The global climate change and environmental pollution issues are becoming increasingly serious (Ren et al., 2023a; Zheng et al., 2022). In the process of China’s industrial development, the trade opening and energy use consume a large amount of fossil fuels, and the consumption of fossil fuels increases carbon emissions (Abbas et al., 2022; Ali et al., 2022; Wen et al., 2022). Improving the modernization of industrial chain can improve the level of innovation, open up its trade and improve resource utilization efficiency, reduce energy consumption and environmental pollution, and help achieve a balance between economic development and environmental protection (Fan et al., 2020; Hu X et al., 2021; Ali et al., 2023). With the background of complex global industrial and supply chain changes, the modernization of the industrial chain has become an important goal for China as China is pursuing a high-quality development of industry in the new era.

Capital investment is the fore-end of industrial modernization development and occupies an unquestionable key position in the entire modern industrial chain construction. Compared to traditional finance, digital finance has many advantages in enhancing the modernization of China’s industrial chain. Firstly, as an emerging financial tool, digital finance has provided new sources of investment and financing for enterprises through its own financial essence (Awai et al., 2023). Secondly, digital finance is not limited by geography or time, and can cover vast rural areas and small and medium-sized enterprises that are difficult to reach by traditional financial services. It is a major policy that benefits all people, especially small and medium-sized enterprises. Finally, digital finance’s essence is relying on big data and artificial intelligence technology, which can monitor the dynamics of the financial market and enterprises’ credit status in real-time. This helps to reduce the transmission of financial risks in the industrial chain and ensure the stable operation of the industrial chain.

At present, scholars have conducted relevant research on the relationship between digital finance and industrial chain development, but there are some shortcomings in the research process of these studies. Firstly, the different impacts of different dimensions of digital finance on the modernization of the industrial chain were ignored. Secondly, the study did not consider the spatial spillover impact of digital finance on the development of the industrial chain, nor did it further consider whether digital finance has a long-term impact on the modernization of the industrial chain. Therefore, this article attempts to make up for the shortcomings of previous research by using provincial-level panel data from China to construct indicators for the modernization of China’s industrial chain and applying relevant empirical models to analyze the relationship between digital finance and modernization of the industrial chain from both theoretical and empirical perspectives, thereupon expanding the research scope of digital finance and adding specific paths to enhance the modernization of the industrial chain. The innovation of this article lies in: Firstly, industrial agglomeration, industrial structure upgrading, and innovation achievements transform as mechanism variables, fully reflect the internal mechanism of digital finance’s impact on industrial chain modernization, and enrich the theoretical connotation of existing research; Secondly, measure the indicators of various dimensions of digital finance, and study how these dimensions affect industrial agglomeration, industrial structure upgrading, and innovation achievement transformation; Thirdly, delve into the spatial and temporal effects of digital finance on the modernization of the industrial chain by considering spatial and temporal factors.

As an innovative product generated from the integration of finance and digital technology (Ren et al., 2023b; Yu et al., 2023), the impact of digital finance on the modernization of industrial chains is not only limited to the financial sector but also manifests in the positive externality of digital technology (Xiao et al., 2023a). These two facets play a crucial role in how digital finance influences the development of industrial chains. Digital technology alters the geographical limitations of financial services, breaks the industry barriers for capital utilization, fully demonstrates the efficiency of capital allocation (Lei et al., 2023), and paves new pathways and models for the financing needs of modernizing industrial chains. With the support of digital technology, digital finance can mitigate the financing pressures of businesses in a timely manner (Qiu et al., 2023), increase capital sources, thereby directly affecting the development, spatial layout, and technological advancement of businesses. Simultaneously, digital finance can leverage its digital technology to enhance efficiency of resource allocation and communication efficiency, and reduce transaction costs, profoundly influencing the development of businesses and even entire industries. However, the development of digital finance has generated a digital divide, which has led to digital inequality between regions, reduced regional financial efficiency and is not conducive to the modernization and balanced development of the industrial chain (Heeks, 2022; Wang et al., 2020). In conclusion, the article proposes Hypothesis 1_a and Hypothesis 1_b .

H1_a

The development of digital finance can contribute to the improvement of the modernization of the industry chain.

H1_b

The development of digital finance cannot contribute to the improvement of the modernization of the industry chain.

The issue of information asymmetry is a key issue that restricts the modernization of the industrial chain in obtaining credit funds. In the process of allocating credit funds, traditional financial markets mainly rely on mortgaged assets as the measurement criteria for issuing corporate credit funds. However, items that can be mortgaged cannot accurately identify the needs of the fund demand side. Digital finance avoids information asymmetry between credit parties and increases the availability of industrial financial services. It should be noted that the digital economy has real-time characteristics in solving information asymmetry, so the modernization of industrial chain has dynamic spatial spillover effects. Therefore, this section introduces a spatial econometric model that includes spatial lag term, time lag term, and spatiotemporal lag term to detect the dynamic spatial spillover effects of digital finance and industrial chain modernization, which can effectively avoid endogeneity issues in the model. The model is as follows: y i t = ρ ∑ j = 1 N w i j y i t + ∂ y i , t − 1 + α ∑ j = 1 N w i j y j , t − 1 + ∂ n f i t + β c o n t r o l i t + μ i + δ t + ε i t + γ ∑ j = 1 N w i j n f i t + c o n t r o l i t (3)

In Formula 3, w is N × N-dimensional normalized non-negative spatial weight matrix. ρ represents the lag coefficient of the spatial dependent variable, ∑ w i j y i t represents the interaction effect of the endogenous dependent variable, μ i   a n d   δ t represent the spatial individual effect and time effect respectively, ε i t is an independent and identically distributed random disturbance term, and the other variables are the same as Eq. 1.

