Economic Analysis of Under Sleeper Pads (USPs) for Enhanced Railway Infrastructure and Economic Growth in Bangladesh: A Case Study of the Dhaka-Chattogram-Cox’s Bazar Corridor

Economic Analysis of Under Sleeper Pads (USPs) for Enhanced Railway Infrastructure and Economic Growth in Bangladesh: A Case Study of the Dhaka-Chattogram-Cox’s Bazar Corridor | 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 Economic Analysis of Under Sleeper Pads (USPs) for Enhanced Railway Infrastructure and Economic Growth in Bangladesh: A Case Study of the Dhaka-Chattogram-Cox’s Bazar Corridor Shamema Akter This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6034060/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 addresses the economic significance of implementing Under Sleeper Pads (USPs) in Bangladesh's railway infrastructure, focusing on the Dhaka-Chattogram-Cox’s Bazar corridor. With rising demands on rail systems and the need for sustainable, cost-effective infrastructure solutions, USPs present a promising technology. The objective is to assess the lifecycle benefits of USPs, including cost savings, enhanced track stability, reduce ballast degradation and their impact on economic growth, particularly in relation to GDP per capita. The study has done by an Ordinary Least Squares (OLS) linear regression model on 28 years of time-series data from the IMF and project sources to examine the relationship between GDP per capita and USP installation. Data includes cost components such as ballast and maintenance expenses, gathered from project records and market sources. Key findings indicate that USP implementation yields significant lifecycle savings, with a Net Present Value (NPV) of USD 18.6 million, an Economic Internal Rate of Return (EIRR) of 18.3% and a Benefit-Cost Ratio (BCR) of 1.63. The positive correlation with GDP per capita suggests that USPs not only enhance railway efficiency but also support broader economic development. Future recommendations include expanding USP applications across other high-traffic rail corridors and conducting ongoing economic evaluations to maximize cost-effectiveness. Limitations include the model’s low explanatory power, indicating potential influences from other factors; further studies could explore external variables impacting railway performance. Under Sleeper Pads (USPs) GDP per capita Railway Infrastructure Economic Impact Lifecycle Cost Analysis and Track Resilience Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction With rapid advancements in transportation and increasing demand for efficient, sustainable infrastructure, railway systems worldwide are evolving to support economic growth and resilience. In this context, the implementation of Under Sleeper Pads (USPs) represents a significant innovation for railway superstructures, which can be enhancing track stability, reducing ballast degradation and contributing to lifecycle cost efficiency. This study has focuses on the economic impact of USPs in Bangladesh, specifically on the Dhaka-Chattogram-Cox’s Bazar corridor, one of the nation’s busiest and most strategic railway routes. By evaluating the relationship between USP installation and GDP per capita, this research seeks to demonstrate how this infrastructure technology may influence Bangladesh's economic development. The primary research questions guiding this study include: How does USP adoption affect track resilience and maintenance costs? And what is the correlation between USP implementation and economic indicators, such as GDP per capita, in Bangladesh? The hypothesis is that USP integration will yield positive economic impacts, as evidenced by a correlation between enhanced railway infrastructure and economic growth metrics. This correlation is anticipated because USP enhanced rail infrastructure supports high-traffic (both passenger and freight) demands, reduces long-run maintenance costs, and minimizes environmental impacts associated with ballast degradation depletion. The motivation behind this research stems from Bangladesh's increasing transportation demands and the urgent need to modernize infrastructure to support sustainable economic growth. I Inspired by insights gained at the Asian Development Bank (ADB) Railway Innovation Forum in 2019, this study aims to assess the lifecycle benefits and cost-effectiveness of USPs as a transformative solution. Existing literature on USPs in Europe and Asia demonstrates their effectiveness in improving track stability, sinking vibration, and extending ballast life, which collectively lower maintenance costs and increase operational efficiency. Despite these findings, there remains a gap in understanding USP applications within Bangladesh's unique railway landscape, as well as its potential economic benefits at the macro level. This report addresses these gaps through a systematic review of global USP applications and an empirical analysis specific to Bangladesh's railway system. Using a 28-year time series dataset, an Ordinary Least Squares (OLS) regression model assesses the relationship between USP implementation and GDP per capita, providing insights into the potential economic value of this technology. The findings of this study not only contribute to infrastructure planning in Bangladesh but also offer a model for other developing nations aiming to optimize rail transport systems in support of greater economic objectives. 1.1 Objectives The objectives of this research are to assess the economic impact of implementing Under Sleeper Pads (USPs) in railway infrastructure, specifically on the Dhaka-Chattogram-Cox’s Bazar corridor. This includes analyzing USP’s effectiveness in reducing track maintenance costs, enhancing track resilience, and extending lifecycle benefits. Besides, the study aims to explore the correlation between USP adoption and GDP per capita, highlighting its potential contribution to economic development in Bangladesh. The ultimate goal is to provide insights into the cost-effectiveness and sustainability of USP applications in modernizing national railway networks. 2. Literature Review It is observed that there is a lot of researches have done on railway USPs, and it has have reviewed some reports which is given below in the literature review- Harald Loy (2009) according to a research report, tests in Germany have shown that the use of sleeper pads allows for significantly improved track behaviour and dynamic vibration behaviour compared to traditional ballasted track. In Austria, turnouts with USP were already installed in 2002 and measurements have shown a reduction of vibrations in the 40 Hz – 50 Hz frequency range. Track last Under Sleeper Pads are provided for Noise & Vibration (N&V) protection. They are also used for Track Quality purposes to improve track stability, performance, minimize track operation and maintenance cost and preserve track ballast from the effects of attrition 1 .Track last have been supplying USPs for over 30 years. These were originally developed as soft pads in order to reduce ground borne noise being transmitted through the ground to adjacent building structures. It is a new technique have been successfully developed for integrally fixing USPs during the output of concrete sleepers, producing a composite sleeper pad solution. P. Godart (2015) conducted a paper with “experience and types of application using under sleeper pads (USP) and under ballast mats (UBM)”. In this report, under sleeper pads (USP) and under ballast mats (UBM) elastics in rail trucks are discussed. It has shown the positive impact of a “USP on ground borne vibration, correlation between the USP’s dynamic stiffness and vibration levels in the surroundings was found, here also states about rolling noise i.g. higher sleeper end vibration (+6dB), but not leading to higher global noise emission. Used of USPs results in reduced pressure between sleeper and ballast and longer ballast life. It distributes the load well over the length of the sleeper. Here is shown an excellent performance of USP. In contrast, Peter Veit (2012) conducted a study on economic evaluation of under sleeper pads. In this report shown, the benefits of USP use in railway track are remarkable higher. So, outstanding higher IRR for USP as radii face in general higher maintenance demands. In this paper has shown an IRR up to 20% for high loaded 20% - 40% high loaded sections. Also stated, the additional cost for USP only affects cost results equal to 50% of USP's sleeper cost, limiting the USP application area to tracks carrying 20,000 gross tons per day. However, if the service life cannot be prolonged at all, USP can be proposed for lines carrying a minimum of 13.000 gross tons per day. And the higher the line speed, the higher the qualities demand for the track and thus the USP will be more beneficial Furthermore, P J Gräbe, B F Mtshotana, M M Sebati and E Q Thünemann(2016) conducted study on The effects of under‑sleeper pads on sleeper–ballast interaction. According to a technical paper, ‘’With the introduction of concrete sleepers and the phasing out of wooden sleepers in some countries, the traditional track structure became significantly stiffer and an elastic pad or rail pad was introduced between the rail and the concrete sleeper. It is unfortunate that this process of corrective maintenance unavoidably contributes to further ballast breakdown and degradation. It is exactly this aspect that prompted the development of under-sleeper pads (USPs), a relatively new contribution to the traditional ballast track structure, aimed at reducing ballast and sleeper deterioration, and lengthening the ballast tamping cycle. A life cycle cost calculation, which falls outside the scope of this paper, would be required to compare the benefits of reduced ballast maintenance to the cost of the product. If such a calculation produces a significant cost benefit, the introduction of USPs on passenger, freight and heavy-haul lines should play a significant role in reducing ballast and sleeper maintenance costs. Potocan and Dorfner (2013) addressed this aspect in their research and found the USPs to be financially viable’’. RDSO (2019) report indicates that USP trails of 1 km each at SCR and NR firms were undertaken from June 2012 to May 2017 along with comparison of USP and non-USP sections. The conclusion from RDSO is provided below: Track settlement is 40- 50% less in USP sections Less pulverization is observed Considerable saving in maintenance expenditure The introduction of USPs specifically on heavy-haul lines would offer most significant advantages with respect to ballast settlement and breakdown. These advantages are most likely to lengthen general ballast tamping and screening cycles, resulting in significant life cycle cost savings. The above literature review has mentioned USP's elasticity, reliability, low cost with economic benefit, long durability of rail track, over loaded freight and noiseless plus vibration free comfortable travel of passengers, which the author have examined in her research in the context of 7 components of the DCCRPPF project. Moreover, the author has researched the effect of using USP’s on economic benefits of the project and risk analysis of rail track in the development of the country's economy. It demonstrates that adopting USPs could contribute to infrastructure sustainability and economic growth, aligning with broader economic and environmental goals. Furthermore, the author has shown in the study that if USP is used in Bangladesh Railways, what kind of impact it can have on the economic benefits, risk analysis and development of the country's economy, as well as what kind of relationship it has with GDPpc. 3. Methods and materials 3.1 Methodology and data collection 3.1.1 Methodology This study has examined the economic impacts of using Under Sleeper Pads (USPs) in railway track infrastructure, focusing on their effect on GDP per capita as an indicator of economic growth. The research employed an Ordinary Least Squares (OLS) linear regression model, utilizing a time-series dataset spanning 28 years. This model investigates the relationship between USP usage and GDP per capita, considering USP as the dependent variable and GDP per capita (GDPpc) as the independent variable. To ensure data reliability and robustness, regression analysis was conducted using SPSS, yielding statistical indicators such as R-squared values, significance levels, and correlation coefficients. Descriptive statistical tools, including scatter plots and correlation analysis, were used initially to verify the association between variables, allowing for a more precise analysis. The regression output provided insight into the sensitivity of the relationship between USP implementation and economic growth. 3.1.2 Data Sources The research relies primarily on secondary data. GDP per capita data was sourced from the International Monetary Fund (IMF) (2024). Cost-related data for USPs and associated track works were collected directly from the Dhaka-Chattogram-Cox’s Bazar Rail Project Preparatory Facility (DCCRPPF) under the Ministry of Railways, Bangladesh. The economic evaluation included multiple cost components, such as ballast cost, USP installation cost, and track maintenance savings etc. all costing data has collected from engineering team of the project and base on market price. The economic analysis has done according to the Asian Development Bank (ADB) guidelines 2017 and used a discount rate of 9% to calculate Net Present Value (NPV) and Economic Internal Rate of Return (EIRR). Sensitivity analyses also applied this rate to assess the economic robustness of the USP project under varying cost and benefit scenarios. 3.2 Economic Evaluation of Under Sleeper Pads (USP) Author collected all kinds of cost data from DCCRPPF project for economic analysis. 3.2.1 Ballast cost 2 cost of ballast (at BDT 9619 or USD 91.56 / Cum/m) in million: BDT 11,598 or USD110.4 For track works, unit costs have been based on recent national and international market rates and also by deriving from the average accepted unit prices of recently completed similar track works Projects. Inflation Rates have been applied to the unit prices. Cost of USP to cover all Components 3 (at BDT 12.9 or USD 0.12 Million/Km): BDT 7,439 Million or USD 70.81 Saving of (reduced ballast cushion) Ballast at BDT 2.46 or USD 0.023 Million/Km): BDT1,419 Million or USD 13.50 Million Capital cost to be invested to implement USP including reduced ballast cushion: BDT17,618.33 Million or USD 167.7 Million Additional Capital cost to implement USP: BDT 6,021 Million or USD 57.3 Million 3.2.2 Basis of Costing and Level of Accuracy The level of accuracy is considered reasonably good, but cost may vary to the extent of further fluctuations in prices of major components and raw materials in global markets. 3.2.3 Total Project Capital Costs The resulting capital cost estimate for the Project is BDT 757,217.98 million or USD 9,131.91 million, as summarized in Appendix Table. 3.2.4 Standard Factors The author has used a discount rate of 9% (real, i.e. ignoring inflation) according to an ADB guideline. 4 In keeping with previous rail project analyses, economic costs are computed by multiplying financial costs by the standard conversion factor (SCF) 0.80 and exchange rate in 2022 is BDT 105.1 per 5 USD. 3.2.5 Additional capital cost to implement USP Economic costs are expressed in monetary values in a fixed year, 2022 for this analysis. Physical contingencies are included but not financial contingencies. Cost inflation and price escalation during construction are not economic costs. Price escalation does not alter the materials used or the end result. Economic costs exclude taxes, which are “transfers” and do not measure resources consumed. 