1. Introduction
Global warming is a serious threat to the human living environment. Carbon dioxide emissions and other pollution indicators (such as SO
2 and nitrogen oxides) are the main “culprits” of global warming [
1]. The development of a low-carbon economy is considered an effective way to cope with global warming. As an important participant in tackling global warming, China solemnly promises to achieve a carbon peak by 2030 and carbon neutrality by 2060. This “double carbon” goal not only points out the direction but also imposes increased requirements for China’s low-carbon economic transformation. In particular, in the context of the COVID-19 pandemic, it is urgent to explore new drivers of China’s low-carbon development. Furthermore, the digital economy based on 5G, big data, artificial intelligence, the Internet of Things, and other next-generation information technologies is profoundly changing the means of production and social governance [
2]. The digital economy is a series of economic activities involving digital technology, digital equipment, digital knowledge, and information as production factors [
3,
4]. The digital economy is the most dynamic, innovative, shared, and resilient economic form in the context of the current global epidemic. Data are the core element involved in the development of the digital economy, and governments around the world are actively developing digital economies with the data element as the core. For example, the United States formulated the Big Data Research and Development Plan in 2011 [
5], and the EU issued the EU Data Strategy in 2020 [
6]. In order to promote the development of China’s digital economy, the Chinese government wrote big data into a government work report for the first time in 2014, and the Plan of Action for Promoting Big Data Development issued in 2015 has identified big data as a national strategy. The report of the 19th National Congress of the Communist Party of China in 2017 required the promotion and deep integration of big data and the real economy. In 2020, the Chinese government identified data as a factor of production, and in 2021, China’s 14th Five Year Plan set the improvement of a big data standard system as the focus of development. A series of policies fully demonstrates that big data have become the key element and the new driving factor of China’s economic transformation and development. With the development of big data, China’s digital economy accounted for 39.8% of GDP in 2021. In order to accelerate the deep development and application of big data and summarize and refine the successful development experience of the big data industry, the Chinese government approved Guizhou Province as the first national big data comprehensive pilot zone (NBDCPZ) in 2015. In 2016, the second batch of comprehensive pilot areas was approved in nine provinces (cities), including Beijing. For example, there have been more than 5000 big data enterprises established in Gui’an City since 2021. The revenue of software and information technology services increased by 67.74%, reaching RMB 38.8 billion, accounting for 91.04% of the province’s total, with the digital economy accounting for 41.9% of the region’s GDP. In addition, the bandwidth of Gui’an’s national Internet backbone direct connection point was expanded to 500 G, with a direct connection with 28 cities, including Beijing, Shanghai, Guangzhou, and Shenzhen (
https://www.guiyang.gov.cn/zwgk/zwgkxwdt/zwgkxwdtbmdt/202204/t20220427_73651156.html, accessed on 4 December 2022). Under the dual background of “dual carbon” and digital economy, can the construction of NBDCPZs promote the low-carbon transformation of China’s economy? If the answer is yes, what is the impact mechanism? What are the characteristics of impact heterogeneity? Is there any spatial spillover effect? Studying these issues will help the Chinese government clarify the relationship between the digital economy and low-carbon development, with China’s theoretical and practical experience serving as an example for the world to better use the digital economy to support low-carbon and sustainable development.
