The Nexus between Digital Finance and High-Quality Development of SMEs: Evidence from China

Abstract

In the context of digital finance and based on the characteristics of the high-quality development of SMEs in China, this paper investigates the influence of digital finance on the high-quality development of SMEs and explores their mechanism of influence. A panel econometric model and mediation model are used to evaluate the data of 581 SMEs in China from 2011 to 2020. The results show that digital finance has a significant role in promoting the development quality of SMEs. Heterogeneity analysis shows that the promotion effect of digital finance is more obvious in central and western regions, non-heavy pollution industries and non-state-owned SMEs than that of other SMEs. Further analysis shows that digital finance improves the efficiency of financial resource allocation, which in turn promotes the high-quality development of SMEs. After applying a test of robustness, the results proved significant.

1. Introduction

With the background of economic transformation and major health emergencies, small and medium-sized enterprises (SMEs) play an important role [1]. As the main part of economic development, SMEs not only stabilize society but also promote social progress. Since the implementation of China’s reform and opening-up policy, the development of SMEs has grown from weak to strong, and play an important role in promoting social and economic development, contributing to employment and stabilizing tax revenues [2]. First of all, with the transformation of China’s economic structure, a large amount of the labor force has been transferred to the tertiary industry. Since SMEs are mainly distributed in the tertiary industry and most of them are labor-intensive, they relieve social employment pressure. Secondly, the number of SMEs is relatively large, which can improve market vitality through competition and promote China’s economic development [3]. The number of SMEs accounts for more than 90% of the total number of enterprises in China and they contribute more than 50% of the country’s tax revenue, more than 60% of GDP and more than 80% of urban employment [4,5]. Their large size as well as their ability to generate synergies make the development of SMEs extremely vital to policy makers. At present, China’s economy has shifted to the stage of high-quality development [6], so promoting the high-quality development of SMEs can help the economy better achieve high-quality development.

In the context of rapid development of information technology and the Internet, digital finance has developed rapidly [7]. The median value of China’s digital finance index in 2011 was 33.6, and the median value of the digital finance index in 2020 was 334.8, with an average annual increase of 30.12% [8]. In addition, some new financial institutions, such as JD Finance and Zhongan Insurance, have emerged and the scale of third-party payment and online loans have also gradually expanded [9]. As a new form of financial industry, digital finance impacts the traditional financial system and promotes the reconstruction of the financial system [10]. The development of digital finance lowers the threshold of people’s access to financial products, which has an important impact on the social economy [11], such as promoting economic growth [12,13,14], narrowing the income gap [15,16,17] and promoting residents’ consumption [18,19]. The biggest advantage of digital finance is that it supports the development of inclusive finance [20]. Compared with the traditional financial industry, digital finance relies on Internet technology and has higher accessibility and wider service coverage, which is more conducive to the development of SMEs [21].

The contribution of this paper lies in the following aspects. Firstly, although the development of SMEs should be comprehensive and holistic, most of the existing studies on SMEs focus on a certain aspect of SMEs. Therefore, according to the existing research on the high-quality development of SMEs [22,23,24,25], this paper establishes a comprehensive index, which can reflect the degree of high-quality development of SMEs. Secondly, in view of the existing studies, and in context of the rapid development of digital finance, this paper investigates the relationship between digital finance and the high-quality development of SMEs, and explores their heterogeneity in terms of region, industry, and nature of enterprises, enriching the literature on digital finance. Thirdly, when considering how digital finance affects the high-quality development of SMEs, this paper adopts a mediating effects model to further evaluate the transmission effect of financial resource allocation efficiency on digital finance affecting the high-quality development of SMEs, further deepening the existing literature. In addition, this paper changes the model to increase the robustness of the main conclusions.

The rest of this paper is organized as follows. Section 2 provides relevant literature and the development of hypotheses. Section 3 presents the data and methodology used in the study. Section 4 discusses the empirical results. Section 5 presents a discussion. Section 6 summarizes the study and provides policy implications.

2. Literature Review and Research Hypothesis

2.1. Literature Review

In terms of research on the definition of digital finance, Polasik et al. [26] and Uddin et al. [27] both believe that digital finance is essentially a fusion of computer technology and traditional financial services. In other words, digital finance is the internet-based generation of traditional finance. It provides customers with a variety of traditional financial services such as payment and settlement by using digital technology [28]. Some scholars believe that the core of digital finance is inclusive finance. Dong and Zhao [29] believe that digital inclusive finance originates from financial geography and focuses on financial accessibility. Its goal is to achieve the equalization of financial rights and improve the level of financial resource allocation [30]. In addition, the definition of digital finance may change with time. For example, Zhou [31] thinks that early digital finance was the combination of traditional finance and the Internet, but now digital finance refers to the development of emerging products and services driven by technological innovation.

Digital finance has various functions in the economy; it can not only exchange value across time and space, but also optimize resource allocation [32] and use relevant technologies to reduce credit risk at an early stage, especially in banks with a high management shareholding [33]. In addition, digital finance can capably prevent risk of default, which is caused by information asymmetry by using blockchain technology in the personal credit system [34]. Wang et al.’s [35] research finds that digital finance based on information technology has a subversive impact on the existing financial model in broadening the sources of risk assessment, mining the potential needs of users and improving the efficiency of risk pricing. Additionally, some emerging literature suggests that digital finance can also reduce poverty [36]. The development of digital finance can protect low-income groups and help economically challenged areas to obtain formal financial services, improving productivity and promoting economic development in these areas [37]. Furthermore, digital finance can also narrow the income gap [35] and significantly reduce effects of poverty in different Asian countries [38].

