From the record high temperatures caused by continuous increases in greenhouse gases (mainly carbon dioxide) to the prolonged fires in the Amazon rainforests of South America and the long-lasting forest fires in Australia, it is clear that curbing global warming is an important task and challenge for all of humankind. The increase in carbon emissions will directly lead to global warming, causing extreme weather such as typhoons and high temperatures, and damaging people’s health and quality of life [1
]. Hence, looking for suitable ways to reduce greenhouse gas emissions in the process of economic development has become a focus for all countries in the world. As the largest developing country in the world, exploring low-carbon development strategies is necessary for China to engage in high-quality development while reducing carbon emissions in the future.
Since the information revolution, the digital economy, consisting of two major categories, digital industrialization and industrial digitization, has become the main economic form after the agricultural economy and the industrial economy. In 2022, the size of China’s Internet users exceeded 1.05 billion and the Internet penetration rate rose to 74.4%. Meanwhile, China has built the world’s largest 5G network and become one of the global leaders in 5G standards and technologies. In addition, the digital economy has been instrumental in promoting regional economic growth [3
], increasing green total factor productivity [6
], and promoting green technological innovation [8
] while also positively affecting environmental improvement [11
]. Specifically, many studies have analyzed the impact of information technology and environmental regulation on carbon emissions. Some scholars have found that the rapid development of Information and Communication Technologies (ICTs) and industries has led to rapid increases in electricity consumption, which has driven increases in carbon emissions [13
]. Other scholars believe that the development of ICT and related industries (e.g., the spread of the Internet and the construction of ICT infrastructure) will reduce greenhouse gas emissions and thus improve environmental quality [15
]. In addition, the Chinese government has proposed the goal of reaching carbon and energy development peak by 2030. Currently, the overall inequality of China’s carbon emissions shows a downward trend while intragroup inequality shows a slight upward trend [17
]. The current level of development may not fully support the achievement of the 2030 target [18
]. Therefore, many scholars are concerned about whether the higher the development level of the digital economy (DLDE), the more it can help China achieve carbon peak and carbon neutrality.
The digital economy, an innovation driving factor, may have been underestimated in its positive impact on low-carbon development in the past. Zhang et al. found that since China launched the carbon emission trading pilot, the digital economy has made a significant contribution to low-carbon development [19
]. Using inter-provincial panel data, some scholars found that DLDE has a positive effect on carbon emission reduction (CER) [20
] and significant spatial spillover effect [22
]. However, this issue at the city level needs to be discussed further. So, can the digital economy be an effective driver of urban carbon reduction in this new phase of development? If the answer is yes, what are the underlying mechanisms? Are there any spatial and temporal differences in the effects? The purposes of this study were to identify whether the digital economy can become a new driver of CER at the city level and to provide recommendations for government policies to guide the development of a vibrant digital economy. Therefore, this study considered the panel data of 282 cities in China from 2011 to 2019, used different econometric models to conduct in-depth research on the impact of DLDE on CER, and took the rationalization of the urban industrial structure and the upgrading of the industrial structure as intermediary variables to investigate the transmission mechanism of carbon reduction effects of the digital economy.
This study used a comprehensive index system to measure the urban DLDE, rather than a single index. Additionally, compared with most previous studies that measured China’s provincial carbon emission intensity (CEI), this study innovatively combined the Intergovernmental Panel on Climate Change (IPCC) carbon emission estimation method and satellite light data to establish a carbon emission inversion model to measure CEI and obtained new carbon emission data from the city level. In terms of mechanism analysis, we focused on discussing and testing the impact of industrial structure upgrading measured in terms of industrial structure rationalization and the impact of green innovation measured in terms of green patents on urban carbon reduction, thus providing a new perspective and empirical evidence on the potential of the digital economy to promote urban carbon reduction. In addition, the instrumental variable method, quasi-experimental analysis, the placebo test, and other methods were used to verify the robustness of our empirical results, providing more solid support for our regression analysis.
