Loan Management Practices as Key Drivers for the Operation Efficiency of Microfinance Institutions in Northern Mindanao, Philippines

Loan Management Practices as Key Drivers for the Operation Efficiency of Microfinance Institutions in Northern Mindanao, Philippines

Chrisman P. Penaso, Anthony Ly Dagang

Business Administration, Lourdes College, Inc., Cagayan de Oro City, Philippines

DOI: https://doi.org/10.51244/IJRSI.2025.120500162

Received: 12 May 2024; Accepted: 15 May 2025; Published: 18 June 2025

ABSTRACT

In the context of increasing worries over the sustainability and performance of microfinance institutions (MFIs) in the face of increasing credit risks, this research examines the influence of non-performing loan (NPL) management practices on the operational efficiency of MFIs in Northern Mindanao, Philippines. Utilizing a descriptive-correlational design, data were gathered from 200 personnel of different MFIs using a structured questionnaire. The study explores four major loan management areas namely procedures of creditworthiness appraisal processes, loan monitoring and follow-up practices, methods of risk handling, and recovery of loans and how this impact working efficiency, especially in regard to the payment and recovery of loans.  Results confirm high agreement by the respondents on the performance of these practices, and high mean scores point to the most important role of accurate credit judgments and active loan management in maximizing business efficiency. Correlation analysis verifies that all four loan management practices are positively correlated with business efficiency, meaning any improvement in them is linked with enhanced business performance. Moreover, the multiple linear regression analysis confirms the overall significance of the model and identifies that loan management practices that are being analyzed are significant to ascertain operational efficiency. Surprisingly, loan recovery methods were found to be the most important among all, and then loan follow-up and monitoring procedures. In contrast, while in isolation, credit assessment methods and risk management techniques did not reflect statistically significant effects on operational efficiency. The research concludes that the most critical area to enhance the operational performance of MFIs is the innovation of loan recovery techniques and monitoring processes. More importantly, there is an urgent need to improve credit evaluation processes and risk management practices to ensure operational effectiveness.

Keywords:  Credit Assessment Procedures, Loan Monitoring and Follow-up Practices, Risk Management Strategies, Loan Recovery Methods, Operational Efficiency.

INTRODUCTION

Managing Non-Performing Loans (NPLs) remains a critical challenge for microfinance institutions (MFIs), especially in economically vulnerable regions such as Northern Mindanao, Philippines. MFIs serve as key drivers of financial inclusion, offering credit and other financial services to marginalized sectors, including low-income families and microentrepreneurs. However, elevated NPL ratios severely limit their operational capacity, restricting lending activities and undermining efforts to reduce poverty (Illangakoon, 2023). In Northern Mindanao, the NPL crisis is largely fueled by external pressures such as natural disasters, inflation, and inadequate access to formal banking services. These conditions increase the likelihood of loan defaults, contributing to persistently high NPL levels. While global NPL ratios typically range between 5% and 10%, some developing economies report figures exceeding 20% due to heightened economic vulnerability (Qualco Blog, 2023). In the Philippine context, MFIs report an average NPL ratio of approximately 8%, reflecting the compounded effects of these external challenges (Illangakoon, 2023).  From the perspective of the SDGs, effective NPL handling is directly aligned with SDG 1 (No Poverty) and SDG 8 (Decent Work and Economic Growth). chieving these goals depends heavily on the financial health of microfinance institutions (MFIs), as their ability to extend affordable credit to the poor and underserved hinges on sustainable operations. However, ineffective management of non-performing loans (NPLs) threatens this stability, undermining their capacity to fulfill their social mission and avoid exploitative lending practices.

Despite growing recognition of the importance of NPL management in microfinance, a noticeable gap remains between the challenges faced by institutions and the strategies currently employed to address them. This study seeks to close that gap by offering a deeper understanding of the practices that can enhance financial stability and operational effectiveness in the microfinance sector.

With this context, it is essential to examine how microfinance institutions manage their Non-Performing Loan (NPL) portfolios, particularly in regions like Northern Mindanao where economic vulnerabilities persist. Understanding the drivers and consequences of NPLs is not merely a financial inquiry—it is critical for institutions striving to remain viable while serving the poor and underserved. Exploring the factors that lead to high NPL ratios and their operational implications enables MFIs to make informed decisions on lending policies, risk mitigation strategies, and sustainability measures. For MFI leaders and stakeholders, this understanding is key to crafting policies that support financial stability, promote inclusive growth, and uphold the social mission of empowering low-income communities.

