Statistical Analysis of Factors Influencing Green Cost Performance in Indonesian Toll Road Projects Based on the Greenroads Framework
DOI:
https://doi.org/10.59261/jequi.v8i4.404Keywords:
Green Toll Road, Value Engineering, Greenroads, Cost Performance, Sustainable InfrastructureAbstract
Background: Road transport contributes approximately 69% of global inland transport greenhouse gas (GHG) emissions, making compliance with green infrastructure standards increasingly critical. However, no evidence-based model of green cost performance has yet been developed for Indonesian toll road projects.
Objective: This study examined the statistical factors influencing green cost performance in Indonesian toll road projects implementing the Greenroads sustainability framework.
Method: A quantitative survey of 80 toll road industry professionals investigated the effects of three independent variables Key Success Factors (X1), Greenroads implementation (X2), and Value Engineering application (X3) on Green Cost Performance (Y). Data were analyzed using IBM SPSS Statistics Version 21 through reliability (Cronbach’s alpha), validity (Pearson correlation), normality (Kolmogorov–Smirnov), and multiple linear regression analyses. All 93 sub-indicators were found to be valid and reliable.
Results: The Durbin–Watson statistic (DW = 2.153) indicated no autocorrelation, while tolerance values > 0.10 and variance inflation factor (VIF) values < 10.0 confirmed the absence of multicollinearity. The regression equation, Y = 3.591 + 0.135X1 + 0.125X2 + 0.160X3, identified Value Engineering (X3) as the strongest predictor (t = 7.490), followed by Greenroads implementation (X2; t = 6.898) and Key Success Factors (X1; t = 5.394). The overall model was statistically significant (F = 47.329, p < .05), with R² = 0.734, indicating that the three independent variables jointly explained 73.4% of the variance in green cost performance.
Conclusion: The findings provide a measurable and replicable decision-making framework for cost-sustainable infrastructure development, with direct implications for policies promoting mandatory green financing.
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