With the global warming caused by carbon dioxide becoming increasingly serious, some researchers began to use carbon emission intensity [
7,
8], carbon emission efficiency, or carbon emission performance [
9,
10,
11] to evaluate the low-carbon transformation of the economy. Other researchers have considered the influencing factors of low-carbon economic transformation from the perspectives of economic spatial agglomeration [
12], green innovation [
13], global value-chain embeddedness [
14], urbanization [
15], low-carbon policy [
16], innovation policy [
17], etc. In addition, a number of studies have focused on the green and low-carbon effects of the digital economy. Most scholars believe that the development of the digital economy can effectively replace traditional factors with data, help reduce environmental pollution through technological innovation [
18,
19], and reduce carbon emission intensity by optimizing industrial structure [
20]. However, some researchers suggest that the application of digital equipment and infrastructure has increased energy demand [
21,
22], which is not conducive to green and low-carbon development. Some of the literature also indicates that the development of the digital economy and high-quality green development have a positive, nonlinear connection [
23]. As far as specific carbon emission performance and efficiency are concerned, most studies include an indicator system to evaluate the digital economy and examine its effect on low-carbon transformation from the perspectives of artificial intelligence [
24], digital inclusive finance [
25], and Internet development [
26,
27,
28]. Some studies consider “Broadband China” as a quasi-natural experiment, indicating that the impact of Internet development on energy conservation and emission reduction efficiency is non-linear [
29]. In the era of the digital economy, data have no specific value, but digital and intelligent data elements have unique value [
30]. The existing literature includes multilevel discussions on data elements from the perspectives of their connotation [
30], characteristics [
31,
32], market cultivation mechanism [
33], value creation [
34], etc., as well as examinations of their enabling effect on traditional production factors [
35], innovation effect [
36], and economic growth effect [
37,
38]. Researchers employed the text analysis method to examine the impact of data elements on the high-quality development of the manufacturing industry [
39]. With the gradual development of the event analysis method, researchers who combined it with theoretical and empirical analysis concluded that NBDCPZs can promote the digital transformation of enterprises by improving the construction of digital infrastructure, promoting the development of digital industry, and improving the intensity of financial science and technology expenditure [
40], in addition to helping improve air pollution by promoting industrial upgrading and technological innovation and optimizing resource allocation [
41]. The low-carbon transformation effect of the construction of NBDCPZs remains to be further studied.
The above research has laid a foundation for in-depth understanding of the green and low-carbon effects of the digital economy. However, the following shortcomings remain. On the one hand, data elements are the core content and key driving force of the digital economy, and although many studies have examined the green and low-carbon effects of the digital economy from the perspectives of artificial intelligence, digital inclusive finance, Internet development, etc., few studies focus on the impact of big data on the low-carbon transformation of the economy. On the other hand, most studies use an indicator system to evaluate the digital economy, examining its low-carbon transformation effect and ignoring the endogenous problem between the two, which may underestimate the low-carbon transformation effect of the digital economy. In contrast to existing research, in this study, we focus on the urban level from the perspective of data production factors, with NBDCPZs as a quasi-natural experiment and a deep commitment to research on the impact of big data on urban low-carbon transformation and development. The possible marginal contributions of this study are mainly reflected in the following three aspects. (1) This study comprises research from the perspective of big data, with thorough discussion of the contribution and impact mechanism of big data in promoting urban low-carbon development, with a review of relevant literature on the digital economy and the low-carbon economy. (2) We considered the “quasi-natural experiment” of NBDCPZs, alleviating the endogenous problem of using an indicator system to evaluate the low-carbon transformation effect of the digital economy. (3) We further investigated the heterogeneity and spatial spillover effects of NBDCPZ construction on urban low-carbon transformation, contributing to the understanding that big data affect urban low-carbon transformation.
2. Theoretical Mechanism and Research Hypothesis
Emission reduction and efficiency enhancement is the most direct embodiment of urban low-carbon transformation. On the one hand, data elements and traditional production factors such as labor, capital, and energy complement and cooperate with one another and combine to activate traditional production factors and improve total factor productivity [
42]. On the other hand, big data can achieve more accurate monitoring, analysis, prediction, and early warning of carbon emissions by establishing an environmental monitoring data center, improving the pertinence, scientificity, and timeliness of environmental regulatory decisions, thus providing strong support for precise and scientific emissions reduction [
43]. Although China has made some progress in the development and application of big data, problems such as insufficient data opening and sharing, weak digital infrastructure, and imperfect systems and mechanisms persist [
5]. Open data resource management and sharing, data center integration, data resource application, data element circulation, big data industry agglomeration, big data international cooperation, and big data system innovation are the seven major tasks of NBDCPZ construction [
5]. With these seven tasks, NBDCPZs can break data resource barriers; strengthen digital infrastructure construction; formulate laws, regulations, and standards; and highlight the low-carbon transformation effect of big data.