The rest of this study is arranged as follows. In Section 2
, we analyze the theoretical mechanism and propose the research hypotheses. In Section 3
, we explain the selected indicators and the measurement model. In Section 4
, we report and fully analyze the results of the empirical analysis, as well as perform the robustness test and endogeneity discussion. In Section 5
, we further analyze the mechanism and realization path of the digital economy that affects urban carbon emissions and analyze the heterogeneity according to urban characteristics. Finally, we summarize the conclusions and propose corresponding policy implications. The research framework of this study is shown in Figure 1
2. Theoretical Mechanisms and Research Hypotheses
Since Tapscott first introduced the term “digital economy” in the 1990s, research on the digital economy has gone through three stages from the Information Economy to the Internet Economy to the New Economy. However, there is no standard to define the meaning of digital economy uniformly. Zimmerman showed that the digital economy is open, representing not only a technology change but also challenges and opportunities for business structures and economic activities; it is innovative, fundamentally changing the means of creating value [23
]. Bukht and Heeks argued that the ICT sector, which provides the underlying digital goods and services, is the digital economy’s core [24
]. Barefoot et al. defined the digital economy as the digital infrastructure on which users can operate over the Internet to carry out digital transactions that can create value in terms of complexity and human resource costs [25
]. Additionally, Chen claimed that all ICT-based economic activities fall within the scope of the digital economy [26
]. Therefore, synthesizing previous analyses, the authors of this study believe that the digital economy is an economic activity characterized by data support, integrated innovation, and open sharing. It uses digital technology to drive digital information to communicate on the Internet platform, and concretely manifests itself through business models.
With the widespread promotion and application of digital technology, the development of the digital economy also integrated with the development of the real social economy and plays an important role in reducing CEI. On the one hand, the digital economy can promote the transformation of traditional cities into smart cities. The digital economy relies on the use of digital technologies in urban construction and management, which can contribute to the digitalization, informatization, and intelligent operation of cities [27
]. On the other hand, the digital economy can contribute to the digital management of enterprises in cities, enabling the accurate measurement of carbon footprints and the tracing of carbon emissions to their sources. The digital economy can also facilitate the digital transformation of enterprises, allowing them to efficiently use digital technologies to monitor and analyze their energy consumption and improve their ESG performance [28
]. A tangible example of effective CER using digital economy technologies is Jing Dong Company (JD) in China. JD’s data center uses energy-saving technologies such as frequency conversion and indirect evaporative cooling, and the average annual power usage has gradually decreased through economic management, making the data center greener and less carbon-intensive. JD also strategically partnered with Didi Taxi to reduce the carbon footprint of employee travel via “car-pooling”, a move that has reduced carbon emissions by over 270,000 kg. In terms of packaging design for its products, JD uses reusable recycled delivery boxes and is exploring new green models at the source through digital operations. In addition, JD fully opened up its digital social supply chain to drive upstream and downstream industries to jointly achieve sustainable development. By using digital technology to accelerate its low-carbon development, JD promotes the green transformation of the industry and leads the green operation and green consumption trends in society.
This example shows that the digital economy can reduce the complexity of using its data and information capital for value creation and can effectively reduce the cost of human and material resource dissemination. It can also promote convergence and innovation to enhance the efficiency of economic operations and energy use. In this way, an open, shared, and symbiotic ecosystem can be formed, which can effectively reduce carbon emissions. Therefore, Hypothesis 1 is proposed.
The digital economy can reduce urban carbon emissions.
In general, the digital economy mainly promotes the upgrading of the urban industrial structure in two ways: industrial structure rationalization [29
] and industrial structure supererogation [30
]. First, with the wide application and comprehensive penetration of digital technologies such as the Internet in the industrial field, the operational efficiency of industrial organizations has been significantly improved [31
]. This will lead to the formation and development of new industries. In this way, the proportional relationship between industries will be changed, labor productivity will be improved, and the output value proportion of industries with high levels of labor productivity will be increased. The overall industrial structure will be shifted towards the direction of intelligence and greening, and the level of the advanced industrial structure will be improved. Second, improvements in the digital infrastructure can lead to the rational allocation of production resources and factors, which will lead to a more orderly synergistic division of labor among industries and thus a more rational industrial structure [32
]. In addition, developing the regional economy will lead to changes in the dominant industrial sectors in the region. Since different dominant industrial sectors have different resource consumption patterns, resource mismatch and misallocation will inevitably result in huge waste, which will lead to abnormal carbon emission growth [33
]. Industrial structure upgrading can not only improve the efficiency of regional resource element utilization, reduce energy consumption per unit product, and thus reduce carbon emissions per unit product [11
], but also promote the rapid development of technology-intensive industries with high tech at their core, enhance the clean and efficient utilization of coal, oil, and other energy sources, and help realize the greening and decarbonization of the whole society’s industrial chain [35
]. Hence, Hypothesis 2 is proposed.