The research on digital finance and SMEs is mainly divided into three aspects. Firstly, digital finance is beneficial to the technological innovation of SMEs. Financial institutions can use digital technology and other emerging technologies to help SMEs value new projects and more easily track the use of funds, which helps SMEs’ innovation activities to run smoothly [21,39]. Secondly, digital finance has the function of relieving the financing constraints of SMEs. On the one hand, the development of digital finance has reduced the cost of credit and increased the amount of funds that SMEs can obtain. On the other hand, digital finance can innovate financial products and services through scenario application and other technologies. Therefore, digital finance can alleviate the financing constraints of SMEs [1,40,41]. Finally, digital finance can improve the operating efficiency of SMEs. For one thing, digital finance promotes information sharing, improves the quality of information disclosure of SMEs, and establishes an effective sharing mechanism to improve the operating efficiency of SMEs. In addition, digital finance optimizes the external financial environment and helps improve the productivity of enterprises [42].

In summary, the papers on the quality development of SMEs are mainly qualitative studies, and there is scant literature on the relationship between digital finance and the quality development of SMEs. Therefore, this paper attempts to construct an index system for high-quality SME development based on the connotations of high-quality SMEs’ development, and further investigates whether the development of digital finance can promote high-quality SME development and thus accelerate China’s economic transformation.

2.2. Research Hypothesis

2.2.1. Digital Finance and High-Quality SMEs

The concept of financial inclusion was introduced by the United Nations and the World Bank in 2005. The concept of financial inclusion is “Let everyone have access to timely, dignified and high-quality financial services at appropriate prices when they have financial needs” [43]. In the context of rapid development of emerging technologies, such as big data and mobile Internet, traditional inclusive finance has combined with digital technology, resulting in the emergence of digital finance [10]. The essence of high-quality development is the pursuit of quality and efficiency, which is a new development concept. The high-quality development of enterprises should also pursue both quality and efficiency. High-quality development of SMEs should have (i) the ability to innovate, (ii) quality products and services, (iii) sound management and governance mechanisms, and (iv) outstanding financial performance [22,44,45]. In addition, the high-quality development of SMEs should (v) improve the level of green ecology and improve environmental protection abilities [23].

Firstly, innovation is a long-cycle, high-risk and high-return activity. Traditional financial institutions usually have disadvantages in the process of serving SMEs, so SMEs have a higher threshold for innovation [46]. The traditional financial industry is more rigorous in risk control, while SMEs have a vacancy in operating information due to their small size, lack of collateral and relatively opaque financial status, making it difficult for financial institutions to make a comprehensive assessment of SMEs, leading to most financial institutions being reluctant to provide financial support to projects with higher risks and longer cycles. Because most SMEs are excluded from traditional financial services, the problem of insufficient financial resources constrains the innovative activities of SMEs [7]. However, digital finance can use cloud computing and other technologies to conduct a comprehensive assessment of enterprises based on their existing information, which eases the problem of information asymmetry and effectively identifies enterprise information, resulting in enabling financial services to reach more long-tail users and better cover SMEs; as a result, digital finance can provide financial support for SMEs to carry out innovative activities [39]. Therefore, digital finance can promote the high-quality development of SMEs. Secondly, digital finance improves residents’ levels of consumption [47]. Digital finance promotes the upgrading of residents’ consumption by expanding the coverage of financial services and optimizing the payment environment [48]. The upgrading of residents’ consumption can promote SMEs to improve product quality and produce more quality products, improving the quality of SMEs. Thirdly, digital finance increases the accessibility of financial services [49] and improves the governance capacity of the non-family shareholders of SMEs. Importantly, digital finance can monitor the major shareholders and management with the help of cutting-edge and other technological tools, which improves the transparency of SMEs and circumvents the problems of adverse selection and moral risks, which further optimizes internal governance mechanisms and thus improves the quality of SMEs’ development. Fourthly, due to the slow market response and lack of liquidity, SMEs face financing constraints in the process of development, making financing difficult and costly [21]. Digital finance can reduce the cost of financing for SMEs using new financing methods, such as third-party payment platforms [42], which reduces the financial costs of SMEs and helps them achieve sustainability and improve the quality of their development [50]. Finally, digital finance as a deep combination of technology and finance can help SMEs to carry out green projects; in addition, digital finance innovates green financial products to serve the green innovation of enterprises [51]. Digital finance uses emerging technologies such as big data to optimize the production processes of SMEs and create the conditions for green innovation [52].

Therefore, based on the above analysis, the following hypothesis is proposed in this paper:

Hypothesis 1 (H1).

 The development of digital finance can promote the high-quality development of SMEs.

2.2.2. Digital Finance, Financial Resource Allocation and High-Quality SMEs

Resource allocation efficiency refers to the efficiency of allocating scarce resources from a marginal inefficient sector to a more efficient sector, so as to make it as close to the Pareto optimal state as possible [53]. The allocation of resources is mainly completed by the financial market, so the development of finance is the main factor determining whether the allocation of resources can be optimized. Moreover, because the most basic function of finance is to guide social resources to flow into more efficient sectors as much as possible, the development of finance helps to improve the efficiency of resource allocation [54]. Digital finance, as a new stage of financial development, is a continuation of the sustainable development of the financial industry, causing changes in the financial structure [53]; it is believed that the financial structure would affect the efficiency of resource allocation based on neoclassical economics. This paper analyzes how digital finance affects the allocation efficiency of financial resources from two aspects of the financial system structure and financing structure, and finally, how the high-quality development of SMEs can be achieved.

