Author ORCID Identifier

Date Available


Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation




Civil Engineering

First Advisor

Dr. Gabriel Dadi


Transportation Asset Management (TAM) is a data-driven decision-making process to maintain and extend the serviceability of transportation assets throughout their lifecycle. TAM is an extensive data process requiring accurate, high-quality information for better decision-making. A significant challenge that state Departments of Transportation (DOTs) face is allocating limited funds to optimize their assets’ performance. The criticality of this challenge increases when state DOTs need to manage a wide variety of assets distributed along with a vast network; thus, they prioritize the management of high-value assets and visible ones such as bridges, and they pay less attention to ancillary assets even though a significant percentage of these assets is critical for highway safety. This research aims to fill the gap in the current body of knowledge by focusing on ancillary transportation assets, a complicated area of the highway system that researchers and practitioners rarely investigate.

Conversely, emerging technologies, namely Digital Twins, have the potential to leverage the value of asset data and transform data into valuable insights to inform decision-making. The research arc “What- Where- and How” implementing Digital Twins as an information management system for transportation assets was explored to expand the knowledge on Digital Twins further. This research 1) investigates the awareness of the Digital Twins concept and its implementation in the civil infrastructure industry, 2) documents the current practices of state DOTs toward the digital transition of their transportation asset data, contextualizes the DOTs’ maturity in the advancement of digital processes, and determines where they stand in their Digital Twins journey, and 3) investigates how to support state DOTs in achieving their Digital Twins vision for infrastructure assets by identifying the data requirements and the “ideal” environment that fulfills the vision of Digital Twins. Additionally, this research helps set the wheel to put the Digital Twins vision into action by developing the laying foundation for an interactive business canvas model that state DOTs can use as a guidance tool to implement Digital Twins.

Digital Object Identifier (DOI)

Available for download on Saturday, July 12, 2025