Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3, 243-257 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 30 December 2024; Revised: 17 February 2025; Accepted: 20 February 2025; Published: 4 March 2025 * Correspondence: farikhiamrin@gmail.com Project-based Sukuk issuance for sustainable toll road refinancing in Indonesia: A confirmatory factor analysis Amrin Farikhi1*, Christiono Utomo2, Rifki Ismal3 1,2Department of Civil Engineering, Institut Teknologi Sepuluh Nopember, Indonesia; farikhiamrin@gmail.com (A.F.) christiono@ce.its.ac.id (C.U.) 3Bank of Indonesia and Tazkia Institute, Indonesia; rifki_ismal@yahoo.com (R.I.) Abstract: This paper examines the factors determining the issuance of project-based Sukuk for sustainable refinancing of toll road development in Indonesia. A questionnaire survey was used to obtain the factors that determine the issuance of project-based Sukuk. Experts and practitioners were consulted to identify and analyze the factors influencing the issuance of project-based Sukuk. The questionnaire participants included experienced infrastructure practitioners, regulators, and researchers. The results show that twelve indicators explain the decision to issue project-based Sukuk. Among them, the exchange rate is the most significant influence, with a loading factor value of 0.935, indicating that exchange rates affect Sukuk issuance, followed by the high cost of funds with a value of 0.857, which suggests that the high cost of funding is a strong reason for companies to choose Sukuk as an alternative for infrastructure refinancing. Other indicators, such as the inflation rate with a value of 0.835 and firm competence with a value of 0.809, also have a significant influence. This paper provides valuable findings and references for a toll road project-based Sukuk refinancing scheme to take over a stalled toll road project. The revealed factors benefit toll road stakeholders, such as business entities and the government, when preparing a refinancing scheme. Keywords: Factor Analysis, Indonesia, Project-based Sukuk, Refinancing, Sustainability, Toll Road. 1. Introduction Indonesia's toll road development program requires a lot of funds. However, due to the current Government's limited budget, it must find an alternative financing scheme to support Indonesia's accelerated infrastructure development program. Creative financing schemes are needed to fund the toll road infrastructure projects by involving private parties or business entities to invest directly in toll road infrastructure. The toll road investment requires robust infrastructure investment characteristics because it needs to have fixed assets, high funding requirements to be provided, and high up-front capital requirements. However, the current conditions faced by business entities that have invested in toll road construction are having problems regarding toll road funding support. Meanwhile, the government still hopes for the participation of business entities in accelerating infrastructure by continuing the construction of the toll road that it has started. Unfortunately, the construction of the ongoing toll road sections is stalled due to the lack of financial support. Indeed, the sustainability of toll road financing is a solution that must be immediately sought. Currently, most of the toll road financing in Indonesia uses conventional schemes. Meanwhile, Sharia (Islamic principle-based) funds have not been appropriately maximized for infrastructure financing, while Sharia finance has great potential to contribute to Indonesia's infrastructure development. Sharia financing schemes are also the right instrument for infrastructure financing because the fundamental asset is the project itself, which can be used to fund infrastructure investment. 