The value of cloud computing technology in public transportation construction

The analysis of large datasets to create value using cloud computing technology has helped many industries improve decision-making processes and better predict risk. The construction of transportation infrastructure systems managed by Departments of Transportation (DOT) produce significant amounts of project data that are stored in various locations by individuals working in multiple agency offices at every phase of the project’s lifecycle. Currently, DOTs do not have effective tools or processes to gather and analyze this fragmented data. Project records are generally stored in either physical repositories (e.g., actual paper files and file cabinets) or digital repositories (unsearchable file types and folders on multiple computers and servers) that are not able to be accessed by computers and/or whose contents cannot be searched and processed making it difficult, if not impossible, to create value from this vast amount of data. The exchange of project data throughout a DOT’s entire organization can create opportunities for new decision-making applications to better manage the development and operation of transportation infrastructure. To date, there has not been any significant literature studying the adoption of cloud computing technologies by DOTs. In general, DOTs have implemented market ready technologies and processes (e.g., mobile devices and electronic signatures) in an ad-hoc manner, limiting the results of these initiatives to a small group of users. The principal objective of this research is to examine the value of cloud computing technology in highway construction inspection. Data and observations are collected from the implementation of a cloud computing technology specifically developed for DOT project inspection, named HeadLight, to the Washington State DOT, Minnesota DOT, Texas DOT, Rhode Island DOT, and Louisiana Department of Transportation and Development (WSDOT, MnDOT, TxDOT, RIDOT, LADOTD respectively). The dissertation examines the following: 1. Productivity and data quality improvements associated with the use of HeadLight compared to traditional inspection practices 2. How the implementation method and organizational change management activities affect acceptance and adoption of new technologies 3. How HeadLight and the data collected within can be used beyond its intended project inspection purpose to create additional value throughout the organization Contributions of this work include (1) empirical measures of productivity and data quality improvements associated with the use of cloud computing technology over traditional inspection methods that can help transportation agencies understand and articulate the benefits of investing in such technology solutions, (2) examination of a DOT technology implementation case study identifying key organizational change management factors that promote the likelihood of technology adoption for transportation agencies, and (3) potential applications of construction inspection data for project management, asset management, and environmental compliance offices. The outcomes and guidance provided in this dissertation informs transportation agencies the value of cloud computing technology and the importance of managing the implementation process of such technology.