Firstly, as the core component of the mechanism of the modern market, the perfection of the financial system is directly related to the efficiency of financial resource allocation. Dai and Zhang [55] believe that a perfect financial system should have a reasonable structure and diversified business forms. As a typical bank-oriented financial system structure, China is characterized by excessive government intervention [56]. Banks have a natural preference for risk avoidance and often have a significant “anchoring effect” when supporting enterprises in economic activities. The first is “attribute anchoring”. Due to the lack of price signal guidance and the constraints of a prudential risk assessment system of banks in China’s traditional financial system, there is often “ownership discrimination” in China’s traditional financial sector. Financial resources tend to flow to state-owned enterprises with implicit government guarantees and policy support, resulting in potentially unfair allocation of financial resources. The second is “stage anchoring”: the traditional financial sector, when conducting a credit qualification screening, often uses enterprises’ “hard information”, such as mortgage assets, profitability, etc. Due to the nature of SMEs’ early growth or projects or risk, a lack of collateral resources causes the SMEs to be excluded from the traditional financial system. Traditional finance appears to be an “inertia problem” in the process of serving the real economy, which is not conducive to the high-quality development of SMEs [57]. An “anchoring effect” often leads to the distortion of financial resource allocation and reduces the efficiency of financial resource allocation. According to the Schumpeterian economic analysis framework, the bank-dominated financial system structure adapts to the needs of growing technological change. The structure of China’s financial system is dominated by state-owned banks and has some outstanding problems in resource allocation efficiency and sustainable economic development [58]. The rapid development of digital finance relies on the traditional financial system but has spawned a large number of new financial institutions and technology companies. The emergence of Internet banks (Webank, Xinwangbank, etc.) and online crowdfunding platforms has profoundly affected the pattern of the traditional bank-dominated financial system [59]. The emergence of new financial institutions, such as Internet banks, covers low-income groups and SMEs well, expands the coverage of financial services, improves the financing capacity of capital and the allocation efficiency of financial resources. At the same time, driven by digital technology, traditional financial institutions have in-depth cooperation with new Internet banks to form joint loans or realize data sharing with third-party institutions to form open banks [9]. The new financial institutions enhance the competitive pressure of the traditional financial industry, which has caused some impact on traditional financial institutions and accelerated the digitalization process of traditional financial institutions. For example, the establishment of the “Inclusive finance Business Department” has significantly improved the efficiency and quality of financial services [30]. Therefore, digital finance can improve the efficiency of financial resource allocation and reduce the financing constraints of SMEs, which can create the conditions for their economic activities and ultimately achieve the high-quality development of SMEs.

Secondly, since China has a bank-based financial structure, the structure of the financing market is dominated by indirect financing. In terms of the internal structure of indirect financing, the flow of financing is mostly concentrated in large enterprises and state-owned enterprises [60]. In 2020, SMEs accounted for 95.6% of market entities and more than 50% of tax payments [5], but the balance of domestic and foreign currency loans from financial institutions was CNY 178.4 trillion, and that of SMEs was CNY 15.1 trillion (Data Source: www.pbc.gov.cn). In addition, although there are many main bodies of various banks in indirect financing in China, the problem of homogenization is serious, the institutional structure is singular, and the positioning is not clear [61]. Therefore, the indirect financing structure dominated by banks cannot meet the capital needs of SMEs. However, in the direct financing market, the entry threshold of the bond market and stock market is high, and large enterprises have a large capital demand but slow turnover and low capital utilization efficiency, while SMEs in the growth stage have a relatively small capital demand and high capital utilization rate, but it is difficult to obtain equity-based assets [62]. Therefore, it is obvious that there exists some financial resource misallocation and a low efficiency of financial resource allocation in China’s existing financing structure. However, with the development of digital finance, the p2p online loan market [30], equity crowdfunding methods and supply chain finance [20,63] have a low cost and low investment threshold. They can take advantage of the long-tail effect to provide personalized services to serve small and medium-sized enterprises. Therefore, digital finance can increase the proportion of direct financing [64], optimize the financing structure and improve the efficiency of financial resource allocation.

Through the above analysis, it is obvious that digital finance can improve the efficiency of financial resource allocation. The improvement of financial resource allocation efficiency provides funds for the development of SMEs and lays the foundation for achieving high-quality development.

In view of the above analysis, we therefore propose:

Hypothesis 2 (H2).

 The efficiency of financial resource allocation mediates the role between digital finance and the high-quality development of SMEs.

3. Methodology and Data

3.1. Models

3.1.1. Super Efficiency SBM Model

The SBM model is different from the previous CCR and BCC models in that its efficiency value does not change with input and output. The traditional DEA model can divide DMU into effective and invalid parts, and the effective decision units are all assigned a value of 1. Due to the disadvantages of exogenous fixed parameters, it is difficult to evaluate and screen decision-making units [65]. Therefore, referring to the research of Qu et al. [65], this paper adopts a super-efficiency SBM model to measure the allocation efficiency of financial resources. The super-efficiency SBM model will change with the degree of input and output relaxation, and the input and output will not affect the change of efficiency value. The calculated efficiency value can be further compared.

3.1.2. Basic Model

When studying the relationship between digital finance and SMEs, Chen et al. [66] use a fixed-effects model controlling time and industry factors to study the influence of digital finance on debt financing cost. Bai et al. [42] also use this method to explore the relationship between digital finance and total factor productivity of SMEs. Similarly, Lang et al. [39] use a fixed-effects model controlling time and industry factors to investigate the relationship between digital finance and innovation of SMEs. He et al. [1] also use this method to research the relationship between digital finance and the financing constraints of SMEs. Drawing on previous research, this paper constructs a fixed-effects model controlling time and industry as a way to investigate the study of the impact of digital finance on the high-quality development of SMEs to test Hypothesis 1:

$$H{S}_{it}={\alpha }_0+{\alpha }_{1}D{F}_{it}+{\alpha }_{2}Control{s}_{it}+{\epsilon }_{it}$$

(1)

where HS stands for SMEs’ high quality development index, DF stands for digital financial inclusion development index, Controls stands for control variables, i and t stand for enterprise and time, respectively, α stands for coefficient, and ε stands for residual term.