244 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate The Sharia requirement to use underlying assets in its funding schemes gives it better security and investment options for investors [1]. Investment in infrastructure with Sharia schemes is not only limited to Muslims but also the non-Muslims both domestically and internationally [2]. Recently, the Sharia financial industry is gaining momentum sharia-compliant investments on the rise in Muslim countries and globally [3]. As such, the solution for the ongoing toll road infrastructure financing is resumed or refinanced by using a Sharia scheme particularly project-based Sukuk. According to Hussain and Khalil [4] the Sharia capital markets play a vital role in providing long-term funding for economic growth. One of its main instruments is sukuk, which is used to raise funds from the public and assist organizations in financing. The increase in the issuance of Sharia securities in the Southeast Asian Sharia capital market has reflected a rise in economic growth rates, support economic growth and market development [5]. This study will examine factors influencing the issuance of project-based Sukuk, which will be used to refinance toll road development in Indonesia. 2. Literature Review Utami, et al. [6]Empirical research shows that Sukuk issuance in Indonesia is influenced by company profitability, sharia compliance, Sukuk yield, company age, and inflation rate. Abdullah, et al. [7] increase in interest rates reduces the value of fixed-income Sukuk, which means interest rate influences Sukuk. Sharia compliance is also considered a key risk in Sukuk Issuance for funding infrastructure projects. Said and Grassa [8] explained the implementation of some variables in macroeconomics that influence Sukuk issuance, such as political stability. Kalimullina [9] stated that the exchange rate impacts the performance and size of the Sharia finance market. Furthermore, Saad, et al. [10] Risk of default on bonds and sukuk can be reduced by analyzing the impact of GDP levels on maintaining corporate sustainability. Ahmad, et al. [11] Sukuk affect GDP, while GDP increases producer and consumer prices. Furthermore, Bacha and Mirakhor [12] stated that Sukuk returns depend on GDP growth if the project is non-revenue-generating and on project revenues if it is revenuating, thus avoiding the associated risks. Rusgianto and Ahmad [13]stated that government incentives attract investors and increase trading. Jobst, et al. [14] explained the Sukuk market has attracted widespread interest from issuers in various countries, although it still faces legal and regulatory hurdles. Continued efforts are needed to overcome the economic, regulatory and legal uncertainties. Bo, et al. [15] found Sukuk Issuance in China faces challenges such as regulation, tax, stamp duty and investor protection, the rule of law, and establishing the Sharia supervisory committee. Bacha and Mirakhor [12] explained that the innovative Sukuk can break the borrowing, leverage, and vulnerability cycle. Leverage magnifies economic fluctuations, causing financial distress and currency depreciation. Foreign currency-denominated projects are often burdened with large debts, requiring government subsidies for continued operations. Kalimullina [9] argued that the unfriendly tax regime makes Sharia investors subject to higher taxes than bank depositors. Value-added tax increases financing costs, while the lack of Sharia mediation, regulation and infrastructure support in Russia may affect investment in Sharia financial markets. Saad, et al. [16] described that Sukuk trading in the Malaysian capital market is on a larger scale than conventional bonds, which influences Sukuk's attractiveness. While Nagano [17] argued that Sukuk Issuance tends to be chosen based on market momentum and accessibility, which is related to trading volume and liquidity in the secondary market. Ahmed, et al. [1] studied how the issuing company's earnings outlook influences investor reaction, with lower outlooks tending to elicit a negative response. Duqi and Al-Tamimi [18] indicated that sukuk characteristics are the main factors influencing UAE investors' interest, followed by religious factors, return expectations and information availability. Nagano [19] concluded that investors high value companies tend to Sukuk market or has a high reputation. Guermazi [20] explored that rating agencies assess Sukuk, encouraging issuance quality and corporate transparency. Ahmed, et al. [1] stated that investors consider the firm's value and competence and investors value Sukuk from low-prospect companies less. Bo, et al. [15] argued that 245 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate enhancing investor education, especially for Sukuk investment, operational mechanisms, and risk behaviours, is the most important in influencing Sukuk. Rarasati, et al. [21] explored the factors related to infrastructure project financing