The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises

Studies Management and Finance Economics, of Journal 0504-2644 (online): ISSN 0490,-2644 (print): ISSN 5202 November 11 Issue 80 Volume 8.317 Factor: Impact ,06-i11-10.47191/jefms/v8 DOI: Article 8571-7178 No: Page JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7178 The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises Yanita Ella Nilla Chandra1, Titik Purwinarti2, Arif Santoso3*, Riskon Ginting4 1,2,3,4Department of Business Administration, Politeknik Negeri Jakarta, Indonesia ABSTRACT: Access to financing is one of the crucial challenges faced by State-Owned Enterprises (SMEs), especially in developing countries. This study aims to examine the effect of capital structure and access to and barriers to financing on the performance of SMEs. This study also integrates government policy as a moderating variable in the relationship between access to and barriers to financing and business performance. Data were obtained from a survey of SME owners or managers and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings show that capital structure has a positive effect on financial performance. In addition, access to and barriers to financing have a positive effect on capital structure and SME business performance. Finally, this study provides empirical evidence that government policy is an important mechanism in strengthening the relationship between access to financing and improving business performance. This study contributes to the theoretical and practical understanding of how the dynamics of financing and government policy can shape the sustainable performance of SMEs. KEYWORDS: Financial Access; Financial Constraints; Capital Structure; Business Performance; Government Policy I. INTRODUCTION Small and Medium Enterprises (SMEs) play an important role in driving inclusive economic growth, reducing unemployment, and enhancing national competitiveness [1]. In developing countries such as Indonesia, SMEs are one of the catalysts driving the economic system, accounting for approximately 99% of total business units and employing more than 97% of the workforce, as well as contributing more than 60% to the national gross domestic product (GDP). Despite their significant contribution, SMEs still face ongoing challenges, particularly regarding access to external financing. This situation poses a major challenge to SMEs, hindering business development, productivity, and sustainability in the face of market fluctuations [2]. This financing issue is becoming increasingly important in an era of economic uncertainty, where financial flexibility and access to credit determine business continuity and long-term sustainability. Access to financing is not merely an operational necessity, but also a strategic determinant of a company's ability to expand, innovate, and compete. In practice, many SMEs find it difficult to obtain external financing from formal institutions such as banks. The financing gap faced by SMEs often stems from structural constraints, such as inadequate collateral, high perceived credit risk, limited financial literacy, and information asymmetry between SMEs and lenders [3–6]. As a result, SMEs tend to rely heavily on internal funds or informal sources of borrowing, thereby limiting their ability to optimize capital structure decisions [7]. An unbalanced capital structure with minimal external funding has the potential to lead to a lack of investment and reduced operational efficiency, which ultimately affects company performance. Therefore, examining how access to and barriers to financing affect capital structure and business performance is essential to understanding the broader dynamics of SME growth. Previous studies highlight that access to financing and financial constraints are among the key determinants of the capital structure and performance of SMEs [8, 9]. Companies with greater access to financing are able to implement strategies that focus on growth, innovation, and increasing competitiveness. Conversely, companies that face high financing barriers tend to invest less, remain small in scale, and show weak performance results [10]. Furthermore, these conditions in developing countries pose even greater challenges for SMEs, as credit markets are still underdeveloped and risk assessment mechanisms The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7179 remain constrained. In this context, understanding how financing accessibility and financing constraints interact to shape the capital structure and performance of SMEs is becoming increasingly relevant for researchers and policymakers. Government intervention is considered one of the key factors in overcoming SME financing challenges. The government can help reduce financing barriers, mitigate credit risk, and strengthen the SME financing ecosystem through targeted policies and institutional reforms. In Indonesia, several policy initiatives have been implemented to increase financial inclusion for SMEs, including the People's Business Credit (KUR) program, export financing support through the Indonesian Export Financing Agency (LPEI), and various digital financing platforms in the national financial inclusion