Impact of Digital Finance on Energy Efficiency in the Context of Green Sustainable Development

Abstract

Limited by ecological conditions, in order to improve the innovation efficiency concerning energy, a change from “extensive” to “green” is required. The development of sustainable technology is the most important productive force. Economic development is centered on finance. Only by mutual penetration and interaction can China’s energy innovation be effectively promoted. “Green GDP (Gross Domestic Product)” is the main direction of China’s current economic development. A sustainable green digital economy is the primary condition for promoting energy efficiency, and it is the key to improving energy efficiency in China to achieve a green transition. Green finance for sustainable development refers to economic finance centered on energy conservation, environmental protection and technological innovation. Attention is constantly paid to the financial industry in China, and we are trying to combine the concept of environmental protection with financial development to promote the continuous development of China’s environmental protection economy. A company’s economic and environmental benefits will be improved from the point of view of improving resource conservation and reducing the environmental impact of equipment and processes. To achieve this goal, the “efficiency effect” of the financial system needs to be fully exploited to maximize energy efficiency. An empirical study about the relationship of financial performance and energy efficiency in the green sector is carried out while considering the environmental constraints. The results show that the expansion of the financial scale and the adjustment of the financial structure have increased the energy utilization efficiency by more than 15% from the past to the present and reduced the pollution of the ecological environment by more than 10% nationwide, realizing the effective allocation of resources. Digital finance is a new generation of financial services that combines the Internet and information technology with traditional financial service formats. Including Internet payment, mobile payment, online banking, financial service outsourcing and online loans, online insurance, online funds and other financial services. Therefore, the sustainable development of all aspects of finance has a huge catalytic effect on the doubling of energy utilization efficiency.

1. Introduction

In recent years, China’s economy has grown at an alarming rate. Under this circumstance, the problem of environmental pollution has become increasingly serious, and the global climate has increased abnormally. To change this situation, we must accelerate the transformation of the current social and economic structure. This includes industrial structure, distribution structure, exchange structure, consumption structure, labor structure, and so on. Among them, green finance is the most important part of the whole market economy system. It promotes social and economic transformation to a large extent and accelerates the deepening of the concept of green sustainability. There are three main definitions of green finance. The first refers the purpose of green finance, which is to support projects with environmental benefits, and environmental benefits include support for environmental improvement, addressing climate change, and efficient use of resources. The second relates to the main categories of green projects, which has important guiding significance for the definition and classification of various green financial products. The third involves clarifications of green finance that includes financial services to support green project investment and financing, project operation and risk management, as well as the reference materials are all in the relevant financial policies. Therefore, it is necessary to strengthen the revision of green finance and establish a long-term guarantee system for green finance to reduce environmental pollution based on the national perspective. This has far-reaching significance for improving the traditional development model, energy efficiency in industrial development, and ultimately promoting the improvement of the ecological environment. It provides a guarantee for China to achieve sustainable economic development.

Green finance in China started relatively late, in the early 1990s. Correspondingly, relevant environmental and economic policies have also been formulated. Simultaneously, due to the on-going evolution of eco-green finance, the types of these policies have been expanding. However, from a global perspective, although green financing is developing very rapidly in China, the corresponding fiscal policy is still in its infancy, which is far from meeting the needs of today’s social and economic transformation and upgrading. To this end, relevant departments should continuously improve and perfect the economic response measures for green finance and formulate new policies that meet the actual needs. Only in this way can China’s environmental protection and economic policy system be further improved to encourage the durable and healthy development of the whole green economy.

Green finance can promote environmental protection and governance and guide the flow of resources from high-polluting and energy-intensive industries to sectors with advanced concepts and technologies. Power finance is simply a part of the green finance policy. At the same time, digital finance is the most important part of the digital economy, and it is also the development direction of green finance, innovation and financial technology. For this we can accelerate the deep integration of digital technology and financial development, combine the long-term benefits of investment projects with ecological benefits, focus on developing green industries, and promote green and sustainable social and economic development. Under the vision of “carbon neutrality”, the transition to a low-carbon economy has become a global consensus issue, and “green finance” + “digital finance” just happens to be a bridge to balance industrial development and protect the ecological environment. Therefore, a survey was conducted on the degree of integration of digital technology and financial development. The conclusions of the survey are: First, the trend in electric financing can significantly enhance power utilization efficiency, and the improvement of regional innovation capabilities is an efficient means of promoting digital finance to improve energy efficiency. Second, digital finance and the improvement of innovation levels in different regions have different impacts on energy utilization efficiency, and energy utilization has a positive spatial spillover effect on adjacent regions. Whether it is digital finance or regional innovation, it will promote energy efficiency in adjacent regions. For this reason, new bridge infrastructure must first be developed, such as “5G”, artificial intelligence, big data, etc., for provision of a robust pipeline for the evolution of financial services in digital form. The third is to speed up the pace of the independent innovation of enterprises, innovate and promote energy efficiency through innovation and reduce environmental pollution. The third is to take full advantage of the evolution of digital finance to enhance China’s technological innovation capabilities. Simultaneously, through technological innovation, the advancement of financial accounting has been further promoted, and the benevolent cooperation and win–win interaction between the two has been progressively materialized. All in all, in the context of green and sustainable development, digital finance has greatly improved energy utilization, laying the foundation for future social development without destroying the ecology.