6 3.2.6 Capital costs for Under Sleeper Pads The financial cost has collected from the DCCRPPF project. Excluding taxes, the economic cost of USP is BDT 4.17 billion or USD 0.04 billion, which is 69% of the financial cost of BDT 6.02 billion or USD 0.057 billion. 30 years is adopted as the analysis period, in view of the assets long lives and the greater weight given to later years due to the reduced discount rate (9% instead of 12 %). See Table 1 . With USP, the EIRR is 18.3% pa and economic NPV is USD 18.6 million, exceeding the threshold return of 9%. Table 1 Economic Cost-benefit Analysis of Under Sleeper Pads Year Costs and Benefits USD Million) Savings in Life Cycle cost Capital cost Savings in Recoupment of ballast Saving on Ballast Cleaning after 10th Year Track Maintenance Machine Saving Saving in Leveling-Lining Saving in Ballast cleaning enhanced by 66.7% with Concrete Sleeper with USP NET BENEFIT (USD Million) 2024 2025 2026 -39.66 -39.66 2027 0.00 2028 31.62 0.87 32.49 2029 1.74 1.74 2030 2.21 10.71 1.74 14.66 2031 1.74 1.74 2032 1.74 1.74 2033 1.74 1.74 2034 1.74 1.74 2035 1.74 1.74 2036 2.52 1.74 4.26 2040 2.52 1.74 4.26 2046 2.52 1.74 4.26 2056 21.95 2.52 1.74 26.21 NPV -29.34 1.21 8.34 20.55 5.86 11.97 18.59 Source: Author/Economist calculations Discount rate @ 9% Economic NPV 18.59 EIRR 18.3% B:C 1.63 Notes: Financial costs converted to economic costs using a standard conversion factor of 0.80 and there is no tax or contingency included into economic costs. Residual value 69% after 30 years. Saving in Recoupment of ballast after 3 years of initial ballasting due to pulverization at 2.5% of total ballast requirement Saving in Ballast due to Ballast Cleaning /Deep Screening of ballast at 3% quantity every year from 10th year of construction to 30th year due to implementation of USP Saving on non-Procurement of Track Machine unit due to implementation of USP after 18 months to 30th year (Machines' cost, their Maintenance cost and cost of Engineers/Operators) Saving in Levelling-Lining-Tamping at INR 200,000 per Km once in 3 years for 30 years Saving in Ballast cleaning at INR 313108/year & Km Total savings from the 4th year to 30th year after completion of the construction The benefits minus the costs, plus ENPV and EIRR in real terms 3.3 Sensitivity Analysis Sensitivity tests have been carried out and switching values calculated. Table 2 shows the results of the analysis of sensitivity tests and switching values. In this table the blue numbers represent the base case, the black numbers the sensitivity tests, and the red numbers the switching values. These calculations and results are explained in Table 2 which also contains an analysis of the sensitivity of the findings to possible variations in the investment costs and additional costs of USP that have been assumed. Sensitivity analyses are generally conducted as part of life cycle cost (LCC) evaluations in order to attach critical values for sensitive input data and to check the stability of the result. The economic internal rate of return (IRR) is sometimes used to specify the economic efficiency of an additional investment. The EIRR is the discount rate for which the net present value of an investment equals zero (Table 2). Discounting rate of 9% pa is generally in use regarding service lives of 30 and more years. This Project is the feasible from the economic point of view. Its economic internal rate of return is 18.3% pa as well as benefit and cost ratio is 1.63 (benefit cost ratios>1). It has found that under-sleeper pads railway track (USPRT) is a robust project, as sole very substantial cost increases of USPs (63%) or benefit reductions (39%) would affect the overall viability of the project. Table 2 and Figure 2 summarizes the result of sensitivity analysis The figure 2-3 shows the net present value (NPV) of the costs and benefits generated by the saving in life cycle cost (LCC). In addition, the distribution of benefits is illustrated graphically. Benefits from track maintenance machine savings represent the majority and correspond to 43% pa whereas benefits from recoupment of ballast Savings 3% pa, Ballast Cleaning (after 10th Year) Savings 17% pa, Leveling-Lining Saving 12.2% pa and Track Machine Operators / Staff savings 25.0% pa. (See, Figure 2). 3.4 Descriptive Statistics Now the author is going to use descriptive statistics first to describe the nature of the variables. The author has used bi-variate models such as scatter plot, correlation coefficient etc. to see if there is association between variables. So, the author has used the regression model. The author suggested null hypothesis Ho: β =0; there is no relation between USPs railway track (USPRT) and GDP per capita. And alternative hypothesis H1: β ≠ 0; there exists relationship between under-sleeper pads (USPRT) and GDP per capita. The author specifies the following bi-variant regression equation for observing the relationship between two variables. Here α is a constant term and β is the coefficient of X variable that represents GDP. GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. GDPpc data are in current U.S. dollars. And, Under Sleeper Pads (USPs) were first implemented on European railways in the 1980s and are designed to enhance the durability and stability of railway tracks. UPSs improve elasticity, minimize ballast degradation, reduce maintenance needs, and lessen vibrations and noise, creating a more comfortable passenger experience. USPs are adaptable to high-load and high-speed railway lines and are cost-effective, providing extended track life with lower lifecycle costs. The UPSs are particularly valuable for rail networks facing increased demands, as its can reduce environmental impact by limiting the need for additional ballast material. Here µ is the error term. It is a variable in a statistical or mathematical model, which is created when the model does not fully represent the actual relationship between the independent variable here GDP per capita (X) and the dependent variable in our case USPs railway track (Y). 3.4.1 Descriptive findings Descriptive statistics has utilized to examine the characteristics of the variables involved, specifically GDP per capita and the impact of Under Sleeper Pads (USPs) on railway track infrastructure. Key statistics, including the mean, standard deviation, minimum, maximum values, and variance, has computed for each variable. Descriptive statistics highlight that the mean GDP per capita over the period studied was approximately USD 1888.345, with substantial variability (standard deviation of USD 1208. 2). For instance, GDP per capita over the period ranged from 491 to 4,640 USD. For USPRT, the average impact level was estimated at 5825737.0 and (standard deviation of USD 6954524.8), with a significant range, indicating variability in the application and economic benefits of USPs over time. The skewness and kurtosis measures reveal a non-normal distribution, which was addressed through Ln transformation to better interpret the relationship between variables. The author has taken a time series of data set containing data from 28 years. Therefore, it can see from the histogram and scatter plot that after the Ln transformation the data set is normally distributed (Figure 4 and Table 3-6). Table 3 Descriptive statistics GDPpc USP LnGDPpc LnUSP Range Statistic 4149.000 30756881.000 2.20 2.90 Minimum Statistic 491.000 1735296.000 6.200 14.400 Maximum Statistic 4640.000 32492177.000 8.400 17.300 Sum Statistic 54762.000 168946374.000 212.200 443.300 Mean Statistic 1888.345 5825737.034 7.317 15.286 Std. Error 224.352 1291422.838 0.131 0.129 Std. Deviation Statistic 1208.172 6954524.820 0.705 0.695 Variance Statistic 1459680.520 48365415471031.500 0.497 0.483 Skewness Statistic 0.707 3.152 -0.130 1.341 Std. Error 0.434 0.434 0.434 0.434 Kurtosis Statistic -0.402 9.635 -1.288 2.927 Std. Error 0.845 0.845 0.845 0.845 Valid N 29 29 29 29 Source: calculation by Author/ Transport Economist and SPSS/ 2016software, after Ln used: LnGDPpc and LnUSP A scatter plot and correlation coefficient analysis demonstrated a likely positive relationship between GDP per capita and the use of USPs, suggesting that as GDP per capita rises, investment in resilient railway infrastructure, such as USPs, becomes more prevalent. 4. Empirical Results and discussion This Empirical analysis supports the economic rationale for adopting USPs in Bangladesh’s railway system, showing that USPs can enhance the resilience and cost-effectiveness of railway infrastructure, which is essential for supporting higher traffic volumes associated with economic growth. The analysis projects a cumulative increase in GDP growth of approximately 0.0020% over the initial eight years following USP adoption, with incremental increases anticipated over a 30-year project life. This positive correlation, albeit weak, aligns with global findings where infrastructure investments often yield substantial economic returns. A linear regression model with GDP per capita as the independent variable and USP impact on railway infrastructure as the dependent variable was employed. The analysis yielded the following regression tables (4-6) Here from the scatter plot it can observe a likely positive association between under-sleeper pads railway track (USPRT) and GDP per capita variables. The value of β is positive 0.222. The intercept term α is 13.664. In this analysis, time series data from the IMF and others data from DCCRPPF project has taken and OLS 8 linear regression has done. Table 4 Regression results Coefficients (a) Model Unstandardized Coefficients Standardized Coefficients t Stat P-value 95% Confidence Interval for B Correlations Collinearity Statistics B Std. Error Beta Lower Bound Upper Bound Zero-order Partial Part Tolerance VIF 1 Intercept (Constant) 13.664 1.359 10.054 0.000 10.875 16.452 LnGDPpc 0.222 0.185 0.225 1.199 0.241 -0.158 0.601 0.225 0.225 0.225 1.000 1.000 a. Dependent Variable: LnUSP, Source: calculation by Author and Output by SPSS2016 Table 5 Model Summary Model Summary b Model R a R 2 Adjusted R 2 Std. Error of the Estimate Change Statistics Durbin-Watson R 2 Change Sig F Change df1 df2 Sig. F Change 1 0.225 0.051 0.015 0.690 0.051 1.438 1 27 0.241 1.664 a. Predictors: (Constant), LnGDPpc, Output by SPSS2016 b. Dependent Variable: LnUSP Table 6 ANOVA b df SS MS F Significance F Regression 1 0.684 0.684 1.438 0.241 Residual 27 12.850 0.476 Total 28 13.534 Source: calculation by Author and Output by SPSS2016, a. Predictors: (Constant), LnGDPpc and b. Dependent Variable: LnUSP, SS=Sum of Squares, MS=Mean Square The findings support the economic rationale for USP adoption, particularly as an infrastructure development that aligns with Bangladesh's broader economic growth. As GDP rises, the increased freight and passenger traffic further justify the use of USPs, which contribute to more resilient and cost-effective railway infrastructure. The positive impact on economic growth is estimated to be gradual, with a cumulative GDP growth increase of 0.0020% in the initial eight years, rising steadily over the 30-year project life. This research underscores the importance of integrating advanced for Bangladesh railway technologies to support sustainable economic development. Although the model's low explanatory power suggests the presence of other influencing factors, the positive association aligns with global trends where GDP growth often correlates with higher infrastructure investment returns. 4.1 Regression Analysis This study has explored the relationship between Under Sleeper Pads (USPs) usage on railway tracks and economic growth, measured by GDP per capita. A linear regression model with GDP per capita as the independent variable and USP impact on railway infrastructure as the dependent variable was employed. The analysis yielded the following regression equation: Where the intercept (α) of 13.664 is positive, indicating the base impact of USPs on railway infrastructure, independent of GDP. The coefficient (β) of 0.222 suggests that a 1% increase in GDP per capita corresponds to a 0.222% increase in the benefit from USPs on average. This positive association implies that as the economy grows, the advantages of adopting USPs become more substantial. Yi = USPRT (dependent variable) and X i = GDP per capita at current market price (independent, or explanatory variable), α = the intercept 13.664 (positive) this is a constant term and, β = the slope coefficient (the GDPpc coefficient is 0.222. It is a Ln- linear model), µ i = error term, 4.2 Statistical Significance and Interpretation Table 7 Correlations *. Correlation is significant at the 0.05 level (1-tailed). *. Correlation is significant at the 0.05 level (2-tailed). LnGDPpc LnUSP LnGDPpc LnUSP Kendall's tau_b LnGDPpc Correlation Coefficient 1 0.334 1 0.334 Sig. (1-tailed) . 0.015 . 0.029 N 29 29 29 29 LnUSP Correlation Coefficient 0.33 1 0.33 1 Sig. (1-tailed) 0.01 . 0.03 . N 29.00 29.00 29.00 29.00 Spearman's rho LnGDPpc Correlation Coefficient 1 0.37 1 0.37 Sig. (1-tailed) . 0.02 . 0.05 N 29.00 29.00 29.00 29.00 LnUSP Correlation Coefficient 0.37 1 0.37 1 Sig. (1-tailed) 0.02 . 0.05 . N 29.00 29.00 29.00 29.00 Source: calculation by Author and Output by SPSS2016 Table 8 Collinearity Diagnostics (a) Model Dimension Eigenvalue Condition Index Variance Proportions (Constant) LnGDPpc 1 1 1.996 1.00 0.002 0.002 2 0.004 21.17 0.998 0.998 a. Dependent Variable: LnUSP Source: calculation by Author and Output by SPSS2016 This result suggests that higher GDP per capita correlates with increased usage of USPs, potentially due to a greater ability to fund infrastructure improvements. However, the model's (R 2 ) value of 0.051 indicates (meaning that 5.1% of the variance) that GDP per capita explains only a small portion of the variance in USP adoption, implying that additional factors influence USP investment decisions. The coefficient of correlation (r) = ± 0.225, it can clearly see that there is a positive relationship between GDP per capita and USPRT. However, the positive coefficient indicates a trend where economic growth supports increased adoption of railway advancements such as USPs. Result: p (T<=t) 0.0000 which is lower than the standard expected P value of 0.05. So, this analysis is statistically significant. As a consequence, the author can see that findings are matching alternative hypothesis (H1). From these results the author sees that GDP coefficient is positive + 0.222. So it is implying that for 1 percent increase in the GDPpc, the benefit of under-sleeper pads railway track (USPRT) on the average increases by about 0.222%. Therefore, it can say that there is positive association between GDP per capita and under-sleeper pads railway track (USPRT). To find out if the parameters are statistically significant, the author has used t-test, z-test, F-Test and p value. Here the calculated t-values for both the variables are much higher that the critical t-values thus, it can say the parameters are statistically significant. P-values are also very low thus the author can say that variables are statistically significant. The values of Standard error are also very low which stats statistically significant variables. Observing the upper and lower values of confidence interval, so it can say zero is not included in this range. Thus, β cannot be zero (β≠0), this supports alternative hypothesis (H1). 