A role model, whether an individual or a project, can inspire similar performance in others. This research examines such a phenomenon during the design process for more sustainable physical infrastructure. In this empirical study, engineering professionals (n = 54) were randomly assigned either a modified version of the Envision rating system for sustainable infrastructure, which was changed to include details from an exemplary role model project, or the current version of Envision, with no role model. Professionals given the role model version of Envision achieved on average 34% more points (SD = 27) than the control group (p = 0.001). A positive role model project appears to lead engineering professionals to higher goals for sustainability performance in their design decisions. This finding, and the corresponding line of interdisciplinary research, can be used in decision-structuring interventions, which are a relatively low-cost approach to support greater sustainability in physical infrastructure development.

Monitoring-based commissioning (MBCx) is a continuous building energy management process used to optimize energy performance in buildings. Although monitoring-based commissioning (MBCx) can reduce energy waste by up to 20%, many buildings still underperform due to issues such as unnoticed system faults and inefficient operational procedures. While there are technical barriers that impede the MBCx process, such as data quality, the focuses of this paper are the non-technical, behavioral and organizational, barriers that contribute to issues initiating and implementing MBCx. In particular, this paper discusses cognitive biases, which can lead to suboptimal outcomes in energy efficiency decisions, resulting in missed opportunities for energy savings. This paper provides evidence of cognitive biases in decisions during the MBCx process using qualitative data from over 40 public and private sector organizations. The results describe barriers resulting from cognitive biases, listed in descending order of occurrence, including: risk aversion, social norms, choice overload, status quo bias, information overload, professional bias, and temporal discounting. Building practitioners can use these results to better understand potential cognitive biases, in turn allowing them to establish best practices and make more informed decisions. Researchers can use these results to empirically test specific decision interventions and facilitate more energy efficient decisions.

Across fields, more sustainable and resilient outcomes are being realized through a whole systems design perspective, which guides decision-makers to consider the entire system affected including interdependent physical and social networks. Although infrastructure is extremely interdependent, consisting of diverse stakeholders and networks, the infrastructure design and construction process is often fragmented. This fragmentation can result in unnecessary tradeoffs, leading to poor outcomes for certain stakeholders and the surrounding environment. A whole systems design perspective would help connect this fragmented industry and lead to more sustainable outcomes. For example, a whole systems design approach to relieve traffic on a highway might see beyond the obvious, but often ineffective, response of adding a new vehicle lane to encourage a solution such as repurposing existing road lanes from automobiles to above-ground "subway" systems. This paper discusses influences to whole systems design and how intentional choice architecture, meaning the way decisions are posed, can nudge decision-makers to employ whole systems design and result in more sustainable infrastructure. By uncovering these influences and organizing them by the social, organizational, and individual levels of the infrastructure design process, this paper provides the needed foundation for interdisciplinary research to help harness these influences through choice architecture and whole systems design for the infrastructure industry.

The practice of monitoring-based commissioning (MBCx) using energy management and information systems (EMIS) has been shown to enable and help sustain up to 20% energy savings in buildings. Despite research that has quantified the costs, benefits, and energy savings of MBCx, the process remains underutilized. To understand why MBCx is not more frequently adopted and how to encourage its use, this research synthesizes qualitative data from over 40 organizations, currently engaging in MBCx. The outcome of this research is a framework containing variables that emerged from the qualitative data, marked as barriers or enablers, organized by phases of the MBCx process. The framework is comprised of 51 emergent variables that fall within 13 different categories. The variables that most frequently act as barriers are data configuration, measurement & verification (M&V), developing specifications for EMIS, and data architecture. Although some variables that act as barriers for one organization were identified as enablers for another. For example, payback/ROI was considered a barrier 7 times and an enabler 3 times. One organization had difficulty making the business case for the initial investment for MBCx due to lack of cost information, while another was able to justify large investments with documented savings of previously implemented measures identified through MBCx. The framework formally validates barriers found in previous research, and can be used by practitioners to better understand common experiences with MBCx. This research highlights the need for a similar collective data set to validate common enablers to MBCx and also the need for empirical research to determine relationships between variables. 2.3. Examples of variables impacting MBCx Previous case studies describe some variables [3,6,16-18] that act as barriers, impeding the process, or enablers, supporting the institutionalization of EMIS and/or MBCx, and energy saving goals. These variables can be inherent to the MBCx process, but cause unexpected challenges or barriers. For example, the University of California, Merced (UC Merced), adopted an MBCx process and reported that one of the biggest issues was data quality [3]. Although the performance of data quality checks is a step within the MBCx process, organizations might not know how often this actually impedes the process or that this can lead to issues like false positive alarms that cause cascading alert notifications during the implementation phase.

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