agenda. Although these initiatives aim to improve access to financing, their effectiveness in moderating the relationship between access and financing barriers and business performance remains questionable in previous literature. Several studies show that government policies can improve company performance by reducing transaction costs and increasing access to credit [11–13]. In addition, well-designed policies can overcome financial constraints and encourage company growth [14]. Thus, evaluating the moderating role of government policy is crucial to assess whether policy interventions actually strengthen access to finance and reduce financing barriers to SME performance. This study is based on the Pecking Order Theory and Resource-Based View (RBV). The Pecking Order Theory states that companies prefer internal financing over external financing due to asymmetric information and high external financing costs [15]. This perspective is particularly relevant for SMEs, as they often face limited transparency and higher risk perceptions, leading to greater reliance on internal capital. On the other hand, RBV emphasizes that financial resources are strategic assets that enable companies to develop capacity, pursue innovation, and maintain competitive advantage [16]. The integration of these two theories provides a comprehensive perspective for understanding how access to funding and funding barriers affect capital formation and business performance, as well as the potential moderating role of government policy interventions. Although there have been studies examining the impact of access to finance and barriers to finance independently, these studies are still limited and have not explored how these factors jointly affect capital structure and business performance, especially under the moderating influence of government policy. Previous studies highlight financing constraints as a major obstacle to the growth of SMEs in developing countries [17, 18]. Meanwhile, other studies have found that access to financing significantly increases profitability and productivity [19]. However, few studies have empirically tested the role of government policy in moderating this relationship [20], especially in the Indonesian context, where policy implementation often varies across regions and sectors. Based on the above discussion, this study aims to analyze the effect of access to and barriers to financing on capital structure and business performance, as well as to examine the role of government policy in moderating the relationship between access to and barriers to financing and business performance in Indonesian SMEs. These findings are expected to contribute to theoretical and practical understanding of how financing dynamics and government policy can shape the sustainable performance of SMEs. This study also offers valuable policy implications for financial institutions and government agencies in designing inclusive and effective financing programs that can encourage SME growth. II. HYPOTHESIS DEVELOPMENT Capital structure is a combination of debt and equity financing of a company, which has a significant impact on its cost of capital and risk profile. An optimal capital structure can minimize the cost of capital and maximize the value of the company [21]. For SMEs, the right level of leverage can boost growth by increasing investment capacity, but excessive debt can increase financial difficulties and reduce performance. Previous studies show that the right leverage can increase profitability and company performance [22]. H1. Capital structure positively influences the performance of SMEs. Access to and barriers in obtaining external financing play an important role in shaping a company's capital structure decisions. According to the Pecking Order Theory, companies prefer internal funds over external financing [15, 23]. However, when internal resources are insufficient, the ability to access external financing becomes significant for maintaining business operations and corporate sustainability. SMEs often face financing constraints due to collateral limitations, asymmetric information, and higher transaction costs [17]. When access to financing improves, companies can optimize their capital structure by balancing debt and equity more effectively. Conversely, severe financial constraints can force companies to rely too heavily on internal financing or debt, resulting in a less-than-optimal capital structure. H2. Access and financing constraints positively influence the capital structure of SMEs. The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7180 Access to adequate financial resources enables SMEs to invest in innovation, technology adoption, and market expansion, thereby improving business performance [16]. RBV states that financial capital is a strategic resource that supports companies in obtaining various other resources to support their operations and competitive advantage [24]. Conversely, financial constraints can hinder such strategic initiatives, resulting in inefficiency, limited scalability, and low competitiveness. Previous studies show that SMEs with better access to credit tend to report higher performance [25]. H3. Access and financing