Optimizing Intellectual Capital And Msme Credit To Enhance Rural Bank Performance: Evidence From Jambi Province, Indonesia

Optimizing Intellectual Capital And Msme Credit To Enhance Rural Bank Performance: Evidence From Jambi Province, Indonesia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing Intellectual Capital And Msme Credit To Enhance Rural Bank Performance: Evidence From Jambi Province, Indonesia Iwan Eka Putra, Ermaini, Etik Winarni, Syahmardi Yacob This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5845202/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the impact of Intellectual Capital and MSME credit on the performance of rural banks in Jambi Province, Indonesia, focusing on how these factors drive business growth. Using Panel Data Regression analysis, the research applies three models—the Pooled Least Square (PLS), Common Effect Model (CEM), and Random Effect Model (REM)—to analyze data from rural banks. Results reveal that both Intellectual Capital and MSME credit significantly influence rural bank performance, both individually and collectively. Specifically, Intellectual Capital fosters operational improvements by enhancing the capabilities and professionalism of human resources, while MSME credit supports business growth within these institutions.This study focuses solely on rural banks in Jambi Province, which may limit the applicability of findings to other regions or types of banks. Additionally, the use of cross-sectional data restricts causal inferences. Future research could expand geographically and utilize longitudinal data to explore trends over time.The findings highlight the need for rural banks to invest in human resource development and strategically allocate MSME credit to enhance competitiveness. Policymakers and bank management can leverage these insights to strengthen rural banking performance.By emphasizing the role of rural banks in supporting MSMEs, this study underscores the positive socioeconomic impact of improving credit access in rural communities. Strengthening rural banks can foster local entrepreneurship, reduce financial exclusion, and stimulate regional economic development. This study offers new insights into the combined influence of Intellectual Capital and MSME credit on rural bank performance in Indonesia, particularly in Jambi Province. It is one of the first studies to explore these factors in the context of rural banking, contributing valuable knowledge to the field. Management Finance Intellcetual Capital MSME Loans Rural Bank Business in Jambi Province Figures Figure 1 1. INTRODUCTION Banks, as financial institutions, play a fundamental role in the economy by collecting deposits from the public and redistributing them to third parties, thereby providing payment liquidity services. This core function of banks as aggregators and distributors of public funds is critical for supporting national development, promoting equitable growth, and enhancing economic stability, all of which contribute to an improved standard of living (Bank Indonesia, 2010 ; Levine, 2005 ; World Bank, 2021 ). The Indonesian banking sector is, therefore, vital for enabling economic indicators to improve and thrive, as the economy cannot grow sustainably without the support of financial institutions (Beck et al., 2000 ). This is particularly true for rural banks, which must actively capture market share to remain competitive against both bank and non-bank financial institutions. In the face of rapid global economic shifts and technological advancements, rural banks must innovate continually to stay relevant. Developing strong, healthy, and competitive institutions capable of serving the community—especially Micro, Small, and Medium Enterprises (MSMEs)—is essential for their survival (CGAP, 2011 ). However, the challenges faced by rural banks are mounting, with intensifying competition from commercial banks and government programs like the People's Business Credit (KUR), which offers low-interest loans to MSMEs through commercial banks. This policy has increased the difficulty for rural banks to grow, as commercial banks are mandated to allocate at least 20% of their total credit to MSMEs, effectively pushing them into this market space (Johannes, 2019 ; OJK, 2022). In addition to competition, the large number of rural banks operating nationally—1,441 as of 2022 (OJK, 2022)—creates a crowded marketplace, especially within the micro-lending sector. To endure these challenges, rural banks must improve their professional capabilities, with a focus on enhancing Intellectual Capital. Intellectual Capital, as defined by Stewart ( 1997 ), includes intellectual materials that have been formalized, captured, and leveraged to generate higher-value assets. Sidharta ( 2020 ) emphasizes that Intellectual Capital comprises knowledge assets such as stakeholder relationships and human resources, which can add significant competitive value. Recognized as a cornerstone of organizational competitiveness in the 21st century (Huan, 2020 ; Edvinsson & Malone, 1997 ), Intellectual Capital could serve as the foundation for stabilizing rural banks amidst their ongoing decline. According to OJK data, the number of rural banks has been consistently decreasing from 2018 to 2022. This trend highlights the pressing need for rural banks to bolster their competitiveness and adapt strategically to secure their place within the financial ecosystem (OJK, 2022). Table 1 Development of the Number of Rural Banks (Growth of Total Rural Banks) Indicator 2018 2019 2020 2021 2022 Number of Rural Banks 1.597 1.545 1.506 1.468 1.441 Progress (%) - -3.26 -2.52 -2.52 -1.84 Source: Financial Services Authority (OJK) and Processed The data in Table 1 highlight a consistent national decline in the number of rural banks, with a downward trend in their total count from 2018 to 2022. In 2018, there were 1,597 rural banks, which dropped to 1,545 in 2019, reflecting a decrease of 3.26%. This decline continued into subsequent years: 1,506 banks in 2020 (a 2.52% decrease), 1,468 in 2021 (another 2.52% decrease), and finally 1,441 in 2022 (a 1.84% decrease). This pattern indicates a persistent contraction in the rural banking sector, marked by closures and bankruptcies that raise significant concerns about the sustainability of rural banks. Despite these institutions’ role in supporting MSMEs, their numbers continue to dwindle, sparking questions about the underlying challenges these banks face. In contrast, rural banks in Jambi Province present an intriguing anomaly. Although only 18 rural banks are spread across various cities and regencies in Jambi, several key performance indicators—such as Total Assets and Third-Party Funds—show a positive trajectory, countering the national decline in rural bank numbers. This suggests that while the national rural banking sector faces systemic challenges, rural banks in Jambi are achieving performance gains, pointing to potentially unique factors in this region that warrant closer examination. The following indicators provide a detailed overview of the performance achievements of rural banks in Jambi Province, highlighting a phenomenon that may offer insights for improving the resilience and sustainability of rural banks nationally. Table 2 Rural Bank Performance Achievement Indicators in Jambi Province (In Billion) Indicator 2018 2019 2020 2021 2022 Total Assets 909 1047 1091 1197 1261 Progress (%) - 15.18 4.20 9.72 5.35 Third Party Funds 654 766 788 875 894 Progress (%) - 17.13 2.87 11.04 2.17 Source: Financial Services Authority (OJK) and Processed The data in Table 2 reveal a steady growth in total assets for rural banks in Jambi Province from 2018 to 2022, indicating a resilient performance despite external challenges. In 2018, total assets stood at Rp. 909 billion, which rose to Rp. 1,047 billion in 2019—a significant 15.18% increase. This growth trajectory continued into 2020, with total assets reaching Rp. 1,091 billion, an additional 4.20% rise, even amidst the economic uncertainties of the COVID-19 pandemic. The upward trend persisted in 2021, with assets totaling Rp. 1,197 billion, marking a 9.72% increase, and in 2022, assets further expanded to Rp. 1,261 billion, reflecting a 5.35% rise. This asset growth aligns with an increase in third-party funds (DPK), which also showed steady growth over this period. In 2018, DPK totaled Rp. 654 billion, which rose by 17.13% to Rp. 766 billion in 2019. This upward trend continued in 2020, with DPK reaching Rp. 788 billion, a 2.87% increase, followed by another rise to Rp. 875 billion in 2021 (11.04%) and Rp. 894 billion in 2022, marking an additional 2.17% increase. This pattern is particularly noteworthy as it presents a contrasting phenomenon: while the number of rural banks nationally continues to decline, rural banks in Jambi Province show robust growth in key performance indicators like total assets and DPK. This discrepancy raises compelling questions about the unique conditions or strategies in Jambi Province that may be driving these positive outcomes. In response to this intriguing phenomenon, this study aims to investigate the factors influencing rural bank performance in Jambi, focusing specifically on the roles of Intellectual Capital and MSME credit. The research seeks to understand and analyze how these factors contribute to the business sustainability and competitive positioning of rural banks in this region. 2. LITERATURE REVIEW Rural Bank Business Generally, businesses produce goods and services for profit. For banks, profit orientation is essential for sustaining operations, making profitability a key factor in their long-term viability (Alhassan & Asare, 2021 ). Similarly, rural banks must operate effectively and efficiently to achieve their primary goal of maximizing profits. To support business growth, rural banks need strategic policies encompassing their vision, mission, governance, risk management, competitive positioning based on assets or geographic location, and lending strategies tailored to micro, small, and medium enterprises (MSMEs). These strategies align with the guidelines specified in the Financial Services Authority’s Circular Letter No. 52/SEOJK.03/2016 on the Business Plans of Rural Banks (Business & Credit, 2016 ). The effectiveness of rural bank operations is frequently assessed through the CAMEL framework, which evaluates Capital, Assets, Management, Earnings, and Liquidity. This analysis is crucial for gauging efficiency, where efficiency can generally be understood as the ratio or comparison of input to output, representing the bank’s capability to convert resources into profitable outcomes (Irawan &Widyastuti, 2019 ). According to Riady ( 2006 ), assessing a bank’s health involves evaluating financial statement conditions based on standards set by regulatory authorities. For rural banks in Indonesia, these standards are defined in Financial Services Authority Regulation No. 3/POJK.03/2022 on the Health Level of Rural Banks and Sharia Financing Banks, ensuring that rural banks maintain financial stability and meet regulatory benchmarks (Financial Services Authority, 2022 ). Given the intensified competition within the banking sector, effective strategies and rigorous health assessments are even more critical. Recent studies highlight that rural banks’ success increasingly depends on adapting to dynamic regulatory environments and technological advances, which are integral to sustaining competitiveness in a rapidly evolving market (Yulianto & Hidayat, 2020 ; World Bank, 2022 ). This suggests that strategic adaptation and regulatory compliance are indispensable for the long-term sustainability of rural banks. Intellectual Capital Intellectual capital (IC) is a crucial intangible asset in the modern era of information and knowledge-driven economies. Stewart ( 1997 ) defines Intellectual Capital as the sum of a company's intangible assets that enable it to compete effectively in the market, encompassing intellectual material, knowledge, experience, and intellectual property that contribute to value creation. Nahapiet and Ghoshal ( 1998 ) expand on this by describing IC as the knowledge and capabilities possessed by a social collectivity—such as an organization or intellectual community—that can be leveraged to create value through collective expertise. Intellectual Capital thus represents a strategic resource, with the potential to enhance a company’s market position and operational effectiveness. Brooking ( 1996 ) conceptualizes Intellectual Capital as the combined intangible assets of a company, including intellectual property, human resources, and infrastructure that together enable the organization to function and innovate. This view aligns with the notion that Intellectual Capital encompasses a spectrum of intangible assets that drive a company’s competitive edge. According to Stewart ( 1997 ), IC can be divided into three core components: Human Capital, Structural Capital, and Customer Capital. Human Capital refers to the skills, knowledge, and competencies of employees, while Structural Capital represents the systems, processes, databases, and intellectual property that support the company’s operations. Customer Capital, meanwhile, reflects the value derived from customer relationships and loyalty. Pulic ( 1997 ) introduced the Value-Added Intellectual Coefficient (VAICTM) model, which quantifies the value-creation capacity of IC by examining three types of added value: Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE). The VAICTM model has since become widely used to measure a firm’s intellectual capital performance and its ability to generate value (Chen et al., 2004). Recent studies affirm that IC contributes significantly to organizational success, particularly in knowledge-intensive industries. Bontis ( 1998 ) posits that intellectual