| Title |
A Multi-Attribute Utility Theory?Based Framework for Decision-Making on Infrastructure Maintenance Investment |
| Authors |
Changjun Lee ; Taeil Park ; Wonyoung Park ; Yongwoon Cha ; Changyoon Kim |
| DOI |
https://dx.doi.org/10.6106/KJCEM.2026.27.5.003 |
| Keywords |
Infrastructure Maintenance; Multi-Attribute Utility Theory; Budget Allocation; Maintenance Priority |
| Abstract |
Core infrastructure, including roads, railways, and water supply and sewerage systems, underpins national economic and social activities such as manufacturing, logistics, energy supply, transportation, and daily public services. However, Korea’s infrastructure has entered a phase of accelerated aging, raising concerns over structural safety, service reliability, and cost efficiency. As of 2020, 17.5% of infrastructure assets were more than 30 years old. Although national infrastructure policy has shifted from new construction toward maintenance-oriented management, limited budgets and human resources have made efficient budget allocation and transparent prioritization increasingly important. This study proposes a Multi-Attribute Utility Theory (MAUT)-based decision-making framework for prioritizing maintenance investments across heterogeneous infrastructure assets. Urgency, impact, and economics are defined as core attributes, and single-attribute utility functions are estimated using survey-based anchor points. Attribute weights are derived through the Analytic Hierarchy Process (AHP), using only responses that satisfy the consistency criterion. The standardized attribute values and AHP-based weights are then integrated into an additive multi-attribute utility function. The proposed framework quantifies the relative investment value of each facility and identifies the contribution of each attribute to the overall utility, thereby supporting transparent and consistent priority setting. Because the framework maintains a common analytical structure, it can be reapplied to other regions or facility types by recalibrating attribute values, utility functions, and weights. Future research should extend the attribute system to include safety, resilience, and equity, and link operational data to support periodically updated decision-making for infrastructure maintenance. |