Bayesian Second-Order Factor Model for Maturity Assessment of CIM Technologies and Practices at Highway Agencies

Abstract

The work processes for highway infrastructure projects are undergoing significant transformations because of the advent of digital technologies for project delivery and asset management. Civil integrated management (CIM) encompasses the digital tools and practices that facilitate the collection, organization, and use of accurate project information throughout the facility lifecycle. With the increasing reliance on CIM technologies due to their proven benefits, there is a growing need to formalize a CIM maturity model that helps agencies gauge their CIM utilization activities. Through a survey of state transportation agencies and other CIM experts, this paper develops a quantitative approach to benchmark an agency’s CIM capability. A multistage Bayesian factor analysis technique was used in this study. The study jointly analyzes the information from the relevant literature and the collected data on relative importance and actual implementation levels of 16 attributes related to CIM utilization. Results suggest the existence of three latent factors that adequately indicate the measurements on these attributes related to technology, processes, and organization. Furthermore, results demonstrated an overall CIM maturity score exists at second-order and can adequately summarize the measurements along the first-order latent factors. The empirical validity of the second-order model was demonstrated by applying this framework to the usage data of six U.S. highway agencies to benchmark their CIM maturity. The mathematical framework of this study can help highway agencies develop customized applications for maturity assessment and support decisions for prioritizing CIM investments.