capital provides a competitive advantage that is sustainable over the long term. Likewise, Youndt et al. ( 2004 ) assert that organizations with well-managed intellectual resources are better equipped to respond to market changes and achieve superior financial performance. The importance of IC is underscored by its role in driving innovation, fostering relationships with stakeholders, and enhancing overall business resilience in rapidly changing environments (Subramaniam & Youndt, 2005 ). Micro, Small and Medium Enterprise (MSME) Loans One of the primary challenges faced by rural banks in extending credit to MSME customers is the government’s People's Business Credit (Kredit Usaha Rakyat, or KUR) program, which channels low-interest loans through commercial banks. The KUR program, launched by the Indonesian government, aims to enhance community income levels by increasing financial accessibility for MSMEs through a credit guarantee scheme (Pambudi& Santoso, 2020 ). This initiative supports MSME growth by providing low-interest loans, aligning with the broader goals of economic empowerment and sectoral development under financial sector reform policies and Law No. 20/2008 on MSMEs, which mandates that "The government and local governments are obliged to create a business climate by stipulating regulations and legislation covering aspects of funding, facilities, infrastructure, etc." (Government of Indonesia, 2008 ). However, the competitive advantage provided by the KUR program poses significant challenges for rural banks. With KUR loans offered at a low interest rate of 6% per year, rural banks find it difficult to compete, as their loans typically have interest rates ranging from 15–18% per year (Mulyani&Syahputra, 2021 ). This disparity puts rural banks at a disadvantage, as potential MSME borrowers may prefer the lower-cost KUR loans provided by commercial banks. The policy, while beneficial for MSMEs, inadvertently limits the ability of rural banks to serve this sector effectively, thus impacting their profitability and market share (Wijaya, 2021 ). The sustainability of rural banks is further challenged by their reliance on MSME loans, a core segment of their lending portfolios. Recent studies highlight that the KUR scheme, while successful in improving financial inclusion, has intensified competition, making it difficult for rural banks to sustain their loan portfolios without additional government support or differentiation strategies (Savitri & Mulyono, 2022 ). This situation calls for policy adjustments that would enable rural banks to better support MSME financing without being overshadowed by commercial banks under the KUR scheme. Furthermore, there is a growing need for rural banks to innovate and adopt more flexible credit products tailored to the unique needs of MSMEs in rural areas (Yulianti et al., 2022 ). Based on the explanation provided in the literature review above, the research model can be illustrated as shown in the following Fig. 1. Building on the literature review and the research model outlined above, the research hypotheses can be formulated as follows: The Research Hypothesis : H1: Intellectual Capital factor effects to BPR business in Jambi Province H2: UMKM Credit factor effects to BPR business in Jambi Province H3: Intellectual Capital and UMKM Credit factors effects to BPR business in Jambi Province 3. RESEARCH METHODS The research methodology in this study involves systematic steps taken by researchers to gather and analyze data effectively. Methodology is fundamental as it shapes the approach to data collection and analysis, thereby ensuring reliable and valid results (Creswell & Creswell, 2018 ). The primary data collected consists of financial reports from rural banks in Jambi Province, covering the period from 2013 to 2022. These financial reports were obtained from reputable sources such as Bank Indonesia (BI), the Financial Services Authority (OJK), and the Central Statistics Agency (BPS), as well as directly from each rural bank’s institutional records. This comprehensive data collection approach ensures a reliable and robust data foundation for analyzing rural bank performance (Sekaran & Bougie, 2016 ). For data processing, this study employs panel data regression analysis, a powerful method for examining data across multiple entities over time. The regression analysis involves several calculation stages, specifically utilizing the Pooled Least Square (PLS) model, Common Effect Model (CEM), and Random Effect Model (REM). Panel data regression is particularly effective in capturing both cross-sectional and temporal variations, offering deeper insights into trends and relationships within financial data (Gujarati & Porter, 2009 ). By leveraging these models, the study is able to identify trends, patterns, and potential relationships within the dataset with greater accuracy (Baltagi, 2013 ). The type of data utilized is quantitative, derived from publicly available financial statements published by the OJK, including balance sheets, income statements, and various financial ratios. Only data from rural banks that are active and operational in specific regions, such as province and district/city levels, were included. This information was accessed through OJK’s official publications and databases, available online at https://www.ojk.go.id/id/Default.aspx . Accessing consistent and standardized datasets enhances the credibility and reliability of research findings (Yin, 2018 ). 4. RESULTS AND DISCUSSION The results and discussion of this study, which examines the impact of Intellectual Capital and MSME credit on the business operations of rural banks in Jambi Province, are structured in two main stages. First, the research results encompass statistical analysis, model specification testing, and model selection, which are integral for validating the robustness of the model and confirming the research hypotheses (Greene, 2012 ). Statistical rigor in these initial steps ensures that the conclusions drawn are reliable and reflective of actual trends within the data (Wooldridge, 2010 ). Second, the analysis includes a comprehensive discussion of the research model, conducted quantitatively in alignment with the data collected for each rural bank. Quantitative methods are particularly useful in banking research as they provide objective insights and help to establish causal relationships (Bryman, 2016 ). For analyzing the results, this study uses panel data processed through the E-views-10 software application, which is well-regarded for handling complex panel data analysis efficiently (Asteriou& Hall, 2015 ). Utilizing panel data allows for a deeper examination of both cross-sectional and longitudinal variations, offering insights into temporal trends while accounting for individual bank characteristics (Hsiao, 2007 ). Through this approach, the study aims to provide a nuanced understanding of how Intellectual Capital and MSME credit influence the business performance of rural banks in a specific regional context. The findings from this analysis are anticipated to contribute to the broader literature on rural banking and financial inclusion, particularly in emerging markets. First Stage , Analysis of the Effect of Intellectual Capital and MSME Credit on RURAL BANK Business in Jambi Province To analyze the impact of Intellectual Capital and MSME credit on rural bank business performance in Jambi Province, this study employs statistical panel data regression. Panel data regression is widely used for its ability to capture both cross-sectional and time-series variations, thus providing a robust approach to understanding financial performance over time (Baltagi, 2013 ; Hsiao, 2007 ). This analysis specifically utilizes three regression models: the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). By integrating Intellectual Capital (IC) and MSME Credit as independent variables, the study aims to predict and quantify their effect on rural bank business performance in Jambi Province, covering data from 18 rural banks over a period of 10 years (2013–2022). Following standard procedures in panel data analysis, three tests were employed to determine the most suitable model: the Chow Test, the Hausman Test, and the Lagrange Multiplier Test. These tests are crucial in selecting between fixed and random effects and ensuring that the model aligns with the data characteristics (Gujarati & Porter, 2009 ). Based on these tests, the Random Effect Model (REM) was identified as the best fit for this study. REM is particularly suitable when variations across entities (rural banks) are assumed to be random and uncorrelated with the independent variables, allowing for generalizable insights across the sample (Wooldridge, 2010 ). In this regression model, the rural bank business performance (dependent variable, Y) is analyzed in relation to two independent variables: Intellectual Capital (X1) and MSME Credit (X2). Intellectual Capital has been shown to contribute to enhanced financial performance through improved organizational efficiency and innovation (Chen et al., 2005 ; Youndt et al., 2004 ). Meanwhile, MSME Credit is a critical factor, as it aligns with the banks’ mission to support local economic growth by extending credit to smaller enterprises, which is often linked to increased bank profitability and community impact (Beck et al., 2015 ; Berger & Udell, 2006 ). This methodological approach enables the study to examine whether Intellectual Capital and MSME Credit have significant, positive impacts on rural bank performance, offering valuable insights into the strategic factors that drive financial success in this sector. Hypothesis Testing a. T-Test The t-test is employed to evaluate the significance of each independent variable's impact on the dependent variable, specifically by comparing the calculated t-statistic (t-count) for each independent variable's coefficient with the critical t-table value. This test helps determine whether the independent variables—Intellectual Capital and MSME Credit—have a statistically significant effect on the dependent variable, which in this case is rural bank business performance in Jambi Province. According to standard statistical procedures, if the t-count exceeds the t-table value or if the p-value is less than 0.05, the null hypothesis (indicating no effect) is rejected. This signifies that the independent variable has a significant influence on the dependent variable (Hair et al., 2010 ; Field, 2013). In conducting this analysis, the study uses the E-views 10 software application to facilitate the panel data processing and hypothesis testing. E-views is particularly suitable for handling complex econometric analyses involving time-series and cross-sectional data, which enhances the reliability and precision of the results (Brooks, 2019). The t-test outcomes obtained through E-views offer a rigorous basis for evaluating the relationships between the variables, as the software provides exact p-values, allowing researchers to make informed decisions based on probability thresholds (Greene, 2012 ). The significance of these results is underscored by the practical implication that, if Intellectual Capital and MSME Credit show significant t-test results, these variables can be considered key drivers of rural bank performance. Intellectual Capital, for example, has been linked to enhanced financial performance through increased efficiency and innovation, as established in previous studies (Chen et al., 2005 ; Youndt et al., 2004 ). Similarly, MSME Credit is a critical component in rural bank lending portfolios, often associated with improved financial outcomes and community impact, which are essential for sustaining bank profitability in local economies (Beck et al., 2015 ; Berger & Udell, 2006 ). The application of these t-test results thus allows for evidence-based decisions about the strategic factors influencing rural bank success in a regional context. Table 3 t-test results Variable Coefficient Std. Error t-Statistic Prob. C 8438373. 1256243. 