LITERATURE REVIEW

Effective management of Non-Performing Loans (NPLs) is a key factor in enhancing the operational efficiency of microfinance institutions (MFIs), particularly in terms of loan collection and disbursement in Northern Mindanao. When NPL levels are poorly managed, institutions face serious challenges such as reduced profitability and limited capacity to extend credit to other clients. This study is anchored on three foundational theories namely Risk Management Theory, Information Asymmetry Theory, and Financial Performance Theory, which provide a framework for understanding the relationship between loan management practices and institutional efficiency.

Risk Management Theory emphasizes the systematic identification, analysis, and mitigation of risks associated with lending operations. In the context of microfinance, effective risk management plays a vital role in reducing non-performing loans (NPLs). As noted by Chambati (2021), microfinance institutions (MFIs) that implement strong risk management frameworks are more likely to minimize defaults by accurately assessing borrowers’ creditworthiness. Oh the other hand, efficient risk management requires the establishment of contingency mechanisms to address potential defaults before they threaten institutional stability. This may include setting aside provisions for bad debts or negotiating internal safeguards with management teams to preserve capital and maintain operational viability (Ledgerwood, 2013). Moreover, risk management strategies must remain flexible and responsive to shifts in economic conditions. During periods of inflation or economic downturns, for instance, MFIs may need to reassess their risk profiles and recalibrate lending practices to preserve portfolio quality (Jain & Mansuri, 2003).

Moreover, Information Asymmetry Theory explains how unequal access to information between borrowers and lenders can lead to adverse selection and moral hazard, both of which contribute to elevated non-performing loan (NPL) ratios. As noted by Dai et al. (2023), when lenders lack complete or accurate knowledge of a borrower’s creditworthiness, they may unintentionally approve loans that are at high risk of default. This issue is particularly evident in microfinance, where some lenders may also lack sufficient financial literacy or due diligence mechanisms, making them vulnerable to misjudgments. To mitigate the effects of information asymmetry, microfinance institutions (MFIs) must implement efficient follow-up and monitoring mechanisms. These systems involve consistent post-disbursement tracking of borrower accounts and timely communication regarding repayment schedules (Ledgerwood, 2013). Regular engagement with borrowers enables MFIs to detect early warning signs of potential repayment issues, allowing for timely interventions such as rescheduling or counseling. Furthermore, maintaining strong client relationships fosters trust and encourages borrowers to disclose financial difficulties, which supports preemptive risk mitigation. These strategies not only reduce the likelihood of default but also contribute to operational efficiency in loan management. Additionally, Financial Performance Theory provides a framework for assessing how operational practices such as credit monitoring, borrower communication, and risk control impact a firm’s profitability and overall financial health (Brigham & Houston, 2022). Within the microfinance context, aligning loan management with sound financial performance principles ensures long-term sustainability and the ability to serve economically vulnerable populations.

These theories are combined to form an integrated conceptual model that explores how various practices influence the management of Non-Performing Loans (NPLs) in microfinance institutions (MFIs).

With the above premise, certain variables in this study will be considered.  The independent variables are Credit Assessment Procedures, Loan Monitoring and Follow-Up Practices, Risk Management Strategies, and Loan Recovery Methods. These variables will be tested if it has an influence on the dependent variable which is operational efficiency in terms of loan collection and releases.

The following figure shows the schematic diagram of the concepts used in this study.

Research Questions

This study aimed to examine how non-performing loan management practices affect the financial performance of microfinance institutions in Northern Mindanao. Specifically, it seeks to address the following questions:

1. What is the participants’ assessment of loan management practices in terms of:

1.1 Credit Assessment Procedures

1.2 Loan Monitoring and Follow-up Practices

1.3 Risk Management Strategies, and;

1.4 Loan Recovery Methods?

2. What is the participants’ assessment of operational efficiency of loan collection and releases?
3. Is there a significant relationship between loan management practices and operational efficiency?
4. Do the participants’ loan management practices significantly influence their operational efficiency?

METHODOLOGY

This study employed a quantitative descriptive-correlational research design to assess the relationship between non-performing loan (NPL) management practices and the operational efficiency of microfinance institutions (MFIs) in Northern Mindanao. A total of 200 employees from various MFIs were selected through stratified random sampling to ensure representation across different institutions and roles within the organizations. This approach aimed to capture a diverse range of perspectives on loan management practices and operational efficiency.

