Supply chain finance, fintech development, and financing efficiency of SMEs in China

Guan, Yamei; Sun, Na; Wu, Sarah Jinhui; Sun, Yuxi Article Supply chain finance, fintech development, and financing efficiency of SMEs in China Administrative Sciences Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Guan, Yamei; Sun, Na; Wu, Sarah Jinhui; Sun, Yuxi (2025) : Supply chain finance, fintech development, and financing efficiency of SMEs in China, Administrative Sciences, ISSN 2076-3387, MDPI, Basel, Vol. 15, Iss. 3, pp. 1-16, https://doi.org/10.3390/admsci15030086 This Version is available at: https://hdl.handle.net/10419/321230 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Supply Chain Finance, Fintech Development, and Financing Efficiency of SMEs in China. Administrative Sciences,15(3), 86. https://doi.org/10.3390/ admsci15030086 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Supply Chain Finance, Fintech Development, and Financing Efficiency of SMEs in China Yamei Guan 1, Na Sun 1,* , Sarah Jinhui Wu 2and Yuxi Sun 3 1 School of Accounting, Nanjing University of Finance and Economics, 3 Wenyuan Road, Xianlin College Town, Nanjing 210023, China; [email protected] 2Gabelli School of Business, Fordham University, 113 West 60th Street, New York, NY 10023, USA; [email protected] 3Graduate School of Arts and Sciences, Columbia University, 109 Low Memorial Library, MC 4306, 535 West 116th Street, New York, NY 10027, USA; [email protected] *Correspondence: [email protected] Abstract: A long-term strategy for China’s national development is to foster the growth of “Specialized, Refined, Niche, and Innovative (SRNI)” small and medium-sized enterprises (SMEs). However, these enterprises often face significant financing constraints due to their high technological input, high human capital input, light asset characteristics, and lack of effective collateral. Supply chain finance, as an important way to combine production and financing, could provide financial services in the real economy by alleviating these constraints of SMEs and improving the quality of credit so as to revitalize supply chain funds. This paper empirically examines the relationship between supply chain finance, fintech development, and financing efficiency using a sample of 757 “SRNI” SMEs in Shanghai and Shenzhen A-shares from 2013 to 2023. The findings reveal that supply chain finance significantly enhances the financing efficiency of “SRNI” SMEs. Moreover, the development of financial technology further amplifies such positive effects. This research contributes to the theoretical understanding of how supply chain finance and fintech impacts the financing efficiency of SRNI SMEs and provides valuable insights for evaluating SME financing efficiency. Keywords: supply chain finance; financing efficiency; financial technology (fintech); small and medium-sized enterprises (SMEs); data envelope analysis (DEA) 1. Introduction China’s Small and Medium-sized Enterprises (SMEs) have contributed significantly to the national economy and social development. Despite their significant contributions and considerable size, SMEs have faced numerous challenges, such as fluctuations in the macroeconomic environment, increasing supply chain uncertainty, and the pressure to reduce excess capacity. These obstacles hinder their transition to a “small but mighty” development model. In light of this developmental context, the Chinese government has instituted a series of policies. One aims to cultivate a group of “Specialized, Refined, Niche, and Innovative (SRNI)” SMEs that have niche markets, possess robust innovation capabilities, and are adept in key core technologies. These entities serve as pivotal conduits, enhancing supply chain resilience and competitiveness. “Specialized, Refined, Niche, and Innovative” (SRNI) small and medium-sized enterprises (SMEs) embody four key characteristics: specialization, refinement, uniqueness, and innovation. “Specialized” refers to a focus on specialized development and niche markets, dedicating efforts to specific product applications. “Refined” emphasizes precision Adm. Sci. 2025,15, 86 https://doi.org/10.3390/admsci15030086 Adm. Sci. 2025,15, 86 2 of 16 and excellence in enterprise management, providing high-quality products and services. “Niche” highlights the distinct advantages of technology, processes, and products, showcasing regional characteristics and functional uniqueness. “Innovative” underscores strong innovation capabilities, adopting diverse and creative production methods, increasing investment in innovation, and enhancing overall innovation capacity. However, the “SRNI” SMEs, characterized by their high technological and human capital inputs and asset-light attributes, face challenges in a number of ways. In terms of financing channels, SMEs primarily rely on credit loans and internal financing to address their funding shortages. However, these financing channels are relatively narrow and cannot fully meet the financing needs of SMEs. To mitigate the risks associated with fund delegation, fund providers must invest significant human, financial, and material resources to assess the financial status, creditworthiness, and market prospects before extending funds. Even after providing the funds, additional resources are required to monitor how the funds are utilized. This process leads to increased transaction costs, resulting in higher financing costs