2. Related Work

With the rapid development of society, the pace of the economy is also accelerated, and environmental pollution is becoming more and more serious. Therefore, it is necessary to accelerate the improvement of traditional development models and improve the energy efficiency of industrial development, thereby promoting the improvement of the ecological environment. However, due to the rapid economic development, ecological environment in the information age and the deterioration of the environment, China does not have a relatively complete response policy. Optimizing incentive policies for the ecological environment has become an important task for enterprises and society. Tan, Chen and Sun [1] use a nonlinear programming model to study the auxiliary role of ecological policy and digital economy on enterprise ecological governance policy. Research shows that when the prepaid amount of ecological governance is insufficient, green digital financial loans can be used to obtain the most ideal decision-making space and finally achieve the desired effect [1]. Based on the background of developing green sustainable goals to protect the environment, a sustainable green digital economy is the best direction for the financial industry and shifting financial development to green and sustainable digital finance is a major reform. Sustainable financial development refers to the continuous adjustment of the financial system and financial mechanisms with the development of the economy, to rationally and effectively mobilize and allocate financial resources and improve financial efficiency to realize the effective operation and stable development of the economy and finance in the long run. A sustainable financial centre is a financial market that, as a whole, contributes to sustainable development and value creation in economic, environmental and social terms. In other words, ensuring and enhancing economic efficiency, prosperity and economic competitiveness today and in the long term, while protecting and restoring ecosystems, promoting cultural diversity and social well-being. The main problems are that there is no unified standard for strategy, insufficient reform and innovation, and insufficient friendly cooperation. Zhou [2] issuesand guides relevant decisions according to the basic status quo of China, further analyzes the seriousness of the problem, and gives improvement methods so that green finance can develop better and contribute to the construction of ecological civilization. In the era of rapid economic development, the awareness of sustainable development is also increasing, and energy conservation and environmental protection are also topics of concern. At the same time, the sustainable development of the green economy is making rapid progress in decision-making, optimization and practical research. Li, Wu and Zhang [3] builds a framework for green finance based on the identification and detection of return-on-investment theory. From 2002 to 2018, China measured industrial linkages in two provinces and studied the relationship between the financial and environmental protection sectors. The results show that from 2002 to 2015, the national energy conservation and emission reduction agencies have evolved from a situation of backward-oriented weak and forward-oriented efforts to a situation of backward-oriented strong and forward-oriented weak [3]. After a long-term summary and research, it is found that the social, energy, and ecological consequences should be an important part of the sustainable development of the natural gas and oil industries in China but are not limited to many countries in China. Steblyanskaya, Wang, and Gabdrahmanova [4] report that there is a certain relationship between sustainable financial and nonfinancial factors. After comparing the industrial development of many countries, it iss found that China’s progress is relatively stable. The growth and sustainable development of the digital economy will soon cover the ideology of the global national economy, and the key point is also shifting from the measurement of achievement to rational choice. This will become the key to green and sustainable development in the future, so it may be necessary to optimize this kind of economy. All in all, the looming issue of sustainable development is the transformation of the financial system and the emergence of a new green economy based on corporate social responsibility. Alieva and Altunina [5] experiment on how to establish a sustainable green finance theory and practice to ensure the stable development of Russia.

In the era of big data, many daily problems can be solved by making assumptions and then experimenting with existing experience, the main purpose is to obtain the optimal solution. At present, energy efficiency is also planned, but there is no relatively optimized technology that can solve the problem of energy waste in a short time. Escamilla, Salido and Giret [6] invent the genetic algorithm to solve a series of problems in traditional scheduling. In these problems, each step must be operated by the same device, and it can operate at different speeds to handle diverse tasks with different device energy consumption. The test results show that traditional energy tools cannot solve intractable diseases in a short time, but genetic algorithms can solve all problems through one-to-one personalized solutions [6]. The decoupled structure of Software Defined Networking (SDN) is a solution for more flexible and easier network management. Here, the composition of the rate of return reflects the predictability of the network, which has an auxiliary effect on the improvement of energy efficiency, and there are many hidden dangers that cannot be predicted by the naked eye in today’s social network, but SDN can make the network more secure and improve energy utilization. Rawat and Reddy [7] propose to use SDN to solve various security threats. Zappone, Lin, and Jorswieck [8] discuss the energy drain problem of multiwire listening communication channels, where malicious users attempt to eavesdrop on communications between two legitimate users. Contrary to the views of most scholars, the purpose of improving energy efficiency is to minimize loss and send information secretly, which will eventually make the loss ratio the lowest confidentiality rate. Therefore, many unexposed problems may emerge from this, so algorithms are also optimized to produce solutions with intractable solutions [8]. All in all, from the relevant research of the above scholars, the development of digital finance under the background of green and sustainable development can promote the improvement of energy efficiency to the greatest extent and lay the foundation for further social and economic development. For a detailed overview, see

Table 1. Overview of the literature review.