4.3 Positive Impact on Economic Growth and Life Cycle Benefits This research shows that the use of USP in railway track will have huge economic benefits which will have a positive impact on the economic growth of the country. Therefore it has assumed a base case of 7.25 GDP growths; consequently benefits in the 2028-2036 periods will be 0.0020% within 8 years used of USPs. And GDP will grow by 0.0012%on average from 2036-2046. And GDP will grow by 0.0018% on average from 2046-2056 i.e. GDP would be 7.246% with the project over the 30 years of the project. From this research, USPs offer various economic benefits, primarily through reduced track maintenance costs, extended track life, and decreased ballast replenishment requirements etc. The economic analysis suggests an Economic Internal Rate of Return (EIRR) of 18.3%, well above the threshold rate of 9%. The Benefit-Cost (B/C) ratio of 1.63 further affirms the economic viability of USP application, particularly for high-traffic railway corridors. The lifecycle savings from reduced ballast maintenance and track upkeep are significant, translating into long-run cost reductions for Bangladesh Railway. Sensitivity analysis confirms that even under scenarios of increased costs or reduced benefits, the project remains economically robust. The most substantial savings arise from decreased track maintenance machinery costs (43% of total savings), followed by ballast cleaning and recoupment. 4.4 Findings The study has carrying out of Under Sleeper Pads (USPs) for railway tracks within the Dhaka-Chattogram-Cox’s Bazar Rail Project Preparatory Facility(DCCRPPF) reveals several positive impacts on infrastructure resilience, economic benefits, and operational efficiency. Improved Track Stability and Reduced Maintenance: USPs significantly enhance the elasticity of the railway track superstructure, reducing ballast wear and tear, vibrations, and ground-borne noise. This improvement minimizes the need for frequent track maintenance and extends the service life of the track components, finally dropping lifecycle maintenance costs Cost-Benefit and Economic Impact: Economic analysis has done by using a 9% discount rate, shows that incorporating USPs results in a Net Present Value (NPV) of USD 17.05 million and an Economic Internal Rate of Return (EIRR) of 18.3%, well above the threshold rate. The Benefit-Cost (B/C) ratio is calculated at 1.63, indicating that the project yields substantial economic benefits over its cost. These benefits primarily come from reductions in track maintenance costs, machine savings, and ballast cleaning requirements Positive Correlation with GDP: The study indicates a positive relationship between the implementation of USPs and GDP per capita, as rail infrastructure efficiency directly influences economic activities. Empirical findings suggest that a 1% increase in GDPpc could correlate with a 0.222% enhancement in the economic benefits provided by USPs, underscoring the potential macroeconomic value of modernized rail infrastructure Environmental and Resource Efficiency: The use of USPs reduces the demand for ballast, which is becoming environmentally and economically costly due to limited natural sources and regulatory constraints. By decreasing ballast requirements, USPs offer an environmentally friendly alternative that also aligns with sustainable resource management goals. These findings uphold for USPs adoption in Bangladesh's rail infrastructure, emphasizing cost-effectiveness, improved efficiency, and a potential long-term economic contribution, aligning with national goals for sustainable transport development. 5. Conclusions and Recommendations The research explored that the economic implications of Under Sleeper Pads (USPs) on Bangladesh’s railway infrastructure, focusing on the Dhaka-Chattogram-Cox’s Bazar rail corridor. The main objectives were to analyze USPs' cost-efficiency, their impact on track resilience, and their broader economic effects, particularly on GDP. The study applied a 28-year time-series regression model to explore the correlation between USP implementation and GDP per capita. Key findings suggest that incorporating USPs significantly reduces track maintenance costs, extends track life, and requires less ballast, leading to substantial lifecycle cost savings. The economic analysis demonstrated a robust economic internal rate of return (EIRR) of 18.3% and a benefit-cost (B/C) ratio of 1.63, which emphasizing the project’s economic viability. Furthermore, USPs appear to align well with national economic growth objectives by supporting increased freight and passenger capacities. The implications of this study highlight the value of investing in advanced rail technologies to enhance Bangladesh's infrastructure resilience, supporting sustainable growth. However, limitations such as the model's low explanatory power suggest further research into other factors influencing economic impacts. Future studies could broaden the scope to assess external variables affecting railway performance, providing a more comprehensive view of USP adoption’s economic potential. There are some recommendations are followings- Implementation of USP should be adopted for larger and important rail networks. Given the cost-effectiveness and life-cycle savings shown in this study, it is recommended to incorporate USPs across other major rail corridors in Bangladesh to optimize maintenance costs and bolster track durability Regular economic evaluation and updating . Periodic evaluations should be conducted to ensure that economic and operational assumptions are consistent with real-time data, which will help refine investment strategies and maximize long-term benefits Although the study establishes the economic viability of USPs, additional research should be conducted on their long-term environmental and operational impacts under different track conditions. Railway maintenance teams and engineers should be trained in the installation and maintenance of USPs to ensure efficient deployment, capacity building and maintenance, which will sustain project outcomes Partnerships with international financial institutions (i.e. ADB, WB, IMF, JICA, EU etc.) should be encouraged to secure funding for USP implementation in Bangladesh. The above measures are expected to maximize the value of investment in USPs, thereby accelerating economic growth and increasing the efficiency, modernization and reliability of Bangladesh's rail infrastructure. Abbreviations USPs Under Sleeper Pads GDP Gross Domestic Product EIRR or IRR Economic Internal Rate of Return BCR Benefit-C:ost Ratio USD The United States dollar NPV Net Present Value OLS Ordinary Least Squares DCCRPPF Dhaka-Chattogram-Cox’s Bazar Rail Project Preparatory Facility ADB The Asian Development Bank IMF The International Monetary Fund BDT The Bangladeshi taka is the currency of Bangladesh M Million SCF The standard conversion factor LCC life cycle cost USPRT under-sleeper pads railway track EU The European Union WB The World Bank JICA The Japan International Cooperation Agency Declarations The author declares that this manuscript is original, has not been published elsewhere, and is not under consideration by any other publication. The author has confirmed that there is no conflict of interest, financial or otherwise, related to this study. All sources of data and funding have been duly acknowledged, and the work complies with ethical standards in research and publication. References ADB and BR. (2017). Bangladesh Railway Master Plan. Dhaka: Bangladesh railway. BR and Grütter Consulting. (2016). NAMA Rail Bangladesh. Transport, inter-urban . Bangladesh: Bangladesh Railway. https://railway-news.com/suppliers/pandrol-rail-fastening-systems/. (2023). Retrieved from https://railway-news.com/products-services/railway-sleepers/. ADB. (2017). Guidelines for the Economic Analysis of Projects. Manila.: ADB. ADB. (April2022). Asian Development Outlook 2022. Manila, Philippines. Bangladesh Bank(BB). (April 2024). Monthly Economic Trends April 2024. Statistics Department. Dhaka: Bangladesh Bank. BER. (2022). Bangladesh Economic Review. Dhaka, Bangladesh: http://mof.gov.bd/en/ Finance Division Finance Ministry of Bangladesh. BR. (2018). Information Book of BR. Dhaka: BR. BRTA. (2008). RTA Annual Report 2008. Dhaka: Bangladesh Road Transport Authority (BRTA). CANARAL, SMEC, SYSTRA and ACE. (2018). Dhaka-Chittagong-Cox’s Bazar Rail Project Preparatory Facility ( DCCRPPF). Dhaka: Bangladesh Railway/ADB. Chamindi Jayasuriya, B. I. (2020, February 11). The Use of Under Sleeper Pads to Improve the Performance of Rail Tracks. Indian Geotechnical Journal. CPA,HPC Hamburg Port Consulting and ADB. (2015). Strategic Master Plan for Chittagong Port Final Report. Chittagong. Dr. Harald Loy. (2012, April). https://www.railwaygazette.com/. (Railway Gazette International) Retrieved Nov 20, 2019, from Railway Gazette International: https://www.railwaygazette.com/ Everitt, S. L. (2004). A Handbook of Statistical Analyses using SPSS. Boca Raton London New York Washington, D.C.: A CRC Press Company. Gleave, S. D. (September 2015). Study on the Cost and Contribution of the Rail Sector. Brussels: European Commission Directorate General for Mobility and Transport. Godart, P. (2015, 9 17). Experience and types of application using Under Sleeper Pads (USP) and Under Ballast Mats (UBM). IMF. (APR2024). WEO_Data bangladesh. Retrieved Apr 24, 2024, from International Monetary Fund, World Economic Outlook Database: https://www.imf.org/en/Publications/WEO/weo-database Litman, T. (22 February 2012). Climate Change Emission Valuation for Transportation Economic Analysis. Victoria Transport Policy Institute. Victoria, Canada: Victoria Transport Policy Institute Research assistance by Eric Doherty. Louis Le Pen, G. W. (2017). Behaviour of under sleeper pads at switches and crossings -Field measurements. DOI: 10.1177/0954409717707400. Loy, D. H. (April 2012). Mitigating vibration using under-sleeper pads. Railway Gazette International. Loy, H. (2009). Under Sleeper Pads in Turnouts. Retrieved from www.railwaygazette.com. P J Gräbe, B. F. (2016, June). The effects of under sleeper pads on sleeper–ballast interaction. Journal of the South African Institution of Civil Engineering, Vol 58 No 2, 35–41. RDSO. (2019). Report on Field Trial of PSC Sleepers with USP of M/A Getzner, Australia (2019). India. RHD. (2004-05). Road User Cost Annual Report For 2004 - 2005. Economics Circle. Dhaka: Government of the People’s Republic of Bangladesh Ministry of Communications Roads and Highways Department. RHD. (November 2017). RUC Report 2016-17. RHD. Road Transport and Bridges Road Transport and Highways Division. (January 2016). Regional Road Connectivity Bangladesh Perspective. Dhaka: Government of The People’s Republic of Bangladesh Ministry of Road Transport and Bridges Road Transport and Highways Division. Stefan Marschnig, A. P. (2014). Under Sleeper Pads @ for tracks of Indian Railways. Trackelast. (n.d.). www.trackelast.com. Retrieved 2022, from under sleeper balast protection. Veit, P. (2012). Economic Evaluation of Under Sleeper Pads. Retrieved 2022, from www.ebw.tugraz.at Vít Hromádka, E. V. (2015). Risk Analysis and its Importance in Economic Valuation of Large Infrastructure Projects. European Journal of Research on Education by IASSR, ISSN: 2410-5465, Book of Proceedings ISBN: 978-969-7544-00-4, European Journal of Research on Education by IASSR. WB, BR, CPA and CES. (2007). Feasibility Study for Construction of New ICD. Dhaka. World bank. (6/28/2022). world bank. Retrieved October 10, 2022, from http://www.worldbank.org/: https://data.worldbank.org/country/bangladesh Footnotes 1. http://www.trackelast.com/undersleeper-pads.html 2. Data collected from engineering team, DCCRPPF (note, total quantity of ballast required for main line: 1,205,718 main line (at 2.118 cum/m). requirement of ballast for various components (with 300 mm for main line and 250 mm for other than mainline) 3. Total 576.7 track km for 1-7 components under DCCRPPF project 4. Guidelines for the Economic Analysis of Projects, ADB 2017 5. Bangladesh Bank(BB) December 2022 7. Picture source: from online (https://www.delkorrail.com/track-products/under-sleeper-pads) and experience and types ofapplication using under sleeper pads (USP) and under ballast mats (UBM)/ https://www.oevg.at/fileadmin/user_upload/Editor/Dokumente/Veranstaltungen/2015/Fahrweg/docs/godart.pdf 8. Ordinary Least Squares 9. RSS = Residuals sum of squares and TSS = Total sum of squares, formula source: Jim Frost, Regression Analysis by Example" by Samprit Chatterjee and Ali S. Hadi/ The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman 10. where k is the total number of repressors in the linear mode 11. This formula has used for significance tested by the t ratio Table Table 2 is available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. Supplementary Files Table2EconomicIRR.docx 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-6034060","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":416081477,"identity":"cc0a2c7a-fe57-4b18-af8d-6b7efc25dd0f","order_by":0,"name":"Shamema Akter","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0001-8666-411X","institution":"BCL Associates Limited, Dhaka, Bangladesh","correspondingAuthor":true,"prefix":"","firstName":"Shamema","middleName":"","lastName":"Akter","suffix":""}],"badges":[],"createdAt":"2025-02-15 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rate\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6034060/v1/6c3decfd71a0f983730d3d8c.png"},{"id":78154632,"identity":"6c5986a3-242a-423d-8a22-52ee81831e42","added_by":"auto","created_at":"2025-03-10 12:19:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":417449,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of Benefits and saving in LCC\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6034060/v1/f4ff14846e90af14f0e27404.png"},{"id":78155875,"identity":"ff160f61-c185-4c04-885a-5ab27ab52a58","added_by":"auto","created_at":"2025-03-10 12:35:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":250871,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUnder Sleeper Pads\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6034060/v1/b7c079b46b08cf8ea0060c50.png"},{"id":78154635,"identity":"4b043bf7-982f-429c-8290-de72d4f04032","added_by":"auto","created_at":"2025-03-10 12:19:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":260017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHistogram (Chart -1) and Scatter Plot (Chart -2)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6034060/v1/51ece04c24f106d873a8d170.png"},{"id":78157380,"identity":"398c369a-4846-40b3-abfb-5515da55d55c","added_by":"auto","created_at":"2025-03-10 12:51:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3260298,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6034060/v1/8a80eecf-2697-40ab-9777-f6d46d497be6.pdf"},{"id":78155605,"identity":"36cefd9a-07df-4b06-9cc4-6fdb893911dc","added_by":"auto","created_at":"2025-03-10 12:27:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16770,"visible":true,"origin":"","legend":"","description":"","filename":"Table2EconomicIRR.docx","url":"https://assets-eu.researchsquare.com/files/rs-6034060/v1/19fa76256e1fbbd76f9a877b.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEconomic Analysis of Under Sleeper Pads (USPs) for Enhanced Railway Infrastructure and Economic Growth in Bangladesh: A Case Study of the Dhaka-Chattogram-Cox’s Bazar Corridor\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWith rapid advancements in transportation and increasing demand for efficient, sustainable infrastructure, railway systems worldwide are evolving to support economic growth and resilience. In this context, the implementation of Under Sleeper Pads (USPs) represents a significant innovation for railway superstructures, which can be enhancing track stability, reducing ballast degradation and contributing to lifecycle cost efficiency. This study has focuses on the economic impact of USPs in Bangladesh, specifically on the Dhaka-Chattogram-Cox\u0026rsquo;s Bazar corridor, one of the nation\u0026rsquo;s busiest and most strategic railway routes. By evaluating the relationship between USP installation and GDP per capita, this research seeks to demonstrate how this infrastructure technology may influence Bangladesh's economic development.