6.717149 0.0000 X1 0.146412 0.067633 2.164806 0.0326 X2 1.169059 0.034673 33.71641 0.0000 Source: Data processed by E-Views Table 3 illustrates that both Intellectual Capital (X1) and MSME Credit (X2) significantly influence rural bank business performance in Jambi Province. This impact is evident in the Intellectual Capital variable, which shows a significance value of 0.0326 (0.0326 < 0.05), indicating that Intellectual Capital has a meaningful effect on the rural bank business. Intellectual Capital's contribution aligns with the findings of Chen et al. ( 2005 ), who argue that intangible assets such as knowledge and expertise positively influence firm performance by enhancing efficiency and innovation. The role of Intellectual Capital in improving bank performance highlights its value as a strategic resource in a competitive financial environment (Youndt et al., 2004 ). Similarly, the MSME Credit variable demonstrates a highly significant effect on rural bank business performance, with a p-value of 0.0000 (0.0000 < 0.05). This result underscores the importance of MSME Credit in supporting rural bank profitability, consistent with Berger and Udell’s ( 2006 ) findings, which indicate that credit to smaller enterprises fosters local economic growth and strengthens the financial foundation of rural banking institutions. MSME Credit allows rural banks to expand their customer base and community impact, reinforcing their role in financial inclusion (Beck et al., 2015 ). In summary, these findings validate the hypothesis that both Intellectual Capital and MSME Credit play significant roles in rural bank performance, underscoring the strategic importance of these factors in enhancing financial outcomes in Jambi Province. b. F test The F-test is utilized to evaluate whether the independent variables, collectively, have a significant effect on the dependent variable. This test is essential in determining the overall explanatory power of the model, assessing if Intellectual Capital and MSME Credit jointly impact rural bank business performance in Jambi Province. The test criterion states that if the F-count value exceeds the F-table value or if the p-value (ρ) is less than 0.05, the null hypothesis (indicating no effect) is rejected. This outcome would imply that the independent variables as a group significantly influence the dependent variable (Hair et al., 2010 ; Greene, 2012 ). Conducting the F-test is critical for validating the model’s adequacy, as it indicates whether the chosen independent variables meaningfully explain variations in rural bank business performance. This collective assessment is especially valuable in multivariate regression contexts, where understanding the combined effect of variables like Intellectual Capital and MSME Credit provides insights into their cumulative influence on financial performance (Wooldridge, 2010 ). The results from the panel data processing, performed using the F-test in E-views 10, demonstrate whether the model has statistically significant explanatory power. This testing approach aligns with best practices in econometric analysis, offering a robust statistical foundation for examining the overall relationship between independent and dependent variables (Asteriou& Hall, 2015 ). Table 4 F Test Results Test R-squared Adjusted R-square S.E of regression F-statistic Prob (F-statistic) Results 0.976805 0.973960 4699669 343.3760 0.000000 Source: Data processed by E-Views In Table 4 , the F-test results demonstrate that the probability (Prob) value of the F-statistic is 0.000000, which is considerably lower than the significance level (α) of 0.05 or 5% (0.000000 < 0.05). This outcome indicates that the null hypothesis (H0) is rejected, while the alternative hypothesis (H1) is accepted. Thus, it can be concluded that the independent variables—Intellectual Capital (X1) and MSME Credit (X2)—have a statistically significant combined effect on the rural bank business performance in Jambi Province over the period 2013–2022. The significance of this finding underscores the combined influence of Intellectual Capital and MSME Credit on enhancing the performance and sustainability of rural banks. Intellectual Capital, encompassing knowledge, skills, and innovative capabilities, plays a critical role in creating value and competitive advantage for financial institutions (Chen et al., 2005 ; Youndt et al., 2004 ). Similarly, MSME Credit is crucial for supporting local economies and ensuring financial inclusion, which, in turn, strengthens rural banks' customer base and profitability (Berger & Udell, 2006 ; Beck et al., 2015 ). The strong Prob (F-statistic) outcome suggests that these variables are vital contributors to rural bank performance, aligning with existing literature that highlights their importance in financial stability and growth. This result provides robust evidence that both Intellectual Capital and MSME Credit are not only individually impactful but also collectively essential for driving rural bank success in regional economies like Jambi Province, where financial resources and intellectual assets directly support community-based banking activities. R test 2 ( R-Square ) The results of the R² (coefficient of determination) model testing reveal a value of 0.976805 in the panel data regression model. This high R² value indicates that 97.68% of the variation in the rural bank business performance in Jambi Province can be explained by the independent variables—Intellectual Capital and MSME Credit—at a highly significant level (less than 1%). The remaining 2.32% is attributed to other variables not included in the model, suggesting a minimal impact from external factors. This high level of explanatory power underscores the substantial influence of Intellectual Capital and MSME Credit on rural bank development. A model with an R² close to 1, as seen here, implies that the selected independent variables are highly predictive of the dependent variable, signifying their importance in shaping rural bank outcomes (Hair et al., 2010 ). The findings are consistent with previous research that highlights the critical role of Intellectual Capital—through enhanced knowledge, skills, and innovation—in driving financial performance and organizational resilience in banking institutions (Chen et al., 2005 ; Youndt et al., 2004 ). Similarly, MSME Credit, by supporting local businesses, not only contributes to financial inclusion but also strengthens the operational foundations of rural banks, as evidenced in various studies on MSME financing and rural banking (Berger & Udell, 2006 ; Beck et al., 2015 ). Overall, the R² value provides robust evidence of the model’s effectiveness, affirming that Intellectual Capital and MSME Credit are pivotal factors in the growth and sustainability of rural banks in Jambi Province. This high explanatory power reinforces the importance of strategic investments in these areas for long-term rural bank success. Second stage , analyze the discussion of research results The findings from this study provide compelling evidence that Intellectual Capital and MSME Credit significantly impact the business performance of rural banks in Jambi Province. This result aligns with substantial research highlighting the value of Intellectual Capital in enhancing organizational performance, particularly in knowledge-intensive sectors like banking (Chen et al., 2005 ; Youndt et al., 2004 ). Intellectual Capital—comprising human knowledge, relational capital, and structural systems—enables banks to improve efficiency, foster innovation, and develop competitive advantages that are crucial in highly regulated and competitive environments (Bontis, 1998 ). The ability to harness Intellectual Capital thus emerges as a key differentiator for rural banks striving to sustain their operations amidst rising competition. However, the study’s findings must be considered within the broader context of the rural banking industry in Indonesia, where unique challenges persist. While Intellectual Capital is a positive driver of performance, Kamath ( 2007 ) argues that structural and regulatory barriers can limit the impact of Intellectual Capital in developing markets. Rural banks, unlike their conventional counterparts, often have limited resources to invest in sophisticated training or knowledge management systems, which constrains their ability to fully leverage Intellectual Capital. Furthermore, regulatory requirements and market conditions may hinder these banks from translating Intellectual Capital into financial gains. This presents a nuanced view: while Intellectual Capital is influential, its potential impact can vary significantly depending on external factors such as policy constraints and market maturity (Holland, 2006 ). The study also underscores the critical role of MSME Credit, a core offering of rural banks, which aligns with the banks’ mission to support local economic development. Providing credit to MSMEs has been shown to enhance financial inclusion and stimulate economic growth in underserved regions (Beck et al., 2015 ; Berger & Udell, 2006 ). However, the competitive advantage of rural banks in this sector is increasingly challenged by larger commercial banks offering KUR loans at significantly lower interest rates, often around 6%. This contrast in lending terms places rural banks at a disadvantage, particularly as they typically offer rates between 15% and 18% to maintain operational sustainability. According to Coleman ( 2000 ), high interest rates can lead to borrower selection issues, limiting the appeal of rural banks for MSMEs, which are price-sensitive and often opt for lower-cost credit solutions. Moreover, while MSME Credit positively impacts rural banks' business, the findings raise questions about the long-term viability of rural banks in regions with high commercial bank penetration. Nawaz and Munir ( 2012 ) suggest that rural banks must innovate and diversify their service offerings to differentiate themselves from commercial banks. This might involve tailoring products specifically to niche segments within MSMEs or expanding non-traditional financial services that commercial banks do not provide. Additionally, policymakers could consider regulatory support that allows rural banks to compete on more equal terms with commercial banks, especially regarding KUR distribution. From a strategic perspective, the study's findings advocate for the professionalization of rural bank employees through enhanced Intellectual Capital. By developing specialization in MSME lending and employing advanced analytical tools, rural banks can better assess borrower risk and identify profitable opportunities (Subramaniam & Youndt, 2005 ). Yet, this recommendation faces practical challenges. Investing in Intellectual Capital is costly, and rural banks typically operate with limited budgets, which could impact the implementation of such strategic initiatives (Kamath, 2007 ). Additionally, intellectual capital initiatives, while valuable, may not yield immediate financial returns, which could deter rural banks focused on short-term performance from pursuing these strategies (Edvinsson & Malone, 1997 ). This study provides a novel contribution to the literature on rural banking by empirically examining the combined impact of Intellectual Capital and MSME Credit on the business performance of rural banks in Jambi Province. While prior research has explored the effects of Intellectual Capital on banking performance in various contexts (e.g., Ismail & Al-Musali, 2014 ; Kamath, 2007 ), this study specifically focuses on rural banks, which face unique competitive pressures from conventional banks and policy-driven lending programs such as the People’s Business Credit (KUR). The integration of MSME Credit as a key variable, given its importance in rural bank portfolios, adds a unique dimension to the analysis, addressing a gap in the understanding of rural bank resilience in emerging markets. This research uniquely highlights how these variables jointly contribute to rural banks' sustainability amidst competitive challenges, thus offering insights specifically tailored to the rural banking sector in Indonesia. The findings of this study carry several important implications for rural bank management and policymakers. For rural bank leaders, the study emphasizes the critical role of Intellectual Capital in enhancing business performance. Rural banks are encouraged to invest in human capital development, particularly by providing specialized training in MSME lending and credit risk assessment. This could enhance employee skills and enable rural banks to develop unique, competitive financial products that cater to the needs of local MSMEs. Furthermore, the significant impact of MSME Credit on rural bank performance underscores the need for rural banks to focus on this segment, potentially by innovating with lower-cost lending solutions or expanding into niche areas not served by commercial banks. For policymakers, the study’s findings suggest a need to review the KUR program’s structure and consider measures that support rural banks in competing on more equal terms with commercial banks. Adjusting regulations to allow rural banks access to some form of subsidized credit for MSMEs, similar to the KUR program, could help balance competition and foster greater financial inclusion. Additionally, policies that encourage partnerships between rural and commercial banks, or incentives for rural banks to adopt technological advancements, could further enhance rural banks' sustainability and reach. The social implications of this study are significant, particularly concerning financial inclusion and local economic development. By highlighting the importance of MSME Credit, the research underlines the role of rural banks in providing accessible financial services to micro and small enterprises that may not meet the eligibility criteria for commercial bank loans. The empowerment of MSMEs through credit access has direct benefits for local economies, as it can stimulate job creation, promote entrepreneurship, and reduce poverty levels in underserved areas. Furthermore, the focus on Intellectual Capital development within rural banks points to a need for skills enhancement in the rural workforce, which can elevate the quality of financial services available to communities. Enhanced Intellectual Capital not only improves rural bank performance but also builds a knowledgeable, professional workforce that can contribute to the broader economic development of rural regions. This investment in human resources can lead to better customer service, stronger community ties, and increased trust in financial institutions, ultimately fostering a more inclusive financial system that supports sustainable economic growth. In summary, this study provides actionable insights for rural banks, policymakers, and society by highlighting the critical roles of Intellectual Capital and MSME Credit in shaping the future of rural banking in Indonesia. By addressing these key factors, stakeholders can work towards strengthening rural banks' resilience and supporting economic development in rural areas. 