3.1.3. Mediating Effect Model

To investigate whether there is a mediating effect of financial resource allocation efficiency between digital finance and the high-quality development of SMEs, in accordance with the study of Wen et al. [67], this paper constructs a mediating effect model as a way to test Hypothesis 2.

$$H{S}_{it}={\alpha }_0+{\alpha }_{1}D{F}_{it}+{\alpha }_{2}Control{s}_{it}+{\epsilon }_{it}$$

(2)

$$E{F}_{it}={\beta }_0+{\beta }_{1}D{F}_{it}+{\beta }_{2}Control{s}_{it}+{\eta }_{it}$$

(3)

$$H{S}_{it}={\gamma }_0+{\gamma }_{1}D{F}_{it}+{\gamma }_{2}E{F}_{it}+{\gamma }_{3}Control{s}_{it}+{\zeta }_{it}$$

(4)

where EF represents the efficiency of financial resource allocation, β and γ represent the coefficients, η and ζ represent the residual terms, and the other letters represent the same meanings as above. In addition, in the mediating effect model, α₁ represents the total effect, γ₁ represents the direct effect, and the result of multiplying β₁ and γ₂ represents the mediating effect [67].

3.2. Description of the Data

3.2.1. Dependent Variables

In this paper, we construct the SME high-quality development index (HS) as a dependent variable. The report to the 19th National Congress of the Communist Party of China (CPC) proposed high-quality development for the first time, pointing out that China’s phase of rapid economic growth has turned into high-quality development. The basic criteria of high-quality development evaluation are the five development concepts of “innovation, coordination, green, open and sharing” [25]. Dai and Wang [45] argue that the connotation of high-quality development of SMEs should be based on five major concepts, which are manifested in SMEs as: innovation-driven development; active integration of internal and external resources for synergistic development; provision of safe, reliable and quality-assured products; transparent and open operations; and sharing wealth with employees, customers and stakeholders. Zhang [22] points out that the transformation and upgrading of SMEs require industrial upgrading, product upgrading and output adjustment. Guo [23] points out that the high-quality development of the private economy in the new era should firstly carry out quality changes and promote innovation to achieve quality optimization and upgrading, followed by efficiency changes through organizational and management innovation and optimization of talent allocation to improve management efficiency. Wang and Huang [44] argue that high-quality development requires a target state characterized by sound governance institutions, reliance on innovation-driven development, and outstanding financial performance. Synthesizing existing studies, this paper portrays the index system of high-quality development of SMEs into four dimensions: supply quality, supply efficiency, green supply, and financial quality.

(1) Supply Quality: With product as the basis of the enterprise, product quality is directly related to the development of enterprises [24], so if enterprises want to achieve long-term development, they must be innovative [45]. Innovation, as the source of long-term high-quality development, requires enterprises to improve the technological content of products and services, transform growth momentum, and implement innovation-driven development strategies [44]. Innovation is manifested in two aspects: innovation input and innovation output. Innovation input is manifested in the upgrading of fixed assets and the development of new products, while innovation output is mainly manifested in the upgrading of traditional technology, accelerating the application of new materials, new equipment and new technology, and the value-added of intangible assets as a result of innovation input [21]. Therefore, this paper measures innovation input in terms of R&D input intensity and net intangible assets ratio [68], innovation output [13,69] in terms of the number of patents granted by enterprises and the number of utility patents granted, and innovation input and innovation output in terms of the supply quality of enterprises.

(2) Supply Efficiency: Efficiency improvement is mainly divided into organizational management as well as talent motivation, and effective management is a prerequisite for achieving high-quality enterprise development [23]. At present, most of the SMEs in China are family enterprises, so the control is relatively centralized and prone to the problem of agency competition, and different demands lead to chaotic management, which is not conducive to the long-term development of the enterprise [70]. Talent motivation is conducive to the rapid development of enterprises, emphasizing “respect for God and love for people” and treating employees as partners of the enterprise. At the same time, increasing the proportion of R&D personnel is conducive to the development of core technology [23]. Therefore, this paper measures the degree of separation of power and concentration of equity to measure the organizational management of SMEs, and the ratio of R&D personnel and the ratio of executive compensation to measure the degree of talent motivation of SMEs.

(3) Green Supply: At present, China strongly emphasizes green production and lifestyle, and enterprises actively engaged in green production and environmental responsibility can help improve their image and credibility, reduce information asymmetry, enhance investors’ confidence, and contribute to the high-quality development of SMEs [71]. Secondly, in the process of green production and environmental responsibility, enterprises will also transform their own production technology, try to realize the recycling of production materials, and realize the production process of “cradle to cradle”, which further reduces the production cost by recycling production materials, thus increasing the value of enterprises and indirectly promoting the recycling of production materials, further reducing production costs, thus increasing the value of enterprises and indirectly promoting the high-quality development of SMEs. Therefore, this paper measures the degree of green supply by the degree of environmental responsibility [72], which is divided into whether the pollutant emission is up to the standard, and whether the company has passed the ISO14001 or the ISO9001 certification.

(4) Financial Quality: The financial quality directly reflects the business conditions of the enterprise, and the financial indicators also reflect the comprehensive governance of the enterprise and the quality of products and services from this side [44]. Tobin’s Q value can reflect the overall value and operation of the enterprise. The growth rate of operating income reflects whether the enterprise has the ability of long-term development. Therefore, borrowing ideas from Wang and Huang’s research [44], this paper chooses Tobin’s Q value and the growth rate of operating income to measure the overall financial quality of the enterprise; the specific indicators are detailed in

Table 1. Index system of high-quality development of SMEs.

The Target Layer	Rule Layer	Specific Measure Index	Measure
High-quality development of SMEs	Supply Quality	R&D investment intensity (+)	R&D investment/Revenue
		Proportion of intangible assets (+)	Intangible assets/Total assets
		Number of patents granted (+)	Number of patents granted +1
		Number of practical patents granted (+)	Number of practical patents granted +1
	Supply Efficiency	Separation degree of two weights (+)	The difference between actual control and ownership of a company
		Ownership concentration (−)	Shares held by top 5 shareholders/Total shares
		Ratio of R&D personnel (+)	Number of R&D personnel/Total personnel of the enterprise
		Proportion of executive compensation (+)	Total compensation of top three executives/Company assets
	Green Supply	Environmental responsibility (+)	(Pollutant discharge standard + whether through ISO14001 certification + whether through ISO9001 certification)/3
	Financial Quality	Tobin Q (+)	Company market capitalization/Total assets
		Growth rate of operating income (+)	Current year’s operating profit growth/Previous year’s operating profit growth

, where + represents the positive indicators, − represents the negative indicators, and the data of each indicator are from the CSMAR database.