Study	Research Content
[1]	Using a nonlinear programming model to study the auxiliary role of ecological policy and digital economy on enterprise ecological governance policy
[2]	Combined with the relevant strategic deployment and guidance of China’s economic development, in-depth analysis of existing problems and recommendations
[3]	Provides a framework for evaluating green finance through linkage analysis based on input–output theory
[4]	Links between financial sustainability and non-financial factors were found, represented by a new mathematical dynamic model
[5]	Consider the theoretical and practical aspects of creating a national green finance model to ensure sustainable growth in the Russian Federation
[6]	A genetic algorithm is developed to solve an extended version of the classic job shop scheduling problem
[7]	Various security threats addressed by SDN and new threats emerging due to SDN implementation are presented
[8]	The problem of energy-saving resource allocation in multi-antenna eavesdropping channels is studied

.

3. Promote the Sustainable Development of Green Finance and Improve Energy Utilization

3.1. Establish and Improve the Green Financial System

The GFS is an important part of the development of green digital finance, China’s green economic model consists of the following aspects: basic legal system, implementation system, and supervision system [9]. However, to promote the systematic growth of the green finance sector, these systems still have many defects in some aspects. Thus, it is essential to further strengthen the establishment of the green financial system and improve the energy order supervision of the green marketing market, to achieve the goal of its development. First of all, it is required to fully recognize the importance of the green GDP accounting system and, at the same time, integrate green finance into government performance evaluation. Only in this way can various environmental indicators of green finance meet relevant standards. Only in this way can the guiding function of the government be strengthened, better manage the development of green finance and influence energy efficiency in the process of economic development [10]. Secondly, all financial enterprises must do a good job of avoiding economic risks in advance and ensure that the company’s green financing business is standardized. Only in this way can they encourage the advancement of the green industry and enable the harmonious development of both people and finance [11]. To make green finance achieve sustainable development and improve energy efficiency as soon as possible, it is required to strengthen the coordination of the green regulation of finance agencies in the reform of the financial system and establish a sound information exchange mechanism. In this way, the government and the market can truly complement each other and promote each other [12]. At the same time, it is necessary to keep abreast of the environmental status and environmental protection status of the relevant enterprises and inform the relevant units of the specific situation, to solve and deal with the existing environmental pollution problems in the shortest time, to ensure better financial green development [13]. On this basis, the state and enterprises should cooperate with each other to maintain a state of relative cooperation and —win-win, to improve the sustainable green economic system. Efforts should be made to enable various departments to implement fiscal policies in a coordinated manner. Only in this way can green financial policies be further improved and provide guarantees for the sustainable and stable development of the green digital economy. With these prerequisites, energy efficiency can be improved steadily [14]. Finally, to expand the scale of green insurance, especially for relatively heavily polluting companies, an environmental pollution liability insurance system should be established, and green insurance products should be improved to meet the company’s long-term development needs. Only in this way can energy utilization be maximized, and the long-term goal of green energy conservation and environmental protection be achieved [15].

3.2. Impact of Green Finance on Energy Efficiency

Energy is an essential ingredient for green economic growth. In recent years, the substantial increase in energy consumption, environmental pollution, global warming and other issues have posed a great threat to human health and the ecological balance [16]. At present, China has listed the advancement of sustainable business growth and the improvement of energy efficiency as the decisive goals of China’s long-term development [17]. A digital economy that adheres to the concept of sustainability is a change to China’s high-loss and high-pollution modes. From the perspective of optimizing traditional structures, energy conservation and emission reduction, energy efficiency can be improved. [18]. According to China’s current level of evolution, the evolution of the green market economy not only reflects the global responsibility for the environment but is also a major route for China to accelerate the transformation of sustainable evolution through energy efficiency [19]. To this end, the Chinese government proposes to take the evolution of a green electronic market as the most important development tool to promote the efficient use of resources and the progressive realization of environmental protection [20]. Figure 1 shows the development level of power-based and nonpower-based regions.