schemes and Sharia finance concepts; both knowledge of infrastructure business and Sharia finance should be well-known by all stakeholders. Grassa and Miniaoui [22] identified that large and long-standing companies prefer conventional bonds. Rarasati, et al. [23] explored the lack of understanding and preparation hampers financing of Islamic projects in infrastructure. Biancone and Radwan [3] stated that the lack of expert human resources in Sharia finance with a financial background and sharia knowledge. Guermazi [20] shows that the Company balances Sukuk costs with religious and social benefits. Warsame and Ireri [24] concluded that Attitude has a significant effect on the intention to use Sukuk, while religiosity alone is not enough. Quality of service and understanding of Sukuk features play an important role. Increasing awareness among Muslims and non-Muslims can encourage the use of Sukuk. Saad, et al. [10] stated that institutional investors reduce the risk of Sukuk default. Saad, et al. [16] investigated that the Board of Directors, with clear rights and responsibilities, can focus on long-term investment decisions of Sukuk, reducing the risk of default and lowering the yield spread. This decision supports long-term financial planning, attracting more institutional investors. Paltrinieri, et al. [25]analyzed that low growth companies tend to issue Sukuk to expand the investor base and control funding costs. Based on Nagano [17] firms approach the Sukuk market with finance and stock valuations are low. Ahmed, et al. [1] stated that small or risky companies tend to issue Sukuk because of more flexible market access. Halim, et al. [26] indicated that sukuk structure is determined by the financial capacity of the company, not religious identity. Companies with high agency costs, companies with high free cash flow and growth tend to issue Sukuk. Bacha and Mirakhor [12] argued that the problem with debt financing is that the terms of service are not aligned with the risks or cash flows of the project. Pribadi and Wibowo [27] this study uses a logit model to test the effect of company size and fixed assets have a positive effect on Sukuk issuance. Grassa and Miniaoui [22] proved that companies tend to issue Sukuk to obtain larger and longer-term debt than conventional bonds. Guermazi [20] using the sukuk is negatively related to profitability. 3. Methods 3.1. Participants In this study, the characteristics of respondents are experts and practitioners who can provide correct and objective opinions or answers to empirical problems and have professional experience in specific fields of toll road infrastructure, capital market, and Sharia financing. Experts who can explain constructive and critical published opinions on developing problems can provide justification or opinion on solutions because of their experiences working in areas directly related to the problem and supported by a level of education and specific technical skills.The total number of selected experts and practitioners was 30, with 26.67 % from academics, 13.37 % from regulators, 16.67 % from conventional financing boards, 20 % from Sharia financing boards, and 23.33 % engaged in toll road business entities. Table 1 illustrates respondents from different sectors. Table 1. Distribution of respondents. Roles of Respondent Frequency Percentage (%) Academics 8 26.67 Regulator 4 13.33 Conventional Financing Board 5 16.67 Sharia Financing Board 6 20.00 Toll Road Business Entity 7 23.33 Total 30 100 246 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate The questionnaire respondents were distributed in years of experience, last education, and job level position. As shown in Table 2, the working experience of respondents was 3.33 % less than 11 years, 40 % between 11-20 years, 40 % between 21-30 years, and 16.67 % more than 30 years. In addition, the last education of the respondents was 6.67 %, 63.33% masters, 30% doctorates, the rest bachelor's degrees. Questionnaire participants included infrastructure industry practitioners and regulators, and researchers from colleges, with 40 % at the director/commissioner level, 33.33 % at the general manager level, and 26.26 % at the professor and associate professor. Table 2. Respondent characteristics. Respondent characteristic Frequency Percentage (%) Years of experience Less than 11 years 1 3.33 11 – 20 