EAGER: SAI: Collaborative Research: Behavioral Theories for Resilient and Sustainable Infrastructure

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership.

To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.

This SAI project investigates interactions between the human decision-making process and infrastructure performance. Human actions and the decisions made in planning, designing and constructing infrastructure are influenced by an engineer’s socioeconomic and demographic characteristics, attitudes, values, and perceptions. Infrastructure response is also driven by uncertainties in material properties, design strategies, and physical and climatic stressors.

This project links a well-studied social science framework (The Theory of Planned Behavior) to engineering modeling, offering new and transformative knowledge about infrastructure management. The new research models are specifically tested in the context of resilient flood protection systems such as levees and breakwaters in flood-prone communities of the Northeastern United States.

The project aims to advance social science theory, develop new metrics for measuring and predicting the interaction of social, economic, and physical behavior of infrastructure components, and to use these metrics to enhance the resilience of infrastructure. The project ultimately helps to connect engineers with tools and methods that enable them to better understand and consider human behavior, potentially leading to tangible physical outputs.

This will improve infrastructure design and performance assessment, making infrastructure safer, more cost-effective, and resilient.

This project focuses primarily on theory building to develop a dynamic and novel model merging the Theory of Planned Behavior (TPB) and System Dynamics Modeling. The goal is to integrate important social science variables such as values, norms, and attitudes into the flow of decision making an engineer undertakes for infrastructure design and uncertainties associated with infrastructure performance.

The project develops a refined theoretical framework merging TPB with engineering, including a systematic theory-driven literature review, interviews with experts, and a survey of the engineering community. This static model is then transitioned to a more dynamic system platform incorporating dependencies, sensitivity analyses, and multivariate statistics.

Bridging the theory to practice is tested on two flood defense target infrastructure systems (levees and breakwaters) in flood-prone communities of the Northeastern United States. The anticipated outcomes of the research include advancing social science theory, developing new metrics for measuring and predicting the interaction of social, economic, and physical behavior of infrastructure components, and using these metrics to enhance the resilience of infrastructure in design, construction, performance, and maintenance phases.

The project builds a transdisciplinary new theory by extending a widely studied behavioral framework to strengthen convergence between social science and infrastructure. Ultimately, the project will help to connect engineers with tools and methods that enable better understanding of human processes that intervene in the performance of urban infrastructure.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.