At present, China is in a critical phase of industrialization and urbanization, and the need for energy has increased from day to day. Simultaneously, China’s current power utilization rate is still at the primary level, economic growth is heavily dependent on energy and the development mode is still extensive [21]. Therefore, it is of great practical importance to increase the innovation level of Chinese energy technology and increase energy efficiency [22]. All in all, the development of green finance can improve the energy efficiency of enterprises and promote technological innovation. Simultaneously, with the improvement of the financial system, the sustainable development of the financial market will further reduce China’s pollution emissions [23]. Details can be found in

Table 2. Energy efficiency and financial ratios.

Year	Energy Consumption	Economic Growth/Billion	Energy Efficiency	Financial Ratios
1995	143,896	68,523	0.45	0.99
2000	152,304	98,563	0.68	1.32
2005	228,956	195,623	0.77	1.55
2010	335,612	418,956	1.22	1.81
2015	401,256	405,689	1.55	2.23
2020	516,203	752,356	1.98	2.56

.

3.3. Past and Present Status and Future Evolution Tendency of the Energy Consumption in China

Due to the rapid development of the times China’s resource consumption has also seen tremendous growth. From 1990 to 2000, it could be said that energy consumption was not very low and even increased gradually every year compared with the previous year. The improvement of energy-saving efficiency is an essential strategy for green business. Although China’s energy efficiency has improved significantly in recent years, there is still a considerable gap in comparison with the remainder of China. The results of previous studies show that there is some relationship within China between the growth of the economy and power expenditure, and power expenditure and environmental pollution emissions are the main driving forces for economic development. As can be seen from the chart, energy consumption and economic development are synchronized. As shown in the illustration, the enhancement of energy consumption and GDP is stable; while the GDP is developing rapidly, energy consumption also experienced large growth. From this point, it follows that the development of China’s green and sustainable economy is inseparable from power expenditure. Simultaneously, on the basis of the low energy utilization rate in China, economic growth is heavily dependent on energy, but extensive development is still the main business evolution. Therefore, the evolution of green finance is an important way to improve China’s power efficiency, as shown in Figure 2.

Decades of trend data have shown that the key to improving energy efficiency in recommending sustainable green finance lies in independent innovation and technological progress. The green financial system can not only provide external financing for technological innovation of enterprises but also optimize the process and reduce consumption costs, thus having a profound effect on the resource depletion in the process of the financial processes. This ultimately acts on the improvement of the ecological surroundings and enables a sustainable economic process to be realized. At the same time, the evolution of the green economy is market-oriented, based on the traditional enterprise economy and developed for the purpose of harmony between the economy and the environment. It can not only effectively reduce consumption costs, but also promote and supervise investment in technological innovation through the establishment of debt relationships. In sum, financial development contributes to the overall technological innovation of enterprises, and to a certain extent, encourages the enhancement of the efficiency of energy use in China.

3.4. Model Construction and Solution of the Impact of Digital Finance (DF) on Energy Efficiency (EE)

From vigorously improving the financial system to the impact on energy efficiency, combined with the development trend of energy consumption, after conducting the relevant research, this paper first establishes a benchmark-based regression model to study the effects of digital finance on energy efficiency:

$$E{E}_{it}={\alpha }_0+{\alpha }_{1}Inde{x}_{it}+{{\displaystyle \sum }}_{j=2}^n{\alpha }_j{X}_{it}+{\mathsf{ℇ}}_{it}$$

(1)

As DF has a profound effect on regional Neuerungen capabilities, it improves energy efficiency.

This mechanism is tested accordingly. On the basis of the basic regression formula, an intermediate action formula is introduced:

$$C{X}_{it}={\beta }_0+{\beta }_{1}Inde{x}_{it}+{{\displaystyle \sum }}_{j=2}^n{\beta }_j{X}_{it}+{\mathsf{ℇ}}_{it}$$

(2)

$$E{E}_{it}={\chi }_0+{\chi }_{1}Inde{x}_{it}+{\chi }_{2}C{X}_{it}+{{\displaystyle \sum }}_{j=3}^n{\chi }_j{X}_{it}+{\mathsf{ℇ}}_{it}$$

(3)

In the empirical analysis, if both $\beta$ and ${\chi }_1$ are positive, it means that the mediation effect is effective. If at least one of $\beta$ and ${\chi }_1$ is non-significant, then the significance of the mediation effect must be further tested.

From the large logarithmic data, problems such as spikes, fat tails, heteroscedasticity, etc., tend to appear, so the estimates will be biased. To overcome this shortcoming, Koenker and Bassett propose a quantile regression method. The specific quantile expression is as follows:

$$Q_{E{E}_{it}}(\mathsf{\tau }|Inde{x}_{it})={ᶊ}_i+Inde{x}_{it}^T\partial (\mathsf{\tau })$$

(4)

In the quantile case, the fixed effect factor does not change. However, in different quantiles, the estimated coefficients of $Index$ will change, and Model (5) must be solved to obtain the parameters of Model (4) at different quantiles at the same time.

$$\min \partial {{\displaystyle \sum }}_{k=1}^q{{\displaystyle \sum }}_{t=1}^T{{\displaystyle \sum }}_{i=1}^n{\omega }_k{U}_{\tau k}(E{E}_{it}-{ᶊ}_i-Inde{x}_{it}^T\partial (\mathsf{\tau }))+\mathsf{Ϩ}{{\displaystyle \sum }}_{i=1}^n|{ᶊ}_i|$$

(5)

On this basis, the estimation method determined by Koenker and Bassett is used to solve Model (5).

