PURPOSES: This study evaluates the efficiency of snow removal operation resources using data envelopment analysis (DEA). The results of this study can help decision-making strategies, especially for resource allocation for snow removal works on national highways. METHODS: First, regional road management offices (DMUs) for efficiency evaluation were set up, and a database (for years 2012-2016) for analysis was formed. Second, DEA was carried out by selecting input and output variables based on the constructed database. Lastly, based on the results of the DEA, the efficiency of each regional road management office was evaluated. In addition, the potential for future improvement was determined. RESULTS: The results showed that there was a large variation in efficiency of snow removal operation resources by regional offices. CONCLUSIONS: The results of this study imply that the evaluation of efficiency for snow removal operation resources is important when decisions related to snow-removal strategies are made by road management offices.

본 연구에서는 해양플랜트 산업의 가치사슬 및 수명주기 연구를 통해 해양 자원개발 비즈니스의 포괄적인 형상을 파악하였고 해양프로젝트 검증 목적의 시뮬레이션을 위해 조립 및 인간공학 시뮬레이션에 대한 연구를 수행하였다. 구체적으로는 조립 시뮬레이션의 경우 드릴쉽을 대상으로 탑재공정에 대한 조립 시뮬레이션을 통해 공정에 대한 유효성 검증을 수행할 수 있었고, 인간공학 시뮬레이션의 경우 FPSO 플랫폼을 대상으로 작업자 시뮬레이션을 통해 작업환경에서의 문제점을 사전에 도출할 수 있었다.

  This study proposes a new approach which combines Data Envelopment Analysis (DEA) and the Analytic Hierarchy Process (AHP) techniques to effectively evaluate Decision Making Units (DMUs). While DEA evaluates a quantitative data set, employs linear progr

This study proposes a new approach which combines Data Envelopment Analysis (DEA) and the Analytic Hierarchy Process (AHP) techniques to effectively evaluate Decision Making Units (DMUs). While DEA evaluates a quantitative data set, employs linear programming to obtain input and output weights and ranks the performance of DMUs, AHP evaluates the qualitative data retrieved from expert opinions and other managerial information in specifying weights. The objective of this research is to design a decision support process for managers to incorporate positive aspects of DEA's absolute numerical evaluations and AHP's human preference structure values. It is believed that a pragmatic manager will be more receptive to the results that include subjective opinions incorporated into the evaluation of the efficiency of each DMU efficiency when the AHP and DEA are combined simultaneously. The WPDEA method provides better discrimination than the DEA method by reducing the number of efficient units.