5. CONCLUSION AND RECOMMENDATION This study underscores the pivotal role of Intellectual Capital and MSME Credit in enhancing the performance of rural banks in Jambi Province. In a competitive environment, especially with the expansion of low-interest KUR loans by commercial banks, rural banks face significant pressure to serve MSMEs effectively. Nevertheless, the findings confirm that investing strategically in Intellectual Capital—through skill development, expertise, and a knowledge-driven workforce—along with a focus on MSME lending, is essential for rural banks to strengthen their sustainability and competitiveness. Intellectual Capital is particularly valuable, empowering rural banks to innovate, improve service quality, and adapt to customer needs. Meanwhile, MSME Credit supports entrepreneurship, financial inclusion, and socioeconomic growth in underserved communities. By financing small businesses, rural banks contribute directly to local economic resilience, creating jobs and improving livelihoods, positioning them as essential engines of rural economic development. To further develop rural banks, it is recommended that they invest in human capital by offering specialized training in MSME financing and credit risk management, fostering stronger client relationships. Product innovation is also key; rural banks could differentiate themselves by offering flexible loan terms, customized repayment options, or community-centered services that large banks may not provide. Government support is critical in ensuring fair competition, particularly with subsidized credit programs. Policymakers might consider funding options that enable rural banks to offer competitive rates to MSMEs or grants for technological and capacity-building advancements. Investing in digital tools would also enhance operational efficiency and service reach. Strategic partnerships with larger institutions could provide rural banks with additional resources and access to shared technology infrastructure. Through these approaches, rural banks in Jambi Province can not only compete but thrive, reinforcing their vital role in empowering MSMEs, fostering economic stability, and driving inclusive growth. Such efforts ensure that rural banks remain essential drivers of regional development, meeting community needs and contributing to a more resilient rural economy. RESEARCH LIMITATIONS This study, while providing valuable insights, has several limitations. First, it is limited to rural banks in Jambi Province, which may restrict the generalizability of the findings to other regions with different economic conditions, regulatory environments, and levels of competition. The focus on a single province means that the unique challenges and dynamics faced by rural banks in Jambi may not fully represent those encountered in other parts of Indonesia. Additionally, the study relies on secondary data from financial reports, which provides a quantitative view of performance but may overlook qualitative factors, such as customer satisfaction, employee motivation, or community impact, that could also influence bank performance. Another limitation is the timeframe of the study, which spans a period of ten years. Although this allows for a thorough analysis of trends over time, a longer or broader dataset could provide a more comprehensive view of how Intellectual Capital and MSME Credit impact rural bank performance over changing economic cycles. Furthermore, the use of panel data analysis does not fully account for external factors, such as regulatory changes or macroeconomic conditions, which could also influence rural bank performance. FUTURE RESEARCH Future research could address these limitations by expanding the geographic scope to include rural banks from multiple regions in Indonesia, allowing for a comparative analysis across different local economies. This broader scope could reveal regional differences and provide insights into the specific challenges and opportunities faced by rural banks in diverse settings. Additionally, future studies could incorporate qualitative research methods, such as interviews or case studies, to capture a deeper understanding of the impact of Intellectual Capital on organizational culture, customer loyalty, and community engagement. Researchers may also consider examining the role of technological advancements and digital banking solutions in supporting rural bank performance, particularly in remote areas where traditional banking infrastructure is limited. Finally, exploring the effects of macroeconomic variables, such as inflation, interest rates, and government policy changes, on rural bank performance could provide a more nuanced understanding of the external pressures that impact their operations. This expanded focus would offer a more comprehensive picture of the factors influencing rural bank sustainability and provide a stronger foundation for policy recommendations that support the growth of rural banks and their contribution to economic development. In conclusion, further exploration into these areas would not only enhance the understanding of rural banking in Indonesia but also support the development of strategies that strengthen the resilience and sustainability of rural banks, ensuring their continued role in fostering financial inclusion and local economic growth. Declarations Acknowledgment We extend our deepest gratitude to all parties who have supported and contributed to this research. Our sincere thanks go to the Rector of Universitas Muhammadiyah Jambi for the guidance and support provided throughout the research process. Your leadership has been a source of motivation and strength.We also express our appreciation to the Head of the Research and Community Service Institute at Universitas Muhammadiyah Jambi for the guidance, resources, and administrative support that facilitated the smooth progress of this project. Our heartfelt thanks go to the field researchers and key informants for their dedication in gathering data accurately and thoroughly. Their efforts were instrumental in ensuring the quality and reliability of our findings.To the research team and faculty members involved, we thank you for your collaboration, constructive insights, and commitment at every stage. Your professionalism and teamwork were invaluable in bringing this research to completion.Lastly, we offer our gratitude to all respondents who willingly shared their time and insights during data collection. Your participation was essential to achieving meaningful and relevant research outcomes.May this research contribute to the advancement of knowledge and the betterment of society. Declaration of No Conflict of Interest The authors declare that there are no conflicts of interest regarding the publication of this research. This study was conducted independently, without any financial or personal interests that could influence the research outcomes. All findings, conclusions, and interpretations presented in this article are solely based on the data collected and analyzed in accordance with ethical research standards. The authors affirm that the research was carried out objectively, with full academic integrity, and that no external party influenced the study's design, methodology, or results. References Alhassan, A. L., & Asare, N. (2021). Profitability in banking: A review of literature and avenues for future research. Journal of Banking & Finance , 128, 106120. https://doi.org/10.1016/j.jbankfin.2021.106120 Asteriou, D., & Hall, S. G. (2015). Applied Econometrics (3rd ed.). Palgrave Macmillan. Baltagi, B. H. (2013). Econometric Analysis of Panel Data (5th ed.). Wiley. Bank Indonesia. (2010). Bank Indonesia Annual Report . Jakarta: Bank Indonesia. Beck, T., Demirguc-Kunt, A., & Levine, R. (2000). 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(2020). Intellectual Capital in Financial Institutions: Stakeholder Relationships and Human Resources. Journal of Economic Studies , 28(1), 23–39. Stewart, T. A. (1997). Intellectual Capital: The New Wealth of Organizations . New York: Doubleday. Subramaniam, M., & Youndt, M. A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal , 48(3), 450-463. https://doi.org/10.5465/amj.2005.17407911 Ulum, I., Ghozali, I., & Purwanto, A. (2014). Intellectual Capital Performance of Indonesian Banking Sector: A Modified VAIC (M-VAIC) Perspective. Asian Journal of Finance & Accounting , 6 (2), 103. https://doi.org/10.5296/ajfa.v6i2.5246 Wijaya, R. (2021). Competitive Pressures on Rural Banks Due to the KUR Program: An Analysis of Market Dynamics. International Journal of Bank Marketing , 37(5), 389-404. https://doi.org/10.1108/IJBM-03-2021-0087 Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.) . 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Journal of Financial and Banking Studies , 4(3), 45-60. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5845202","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":403253160,"identity":"d145a27b-eca8-4bb7-b262-2d719a465492","order_by":0,"name":"Iwan Eka Putra","email":"","orcid":"","institution":"Universitas Muhammadiyah Jambi","correspondingAuthor":false,"prefix":"","firstName":"Iwan","middleName":"Eka","lastName":"Putra","suffix":""},{"id":403253161,"identity":"09870865-79c1-491c-bc61-0de738bcb536","order_by":1,"name":"Ermaini","email":"","orcid":"","institution":"Universitas Muhammadiyah Jambi","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"Ermaini","suffix":""},{"id":403253162,"identity":"712585a4-b16f-4ee4-a3ac-0416ad43a5af","order_by":2,"name":"Etik Winarni","email":"","orcid":"","institution":"Universitas Muhammadiyah Jambi","correspondingAuthor":false,"prefix":"","firstName":"Etik","middleName":"","lastName":"Winarni","suffix":""},{"id":403253163,"identity":"294618e2-38b5-4b82-8542-91c40748b919","order_by":3,"name":"Syahmardi Yacob","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-6827-277X","institution":"Universitas Jambi","correspondingAuthor":true,"prefix":"","firstName":"Syahmardi","middleName":"","lastName":"Yacob","suffix":""}],"badges":[],"createdAt":"2025-01-17 01:43:14","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5845202/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5845202/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74215686,"identity":"0a7fcfda-a946-4bee-aff6-8ce100dc2209","added_by":"auto","created_at":"2025-01-20 05:42:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15387,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResearch Model\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5845202/v1/d178cb4d7d7fcf1106355b8c.png"},{"id":74217603,"identity":"86054da8-2dfc-40bd-9acd-434da05d1641","added_by":"auto","created_at":"2025-01-20 06:06:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":779223,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5845202/v1/635269ed-b544-411e-82ae-3b51b85ae780.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eOptimizing Intellectual Capital And Msme Credit To Enhance Rural Bank Performance: Evidence From Jambi Province, Indonesia\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eBanks, as financial institutions, play a fundamental role in the economy by collecting deposits from the public and redistributing them to third parties, thereby providing payment liquidity services. This core function of banks as aggregators and distributors of public funds is critical for supporting national development, promoting equitable growth, and enhancing economic stability, all of which contribute to an improved standard of living (Bank Indonesia, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Levine, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; World Bank, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Indonesian banking sector is, therefore, vital for enabling economic indicators to improve and thrive, as the economy cannot grow sustainably without the support of financial institutions (Beck et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis is particularly true for rural banks, which must actively capture market share to remain competitive against both bank and non-bank financial institutions. In the face of rapid global economic shifts and technological advancements, rural banks must innovate continually to stay relevant. Developing strong, healthy, and competitive institutions capable of serving the community\u0026mdash;especially Micro, Small, and Medium Enterprises (MSMEs)\u0026mdash;is essential for their survival (CGAP, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, the challenges faced by rural banks are mounting, with intensifying competition from commercial banks and government programs like the People's Business Credit (KUR), which offers low-interest loans to MSMEs through commercial banks. This policy has increased the difficulty for rural banks to grow, as commercial banks are mandated to allocate at least 20% of their total credit to MSMEs, effectively pushing them into this market space (Johannes, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; OJK, 2022).\u003c/p\u003e \u003cp\u003eIn addition to competition, the large number of rural banks operating nationally\u0026mdash;1,441 as of 2022 (OJK, 2022)\u0026mdash;creates a crowded marketplace, especially within the micro-lending sector. To endure these challenges, rural banks must improve their professional capabilities, with a focus on enhancing Intellectual Capital. Intellectual Capital, as defined by Stewart (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), includes intellectual materials that have been formalized, captured, and leveraged to generate higher-value assets. Sidharta (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) emphasizes that Intellectual Capital comprises knowledge assets such as stakeholder relationships and human resources, which can add significant competitive value. Recognized as a cornerstone of organizational competitiveness in the 21st century (Huan, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Edvinsson \u0026amp; Malone, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), Intellectual Capital could serve as the foundation for stabilizing rural banks amidst their ongoing decline.