years 12 40.00 21 – 30 years 12 40.00 More than 30 years 5 16.67 Total 30 100 Last Education Bachelor Degree 2 6.67 Master Degree 19 63.33 Doctoral 9 30.00 Total 30 100 Job Level Position Director/Commissioner 12 40.00 General Manager 10 33.33 Professor/Associate Professor 8 26.67 Total 30 100 3.2. Materials This paper mainly focuses on the questionnaire on three key elements related to the knowledge, experience, and views on Islamic infrastructure project financing, particularly on toll road development in Indonesia. The respondents were informed earlier about their selection in this research and the questionnaire's objective. The respondents were also free to ask the researchers questions and share their experiences and views on Islamic infrastructure project financing and toll road development in Indonesia. Respondents received an invitation with an information letter and a link to the questionnaire. They could complete it online at their convenience. Respondents who had not completed it were initially reminded by phone. 3.3. Procedure Confirmatory Factor Analysis (CFA) was performed in R Studio R.4.4.1 Package Lavaan & SemPlot. Hair Jr, et al. [28] explained that CFA is an analytical method used to test the extent to which several measured variables or indicators can effectively describe a particular factor. In CFA, factors are often called constructs, abstract concepts or latent variables that cannot be measured directly. Therefore, constructs need the help of measurable variables to represent their characteristics. The CFA is formulated as follows: 𝑋 = Λ𝜉 + Ψε (1) Where : X = matrix (p x 1) from indicators ξ = matrix (g x 1) from construct variable ε = matrix (p x 1) from error Λ = matrix (p x g) from loading between indicator and construct Ψ = diagonal matrix (p x p) from loading between indictor and error 247 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate p = amount of indicators g = amount of construct Hair Jr, et al. [28]explained that CFA does not have the best single statistical test to illustrate the power of estimating a model. Instead, several combinations of model fit measures have been developed, producing two perspectives measurement, model fit measures and overall model fit measures. CFA helps ensure that the indicators used are relevant and can accurately describe the construct. Validity can be evaluated through several metrics, such as: 1. Standardized Loading: Loading values above 0.5, ideally more than 0.7, indicate a strong relationship between the indicator and the construct. 2. t-value: Statistical value that shows the significance of the relationship between the indicator and its construct. This value must be greater than the critical value at a particular significance level. However, it can also use the p-value, where a significant indicator measures the construct when the p-value <0.05. CFA also evaluates indicators' internal consistency level when describing a construct. Reliability can be calculated using metrics such as Construct Reliability (CR). When the value of CR is more than 0.7, these indicators have good consistency. CR is formulated as follows: 𝐶𝑅 = (∑ 𝐿𝑖 𝑛 𝑖=1 ) 2 (∑ 𝐿𝑖 𝑛 𝑖=1 ) 2 +∑ 𝑒𝑖 𝑛 𝑖=1 − (∑ 𝐿𝑖 𝑛 𝑖=1 ) 2 (∑ 𝐿𝑖 𝑛 𝑖=1 ) 2 +∑ (1−𝐿𝑖) 𝑛 𝑖=1 (2) Where : Li = standardized loading value e = measurement error value for a construct with a value of 1 – L Hair Jr, et al. [28] stated that the CR value must exceed 0.7. Several goodness-of-fit methods, namely Absolute Fit Measure and Increment Fit Measure, are used to assess the model's overall suitability. An absolute fit measure calculates the overall model fit using several criteria as follows: 1. Chi-Square Statistics: Chi-square measures the covariance of deviations; the model is appropriate if the value is small or P > 0.05. 2. Goodness of Fit Index (GFI): GFI is used to estimate Maximum Likelihood Estimation (MLE) and Unweighted Least Square (ULS) and then generalized to other estimation methods. The GFI value indicates the model fit, with ≥ 0.90 considered good. GFI is formulated as follows: 𝐺𝐹𝐼 = 1 − 𝐹𝑘 𝐹0 (3) Where : Fk = Minimum value of the fit function after SEM modelling with k degrees of freedom (S-Σk) F0 = The fit function shows the model's fit when the parameters are 0. High GFI values indicate good model fit. GFI ≥ 0.90 good, 0.80–0.90 marginal [28]. 