constraints positively influence the performance of SMEs. Government policies play a crucial role in supporting SMEs through credit guarantees, financial inclusion programs, and various other policies. These policies can reduce financial constraints, improve financing schemes, and encourage formal financial institutions to support SME growth [26]. In the context of strong government support, the negative impact of financial barriers on company performance can be reduced, while the positive impact of financial access can be strengthened [27]. Thus, the effectiveness of financing conditions in improving SME performance is closely related to the strength of government intervention through its policies. H4. Government policy moderates the relationship between access and financial constraints and firm performance, such that the relationship is stronger when government support is high. III. METHODS This study uses a quantitative approach with a survey method to collect primary data from SMEs. The study was conducted on SMEs in developing countries, specifically in Indonesia, which often have limited access to financing. The research population consists of SMEs in Jakarta, Bogor, Depok, Tangerang, and Bekasi (Greater Jakarta). A quantitative approach was chosen because it allows for systematic testing between variables and supports generalization of findings in similar contexts. The data was obtained through a structured questionnaire distributed online via Google Forms to SME business owners or managers. Respondents were selected using a non-probability sampling technique with a convenience sampling approach. This method was chosen because it allowed researchers to efficiently reach participants who were willing to provide accurate responses, especially in field conditions where a comprehensive sample frame was difficult to obtain. Although convenience sampling may reduce the level of generalization, this method is widely accepted in exploratory research aimed at specific economic and geographical contexts [28]. The final sample for this study consisted of 140 SMEs. This questionnaire was designed based on a review of relevant literature and previous empirical studies. It includes statements that measure the main constructs in this study, namely capital structure (X1), access to and barriers to financing (X2), government policy (M), and business performance (Y). All constructs are measured using several indicators on a five-point Likert scale, ranging from 1 (Strongly Disagree) to 6 (Strongly Agree), to capture respondents' perceptions consistently. Prior to the main data collection, a pilot test was conducted with several SME owners to ensure that all questions were clear, relevant, and contextually appropriate. Minor adjustments were made to improve the clarity of the wording and the logical flow of the questionnaire. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM–PLS) with SmartPLS 3.0 software. This analysis technique was chosen because it is well suited for studies involving multiple relationships, mediating and moderating effects, and models with small to medium sample sizes [29]. SEM–PLS allows researchers to assess the validity of measurements and structural relationships between variables simultaneously. The analysis was conducted in several stages to test the hypotheses in this study. The model tests the direct influence of capital structure and access to and barriers to financing on company performance, as well as the moderating role of government policy in the relationship between access to and barriers to financing and company performance. The SEM-PLS approach provides a comprehensive understanding of the financial dynamics that influence the capital structure and performance of SMEs, while also illustrating how government policy can moderate this relationship in the Indonesian context. IV. RESULTS AND DISCUSSION Outer Model Test Reliability testing aims to measure the level of consistency and stability of an instrument used in research. With an Outer Loading (λ) value of > 0.70. For Cronbach's alpha (α) and composite reliability (CR) values > 0.70. Furthermore, the AVE value is the ability of the latent variable value to represent the value of the original data. If the AVE value for each construct is > 0.50, then the variable or construct can be considered reliable [30]. The reliability test results can be seen in Table 1. The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7181 Table 1. Validity and Reliability Test Variable Indicators λ α CR AVE Access and Financial Constraints (AHP_X2) AHP1 0.791 0.860 0.899 0.641 AHP2 0.773 AHP3 0.757 AHP4 0.857 AHP5 0.821 Government Policy (KP_M) KP1 0.787 0.819 0.871 0.576 KP2 0.700 KP3 0.726 KP4 0.836 KP5 0.735 Business Performance (KU_Y) KU1 0.790 0.850 0.893 0.625 KU2 0.793 KU3 0.788 KU4 0.809 KU5 0.771 Capital Structure (SM_X1) SM1 0.773 0.799 0.860 0.553 SM2 0.722 SM3 0.723 SM4 0.714 SM5 0.783 Government Policy (KP_M) x Access and Financial Constraints (AHP_X2) KP (M) X AHP (X2) 1.000 Based on Table 1, it can be concluded that all indicators in this study have met the reliability criteria. All outer loading values are above 0.70, meaning that each indicator can represent its construct