The digital economy can reduce carbon emissions by promoting the upgrading of urban industrial structures.
Green innovation is an effective means to address environmental pollution problems, and it can significantly reduce CEI [36
]. The impact of the digital economy on green innovation capability is mainly reflected in three aspects: First, the knowledge spillover effect generated by the agglomeration of the digital economy drives enterprises to accelerate the use of new methods in pollution management and green development, thus promoting urban green innovation. Second, the digital economy can gradually eliminate the traditional high-pollution and high-energy-consuming industries through the substitution effect. Digital technologies can improve the efficiency of traditional backward industries and speed up transformation and upgrading. In a greener environment, the same unit of factor input will generate greater economic and social benefits [37
]. Third, the development of the digital economy has enabled inclusive finance to benefit more economic agents through digital technology. Faster and more convenient financial support can help provide enterprises more green innovation research and development funds, as well as production and operation backup support from the supply side. At the same time, it also helps to enhance innovation and entrepreneurial activities in traditionally financially underdeveloped areas, which then indirectly promotes improvements in regional green innovation. Moreover, green innovation is conducive to CER while ensuring economic development [38
]. It can promote improvements in enterprises’ production efficiency and the gradual substitution of clean energy for fossil fuel resources in the production process, thus effectively reducing carbon emissions, which can help a country achieve green and sustainable development [39
]. Additional tools of green innovation include scientific instruments of environmental regulation. Carbon trading is an important market-based instrument used to control greenhouse gas emissions, and China’s carbon trading market has demonstrated that this policy helps to stimulate companies’ green innovation [40
]. Thus, Hypothesis 3 is proposed.
The digital economy can reduce carbon emissions by increasing the green innovation capacity of cities.
5. Further Analyses
5.1. Mechanism Test
A step-to-step test model was built with the mediation effect test method, and the results are shown in Table 8
The estimated results of column (1) showed that the digital economy significantly promotes at the 1% level. After adding to regression column (2), it was found that the coefficient of was significantly negative at the 1% level, indicating that the digital economy promotes CER by promoting the upgrading of the industrial structure. The estimation results of column (3) indicated that the digital economy significantly positively promotes at the 1% level. In recent years, the digital economy has been widely applied in the primary, secondary, and tertiary industries through, for instance, green and smart agriculture, the transformation of high-pollution industrial enterprises, and the encouragement of enterprises to research and develop green technology innovation patents. After adding to regression column (2), it was found that the coefficient of was significantly negative at the 1% level, indicating that the digital economy promotes CER by promoting industrial structure upgrading. Therefore, Hypothesis 2 was preliminarily confirmed. The empirical results of column (5) showed that the digital economy significantly accelerates green innovation at the 1% level. However, after adding to regression column (6), it was found that the coefficient of was significantly negative at the 1% level, which also confirmed that the digital economy can reduce carbon emissions by promoting green technology innovation. Therefore, Hypothesis 3 was proven. In column (7), the three mechanism variables were uniformly added to the regression model for another test to confirm the effectiveness of the mechanism variables. The results showed that when the three mechanism variables were added, the coefficient of was significantly positive at the level of 1%, which again confirmed Hypothesis 2 and Hypothesis 3.
To further confirm the existence of the mediation effect, this study adopted the bootstrap method, and the specific results are shown in Table 9
. The model used 1000 self-samples, and it revealed that the two mediating effects were very significant, which fully explained the path of the digital economy to reduce carbon emissions.
5.2. Heterogeneity Analysis
Due to differences in economic foundation and resource endowment, we found obvious heterogeneity in both the quality of economic development and DLDE in China. The impact may also have heterogeneity in time and space, the type of urban economic development, and at the city level. It was necessary to conduct an in-depth discussion of this topic.