for SMEs. As for credit scale discrimination, larger financial institutions have a tendency to prioritize financing services for larger enterprises, while SMEs often encounter limited access to finance from commercial banking institutions. Similarly to credit scale discrimination, the distinctive characteristics of China’s socialist market economy leads to financing biases due to differences in property rights between borrowers and lenders. It is easier for state-owned enterprises to obtain credit from financial institutions than private enterprises (such as SMEs). Consequently, in order to achieve the sustainable development of “SRNI” SMEs, it is imperative to identify a suitable “engine”, leveraging financial support to alleviate the technological innovation bottleneck and technological innovation to address the financing. Supply chain finance, a means of integrating production and financing, offers a potential solution. It is a financing model in which financial institutions, based on supply chain partnerships, provide financing, settlement, and other comprehensive financial services for their upstream and downstream enterprises around the core enterprises. The model aims to meet the capital demand and risk management needs of all parties in the supply chain. It has the potential to assist companies in enhancing their cash flow efficiency and addressing issues related to payment, financing, and credit risk across all segments of the supply chain. In academia, supply chain finance has garnered significant attention due to its capacity to alleviate the financing constraints experienced by SMEs. It has been shown to enhance the quality of credit, thereby revitalizing supply chain funds and facilitating the delivery of financial services to the real economy (Song et al.,2016). There are many examples of using supply chain finance to address the financing challenges of SMEs. For example, a supply chain finance model led by Ant Group, in collaboration with MYbank and China Continent Property and Casualty Insurance, involves leading supply chain companies such as Mengyang Group, Kerchin Cattle Industry, and Yiguo Fresh. It provides supply chain financial services ranging from loans to sales for upstream large-scale breeding enterprises and downstream agricultural material sales enterprises, significantly improving the financing efficiency of the entire supply chain partners (Y. Wang & Mao,2019). While the previous case shows the promising role of supply chain finance, the purpose of this study is to empirically investigate the relationship between supply chain finance and financing efficiency using a larger dataset, particularly in a sample of “SRNI” SMEs. In addition, this study explores the role of financial technology in such a relationship. Data from 757 listed “SRNI” SMEs in Shanghai and Shenzhen A-shares from 2013 to 2023 are used in a panel data analysis to test the corresponding hypotheses. The findings indicate that implementing supply chain finance can substantially enhance the financing Adm. Sci. 2025,15, 86 3 of 16 efficiency of “SRNI” SMEs. Furthermore, this study suggests that advanced regional fintech positively moderates the effect of supply chain finance and financing efficiency. This conclusion remains consistent after conducting an endogeneity test, ensuring the robustness of the findings. The results offer a promising solution to the survival and success of SMEs. It not only enriches the theoretical research on the impact of supply chain finance on the financing efficiency of SMEs but also generates crucial policy implications and guidance on the sustainable development of “Specialized, Re-fined, Niche, and Innovative” SMEs. The remainder of this paper is organized as follows. Section 2provides a relevant literature review on this topic. Section 3contains the theoretical development of the hypotheses. Section 4describes the methodology, while Section 5presents the analysis and results. Section 6concludes this study with contributions, implications, and limitations. 2. Literature Review 2.1. Supply Chain Finance The core objective of supply chain finance is to optimize the capital flow mechanism among enterprises by leveraging solutions offered by financial institutions and technical service providers. From the perspective of the entire supply chain, it enhances the management of capital flow and drives the rapid development of industrial supply chains through financial business innovation and advanced management tools. The research focus of supply chain finance literature primarily concentrated on the micro level of enterprises, encompassing the following three dimensions. First, existing studies primarily focus on analyzing the economic effects of supply chain finance to evaluate its effectiveness in alleviating financing constraints. For instance, L. Wang and Hu (2018) incorporated elements such as industry–finance integration and strategic commitment into the comprehensive analysis system of supply chain finance and corporate financing constraints. Their results reveal that supply chain finance has a significant negative effect on financing constraints of enterprises, meaning it effectively alleviates financing constraints. Additionally, both industry–finance integration and strategic commitment play a significant positive moderating role in the relationship between supply chain finance and the financing constraints of enterprises. In