Data were collected using a structured, Likert-Scale questionnaire that consisted of two main sections. The first section assessed four key loan management practices: credit assessment procedures, loan monitoring and follow-up practices, risk management strategies, and loan recovery methods.   The second section evaluated the participants’ perceptions of operational efficiency practices related to loan releases and collections.  The scale is ranging from 1 (Very Low) to 5 (Very High).

Prior to the main data collection, the questionnaire was pre-tested with a small group of respondents to ensure clarity and reliability, and feedback was used to refine the instrument. Data collection involved distributing the questionnaire to participants through both online and paper formats, depending on the preferences of the institutions involved. Participants were informed about the purpose of the study, and their consent was obtained before participation. The data collection period lasted for two weeks, during which follow-up reminders were sent to encourage participation and maximize response rates.

Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) software. Descriptive statistics, including means and standard deviations, were applied to summarize the participants’ assessments of loan management practices and operational efficiency. To examine the relationships between loan management practices and operational efficiency, Spearman Rho correlation analysis was conducted since the data is not normally distributed.  Lastly, multiple linear regression analysis was performed to assess the influence of loan management practices on operational efficiency, allowing for the identification of significant predictors among the independent variables.

RESULTS AND DISCUSSION

Assessment of Loan Management Practices and Operation Efficiency

Table 1 presents the summary of the Mean, Interpretation and Standard Deviation of the Loan Management Practices

Table 1. Summary of the Mean and Interpretations of the Loan Management Practices and Operational Efficiency

Variable	Mean	Interpretation	SD
Credit Assessment Procedures	4.87	Very Highly Practiced	.409
Loan Monitoring and Follow-up Practices	4.55	Very Highly Practiced	.434
Risk Management Strategies	4.61	Very Highly Practiced	.539
Loan Recovery Methods	4.67	Very Highly Practiced	.512
Operational Efficiency	4.68	Very Highly Practiced	.512

The study’s findings indicate that the institution maintains strong loan management practices, with credit assessment, loan monitoring, risk management, and loan recovery all receiving high ratings from respondents. Credit assessment procedures received the highest rating (M = 4.87, SD = 0.409), highlighting the institution’s thorough evaluation of borrowers before approving loans. Patel et al. (2021) emphasized that rigorous financial document checks help minimize the risk of loan defaults​.

Loan monitoring and follow-up practices (M = 4.55, SD = 0.434) were also rated highly, suggesting that the institution actively engages with borrowers to track repayments. Regular monitoring allows early detection of repayment issues, which helps prevent defaults. Nguyen and Tran (2023) stressed the importance of continuous financial health assessments in reducing loan delinquency​. Risk management strategies (M = 4.61, SD = 0.539) were found to be efficient, indicating that the institution has measures in place to address financial risks. Emmanuel et al. (2022) noted that organizations with strong risk management frameworks experience greater financial stability and lower non-performing loan (NPL) ratios​Similarly, loan recovery methods (M = 4.67, SD = 0.512) and operational efficiency (M = 4.68, SD = 0.512) were rated favourably, reflecting the institution’s structured approach to collecting overdue accounts while maintaining good borrower relationships. Lewis and Martin (2022) found that well-defined loan recovery strategies contribute to financial sustainability​.

Overall, the operational efficiency of the institution’s loan management system, particularly in ensuring careful credit assessment procedure, loan monitoring and follow-up practices, risk assessment, and loan recovery method, is evident. Strengthening these practices further will help sustain financial stability and improve overall lending operations.

The Relationship of Loan Management Practices and Operational Efficiency

Table 2 presents the correlation between the independent variables credit assessment procedures, loan monitoring and follow-up practices, risk management strategies and loan recovery methods and the dependent variable operational efficiency.

Table 2 Sperman Correlation RHO The Participants’ Assessment of Operational Efficiency in terms of Loan Collection and Releases.

Correlations
		Credit Assessment Procedures		Loan Monitoring and Follow-up Practices	Risk Management Strategies	Loan Recovery Methods
Operational Efficiency	Spearman Rho	.478**		.688**	.529**	.744**
	Sig. (2-tailed)	.000		.000	.000	.000
**. Correlation is significant at the 0.01 level (2-tailed).

