Exploring impact of digital economy on sustainable urban development by panel data of 30 underdeveloped cities in China
Analysis of necessary conditions
To clarify the importance of each conditional variable, refer to the evaluation criteria of Schneider and Wagemann31: conditions with a consistency level greater than 0.9 are considered necessary conditions. In the analysis of QCA Panel data, when the adjustment distance is less than 0.2, it can be considered that its summary consistency has high accuracy19. The necessity test of a single condition is shown in Table 2.
From Table 2, it can be seen that the adjustment distances for the five conditional variables of digital industry development, digital infrastructure construction, economic development level, degree of openness to the outside world, and technological progress are all less than 0.2, and their aggregated consistency is less than 0.9, indicating that the above conditions are all unnecessary. However, there are situations where the consistency adjustment distance between groups is greater than 0.2 in economic development level, industrial structure, digital industry development, digital infrastructure construction, and digital finance, and further analysis is needed.
Data for years with intergroup adjustment distance greater than 0.2 is shown in Table 3.
By analyzing Table 3, it can be found that: firstly, in situations a to e, the consistency level of each year is less than 0.9, and there is no necessary relationship; Secondly, in cases f and g, the consistency from 2016 to 2020 is greater than 0.9 and the coverage rate is greater than 0.5, but the values in the scatter plot are concentrated on the right y-axis, which does not meet the necessary conditions31; Thirdly, in case h, the consistency between 2011 and 2013 is greater than 0.9, but the coverage is less than 0.5, which does not constitute a necessary condition; Fourthly, in situations d and i, the consistency from 2011 to 2013 is greater than 0.9 and the coverage is greater than 0.5, but neither of them meets the requirements in the following years, so it is unnecessary. Consistency between groups h and i is shown in Fig. 1.
Consistency between groups h and i.
It should be noted that in situations h and i, although digital finance is not a necessary condition, it can be seen from Fig. 1 that this condition exhibits a significant time effect, and its necessity is increasing year by year. Similarly, further analysis was conducted on cases where the adjustment distance for intra-group consistency was greater than 0.2, and it was found that none of them were necessary conditions and were not shown in the article due to space limitations.
This result is consistent with existing research findings, emphasizing the importance of digital finance. The reason may be that as Big data, artificial intelligence, the Internet of Things, and other digital technologies gradually penetrate all aspects of economic development and various fields of the financial industry, gradually complete a deeper integration with the real economy, and on this basis, promote the digital transformation of traditional industries, stimulate new momentum, promote the financial industry to accelerate Digital transformation, to provide more accurate services for the real economy, Becoming a “new engine” that promotes high-quality economic development with strong innovation vitality. In addition, by observing its increasing trend year by year, combined with current planning policies, it can be foreseen that its importance will continue to steadily increase in the future.
Configuration analysis
Key findings
Based on existing literature, this article sets the case threshold to 1 and the consistency threshold to 0.8. Due to significant differences in resources among cities, it is difficult to uniformly determine the role of antecedent conditions in the outcome, so no direction is preset. A standard analysis of the case was conducted, and the conditional variables were subdivided into core and edge conditions based on the obtained simple and intermediate solutions18.The configuration results for achieving high sustainable development efficiency are shown in Table 5. The results will be analyzed from three aspects: intergroup, intra-group, and summary.
From the intergroup results, although the intergroup consistency adjustment distances for all three configurations are less than 0.2, it indicates that there is no significant time effect. Further investigation of its temporal variation revealed that the consistency levels of the three configurations were all greater than 0.75 between 2011 and 2020, indicating that the results of this study still have good applicability for normal development. Although it will decline in 2020 due to COVID-19, home office, home classes, and other ways will also accelerate the transformation and upgrading of the digital economy, making it expand from the Internet field to education, finance, medical care, and many other traditional fields and deeply integrate with the industry and the real economy. Therefore, the fluctuation is stable above 0.75. Changes in consistency between groups are shown in Fig. 2.
Changes in consistency between groups.
From the results within the group, the adjustment distance for consistency within the group was also less than 0.2, indicating that the explanatory power of the three configurations among cities was good, but there was no significant difference. In this case, the regional distribution of cases that can be explained by each configuration can be reflected by comparing the differences in coverage within the group. The mean regional configuration coverage is shown in Table 4.
From Table 4, it can be seen that Configuration 1 can mainly explain urban cases in the Gansu and Qinghai regions; Configuration 2 can explain urban cases in the Shaanxi and Qinghai regions; Configuration 3 mainly explains the case of cities in the Gansu region. Configuration analysis results are shown in Table 5
From Table 5, it can be seen that from the summary results, the consistency of the solution is 0.934, greater than 0.75, which meets the sufficiency criterion27. Moreover, the intergroup consistency adjustment distances for individual configurations are all less than 0.2, indicating that this model has good explanatory power. Considering that the digital economy has been widely infiltrated into all fields and links of the economic society, and has been integrated and developed with the real economy, showing its superior penetration effect, this penetration effect will also attract more users to participate in it with the Network effect of the trading platforms of both sides, thus producing a certain scale effect The role of the digital industry development and digital finance can be divided into two forms: penetration effect and scale effect. Based on the theory of this article and typical urban cases, this article takes the development of digital industry, digital infrastructure, and digital finance in the digital economy as anchors that balance integrity and uniqueness. Three configurations are named: high penetration effect, high scale penetration effect, and high scale effect mode.
