This study proposes a quantitative and systematic evaluation framework for rationally determining investment priorities in maintenance projects for heterogeneous road infrastructures such as bridges and tunnels. In Korea, conventional maintenance decision-making relies significantly on empirical judgments and policy-driven preferences, thus resulting in inefficiencies, inconsistencies, difficulties across facility types, as well as limited transparency in budget allocation. Hence, a multicriteria decision-making model integrating three key indicators–defect (performance), economic value (asset-based benefit), and risk (safety)–is developed. In particular, the economic evaluation introduces the concept of asset-value recovery and employs artificial intelligence-based machine-learning models (i.e., random forest, light gradient boosting machine, and extreme gradient boosting) to estimate reasonable replacement costs and quantify benefits in monetary terms. The proposed model enables the correlation between these quantitative indicators with maintenance project types to prioritize investments by combining benefit scores and risk indices. The case study demonstrates that the proposed framework enhances the objectivity and efficiency of budget allocation and enables data-driven investment prioritization instead of policydependent decisions. Moreover, this approach provides a foundation for transitioning from experience-based decisions to data-driven infrastructure management. This methodology can be further expanded to include probabilistic risk assessment and life-cycle cost-based management frameworks, thus ultimately contributing to sustainable evidence-based decision support systems for national infrastructure asset management.

As workplace incidents has been being declining in Korea, there is criticism of the effectiveness of occupational safety policy implementation. It is unknown that which policy target group needs to be targeted to yield effective injuries prevention. The purpose of this paper is to analyze and reveal the policy intervention group with a high priority in terms of industrial incident prevention and the related investment cost. A Policy Priority Model(PPM) is composed of 6 indicators regarding influences of both the incident reduction and the cost reduction. Z-score analyses are used to confirm the high policy priority area or policy target group. Overall, workplace with worker below 50 persons, construction site with the sales of more than a hundred million won, workplace with relatively small percentage of female employees and relatively higher percentage of older worker should be prioritized to reduce workplace injuries. This paper provides an analytic way that can be used to decide the policy priority workplace in order not only to reduce work-related injuries&illnesses and the related investment cost but to further lessen the related societal costs.

Kano(1984) distinguishes five types of Quality requirement which influence customer satisfaction; Attractive, One-dimensional, Must-be, Indifferent, Reverse Quality element. Attractive requirements lead more than proportional satisfaction. Attractive Quality requirements are the key factors of order winner and the sources of customer delight. Attractive requirements do not influence customer satisfaction equally. This study presents Kano's model using AHP(Analysis Hierarchy Process) for the priorities of attractive Quality requirements.

수자원 사업의 계획을 수립함에 있어서 그 사업이 추구하는 목적과 목표를 달성하기 위해서는 다양한 가치의 수렴이 중요시 되어야 하며, 이를 통하여 목적과 가치의 관계를 설정하는 과정에서 다양한 기준과 대안들이 선정되어야 한다. 또한 선정된 대안에 대해서는 개별사업의 중요도를 바탕으로 한 투자우선순위를 결정하는 것도 중요한 사항이 될 수 있다. 특히, 댐 직하류 하천정비사업과 같이 내재된 가치가 복합적이고 판단기준이 다양한 경우 최적의 대안을 결정하는데 어려움이 있을 수 있는데, 이는 다기준의사결정 기법을 활용함으로써 해결할 수 있다. 본 연구는 과거 연구에서 수행되어 제시된 댐 직하류 하천정비사업의 투자우선순위로부터 상위 10개 대안을 선별하고, 이를 순위선호 결정에 장점이 있는 PROMETHEE 기법에 적용하여 그 결과를 비교하였다. 이를 위해 평가기준별 가중치는 AHP 기법에서 제안하는 고유벡터법에 의해 산정된 값을 적용하였고, PROMETHEE 기법에 의해 재선정된 투자우선순위 결과는 각 평가기준에 대한 대안들의 상관성 및 특성을 시각적으로 나타내는데 효과적인 GAIA 기법을 이용하여 고찰하였다. 분석결과, 총 10개의 대안 가운데 주암조절지댐, 운문댐, 용담댐 순으로 투자우선순위가 높은 것으로 나타났으며, 과거 연구에서 제시한 결과와는 다소 차이를 보였다. 본 연구에서 활용한 PROMETHEE 기법은 댐 직하류 하천정비사업을 비롯한 다양한 대안이 고려되는 의사결정 문제에서 많은 도움을 줄 것으로 기대되며, 다양한 정보로 이루어진 의사결정 과정의 내부적 구조를 GAIA 기법을 통해 확인함으로써 다소 복잡할 수 있는 의사결정 평가체계를 이해하는 데 도움을 줄 것으로 판단된다.

The Port Development has been achieved by the Government because it needs large scale of funds. However, since 1994, the Govenment has been implemeting private investments for constructing and operating the ports and so on. Although the Government had high expectation that it could expedite the expansion of the port facilities, there were many problems in view of construction, management, financial and social environment. This study figure out that most of the important reasons are the uncertainty of risk allocation between private investors and the Government, using with Analytic Hierarchy Process. It is expected that the results of this study will encourage more private investors to participate in port private investments in the future.