The spatial weight matrix W adopts the geographical distance matrix based on the distance function, as follows: W i j ∗ d = 1 d i j 2   i ≠ j 0   i = j (4)

In Formula 4, W i j ∗ d represents the spatial dependency relationship between regions, and the larger the value, the greater the spatial dependency. d i j represents the spherical distance between region i and region j and it’s calculated based on the longitude and latitude data provided by the national basic geographic information system.

Columns (1)–(3) in Table 9 show the time lag term, spatial lag term, and time and spatial lag term of the spatial Durbin model (SDM). The results show that in the Spatial Durbin Model (SDM), the lag coefficient of the dependent variable ρ is significantly positive at 1%. This indicates that there is a spatial spillover effect in the modernization of industrial chain, and the coefficient of digital finance is significantly positive, indicating that digital finance can significantly improve the modernization of industrial chain. Under the real-time nature of digital technology, the modernization of industrial chain has significant spatial dynamic effects. The implementation of digital finance provides strength for a new round of financial supply in the entire financial market, increases the types of financial services, and increases the probability and scope of industrial entities obtaining credit capital. As a strong supplement to traditional financial services, digital finance also relies on a series of digital technology advantages to broaden financing channels, increase the scale of financial coverage in the industrial chain, and provide capital support to the main body of industrial development. With the support of digital finance, the modernization of the previous industrial chain can significantly have a positive effect on the modernization of the next industrial chain.

The model I, model II, and model III in Table 10 respectively correspond to the model decomposition effect of adding time lag term, space lag term, time lag term, and space lag term. The regression results of the three models are consistent and can be used as robustness tests for each other. In the short term, the direct impact of digital finance on the modernization of industrial chain is significantly positive, while the indirect impact is not significant. The overall effect is significantly positive. In the long run, the direct impact of digital finance on the modernization of industrial chain is also significantly positive, while the indirect impact is not significant. The overall effect is significantly positive. That is to say, digital finance has a significant positive impact on the modernization of local industrial chains in both the short-term and long-term, but has no significant impact on the modernization of adjacent regional industrial chains. The long-term direct effect is greater than the short-term direct effect, indicating that in the short term, digital finance may influence the modernization development of the industrial chain through its own role, while in the long term, it is through the joint action of itself and technological changes on the modernization of the industrial chain. In other words, digital finance can not only support the modernization of the industrial chain itself, but also make this boosting effect more apparent through technological changes in the long term.

The empirical results show that digital finance has a positive and positive impact on the modernization of the Chinese industrial chain, which is consistent with the research findings Lei et al., 2023; Xiao et al., 2023b). Our findings underscore the fact that digital finance has a significant and positive impact on this process, primarily by breaking down traditional time-space constraints between capital demand and supply.

Notably, the influence of digital finance is heterogeneous across different regions of China. The eastern region, which is typically more developed and has more mature digital infrastructure, benefits more significantly from digital finance compared to the central and western regions. This implies that digital finance might be more effective in regions with a certain level of economic and digital development, suggesting that digital infrastructure could be a prerequisite for maximizing the benefits of digital finance. Therefore, the existence of differences in financial endowments across regions may account for the differences with the findings of scholars (Heeks, 2022; Wang et al., 2020).

Our results also highlight that the impact of digital finance has been more pronounced after 2016. This might be attributed to the rapid advancements in digital technologies and financial innovations that have occurred in recent years. Furthermore, we found that digital finance contributes positively to industrial agglomeration, industrial structure optimization, and Innovation Achievements Transformation. The varying effectiveness across these subindicators suggests the multifaceted nature of digital finance’s influence on industrial modernization.

Finally, our research reveals positive spatial spillovers of digital finance and industrial chain modernization. However, the impact of digital finance on adjacent regions was found to be negligible. This could be due to the localized nature of digital finance, where its benefits are primarily reaped within the region where it is implemented.

The research concludes that digital finance has a positive and significant impact on the modernization of industrial chain. Digital finance uses high-end and cutting-edge digital technology to break the objective time-space constraints between the demand side of financial capital and the supplier of financial resources, and can obtain credit capital more quickly, which provides a basis for promoting the industrial structure upgrading, industrial agglomeration and Innovation Achievements Transformation.

Therefore, this paper puts forward the following policies and suggestions: firstly, improve the quality of financial services, form a large-scale digital financial market system, further expand the depth and breadth of financial services, and transform digital finance from capital allocation function to capital allocation; Give full play to the leading role of the capital market, provide operational capital for the industrial chain development, increase the direct financing’s proportion by enterprises, inject new momentum into industrial development, and promote the high-end trend of the industrial chain. Secondly, promote a high degree of integration between digital finance business and the industrial chain, create and set up digital finance products that are in line with the industrial chain development, guide funds to flow into high-end industries, strengthen the role of digital finance in fund allocation in the industrial chain, actively promote the allocation of capital elements from low-end industries to high-end industries in the value chain, and assist in industrial agglomeration, industrial upgrading, and innovation transformation.

Despite the significant findings, our research is not without limitations. First, our study focused on the provincial level, potentially overlooking variations at the city or district level. Digital finance development and its impacts could be more nuanced and vary significantly within provinces, which our study does not capture. Finally, our study did not examine the potential negative impacts or risks associated with digital finance, such as increased cybersecurity threats or financial instability. Future research could aim to provide a more balanced perspective by investigating both the advantages and potential risks of digital finance.