\u003c/p\u003e \u003cp\u003eThe primary research questions guiding this study include: How does USP adoption affect track resilience and maintenance costs? And what is the correlation between USP implementation and economic indicators, such as GDP per capita, in Bangladesh? The hypothesis is that USP integration will yield positive economic impacts, as evidenced by a correlation between enhanced railway infrastructure and economic growth metrics. This correlation is anticipated because USP enhanced rail infrastructure supports high-traffic (both passenger and freight) demands, reduces long-run maintenance costs, and minimizes environmental impacts associated with ballast degradation depletion.\u003c/p\u003e \u003cp\u003eThe motivation behind this research stems from Bangladesh's increasing transportation demands and the urgent need to modernize infrastructure to support sustainable economic growth. I Inspired by insights gained at the Asian Development Bank (ADB) Railway Innovation Forum in 2019, this study aims to assess the lifecycle benefits and cost-effectiveness of USPs as a transformative solution. Existing literature on USPs in Europe and Asia demonstrates their effectiveness in improving track stability, sinking vibration, and extending ballast life, which collectively lower maintenance costs and increase operational efficiency. Despite these findings, there remains a gap in understanding USP applications within Bangladesh's unique railway landscape, as well as its potential economic benefits at the macro level.\u003c/p\u003e \u003cp\u003eThis report addresses these gaps through a systematic review of global USP applications and an empirical analysis specific to Bangladesh's railway system. Using a 28-year time series dataset, an Ordinary Least Squares (OLS) regression model assesses the relationship between USP implementation and GDP per capita, providing insights into the potential economic value of this technology. The findings of this study not only contribute to infrastructure planning in Bangladesh but also offer a model for other developing nations aiming to optimize rail transport systems in support of greater economic objectives.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Objectives\u003c/h2\u003e \u003cp\u003eThe objectives of this research are to assess the economic impact of implementing Under Sleeper Pads (USPs) in railway infrastructure, specifically on the Dhaka-Chattogram-Cox\u0026rsquo;s Bazar corridor. This includes analyzing USP\u0026rsquo;s effectiveness in reducing track maintenance costs, enhancing track resilience, and extending lifecycle benefits. Besides, the study aims to explore the correlation between USP adoption and GDP per capita, highlighting its potential contribution to economic development in Bangladesh. The ultimate goal is to provide insights into the cost-effectiveness and sustainability of USP applications in modernizing national railway networks.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eIt is observed that there is a lot of researches have done on railway USPs, and it has have reviewed some reports which is given below in the literature review-\u003c/p\u003e\n\u003cp\u003eHarald Loy (2009) according to a research report, tests in Germany have shown that the use of sleeper pads allows for significantly improved track behaviour and dynamic vibration behaviour compared to traditional ballasted track. In Austria, turnouts with USP were already installed in 2002 and measurements have shown a reduction of vibrations in the 40 Hz \u0026ndash; 50 Hz frequency range. Track last Under Sleeper Pads are provided for Noise \u0026amp; Vibration (N\u0026amp;V) protection. They are also used for Track Quality purposes to improve track stability, performance, minimize track operation and maintenance cost and preserve track ballast from the effects of attrition\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e1\u003c/sup\u003e.Track last have been supplying USPs for over 30 years. These were originally developed as soft pads in order to reduce ground borne noise being transmitted through the ground to adjacent building structures. It is a new technique have been successfully developed for integrally fixing USPs during the output of concrete sleepers, producing a composite sleeper pad solution.\u003c/p\u003e\n\u003cp\u003eP. Godart\u0026nbsp;(2015) conducted a paper with \u0026ldquo;experience and types of application using under sleeper pads (USP) and under ballast mats (UBM)\u0026rdquo;. In this report, under sleeper pads (USP) and under ballast mats (UBM) elastics in rail trucks are discussed. It has shown the positive impact of a \u0026ldquo;USP on ground borne vibration, correlation between the USP\u0026rsquo;s dynamic stiffness and vibration levels in the surroundings was found, here also states about rolling noise i.g. higher sleeper end vibration (+6dB), but not leading to higher global noise emission. Used of USPs results in reduced pressure between sleeper and ballast and longer ballast life. It distributes the load well over the length of the sleeper. Here is shown an excellent performance of USP.\u003c/p\u003e\n\u003cp\u003eIn contrast, Peter Veit (2012) conducted a study on economic evaluation of under sleeper pads. In this report shown, the benefits of USP use in railway track are remarkable higher. So, outstanding higher IRR for USP as radii face in general higher maintenance demands. In this paper has shown an IRR up to 20% for high loaded 20% - 40% high loaded sections. Also stated, the additional cost for USP only affects cost results equal to 50% of USP\u0026apos;s sleeper cost, limiting the USP application area to tracks carrying 20,000 gross tons per day. However, if the service life cannot be prolonged at all, USP can be proposed for lines carrying a minimum of 13.000 gross tons per day. And the higher the line speed, the higher the qualities demand for the track and thus \u0026nbsp; the USP will be more beneficial\u003c/p\u003e\n\u003cp\u003eFurthermore, P J Gr\u0026auml;be, B F Mtshotana, M M Sebati and E Q Th\u0026uuml;nemann(2016) conducted study on The effects of under‑sleeper pads on sleeper\u0026ndash;ballast interaction. According to a technical paper, \u0026lsquo;\u0026rsquo;With the introduction of concrete sleepers and the phasing out of wooden sleepers in some countries, the traditional track structure became significantly stiffer and an elastic pad or rail pad was introduced between the rail and the concrete sleeper. It is unfortunate that this process of corrective maintenance unavoidably contributes to further ballast breakdown and degradation. It is exactly this aspect that prompted the development of under-sleeper pads (USPs), a relatively new contribution to the traditional ballast track structure, aimed at reducing ballast and sleeper deterioration, and lengthening the ballast tamping cycle. A life cycle cost calculation, which falls outside the scope of this paper, would be required to compare the benefits of reduced ballast maintenance to the cost of the product. If such a calculation produces a significant cost benefit, the introduction of USPs on passenger, freight and heavy-haul lines should play a significant role in reducing ballast and sleeper maintenance costs. Potocan and Dorfner (2013) addressed this aspect in their research and found the USPs to be financially viable\u0026rsquo;\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003eRDSO (2019) report indicates that USP trails of 1 km each at SCR and NR firms were undertaken from June 2012 to May 2017 along with comparison of USP and non-USP sections. The conclusion from RDSO is provided below:\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTrack settlement is 40- 50% less in USP sections\u003c/li\u003e\n \u003cli\u003eLess pulverization is observed\u003c/li\u003e\n \u003cli\u003eConsiderable saving in maintenance expenditure\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe introduction of USPs specifically on heavy-haul lines would offer most significant advantages with respect to ballast settlement and breakdown. These advantages are most likely to lengthen general ballast tamping and screening cycles, resulting in significant life cycle cost savings.\u003c/p\u003e\n\u003cp\u003eThe above literature review has mentioned USP\u0026apos;s elasticity, reliability, low cost with economic benefit, long durability of rail track, over loaded freight and noiseless plus vibration free comfortable travel of passengers, which the author have examined in her research in the context of 7 components of the DCCRPPF project. Moreover, the author has researched the effect of using USP\u0026rsquo;s on economic benefits of the project and risk analysis of rail track in the development of the country\u0026apos;s economy. It demonstrates that adopting USPs could contribute to infrastructure sustainability and economic growth, aligning with broader economic and environmental goals.\u003c/p\u003e\n\u003cp\u003eFurthermore, the author has shown in the study that if USP is used in Bangladesh Railways, what kind of impact it can have on the economic benefits, risk analysis and development of the country\u0026apos;s economy, as well as what kind of relationship it has with GDPpc.\u0026nbsp;\u003c/p\u003e"},{"header":"3. Methods and materials","content":"\u003ch3 id=\"_Toc12790333\"\u003e3.1 Methodology and data collection\u0026nbsp;\u003c/h3\u003e\n\u003ch4 id=\"_Toc184291513\"\u003e3.1.1 Methodology\u003c/h4\u003e\n\u003cp\u003eThis study has examined the economic impacts of using Under Sleeper Pads (USPs) in railway track infrastructure, focusing on their effect on GDP per capita as an indicator of economic growth. The research employed an Ordinary Least Squares (OLS) linear regression model, utilizing a time-series dataset spanning 28 years. This model investigates the relationship between USP usage and GDP per capita, considering USP as the dependent variable and GDP per capita (GDPpc) as the independent variable.\u003c/p\u003e\n\u003cp\u003eTo ensure data reliability and robustness, regression analysis was conducted using SPSS, yielding statistical indicators such as R-squared values, significance levels, and correlation coefficients. Descriptive statistical tools, including scatter plots and correlation analysis, were used initially to verify the association between variables, allowing for a more precise analysis. The regression output provided insight into the sensitivity of the relationship between USP implementation and economic growth.\u003c/p\u003e\n\u003ch4 id=\"_Toc184291514\"\u003e3.1.2 Data Sources\u003c/h4\u003e\n\u003cp\u003eThe research relies primarily on secondary data. GDP per capita data was sourced from the International Monetary Fund (IMF) (2024). Cost-related data for USPs and associated track works were collected directly from the Dhaka-Chattogram-Cox\u0026rsquo;s Bazar Rail Project Preparatory Facility (DCCRPPF) under the Ministry of Railways, Bangladesh. The economic evaluation included multiple cost components, such as ballast cost, USP installation cost, and track maintenance savings etc. all costing data has collected from engineering team of the project and base on market price.\u003c/p\u003e\n\u003cp\u003eThe economic analysis has done according to the Asian Development Bank (ADB) guidelines 2017 and \u0026nbsp; used a discount rate of 9% to calculate Net Present Value (NPV) and Economic Internal Rate of Return (EIRR). Sensitivity analyses also applied this rate to assess the economic robustness of the USP project under varying cost and benefit scenarios.\u003c/p\u003e\n\u003ch3 id=\"_Toc184291515\"\u003e3.2 Economic Evaluation of Under Sleeper Pads (USP)\u003c/h3\u003e\n\u003cp\u003eAuthor collected all kinds of cost data from DCCRPPF project for economic analysis.\u003c/p\u003e\n\u003cp\u003e\u003cspan id=\"_Toc184291516\"\u003e\u003cstrong\u003e3.2.1 Ballast \u0026nbsp;cost\u003c/strong\u003e\u003c/span\u003e\u003cstrong\u003e\u003ca title=\"\" href=\"#_ftn1\" name=\"_ftnref1\"\u003e\u003c/a\u003e\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ecost of ballast (at BDT 9619 or USD 91.56 / Cum/m) in million: BDT 11,598 or USD110.4 \u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eFor track works, unit costs have been based on recent national and international market rates and also by deriving from the average accepted unit prices of recently completed similar track works Projects. Inflation Rates have been applied to the unit prices.\u0026nbsp;\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eCost of USP to cover all Components\u003ca title=\"\" href=\"#_ftn2\" name=\"_ftnref2\"\u003e\u003c/a\u003e\u003csup\u003e3\u003c/sup\u003e (at BDT 12.9 or USD 0.12 Million/Km): \u0026nbsp; BDT 7,439 Million or USD 70.81\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSaving of (reduced ballast cushion) Ballast at BDT 2.46 or USD 0.023 Million/Km): BDT1,419 Million or USD 13.50 Million \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCapital cost to be invested to implement USP including reduced ballast cushion: BDT17,618.33 Million or USD 167.7 Million \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAdditional Capital cost to implement USP: BDT 6,021 Million or USD 57.3 Million \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cspan id=\"_Toc184291517\"\u003e\u003cstrong\u003e3.2.2 Basis of Costing and Level of Accuracy\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe level of accuracy is considered reasonably good, but cost may vary to the extent of further fluctuations in prices of major components and raw materials in global markets.\u003c/p\u003e\n\u003cp\u003e\u003cspan id=\"_Toc184291518\"\u003e\u003cstrong\u003e3.2.3 Total Project Capital Costs\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe resulting capital cost estimate for the Project is BDT 757,217.98 million or USD 9,131.91 million, as summarized in Appendix Table.\u003c/p\u003e\n\u003cp\u003e\u003cspan id=\"_Toc184291519\"\u003e\u003cstrong\u003e3.2.4 Standard Factors\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe author has used a discount rate of 9% (real, i.e. ignoring inflation) according to an ADB guideline.\u003ca title=\"\" href=\"#_ftn3\" name=\"_ftnref3\"\u003e\u003c/a\u003e\u003csup\u003e4\u003c/sup\u003e In keeping with previous rail project analyses, economic costs are computed by multiplying financial costs by the standard conversion factor (SCF) 0.80 and exchange rate in 2022 is BDT 105.1 per\u003ca title=\"\" href=\"#_ftn4\" name=\"_ftnref4\"\u003e\u003c/a\u003e\u003csup\u003e5\u003c/sup\u003e USD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.5 Additional capital cost to implement USP\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEconomic costs are expressed in monetary values in a fixed year, 2022 for this analysis. Physical contingencies are included but not financial contingencies. Cost inflation and price escalation during construction are not economic costs. Price escalation does not alter the materials used or the end result. Economic costs exclude taxes, which are \u0026ldquo;transfers\u0026rdquo; and do not measure resources consumed.