the high-quality development of the manufacturing industry in the Yangtze River Economic Belt while formulating relevant policies and measures to ensure the sustained growth of research investment. This practice includes setting up special funds for scientific research, supporting the R&D activities of enterprises, universities, and research institutes in areas such as the digital economy and smart manufacturing, as well as providing financial support and tax incentives for industry–university–research cooperation projects. In order to strengthen industry–university–research cooperation, government agencies should actively build up platforms to promote information exchange and cooperation between enterprises, universities, and research institutions. Interfacing activities between enterprises, universities, and research institutes can be held regularly, so as to drive the transformation and implementation of technological results. In addition, enterprises are encouraged to set up R&D centers, co-build laboratories or technological innovation centers with universities and research institutions, and jointly carry out technological R&D and innovation activities.

②

To deepen regional openness to the outside world

The government should embody the degree of openness to the outside world through countermeasures such as deepening international trade cooperation, optimizing the environment for foreign investment, strengthening international cooperation in technology innovation, and advancing international cooperation and exchanges on the digital economy, so as to boost the role of the digital economy in promoting the manufacturing industry in the Yangtze River Economic Belt. This will help the manufacturing industry in the Yangtze River Economic Belt to deliver high-quality development and enhance its international competitiveness.

Firstly, the government should deepen international trade cooperation and actively expand the international market. By strengthening economic and trade exchanges with countries and regions along the “Belt and Road”, the government can push the products from the manufacturing industry of the Yangtze River Economic Belt to the world. At the same time, it should encourage enterprises to participate in international exhibitions, forums and other events, so as to demonstrate the power and characteristics of the manufacturing industry in the Yangtze River Economic Belt and explore more international cooperation opportunities. Secondly, the government should optimize the environment for foreign investment, so as to appeal to foreign investment. By relaxing the admission threshold for foreign investment, simplifying the approval process, and taking other measures, the Yangtze River Economic Belt can attract more foreign enterprises. At the same time, a sound foreign investment service system should be established; one-stop services for foreign-funded enterprises should be provided to address the troubles they may encounter in the investment process. The introduction of foreign investment can not only bring financial and technical support to the manufacturing industry but can also promote local enterprises to meet international standards and enhance their overall competitiveness. Meanwhile, enterprises should be encouraged to introduce advanced foreign management ideas and methodologies, so as to enhance their management level and production efficiency. Finally, the government should facilitate international cooperation and exchanges in the field of digital economy. Through strengthened cooperation with other countries and regions in this field, new modes and paths can be jointly explored for the development of the digital economy.

③

To formulate rational environmental regulatory policies

Nowadays, as environmental protection is increasingly emphasized, how the government could scientifically and effectively enforce environmental regulation has become an urgent issue, so as to achieve the purpose of protecting the environment, while not imposing an excessive burden on the society and economy. On the other hand, in the face of environmental regulation, how manufacturing enterprises can make positive responses is an important topic currently, so as to deliver sustainable development through digital transformation.

For environmental regulation, the government should scientifically formulate and adjust relevant regulations first. This means that the government should enact environmental regulations that are in line with local realities, based on the current state of the environment as well as the development trends, while taking into account the advanced environmental protection concepts and practices at home and abroad. Additionally, these regulations should not be set in stone; rather, they should be adjusted in due course with changes in environmental conditions as well as advances in environmental protection technology. Furthermore, the government should continuously optimize its environmental administration strategies and enhance the effectiveness of the enforcement of environmental regulations. The optimization of environmental administration strategies includes, without limitation, the following: strengthening publicity and education for environmental protection, improving the reward and punishment mechanisms for environmental protection, and establishing environmental protection information-sharing platforms. Through these measures, the environmental awareness of the public and enterprises can be strengthened, and their conscientiousness and enthusiasm in complying with environmental regulations can be enhanced. Moreover, it is also crucial to lift the effectiveness of the enforcement of environmental protection regulations. The government should step up law enforcement and ensure that the regulations are strictly enforced. In addition, it is also essential to establish a comprehensive mechanism for evaluating the effectiveness of environmental regulations. The government should assess the enforcement effectiveness of environmental regulations on a regular basis in order to identify and address problems in a timely manner. Such an evaluation mechanism should include both quantitative and qualitative aspects, taking into account both the improvement of environmental quality and the social and economic impacts. Nevertheless, the government must be cautious to avoid over-regulation when formulating and implementing environmental regulations. Over-regulation may lead to hiking operating costs of enterprises, or may even hurt their normal operation and innovation ability, which would in turn deliver negative impacts on the society and economy. Therefore, the government should search for a balance point between protecting the environment and promoting economic development.