To avoid subjectivity and retain more original information, the weights of each index are measured by the TOPSIS entropy weighting method in this paper to make the results more objective. The entropy weight method can solve the problem of information overlap between variables and TOPSIS can evaluate the advantages and disadvantages of each observation object [73]. Therefore, drawing lessons from Deng et al. [73], Tao and Xu [74], and Liu et al. [75], this paper combines TOPSIS with the entropy weight method to make the measurement results more reliable. In order to avoid the influence of extreme values, the data need to be standardized first, and the weights of each index are measured as shown in

Table 2. Index weight (unit: %).

Indicators	Weight	Indicators	Weight
R&D investment intensity	7.492%	Ratio of R&D personnel	13.959%
Proportion of intangible assets	5.252%	Proportion of executive compensation	6.329%
Number of patents granted	28.184%	Environmental responsibility	3.101%
Number of practical patents granted	25.194%	Tobin Q	5.035%
Separation degree of two weights	1.007%	Growth rate of operating income	3.187%
Ownership concentration	1.259%

.

3.2.2. Independent Variable

This paper selects the digital finance index (DF) as the independent variable and adopts the Digital Inclusive Finance Index released by Peking University to measure the degree of digital finance development [8], which draws on the research of Liu and Yang [7], Bai et al. [42] and Chen et al. [66]. This index is reasonably compiled and used by many scholars in the research of digital finance, which is reliable and representative [7]. To avoid the problem of overly large indicator values, and drawing on the practice of Lu and Wang [76], this paper divides the digital finance index by 100 and matches the SME quality development index with the processed digital index according to the province to which the enterprise’s office address belongs.

3.2.3. Mediating Variable

This paper selects financial resource allocation efficiency (EF) as the mediating variable. Resource efficiency refers to the effective degree of allocating scarce resources from the departments with lower marginal efficiencies to the departments with higher efficiencies, so as to make them as close to the Pareto optimal state as possible [53]. Some scholars use the degree of capital price distortion to measure the allocation efficiency of financial resources [77,78]. Some scholars use the DEA model to measure financial efficiency [79,80,81,82]. The DEA model has been widely used to calculate the allocation efficiency of financial resources, but the traditional DEA model has the disadvantage of multiple DMU being effective at the same time [65]. Therefore, this paper uses Qu et al.’s research [65] for reference and uses the super-efficiency SBM model to measure the allocation efficiency of financial resources. As for the index of financial resource development, the level of financial intermediary development, and R&D input strength, the output indicators consist of financial output and patent quality, and the specific indicator system is shown in

Table 3. Index system of financial resource allocation.

The Index Type	Evaluation Content	Specific Indicators
Input indicators	Level of financial human resources	Number of financial employees
	The government supports financial development	Government budget expenditure
	Research and development investment intensity composition	Number of R&D investment
		Number of R&D personnel
	The development level of financial intermediation	Balance of loans from financial institutions
Output indicators	Financial output	Added value of financial industry
	Composition of patent quality	Proportion of the number of invention patents granted

. Feng et al. [83] and Shi and Zhao [84] measure the efficiency of financial resource allocation by the ratio of loan balance to gross regional product. Shi [85] takes fixed asset investment and deposit balance of banking institutions as the input index, and gross regional product as the output index. Qu et al. [65] and Tian and Zhang [86] simultaneously take financial resource inputs and scientific and STI outputs into account. Drawing on Tian and Zhang’s approach [54], the input indicators in this paper consist of the level of financial human resources, government support for financial development, the level of financial intermediary development, and R&D input strength; the output indicators consist of financial output and patent quality. The specific indicator system is shown in Table 3.

3.2.4. Control Variables

This paper aims to study the impact of digital finance on the high-quality development of SMEs. Therefore, other important control variables should be taken into account to control for the effects on the independent variables. In this paper, firm size (Size), firm age (Age), operating income (IN), gearing ratio (AR), and cash recovery ratio (CR) are selected as control variables. Firstly, at the very beginning of the life cycle, companies aim to achieve the minimum size that allows them to survive in the market. Size and age are the factors that restrict the growth of SMEs. Referring to the studies of Zhang and Li [86] and Li [87], this paper chooses the year-end assets of SMEs to measure their size, and chooses the years of their establishment to measure their age. Secondly, if the enterprise’s solvency is poor, it will face the risks of bankruptcy and acquisition, which will affect the development of the enterprise [88]. Referring to Du and Chen’s research on enterprise value, this paper chooses asset-liability ratio (AR) and income (IN) to measure the solvency of enterprises. Finally, according to the research of Sun et al. [89], the failure of enterprises to recover cash can lead to debt crisis, which is not conducive to the development of enterprises. Xu [90] also finds that cash recovery reflects the development of enterprises, so the control variable in this paper also includes cash recovery rate (CR).

3.3. Data Source

This paper takes small and medium-sized board listed companies from 2011–2020 as the research sample, excluding ST class enterprises and enterprises with missing data and outliers, for a total of 581 enterprises and 5810 research samples. Among them, the enterprise class data related to the construction of high-quality development of SMEs are from the CSMAR database, the digital finance index is from the Digital Inclusive Finance Index released by Peking University, and the data related to the construction of financial resource allocation efficiency are from the National Bureau of Statistics and China Financial Statistics Yearbook. The variable descriptions are given in

Table 4. Descriptive Statistical Results of Main Variables.