\u003ca title=\"\" href=\"#_ftn5\" name=\"_ftnref5\"\u003e\u003c/a\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.6 Capital costs for Under Sleeper Pads\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe financial cost has collected from the DCCRPPF project. Excluding taxes, the economic cost of USP is BDT 4.17 billion or USD 0.04 billion, which is 69% of the financial cost of BDT 6.02 billion or USD 0.057 billion. 30 years is adopted as the analysis period, in view of the assets long lives and the greater weight given to later years due to the reduced discount rate (9% instead of 12 %). \u0026nbsp;See \u003cstrong\u003eTable 1\u003c/strong\u003e. With USP, the EIRR is 18.3% pa and economic NPV is USD 18.6 million, exceeding the threshold return of 9%.\u003c/p\u003e\n\u003cp id=\"_Toc123812022\"\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Economic Cost-benefit Analysis of Under Sleeper Pads\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 944.734%;\" colspan=\"7\"\u003e\n \u003cp\u003eCosts and Benefits USD Million)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 944.734%;\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eSavings in Life Cycle cost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCapital cost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSavings in Recoupment of ballast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSaving on Ballast Cleaning after 10th Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrack Maintenance Machine Saving\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSaving in Leveling-Lining\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSaving in Ballast cleaning enhanced by 66.7% with Concrete Sleeper with USP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eNET BENEFIT\u003cbr\u003e\u0026nbsp; (USD Million)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-39.66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e-39.66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e31.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.87\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e32.49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2036\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e2040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e4.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2056\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21.95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-29.34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.55\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.734%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2546%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 53.1251%;\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSource: Author/Economist calculations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40%;\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiscount rate @ 9%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.988%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEconomic NPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45%;\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.988%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEIRR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.12513%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45%;\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 879.988%;\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eB:C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.63\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes:\u003c/p\u003e\n\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eFinancial costs converted to economic costs using a standard conversion factor of 0.80 and there is no tax or contingency included into economic costs. \u0026nbsp; Residual value 69% after 30 years. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSaving in Recoupment of ballast after 3 years of initial ballasting due to pulverization at 2.5% of total ballast requirement \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSaving in Ballast due to Ballast Cleaning /Deep Screening of ballast at 3% quantity every year from 10th year of construction to 30th year due to implementation of USP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSaving on non-Procurement of Track Machine unit due to implementation of USP after 18 months to 30th year (Machines\u0026apos; cost, their Maintenance cost and cost of Engineers/Operators)\u003c/li\u003e\n \u003cli\u003eSaving in Levelling-Lining-Tamping at INR 200,000 per Km once in 3 years for 30 years\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSaving in Ballast cleaning at INR 313108/year \u0026amp; Km \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTotal savings from the \u0026nbsp;4th year to 30th year after completion of the construction \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe benefits minus the costs, plus ENPV and EIRR in real terms\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch3 id=\"_Toc184291522\"\u003e3.3 Sensitivity Analysis\u003c/h3\u003e\n\u003cp\u003eSensitivity tests have been carried out and switching values calculated. Table 2 shows the results of the analysis of sensitivity tests and switching values. \u0026nbsp;In this table the blue numbers represent the base case, the black numbers the sensitivity tests, and the red numbers the switching values.\u003c/p\u003e\n\u003cp\u003eThese calculations and results are explained in Table 2 which also contains an analysis of the sensitivity of the findings to possible variations in the investment costs and additional costs of USP that have been assumed. Sensitivity analyses are generally conducted as part of life cycle cost (LCC) evaluations in order to attach critical values for sensitive input data and to check the stability of the result. The economic internal rate of return (IRR) is sometimes used to specify the economic efficiency of an additional investment. The EIRR is the discount rate for which the net present value of an investment equals zero (Table 2). Discounting rate of 9% pa is generally in use regarding service lives of 30 and more years. This Project is the feasible from the economic point of view. \u0026nbsp;Its economic internal rate of return is 18.3% pa as well as benefit and cost ratio is 1.63 (benefit cost ratios\u0026gt;1). \u0026nbsp;It has found that under-sleeper pads railway track (USPRT) is a robust project, as sole very substantial cost increases of USPs (63%) or benefit reductions (39%) would affect the overall viability of the project. Table 2 and Figure 2 summarizes the result of sensitivity analysis\u003c/p\u003e\n\u003cp\u003eThe figure 2-3 shows the net present value (NPV) of the costs and benefits generated by the saving in life cycle cost (LCC). In addition, the distribution of benefits is illustrated graphically. Benefits from track maintenance machine savings represent the majority and correspond to 43% pa whereas benefits from recoupment of ballast Savings 3% pa, Ballast Cleaning (after 10th Year) Savings 17% pa, Leveling-Lining Saving 12.2% pa and Track Machine Operators / Staff savings 25.0% pa. (See, Figure 2).\u003c/p\u003e\n\u003ch3 id=\"_Toc417569850\"\u003e3.4 Descriptive Statistics\u003c/h3\u003e\n\u003cp\u003eNow the author is going to use descriptive statistics first to describe the nature of the variables. The author has used bi-variate models such as scatter plot, correlation coefficient etc. to see if there is association between variables.\u003c/p\u003e\n\u003cp\u003eSo, the author has used the regression model. \u0026nbsp; The author suggested null hypothesis Ho: \u0026beta; =0; there is no relation between USPs railway track (USPRT) and GDP per capita. And alternative hypothesis H1: \u0026beta; \u0026ne; 0; there exists relationship between under-sleeper pads (USPRT) and GDP per capita. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe author specifies the following bi-variant regression equation for observing the relationship between two variables. Here \u0026alpha; is a constant term and \u0026beta; is the coefficient of X variable that represents GDP. GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. GDPpc data are in current U.S. dollars. And, Under Sleeper Pads (USPs) were first implemented on European railways in the 1980s and are designed to enhance the durability and stability of railway tracks. UPSs improve elasticity, minimize ballast degradation, reduce maintenance needs, and lessen vibrations and noise, creating a more comfortable passenger experience. USPs are adaptable to high-load and high-speed railway lines and are cost-effective, providing extended track life with lower lifecycle costs. The UPSs are particularly valuable for rail networks facing increased demands, as its can reduce environmental impact by limiting the need for additional ballast material.\u003c/p\u003e\n\u003cp\u003eHere \u0026micro; is the error term. It is a variable in a statistical or mathematical model, which is created when the model does not fully represent the actual relationship between the independent variable here GDP per capita (X) and the dependent variable in our case USPs railway track (Y).\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003e3.4.1 Descriptive findings\u003c/h4\u003e\n\u003cp\u003eDescriptive statistics has utilized to examine the characteristics of the variables involved, specifically GDP per capita and the impact of Under Sleeper Pads (USPs) on railway track infrastructure. Key statistics, including the mean, standard deviation, minimum, maximum values, and variance, has computed for each variable.\u003c/p\u003e\n\u003cp\u003eDescriptive statistics highlight that the mean GDP per capita over the period studied was approximately USD 1888.345, with substantial variability (standard deviation of USD 1208. 2). \u0026nbsp;For instance, GDP per capita over the period ranged from 491 to 4,640 USD. For USPRT, the average impact level was estimated at 5825737.0 and (standard deviation of USD 6954524.8), with a significant range, indicating variability in the application and economic benefits of USPs over time. The skewness and kurtosis measures reveal a non-normal distribution, which was addressed through Ln transformation to better interpret the relationship between variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe author has taken a time series of data set containing data from 28 years. Therefore, it can see from the histogram and scatter plot that after the Ln transformation the data set is normally distributed (Figure 4 and Table 3-6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Descriptive statistics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" valign=\"bottom\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e4149.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e30756881.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" valign=\"bottom\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e491.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e1735296.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e6.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e14.400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" valign=\"bottom\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e4640.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e32492177.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e8.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e17.300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" valign=\"bottom\"\u003e\n \u003cp\u003eSum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e54762.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e168946374.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e212.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e443.300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" rowspan=\"2\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e1888.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e5825737.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e7.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e15.286\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e224.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e1291422.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e1208.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e6954524.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" valign=\"bottom\"\u003e\n \u003cp\u003eVariance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e1459680.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e48365415471031.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" rowspan=\"2\"\u003e\n \u003cp\u003eSkewness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e0.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1.341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\" rowspan=\"2\"\u003e\n \u003cp\u003eKurtosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eStatistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e-0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-1.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2.927\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eValid N\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\" valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\" valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\" valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 100px;\" colspan=\"6\"\u003e\n \u003cp\u003eSource: calculation by Author/ Transport Economist and SPSS/ 2016software, after Ln used: LnGDPpc and \u0026nbsp;LnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA scatter plot and correlation coefficient analysis demonstrated a likely positive relationship between GDP per capita and the use of USPs, suggesting that as GDP per capita rises, investment in resilient railway infrastructure, such as USPs, becomes more prevalent.\u003c/p\u003e"},{"header":"4. Empirical Results and discussion","content":"\u003cp\u003eThis Empirical analysis supports the economic rationale for adopting USPs in Bangladesh\u0026rsquo;s railway system, showing that USPs can enhance the resilience and cost-effectiveness of railway infrastructure, which is essential for supporting higher traffic volumes associated with economic growth. The analysis projects a cumulative increase in GDP growth of approximately 0.0020% over the initial eight years following USP adoption, with incremental increases anticipated over a 30-year project life. This positive correlation, albeit weak, aligns with global findings where infrastructure investments often yield substantial economic returns.\u003c/p\u003e\n\u003cp\u003eA linear regression model with GDP per capita as the independent variable and USP impact on railway infrastructure as the dependent variable was employed. The analysis yielded the following regression tables (4-6)\u003c/p\u003e\n\u003cp\u003eHere from the scatter plot it can observe a likely positive association between under-sleeper pads railway track (USPRT) and GDP per capita variables. The value of \u0026beta; is positive 0.222. The intercept term \u0026alpha; is 13.664. In this analysis, time series data from the IMF and others data from DCCRPPF project has taken and OLS\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e8\u003c/sup\u003e linear regression has done.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Regression results\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"111%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficients\u003csup\u003e(a)\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7px;\"\u003e\n \u003cp\u003et Stat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 6px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e95% Confidence Interval for B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 19px;\"\u003e\n \u003cp\u003eCorrelations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollinearity Statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003eLower \u0026nbsp;Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eZero-order\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003ePartial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003ePart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eTolerance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eIntercept (Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e13.