studying how supply chain finance enhances financing effectiveness, scholars have conducted in-depth analyses of its specific impact on financing cost and financing efficiency of SMEs from both qualitative and quantitative dimensions. Based on social network theory, X. Li et al. (2020) constructed a theoretical model examining the relationship between sustainable supply chain finance, environmental regulation, and financing effectiveness. They empirically validated this model using survey data from 386 SME executives. The results indicate that sustainable supply chain finance significantly contributes to the financing effectiveness of SMEs across all three dimensions: economic, social, and environmental. Second, some studies have explored the risk control mechanism of supply chain finance. The execution of financial credit business is often accompanied by risks, and its transferable, dynamic, and complex nature may expose the financing system of supply chains to uncertainty. Su and Lu (2015) employed cluster analysis to classify companies into different levels and introduced an adaptive weight formula for each level based on the number and degree of attention to that level while considering the characteristics of corporate supply chain networks. They found that the enterprise-level credit risk assessment with higher attention carries a greater weight in the overall credit risk assessment of the supply chain system, thereby exerting a more significant impact on the supply chain. Building on the general framework of supply chain risk management, Song and Yang (2018) approached the risk management problem of supply chain finance from three Adm. Sci. 2025,15, 86 4 of 16 dimensions—structure, process, and elements—to effectively address various sources of risks and achieve desired financing performance. Wan (2008) found that the risk mitigation mechanisms integral to supply chain finance are susceptible to failure through an examination of the risk model associated with accounts receivable financing. They emphasized the need for banks to establish a new type of cooperative relationship with the core enterprises and leverage their respective strengths to fulfill the role of supply chain finance. Third, some of the literature explores the operational strategies of supply chain finance, including financing strategies, transaction strategies, inventory management strategies, and production strategies. Among them, numerous studies consider the interplay of production decisions, inventory decisions, transaction decisions, and financing decisions within the context of dual supply chain finance constraints. From the perspective of external financing, Buzacott and Zhang (2004) highlighted the importance of production and external financing decisions to the business environment by incorporating a financing element into the production decision and modeling the available cash in each period as a function of assets and liabilities. Yan and Sun (2011) investigated the optimal warehouse receipt pledge financing strategy for capital-constrained retailers within supply chain finance systems under demand uncertainty. Through numerical examples, they analyzed the effects of varying credit limits of retailers on the optimal strategy of the supply chain finance system and concluded that the limited credit limit financing scheme can motivate the supply chain finance system to increase order quantities and provide effective financing incentives for risk-taking retailers. 2.2. Efficiency of Corporate Finance In the context of enterprise financing efficiency, scholars have not yet provided a clear and unified definition of the efficiency of corporate finance. Research has mainly focused on the relationship between financing methods and enterprise performance. Klapper et al. (2002) argued that the choice of financing methods—equity, bonds, or endogenous—results in different financing costs, which, in the long run, will affect the enterprise’s future financing efficiency. Jain and Kini (1994) found that there is a significant decline in the operating performance of enterprises following initial public offering, indicating a general inefficiency in equity financing. Bradford and Chen (2004) studied the financing efficiency of science and technology SMEs, concluding that financing through loan guarantees is more efficient than direct loans provided by the Chinese government. Xiao and Ma (2004) believed that financing efficiency includes transaction efficiency and allocation efficiency. They emphasized that investors should be able to obtain financial resources at the lowest cost while utilizing limited resources for optimal production. Zhang and Zhao (2015) further refined the concept of financing efficiency, defining it as the ability of an enterprise to secure financial capital with the optimal benefit–cost ratio and the lowest risk during financing activities. Factors affecting corporate financing efficiency can be categorized into macro and micro factors. Macro-level factors include the economic environment, political environment, information environment, financial environment, and so on. Xiong et al. (2011) concluded that the development of strategic emerging industries is significantly influenced by the macroeconomic environment, and the factors affecting financial support efficiency exhibit stage-specific characteristics: emerging industries related to low-carbon technologies achieved