The correlation analysis using Spearman’s Rho reveals significant relationships between Operational Efficiency and the key loan management variables: Credit Assessment Procedures, Loan Monitoring and Follow-up Practices, Risk Management Strategies, and Loan Recovery Methods. All correlations are significant at the 0.01 level (2-tailed), indicating strong statistical associations.

Loan Recovery Methods showed the highest correlation with Operational Efficiency (ρ = .744, p = .000), suggesting that efficient loan collection practices contribute significantly to streamlined operations. This implies that institutions with strong recovery mechanisms are better able to manage resources, reduce financial losses, and maintain liquidity. Lewis and Martin (2022) emphasized that structured and timely loan recovery efforts enhance financial stability and improve operational performance​.  Loan Monitoring and Follow-up Practices also exhibited a strong correlation with Operational Efficiency (ρ = .688, p = .000). This suggests that consistent monitoring and borrower engagement contribute to improved operational workflows by reducing late payments and defaults. Nguyen and Tran (2023) noted that institutions with proactive loan monitoring systems experience fewer repayment issues, leading to smoother financial operations​.

Risk Management Strategies demonstrated a moderate correlation with Operational Efficiency (ρ = .529, p = .000). This indicates that institutions that implement strong risk mitigation policies, such as credit risk assessment and diversified lending portfolios, tend to operate more efficiently. Emmanuel et al. (2022) found that financial institutions with sound risk management practices report lower non-performing loan (NPL) ratios and improved operational outcomes​.  Credit Assessment Procedures showed the lowest but still significant correlation with Operational Efficiency (ρ = .478, p = .000). While thorough credit evaluations help prevent lending to high-risk borrowers, their direct impact on operational efficiency may be less pronounced compared to monitoring, risk management, and recovery strategies. Patel et al. (2021) highlighted that while credit assessment is crucial in reducing loan defaults, its influence on day-to-day operations depends on how well it integrates with overall loan management strategies​.

The Influence of Loan Management Practices on Operational Efficiency

Table 3 presents the linear regression analysis of the participants assessments of the loan management practices in terms of credit assessment procedures (CAP), loan monitoring and follow-up practices (LMFP), risk management strategies (RMS) and loan recovery methods (LRM)towards the operational efficiency of MFIS.

Table 3.  Regression Analysis of the Participants’ Loan Management Practices towards the MFI’s Operational Efficiency (OE)

	Unstandardized Coefficients		Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
(Constant)	.324	.207		1.57	.119
Credit Assessment Procedures (CAP)	-.015	.059	-.014	-.259	.796
Loan Monitoring and Follow-up Practices (LMFP)	.359	.050	.372	7.133**	.000
Risk Management Strategies (RMS)	-.068	.056	-.070	-1.22	.225
Loan Recovery Methods (LRM)	.663	.067	.631	9.89**	.000
Model Summary R = .858          R2 = .736        Adjusted R2 = .731       F = 136.18**       p = .000

**significant at 0.01 level

The result confirms that the overall regression model, when all independent variables (CAP, LMFP, RMS, and LRM) combined, is highly significant (F = 136.18, P = .000), explaining 73.6% of the variation in Microfinance Institutions’ (MFI) operational efficiency (OE). The remaining 26.4% of the variation is due to other factors not included in the model, which can be included in future studies.  Moreover, this indicates that the loan management practices used in this study play a crucial role in shaping operational efficiency, reinforcing the idea that well-structured lending, monitoring, and collection strategies contribute to operational efficiency.

The regression analysis shows that Loan Monitoring and Follow-up Practices (LMFP) and Loan Recovery Methods (LRM) are the strongest predictors of Operational Efficiency, both with significant positive effects (p = .000). LMFP (B = .359, t = 7.133) suggests that consistent borrower engagement improves efficiency, while LRM (B = .663, t = 9.89) highlights the impact of efficient loan collection on overall operations.  Credit Assessment Procedures (CAP) and Risk Management Strategies (RMS), however, were not significant predictors (p > .05), indicating that while important, they may not directly influence operational efficiency in this model.  May scholars confirmed these results.  Hassan (2021), states that institutions with well-defined recovery mechanisms experience fewer defaults and greater liquidity, allowing them to expand services to more borrowers. Likewise, Serrano-Cinca et al. (2016) contend that strong loan recovery techniques improve the financial performance and guarantee long-term sustainability.  On the other hand, monitoring is most critical in financial systems where borrowers might not be aware of organized repayment schedules. A study conducted by Cull et al. (2018) indicates that timely reminders are a valuable resource in minimizing delayed payments because timely reminded borrowers are more likely to meet their payment obligations. Additionally, institutions that implement borrower-centered monitoring systems, including personalized check-ins and automated alerts, tend to see improved loan performance and overall institutional efficiency.