\u003c/p\u003e \u003cp\u003eAccording to OJK data, the number of rural banks has been consistently decreasing from 2018 to 2022. This trend highlights the pressing need for rural banks to bolster their competitiveness and adapt strategically to secure their place within the financial ecosystem (OJK, 2022).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDevelopment of the Number of Rural Banks (Growth of Total Rural Banks)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Rural Banks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgress (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource: Financial Services Authority (OJK) and Processed\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe data in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e highlight a consistent national decline in the number of rural banks, with a downward trend in their total count from 2018 to 2022. In 2018, there were 1,597 rural banks, which dropped to 1,545 in 2019, reflecting a decrease of 3.26%. This decline continued into subsequent years: 1,506 banks in 2020 (a 2.52% decrease), 1,468 in 2021 (another 2.52% decrease), and finally 1,441 in 2022 (a 1.84% decrease). This pattern indicates a persistent contraction in the rural banking sector, marked by closures and bankruptcies that raise significant concerns about the sustainability of rural banks. Despite these institutions\u0026rsquo; role in supporting MSMEs, their numbers continue to dwindle, sparking questions about the underlying challenges these banks face.\u003c/p\u003e \u003cp\u003eIn contrast, rural banks in Jambi Province present an intriguing anomaly. Although only 18 rural banks are spread across various cities and regencies in Jambi, several key performance indicators\u0026mdash;such as Total Assets and Third-Party Funds\u0026mdash;show a positive trajectory, countering the national decline in rural bank numbers. This suggests that while the national rural banking sector faces systemic challenges, rural banks in Jambi are achieving performance gains, pointing to potentially unique factors in this region that warrant closer examination.\u003c/p\u003e \u003cp\u003eThe following indicators provide a detailed overview of the performance achievements of rural banks in Jambi Province, highlighting a phenomenon that may offer insights for improving the resilience and sustainability of rural banks nationally.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRural Bank Performance Achievement Indicators in Jambi Province (In Billion)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Assets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgress (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThird Party Funds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgress (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource: Financial Services Authority (OJK) and Processed\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe data in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reveal a steady growth in total assets for rural banks in Jambi Province from 2018 to 2022, indicating a resilient performance despite external challenges. In 2018, total assets stood at Rp. 909\u0026nbsp;billion, which rose to Rp. 1,047\u0026nbsp;billion in 2019\u0026mdash;a significant 15.18% increase. This growth trajectory continued into 2020, with total assets reaching Rp. 1,091\u0026nbsp;billion, an additional 4.20% rise, even amidst the economic uncertainties of the COVID-19 pandemic. The upward trend persisted in 2021, with assets totaling Rp. 1,197\u0026nbsp;billion, marking a 9.72% increase, and in 2022, assets further expanded to Rp. 1,261\u0026nbsp;billion, reflecting a 5.35% rise.\u003c/p\u003e \u003cp\u003eThis asset growth aligns with an increase in third-party funds (DPK), which also showed steady growth over this period. In 2018, DPK totaled Rp. 654\u0026nbsp;billion, which rose by 17.13% to Rp. 766\u0026nbsp;billion in 2019. This upward trend continued in 2020, with DPK reaching Rp. 788\u0026nbsp;billion, a 2.87% increase, followed by another rise to Rp. 875\u0026nbsp;billion in 2021 (11.04%) and Rp. 894\u0026nbsp;billion in 2022, marking an additional 2.17% increase.\u003c/p\u003e \u003cp\u003eThis pattern is particularly noteworthy as it presents a contrasting phenomenon: while the number of rural banks nationally continues to decline, rural banks in Jambi Province show robust growth in key performance indicators like total assets and DPK. This discrepancy raises compelling questions about the unique conditions or strategies in Jambi Province that may be driving these positive outcomes.\u003c/p\u003e \u003cp\u003eIn response to this intriguing phenomenon, this study aims to investigate the factors influencing rural bank performance in Jambi, focusing specifically on the roles of Intellectual Capital and MSME credit. The research seeks to understand and analyze how these factors contribute to the business sustainability and competitive positioning of rural banks in this region.\u003c/p\u003e"},{"header":"2. LITERATURE REVIEW","content":"\u003cp\u003e \u003cb\u003eRural Bank Business\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGenerally, businesses produce goods and services for profit. For banks, profit orientation is essential for sustaining operations, making profitability a key factor in their long-term viability (Alhassan \u0026amp; Asare, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, rural banks must operate effectively and efficiently to achieve their primary goal of maximizing profits. To support business growth, rural banks need strategic policies encompassing their vision, mission, governance, risk management, competitive positioning based on assets or geographic location, and lending strategies tailored to micro, small, and medium enterprises (MSMEs). These strategies align with the guidelines specified in the Financial Services Authority\u0026rsquo;s Circular Letter No. 52/SEOJK.03/2016 on the Business Plans of Rural Banks (Business \u0026amp; Credit, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effectiveness of rural bank operations is frequently assessed through the CAMEL framework, which evaluates Capital, Assets, Management, Earnings, and Liquidity. This analysis is crucial for gauging efficiency, where efficiency can generally be understood as the ratio or comparison of input to output, representing the bank\u0026rsquo;s capability to convert resources into profitable outcomes (Irawan \u0026amp;Widyastuti, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). According to Riady (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), assessing a bank\u0026rsquo;s health involves evaluating financial statement conditions based on standards set by regulatory authorities. For rural banks in Indonesia, these standards are defined in Financial Services Authority Regulation No. 3/POJK.03/2022 on the Health Level of Rural Banks and Sharia Financing Banks, ensuring that rural banks maintain financial stability and meet regulatory benchmarks (Financial Services Authority, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the intensified competition within the banking sector, effective strategies and rigorous health assessments are even more critical. Recent studies highlight that rural banks\u0026rsquo; success increasingly depends on adapting to dynamic regulatory environments and technological advances, which are integral to sustaining competitiveness in a rapidly evolving market (Yulianto \u0026amp; Hidayat, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; World Bank, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This suggests that strategic adaptation and regulatory compliance are indispensable for the long-term sustainability of rural banks.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIntellectual Capital\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIntellectual capital (IC) is a crucial intangible asset in the modern era of information and knowledge-driven economies. Stewart (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) defines Intellectual Capital as the sum of a company's intangible assets that enable it to compete effectively in the market, encompassing intellectual material, knowledge, experience, and intellectual property that contribute to value creation. Nahapiet and Ghoshal (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) expand on this by describing IC as the knowledge and capabilities possessed by a social collectivity\u0026mdash;such as an organization or intellectual community\u0026mdash;that can be leveraged to create value through collective expertise. Intellectual Capital thus represents a strategic resource, with the potential to enhance a company\u0026rsquo;s market position and operational effectiveness.\u003c/p\u003e \u003cp\u003eBrooking (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) conceptualizes Intellectual Capital as the combined intangible assets of a company, including intellectual property, human resources, and infrastructure that together enable the organization to function and innovate. This view aligns with the notion that Intellectual Capital encompasses a spectrum of intangible assets that drive a company\u0026rsquo;s competitive edge. According to Stewart (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), IC can be divided into three core components: Human Capital, Structural Capital, and Customer Capital. Human Capital refers to the skills, knowledge, and competencies of employees, while Structural Capital represents the systems, processes, databases, and intellectual property that support the company\u0026rsquo;s operations. Customer Capital, meanwhile, reflects the value derived from customer relationships and loyalty.\u003c/p\u003e \u003cp\u003ePulic (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) introduced the Value-Added Intellectual Coefficient (VAICTM) model, which quantifies the value-creation capacity of IC by examining three types of added value: Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE). The VAICTM model has since become widely used to measure a firm\u0026rsquo;s intellectual capital performance and its ability to generate value (Chen et al., 2004).\u003c/p\u003e \u003cp\u003eRecent studies affirm that IC contributes significantly to organizational success, particularly in knowledge-intensive industries. Bontis (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) posits that intellectual capital provides a competitive advantage that is sustainable over the long term. Likewise, Youndt et al. (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) assert that organizations with well-managed intellectual resources are better equipped to respond to market changes and achieve superior financial performance. The importance of IC is underscored by its role in driving innovation, fostering relationships with stakeholders, and enhancing overall business resilience in rapidly changing environments (Subramaniam \u0026amp; Youndt, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMicro, Small and Medium Enterprise (MSME) Loans\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOne of the primary challenges faced by rural banks in extending credit to MSME customers is the government\u0026rsquo;s People's Business Credit (Kredit Usaha Rakyat, or KUR) program, which channels low-interest loans through commercial banks. The KUR program, launched by the Indonesian government, aims to enhance community income levels by increasing financial accessibility for MSMEs through a credit guarantee scheme (Pambudi\u0026amp; Santoso, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This initiative supports MSME growth by providing low-interest loans, aligning with the broader goals of economic empowerment and sectoral development under financial sector reform policies and Law No. 20/2008 on MSMEs, which mandates that \"The government and local governments are obliged to create a business climate by stipulating regulations and legislation covering aspects of funding, facilities, infrastructure, etc.\" (Government of Indonesia, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the competitive advantage provided by the KUR program poses significant challenges for rural banks. With KUR loans offered at a low interest rate of 6% per year, rural banks find it difficult to compete, as their loans typically have interest rates ranging from 15\u0026ndash;18% per year (Mulyani\u0026amp;Syahputra, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This disparity puts rural banks at a disadvantage, as potential MSME borrowers may prefer the lower-cost KUR loans provided by commercial banks. The policy, while beneficial for MSMEs, inadvertently limits the ability of rural banks to serve this sector effectively, thus impacting their profitability and market share (Wijaya, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe sustainability of rural banks is further challenged by their reliance on MSME loans, a core segment of their lending portfolios. Recent studies highlight that the KUR scheme, while successful in improving financial inclusion, has intensified competition, making it difficult for rural banks to sustain their loan portfolios without additional government support or differentiation strategies (Savitri \u0026amp; Mulyono, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This situation calls for policy adjustments that would enable rural banks to better support MSME financing without being overshadowed by commercial banks under the KUR scheme. Furthermore, there is a growing need for rural banks to innovate and adopt more flexible credit products tailored to the unique needs of MSMEs in rural areas (Yulianti et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the explanation provided in the literature review above, the research model can be illustrated as shown in the following Fig.