The formulation of construction material unit price policies in areas with limited accessibility is a critical issue in ensuring effective and accountable government infrastructure planning. In such regions, construction costs are often highly volatile and difficult to predict, primarily due to transportation constraints, logistical inefficiencies, and geographical challenges. These conditions frequently result in budget overruns and inconsistencies between planned and actual project expenditures. Therefore, a rational and context-sensitive policy framework is required to support accurate cost estimation and sustainable infrastructure development. This study aims to develop a policy-oriented model for determining construction material unit prices in areas with limited accessibility based on influencing factors. A quantitative research approach was employed through a questionnaire survey involving 235 respondents, consisting of contractors, government representatives, consultants, and academics with experience in infrastructure development in remote or access-constrained regions. The collected data were analysed using Partial Least Squares–Structural Equation Modelling (PLS-SEM) to identify and validate the dominant factors affecting construction material unit prices. The results of the PLS-SEM analysis identified 33 influential factors that significantly contribute to the unpredictability of construction material unit prices in limited-accessibility areas. These factors encompass logistical costs, material price dynamics, government policies, geographical conditions, and local cultural aspects. The proposed model demonstrates that government policy plays a central role, both directly and indirectly through local cultural mediation, in influencing project performance and cost reliability. The findings of this study provide a structured and empirically grounded framework that can be utilized by local governments as a policy reference in establishing construction material unit prices for remote and access-constrained areas. By incorporating the identified influencing factors into unit price formulation, cost prediction accuracy can be improved, thereby supporting more effective budget allocation and ensuring that infrastructure quality is maintained without compromise due to unanticipated cost escalation. These improvements contribute to more sustainable infrastructure development by enhancing resource efficiency, minimizing cost overruns, and supporting equitable infrastructure provision in remote areas.
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Yamani Yasmin
Dyah Erny Herwindiati
Endah Murtiana Sari
Sustainability
University of Indonesia
Tarumanagara University
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Yasmin et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d8958f6c1944d70ce069c2 — DOI: https://doi.org/10.3390/su18083689
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