The construction of NBDCPZs can also promote urban green innovation. The application of big data can generate new business forms such as digital platforms and digital finance so as to achieve deeper integration with traditional industries [
44]. Networked collaboration between industries can expand the exchange and sharing of data and knowledge elements, which is conducive to urban innovation. The medium of information exchange is one of the main applications of big data, which can effectively reduce the information asymmetry between the needs of enterprises and consumers, thus facilitating the collaborative evolution between enterprises and consumers and playing an important role in promoting the construction of a market demand-oriented green innovation mode [
45]. The construction of NBDCPZs can reduce the cost of information infrastructure and accelerate the process of enterprise green innovation, which is conducive to promoting urban green innovation [
46]. In addition, NBDCPZ construction optimizes the process of green innovation activities of enterprises by integrating big data technology and big data thinking into green innovation decisions. The construction of NBDCPZs is conducive to improving the allocation of urban resources. Big data construction can improve the matching of the degree of labor demand and supply, reshaping and improving the form and efficiency of labor resource allocation [
47]. With the help of NBDCPZ construction, data elements reduce transaction costs and investment risks in the capital market, optimize the investment structure, and guide the allocation of funds to green and low-carbon industries. In addition, the construction of NBDCPZs can help improve the infrastructure of energy big data, integrate various types of energy consumption data of enterprises and residents, and accurately allocate energy elements from the supply side and the demand side.
Based on above analysis, in this study, we propose the following hypotheses:
Hypothesis 1 (H1). The construction of NBDCPZs is conducive to promoting urban low-carbon transformation.
Hypothesis 2 (H2). The construction of NBDCPZs can promote urban low-carbon transformation through green innovation and resource element allocation.
NBDCPZ construction can also affect urban low-carbon transformation through spatial spillover effects. First, the construction of NBDCPZs is conducive to the formation of digital industry clusters, promoting the spread of green technologies and green processes in NBDCPZs, causing spatial spillover of green technologies. Secondly, the construction of NBDCPZs is conducive to the joint prevention and control of regional pollution and the realization of regional coordinated emissions reduction. On the one hand, NBDCPZ construction encourages enterprises in the pilot areas and surrounding cities to optimize production processes and achieve cleaner production by sharing and jointly building environmental pollution treatment facilities. On the other hand, the construction of NBDCPZs is conducive to realizing the interconnection and sharing of environmental monitoring data, thereby reducing environmental governance costs caused by information asymmetry [
48] and promoting resource conservation and pollution reduction in adjacent areas. Finally, during the period of NBDCPZ construction, both local and surrounding cities are faced with the process of factor restructuring, especially when a cluster of various factors forms in the pilot areas driven by policies, causing a “siphon effect” on the surrounding areas. Such an effect causes the surrounding areas to only retain the original production links, maintaining traditional production mode and suppressing the green transformation of the surrounding areas with “negative” spillovers. Moreover, knowledge and technology spillovers of NBDCPZ construction may not play a positive role, and some failed practices and experiences may lead the surrounding areas to go astray in the continuous imitation and learning. Accordingly, in this study, we propose the following hypotheses:
Hypothesis 3 (H3). The construction of NBDCPZs can produce a spatial spillover effect on urban low-carbon transformation.