better financial support efficiency, while the high-end equipment manufacturing sector faced challenges in this regard. They concluded that the better the macroeconomic situation is, the higher the efficiency of financial support the industry receives from the financial market. On the micro-level, firm-specific factors such as financing structure, Adm. Sci. 2025,15, 86 5 of 16 firm size, governance structure, profitability, and solvency also play significant roles in determining financing efficiency. S. Wang (2014) argued that state-owned enterprises (SOEs) are comparatively less efficient in financing than privately owned and foreign-invested firms. Cui et al. (2014), based on the construction of the financing efficiency calculation model, utilized financial data from non-listed SMEs to conduct a dynamic factor panel data model analysis, comprehensively examining the factors influencing the financing efficiency of non-listed SMEs. Their findings revealed that the company’s intrinsic quality and core business conditions have a significant impact on its profitability, the short-term exogenous debt funding sources, their size and liquidity, and the company’s solvency capacity generally play crucial roles. However, the effect of commercial credit financing costs was found to be insignificant. 2.3. Financial Technology In the 1990s, the term “financial technology” was first mentioned by the Chairman of Citigroup (X. Li et al.,2020). Through continuous enrichment and expansion by academia and industry, financial technology (fintech) has been defined as technology-driven financial innovation. Specifically, it refers to financial innovation that leverages cutting-edge technologies to facilitate information exchange between banks and enterprises, transform the delivery of financial products and services, and foster new business models (X. Li et al.,2020) . The application of emerging technologies in the financial sector has effectively reduced information asymmetry in financial markets, streamlined traditional financial service processes, and lowered financing risks and transaction costs (Goldstein et al.,2019). The impact of fintech on supply chain finance and financing efficiency can be argued in a number of ways. First, fintech affects the efficiency of industry–finance integration. From the industry side, Chod et al. (2020) proposed that fintech can enhance the authenticity and transparency of information related to the business flow, logistics, and capital flow of small and medium-sized enterprises in the supply chain. This helps financial institutions, such as commercial banks, recognize their development potential, thereby increasing financing accessibility and enhancing financing efficiency. From the capital side, Berger and Udell (2006) argued that fintech enables banks to gather more comprehensive “soft” information, improve the efficiency of credit assessment, and boost financing efficiency. Second, fintech influences the way financial services are delivered. X. Wang (2015) believed that fintech has driven the development of credit business towards batch processing, intelligence, and intensification, significantly reducing the application and approval processes, thereby improving the efficiency of bank-enterprise credit handling. Huang et al. (2020) proposed that fintech significantly reduces the transaction and processing costs for banks to provide financial services to SMEs; this helps SMEs reduce financing costs, thereby enhancing the level of supply chain financing. Finally, fintech influences risk prevention and control capabilities. Emerging technologies such as big data, cloud computing, and blockchain facilitate information sharing and collaborative development among multiple entities in supply chains. This effectively reduces information asymmetry, lowers credit risks for banks, and improves the accessibility of supply chain financing. Sutherland (2018) investigated how credit reporting affects firms’ access to credit and how lenders engage with them. The findings highlight the mixed effects of fintech-driven transparency enhancements on credit availability. 2.4. Research Gaps The review of the literature shows at least a few gaps. First, content-wise, existing studies predominantly concentrate on supply chain finance models, their influence on operational efficiency, and their role in mitigating financing constraints. However, there Adm. Sci. 2025,15, 86 6 of 16 is a notable gap in the quantitative analysis of how supply chain finance affects financing efficiency. This study addresses this gap by utilizing the Data Envelopment Analysis (DEA) model to quantify financing efficiency and employing linear regression to directly measure the extent of this impact. Second, in terms of the research subject, existing research often involves a wide range of complex subjects, which unavoidably brings in company-specific noises and may contaminate the results. This study narrows its focus to a specific type of enterprises—“Specialized, Refined, Niche, and Innovative” (SRNI) SMEs. Such enterprises are characterized by their high technological content, significant human capital investment, and light asset structure, making their financing challenges more prominent and pertinent to contemporary issues. Third, existing studies have shown that fintech can enhance supply chain finance’s transparency, efficiency, and security, thereby better-serving SMEs. This