consistently. Furthermore, the Cronbach's Alpha values for all variables are in the range of 0.799 to 0.860, and the Composite Reliability values range from 0.860 to 0.899 (>0.70). This shows that the indicators used in each construct provide very similar results and support the accurate measurement of variables. Then, the Average Variance Extracted (AVE) value of each construct also meets the requirement of >0.50, which means that the latent variables are able to explain about 50% of the variance of the indicators or statement items. Thus, all constructs in this study can be declared reliable, and all indicators are able to measure the intended variables accurately and reliably. In this study, discriminant validity was also used through cross loading values to assess whether an indicator has a higher correlation with its construct than with other constructs. An indicator is considered valid if the loading value for its original construct is higher than the loading value for other constructs. An optimal cross-loading value is indicated if it exceeds 0.70, which means that the indicator is more accurate in representing its own construct than other constructs. Table 2 shows the cross-loading values. Table 2. Cross Loading AHP (X2) KP (M) KU (Y) SM (X1) AHP1 0.791 AHP2 0.773 AHP3 0.757 AHP4 0.857 AHP5 0.821 KP1 0.787 KP2 0.700 KP3 0.726 KP4 0.836 KP5 0.735 KU1 0.790 The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7182 AHP (X2) KP (M) KU (Y) SM (X1) KU2 0.793 KU3 0.788 KU4 0.809 KU5 0.771 SM1 0.773 SM2 0.722 SM3 0.723 SM4 0.714 SM5 0.783 Based on Table 2, it can be concluded that all indicators have higher cross-loading values for the construct that should be measured compared to other constructs. These results indicate that each indicator is able to represent its construct accurately, thus meeting the criteria for discriminant validity. Thus, all indicators in this study are declared valid for measuring the intended construct. After conducting reliability testing, validity testing was then carried out by looking at several tests, namely the HeterotraitMonotrait Ratio (HTMT) value. HTMT is the ratio of the correlation between measurement items of variables compared to the geometric mean of the correlation between measurement items. To meet the HTMT value requirement for each variable, which is < 0.90, each construct instrument can be declared valid and has good discriminant validity. The results of the HTMT values can be seen in Table 3. Table 3. HTMT test AHP (X2) KP (M) KU (Y) SM (X1) KP (M) x AHP (X2) AHP (X2) KP (M) 0.276 KU (Y) 0.392 0.246 SM (X1) 0.439 0.190 0.540 KP (M) x AHP (X2) 0.135 0.568 0.342 0.199 Based on Table 3, all variables in this study have HTMT values between constructs that are < 0.90. The highest HTMT value in the relationship between the Capital Structure (X1) and Business Performance (Y) variables is 0.540 (< 0.90). This indicates that there are no overlapping issues between constructs in the research model. Thus, all research variables have met the discriminant validity criteria, so that all constructs are declared valid and suitable for use in the next stage. Inner Model Test Based on Table 4, it can be concluded that Hypothesis 1, which states that capital structure positively influences the performance of SMEs, has a t-statistic of 5.157 at a significance level of 5%, so H1 is accepted. Hypotheses 2 and 3, which state that access and financing constraints positively influence the capital structure and performance of SMEs, have t-statistics values of 3.217 and p-values of 0.001, so the hypotheses are accepted. Finally, Hypothesis 4, which states that government policy moderates the relationship between access and financial constraints and firm performance, such that the relationship is stronger when government support is high, has a t-statistic of 3.116 and a p-value of 0.002, so H4 is accepted. Table 5 shows the r-square results. R-square is used to determine how much of the dependent variable can be explained by the independent variables in the research model. This value provides an overview of the strength of the exogenous construct's influence on the observed endogenous construct. The interpretation of the r-square value is divided into three categories, namely ≥ 0.75 indicates a strong influence, around 0.50 indicates a moderate influence, and around 0.25 indicates a weak influence. Table 5 shows that the business performance (KU) variable has an R-square value of 0.412, which falls into the moderate category. This indicates that the Structure Model (SM), Access and Financing Constraints (AHP), and Government Policy (KP) variables are able to predict 41.2% of Business Performance. The remaining 58.8% is influenced by other factors not included in this research model. Meanwhile, the Structure Model (SM) variable has an R-square value of 0.132, which is classified as low. This explains that Access and Financing Constraints (AHP) can only explain 13.2% of the Structure Model, while the remaining 86.8% is explained by other variables outside this research model. Thus, it can be concluded that this research The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7183 model has moderate predictive power in explaining