If only the general panel mode is used, it is easy to ignore the spatial correlation between areas. When the economic relationship between regions becomes closer and closer, the interaction between regions is increasingly obvious, and in the economic system the energy system is ignored. Due to the influence of correlation, the estimation results of the model will be biased. Therefore, the use of spatial metric models can solve this problem well. The most common in spatial measurement are the spatial postpone model and the spatial fault model. The spatial delay model can study the effect of factors in the adjacent area on the factors around, that is, the spatial spillover influence; the spatial error model mainly studies the impact of the collision error of the explanatory variable in the adjacent area to the area. In addition, since regional innovation is equivalent to the intermediate volume of this paper, it also has a technology spillover effect, that is, the innovative knowledge and technology in developed regions spread to backward regions. Therefore, the regional innovation level is included in the spatial measurement model, and based on Model (3), the effect of digital finance and the regional level of energy efficiency innovation are analyzed.

The spatial delay and spatial error models are constructed as follows:

$$E{E}_{it}={\delta }_0+\mathsf{\rho }WE{E}_{it}+{\delta }_{1}Inde{x}_{it}+{\delta }_{2}C{X}_{it}+{{\displaystyle \sum }}_{j=3}^n{\delta }_j{X}_{it}+{\mathsf{ℇ}}_{it},{\mathsf{ℇ}}_{it}\in (0,\mathsf{\sigma }²I)$$

(6)

$$E{E}_{it}={\varpi }_0+{\varpi }_{1}Inde{x}_{it}+{\varpi }_{2}C{X}_{it}+{{\displaystyle \sum }}_{j=3}^n{\varpi }_j{X}_{itj}+{\mathsf{ℇ}}_{it}$$

(7)

$${\mathsf{ℇ}}_{it}=\mathsf{\lambda }{{\displaystyle \sum }}_{i=1}^{k}W{\mathsf{ℇ}}_{it}+{\mu }_{it},{\mu }_{it}\in \left(0,\mathsf{\sigma }²I\right)$$

(8)

where $\delta$, $\mathsf{\rho }$, $\varpi$ are all coefficients of variables, ${\mathsf{ℇ}}_{it}$, ${\mu }_{it}$ are a normal error, and W is a space weight. In terms of establishing the spatial weight matrix, the previous literature is referred to, and the 0–1 geographic adjacent weight matrix is used as the benchmark.

$$e{g}_{it}={\alpha }_0+{\alpha }_{1}df{i}_{it}+{\alpha }_2{X}_{it}+{\lambda }_i+{\eta }_t+{\mathsf{ℇ}}_{it}$$

(9)

Among these indicators, one explained variable, $e{g}_{it}$, is the province’s energy efficiency i in year t. $df{i}_{it}$ is the digital economy evolution plane of a county in t years. The vector $X_{it}$ is a set of control variables that may have an impact on energy use. ${\lambda }_i$ is a fixed effect. ${\eta }_t$ is the stability of time. ${\mathsf{ℇ}}_{it}$ is a random perturbation.

To address this issue and better recognize the effects of digital banking development on energy efficiency, this paper used instrumental variables. The method 2 SLS regression analysis method was used.

The stage formula is as follows:

$$df{i}_{it}={\beta }_0+{\beta }_{1}i{v}_{it}+{\beta }_2{X}_{it}+{\lambda }_i+{\eta }_t+{\mathsf{ℇ}}_{it}$$

(10)

Here, the instrumental variable of choice is iv. Based on exploring the role of GDF development for power efficiency, this paper adopts the “intermediate effect” model:

$$m_{it}=b_0+b_{1}df{i}_{it}+b_2{X}_{it}+{\lambda }_i+{\eta }_t+{\mathsf{ℇ}}_{it}$$

(11)

$$e{g}_{it}=c_0+c_{1}df{i}_{it}+c_2{m}_{it}+c_3{X}_{it}+{\lambda }_i+{\eta }_t+{\mathsf{ℇ}}_{it}$$

(12)

Here, m is an intermediate changeable, and the specific steps of the intermediate impact test are as follows: First, (9) is regressed, and ${\alpha }_1$ reflects the overall effect. If the value of (9) is positive, it indicates the effects of digital economy on power efficiency. Then (11) is regressed. If the value of (1) is positive, it means that digital finance has a significant effect on the intermediate variable, and finally it is regressed on (12). $c_1$ represents the direct impact of the evolution of digital economy on the improvement of energy efficiency, and $c_2$ × $b_1$ is the indirect effect. Under the premise that $c_2$ is positive, if $c_1$ has no obvious effect, it means that there is a sufficient mediation effect. When it is significantly positive and decreases relative to the value in (9), it indicates that there is a certain intermediate effect, and the proportion of the intermediate effect is $c_2$×$b_1$/${\alpha }_1$; the intermediate effect does not exist.