3. Root Mean Square Error of Approximate (RMSEA): RMSEA ≤ 0.05 indicates a close fit, 0.05–0.08 indicates a good fit [29] RMSEA is formulated as follows: 𝑅𝑀𝑆𝐸𝐴 = √ 𝑑 𝑑𝑓 (4) Where : d = value obtained from the formula 𝜒2−𝑑𝑓 𝑁−1 (5) 𝜒2 = value of the 𝜒2 test statistic being analyzed df = degrees of freedom of the analyzed model test N = number of samples 248 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate Incremental fit compares models. AGFI, as an analogue of R² in regression, is considered good if its value is ≥ 0.9 [30]. The model suitability index is in Table 3. Table 3. Model feasibility testing index. No. Goodness of fit index Cut off value 1 P-value Chi-Square ≥0.05 2 GFI ≥0.90 3 RMSEA ≤0.08 4 AGFI ≥0.90 Source: Hair Jr, et al. [28]. The selection of measurement criteria should meet at least one of the increment fit measures and one of the absolute fit measures. Furthermore, the measurements used are χ2 and degree of freedom, GFI, RMSEA, and AGFI, which provide sufficient information [28]. 3.4. Data Analysis This study uses CFA to determine the factors influencing the decision to issue project-based Sukuk. First-order CFA analysis uses 28 indicators that are thought to influence the decision. First-order CFA analysis also determines each indicator's validity, reliability, and contribution from the latent variable in the decision to issue project-based Sukuk. The indicators are shown in Table 4. Table 4. Indicators that Influence the Decision to Issue Sukuk. Code Indicators (Factors) X1 Inflation X2 Interest Rate X3 Political Stability X4 Exchange Rate X5 Gross Domestic Product X6 Government Regulation X7 Tax Support and Incentives X8 Rule of Law X9 Government Guarantee X10 Trading Volume & Liquidity in the Secondary Market X11 Yield X12 Firm Reputation X13 Firm Age X14 Sharia Knowledge of Investor X15 Firm Size X16 Firm Competence X17 Firm Experience X18 Sharia Knowledge of Firm X19 Religious Values X20 Sharia Compliance Level X21 Behaviour and Characteristics X22 Role of Institutional X23 High Cost of Fund X24 Stock Undervalue X25 Cash Flow X26 Fixed Asset X27 Financial Distress X28 Firm profitability 249 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate The indicator estimation results are shown in Figure 1. Figure 1. Standardized Estimate Value of the CFA Model. 250 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate Figure 1 presents a decision path diagram to issue project-based Sukuk, shown by its standardization value. Next, model suitability testing determines whether the resulting model is feasible. The model feasibility test can be seen in Table 5 on the P-value chi-square, GFI, RMSEA and AGFI. The results of the analysis show P Chi-square and RMSEA do not match the cut-off velocity; the resulting P-value < 0,05, and the RMSEA is 0.385, it is more significant than 0.08, so the resulting model is not fit. In obtaining a fit model, the first step is eliminating indicators that are not valid and reliable. Table 5 shows the validity results with standardized factor loading values and p-values and reliability with composite reliability values. An indicator is declared valid if the standardized factor loading Values ≥ 0.5 and p < 0.05 indicate significance. In this first estimate, there are several invalid indicators because they have a standardized factor loading value of less than 0.5 and a p-value of more than 0.05; this indicator is removed from the model. The reliability test shows a CR value of 0.699; the value is more than 0.6, so reliability is met. Table 5. CFA Analysis Results. Loading Factor Indicator (Factor) Standardise Loading Factor P-Value X1 0.845 0.000 X2 0.081 0.665 X3 -0.542 0.002 X4 0.906 0.000 X5 0.181 0.332 X6 -0.156 0.402 X7 0.788 0.000 X8 -0.53 0.002 X9 0.503 0.004 X10 0.579 0.001 X11 -0.494 0.005 X12 -0.161 0.389 X13 0.634 0.000 X14 0.666 0.000 X15 0.515 0.003 X16 0.736 0.000 X17 0.031 0.869 X18 0.076 0.685 X19 0.391 0.030 X20 -0.61 0.000 X21 0.755 0.000 X22 -0.542 0.002 X23 0.872 0.000 X24 0.751 0.000 X25 0.497 0.005 X26 -0.335 0.066 X27 0.68 0.000 X28 -0.353 0.052 Composite Reliability 0.699 Goodness of Fit P-value (Chi-Square) ≥0.05 0.000 GFI ≥0.90 0.980 RMSEA ≤0.08 0.385 AGFI ≥0.90 0.975 Next, the model is re-estimated until valid and reliable indicator results are obtained, as in Figure 2. 