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e10.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e10.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e16.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ea. Dependent Variable: LnUSP, Source: calculation by Author and Output by SPSS2016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Model Summary\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\"\u003e\n \u003cp\u003eModel Summary\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. Error of the Estimate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange Statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eDurbin-Watson\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Change \u0026nbsp;Sig\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;F Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003edf1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003edf2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSig. F Change\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.664\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"bottom\" style=\"width: 99.8911%;\"\u003e\n \u003cp\u003ea. Predictors: (Constant), LnGDPpc, Output by SPSS2016\u003c/p\u003e\n \u003cp\u003eb. Dependent Variable: LnUSP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;ANOVA\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003edf\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSS\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMS\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eF\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSignificance \u0026nbsp;F\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eRegression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e12.850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e13.534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: calculation by Author and Output by SPSS2016, a. Predictors: (Constant), LnGDPpc and b. Dependent Variable: LnUSP, SS=Sum of Squares, MS=Mean Square\u003c/p\u003e\n\u003cp\u003eThe findings support the economic rationale for USP adoption, particularly as an infrastructure development that aligns with Bangladesh\u0026apos;s broader economic growth. As GDP rises, the increased freight and passenger traffic further justify the use of USPs, which contribute to more resilient and cost-effective railway infrastructure. The positive impact on economic growth is estimated to be gradual, with a cumulative GDP growth increase of 0.0020% in the initial eight years, rising steadily over the 30-year project life.\u003c/p\u003e\n\u003cp\u003eThis research underscores the importance of integrating advanced for Bangladesh railway technologies to support sustainable economic development. Although the model\u0026apos;s low explanatory power suggests the presence of other influencing factors, the positive association aligns with global trends where GDP growth often correlates with higher infrastructure investment returns.\u003c/p\u003e\n\u003ch2 id=\"_Toc184291526\"\u003e4.1 Regression Analysis\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis study has explored the relationship between Under Sleeper Pads (USPs) usage on railway tracks and economic growth, measured by GDP per capita. A linear regression model with GDP per capita as the independent variable and USP impact on railway infrastructure as the dependent variable was employed. The analysis yielded the following regression equation:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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zgeHENIN+R1NPhC5qWJLBaMPIX984LfB/hhkY2MAqB1HueSnPpGf13n+vP588LVB29Iy+X8OUanYnw6QMEt/sZ+8tGkV4MMmBmfaF/UmPQZJBlFezwvXlG0WQjS5XmxxXfk3r1/IUexPr1l6vdloO3Avpcd0EX3WJU/IZPQjG//nvuL4/B6J6Fe+0WfUm0GpRH5cfh/3IUSTc+X1rQkPbUv7jWPzc6d1o1+H/DwMghPlx3VOhY1zRfnkC8mjHaSlshmyRL+ndeZ1XqeQyciT7uc+i6gm5cTaONIjqsk+1gNSV/qItCFtpxzyzxrdGlM0aRvRE9rC+yqi3dEPRNTSvuvzkM1GwTWKa0ud0y8xG0GIJvcl1ye9V4a8LxYB15S6xHViW0REVRYH0+fcJzUxjOn19BrWxDSEdMi0OSx2TrMnvFHjA1/KhMjUpGArw5uGbRZCNPMo4GYR9ZlF6paREM1l6d9FE7JUWqO5TPAZSz1nXZ8JY4mmEjIfbWs0RXL6/q3zPvzgBz+YfIEdukRiU0QTGIgUqTIh4simLJZlE01gMCfKsw6DhqK5HFBPooRDptrHJvpuo6d21w1FU4by/PPPzySIKUzD33777b1+kzNn00QTmE5jQ6zkIoiH/TIOyyiafNlalwg/kVlkgras4yAYU6b5WtNlImQ/pqGXhRDNZavXqsGyAkTzl7/8pf0ovUE2+XyeZUYBF+GH2vmSOMs9t6miSeVDqrrWLG4FEA7le1yWUTSB+5+oJmv9VvXah2TSv2zrJpv5mstllM34UfFllLmIsrJWV0GaHSPDMitEw/miMkQ2iWTyuTLPw26bKpoBAxRyhQRsVUIy12WtngwHwUSA12UaXTYWntLOH3QSEdlslkI0RURERGT9UDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFU0RERERGQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVh70Txy5Eize/fu5sSJE9OUrQn9sHfv3i3fDyIiIrJxrK1onjlzptmzZ89EMk+fPj1N3dogmbt27Wr27ds3TRGRZYLPrR//+MfNzTff3HzyySfTVJF+fP/73598vr/99tvTFNmq/PSnP22OHz8+6HNklmP6MEg0uYG3bdt2YTt8+PB0z3ycOnXqknKRoRT279y5c9B5EUw2PrhT8jYQ6UtJz5PXg7I4nvTIwzn2798/zXGedH+6UTZRRdqT0pU/j0LyupS/tB04cGB61HloA+dbRtmkbrQ3r3MKXxrYT79HG2kPafm17gN9GdeUMruYJX/pOiwr1JcvaNG3pfu1BteG90J6fFybEtGX6bXk/7/61a+mOS5laP5FQNs//elPXzgf78mxBJBzIZi08b333pumXoT7OyQ06kP/co3yPkjzpBv9RfkMJiW+/e1vN1dccUXx2C996UuT8yjAw+Ca0afHjh3bkL77yU9+Mrlnn332Wa/VFoTPiW984xvNb3/720uu/29+85vm9ttvv/D+fuCBB5q33nrrsnsE2cSLzp07N02Zn8ERzRhEcrmalxiQ2UoRSAYr9uViWIK8DAi1SGYMVKUBkIvEPo5PxYX/k8axUS7/RlkpkTdNJw1BJo0tHbzT/PRDpNHWSD969OgkHaKvGDCCuC4Bx/K61MY4Pi1zs6FODJq1Ogfsp0+in7gG9APpaX90Qf8yQFMW56vdK8HQ/MAxfdq0LNCnfAhFP9JGhIU2d0VIuJ85lrwhMRz/uc99btJ+Pi/SDzTeC+Tn/RNlc/6QulychuZfJNEvnKckgIuAvqIt3/rWt4pyEBJK/6ZtRSqoG+//9DjuveibGDDiMyUk9Ec/+lHxXHfeeedkfyqjv/71ry+Ud+jQoeJxUqYmmiH1ixzQA+6X7du3K5tbECTzl7/85SXXHcn8sz/7s4lc8r7//Oc/P7n3+Dx58803L7tHKIN7Z1H35mDRZMDkw2YMSQlhKA3KfJAy0HfBhymd1yYdIWUhKznsI09KSGIuGLwmPScXvyD6L29LrU5x3rQ+5CEtrUvpfG3RJAZs9m82XC8khLpEG9qkjP35lw3KID1vfw3y037uk1T4awzNH0S7uto0C3EfLXIQQUCob1pmfGHh/dR2rpCx5557bppyHu5R0vO6Un/Sc4HlfKRzL8yTf9FwDu6Bsc6B3LWVH8L+u9/9bppyEUSm1P4Qxnyw4H4O2SxFKEOM8qhnXGPeB2PI0VbjrrvumvTnWH3JdeTLAVEr2RoQjfzsZz/bnD17dppynlKEkzS+jCCff/rTn6ap5/n973/f7Nixo3n99dcX8pk3s2jWJG0e+ADkQ4yN/weci7Rc8kqEmLXVL4Smlod95EmJY9J6tRH5czhnW/l5nUr5SWNQSimdD9GpCU700xBxGgPqEXWMttbqXINrwnF9xRnJH9L2ofmBtnDP8oVsljZ1Ee/DRXwIAG1j0CvNVIRczHouju9bV/qN/NzPY+SflTHPEW1A0kvl//znP5/sr0U7a9REE4hQUibvmXx/TTSBgalWpvSHsWzsvuRzkXNw33i91h+u9w033NA89dRTl1xv0vkMye+BkEmWxORiCnfffffkM6+0byijiSYDFvnYiDow4CJHvGbQyqNSQZSfDswc13egDiloI6Ss1gb2kScl2tO3HnGOHM5ZKr9Wp1r+nNr5aiAW5O/bno0g2jq0TiHNtXsqJc7Rd5p9aP6AAZx6zdqmLiiPchclPlFeqZ5t0bQuIqLZNxoYEUreb0Pyf+9732vNH9O+bGnUNk1vax/n4D3Wdg7eUxEp5BxMszM9yucdaRxfmnr/+te/Pim/VnbsH7o8oE004frrry+2ex7RDCkmD1N03P/UgzT6getU6gPuE/oqrgf9l07R53377rvvXojYxbnarg2DbVo+GwMsbYzjmF4kT5wn6puWG9Pd7GcqnPsvrVe+rICHc9L+YB99lNYj3WJ6nfqyLCL6jn1/+Zd/OYlKDeG+++6bnCuPWMn6QTTzU5/6VPPKK69ccg+2ceWVVzZf/epXi/fHwYMHJ+WVptaHMppoQsgZ8hcDGB8ovCFJL0UoeYPxBmfj/7yRyd8XjsujfTk1qQvYl4sddaVs9iEd1K2NmvhFnyAhKbU6RX93SVTtfG2QP29nDfIO2fqWmzJUyvjywrXg/ui7lCO+iIyVH6h/3IND29SXuC/m/QAI4r4syUUIS2lfFwzMQ45l0OZ91nctZN/8vH9jcE/rwnUlvUuiGey5p7v6m88F8nJPcm9GuSFvpagk528rO0RmqOh3iWbsz6fPa6IZUdCvfe1rrf0Qssl7gD7g2tAvIWm5vHFtkF76Jq5j5E3rRhmILuXSX+zjviVfm2hyHOVzXCy9iPLjuPw1dWIKkv7J17tFXsoLsSQ/695K+UM28zrWpB2ppr7cQzHtHdcE2axdzxLIKufZqAeRZPP48pe/PLlH/vjHP05T2uF9QUTzmWeeKd5TvN8RzX/6p38adM+VGFU0I28eDYr02uAd+/kQGSIRwHFdksP+tjbUyuADgPqwn416crFKxDkC8kXkjQ+o/Li8Tml++qGL/Hx9ID/tWRb6Slnkiw0Z7HuPxDGUwXHx5YF+KJ13aP6IFPMv9G3TUCiPchc1eLTJ5KyiyTXhgy9ft1mDAZn+7StUQ/NzTagP7xX6jfcYEtenXelxXZCX/srXk5LOez8tI+rUFpGN8oZ+2PcVzVyASqIZDwP16W/ueY4nYpi3KeSNiGRAxJay0zRAkHifpfUPOUsje0hZm2iGGKbHcO0pK45jvWR+rnjQqtY/eTqySZlc47ScWv5oS359iKyyL3+QJyLQQ6KTUVZb/8h6QHSS+6OvaD7//PPF9ZwB907b1PoQNkQ080G2lp7Cm548fLgPoc8xIWW1NnSVgQBG/fg3pCIlzpFufADR5lwyoZSfD/W+AhXHDyHOsyzMImX0D/3KcV1RXwaCaDPSGNeN68GXIdJTqR+aH6hLmrZVRZO+Qh76fEmCmALvOz08NH+QygPvma57JuAY8vfpb/KWrk0pPaSsTQTiuJow1ugrmvl0b4gR+2Ljc46IYy7PJdraFMsAiLAFiFBJSqkfedP61+SsDY7JJbIPNUmL/ilFCUMG03MNFc0a8fDQLKLpOs31B9Ek4t1HChnDbrnllubkyZOX3cNB1xrOISytaA45TwrHMCC0EVJWK7tPGals8CGWE+foS14nBIrXiEtJTHOGng/IP/SYMaHt1KftviiRCmFbX0X59GkOx7EPuQ+G5qfevE7rkLaJ9NK90gWDC2X03bru3RKINMeWxG2oaIZk8v6ofYilhDT2jXwOzZ+D7NAe2tynfsD56Nc++eN65XlL6dwfpPcRzTySGP3MPrZ8SruvaObXNcRoyBeLlLY2pZIG5A3hqm25lJLWV5qifAbLoaI1i2iWniRfBtGcpf2yOqTRxz73x3e/+93J52fXPYG8KpoFOKZroCXK0lZ2nzKCGKDzsoaKX+RPywmR5d8uhp4PyN9XfMg7ZOvbfym0nWPb7osapf7LYWBuq1veh0PzI5m87toWQbw/8oFuVtrekyEkfdZNIv1DJHPo9PrQ/CVizRzXq+9aUPJzvfu0ibyla1NK534lvU0020Q/jufLUH58l2hG9C2fst4M0Wxrf8pQOYvy+4gWgzX3Btc5fS9vhmjypZToO1+KuLYcH/VRNKUEUviZz3ymUwqZMuc+73M/LKVosi8dqGqDVy09JfKUztMGHxClCFRKlF2bNmNfTS5yavXMJaSLyJ+Ww4dNfOB19cPQ8wH5+7ZzI6CN1KntvqhR6r8S5KndH6TnfTg0f848bWoj7rs+g3MfQuBKX2pI5wtJ17m4X3lCva9kRkSurzQOzV+C9zx1JDpIu7hv+tS1LS/70nRel65NKZ37g/Q20Qoxrq3jRCRKdWsTzXiwp3TcmKKZT51zz1D/rgeMgjY5KxHl815tO4Z1nHFvxZePWSKaQ6bOS3mB+5x99EkaxXbqXNros0YTyeRe73MPpVHSpRJN3szpgBp580G2lp4SeRgAhxDC0QaDDXlKg2qIQemp8JKYRnSUSE5K1IMPuj5E/rxfox/Y30afdqdEO/uuodsIok61+yL2530UQs7WRUSg8+sV0++5VA7Nn9PVplmJ+6LP4NwH+pCBlj5My6T+DG596s+9hJDmUUL6qvTQDcJXmr6Oc+bpQ/PnhKhG/WK9ZtuDOAH5eI/l+ULQ03Rel65NKZ06ddWB/iMP1ybvW64b+0p1q4kmx7T9ZFWIUfrE9xDiepSesEegaEdaJ57WJi2PrJYYKpoQT4PXfrica0C5+TWIp+dropk/rBPlIIhp/WqiWYp+Aj9JRHreH/Eg1SyiWZJ+WS+6njqvSSafB6Xf2QzR/OEPfzjo/VZisGjWhCiekE4HpJCwXGZq6SlxnrY8JaIeXYIa0Sjy09FAm0hni7SA+vBhmJbL/0nLhZVjSe9TD2jLn+7L5TcgDwM8efLrUiP6iQ/HZSHqRF+XoG3s5/qE+PFvyGDed3EPpfck7aU/8zLifsj7b2j+HOpEvtKXmnlYtGhC9D915Z6KdrKlgkOb+UBLz0/eSKttaRmxzrKUj41zpm0bmj+H64hk5gMuaRzfFiWN9nI/pcfS5hC2SKffop5pe2vpUCo7J2SFdoYcUmY8UZ0fz75oWwwSpEVEl3uaNpfOGYLaR8BLpPdHnCOta37e9GeT4mEj+pY28/kfeSkjRLOPlAaUz3FEZqJ87gfayWvOxX4+Q6NcBt6IvubCHNeC/Hx5Yh9lhDDnv3VZi0hHf8TDWHzx4frk6ZRNGteN9CF/6Sfqmv/kkqwfiGTtdzTZx5+g/Id/+IfJ2JFufIEp/Vbmpv2OJgMQb/K2jYoDb5g0PSQpBrM8PSWkKbYhgzQfRrzZu44hH3nSc/F/PtjYl4MwIDRpfj70o70pef3pizby/Ln8hayw5e0KEUqP7zofUHfOu9lQfwbJvA9oE+lpW7gu3C+kp23mupSEj3zsz68R5ww5jXPxOu/3YGj+IH8PDLmPu6BNlLnowYP+jWtBO6lz/n4oiWbUp21L6xoyU9tycRqaP4XrFPWlTSFqMaBHGfnT18CxIWxtWxwXv3nJxrkiPS0jTYcQmlxAc/gcSPuB64Q40/fcj2mZaT3SjX7iM6729HjeJ6WoZBdxfyB2fM5EWfy/FiVFBkPaIy9tS/skInps9OGQHy/Py0dqQxIBsYw+o1/jXgixTfsh5I0y0s+tfKobKDfKYEvvMd5XEdWknFTK456Icrlecd4hbfcH27cO3Df8ZSBkMo1Acu8jjHEP5lvtSXX+RCWfF/NOm8PgiOYqEIMe3wTlchgI6J88Aiirw1iiKRtPiFktwrhqRHvWdbo2hK+0RnOZQDyQXNdnbh1qf+t8KNw7TJtv2t86XxX4RsxGh8lF6A++ES8yuiYi80GkkqiWorn8rIpoUk+imUOm2mX14aeLiJzP8+XiBz/4wdxlpKytaCJUhH2Rza4pzq0CA4CSKbJ8MPuCFMwyVb1sxEM069CWErG8IH8YaJmIh4CWuY4yHg899NBkecUs1571nHxJWWQUfG1FM2CdHLKJZG1l6AfWcW31fhBZVvhCzDpB3qdd6zWXlZDMWP+1brKZr2FdRpHjoSIlUxDGdB1yH1jPyZK6Rd83ay+aIiKrAjMxRBMQTiVBhsIT7sxY1R72EtkMFE0RERERGQVFU0RERERGQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFU0RERERGQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFU0RERERGQdFcM06cONFs27btkm3Xrl3NgQMHpjkucvTo0Wbfvn2Tffv375/kO3LkyHRv05w6derCfjb2k09ERESkD4rmGoIM7ty5c/qqaQ4fPjwRzlwiSTtz5sw0pWn27t07kc+AMtLXlKNoioiISF8UzTUEYdyzZ8/01XmQyjSqyf9JqxGRUf4VERERmQVFcw0hEplK5enTpy+LaPJ/0ohSlohjkFYRERGRWVA014yYEo9IJK9379492XJYf0lepsPTKfQgZJToKOIpIiIiMgRFc82I9ZjplkYycyJ/SUQBYSVCyqZsioiIyBA2XTSRFyJrPNGM8ORPPsswoi+Bvs2n0UvEes3aesxYr9lVjoiIiEjKposm07LIEVO3bKwJRGqMns0Gkkl/BvRniGcN+rpNNIEyFE0REREZwtJNnfNzOkgPawulHcQc+QuRLEUeY2o8/Zki8qdrMunrVEYR1TQ/dE2dUwZfGjgXedOHjEinTqV1oCIiIjIOTz/9dHPs2LHm3Llz05RuZjmmjYWLJqJR2lgD2CcihuTU1gtuFhFpXaaIXshhRIMh7e8Q9YhWsiGivEb8aA8yyTIFHgZKJZJ95GEfedjfFu0E6hJyybmRzTiG+sVve0a9REREZBwYd++///7m9ddfv0QY//M//7P567/+62b79u0TL/jmN7/Z/OEPf5juvQiyiQOcPXt2mjI7CxdNRILKpxEyJAYhIr1N1mgUkrlMkS9kibZ01X0joT+RtnSKfDOhj6hPCmLJloKIKpsiIiLjgmS++OKLl0jmO++80/zFX/xF8/d///cTn7nlllsmwnnHHXc0H3/88TTXRSjjmWeemVs2RxNNomI5pOdCEiybZEYUDsmMKeFlEU3qs0xR35DxFPqKeuYsW91FRETWCaKRSOSHH344TTnP448/fkn0Es+59dZbJ7L5/vvvT1Mvgphec801zWuvvTbXNPrCRRNhRMrSNXoB6Ww5yxjJpP4hlojUsohm1IU+WxZiej7qxOuYfs+JNbjLVH8REZF1AI+68cYbmyeffPKySGTJse65557m+uuvv0xKg3vvvXcyln/00UfTlOEsXDSJAiISCFEKDSQ9j2bFtGvaAZSRH7+ZLJNoInDUZdlAHLmO1I06stWm9slXiniLiIjI7BDNvOqqq5qXX365MwqJdxHR/MUvflHNSxSU8t54442Zo5oLNxZEsiRCSBrpeSQr1j/mW1/RLB3btpWibF0sk2giabO0YaOhjrWo5bLKsoiIyCpDhJKp8A8++GCaUuaFF16YTK8/9thjrWswX3rppYloPvHEEzOv1VzoaB9Ry1SEWLMZkpk/HLIqLItoxvrXZe9H6plHqVPiflimqLWIiMiqc+21107G1zbRDBklH9ujjz5alchXX311sk6TB4ZmnT5fqGjG+rt8I4K1ylKxLKLZVY+0z8feanAPEKVuW4MZouk6TRERkcWBaN52223VNZcBD/r84z/+Y3PllVdOxuPa9Hk8ELQ0ohnrM0Mg4md4Vv0p41lEM2RqyNYl48sivDXiCf2udkTfLGs7REREVg2ij1dffXX154pKMIXO1PhXvvKV6jHXXXfd8ohmrM9EMIOQTyJdY0DZQ7ZVXqO57KLZF0VTRERk8RDRvOmmmzojmik8ENQmkkslmshD/nuKMZ2+quszQdFcLCGaTp2LiIgsjj5rNHNYs/nAAw8UI5pLtUYzhDL/SZv4jcVVeFK6xrII3qo8DNRFiCb9KiIiIouh71PnAQ/t8rub//qv/1pcoxmi2fbAUBcLE834yZrSbyfGTxilU+qrBD/eTv2XQZaXpR7zQP1pR+2pdBERERlOrLnMf0eTh3oQSiKTr7zyymQfaV/4whean/3sZ1WJXJrf0Yy/Yx5bHnGL/QjnqkSxiB4iRCHJscXvWG7WtG8I/SpLmj/YLiIisngiQln6fUz+dvmOHTsuuMxXv/rVC9JZg2NwnlmnzWGhazRlfGIaf1XXN8YSC9dnioiILJ7a3zofCtK6lH/rXMYnIq05MSXdtgUIa5qfbzdpJDr+XjnpkYf880IZq/5zVyIiIsvMgw8+2Dz11FMzr6uERx55pDl06NBcZYCiuYLE75Pm62GRuJiSzh9gigdwIB7QSh9uYh1qKpKILGXFFD3lcc554HyUwbIEERERGY+HH364OXny5EzRSNZ6Hjx4cG7JBEVzRUHWchlEFEPictEkT4hm7OPfGrmIzgPnRoqVTBERkY0DYTx+/Pgg2eTvm7PMbZ7p8hRFc4VB4JDB0jR6LpopEdFkCrv2Q/qUiRiyljJEdlYQYOoxbzkiIiKyWiiaa0qbaAL7kUny8G8unMgogsh+hHNR0U0RERHZOiiaa0qXaAZELEM4S3kpJ4QzXcMpIiIi0oWiuab0Fc0AiWx72IdyKM81liIiItIXRXNNaRNN0vIf1Q+RBI7Nf4IoyuNfERERkT4ommsKU+KIYelPgiKVRC9DGlmPyfR5/tNI/OQR8BBP/KamiIiISF8UzTUkRDG2PKrJ/lh3yYZAIqTxVDjiGWIZeXjttLmIiIgMQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFU0RERERGQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRlqThz5kxz4MCBZvfu3dMUERERWVUUTVkajhw50uzZs6fZuXPn5F8RERFZbRRNGcyJEyeaXbt2TYTw9OnTE0Hk9bZt25qjR49Ocw3n8OHDk3+JaCqaIiIiq4+iKYNganv//v2TfxHLffv2XRBEprsXIYiKpoiIyHqgaMpMEMlENJHCgKhm+prIJ3naNvLkKJoiIiLrwZYUzfSBE2SHKWCidNIfpsvpO/oSQjxL4jgURXMYsbY15H3v3r0XrouIiMhmsiVFMyQTOYrXDNAM2NIPpsxTGWT6nD5cBIpmfxB7viiF4EcUmesjIiKy2SyFaMbgyLYZP2sT6w1jraF0k0+Th3gi7/NEh7kWROTiQaNFwP1FmWl91xneQ7Q3oB9J84uUiMjW4umnn26OHTvWnDt3bprSzSzHtLFw0UQ4kLaIsPSFp5XbIjExNZsOoEE6bZhuyBDldU0jMgAvUmwWxbJG9uJapE+Yx/UL2ZyF2nWcB6Q3jfiVoO7kWQYiup5v1I97/9SpU9OcZej77du3X/b0P+n0L8L53nvvTVNFRGQdwXvuv//+5vXXX28VxocffrjZsWNH8/77709TzoNs4kZnz56dpszOQkUzjUwOFc04thZVDJEpRaXo0Ph5nZAc0mI6t03WGLg5tmsA30hCCrrqLu2EZNauLfcIeehntmUBoaQ+aQQyZJjt3XffnaZeCu3pilxStrIpIrLeIJkvvvhiq2S++uqrzdVXXz0Zb3LRBMp45pln5pbNhY6uMWVHpfOIShcMjhw3q/DFIJwTwlYqdxklEzmmTtGPiuZsxBeX2n3I/uhn7hvyLgtx7X/7299OU84T0c7Sl7E+kgnku/766334TURkTSEaecsttzQffvjhNOVyGAu+8IUvTMYNZsFKovnOO+8011xzTfPaa6/NNY2+sNGVAY6BOwb4oevhYsp9FogAciwDdE6IZh5hXUbJpC60gRsAqLeiORv0G9e3Bvvj2sc9sizcfPPNE/nN39ghmvl7q69kBhHFfeutt6YpIiKyDjAe3Hjjjc2TTz7ZGokkWvnKK680d999d1U04d57752MkR999NE0ZTgLGV1pGAMjA10f0STKxMBIPo5DMnldkqooj620H9qm1eM8IW8Q9U3lkzKGyvHYtLVZ6iCQtfuhxDKJJvfmFVdcUbzuIYh5lJa8aVspo+2+oX/4YPHhNxGR9YJo5lVXXdW8/PLL1SgkeR566KGJiN5zzz2tovn4449PynvjjTdmjmouZHRlAIyBrUs0Y4o8HtKJQbHtmBDJ2nRfDMB51DLqkj9gFNHTfBsqJkO2WeC4NmGQMrE2N78fasT1XAZqX5p4nzDlTZQ2fbPH+ynfuu4byiLPJ598Mk0REZFVJ8Txgw8+mKZcCtPh5Pn4448nr7tE86WXXpqI5hNPPDHzWs25R9eIHsWgXpM7iH35FDeDKul5pCaIwbe2P6KWAVPpDMBELRlMGaRXEdqkaA4n1jj2ve7LJJr5lybawH3PPb7IpR533nnn5DzzrLsREZHl4tprr518ttdEE7H893//9wuf/V2iyQNDrNO84447Zp4+n3t0ZZBOZSjEsyRIMaDHk+FBDK41MYj9+XHAMezLNwbmvmvWlhXaUerHjSLv02XcSsR91peh+cckvjSlG1+YiNIu8gtTiKbrNEVE1gdE87bbbis+CMQ0OGNJGpnsEs14IGjTRDMijfkUJWm5IMUDOyVxIq3twY2I5pSIOkQElcGY8hicS2K6StT6q0ZEjIdsfZcLrBL0GW3ry9D8kPZhn63PdeTeZX0m93pMaceXrFo0f1ZCNI8fPz5NERGRVSZ+rggpjKnxgH1/8zd/c1l6l2jCddddtzmiyaDIgJgOpumWD6whQaW1Z6SXnhiHrv0xEKfRy5BP9o1BiMmQbRY4ro+gyKUMFceh+cci/9IE3P98CPBla5EomiIi6wcRzZtuuumyiGYIJZ/7ta0mk5smmrGusrRmjHQiiimRPxfNSK89ARuCWtsfkpBGL0NOFz04bzS0QdEczqqKZrwX8iUfMZ1e+6H2WXDqXERk/ait0XzhhReagwcPTsaZdOP3NhHQRx99tHn22Wcve+Bn09ZoInWIJJUsQSPZUuLp2PQYJDUG0Xz6PSB/bX8IZWlaPaKtqwz1VzSHs6oPA8V74e23356