business performance variables, but its predictive power for capital structure variables is low. Table 4. Hypothesis Test Hypothesis β Standard Deviation T Statistics P Value Description SM (X1) -> KU (Y) 0.437 0.085 5.157 0.000 Accepted AHP (X2) -> SM (X1) -> KU (Y) 0.162 0.050 3.217 0.001 Accepted KP (M) x AHP (X2) -> KU (Y) 0.260 0.084 3.116 0.002 Accepted Table 5. R-Square Variable R-square R-square adjusted KU (Y) 0.429 0.412 SM (X1) 0.138 0.132 DISCUSSION This study provides empirical evidence that capital structure has a positive effect on business performance. These findings are consistent with previous theories that companies seek an optimal balance of various sources of financing to minimize costs and maximize company value. For SMEs, appropriate leverage increases investment capacity, profitability, and growth [21, 31]. However, excessive reliance on debt can increase financial risk and reduce returns. These findings imply that SMEs in Indonesia are increasingly able to use debt productively to support business development. These findings are in line with previous studies [22]. The findings reveal that access and financing have a significant positive effect on capital structure, supporting H2. These findings indicate that SMEs with more favorable financing conditions, such as easier access to loans, more flexible collateral requirements, and more flexible loan procedures, tend to adopt a more balanced and growth-oriented capital structure. This is consistent with the Pecking Order Theory, which suggests that companies' financing preferences depend on their ability to access external funds. When external financing becomes more accessible, SMEs are more likely to use debt strategically to expand their business rather than relying solely on internal financing. These results are in line with previous studies by [8, 9]. Further analysis confirms that access to financing has a significant positive effect on business performance. This indicates that SMEs with better access to funding sources show higher growth, profitability, and efficiency. Adequate access to capital allows companies to invest in innovation and market expansion, thereby increasing their competitive advantage [16]. Conversely, limited access or high financial barriers restrict operational flexibility and reduce a company's ability to respond to market opportunities. These findings are consistent with the Resource-Based View (RBV) [32, 33], which emphasizes that financial capital is a strategic resource that enables companies to acquire and develop other valuable resources. These findings are supported by previous studies that also found similar results [25]. This study also provides empirical evidence that government policies significantly moderate the relationship between access to and barriers to financing and business performance. This indicates that strong government support reinforces the positive impact of financing conditions on company performance. In other words, government intervention (e.g., credit guarantee schemes, subsidized loan programs, and regulatory simplification) can help SMEs overcome financial barriers and take full advantage of available funding opportunities. When government policies are effective and inclusive, the relationship between access to financing and performance becomes stronger. The results are consistent with the findings of previous similar studies [27]. CONCLUSIONS This study provides empirical findings that access to and barriers to financing, capital structure, and government policies are dynamically integrated to shape the sustainable performance of SMEs. These findings reinforce the argument that access to financing and optimal financial management are key determinants of company performance, especially in developing countries where credit constraints remain a major obstacle. Furthermore, this study highlights that the effectiveness of access to financing depends not only on factors at the SME level but also on the broader institutional environment created by government policy. These findings have several implications. For policymakers, they underscore the importance of strengthening SME-oriented financial programs and ensuring that financing policies effectively reach SMEs, thereby boosting their business performance. For The Influence of Financial Access and Financing Constraints on Capital Structure and Business Performance: The Moderating Role of Government Policy in Small and Medium Enterprises JEFMS, Volume 08 Issue 11 November 2025 www.ijefm.co.in Page 7184 practitioners, the study emphasizes the need for capital structure management to translate financing opportunities into improved performance. For academics, these findings contribute to the integration of the Pecking Order Theory and ResourceBased View in the context of SME performance in developing countries. REFERENCES 1) Bayraktar M, Algan N (2019) The Importance Of SMEs On World Economies. Int Conf Eurasian Econ 2019 500:56–61 2) Gamage SKN, Ekanayake EMS, Abeyrathne GAKNJ, Prasanna RPIR, Jayasundara JMSB, Rajapakshe PSK (2020) A review of global challenges and survival strategies of small and medium enterprises (SMEs). 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