\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eBuilding on the literature review and the research model outlined above, the research hypotheses can be formulated as follows:\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Research Hypothesis\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eH1: Intellectual Capital factor effects to BPR business in Jambi Province\u003c/p\u003e \u003cp\u003eH2: UMKM Credit factor effects to BPR business in Jambi Province\u003c/p\u003e \u003cp\u003eH3: Intellectual Capital and UMKM Credit factors effects to BPR business in Jambi Province\u003c/p\u003e"},{"header":"3. RESEARCH METHODS","content":"\u003cp\u003eThe research methodology in this study involves systematic steps taken by researchers to gather and analyze data effectively. Methodology is fundamental as it shapes the approach to data collection and analysis, thereby ensuring reliable and valid results (Creswell \u0026amp; Creswell, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The primary data collected consists of financial reports from rural banks in Jambi Province, covering the period from 2013 to 2022. These financial reports were obtained from reputable sources such as Bank Indonesia (BI), the Financial Services Authority (OJK), and the Central Statistics Agency (BPS), as well as directly from each rural bank\u0026rsquo;s institutional records. This comprehensive data collection approach ensures a reliable and robust data foundation for analyzing rural bank performance (Sekaran \u0026amp; Bougie, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor data processing, this study employs panel data regression analysis, a powerful method for examining data across multiple entities over time. The regression analysis involves several calculation stages, specifically utilizing the Pooled Least Square (PLS) model, Common Effect Model (CEM), and Random Effect Model (REM). Panel data regression is particularly effective in capturing both cross-sectional and temporal variations, offering deeper insights into trends and relationships within financial data (Gujarati \u0026amp; Porter, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). By leveraging these models, the study is able to identify trends, patterns, and potential relationships within the dataset with greater accuracy (Baltagi, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe type of data utilized is quantitative, derived from publicly available financial statements published by the OJK, including balance sheets, income statements, and various financial ratios. Only data from rural banks that are active and operational in specific regions, such as province and district/city levels, were included. This information was accessed through OJK\u0026rsquo;s official publications and databases, available online at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ojk.go.id/id/Default.aspx\u003c/span\u003e\u003cspan address=\"https://www.ojk.go.id/id/Default.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessing consistent and standardized datasets enhances the credibility and reliability of research findings (Yin, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e"},{"header":"4. RESULTS AND DISCUSSION","content":"\u003cp\u003eThe results and discussion of this study, which examines the impact of Intellectual Capital and MSME credit on the business operations of rural banks in Jambi Province, are structured in two main stages. First, the research results encompass statistical analysis, model specification testing, and model selection, which are integral for validating the robustness of the model and confirming the research hypotheses (Greene, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Statistical rigor in these initial steps ensures that the conclusions drawn are reliable and reflective of actual trends within the data (Wooldridge, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSecond, the analysis includes a comprehensive discussion of the research model, conducted quantitatively in alignment with the data collected for each rural bank. Quantitative methods are particularly useful in banking research as they provide objective insights and help to establish causal relationships (Bryman, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For analyzing the results, this study uses panel data processed through the E-views-10 software application, which is well-regarded for handling complex panel data analysis efficiently (Asteriou\u0026amp; Hall, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Utilizing panel data allows for a deeper examination of both cross-sectional and longitudinal variations, offering insights into temporal trends while accounting for individual bank characteristics (Hsiao, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThrough this approach, the study aims to provide a nuanced understanding of how Intellectual Capital and MSME credit influence the business performance of rural banks in a specific regional context. The findings from this analysis are anticipated to contribute to the broader literature on rural banking and financial inclusion, particularly in emerging markets.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFirst Stage\u003c/b\u003e, \u003cb\u003eAnalysis of the Effect of\u003c/b\u003e \u003cb\u003eIntellectual Capital\u003c/b\u003e \u003cb\u003eand MSME Credit on RURAL BANK Business in Jambi Province\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo analyze the impact of Intellectual Capital and MSME credit on rural bank business performance in Jambi Province, this study employs statistical panel data regression. Panel data regression is widely used for its ability to capture both cross-sectional and time-series variations, thus providing a robust approach to understanding financial performance over time (Baltagi, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hsiao, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This analysis specifically utilizes three regression models: the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). By integrating Intellectual Capital (IC) and MSME Credit as independent variables, the study aims to predict and quantify their effect on rural bank business performance in Jambi Province, covering data from 18 rural banks over a period of 10 years (2013\u0026ndash;2022).\u003c/p\u003e \u003cp\u003eFollowing standard procedures in panel data analysis, three tests were employed to determine the most suitable model: the Chow Test, the Hausman Test, and the Lagrange Multiplier Test. These tests are crucial in selecting between fixed and random effects and ensuring that the model aligns with the data characteristics (Gujarati \u0026amp; Porter, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Based on these tests, the Random Effect Model (REM) was identified as the best fit for this study. REM is particularly suitable when variations across entities (rural banks) are assumed to be random and uncorrelated with the independent variables, allowing for generalizable insights across the sample (Wooldridge, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this regression model, the rural bank business performance (dependent variable, Y) is analyzed in relation to two independent variables: Intellectual Capital (X1) and MSME Credit (X2). Intellectual Capital has been shown to contribute to enhanced financial performance through improved organizational efficiency and innovation (Chen et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Youndt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Meanwhile, MSME Credit is a critical factor, as it aligns with the banks\u0026rsquo; mission to support local economic growth by extending credit to smaller enterprises, which is often linked to increased bank profitability and community impact (Beck et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Berger \u0026amp; Udell, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis methodological approach enables the study to examine whether Intellectual Capital and MSME Credit have significant, positive impacts on rural bank performance, offering valuable insights into the strategic factors that drive financial success in this sector.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHypothesis Testing\u003c/b\u003e \u003c/p\u003e \u003cp\u003ea. T-Test\u003c/p\u003e \u003cp\u003eThe t-test is employed to evaluate the significance of each independent variable's impact on the dependent variable, specifically by comparing the calculated t-statistic (t-count) for each independent variable's coefficient with the critical t-table value. This test helps determine whether the independent variables\u0026mdash;Intellectual Capital and MSME Credit\u0026mdash;have a statistically significant effect on the dependent variable, which in this case is rural bank business performance in Jambi Province. According to standard statistical procedures, if the t-count exceeds the t-table value or if the p-value is less than 0.05, the null hypothesis (indicating no effect) is rejected. This signifies that the independent variable has a significant influence on the dependent variable (Hair et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Field, 2013).\u003c/p\u003e \u003cp\u003eIn conducting this analysis, the study uses the E-views 10 software application to facilitate the panel data processing and hypothesis testing. E-views is particularly suitable for handling complex econometric analyses involving time-series and cross-sectional data, which enhances the reliability and precision of the results (Brooks, 2019). The t-test outcomes obtained through E-views offer a rigorous basis for evaluating the relationships between the variables, as the software provides exact p-values, allowing researchers to make informed decisions based on probability thresholds (Greene, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe significance of these results is underscored by the practical implication that, if Intellectual Capital and MSME Credit show significant t-test results, these variables can be considered key drivers of rural bank performance. Intellectual Capital, for example, has been linked to enhanced financial performance through increased efficiency and innovation, as established in previous studies (Chen et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Youndt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Similarly, MSME Credit is a critical component in rural bank lending portfolios, often associated with improved financial outcomes and community impact, which are essential for sustaining bank profitability in local economies (Beck et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Berger \u0026amp; Udell, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The application of these t-test results thus allows for evidence-based decisions about the strategic factors influencing rural bank success in a regional context.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003et-test results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProb.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8438373.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1256243.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.717149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eX1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.146412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.067633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.164806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eX2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.169059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.71641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSource: Data processed by E-Views\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates that both Intellectual Capital (X1) and MSME Credit (X2) significantly influence rural bank business performance in Jambi Province. This impact is evident in the Intellectual Capital variable, which shows a significance value of 0.0326 (0.0326\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that Intellectual Capital has a meaningful effect on the rural bank business. Intellectual Capital's contribution aligns with the findings of Chen et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), who argue that intangible assets such as knowledge and expertise positively influence firm performance by enhancing efficiency and innovation. The role of Intellectual Capital in improving bank performance highlights its value as a strategic resource in a competitive financial environment (Youndt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, the MSME Credit variable demonstrates a highly significant effect on rural bank business performance, with a p-value of 0.0000 (0.0000\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This result underscores the importance of MSME Credit in supporting rural bank profitability, consistent with Berger and Udell\u0026rsquo;s (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) findings, which indicate that credit to smaller enterprises fosters local economic growth and strengthens the financial foundation of rural banking institutions. MSME Credit allows rural banks to expand their customer base and community impact, reinforcing their role in financial inclusion (Beck et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, these findings validate the hypothesis that both Intellectual Capital and MSME Credit play significant roles in rural bank performance, underscoring the strategic importance of these factors in enhancing financial outcomes in Jambi Province.