paper further explores the “catalytic role” of fintech in supply chain finance, optimizing various aspects of supply chain finance through technological innovation, thereby more effectively addressing the financing challenges faced by SMEs. 3. Theoretical Development of Hypotheses 3.1. Supply Chain Finance and Financing Efficiency Financing efficiency is the result of the combined impact of capital input and output, which is specifically affected by the cost of capital acquisition and the efficiency of capital utilization. “Specialized, Refined, Niche, and Innovative” SMEs have to bear higher financing costs due to their inherent weakness, small scale, information asymmetry, and other vulnerabilities. Therefore, they often struggle to secure the necessary funds, leading to low financing efficiency. This, in turn, impedes their research and development (R&D) efforts and negatively affects their long-term sustainable development. In terms of capital investment, supply chain finance addresses the issue of high financing costs for “SRNI” SMEs in the following three aspects. First, supply chain finance uses the core enterprise as a guarantor for SMEs, enabling them to secure financing. This approach effectively mitigates the financing difficulties of SMEs due to poor credit conditions while maintaining much flexibility. Second, supply chain finance extends its services to multiple enterprises within the supply chain. Such system integration increases information transparency, fosters greater cooperation among enterprises, and reduces risks throughout the financing process. Third, supply chain finance is an effective financing mechanism that can significantly reduce the high risk of default due to information asymmetry. Rooted in actual trade activities, it extends credit evaluation to the whole supply chain process, takes into account the actual needs of enterprises, monitors the circulation of goods, and allows financial institutions to participate in the utilization of funds directly. Therefore, the introduction of supply chain finance into the entire supply chain can reduce the cost of obtaining funds and alleviate the financing difficulties for “SRNI” SMEs. From the output perspective, supply chain finance, grounded in self-paying and closed-loop capital operations, can effectively control risks and improve the efficiency of capital utilization by coordinating financial and industrial resources. In addition, supply chain finance forms an open information-sharing model through a long-term partner cooperation network. It provides dynamic data change prediction and accelerates the flow of information, capital, and other elements between upstream and downstream enterprises. Not only does the model optimize supply chain operations, but it also boosts the innovation performance and product market competitiveness of “SRNI” SMEs, thereby creating a multiplier effect between industrial and financial benefits. According to these arguments, supply chain finance enables “SRNI” SMEs to improve the efficiency of capital mobilization by reducing the marginal cost of financing while promoting the efficient utilization of integrated capital. Accordingly, we propose the following hypothesis. Adm. Sci. 2025,15, 86 7 of 16 H1. The development of supply chain finance can promote the financing efficiency of “Specialized, Refined, Niche, and Innovative” SMEs. 3.2. The Role of Fintech Against the backdrop of the rapid development of digital technology, fintech is transforming the management and operation mode of the financial industry. Empowered by cutting-edge technologies such as cloud computing, big data, and mobile information technology, fintech has overhauled the traditional financial services industry all around, restructuring and optimizing the traditional financial business, and providing more convenient, efficient, and secure financial services (Buchak et al.,2018). First of all, by leveraging emerging technologies, fintech can help financial institutions gain a more comprehensive understanding of the business situation and creditworthiness of enterprises, which is more conducive to integrating the situation of upstream and downstream enterprises in the supply chain and promoting the development of supply chain finance. Second, with the help of emerging technologies, fintech can break through the spatial limitations of the traditional financial sector and increase the supply of funds in the credit market. Fintech provides a wider range of financial products and services to enterprises in different regions through cross-regional financing platforms, thus expanding enterprises’ financing channels. Easing the constraints of enterprises in the financing process creates better conditions for the development of supply chain finance and further promotes the development of financing efficiency of “SRNI” SMEs. Finally, financial technology’s intelligent and informative functions can also help financial institutions supervise the use of enterprises’ post-loan funds, improve the efficiency of post-loan supervision, and reduce moral risks. In conclusion, developing financial technology can reduce the financing cost of “SRNI” SMEs and improve their financing efficiency. Based on this, we put forward the following hypothesis: H2. Fintech development positively moderates supply chain finance and the financing efficiency of “Specialized, Refined, Niche, and Innovative” SMEs. 4. Methodology 