For the threshold effect of this influence, the following model is constructed based on Equation (9), taking the single threshold case as an example:

$$e{g}_{it}={\phi }_0+{\phi }_{1}df{i}_{it}\times I\left(q_{it}\le \mathsf{\gamma }\right)+{\phi }_{2}df{i}_{it}\times I(q_{it}>\mathsf{\gamma })+{\phi }_3{X}_{it}+{\lambda }_i+{\eta }_t+{\mathsf{ℇ}}_{it}$$

(13)

Reviewing the existing research and the literature, scholars often take the provincial-level green finance development level represented by a single green credit and green investment, and a few scholars adopt the index analysis method to comprehensively measure by selecting multiple indicators to give weight. This takes into account that an individual indicator cannot fully report the development standard of the regional green economies. For this reason, this document chose the theory of entropy of panel data to build the regional green finance development indicator system.

The weight and total score are calculated according to m years, k regions, and n indicators. The specific process is as follows:

The first step is to normalize the metrics. Due to inconsistent index scales, the calculated results are biased.

For positive indicators:

$$Z_{\alpha ij}=\frac{x_{\alpha ij}-x_{min}}{x_{max}-x_{min}}$$

(14)

For negative indicators:

$$Z_{\alpha ij}=\frac{x_{max}-x_{\alpha ij}}{x_{max}-x_{min}}$$

(15)

In the formula, $x_{max}$ and $x_{min}$ are the max and min figures of the jth indicator in each year in each region, and $x_{\alpha ij}$ and $Z_{\alpha ij}$ are the values before and after standardization of the jth indicator in the $\mathsf{\alpha }$ year of the i region.

The second step is to normalize the indicators:

$$P_{\alpha ij}=\frac{Z_{\alpha ij}}{{{\displaystyle \sum }}_{\alpha =1}^m{{\displaystyle \sum }}_{i=1}^k{Z}_{\alpha ij}}$$

(16)

This stands for the proportion of the observation value in the $\alpha$ year in the i region in the overall figures from the j pointer.

The third stage is the determination of the degree of entropy $E_j$ of each exponent:

$$E_j=-k_1{{\displaystyle \sum }}_{\alpha =1}^m{{\displaystyle \sum }}_{i=1}^k{P}_{\alpha ij}\mathrm{In}{P}_{\alpha ij}$$

(17)

where m is the overall figure for the year and k is the overall figure for the regions.

$$k_1=\frac{1}{In\left(m\times k\right)}$$

(18)

In addition, if a = 0 then define:

$$\underset{P_{\alpha ij}\to 0}{\lim }{P}_{\alpha ij}\mathrm{In}{P}_{\alpha ij}=0$$

(19)

The fourth stage is the determination of the indicator redundancy $D_j$: $D_j$ = 1 − $E_j$, where j = 1, 2, 3,…, n, represents the jth exponent.

The fifth stage is the determination the indicator repetition $W_j$:

$$W_j=\frac{D_j}{{{\displaystyle \sum }}_{j=1}^n{D}_j}$$

(20)

It is the importance of the jth indicator.

The sixth stage is the determination of the comprehensive exponent score $I_{\alpha I}$ of every area in each year. $\mathsf{\alpha }$ represents the year and i represents the region.

$$I_{\alpha I}=Z_{\alpha i1}\times W_1+Z_{\alpha i2}\times W_2+\dots \dots +Z_{\alpha in}\times W_n$$

(21)

where $Z_{\alpha ij}$ stands for the standardized figures of the jth pointer in the i area in the $\alpha$ year calculated in the first step, and $W_j$ is the jth indicator weight calculated in the fifth step. The results are shown in

Table 3. Data summary.

Changeable	OBS	Indicate	STD	Least	The Largest
ineef	360	825	270	255	1640
ingrefin	360	40	105	07	575
infin	360	1688	458	613	2899
inpi	360	4122	84	1328	5359
ingov	360	1533	387	458	2438
indf	360	103	513	009	2220

.

