Using Data Envelopment Analysis Method to Identify Characteristics of Parameters in Maintenance of Transportation Infrastructure Assets

An essential part in performance-based maintenance for transportation infrastructure assets is well-informed resource allocation process and sound investment strategy in prioritizing maintenance activities and operations. Periodical maintenance cycle commonly used by state transportation agencies includes resource allocation and distribution, actual maintenance work, and condition assessment at the end of the cycle that affects how subsequent maintenance cycle is planned. Maintenance efficiency is defined as a representation of the technical efficiency of this maintenance cycle. Data Envelopment Analysis (DEA) method is often used in a wide variety of fields to compare work efficiency of multiple decision-making units. In transportation infrastructure maintenance, this method is mostly used to compare efficiency of decision-making units within a specific jurisdictional area. This study used DEA in a decentralized fashion and focuses on a single decision-making unit, and compares its own efficiencies each year throughout a seven-year period. This decentralized analysis allows us to understand more about individual decision-making units and to uncover tendencies and identify characteristics of the maintenance parameters, which are helpful in planning for subsequent maintenance cycle. Case studies were performed using sensitivity analysis technique. This was done by gradually varying the values of known maintenance parameters and running them as DEA models. Findings from the case studies are a wealth of information regarding maintenance parameters of a particular decision-making unit. These will help maintenance administrators evaluate the efficiencies of prior work, plan subsequent maintenance period, and possibly establish efficiency guideline to prepare for future, specific situations.