	Variables	Symbols	Mean	Std. Dev.	Min	Max
Dependent Variable	High-quality development of SMEs	DF	0.0691	0.0405	0.0098	0.5317
Independent Variables	Digital Finance	HS	2.4082	1.0139	0.1622	4.3193
Mediator Variable	Efficiency of Financial Resource Allocation	EF	0.8478	1.2945	0.3231	20.242
Control Variables	Size	Size	21.9978	0.9820	18.2756	26.3884
	Age	Age	2.5939	0.4173	0.6931	3.6636
	Income	IN	21.3846	1.1562	17.2727	26.3188
	Asset-liability ratio	AR	0.3844	0.1910	0.0075	2.3940
	Cash-recovery ratio	CR	0.0498	0.0712	−0.7617	0.5327

.

3.4. Correlation Matrix

Table 5. Correlation matrix.

	HS	DF	Size	Age	IN	AS	CS
HS	1.0000
DF	0.4050 ***	1.0000
Size	0.1621 ***	0.3714 ***	1.0000
Age	0.2364 ***	0.2691 ***	0.1571 ***	1.0000
IN	0.0692 ***	0.2843 ***	0.8604 ***	0.1151 ***	1.0000
AR	−0.0380 ***	0.1394 ***	0.4588 ***	0.1013 ***	0.4793 ***	1.0000
CR	0.0473 ***	0.1228 ***	0.0488 ***	0.0888 ***	0.1256 ***	−0.1782 ***	1.0000

Notes: *** imply a significance level of 0.1, 0.05, and 0.01, respectively.

shows the test results of correlation coefficients of each variable. As expected, the high-quality development of SMEs (HS) is positively correlated with digital finance (DF) with a high coefficient (0.4050). In addition, the correlation coefficients between variables all passed the significance test of 1%. Therefore, this study considers that there is no serious multicollinearity problem between the selected variables [91].

4. Empirical Results and Analysis

4.1. Benchmark Regression Results

In this paper, we regress the relationship between digital finance and the high-quality development of SMEs controlling industry and time. The regression results are shown in

Table 6. Regression results.

Variables	Coefficient	Variables	Coefficient
DF	0.0757 *** (2.57)	AR	−0.0731 ** (−2.35)
Size	0.0985 *** (9.07)	CR	0.0501 (0.69)
Age	0.0093 (0.66)	Cons	−3.808 *** (−26.48)
IN	−0.0563 *** (−6.14)
R2	0.3986
Time	YES
Industry	YES

Note: ** and *** represent significance at the level of 5% and 1%, respectively, and the values in brackets are T-values.

. According to Table 6, after controlling for the effects of other factors, the development of digital finance is positively related to SMEs and is significant at the 1% level, indicating that digital finance can significantly improve the level of high-quality development of SMEs, proving the validity of Hypothesis 1. Digital finance can make up for the deficiency of the traditional financial industry with the help of digital technology, reducing SMEs’ resistance to development. It can provide financial support for SMEs to accelerate the application of new skills, achieving innovative development and green development. Among the control variables, the size, age, and cash recovery ratio of SMEs are positively correlated with enterprise quality. SMEs with a larger size and greater age will accumulate corresponding experience, effectively control various unexpected risks, and ensure healthy and sustainable development. Additionally, the cash recovery ratio represents the ratio of net cash flow from operations to total average assets, and a higher cash recovery ratio represents a smaller loss generated by an economic activity. That is to say, there is a greater ability for assets to generate cash, which is beneficial to the development of SMEs. The operating income and asset-liability ratio are negatively correlated with the high-quality development of SMEs. Excessive short-term growth in the operating income of SMEs may be caused by short-term marketing activities, which may be at the expense of cash flow and not conducive to the development of SMEs; and the gearing ratio reflects the degree of risk of enterprise operation. It is not conducive to the high-quality development of enterprises.

4.2. Mechanism Results

This paper uses Sobel to test whether there is a mediating effect of financial resource allocation efficiency between digital finance and the high-quality development of SMEs, and the test results are shown in

Table 7. Mediation effect test results.

Variables	(1)	(2)	(3)
	HS	EF	HS
DF	0.2900 *** (24.81)	0.0451 *** (2.96)	0.2887 *** (24.70)
EF			0.0294 *** (2.92)
Size	0.1063 *** (9.13)	0.0305 ** (2.01)	0.1054 *** (9.05)
Age	0.0610 *** (3.98)	0.0487 ** (2.43)	0.0597 *** (3.88)
IN	−0.0711 *** (7.20)	0.0044 (0.34)	−0.0712 *** (−7.21)
AR	−0.2805 *** (−8.11)	−0.0792 * (−1.76)	−0.2782 *** (−8.05)
CR	−0.0682 (−0.82)	−0.0641 (−0.59)	−0.0663 (−0.80)
Cons	−3.8728 *** (−26.08)	−1.3151 *** (−6.76)	−3.8342 *** (−25.73)
R2	0.1867	0.0105	0.1888
Sobel	0.0013 **
Indirect effect	0.0013 **
Direct effect	0.2889 ***
Total effect	0.2900 ***

Note: *, ** and *** represent significance at the level of 10%, 5% and 1%, respectively, and the values in brackets are T-values.

. According to Table 7, digital finance and the high-quality development of SMEs are positively correlated at the 1% level, i.e., digital finance can promote the high-quality development of SMEs, which is consistent with the findings of the above study [42]. The development of digital finance can significantly improve the efficiency of financial resource allocation. The reasons are as follows. Firstly, with the development of digital finance, the products and types of financial services are greatly enriched, and digital technology has been widely used in various financial services to meet diversified needs and improve the efficiency of financial services. Secondly, the emergence of digital finance solves the problem of the “last mile” in financial services, extending the coverage of financial services and increasing financial inclusiveness. It breaks through the limitations of time and space, which improves the efficiency of financial resource allocation. Finally, digital finance can collect effective information in a diversified and massive way by using new technologies, such as big data and cloud computing, which helps financial institutions identify credit risks, reduce operational risks and the information asymmetry of staff, realizing the precise matching of factors and improving the efficiency of financial resource allocation. According to Table 7, the Sobel intermediary effect test is significant at the 5% level, and for every 1% increase in the degree of digital finance development, the degree of high-quality development of SMEs increases by 0.2900%, of which the direct effect accounts for 0.2889% and the indirect effect accounts for 0.0013%; therefore, there is a partial intermediary effect of financial resource allocation efficiency between digital finance and the high-quality development of SMEs, and digital finance development can promote the high-quality development of SMEs by improving the efficiency of financial resource allocation.