We performed spatial and temporal heterogeneity regression, and the results are shown in Table 10
. First, the results in columns (1) to (3) show that the absolute value of the coefficient of
significantly increased after 2013, indicating that DLDE was improved and its influence on CER was strengthened following the implementation of the “Broadband China” strategy. Second, the results in columns (4) to (6) show that the digital economy plays a more significant role in urban CER in cities located in Eastern China compared with cities located in Central and Western China. This result is also related to the different levels of regional economic development in China. Cities in the eastern region tend to have higher economic levels, are more open to foreign investment, and more fully use energy than those in the central and western regions.
reports the regression results of urban type heterogeneity. According to the classification criteria of the State Council of China in 2013, this study divided cities into growing cities, mature cities, recessionary cities, regenerative cities, and non-resource-based cities. Columns (1) to (5) show that DLDE has a significant impact on the carbon emissions of regenerative and growing cities, with a large absolute coefficient value, though it showed no significant impact on recessionary cities. Columns (7) to (9) show that the absolute value of the coefficient of
was larger for provincial capitals and municipalities directly under the Central Government; additionally, the effect on non-provincial capitals was found to be significant, but the absolute value of the coefficient of
was relatively small. It is obvious that for both regeneration and growth cities, city development needs the help of industry. However, due to the relatively backward nature of urban development and the low level of economic development, the effect on recessionary cities was not found to be significant. In addition, provincial capitals and municipalities directly under the Central Government often have unique development advantages. Their economic level often ranks high in their provinces, and they have relatively significant policy support. Therefore, the digital economy will have more obvious impacts on the CER of these cities.
Generally speaking, DLDE may have a greater impact on the CER intensity of eastern cities, regenerative and growth cities, provincial capitals, and municipalities directly under the Central Government than the other kinds of municipalities because these cities witnessed the earlier development of their digital economies, better supporting environmental health and fully taking advantage of the benefits of the digital economy.
6. Conclusions and Policy Implications
This study explored the carbon reduction effects of the digital economy and the corresponding mechanisms. Our main conclusions are as follows: First, the digital economy can significantly reduce CEI and is an important driving force of achieving environmental protection goals. After further testing with instrumental variables, exogenous policy impact, and index substitution, our conclusion remained valid. Second, the digital economy can influence carbon emissions through two important channels: promoting industrial structure upgrading and green innovation. Third, the carbon reduction effects of the digital economy increase over time. The digital economy was found to have a significant positive effect on CER in cities in Eastern China, though the effect was not obvious for cities in Central and Western China. The development of the digital economy in regenerative cities was found to be conducive to CER best, though the development of the digital economy in recessionary cities was found to have no obvious effect on CER. The positive effect of the digital economy in promoting CER was also found to be more obvious in municipalities directly under the Central Government and provincial capitals. In addition, regarding the limitations of this study, this result may be a conclusion obtained only for a limited sample of cities and in this period of time. The data of some cities in northwest China are not public or difficult to collect, so the sample of this study did not cover all cities in China. If the study samples and the study time are changed, maybe we will have some new findings. Meanwhile, the results may also be influenced by how carbon emissions are estimated or how the digital economy is measured.
Therefore, the following policy implications can be proposed. To begin with, it is necessary to develop the construction of the digital infrastructure and consolidate the foundation for digital industrialization and industrial digitization. The government needs to vigorously support the research of artificial intelligence, big data, cloud computing, blockchain, and other digital technologies, and further promote the deep integration of the digital economy with urban management, enterprise development, energy conservation, and emission reduction. This will help digital technology penetrate traditional energy-intensive industries and optimize the industrial structure. Second, we should pay attention to the positive effects of industrial structure upgrading and green innovation capability on CER. At present, China’s digital economy is immature. During development, it is important to strengthen the extensive applications of the digital economy in various industrial fields such as industry, agriculture, construction, and transportation. Governments can promote improvements in green innovation ability through the introduction of corresponding financial and talent protection policies. Finally, a differentiated digital economy strategy should be implemented to improve the coordination of digital infrastructure construction among different regions. Reducing urban CEI requires overall planning, scientific planning, and gradual progress in different regions. By increasing the intensity and popularization of the “Broadband China” strategy, the “digital divide” between the eastern and central regions can be eliminated such that the central region, western region, mature cities, and recessionary cities can realize the “curve overtake” in environmental issues.