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eb. F test\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe F-test is utilized to evaluate whether the independent variables, collectively, have a significant effect on the dependent variable. This test is essential in determining the overall explanatory power of the model, assessing if Intellectual Capital and MSME Credit jointly impact rural bank business performance in Jambi Province. The test criterion states that if the F-count value exceeds the F-table value or if the p-value (ρ) is less than 0.05, the null hypothesis (indicating no effect) is rejected. This outcome would imply that the independent variables as a group significantly influence the dependent variable (Hair et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Greene, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConducting the F-test is critical for validating the model\u0026rsquo;s adequacy, as it indicates whether the chosen independent variables meaningfully explain variations in rural bank business performance. This collective assessment is especially valuable in multivariate regression contexts, where understanding the combined effect of variables like Intellectual Capital and MSME Credit provides insights into their cumulative influence on financial performance (Wooldridge, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results from the panel data processing, performed using the F-test in E-views 10, demonstrate whether the model has statistically significant explanatory power. This testing approach aligns with best practices in econometric analysis, offering a robust statistical foundation for examining the overall relationship between independent and dependent variables (Asteriou\u0026amp; Hall, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eF Test Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted R-square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS.E of regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF-statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProb (F-statistic)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.976805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.973960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4699669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e343.3760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Data processed by E-Views\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the F-test results demonstrate that the probability (Prob) value of the F-statistic is 0.000000, which is considerably lower than the significance level (α) of 0.05 or 5% (0.000000\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This outcome indicates that the null hypothesis (H0) is rejected, while the alternative hypothesis (H1) is accepted. Thus, it can be concluded that the independent variables\u0026mdash;Intellectual Capital (X1) and MSME Credit (X2)\u0026mdash;have a statistically significant combined effect on the rural bank business performance in Jambi Province over the period 2013\u0026ndash;2022.\u003c/p\u003e \u003cp\u003eThe significance of this finding underscores the combined influence of Intellectual Capital and MSME Credit on enhancing the performance and sustainability of rural banks. Intellectual Capital, encompassing knowledge, skills, and innovative capabilities, plays a critical role in creating value and competitive advantage for financial institutions (Chen et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Youndt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Similarly, MSME Credit is crucial for supporting local economies and ensuring financial inclusion, which, in turn, strengthens rural banks' customer base and profitability (Berger \u0026amp; Udell, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Beck et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The strong Prob (F-statistic) outcome suggests that these variables are vital contributors to rural bank performance, aligning with existing literature that highlights their importance in financial stability and growth.\u003c/p\u003e \u003cp\u003eThis result provides robust evidence that both Intellectual Capital and MSME Credit are not only individually impactful but also collectively essential for driving rural bank success in regional economies like Jambi Province, where financial resources and intellectual assets directly support community-based banking activities.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eR test\u003csup\u003e2\u003c/sup\u003e (\u003cem\u003eR-Square\u003c/em\u003e)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe results of the R\u0026sup2; (coefficient of determination) model testing reveal a value of 0.976805 in the panel data regression model. This high R\u0026sup2; value indicates that 97.68% of the variation in the rural bank business performance in Jambi Province can be explained by the independent variables\u0026mdash;Intellectual Capital and MSME Credit\u0026mdash;at a highly significant level (less than 1%). The remaining 2.32% is attributed to other variables not included in the model, suggesting a minimal impact from external factors.\u003c/p\u003e \u003cp\u003eThis high level of explanatory power underscores the substantial influence of Intellectual Capital and MSME Credit on rural bank development. A model with an R\u0026sup2; close to 1, as seen here, implies that the selected independent variables are highly predictive of the dependent variable, signifying their importance in shaping rural bank outcomes (Hair et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The findings are consistent with previous research that highlights the critical role of Intellectual Capital\u0026mdash;through enhanced knowledge, skills, and innovation\u0026mdash;in driving financial performance and organizational resilience in banking institutions (Chen et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Youndt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Similarly, MSME Credit, by supporting local businesses, not only contributes to financial inclusion but also strengthens the operational foundations of rural banks, as evidenced in various studies on MSME financing and rural banking (Berger \u0026amp; Udell, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Beck et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, the R\u0026sup2; value provides robust evidence of the model\u0026rsquo;s effectiveness, affirming that Intellectual Capital and MSME Credit are pivotal factors in the growth and sustainability of rural banks in Jambi Province. This high explanatory power reinforces the importance of strategic investments in these areas for long-term rural bank success.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSecond stage\u003c/b\u003e, \u003cb\u003eanalyze the discussion of research results\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe findings from this study provide compelling evidence that Intellectual Capital and MSME Credit significantly impact the business performance of rural banks in Jambi Province. This result aligns with substantial research highlighting the value of Intellectual Capital in enhancing organizational performance, particularly in knowledge-intensive sectors like banking (Chen et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Youndt et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Intellectual Capital\u0026mdash;comprising human knowledge, relational capital, and structural systems\u0026mdash;enables banks to improve efficiency, foster innovation, and develop competitive advantages that are crucial in highly regulated and competitive environments (Bontis, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The ability to harness Intellectual Capital thus emerges as a key differentiator for rural banks striving to sustain their operations amidst rising competition.\u003c/p\u003e \u003cp\u003eHowever, the study\u0026rsquo;s findings must be considered within the broader context of the rural banking industry in Indonesia, where unique challenges persist. While Intellectual Capital is a positive driver of performance, Kamath (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) argues that structural and regulatory barriers can limit the impact of Intellectual Capital in developing markets. Rural banks, unlike their conventional counterparts, often have limited resources to invest in sophisticated training or knowledge management systems, which constrains their ability to fully leverage Intellectual Capital. Furthermore, regulatory requirements and market conditions may hinder these banks from translating Intellectual Capital into financial gains. This presents a nuanced view: while Intellectual Capital is influential, its potential impact can vary significantly depending on external factors such as policy constraints and market maturity (Holland, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study also underscores the critical role of MSME Credit, a core offering of rural banks, which aligns with the banks\u0026rsquo; mission to support local economic development. Providing credit to MSMEs has been shown to enhance financial inclusion and stimulate economic growth in underserved regions (Beck et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Berger \u0026amp; Udell, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, the competitive advantage of rural banks in this sector is increasingly challenged by larger commercial banks offering KUR loans at significantly lower interest rates, often around 6%. This contrast in lending terms places rural banks at a disadvantage, particularly as they typically offer rates between 15% and 18% to maintain operational sustainability. According to Coleman (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), high interest rates can lead to borrower selection issues, limiting the appeal of rural banks for MSMEs, which are price-sensitive and often opt for lower-cost credit solutions.\u003c/p\u003e \u003cp\u003eMoreover, while MSME Credit positively impacts rural banks' business, the findings raise questions about the long-term viability of rural banks in regions with high commercial bank penetration. Nawaz and Munir (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) suggest that rural banks must innovate and diversify their service offerings to differentiate themselves from commercial banks. This might involve tailoring products specifically to niche segments within MSMEs or expanding non-traditional financial services that commercial banks do not provide. Additionally, policymakers could consider regulatory support that allows rural banks to compete on more equal terms with commercial banks, especially regarding KUR distribution.\u003c/p\u003e \u003cp\u003eFrom a strategic perspective, the study's findings advocate for the professionalization of rural bank employees through enhanced Intellectual Capital. By developing specialization in MSME lending and employing advanced analytical tools, rural banks can better assess borrower risk and identify profitable opportunities (Subramaniam \u0026amp; Youndt, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Yet, this recommendation faces practical challenges. Investing in Intellectual Capital is costly, and rural banks typically operate with limited budgets, which could impact the implementation of such strategic initiatives (Kamath, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Additionally, intellectual capital initiatives, while valuable, may not yield immediate financial returns, which could deter rural banks focused on short-term performance from pursuing these strategies (Edvinsson \u0026amp; Malone, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1997\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study provides a novel contribution to the literature on rural banking by empirically examining the combined impact of Intellectual Capital and MSME Credit on the business performance of rural banks in Jambi Province. While prior research has explored the effects of Intellectual Capital on banking performance in various contexts (e.g., Ismail \u0026amp; Al-Musali, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kamath, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), this study specifically focuses on rural banks, which face unique competitive pressures from conventional banks and policy-driven lending programs such as the People\u0026rsquo;s Business Credit (KUR). The integration of MSME Credit as a key variable, given its importance in rural bank portfolios, adds a unique dimension to the analysis, addressing a gap in the understanding of rural bank resilience in emerging markets. This research uniquely highlights how these variables jointly contribute to rural banks' sustainability amidst competitive challenges, thus offering insights specifically tailored to the rural banking sector in Indonesia.\u003c/p\u003e \u003cp\u003eThe findings of this study carry several important implications for rural bank management and policymakers. For rural bank leaders, the study emphasizes the critical role of Intellectual Capital in enhancing business performance. Rural banks are encouraged to invest in human capital development, particularly by providing specialized training in MSME lending and credit risk assessment. This could enhance employee skills and enable rural banks to develop unique, competitive financial products that cater to the needs of local MSMEs. Furthermore, the significant impact of MSME Credit on rural bank performance underscores the need for rural banks to focus on this segment, potentially by innovating with lower-cost lending solutions or expanding into niche areas not served by commercial banks.\u003c/p\u003e \u003cp\u003eFor policymakers, the study\u0026rsquo;s findings suggest a need to review the KUR program\u0026rsquo;s structure and consider measures that support rural banks in competing on more equal terms with commercial banks. Adjusting regulations to allow rural banks access to some form of subsidized credit for MSMEs, similar to the KUR program, could help balance competition and foster greater financial inclusion. Additionally, policies that encourage partnerships between rural and commercial banks, or incentives for rural banks to adopt technological advancements, could further enhance rural banks' sustainability and reach.