251 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate Figure 2. Standardise Estimate Value of CFA Model re-estimation. The validity and reliability tests on the re-estimated model are valid and reliable, but the model still does not fit the feasibility test. It can be seen from the four test criteria that the value does not match the cut-off value. Chi-square P value (0.000) < 0.05, the GFI of 0.821 is less than 0.9, the RMSEA value is 0.232, which is still more than 0.08, and the AGFI of 0.682 is less than 0.9, so the model produced in this re-estimation is not fit. 252 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate Table 6. Results of Re-estimation CFA Analysis. Loading Factor Indicator (Factor) Standardise Loading Factor P-Value X1 0.825 0.000 X4 0.933 0.000 X7 0.753 0.000 X10 0.638 0.000 X13 0.587 0.001 X14 0.688 0.000 X16 0.783 0.000 X21 0.755 0.000 X23 0.849 0.000 X24 0.786 0.000 X27 0.650 0.000 Composite Reliability 0.829 Goodness of Fit Goodness of Fit Index Cut off Value Value P-value (Chi-Square) ≥0.05 0.000 GFI ≥0.90 0.821 RMSEA ≤0.08 0.232 AGFI ≥0.90 0.687 Ensuring the validity and reliability of indicators. However, the resulting model still does not fit; modifications need to be made, where the measurement errors on several items are freed to correlate. The re-estimation results are in Figure 3. 253 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate Figure 3. Standardized Estimate Value of the Modified CFA Model. Table 7 shows the results of re-estimation after modification by correlating several measurement errors to obtain a fit model. The modification results show that the cut-off values determine all model suitability criteria. The P-value chi-square is 0.525, the value is more significant than 0.05, meaning good fit; the GFI with a value of 0.952 is more significant than 0.9, meaning good fit, the RMSEA is 0.000; the value is less than 0.08, meaning good fit, and the AGFI is 0.867, the value is between 0.8 and 0.9, meaning marginal fit. In the model suitability test, the resulting model meets the criteria the requirements of a reasonable or feasible model. Based on a series of tests on the validity, reliability, and suitability of the model of 28 indicators, which are thought to describe the decision to issue project- based Sukuk, Table 7 shows that 12 indicators can describe the decision to issue project-based Sukuk. 254 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate Table 7. Results of Modified Re-estimation CFA Analysis. All CFA indicators are shown in Figure 4 significantly contribute to the decision to issue project- based Sukuk because the standardized loading factor values are all above 0.5. Figure 4. Standardise Loading Factor on Influential Indicators/Factors. 4. Discussion The results of the CFA displayed that twelve indicators describe the decision to issue project-based Sukuk-based. Exchange rate shows the most significant influence with a loading factor value of 0.935, indicating that fluctuations in currency exchange rates are the main factor in the decision to issue Sukuk, followed by the high cost of funds with a value of 0.857, which indicates that the high cost of funding is a strong reason for companies to choose Sukuk as alternative financing. Other factors, such as 0.586 0.609 0.663 0.672 0.715 0.740 0.790 0.809 0.835 0.857 0.935 Firm Age (X13) Financial Distress (X27) Sharia Knowledge of Investor (X14) Trading Volume & Liquidity in Secondary Market (X10) Tax Support and Incentives (X7) Behavior and Characteristics (X21) Stock Undervalue (X24) Firm Competence (X16) Inflation (X1) High Cost of Fund (X23) Exchange Rate (X4) Standardize loading factor Loading Factor Indicator (Factor) Standardise Loading Factor P-Value X1 0.835 0.000 X4 0.935 0.000 X7 0.715 0.000 X10 0.672 0.000 X13 0.586 0.001 X14 0.663 0.000 X16 0.809 0.000 X21 0.740 0.000 X23 0.857 0.000 X24 0.790 0.000 X27 0.609 0.000 Composite Reliability 0.826 Goodness of Fit Goodness of Fit Index Cut off Value Value P-value (Chi-Square) ≥0.05 0.525 GFI ≥0.90 0.952 RMSEA ≤0.08 0.000 AGFI ≥0.90 0.867 255 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate inflation with a value of 0.835 and firm competence with a value of 0.809, also have a significant influence. Inflation reflects macroeconomic conditions that influence financing strategies, while firm competence and share undervaluation are related to credibility. Exchange rates reflect a country's economic strength and are influenced by government