4.3. Robust Regression Results

To ensure the accuracy of the results, this paper uses a bootstrap self-sampling method for testing, and the test results are shown in

Table 8. Robustness test results.

	Coefficient	p-Value
Indirect effect	0.0013	0.059
Direct effect	0.2887	0.000

Note: This test result is the test result of the bootstrap self-sampling method over 1000 repetitions.

. According to Table 8, the direct effect of digital finance on the high-quality development of SMEs is 0.2887, which is significantly positive at the 1% level; the indirect effect is 0.0013, which shows that there is a mediating effect of financial resource allocation efficiency between digital finance and the high-quality development of SMEs, and digital finance can promote the high-quality development of SMEs by improving the efficiency of financial resource allocation.

4.4. Heterogeneity Result

In order to test whether there is heterogeneity in digital finance for the high-quality development of SMEs, this paper conducts heterogeneity tests from property rights, industries and regions, and the test results are shown in

Table 9. Heterogeneity test results.

Variables	Heterogeneity of Property Rights (1)		Regional Heterogeneity (2)		Industry Heterogeneity (3)
	State-Owned Enterprises	Non-State-Owned Enterprise	Eastern Region	Central and Western Regions	Heavy Polluting Industry	Non-Heavy Polluting Industries
DF	0.0371 (0.56)	0.1327 *** (3.90)	0.0127 (0.23)	0.1850 ** (2.09)	0.0481 (1.20)	0.0821 * (1.92)
Size	−0.0381 (−1.42)	0.1290 *** (10.85)	0.1304 *** (10.21)	0.0288 (1.39)	0.1419 *** (10.06)	0.0385 ** (2.27)
Age	−0.1611 *** (−3.91)	0.0427 *** (2.86)	0.0446 ** (2.78)	−0.0955 * (−3.26)	0.0448 ** (2.45)	−0.0405 * (−1.88)
IN	0.0474 * (1.96)	−0.0787 *** (−7.97)	−0.0721 ** (−6.67)	−0.0371 ** (−2.16)	−0.0697 ** (−6.12)	−0.0280 * (−1.84)
AR	−0.2422 *** (−3.04)	−0.0535 (−1.56)	−0.0704 ** (−1.97)	−0.0059 (−0.09)	−0.1491 *** (−3.57)	−0.0646 (−1.39)
CR	−0.0392 (−0.20)	0.0463 (0.59)	−0.0098 (−0.12)	0.2196 (1.49)	0.0276 (0.27)	0.1250 (1.22)
Cons	−2.4592 *** (−6.98)	−4.1344 *** (−25.95)	−4.1938 *** (−24.71)	−2.5586 *** (−8.97)	−4.4768 *** (−23.09)	−3.0265 *** (−14.27)
R2	0.4657	0.3978	0.4019	0.4183	0.3180	0.5048
Time	YES
Industry	YES

Note: *, ** and *** represent significance at the level of 10%, 5% and 1%, respectively, and the values in brackets are T-values.

.

(1) Heterogeneity of property rights. According to Table 9 (1), digital finance is more conducive to the high-quality development of non-state-owned SMEs and is significant at the 1% level because it is more difficult for traditional financial institutions to cooperate with non-state-owned SMEs due to opaque financial information and a lack of collateral assets, as compared to state-owned SMEs. Further, due to the institutional background of China, the government still occupies an important position in resource allocation and state-owned SMEs have the government as an “invisible guarantee”; therefore, in the traditional financial market, the connection between state-owned enterprises and financial intermediaries may be closer and non-state-owned SMEs sometimes face “ownership discrimination” in conducting economic activities. Non-state SMEs sometimes face “ownership discrimination” in their economic activities, which is detrimental to the development of SMEs. Digital finance can rely on digital technology to improve transparency, reduce the information asymmetry of non-state enterprises, and better meet the frequent capital needs of non-state enterprises, which is conducive to the high-quality development of SMEs.

(2) Regional heterogeneity. Due to the different distribution of financial resources in China, this paper classifies SMEs into enterprises in the eastern region and enterprises in the central and western regions based on the common office location of the company. According to the columns in Table 9 (2), the impact of digital finance on the high-quality development of SMEs in the central and western regions is more significant. For the eastern region, the financial market is more developed, financial resources are more abundant, financial efficiency is higher, and the economic environment for SMEs’ development is good. The development of traditional financial business in the central and western regions is lagging behind that of other regions, the number of financial institutions is smaller, and it is difficult to cover the marginal enterprises, so the degree of development of digital inclusive finance can break the time and space restrictions, broaden the scope of services, enrich service varieties, and improve service efficiency. Therefore, the development of digital finance has greater marginal utility for SMEs in the central and western regions, and digital finance can significantly promote the high-quality development of SMEs in the central and western regions’ development.

(3) Industry heterogeneity. At present, China practices green production and lifestyle, carries out supply-side structural reform, reduces low-end and ineffective supply, and accelerates green development; green production is essentially credit rationing based on environmental constraints [92]. To test whether there is industry heterogeneity in the high-quality development of digital finance for SMEs, this paper divides SMEs into heavy polluters and non-heavy polluters according to their industries. According to the National Economic Classification Standard, the heavy polluting industries include extractive industries, food and beverage manufacturing industries, textile and fur manufacturing industries, paper and printing industries, pharmaceutical and other manufacturing industries, petrochemical manufacturing industries, and metal and non-metal manufacturing industries; the remaining industries are non-heavy polluting industries (Appendix A provides the details of industry classification). According to the columns in Table 9 (3), digital finance has a more significant role in promoting the high-quality development of SMEs in non-heavy polluting industries. Compared with traditional finance, digital finance makes it easier to supervise the business activities of SMEs and effectively reduces SMEs’ engagement in highly polluting projects. Secondly, digital inclusive finance itself also represents a policy-oriented approach that inhibits the profit-seeking nature of capital and directs the flow of capital to non-heavy polluting industries, which promotes the development of green production.