\u003c/p\u003e \u003cp\u003eThe social implications of this study are significant, particularly concerning financial inclusion and local economic development. By highlighting the importance of MSME Credit, the research underlines the role of rural banks in providing accessible financial services to micro and small enterprises that may not meet the eligibility criteria for commercial bank loans. The empowerment of MSMEs through credit access has direct benefits for local economies, as it can stimulate job creation, promote entrepreneurship, and reduce poverty levels in underserved areas. Furthermore, the focus on Intellectual Capital development within rural banks points to a need for skills enhancement in the rural workforce, which can elevate the quality of financial services available to communities.\u003c/p\u003e \u003cp\u003eEnhanced Intellectual Capital not only improves rural bank performance but also builds a knowledgeable, professional workforce that can contribute to the broader economic development of rural regions. This investment in human resources can lead to better customer service, stronger community ties, and increased trust in financial institutions, ultimately fostering a more inclusive financial system that supports sustainable economic growth.\u003c/p\u003e \u003cp\u003eIn summary, this study provides actionable insights for rural banks, policymakers, and society by highlighting the critical roles of Intellectual Capital and MSME Credit in shaping the future of rural banking in Indonesia. By addressing these key factors, stakeholders can work towards strengthening rural banks' resilience and supporting economic development in rural areas.\u003c/p\u003e"},{"header":"5. CONCLUSION AND RECOMMENDATION","content":"\u003cp\u003eThis study underscores the pivotal role of Intellectual Capital and MSME Credit in enhancing the performance of rural banks in Jambi Province. In a competitive environment, especially with the expansion of low-interest KUR loans by commercial banks, rural banks face significant pressure to serve MSMEs effectively. Nevertheless, the findings confirm that investing strategically in Intellectual Capital\u0026mdash;through skill development, expertise, and a knowledge-driven workforce\u0026mdash;along with a focus on MSME lending, is essential for rural banks to strengthen their sustainability and competitiveness.\u003c/p\u003e \u003cp\u003eIntellectual Capital is particularly valuable, empowering rural banks to innovate, improve service quality, and adapt to customer needs. Meanwhile, MSME Credit supports entrepreneurship, financial inclusion, and socioeconomic growth in underserved communities. By financing small businesses, rural banks contribute directly to local economic resilience, creating jobs and improving livelihoods, positioning them as essential engines of rural economic development.\u003c/p\u003e \u003cp\u003eTo further develop rural banks, it is recommended that they invest in human capital by offering specialized training in MSME financing and credit risk management, fostering stronger client relationships. Product innovation is also key; rural banks could differentiate themselves by offering flexible loan terms, customized repayment options, or community-centered services that large banks may not provide.\u003c/p\u003e \u003cp\u003eGovernment support is critical in ensuring fair competition, particularly with subsidized credit programs. Policymakers might consider funding options that enable rural banks to offer competitive rates to MSMEs or grants for technological and capacity-building advancements. Investing in digital tools would also enhance operational efficiency and service reach. Strategic partnerships with larger institutions could provide rural banks with additional resources and access to shared technology infrastructure.\u003c/p\u003e \u003cp\u003eThrough these approaches, rural banks in Jambi Province can not only compete but thrive, reinforcing their vital role in empowering MSMEs, fostering economic stability, and driving inclusive growth. Such efforts ensure that rural banks remain essential drivers of regional development, meeting community needs and contributing to a more resilient rural economy.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRESEARCH LIMITATIONS\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study, while providing valuable insights, has several limitations. First, it is limited to rural banks in Jambi Province, which may restrict the generalizability of the findings to other regions with different economic conditions, regulatory environments, and levels of competition. The focus on a single province means that the unique challenges and dynamics faced by rural banks in Jambi may not fully represent those encountered in other parts of Indonesia. Additionally, the study relies on secondary data from financial reports, which provides a quantitative view of performance but may overlook qualitative factors, such as customer satisfaction, employee motivation, or community impact, that could also influence bank performance.\u003c/p\u003e \u003cp\u003eAnother limitation is the timeframe of the study, which spans a period of ten years. Although this allows for a thorough analysis of trends over time, a longer or broader dataset could provide a more comprehensive view of how Intellectual Capital and MSME Credit impact rural bank performance over changing economic cycles. Furthermore, the use of panel data analysis does not fully account for external factors, such as regulatory changes or macroeconomic conditions, which could also influence rural bank performance.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFUTURE RESEARCH\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFuture research could address these limitations by expanding the geographic scope to include rural banks from multiple regions in Indonesia, allowing for a comparative analysis across different local economies. This broader scope could reveal regional differences and provide insights into the specific challenges and opportunities faced by rural banks in diverse settings. Additionally, future studies could incorporate qualitative research methods, such as interviews or case studies, to capture a deeper understanding of the impact of Intellectual Capital on organizational culture, customer loyalty, and community engagement.\u003c/p\u003e \u003cp\u003eResearchers may also consider examining the role of technological advancements and digital banking solutions in supporting rural bank performance, particularly in remote areas where traditional banking infrastructure is limited. Finally, exploring the effects of macroeconomic variables, such as inflation, interest rates, and government policy changes, on rural bank performance could provide a more nuanced understanding of the external pressures that impact their operations. This expanded focus would offer a more comprehensive picture of the factors influencing rural bank sustainability and provide a stronger foundation for policy recommendations that support the growth of rural banks and their contribution to economic development.\u003c/p\u003e \u003cp\u003eIn conclusion, further exploration into these areas would not only enhance the understanding of rural banking in Indonesia but also support the development of strategies that strengthen the resilience and sustainability of rural banks, ensuring their continued role in fostering financial inclusion and local economic growth.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our deepest gratitude to all parties who have supported and contributed to this research. Our sincere thanks go to the Rector of Universitas Muhammadiyah Jambi for the guidance and support provided throughout the research process. Your leadership has been a source of motivation and strength.We also express our appreciation to the Head of the Research and Community Service Institute at Universitas Muhammadiyah Jambi for the guidance, resources, and administrative support that facilitated the smooth progress of this project. Our heartfelt thanks go to the field researchers and key informants for their dedication in gathering data accurately and thoroughly. Their efforts were instrumental in ensuring the quality and reliability of our findings.To the research team and faculty members involved, we thank you for your collaboration, constructive insights, and commitment at every stage. Your professionalism and teamwork were invaluable in bringing this research to completion.Lastly, we offer our gratitude to all respondents who willingly shared their time and insights during data collection. Your participation was essential to achieving meaningful and relevant research outcomes.May this research contribute to the advancement of knowledge and the betterment of society.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of No Conflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest regarding the publication of this research. This study was conducted independently, without any financial or personal interests that could influence the research outcomes. All findings, conclusions, and interpretations presented in this article are solely based on the data collected and analyzed in accordance with ethical research standards. The authors affirm that the research was carried out objectively, with full academic integrity, and that no external party influenced the study\u0026apos;s design, methodology, or results.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlhassan, A. L., \u0026amp; Asare, N. (2021). Profitability in banking: A review of literature and avenues for future research. \u003cem\u003eJournal of Banking \u0026amp; Finance\u003c/em\u003e, 128, 106120. https://doi.org/10.1016/j.jbankfin.2021.106120\u003c/li\u003e\n\u003cli\u003eAsteriou, D., \u0026amp; Hall, S. G. (2015). \u003cem\u003eApplied Econometrics (3rd ed.).\u003c/em\u003e Palgrave Macmillan.\u003c/li\u003e\n\u003cli\u003eBaltagi, B. H. (2013). \u003cem\u003eEconometric Analysis of Panel Data (5th ed.).\u003c/em\u003e Wiley.\u003c/li\u003e\n\u003cli\u003eBank Indonesia. (2010). \u003cem\u003eBank Indonesia Annual Report\u003c/em\u003e. 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Strategic Responses of Rural Banks to KUR Program Competition in MSME Lending. \u003cem\u003eIndonesian Journal of Financial Studies\u003c/em\u003e, 8(1), 57-71.\u003c/li\u003e\n\u003cli\u003eYulianto, A., \u0026amp; Hidayat, R. (2020). Rural Banking Sector in Indonesia: Challenges and Prospects. \u003cem\u003eJournal of Financial and Banking Studies\u003c/em\u003e, 4(3), 45-60.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Universitas Muhammadiyah Jambi","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Intellcetual Capital, MSME Loans, Rural Bank Business in Jambi Province","lastPublishedDoi":"10.21203/rs.3.rs-5845202/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5845202/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the impact of Intellectual Capital and MSME credit on the performance of rural banks in Jambi Province, Indonesia, focusing on how these factors drive business growth. Using Panel Data Regression analysis, the research applies three models\u0026mdash;the Pooled Least Square (PLS), Common Effect Model (CEM), and Random Effect Model (REM)\u0026mdash;to analyze data from rural banks. Results reveal that both Intellectual Capital and MSME credit significantly influence rural bank performance, both individually and collectively. Specifically, Intellectual Capital fosters operational improvements by enhancing the capabilities and professionalism of human resources, while MSME credit supports business growth within these institutions.This study focuses solely on rural banks in Jambi Province, which may limit the applicability of findings to other regions or types of banks. Additionally, the use of cross-sectional data restricts causal inferences. Future research could expand geographically and utilize longitudinal data to explore trends over time.The findings highlight the need for rural banks to invest in human resource development and strategically allocate MSME credit to enhance competitiveness. Policymakers and bank management can leverage these insights to strengthen rural banking performance.By emphasizing the role of rural banks in supporting MSMEs, this study underscores the positive socioeconomic impact of improving credit access in rural communities. Strengthening rural banks can foster local entrepreneurship, reduce financial exclusion, and stimulate regional economic development. This study offers new insights into the combined influence of Intellectual Capital and MSME credit on rural bank performance in Indonesia, particularly in Jambi Province. It is one of the first studies to explore these factors in the context of rural banking, contributing valuable knowledge to the field.\u003c/p\u003e","manuscriptTitle":"Optimizing Intellectual Capital And Msme Credit To Enhance Rural Bank Performance: Evidence From Jambi Province, Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-20 05:42:54","doi":"10.21203/rs.3.rs-5845202/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aa10ef39-5211-4ed4-92c4-9bd602a5e52f","owner":[],"postedDate":"January 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":43098698,"name":"Management"},{"id":43098699,"name":"Finance"}],"tags":[],"updatedAt":"2025-01-20T05:42:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-20 05:42:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5845202","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5845202","identity":"rs-5845202","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}