It can be seen that the overall data fluctuate little, and there are no extreme values. Therefore, it can be concluded that in terms of improving efficiency, the digital economy is conducive to reducing market transaction costs and promoting efficiency changes to improve capital and labour productivity, thereby promoting high-quality economic development. In terms of smooth economy, it can quickly and accurately match each demand side of the industrial chain, effectively providing digital support for the development of industrial integration. In terms of green development, by improving transaction efficiency, material and energy consumption and waste in some economic activities have been reduced, and the proportion of effective production has been increased. In terms of promoting openness, domestic and foreign innovation entities and participants in innovation activities can communicate in a timely manner and improve the efficiency of technology research and development and the pace of innovation.

4. Theoretical and Comparison of the Effects of Digital Economy on Power Efficiency

Digital finance is directly related to energy efficiency. All business is carried out online. This digital service and intensive mode of operation is itself a green development method. Digital finance refers to the use of digital technology to build an environmental information sharing platform, through the disclosure of environmental protection projects, products, activities and other information, to help investors identify green investment opportunities and purchase environmentally friendly products for green consumption. This in turn increases the participation of the whole of society in green energy conservation activities, reduces energy consumption and improves energy efficiency. At the same time, digital finance can also effectively reduce the capital restrictions of real enterprises, thereby promoting the allocation of funds in the real economy, and thus having a certain impact on energy efficiency. From this, it can be seen that digital financing has played a beneficial role in improving energy efficiency. Financial institutions use digital technology to innovate financial products and services, providing individuals with a variety of multifunctional financing channels, thereby stimulating individuals’ entrepreneurial enthusiasm, and promoting enterprises’ high-efficiency and high-efficiency entrepreneurial activities. Simultaneously, the use of Web engineering can speed up the transmission of information, improve the transparency of information, allow the supply and demand sides to effectively connect to the network, exchange resources online, and everyone can obtain the maximum resource allocation. The growing demand for online transactions has prompted the emergence of various new economic forms, concentrating production factors in low-energy-consuming industries, creating new entrepreneurial opportunities, increasing residents’ income, as well as the reduction of power use per unit of GDP. Based on this, enterprises can search and integrate information through the use of digital capabilities, for example, big digital analytics, to cut the company’s learning costs, enhance the innovation capability of the enterprise, and then promote its development and reduce the energy consumption of the enterprise. From this, it turns out that the evolution of the digital economy can improve power efficiency by driving innovation in businesses.

The empirical analysis shows that the impact of financing on green development can be regulated by the degree of innovation, and the improvement of the degree of innovation can promote the efficiency of financial institutions, optimizing resource allocation and promoting the evolution of green resources. The digital economy is the combination of digital technology and financial technology, and its healthy development requires technical support. Today, with the continuous improvement of innovation and entrepreneurship, digital financing may support the enhancement of power consumption efficiency through technological reforms, management reform, product reform, etc. The stronger the regional innovation ability and the more active entrepreneurial activities, the more conducive to the research of green environmental protection technology. With the application, the development of the energy-saving industry will be better. From this point, it turns out that the effects of digital finance development on improving energy efficiency dictated the level of creation and entrepreneurship in the region.

To sum up, the effects of digital economy on power efficiency can be reflected in economic growth, innovation level, entrepreneurial activities, reducing environmental pollution and improving the ecological environment. Figure 3 shows the effects of digital banking upon the level of regional development of the economy.

By comparing the figures, it can be seen that these differences in the impact of the development of digital financing on improving energy efficiency are regional. Therefore, when formulating and implementing relevant policies, factors such as geography, economy and infrastructure in different regions ought to be fully considered. Especially in the central region, it is important to articulate regionally differentiated adaptation actions to foster the evolution of the digital industry, enhance the promotion of financial knowledge and improve the financial quality of residents. Figure 4 shows the comparison of innovation levels before and after the use of digital finance.

The level of creation is the main driver for the evolution of a green digital economy, while the progress of technology is the main driver for the improvement of energy saving effects. Due to the lack of concentration of small and small scale, incomplete business records, long-term periodicity of technological innovation activities, high risk, and other reasons, there are serious external financing constraints, and the energy price is too low, but the cost of technological innovation is high. The lack of internal motivation for enterprises to improve energy efficiency has resulted in the overall poor level and efficiency of China’s energy use technology. Digital banking is the fusion of digital skills and banking, and core technologies such as artificial intelligence and big data analysis are utilized. By analyzing the user’s network behaviour, financial analysis is performed on it to conduct a comprehensive credit evaluation, thereby reducing the cost of its acquisition and risk control. Digital funding refers to the use of funds to invest more human and financial resources in research and advancement of new skills, the development of innovative activities, the improvement of innovative output of green and energy-saving technologies, and the improvement of energy efficiency. From this point, the development of digital banking aims to harness energy by continuously improving innovation capabilities. Figure 5 shows the energy efficiency growth ratio between the extensive economy and the digital economy.