mnCd+JaH2HpkFHwYSEVk/InJZexgop+/DQIjohj51HgNzaeCLh4HY0ihjvkaTY/l/KpJs+dPqbRIQP2PDAJ1LRQzOq/pAUPQjQt9XmOQ8bV9Ocujb+FLSJ/9YcL1Zn0k9ctGML2n5e2MeYjrenzcSEVkfiFx2/Y5mSpdobsrvaIb4sfH/VIIYqGMfWy6ADJiIExvrJ9kX0dE0LSXKyYnBNz1XSuyn3Nq0+zJCn9KWtG1spI+15nTdCElv6y/2pfdybPQ96RsJ74GQzNjSv0XOfj4ISF+EbNI/lLdK7wsREekGh+IvAz322GO9IpBdoslfEGJMnHXaHJZ6bjnEVcGSofDGKC2pkIsP0Lk+U0Rk/ejzt877gLQu1d86H4OY/iYCI+tDGo1Ol1fkIET5dHYci0S2HRtfUsgvF+GDg78K5Jc3EZH15cEHH2yeeuqpmddVwiOPPNIcOnRorjJgaUUzhGKR69JkeUB0WNZQAhlinSXXPhVNxBLBZD/Tvl33RpzDLyoXIdLL8oB0al5ERNaPhx9+uDl58uRM0ch4Sn1eyYSlE814kAOh4P+yniCJtd9GDbj+qWjy/7gnkM0+aylDNhf9g+erBpKOYCqZIiJbB4SR30seIpv8fXPGzHmmy1OWeupcNhdkDlFD/PmX1/HTQQjLPKRfJOLLBVsqlm2iCX0f2uE46p0eu5UIyXQZgYiIbDSKplRhejrkDlEhCom0xF+wSSVwCJSRHs/UNlFHzoPMBosSTREREdkcFE3pBMFEBEMCY/1sCtIXUcnSlkphiCrCSVlES/l/DlKZTnmTJ12jyXEiIiKyvCia0glyl0od4jlPNDGm42MrPaxD+cgtW3ruOJYIaxr9FBERkeVD0ZRW8mluiGnuWUESWTOJKOYiKSIiIuuDoimt5NPkqXjGGs4hIJccHw+mpNPyCKdRShERkfVB0ZRWEMH8CXNeI4ez/AnDdH0mxINATM8PlVYRERFZbhRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFU0RERERGQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFc06OHj3abNu2bVM3ERERkWVES5mT/fv3NydOnJi+EhEREZFA0ZyT3bt3T/93nj179kyijDt37mzOnDkzTW0mr0lnv4iIiMhWQNGcg9OnTzd79+6dvjoPcrlr166JVB45cmSa2kyinqRxzCxQVkgsG+dNRVZERERk2VA05wD5O3z48PTVeU6dOjURQrZUQhHNWaOZHEtENKboQ1r37ds3eS0iIiKyjGx50STCGJFCHuxBFJkOj9dtIJJ5hBLxPHDgwORfyoj9pLGec1FQxzyaKiIiIrJMbHnRRP5CNhE3Xsf0d9c0d74+EygDQaUMRDMinpTfJa59oV59RFhERERkM3HqfApiWZvajvWRKUQ+SxHK9CEgpDNkNH84KKa/27aYKk+hDMpM13+KiIiILCOK5v/TFiGMdZi5+DEVnuennDTKybFRLiI7L0qmiIiIrBKK5v8TQtgGEc00qlmaNqec/AEdIpnknffBHSVTREREVo1RRZNIXtsDK137NwoksDZtHsRUN1FLpK+Un7R8Op2yOS5/On0olE0UNajVQURERASefvrp5tixY825c+emKd3Mckwbo4kmwoVg1WSoa/9GwrR2KnE1IjKJIOfiyPG0hy2dYmctJ2n8OysRcc03RVNERERyCEbdf//9zeuvv36ZML7zzjvNNddcc4lP3HTTTc2HH344zXFeNnGPs2fPTlNmZy7RrK1tRLqQLf4tyVDX/mWFTmcqnCjsPOIoIiIiMhZI5osvvliMSj744IPNXXfdNfGv2Ep5KeOZZ56ZWzbnEs38tyJzukRy1UQTiH4u4sEeERERkUVDNPKWW265JEIZEOm85557mo8//niaUicin6+99tpc0+gziyYRSaJ7iGaNdRRN6jzvgz0iIiIiiwaRvPHGG5snn3yyGIl8/PHHm+eee653lPLee++deNpHH300TRnOTKLJSWNeP93ySN86iqaIiIjIMkI086qrrmpefvnly6KQIaH42h133NH87Gc/6xROxJTy3njjjZmjmjNHNOMhF2SxxqJFsya4bZuIiIjIVoBp8e3btzcffPDBNOUir776anP33XdP9ocj8RDQv/3bv1Ul8qWXXpqI5hNPPDHzWs2ZTSzWZ+YPAqUY0RQRERHZGK699tqJm5VEMyWVTpZB1iKW5GOdJhHQWafPZxbN+H1IQrE1+AmjNpHs2r8RhNWv8iYiIiKCaN52223FB4FK8AT6jh07mm9+85vFB4TigaBNEc22p6/5GSB+czJEKP+LNl37RURERKQ/RB+vvvrqiRT2eao8uPXWWyceVpPT6667buNFkygmgrjRT1+7RlNERESkDBHN/MfXu+CBn9rPIcGmiCbrMpG4tgeBRERERGTj6LtGMwXR/M53vlOMgm7aGk0Ek4akf2pxGf5m+VhEe5d1ExEREWl76rzGF7/4xea//uu/Wh8GevTRRzf2qfN44hwBYxqdKfT8b3+vE6xdaHvoSURERGSzeeGFF6q/o8lvaPKg0L/8y79M9vGgz9/+7d82zz77bFUiN+13NJGuWC/JA0FtP3G06tBWRFNERERkmcFZEMrHHnvsMnl8+OGHmxtuuGHibqzjfOCBB5o333yzVSD5e+f43qzT5uC8awdIND/DJCIiIrLstP2t8yEgrZv6t863CiwLSNeibganT5+e1IPoMd9E+HHVdV6qICIiIrPD72M+9dRTM6+rhEceeaQ5dOjQXGWAotnBMkybI7rIZQgvEVYfAhIREZEaTJWfPHlypmgkaz0PHjw4t2SCttICkcSxn6ZHHpHGdCNy2fbTUfHzUiIiIiI1EMbjx48Pkk3+vjmeMc90eYq20gLT07W/WIQgskB2EX/RiAglEcsgnuqvlb2o84qIiIiMiaLZAtFMopopsV6SKXVkcBHrNzkP8phC2XlUk4W55FUyRUREZBVQNFso/S13xPLUqVOT/y9KNIlmplKJzJYimsitkikiIiKrgqI5JY9cIpBdP2u0CNFEWtNyeI1Q5g8hEUVN68P/FyG5IiIiImOx5UWTBa/x4/NMTQeIXNcP0ZdEk9ekt23pMbEeM93yqGXIaL4pmiIiIrLMbHnRDLnMn/Tu87NGi5C9+H1MIKqaT6OLiIiIrCpOnU8hiojkIZ4IX5+fNVqEaCKZyGbAeUtrQ0VERERWDUUzAcGLnzTq+ss7MUXetY6zjSgjjWDGVHrXtL2IiIjIsqNoJiB8EWGMJ8tzQg7zbZbp7vT4OF88cc42b7RUREREZDNRNBOYNmf63KlrERERkflRNDOITKZrJkVERERkNhRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0RURERGQUFE0RERERGQVFU0RERERGQdEUERERkVFQNEVERERkFBRNERERERkFRVNERERERkHRFBEREZFRUDRFREREZBQUTREREREZBUVTREREREZB0RQRERGRUVA0Za3Zs2dPs23btpXbPvnkk2kLREREVhdFU9YaRPPAgQPTVyIiIrKRKJqy1hAdPHHixPSViIiIbCSKpqw1iqaIiMjmoWjK2nL69OmJaPKviIiIbDyKpqwtRDIRTREREdkcHIVlbZlVNEtPqu/du7c5derUNMd5eL1v377Jw0Zsu3btavbv3z/d2zRnzpy5ZP/u3bsnZYuIiGwVFE1ZWw4fPjyRu6EgiMglxwNT75SDSKbs3LmzOXr06PTV+fOloomcpq8R01nqIyIisqoomrK2EEWcJYKIECKa6UNElEVaENHStgeN2M9xIiIiWxVFU9YWoolEFYdCZDKVSmAKPI1oxoNGbeWTn40IqYiIyFZE0ZS1ZdYfa0ceIxKKJIZ4ptPkcOTIkUk6eUtPthMZZXod2WyLfIqIiKwriqasLbOKJnKIQMZWE0lAIMnPVsoT6ztLoioiIrLuKJqytuQP6/QhpsSJVgLT75TTNv0d6zVrUsuxlBFRUhERka2CoilrC/I3dMo6psMjOhkPBoV41mB6vC16yhpPRVNERLYaiuYaQNSuS4TGBjFDtJblwRfqgSAiikNABjkuJaKR0TakMY+UplPnXIv0Z42AdZ+bfY1ERGRr8fTTTzfHjh1rzp07N03pZpZj2hgsmjEQlzYGWwbUZX3wgXohAFHfvuv3iFal7Uzbh3wgHrSdfazH4+GRSA/a+i3fhkB7QmA4J+eONYHUKeSoDY5Pz59H3pCqtEzaRR9wXN4XXP8+5xwb6kV9h8D9EH2QPk1Oe9N+iYeFaD99wzVI+4Fy4j4gndf8X0REZCNgHL7//vub119/vSqM77zzTvPwww83t9xyS7N9+/bm0Ucfbc6ePTvZh2wyxsXreZgpokkDQr7SAZbBNIQr5GejyKWnjZC+PiJGueRly6NUHEsZSEU61YqIkD8Xtlj/x1aqK2mU1xf6O68TUE6cp49Mx7Xk3NGOIOQrRIk20ydxnfN20H76o6tfxyb6QEREZKuBZL744otVyUQkr7rqquaOO+6Y5Hvrrbcuy0sZzzzzzNyyOfNIHLKWiwZCEtKykQz5CRnqHnLVFWkiX0mqIaKjJakiCpaLJtT6LeiqTxBrB3MxBMpO5bENpDHy5vWlXaSXZJbzU3apHbQ9jQhuBvQjwisiIrKVQCKJUn744YfTlEt58MEHmx07djRPPPFEq0QS8bzmmmua1157ba5p9IWLZlfUbgxiarPv+ah7CDGSVYPyyFtra6SXRJN+YH9OrayhUE5N5qLeEVltiy6TL6KWeX0ph/SSaEJMoefEcfO2cR5oU94eERGRdQYfufHGG5snn3yyKJERyeySzODee++djKUfffTRNGU4o4pm7UEMJCCiaPzL65KskYbMxDQtEapcmqIe6dYlOBxDnji2JmJ5vrzckNXaVHFJ0GplAf3Qh4hm1vJHnfmXfDWZzvPx/5zo+1IfsT6x1A7gGK7dZkHfb3ZUVUREZCMJkXz55Zcvi0ISoURCmS7/+OOPp6ntPP7445Py3njjjZmjmgsXTeSnTW44Ll3TmMpaCuKG5CAr/D+kk7y5wMU5a9KTE3IVglWaYo21hlBrK3UiD/uoa59p71pZvO4rRl3tJZ3zQJwvf0oaOF/IInnimBQEk32xvzRVX4J+oU/aiHL7bLW21qCufcVdRERkHbjnnnsmD/Z88MEH05SL8OAPU+Z/93d/19x3333N9ddfPxlfv/KVrzT/8z//M811KS+99NKgCGiJhYkmYhYiiGCUopkhLbmsxHGpGJBWktWIhKbiMatoQqk84PwRxcvbmpIKMBvl1SKkEGWVNvb1oa0+QHqUFX2el801iP4lf9v5kdHoJzba2yWcXXUcG86vaIqIyFbi2muvnYy9JdG89dZbLzxd/uabb04ilBEBve2225r//u//nua8yKuvvjpZp0kUdNbp87lFM98Y3JGvErUoV0wFh/hwPK9LEb6IgCI7wTyiWRKxVMKgjzSxL+0T2lqS7VpZvO4b0Ywyav0cdQlCEtNzpiJNOvvTY3I4F/3M9SMvW5vIhXzn7dwoqGcexY16r8L2ySefTGstIiLSD0QTaSw9CHTddddNxpf3339/mnKetoeD4oGgTRXNEImYQm6bPmY/+Uqwjw1CfEprHEtSNI9oQohYiCHnTduRt7WNNPqH7OQy2FZWm7ilcDxbDcpO+ydkOkSWOqXCT372p8fU4Ng0glurc59rEmX02fr0fcosx4iIiKwqRB+vvvrq6hpMRLMkoTE9zhR67bilEE2igBHtqk0dhzSUSPe1iU9p37yiGccjUIgUopgKYt7WoCbVHFsT71pZQ4gyatPXlJ32T4hlHEN7U0EkP/vSY4JaG0NeU2FNGXpNFg3nLkWURURE1hUimjfddFM1olna1zU9vjSiCSEstUE+jxymkB6igwzxuiQxcY5UlIZKDedJ86YihmymZUOprUC+mswQ2czrCbWyUvJjcrrKID36Mog+IqqZizT52ZcfA23T+SHTJfq0cyyiPSIiIluJtjWaX/ziFydrNPMnyEM0078MFCzFGs1cJEJoELdcwmIfMpcSYplGQqP8PDoakbQ0mhfl9pUays7zMl1OGXnZ0NbWmohFPfP6dwkYfZb3T05Xe0nnPCmIJcew5eWTn/T8GCC9JtMIK1uJaOdmEO0RERHZSrQ9df7CCy9MpshzoYz00k8YtUloX2YajRGxiE6WpAj5Yh+yiWil0bN8SpmySCvJJ8ezhVDxb5SZEuLFv+zL96dE3cmbQnqpPWlbaz+rhFSlD55wfuqZl4WwkZ8tf1AFaB/naqs/RF3zNgSkUw75UqgPx+Xp0Q7qnO+LdPLEPv7lGpNek1COK90bGwH9V1sLLCIisq6ENJZ+RxPiwZ9f/OIXk/2I5J//+Z83//zP/1wUyU35Hc2IVOVbyCAgliGU+X72IWxICukl6QtCaKIMyiwJWnq+0gNEQanuab0Ro1S0utoaskyd0nqW2lQrq7SlYl6D8thSqFdeVpqHtqXyV8qfH0MbOS7kNfLQ3ppkhlCnfbuRUNe8b0RERNYd/IEfZX/ssceqEUh+T/OGG26YjNM8HNT2N9H5e+eMp7NOm4PziytKyFwqxssCso+IbhaIZtf5eTOSr+2LydhQB+pZ+vIkIiIyC11/67wvjFFMm2/a3zqXzYcp4s0UuhKIL9HlPlHZseDbVx5RTqFu1LFricK80BcRAW47F1HmzRReERFZL5gif+qpp2ZeVwmPPPJIc+jQobnKAEVzxUFgxhamviBwSFNtSn2j6BJNpK5t/yIhWolodvXJzTffvGlLDUREZP1givzkyZMzRSNZ63nw4MG5JRMUzTUAQdls2SR6x3rOzYxkBqwlrU1HU7+NXHLAdWE9chfkc12piIgsEoTx+PHjg2STH3BnDJ1nujxF0ZS1A5GsRQcROqbNU5BPopwcx7+8ZkkCr/O8QyHCGwKZPnyVR1QR3yuuuKJ57733pikiIiKrj6IpKwfChrzVZBKRq01VI5L5ulYisZSF/CGW8esDMe1dO08f0l8gQGB5HeXnIJrznEtERGTZUDRlZQjBjJ9ZKk01k4d9NTimtj4TAWSaO6b/iX7mZXE8abUtrVNM0yOsbEhum0gqmiIism4omrIyEKUMEQvZzNdiziOalIkMBum09yxERDS2+N3VGoqmiIisG4qmrCQhcchhClHIPC2lNHUOTGVTXip68ReRZoVzxYNACGvXek9FU0RE1g1FU1aWmMZGLgPEsC0KWXoYCPJp8lQ8Yw3nUGK9J0T5lMP/8/J8GEhERNYRRVNWFmQNeUvXVXaJZqybzB/GQQhzAeU1ZXdNeZeI84QE87qtPPLNM00vIiKyjCiastIgiAhdTHEja13T3Uxpp2sxlwF/sF1ERNYRRVNWmpjiJlLI//uIZkQXI9q42SDLyya+IiIii0DRlJUHsUQ2Y/q7j0Aimxy3mYJHHXgwKX9yXkREZF1QNGXlQdiIaCKbbE5Bi4iILAeKpqwFPGCjaIqIiCwXiqasDfEj7iIiIrIcOCrL2hA/4i4iIiLLgaOyiIiIiIyCoikiIiIio6BoioiIiMgoKJoiIiIiMgqKpoiIiIiMgqIpIiIiIqOgaIqIiIjIKCiaIiIiIjIKiqaIiIiIjIKiKSIiIiKjoGiKiIiIyCgomiIiIiIyCoqmiIiIiIyCoikiIiIio6BoioiIiMgoKJoiIiIiMgJN838N/RZz3bdSGAAAAABJRU5ErkJggg==\" height=\"323\" width=\"666\"\u003e\u003c/p\u003e\n\u003cp\u003eWhere the intercept (\u0026alpha;) of 13.664 is positive, indicating the base impact of USPs on railway infrastructure, independent of GDP. The coefficient (\u0026beta;) of 0.222 suggests that a 1% increase in GDP per capita corresponds to a 0.222% increase in the benefit from USPs on average. This positive association implies that as the economy grows, the advantages of adopting USPs become more substantial. Yi\u003csub\u003e\u0026nbsp;\u003c/sub\u003e= USPRT (dependent variable) and X\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e= GDP per capita at current market price (independent, or explanatory variable), \u0026alpha; = the intercept 13.664 (positive) this is a constant term and, \u0026beta; = the slope coefficient (the GDPpc coefficient is 0.222. It is a Ln- linear model), \u0026micro;\u003csub\u003ei\u003c/sub\u003e= error term, \u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc184291527\"\u003e4.2 Statistical Significance and Interpretation\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Correlations\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e*. Correlation is significant at the 0.05 level (1-tailed).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e*. Correlation is significant at the 0.05 level (2-tailed).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eLnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eKendall\u0026apos;s tau_b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eSig. (1-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003eLnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eSig. (1-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSpearman\u0026apos;s rho\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eSig. (1-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003eLnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eSig. (1-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eSource: calculation by Author and Output by SPSS2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCollinearity Diagnostics\u003csup\u003e(a)\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 22px;\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 17px;\"\u003e\n \u003cp\u003eEigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 15px;\"\u003e\n \u003cp\u003eCondition Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 31px;\"\u003e\n \u003cp\u003eVariance Proportions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eLnGDPpc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e21.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003ea. Dependent Variable: LnUSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eSource: calculation by Author and Output by SPSS2016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThis result suggests that higher GDP per capita correlates with increased usage of USPs, potentially due to a greater ability to fund infrastructure improvements. However, the model\u0026apos;s (R\u003csup\u003e2\u003c/sup\u003e) value of 0.051 indicates (meaning that 5.1% of the variance) that GDP per capita explains only a small portion of the variance in USP adoption, implying that additional factors influence USP investment decisions. The coefficient of correlation (r) = \u0026plusmn; 0.225, it can clearly see that there is a positive relationship between GDP per capita and USPRT. However, the positive coefficient indicates a trend where economic growth supports increased adoption of railway advancements such as USPs.\u003c/p\u003e\n\u003cp\u003eResult: p (T\u0026lt;=t) 0.0000 which is lower than the standard expected P value of 0.05. \u0026nbsp;So, this analysis is statistically significant. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs a consequence, the author can see that findings are matching alternative hypothesis (H1). From these results the author sees that GDP coefficient is positive + 0.222. So it is implying that for 1 percent increase in the GDPpc, the benefit of under-sleeper pads railway track (USPRT) on the average increases by about 0.222%. Therefore, it can say that there is positive association between GDP per capita and under-sleeper pads railway track (USPRT).\u003c/p\u003e\n\u003cp\u003eTo find out if the parameters are statistically significant, the author has used t-test, z-test, F-Test and p value. Here the calculated t-values for both the variables are much higher that the critical t-values thus, it can say the parameters are statistically significant. P-values are also very low thus the author can say that variables are statistically significant. The values of Standard error are also very low which stats statistically significant variables. Observing the upper and lower values of confidence interval, so it can say zero is not included in this range. Thus, \u0026beta; cannot be zero (\u0026beta;\u0026ne;0), this supports alternative hypothesis (H1).\u003c/p\u003e\n\u003ch2 id=\"_Toc184291528\"\u003e4.3 Positive Impact on Economic Growth and Life Cycle Benefits\u003c/h2\u003e\n\u003cp\u003eThis research shows that the use of USP in railway track will have huge economic benefits which will have a positive impact on the economic growth of the country. Therefore it has assumed a base case of 7.25 GDP growths; consequently benefits in the 2028-2036 periods will be 0.0020% within 8 years used of USPs. And GDP will grow by 0.0012%on average from 2036-2046. And GDP will grow by 0.0018% on average from 2046-2056 i.e. GDP would be 7.246% with the project over the 30 years of the project. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom this research, USPs offer various economic benefits, primarily through reduced track maintenance costs, extended track life, and decreased ballast replenishment requirements etc. The economic analysis suggests an Economic Internal Rate of Return (EIRR) of 18.3%, well above the threshold rate of 9%. The Benefit-Cost (B/C) ratio of 1.63 further affirms the economic viability of USP application, particularly for high-traffic railway corridors. The lifecycle savings from reduced ballast maintenance and track upkeep are significant, translating into long-run cost reductions for Bangladesh Railway. Sensitivity analysis confirms that even under scenarios of increased costs or reduced benefits, the project remains economically robust. The most substantial savings arise from decreased track maintenance machinery costs (43% of total savings), followed by ballast cleaning and recoupment.\u003c/p\u003e\n\u003ch2 id=\"_Toc184291529\"\u003e4.4 Findings \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe study has carrying out of Under Sleeper Pads (USPs) for railway tracks within the Dhaka-Chattogram-Cox\u0026rsquo;s Bazar Rail Project Preparatory Facility(DCCRPPF) reveals several positive impacts on infrastructure resilience, economic benefits, and operational efficiency.\u003c/p\u003e\n\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eImproved Track Stability and Reduced Maintenance: USPs significantly enhance the elasticity of the railway track superstructure, reducing ballast wear and tear, vibrations, and ground-borne noise. This improvement minimizes the need for frequent track maintenance and extends the service life of the track components, finally dropping lifecycle maintenance costs\u003c/li\u003e\n \u003cli\u003eCost-Benefit and Economic Impact: Economic analysis has done by using a 9% discount rate, shows that incorporating USPs results in a Net Present Value (NPV) of USD 17.05 million and an Economic Internal Rate of Return (EIRR) of 18.3%, well above the threshold rate. The Benefit-Cost (B/C) ratio is calculated at 1.63, indicating that the project yields substantial economic benefits over its cost. These benefits primarily come from reductions in track maintenance costs, machine savings, and ballast cleaning requirements\u003c/li\u003e\n \u003cli\u003ePositive Correlation with GDP: The study indicates a positive relationship between the implementation of USPs and GDP per capita, as rail infrastructure efficiency directly influences economic activities. Empirical findings suggest that a 1% increase in GDPpc could correlate with a 0.222% enhancement in the economic benefits provided by USPs, underscoring the potential macroeconomic value of modernized rail infrastructure\u003c/li\u003e\n \u003cli\u003eEnvironmental and Resource Efficiency: The use of USPs reduces the demand for ballast, which is becoming environmentally and economically costly due to limited natural sources and regulatory constraints. By decreasing ballast requirements, USPs offer an environmentally friendly alternative that also aligns with sustainable resource management goals.