Policy recommendations and future directions
Overall, in Configuration 2 and Configuration 3 with high-scale effects, digital finance is the core condition, supplemented by advanced industrial structure, indicating that digital finance can promote the transformation and upgrading of industrial structure through deep integration of digital technology and industry, and achieve effective control and reduction of carbon emissions by optimizing resource allocation, thereby achieving high sustainable development of cities. In addition, both Configuration 1 and Configuration 2 with high penetration effect have the condition of taking the development level of high digital industry as the core, supplemented by the high level of economic development, which indicates that the development of the digital industry has been deeply integrated with the real economy, and based on the background of the current digital economy era, the application of digital technologies such as Big data, the Internet of Things and artificial intelligence to social production, transportation and consumption can accelerate information integration, And by guiding the green transformation of energy, we can promote innovation in low-carbon and clean energy production technologies, effectively promoting carbon reduction32, improving environmental pollution, enhancing sustainable development efficiency, and achieving high-quality sustainable development of cities.
The high penetration effect model, Configuration 1, points out that high digital industry development, high economic development level, high degree of openness to the outside world, and non-high industrial structure as core conditions, with digital infrastructure construction as auxiliary conditions, can fully generate high sustainable development efficiency. This kind of city reflects that under the background of an underdeveloped industrial structure, urban subjects mainly integrate the digital economy with the development of the real economy through good digital industry development and digital infrastructure construction, based on the penetration effect, making full use of the advanced technology introduced from the Open platform, and promoting the cross-regional cooperation of digital elements among different urban subjects, to achieve green and high-quality development. Typical cities such as Lanzhou City, according to relevant statistics, Lanzhou City has introduced 39 data information industry projects with a total investment of 37 billion yuan, selected as the ninth batch of national new industrial demonstration bases, and become a provincial Big data industry cluster and data resource center in the northwest region of China. In recent years, Lanzhou has been actively promoting the creation of a demonstration model for the digital economy in Gansu Province. It has become the first independently developed PLC industrial control device enterprise in China and the Kunpeng Ecological Innovation Center. The digital economy has become a key field of industrial cultivation in Lanzhou.
The high-scale penetration effect model, Configuration 2, points out that cities with high digital industry development, high digital infrastructure, high digital finance, high economic development level, high industrial structure, and non-high-tech progress as the core conditions can generate high sustainable development efficiency. This type of city reflects that in the context of insufficient innovation and progress in technology, urban entities mainly achieve industrial optimization through the penetration effect of high digital industry development and digital infrastructure construction, as well as the scale effect of digital finance, thereby effectively promoting the realization of high sustainable development in the city. In a typical city such as Xi’an, according to relevant statistical data, the total digital economy of Xi’an in 2022 reached 524.9 billion yuan, accounting for 5.6% of the city’s GDP. It is the only way to connect the five provinces in northwest China and the public computer network, with the largest network transportation routes and abundant network resources. At present, the city focuses on promoting industrial digitization and digital industrialization, using digital government and smart city construction as development carriers, and using digital elements to promote the transformation and upgrading of traditional industries, promoting the deep integration of digital elements and resource elements, significantly improving the economic and environmental benefits of production factors, and supporting the green and high-quality development of the city.
The high-scale effect model, Configuration 3, points out that the development of non-high digital industries, high digital finance, high degree of openness to the outside world, high industrial structure, and non-high-tech progress as core conditions, and the level of economic development as auxiliary conditions, can fully generate high sustainable development efficiency. This type of city reflects that in the context of technological progress, digital industry development, and poor digital infrastructure construction, it can achieve high sustainable development of the city through a good level of openness to the outside world and a higher level of economic development, based on the scale effect of digital finance, and optimizing the industrial structure of resource elements. Typical cities such as Jinchang, according to relevant statistical data, Jinchang’s digital economy industrial chain will achieve an output value of 4.06 billion yuan in 2021, a year-on-year increase of 4.2 times. In recent years, the city has actively integrated 5G with Big data and other digital technologies and the “2 + 4” industrial chain, enabling upstream and downstream enterprises of the industrial chain to “embrace” development, promoting Big data companies to deeply participate in industrial Internet intranet transformation, smart city, and other projects, and initially formed a digital economy industrial system with Jinchang characteristics of “computing based, gold chain cultivation, operating data, and output services”, Comprehensively improve the efficiency and precision of production and manufacturing, reduce resource waste, and promote industrial optimization to empower sustainable development.
Future directions
The following directions can be drawn: firstly, governments at all levels should explore diversified paths for the integration of digital economy and advantageous industries based on their resource endowments and advantages, adopt differentiated digital economy development models, actively bridge the digital divide, promote the process of coordinated development between urban digital economy and green, and enable cities at different stages of development to share the green benefits brought by digital economy development. Secondly, all provinces should increase their scientific research investment, improve their technological innovation ability, further promote the deep integration of digital technology with clean technology, green manufacturing, pollution control, Recycling, and other fields, constantly improve the digital content of green technology, optimize the combination of factors, reduce resource waste, and improve the level of sustainable development. Finally, in response to the development characteristics and requirements of different industries, explore different “digital + ” models, accelerate the widespread penetration of the digital economy into the traditional three major industries, and take the digital development of industries as the starting point, fully leverage the positive role of the digital economy in promoting industrial structure optimization, guide production factors to flow to green and environmentally friendly emerging industries, and accelerate industrial structure optimization through digital industrialization to promote the transformation of economic development mode, Assist cities in achieving green and high-quality development.
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