It can be seen from the figure that the digital economy and sustainable development will become the most important force for driving the future development of the financial sector. China should speed up the construction of the digital financial system, continuously improve the top-level design, continuously develop digital finance, add support for saving energy and reducing emissions, and promote the combination of digital technology and financial services. The energy efficiency is too low under the extensive economic development model. In the last few years, however, the government has been continuing to optimize the energy structure, focusing on power conservation and consumption reduction, as well as low-carbon development. The specific performance can be seen in

Table 4. Energy efficiency values.

	2005	2010	2015	2020	Growth Rate	Mean
Eastern	1.455	2.352	3.545	4.597	9.75	2.748
Central	0.795	1.152	1.792	1.955	7.48	1.478
Western	0.566	0.923	1.121	1.289	4.95	1.082

.

Figure 6 indicates the enhancement effect of the ecological environment.

Through three studies, it is noted that the evolution of digital banking in the last few years has promoted the participation of the whole society in environmental protection, reduced energy consumption and improved the ecological environment. Research shows that the coverage, breadth of utilization and level of digitalization of digital finance all have a positive effect on resource misallocation (especially in large-scale cities), such as overcapacity and overallocation of resources, which have significantly improved. Under the influence of digital finance, high-tech and green industries have more favourable development space than industries with high pollution and large amounts of power generation. The return on investment is high, which provides financial support for the research and application of green sustainable development economy, thereby helping to improve energy efficiency.

Based on the above data analysis, it can be seen that the development of digital finance has promoted a qualitative leap in the stagnant regional economy. In addition, the original financing means are severely restricted, and the energy utilization efficiency is insufficient. The development of the digital economy aims to continuously improve the innovation ability to control at the same time, under the extensive economic development model, environmental pollution is serious, and the development of the digital economy promotes the participation of the whole society in environmental protection, reduces energy consumption and improves the ecological environment.

5. Conclusions

Based on the above research, it is found that the development of the digital economy is conducive to reducing costs and improving efficiency, thereby improving productivity, and can quickly identify and match the needs of enterprises and formulate personalized response policies, providing a strong backing for technological development and innovation, while improving the green and sustainable development awareness of financial institutions is an important means to promote the development of green financial economy. If enterprises want to truly implement green finance, they need to have a certain approach to green financing and normalize and standardize the work in the field of green financing and comprehensively promote the transformation and upgrading of energy efficiency. The difference is that the evolution of digital finance has promoted the enhancement of the efficiency of energy use, but the improvement effect has regional differences. Finance can promote enterprise innovation and enterprise development; in addition, in areas with higher degrees of innovation and entrepreneurship, the development of electronic banking has a greater impact on power efficiency. Simultaneously, the idea of green and sustainable development should be understood as China’s long-term development decision, to provide a solid foundation for the coordinated growth of finance and people. To promote the sustainable growth of green banking, it is necessary to strengthen the construction of a green financial system, strengthen the supervision and evaluation of green finance, and simultaneously establish the green financing concept and build a solid information exchange system to achieve the goal of advancing social and economic change and achieving the durable evolution of the green market economy. Green bank mainly refers to a new economic form that is market-oriented, based on the traditional industrial economy and developed for harmony between the economy and environment.

In the process of developing digital finance, the original development model has been unable to adapt to the trend of society. The government should first strengthen the construction of China’s digital financial system and provide corresponding policy support for the development of China’s financial market. Secondly, financial enterprises should continuously promote the innovation of green digital financial products, promote technological innovation of enterprises through financial support functions, and thus promote the improvement of energy utilization efficiency. To sum up, the development of a low-carbon economy is inseparable from government guidance and financial support.

The primary problem that China faces in its green and low-carbon development strategy is the lack of financing. The establishment of a carbon financial system can not only solve the financing difficulties of enterprises but also effectively promote the technological innovation of enterprises. Improve the financial organization system and actively cooperate with foreign low-green financial institutions to carry out carbon finance. Banks are required to continuously improve their own organizational system, coordinate and unify the planning, implementation, supervision, and management of financial services, and provide comprehensive services for the development of digital financial services support.

To compel the region to improve the efficiency of resource utilization, enhance the efficiency of innovation and achieve sustainable development under environmental constraints, the following suggestions are put forward: First, promote economic transformation. Under the constraints of the environment, the transformation of the economic structure has a significant relationship with technological innovation, and it is especially required that the growth rate of industrial development must be coordinated with the environment. The second is to further purify the financial market environment and comprehensively promote the process of market-oriented reform. Vigorously develop the capital market, rectify the financial market order and promote the construction of a market-led financial system.

Therefore, the government should actively encourage and guide enterprises to carry out independent innovation and use legal, economic and administrative means to jointly promote SMEs to strengthen independent innovation, to provide long-term development momentum for China’s low-carbon economy. The government should also provide policy subsidies to enterprises that actively carry out low-carbon technology applications, as well as tax reductions, tax exemption and other policies to support enterprises in low-carbon technology innovation.