5. Discussion

The COVID-19 pandemic has had a severe impact on the global economy and posed a severe challenge to China’s high-quality economic development. China’s SMEs are the basic force of market economy and play an important role in the national economy [3]. However, due to information asymmetry and principal-agent reasons, it is difficult for SMEs to develop and obtain corresponding financial services [1]. The emergence of digital finance improves the traditional financial system [10] and has promoted the development of SMEs [7]. High-quality economic development should be a comprehensive concept [25], so evaluation of the high-quality development of SMEs should be comprehensive. This paper constructs a comprehensive system to evaluate the high-quality development of SMEs. On the whole, this paper finds a positive relationship between digital finance and the high-quality development of SMEs. In the research, we can find that innovation is very important in the high-quality development of SMEs [44]. Therefore, when digital finance improves the development quality of SMEs, their innovation ability will also be improved accordingly. In other words, digital finance may improve firms’ ability to innovate, which is consistent with the research of Nie and Wu [68]. Further, Yu and Dou [93] and Xie and Gao [69] also find that digital finance drives innovation in SMEs. In the management efficiency of SMEs, good enterprise management can allow SMEs, especially family-owned SMEs, to develop healthily [45]. Du [70] believes that digital finance can improve corporate governance. The governance level of SMEs will affect the development quality of SMEs. Last but not least, Zhang and Wang [94] use the DEA-BCC model to measure the operating efficiency of SMEs, finding that digital finance can improve the operating efficiency of SMEs. The operating efficiency is also the comprehensive performance of an enterprise. Therefore, through the above discussion, we believe that digital finance can improve the development quality of SMEs.

In the mediating effect test, we can see that the efficiency of financial resource allocation plays a mediating effect. Digital finance can improve the allocation efficiency of financial resources. The improved efficiency of financial resource allocation alleviates financial distortions (Huang, 2021). The improvement of the efficiency of the allocation of financial resources enables more SMEs to enjoy financial services. That is to say, digital finance alleviates the financing constraints of SMEs [40,41,95]. For a long time, there has been a large economic difference between the eastern region and the central and western regions, with a stunted traditional financial development in the central and western regions. The emergence of digital finance can make up for the deficiencies of the traditional financial industry in the central and western regions, thus promoting the development of SMEs [7]. In addition, Lang et al. [39] believes that digital finance can promote the technological innovation of non-state-owned SMEs. In addition, digital finance has the feature of inclusive benefits, so it can optimize resource allocation and guide capital to flow to enterprises with higher production efficiency, which can optimize the industrial structure and promote the development of environmental protection enterprises [96]. Therefore, compared with heavily polluting industries, digital finance can promote the high-quality development of SMEs in non-heavy polluting industries.

In conclusion, from the above discussion, we can see that digital finance can promote the high-quality development of SMEs.

6. Conclusions and Policy Implications

Because SMEs are the capillaries of China’s real economy, the real economy can only achieve a high-quality transformation if SMEs can develop healthily. Based on the data of 581 listed enterprises in China’s small and medium-sized board from 2011 to 2020, this paper constructs an indicator system for the high-quality development of SMEs and empirically tests the impact of digital finance on the high-quality development of SMEs using a fixed-effects model, Sobel mediated-effects model and a bootstrap self-sampling method. The results show that, firstly, digital finance has a significant promoting effect on the high-quality development of SMEs; secondly, digital finance has a significant promoting effect on improving the efficiency of financial resource allocation, and there is a mediating effect of financial resource allocation efficiency between digital finance and the high-quality development of SMEs, with the conclusion still holding after a test of robustness. Finally, there is heterogeneity between digital finance and the high-quality development of SMEs. From the perspective of property rights, digital finance has a more significant role in promoting the high-quality development of non-state-owned SMEs; with regard to the region, digital finance has a more significant role in promoting the high-quality development of SMEs in central and western regions; and from the standpoint of industry, digital finance has a more significant role in promoting the high-quality development of SMEs in non-heavy polluting industries. Based on the above research findings, this paper proposes the following recommendations.

First, since digital finance can promote the high-quality development of SMEs, we can promote the combination of digital technology and the traditional financial industry and accelerate the reform and innovation of the financial industry, which can improve the service capacity of banks and other traditional financial institutions. The realization of the digital transformation of banks will allow the development of financial products and services suitable for SMEs and lay a foundation for their healthy development.

Secondly, in order to promote the high-quality development of SMEs, we can speed up the construction of financial infrastructure and widely use digital technology, which can improve the accuracy of financial asset pricing and reduce financial friction, improve the efficiency of financial asset allocation and ease the financing constraints of SMEs. The relevant government agencies should improve the relevant regulations of financial supervision to prevent risks and create a favorable institutional environment for improving the efficiency of financial resource allocation.

Thirdly, since digital finance is heterogeneous to the high-quality development of SMEs, the government should make relevant financial policies and infrastructure construction according to local and enterprise conditions. In the development of digital finance in the central and western regions, the government should focus on inclusiveness and expand the coverage of financial services, while in the eastern regions, where traditional financial services are well developed, the government should focus on improving the capacity of financial services and the efficiency of financial resource allocation. Relying on technologies such as big data and blockchain, the government should establish good and close relationships with non-state-owned SMEs and SMEs in non-polluting industries to reduce information asymmetry and lay a foundation for the healthy and sustainable development of SMEs.

However, there are two limitations to this research. First, there is room to improve the sample. At present, this paper adopts relevant data from listed companies on the SME board. However, companies listed on the new third board are also an important part of China’s economy, so we hope to take these companies as research samples in the future. Second, there may be other channels of influence between digital finance and the high-quality development of SMEs. Therefore, we will further explore the possibility of other mediating effects in the future.