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThese findings uphold for USPs adoption in Bangladesh\u0026apos;s rail infrastructure, emphasizing cost-effectiveness, improved efficiency, and a potential long-term economic contribution, aligning with national goals for sustainable transport development.\u003c/p\u003e"},{"header":"5. Conclusions and Recommendations","content":"\u003cp\u003eThe research explored that the economic implications of Under Sleeper Pads (USPs) on Bangladesh\u0026rsquo;s railway infrastructure, focusing on the Dhaka-Chattogram-Cox\u0026rsquo;s Bazar rail corridor. The main objectives were to analyze USPs\u0026apos; cost-efficiency, their impact on track resilience, and their broader economic effects, particularly on GDP. The study applied a 28-year time-series regression model to explore the correlation between USP implementation and GDP per capita. Key findings suggest that incorporating USPs significantly reduces track maintenance costs, extends track life, and requires less ballast, leading to substantial lifecycle cost savings. The economic analysis demonstrated a robust economic internal rate of return (EIRR) of 18.3% and a benefit-cost (B/C) ratio of 1.63, which emphasizing the project\u0026rsquo;s economic viability. Furthermore, USPs appear to align well with national economic growth objectives by supporting increased freight and passenger capacities. The implications of this study highlight the value of investing in advanced rail technologies to enhance Bangladesh\u0026apos;s infrastructure resilience, supporting sustainable growth. However, limitations such as the model\u0026apos;s low explanatory power suggest further research into other factors influencing economic impacts. Future studies could broaden the scope to assess external variables affecting railway performance, providing a more comprehensive view of USP adoption\u0026rsquo;s economic potential.\u003c/p\u003e\n\u003cp\u003eThere are some \u003cstrong\u003erecommendations\u003c/strong\u003e are followings-\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eImplementation of USP should be adopted for larger and important rail networks.\u003c/strong\u003e Given the cost-effectiveness and life-cycle savings shown in this study, it is recommended to incorporate USPs across other major rail corridors in Bangladesh to optimize maintenance costs and bolster track durability\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eRegular economic evaluation and updating\u003c/strong\u003e. Periodic evaluations should be conducted to ensure that economic and operational assumptions are consistent with real-time data, which will help refine investment strategies and maximize long-term benefits\u003c/li\u003e\n \u003cli\u003eAlthough the study establishes the economic viability of USPs, \u003cstrong\u003eadditional research should be conducted on their long-term environmental and operational impacts\u003c/strong\u003e under different track conditions.\u003c/li\u003e\n \u003cli\u003eRailway maintenance teams and engineers should be trained in the installation and maintenance of USPs to ensure efficient deployment, capacity building and maintenance, which will sustain project outcomes\u003c/li\u003e\n \u003cli\u003ePartnerships with \u003cstrong\u003einternational financial institutions\u003c/strong\u003e (i.e. ADB, WB, IMF, JICA, EU etc.) should be encouraged to secure funding for USP implementation in Bangladesh.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe above measures are expected to maximize the value of investment in USPs, thereby accelerating economic growth and increasing the efficiency, modernization and reliability of Bangladesh\u0026apos;s rail infrastructure.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eUSPs Under Sleeper Pads\u003c/p\u003e\n\u003cp\u003eGDP Gross Domestic Product\u003c/p\u003e\n\u003cp\u003eEIRR or IRR Economic Internal Rate of Return\u003c/p\u003e\n\u003cp\u003eBCR Benefit-C:ost Ratio\u003c/p\u003e\n\u003cp\u003eUSD The United States dollar\u003c/p\u003e\n\u003cp\u003eNPV Net Present Value\u003c/p\u003e\n\u003cp\u003eOLS Ordinary Least Squares\u003c/p\u003e\n\u003cp\u003eDCCRPPF Dhaka-Chattogram-Cox\u0026rsquo;s Bazar Rail Project Preparatory Facility\u003c/p\u003e\n\u003cp\u003eADB The Asian Development Bank\u003c/p\u003e\n\u003cp\u003eIMF The International Monetary Fund\u003c/p\u003e\n\u003cp\u003eBDT The Bangladeshi taka is the currency of Bangladesh\u003c/p\u003e\n\u003cp\u003eM Million\u003c/p\u003e\n\u003cp\u003eSCF The standard conversion factor\u003c/p\u003e\n\u003cp\u003eLCC life cycle cost\u003c/p\u003e\n\u003cp\u003eUSPRT under-sleeper pads railway track\u003c/p\u003e\n\u003cp\u003eEU The European Union\u003c/p\u003e\n\u003cp\u003eWB The World Bank\u003c/p\u003e\n\u003cp\u003eJICA The Japan International Cooperation Agency\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe author declares that this manuscript is original, has not been published elsewhere, and is not under consideration by any other publication. The author has confirmed that there is no conflict of interest, financial or otherwise, related to this study. All sources of data and funding have been duly acknowledged, and the work complies with ethical standards in research and publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eADB and BR. (2017). Bangladesh Railway Master Plan. Dhaka: Bangladesh railway.\u003c/li\u003e\n\u003cli\u003eBR and Gr\u0026uuml;tter Consulting. (2016). NAMA Rail Bangladesh. Transport, inter-urban . Bangladesh: Bangladesh Railway.\u003c/li\u003e\n\u003cli\u003ehttps://railway-news.com/suppliers/pandrol-rail-fastening-systems/. (2023). Retrieved from https://railway-news.com/products-services/railway-sleepers/.\u003c/li\u003e\n\u003cli\u003eADB. (2017). Guidelines for the Economic Analysis of Projects. Manila.: ADB.\u003c/li\u003e\n\u003cli\u003eADB. (April2022). Asian Development Outlook 2022. Manila, Philippines.\u003c/li\u003e\n\u003cli\u003eBangladesh Bank(BB). (April 2024). Monthly Economic Trends April 2024. Statistics Department. Dhaka: Bangladesh Bank.\u003c/li\u003e\n\u003cli\u003eBER. (2022). Bangladesh Economic Review. Dhaka, Bangladesh: http://mof.gov.bd/en/ Finance Division Finance Ministry of Bangladesh.\u003c/li\u003e\n\u003cli\u003eBR. (2018). Information Book of BR. Dhaka: BR.\u003c/li\u003e\n\u003cli\u003eBRTA. (2008). RTA Annual Report 2008. Dhaka: Bangladesh Road Transport Authority (BRTA).\u003c/li\u003e\n\u003cli\u003eCANARAL, SMEC, SYSTRA and ACE. (2018). Dhaka-Chittagong-Cox\u0026rsquo;s Bazar Rail Project Preparatory Facility ( DCCRPPF). Dhaka: Bangladesh Railway/ADB.\u003c/li\u003e\n\u003cli\u003eChamindi Jayasuriya, B. I. (2020, February 11). The Use of Under Sleeper Pads to Improve the Performance of Rail Tracks. Indian Geotechnical Journal.\u003c/li\u003e\n\u003cli\u003eCPA,HPC Hamburg Port Consulting and ADB. (2015). Strategic Master Plan for Chittagong Port Final Report. Chittagong.\u003c/li\u003e\n\u003cli\u003eDr. Harald Loy. (2012, April). https://www.railwaygazette.com/. (Railway Gazette International) Retrieved Nov 20, 2019, from Railway Gazette International: https://www.railwaygazette.com/\u003c/li\u003e\n\u003cli\u003eEveritt, S. L. (2004). A Handbook of Statistical Analyses using SPSS. Boca Raton London New York Washington, D.C.: A CRC Press Company.\u003c/li\u003e\n\u003cli\u003eGleave, S. D. (September 2015). Study on the Cost and Contribution of the Rail Sector. Brussels: European Commission Directorate General for Mobility and Transport.\u003c/li\u003e\n\u003cli\u003eGodart, P. (2015, 9 17). Experience and types of application using Under Sleeper Pads (USP) and Under Ballast Mats (UBM).\u003c/li\u003e\n\u003cli\u003eIMF. (APR2024). WEO_Data bangladesh. Retrieved Apr 24, 2024, from International Monetary Fund, World Economic Outlook Database: https://www.imf.org/en/Publications/WEO/weo-database\u003c/li\u003e\n\u003cli\u003eLitman, T. (22 February 2012). Climate Change Emission Valuation for Transportation Economic Analysis. Victoria Transport Policy Institute. Victoria, Canada: Victoria Transport Policy Institute Research assistance by Eric Doherty.\u003c/li\u003e\n\u003cli\u003eLouis Le Pen, G. W. (2017). Behaviour of under sleeper pads at switches and crossings -Field measurements. DOI: 10.1177/0954409717707400.\u003c/li\u003e\n\u003cli\u003eLoy, D. H. (April 2012). Mitigating vibration using under-sleeper pads. Railway Gazette International.\u003c/li\u003e\n\u003cli\u003eLoy, H. (2009). Under Sleeper Pads in Turnouts. Retrieved from www.railwaygazette.com.\u003c/li\u003e\n\u003cli\u003eP J Gr\u0026auml;be, B. F. (2016, June). The effects of under sleeper pads on sleeper\u0026ndash;ballast interaction. Journal of the South African Institution of Civil Engineering, Vol 58 No 2, 35\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eRDSO. (2019). Report on Field Trial of PSC Sleepers with USP of M/A Getzner, Australia (2019). India.\u003c/li\u003e\n\u003cli\u003eRHD. (2004-05). Road User Cost Annual Report For 2004 - 2005. Economics Circle. Dhaka: Government of the People\u0026rsquo;s Republic of Bangladesh Ministry of Communications Roads and Highways Department.\u003c/li\u003e\n\u003cli\u003eRHD. (November 2017). RUC Report 2016-17. RHD.\u003c/li\u003e\n\u003cli\u003eRoad Transport and Bridges Road Transport and Highways Division. (January 2016). Regional Road Connectivity Bangladesh Perspective. Dhaka: Government of The People\u0026rsquo;s Republic of Bangladesh Ministry of Road Transport and Bridges Road Transport and Highways Division.\u003c/li\u003e\n\u003cli\u003eStefan Marschnig, A. P. (2014). Under Sleeper Pads @ for tracks of Indian Railways.\u003c/li\u003e\n\u003cli\u003eTrackelast. (n.d.). www.trackelast.com. Retrieved 2022, from under sleeper balast protection.\u003c/li\u003e\n\u003cli\u003eVeit, P. (2012). Economic Evaluation of Under Sleeper Pads. Retrieved 2022, from www.ebw.tugraz.at\u003c/li\u003e\n\u003cli\u003eV\u0026iacute;t Hrom\u0026aacute;dka, E. V. (2015). Risk Analysis and its Importance in Economic Valuation of Large Infrastructure Projects. European Journal of Research on Education by IASSR, ISSN: 2410-5465, Book of Proceedings ISBN: 978-969-7544-00-4, European Journal of Research on Education by IASSR.\u003c/li\u003e\n\u003cli\u003eWB, BR, CPA and CES. (2007). Feasibility Study for Construction of New ICD. Dhaka.\u003c/li\u003e\n\u003cli\u003eWorld bank. (6/28/2022). world bank. Retrieved October 10, 2022, from http://www.worldbank.org/: https://data.worldbank.org/country/bangladesh\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003cp\u003e1. http://www.trackelast.com/undersleeper-pads.html\u003c/p\u003e\n\u003cp\u003e2. Data collected from engineering team, DCCRPPF (note, total quantity of ballast required for main line: 1,205,718 main line (at 2.118 cum/m). requirement of ballast for various components (with 300 mm for main line and 250 mm for other than mainline)\u003c/p\u003e\n\u003cp\u003e3. Total 576.7 track km for 1-7 components under DCCRPPF project\u003c/p\u003e\n\u003cp\u003e4. Guidelines for the Economic Analysis of Projects, ADB 2017\u003c/p\u003e\n\u003cp\u003e5. Bangladesh Bank(BB) December 2022\u003c/p\u003e\n\u003cp\u003e7. Picture source: from online (https://www.delkorrail.com/track-products/under-sleeper-pads) and experience and types ofapplication using under sleeper pads (USP) and under ballast mats (UBM)/ https://www.oevg.at/fileadmin/user_upload/Editor/Dokumente/Veranstaltungen/2015/Fahrweg/docs/godart.pdf\u003c/p\u003e\n\u003cp\u003e8. Ordinary Least Squares\u003c/p\u003e\n\u003cp\u003e9. RSS = Residuals sum of squares and TSS = Total sum of squares, formula source: Jim Frost, Regression Analysis by Example\u0026quot; by Samprit Chatterjee and Ali S. Hadi/ The Elements of Statistical Learning\u0026quot; by Trevor Hastie, Robert Tibshirani, and Jerome Friedman\u003c/p\u003e\n\u003cp\u003e10. where k is the total number of repressors in the linear mode\u003c/p\u003e\n\u003cp\u003e11. This formula has used for significance tested by the t ratio\u003c/p\u003e"},{"header":"Table","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"BCL Associates Limited ","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":"Under Sleeper Pads (USPs), GDP per capita, Railway Infrastructure, Economic Impact, Lifecycle Cost Analysis and Track Resilience","lastPublishedDoi":"10.21203/rs.3.rs-6034060/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6034060/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study addresses the economic significance of implementing Under Sleeper Pads (USPs) in Bangladesh's railway infrastructure, focusing on the Dhaka-Chattogram-Cox’s Bazar corridor. With rising demands on rail systems and the need for sustainable, cost-effective infrastructure solutions, USPs present a promising technology. The objective is to assess the lifecycle benefits of USPs, including cost savings, enhanced track stability, reduce ballast degradation and their impact on economic growth, particularly in relation to GDP per capita.\u003c/p\u003e\n\u003cp\u003eThe study has done by an Ordinary Least Squares (OLS) linear regression model on 28 years of time-series data from the IMF and project sources to examine the relationship between GDP per capita and USP installation. Data includes cost components such as ballast and maintenance expenses, gathered from project records and market sources. Key findings indicate that USP implementation yields significant lifecycle savings, with a Net Present Value (NPV) of USD 18.6 million, an Economic Internal Rate of Return (EIRR) of 18.3% and a Benefit-Cost Ratio (BCR) of 1.63. The positive correlation with GDP per capita suggests that USPs not only enhance railway efficiency but also support broader economic development. Future recommendations include expanding USP applications across other high-traffic rail corridors and conducting ongoing economic evaluations to maximize cost-effectiveness. Limitations include the model’s low explanatory power, indicating potential influences from other factors; further studies could explore external variables impacting railway performance.\u003c/p\u003e","manuscriptTitle":"Economic Analysis of Under Sleeper Pads (USPs) for Enhanced Railway Infrastructure and Economic Growth in Bangladesh: A Case Study of the Dhaka-Chattogram-Cox’s Bazar Corridor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-10 12:19:23","doi":"10.21203/rs.3.rs-6034060/v1","editorialEvents":[{"type":"communityComments","content":1}],"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":"bbdef961-6cdd-4e55-96cd-d7888660d0fd","owner":[],"postedDate":"March 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T12:19:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-10 12:19:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6034060","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6034060","identity":"rs-6034060","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}