4.1. Sample Selection and Data Sources Since the Ministry of Industry and Information Technology (MIIT) first issued the “Guiding Opinions on Promoting the Development of ‘SRNI’ SMEs” in June 2013, we set 2013 as the starting year of the development of “SRNI” SMEs. Using the list of “Specialized, Refined, Niche, and Innovative” enterprises published by the MIIT from 2014 to 2024, we filtered out the listed companies and generated a sample of 1193 SRNI small and mediumsized enterprises listed on the Shanghai and Shenzhen A-shares from 2013 to 2023. To ensure the sample was relevant and meaningful to our research questions, we further excluded companies in the financial industry, those with an ST trading status in the current year, those listed for less than one year, and those with missing financial data. This left us with a final sample of 757 listed companies, comprising 4717 observations over 10 years. The data in this paper primarily comes from the China Stock Market and Accounting Research Database (CSMAR) database. The CSMAR Database is a comprehensive and authoritative financial database designed to support academic research and practical analysis in the fields of economics, finance, and accounting. CSMAR is widely used by researchers, analysts, and institutions globally due to its extensive data coverage, accuracy, and reliability (He et al.,2022). The database includes detailed financial statements, stock Adm. Sci. 2025,15, 86 8 of 16 market trading data, corporate governance information, and specialized datasets such as supply chain finance, ESG metrics, and more. The fintech data in this paper is sourced from the Peking University Digital Inclusive Finance Index (PKU-DFI). The PKU-DFI is a comprehensive and influential index developed by the Institute of Digital Finance at Peking University in collaboration with Ant Group. It measures the development and accessibility of digital financial services across China, focusing on promoting financial inclusion through technology. This paper uses the provincial level fintech index. 4.2. Research Model and Variable Measurements Panel data analysis is conducted using the fixed effect estimation method (analyzed with STATA). The fixed effect model can control for time-invariant individual-specific characteristics (such as corporate culture, geographic location, etc.), thereby reducing omitted variable bias and improving the accuracy of estimation results. Additionally, STATA provides robust standard errors to effectively address issues of heteroskedasticity and autocorrelation. Model 1 is used to test research H1: the relationship between supply chain finance (SCF) and financing efficiency (Fineff) of “SRNI” SMEs. Fine f fi,t=β0+β1SCFi,t+ΣβjControli,t+γi,t+ηi,t+εi,t(1) Model (2) introduces moderating variables to test H2: the moderating effect of fintech (FinTech) development on the relationship between supply chain finance and the financing efficiency of “SRNI” SMEs: Fine f fi,t=β0+β1SCFi,t+β2FinTechp,t+β3SCFi,t×FinTechp,t+ΣβjControli,t+γi,t+ηi,t+εi,t(2) in which ifor SME, tfor year, pfor province, γi,t industry fixed effects, ηi,t year fixed effects, and εi,trandom error terms. There are three common measurement methods for the dependent variable—financing efficiency (Fineff): (1) fuzzy evaluation method and entropy value method; (2) single ratio method; and (3) data envelopment analysis (DEA) method. We chose to use DEA method for two reasons. DEA is a non-parametric method for evaluating the relative efficiency of decision-making units (DMUs) with multiple inputs and outputs. By employing linear programming, DEA constructs an efficient frontier, which serves as a benchmark for comparing the performance of each DMU. The DEA model avoids errors caused by inappropriate functional form assumptions and allows for cross-sectional comparisons of financing efficiency across firms with different scales and units (Zhang et al.,2020). In addition, the DEA approach has been widely used to measure financing efficiency (Sun et al.,2023; Yang et al.,2023). Drawing on the research of F. Li and Wang (2014), we used DEAP 2.1 (a DEA APP) to calculate the annual financing efficiency of enterprises, with efficiency scores ranging between 0 and 1. The input indicators include total assets, asset–liability ratio, and main business costs, while the output indicators include return on net assets, total asset turnover, and operating income growth rate. The independent variable in this paper is supply chain finance (SCF). The measurement of supply chain finance follows the study of Liu et al. (2024). We adopt micro-level continuous proxy variables at the enterprise level and use the sum of short-term borrowings, notes payable, and accounts payable as a proportion of total assets as a proxy for supply chain finance. This measurement is chosen because the “financial attributes” of supply chain finance are primarily reflected in short-term financing tools for supply chain transactions, which alleviate financing constraints for SMEs through short-term borrowings. Meanwhile, Adm. Sci. 2025,15, 86 15 of 16 Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The original data presented in the study are openly available in China Stock Market & Accounting Research Database (https://data.csmar.com/) and Peking University Inclusive Finance Index (https://idf.pku.edu.cn/index.htm). 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