6. Discussion
6.1. Conclusions
Under the dual background of global warming and the rise of the digital economy, data elements have become the core driving force for the digital economy to promote low-carbon economic transformation. Based on theoretical analysis, we considered the construction of NBDCPZ as a quasi-natural experiment and used China’s city-level panel data from 2007 to 2019 to thoroughly investigate the impact of big data construction on urban low-carbon transformation, drawing the following research conclusions. (1) According to the two-way fixed effect benchmark regression model based on the difference-in-differences (DID) method, it can be concluded that NBDCPZ construction can effectively promote urban low-carbon transformation. A series of robustness analysis supports this research conclusion. (2) The panel mediation effect model shows that stimulating urban green innovation and optimizing the allocation of urban resource elements are the main conduction mechanisms of NBDCPZ construction with respect to the promotion of urban low-carbon transformation. (3) The benchmark regression model was further tested and shows that compared with eastern cities, small and medium-sized cities, and resource-based cities, the construction of NBDCPZs can promote the low-carbon transformation of cities in central and western China, large cities, and non-resource-based cities. (4) According to the DID-SDM model, the construction of NBDCPZs can improve the low-carbon transformation of local cities, significantly inhibit the low-carbon transformation of surrounding cities, and exert a negative spatial spillover effect. Construction of NBDCPZs is one of the most fundamental measures for data elements and big data to highlight to the digital economy and promote the low-carbon transformation of the economy. In addition, “smart city” construction and “broadband China” construction are also important parts of China’s digital infrastructure construction. NBDCPZ construction, “smart city” constructions, and “broadband China” construction are mutually reinforcing and collaborative construction models. The conclusions of this study provide reference for further improvements to digital economic policies in China. For example, in the process of building “smart cities” and “broadband China”, the Chinese government should prevent them from exerting a negative impact on the low-carbon transformation of surrounding cities.
Based on the above research conclusions, the policy implications of this study are as follows. First, the Chinese government should continue to reasonably promote the orderly construction of NBDCPZs and highlight and promote the successful experience of the pilot cit. Second, the government should optimize the settlement policy of NBDCPZ digital talents, improve the software and hardware environment of NBDCPZ enterprise innovation, attach importance to the integration of data elements into traditional production, pay attention to the research and development and application of green and low-carbon technologies, and use big data technology to help the core technology breakthrough in the production field and the smart technology development of “imitation innovation”. In addition, it is necessary to constantly improve the property rights, pricing, and trading mechanisms of data elements. Policy makers should strive to build an integrated market system for NBDCPZ elements, break down institutional barriers that hinder the flow of elements, and use administrative means and market forces to continuously encourage the all-round complementation, coordination, and coupling of data resources and traditional resource elements so as to consolidate the external environment to encourage the green innovation effect and resource allocation effect of NBDCPZ construction. Thirdly, it is very important to strengthen cooperation, demonstration, imitation, and competition among various types of cities and to implement the construction of NBDCPZs according to local conditions. If necessary, eastern cities, large cities, and non-resource-based cities can expand pilots to the county level, and according to their own conditions, they can appropriately build a docking mechanism that is complementary to other pilot policies (broadband pilot policies, low-carbon pilot policies, etc.). Fourth, policy makers should carefully consider the negative spatial spillover effect of NBDCPZ construction, develop a cooperation and interaction mechanism between pilot cities, strengthen the learning and exchange mechanism between non-pilot cities and pilot cities, and minimize the negative spatial spillover effect of NBDCPZ construction.
6.2. Research Limitations and Future Directions
Although in this study, we systematically and thoroughly investigated the impact of NBDCPZ construction on urban low-carbon transformation, the following areas can still be improved. (1) In the future, the low-carbon effect of NBDCPZ construction can be considered at the enterprise level to investigate the impact of NBDCPZ construction on enterprise low-carbon transformation. (2) It is meaningful to combine the NBDCPZ pilot policy with other pilot policies and deepen the understanding of the impact of NBDCPZ construction on urban low-carbon transformation from the perspective of policy combination. (3) In the future, we will also focus on a certain type of ecological environment big data supervision platforms and carry out case studies. (4) Other future research directions include the use Python software to capture keywords related to data elements, the use of text analysis to build a data element index system, and accurately investigation of the impact of data elements on urban low-carbon transformation.