To the contrary, Credit Assessment Procedures (P =.796) and Risk Management Strategies (P =.225) did not  have statistically significant effects on operational efficiency. Interview responses, however, indicate that these practices, even if necessary, may have more nuanced effects. Participants reaffirmed the necessity of a balance between tight credit assessments and financial inclusion, one warning against being too tight in credit policies that can push out good borrowers. Second, this agrees with Ledgerwood’s (2013) caution against the danger of over-tightening credit policies, citing the need for MFIs to adopt more flexible strategies using non-conventional information. While credit evaluation is important in determining the borrower’s eligibility, its effect on operating efficiency does not seem to be immediate. Ledgerwood (2013) says that too tight credit policies, by lowering the risk, may also restrict financial inclusion by deterring otherwise creditworthy borrowers. This is an issue of interest to MFIs.  Lending facilities may end up losing borrowers who, with some counseling and financial training, are still good customers if they value stringent screening more than transparency.  Likewise, Risk Management Measures were not found in this study to have the capability to materially contribute to operational efficiency. While risk mitigation remains a core function of any financial institution, its efficiency is largely contingent upon how seamlessly it is integrated into everyday lending and collection operations. Hermes and Lensink (2011) argue that many MFIs adopt reactive risk models rather than proactive strategies, making it difficult to translate risk management practices into measurable operational gains. This could be why risk-based policies alone may not necessarily have improved efficiency in this study.

CONCLUSIONS

The study affirms the relevance of Risk Management Theory, Information Asymmetry Theory, and Financial Performance Theory in understanding how loan management practices influence operational efficiency in microfinance institutions (MFIs). High ratings in risk evaluation and monitoring support Risk Management Theory, while challenges in collateral and documentation highlight the need for better borrower-institution communication, reflecting Information Asymmetry Theory. The strong link between loan practices and efficiency upholds Financial Performance Theory.

Among the practices, loan recovery and follow-up procedures emerged as the most critical to operational efficiency. Structured recovery systems not only ensure timely payments but also foster strong borrower relationships, reducing non-performing loans and promoting financial sustainability. Likewise, active monitoring helps detect repayment issues early, improving both borrower engagement and repayment rates.

While credit assessment and risk mitigation are essential for sound lending, their direct impact on operational efficiency was minimal. Thus, MFIs should prioritize strengthening their monitoring and recovery strategies, as these have the most immediate and significant effect on performance.

RECOMMENDATIONS

Based from the above conclusions, the following are recommended:

1. To Financial Microfinance Institutions

1.1 Enhance Loan Recovery Techniques. Given that loan recovery practices were identified as the most significant predictor of operational efficiency, MFIs should invest in developing and implementing automated payment tracking systems. These systems can facilitate real-time monitoring of borrower payments and enable timely interventions when delays occur. Additionally, establishing clear communication protocols, such as sending timely reminders about overdue accounts, will help keep borrowers informed and engaged.

1.2 Strengthen Loan Monitoring and Follow-Up Processes. The findings highlighted the importance of loan monitoring and follow-up practices in supporting operational performance. MFIs should implement routine borrower check-ins and regular assessments of borrowers’ financial statuses. This proactive approach can help identify potential repayment issues early, allowing institutions to address them before they escalate. Leveraging technology, such as automated reminders for due dates, can further assist borrowers in managing their loans efficiently.