policies. Indonesia implements a floating exchange rate system, where its movements affect bond and Sukuk trading. Unstable exchange rate fluctuations can impact the market, while Sukuk represents ownership claims whose value can increase as the underlying asset increases. The risk profile of Sukuk corresponds one-to-one with the structure. The cost of funds is the cost incurred to collect third-party funds. It means that the fee calculation is issued for every fund successfully collected from various funding sources after considering the existence of reserve funds that must be maintained. Each type of funding source has a different interest rate. Hence, the low average cost of funds depends on the composition of successful funding sources collected. Cost of funds is the interest that financial institutions pay on funds used, affecting returns. The cost of funds reflects the interest that must be paid to obtain funding. Sukuk and bonds, although they have legal differences, are both debt instruments with the obligation to return the principal. Sukuk can be a source of business funding, with the issuance cost in the form of an interest rate paid to investors. Therefore, Sukuk issuance must be done at the right time. Inflation is the increase in prices in a certain period that affects the capital market and Sukuk. A decrease in inflation increases investment interest, while an increase in inflation encourages Sukuk issuers to increase yields. Rising prices make investors tend to sell Sukuk, while potential investors postpone investments. The lack of Sukuk in the market causes low liquidity and limited funds. The few Sukuk issuances limit firms' choices to fulfil their investment needs. Firm competence can influence shareholder considerations when buying, selling, and holding company shares. Reader competency will also be used as a basis for consideration when determining the sukuk rating value. The company's competence will include a collective representation of the historical business entity's activities and its results. Competency describes a business entity's ability to produce value and provide benefits to stakeholders. The competency of business entities in determining the influence of project-based sukuk issuance on the continuation of toll road construction is financial performance. Business entities with good economic performance will foster investor confidence. Companies with high growth and free cash flow tend to choose Sukuk as a source of funding. Sukuk contracts ensure that funds are used only for specific projects, preventing misuse. Empirical studies show that highly leveraged companies issue Sukuk with contracts that are tailored to their financial condition and capital structure. Moreover, the following findings indicate that stock undervalued, with a value of 0.79, and tax support and incentives, with 0.715, increased Sukuk's attractiveness. On the other hand, indicators such as trading volume and liquidity (0.672), sharia knowledge (0.663), financial distress (0.609), and company age (0.586), have quite a significant influence. Investors' Sharia knowledge shows the importance of market education, while the company's financial condition and company age reflect stability and experience as considerations in issuing Sukuk. 5. Conclusion This study identifies the factors influencing Sukuk project-based issuance in refinancing schemes for toll road development in Indonesia, using questionnaires from experts and experienced practitioners from the infrastructure industry, regulators, and college researchers. The results show that twelve indicators describe the decision to issue project-based Sukuk. These results show that exchange rates, high cost of funds, inflation, and firm competence are the main significant determinants in the decision to issue project-based Sukuk. Further, this study highlights the respondents who participated in sustainable refinancing for toll road development. The study may involve other stakeholders, such as the community. However, despite 256 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 243-257, 2025 DOI: 10.55214/25768484.v9i3.5185 © 2025 by the authors; licensee Learning Gate producing valuable findings, the study still has limitations. This research requires more practitioners and experts to get better results. 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