2. To Loan Managers. Loan monitoring and follow-up processes can be enhanced through routine borrower check-ins. Regular assessments of a borrower’s financial status allow for proactive management of potential repayment issues before they escalate. Leveraging technology such as automated reminders for due dates helps borrowers stay on track. Financial literacy workshops and advisory services further equip borrowers to manage their loans responsibly.
3. To Credit Officers. Improving clarity on collateral requirements can be achieved by developing standardized guidelines that clearly explain collateral expectations. This helps borrowers understand their obligations before taking on debt. Furthermore, equipping credit officers with communication training ensures that these requirements are conveyed clearly, reducing misunderstandings and building borrower trust.
4. To Loan Officers. Enhancing communication on loan restructuring options can be pursued by establishing robust channels to inform borrowers about available alternatives. This can include individual counseling sessions or group seminars. Preparing a clear and comprehensive information package about the restructuring process and requirements can also guide borrowers through financial hardship, offering them practical solutions.
5. To All Future Researchers. Conducting longitudinal studies to assess the long-term impact of loan management practices on operational efficiency is suggested. Also, investigating the differences in loan management practices and operational efficiency comparative analysis across various types of financial institutions and using qualitative methods to gain deeper insights into the experiences of borrowers and staff regarding loan management practices and their perceived impact on operational efficiency can also be considered.

Compliance with Ethical Standards

Prior to the start of the study, ethical clearance was first secured through a visit to the Lourdes College Research Ethics Committee (LC REC). This was to ascertain that all research work pertaining to it was at par with the desired ethical standards in carrying out research on human subjects.

Following approval, data were collected from microfinance institutions (MFIs) employees in Northern Mindanao. Informed consent was also obtained from participants through explanation of research purposes, procedures, and voluntariness of study participation in accordance with Rahaman et al.’s (2023) research ethics. Participation was guaranteed so that any withdrawal or participation decision would be unable to affect their work status or their respective institutions’ positions. Confidentiality and anonymity of the respondents were ensured throughout, and the responses were anonymized by personal codes while data was saved securely.

200 employees with roles that were directly engaged in loan management, credit evaluation, and recoveries across different departments of the MFIs were chosen by applying random sampling for a representative and varied sample. To ensure standardized data collection, Likert-scale-based questionnaires were made available to respondents to measure variables such as loan management practices, operating efficiency, and corresponding organizational variables. Respondents were given one week’s time to return the questionnaires, reminders having already been issued to stimulate response rates.

The survey format was kept brief and clear to capture spontaneous impressions. The used Likert scale was “Very High” to “Very Low,” allowing for quantitative analysis of attitudes and experience. The items were matched to loan process, risk management, and operational effectiveness related constructs based on validated literature scales.

Consistent with the Belmont Report of 1979, respect for persons, beneficence, and justice were the bases for the study. As a guarantee of confidentiality, a code number specific to each participant was used for their response, and the data were available only to the researcher. Participants were informed that their involvement was voluntary and no incentive in terms of money or otherwise would be provided.

After the collection of data, completeness and clarity of response were checked. Incomplete or unclear data were made clear with subsequent communication with the participant to the extent possible. Data were analyzed using SPSS software for descriptive statistics, inferential statistics, and correlation analysis to establish associations between loan management practices and operating efficiency.

In accordance with ethical considerations, the participants received a minor debriefing upon completion of the process of collecting data, describing the reason for the research and summarizing the findings to promote openness and appreciation of their contribution. As a whole, the research abided by the norms of institutional ethics and insisted on the participants’ rights, well-being, and confidentiality of concern.

ACKNOWLEDGMENTS

I would like to extend my heartfelt gratitude to those who have supported me throughout the journey of completing this research paper.

First and foremost, I would like to express my sincere appreciation to my thesis writing 1 & 2 instructors, Dr. Miguela Napiere and Dr. Cyril C. Chavez respectively, for their invaluable guidance, encouragement, and insightful feedback. Their expertise and dedication have greatly influenced this study’s direction and have inspired me to strive for excellence.

I am equally thankful to my thesis advisor, Dr. Anthony Ly B. Dagang, whose support and mentorship have shaped my understanding of the research process. His constructive criticism and thoughtful suggestions have significantly improved the quality of this work.

I would also like to acknowledge the management and staff of Microfinance Institutions, particularly those in the loan management department, for their cooperation and willingness to participate in this research. Their insights and experiences provided a rich foundation for understanding non-performing loan management practices.

Special thanks go to the participants who took the time to complete the surveys. Their willingness to share their experiences and perspectives has greatly enriched this study.

Additionally, I am grateful to my colleagues and peers for their support and constructive feedback during the development of this paper. Their encouragement has been a source of motivation.

Finally, I would like to thank my family and friends for their unwavering support and understanding throughout this journey. Their belief in my abilities has inspired me to persevere.

This research would not be possible without the significant individuals who have contributed to the success of this research. Indeed, I am deeply appreciative of their support. Thank you all!

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