Abstracts – Browse Results
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Almazkoor, F B (2014) Two-stage methodology for managing and controlling material flow between multiple construction projects, Unpublished PhD Thesis, , Clemson University.
Altayeb, S A (1990) Drug testing and its impact on the incident rate in the construction industry, Unpublished PhD Thesis, , Clemson University.
Back, W E (1994) Quantifying benefits of electronic technology applied to bulk materials management, Unpublished PhD Thesis, , Clemson University.
Carpenter, N (2014) Comparison of the design-bid-build and construction manager at risk project delivery methods utilized for the construction of public schools, Unpublished PhD Thesis, , Clemson University.
Cole, B K (2012) Building social infrastructure through public-private partnerships: The case of student housing in public higher education, Unpublished PhD Thesis, , Clemson University.
George, R (2007) Information flow to support front end planning, Unpublished PhD Thesis, , Clemson University.
Howard, W E (1996) Innovative strategies for compensation of engineering and construction contractors, Unpublished PhD Thesis, , Clemson University.
Jonnalagadda, S (2016) Artificial neural networks, non linear auto regression networks (NARX) and causal loop diagram approaches for modelling bridge infrastructure conditions, Unpublished PhD Thesis, , Clemson University.
Nikyema, G A B (2020) Barriers to the adoption of green building materials and technologies in developing countries: The case of Burkina Faso, Unpublished PhD Thesis, , Clemson University.
Plumblee, J M, II (2013) Incorporating natural hazard resistance into the life cycle assessment framework, Unpublished PhD Thesis, , Clemson University.
Prince, J R (2004) Evaluating the impact of onsite design on project performance, Unpublished PhD Thesis, , Clemson University.
Rockow, Z R (2020) Qualitative & quantitative analyses of existing buildings’ adaptability, Unpublished PhD Thesis, , Clemson University.
Shealy, E W, III (2015) Decision environments to encourage more sustainable infrastructure outcomes, Unpublished PhD Thesis, , Clemson University.
- Type: Thesis
- Keywords: bias; complexity; sustainability; airport; landfill; landfills; pipeline; standards; decision making; design decision; infrastructure planning; professional; heuristic
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1697333137
- Abstract:
Physical infrastructure (i.e. roads, pipelines, airports, dams, landfills, and water treatment systems) contributes directly to sustainability outcomes such as energy and water use and climate changing emissions. The infrastructure built today will likely impact future generations for many years. Planning, design and development decisions about infrastructure are critical to the future performance of these systems. Such decisions about infrastructure are complex with multiple variables, alternative options, and design stages. To manage decisions that exceed cognitive capacity to consider all options, decision makers often create mental shortcuts (heuristics), and accompanied errors (biases). The potential cognitive biases when dealing with complex decisions about infrastructure are examined and an approach to reframe the decision process during infrastructure planning is explored. A more critical analysis is then provided for decision aids, like energy codes and rating metrics (e.g.LEED and Envision), which are intended to reduce complexity and improve decision making using set goals and scaled points for achieving predefined objectives in sustainability. However, unintentionally, these tools may create additional biases that limit the higher achievements in sustainability that are possible. For instance, framing a decision as a loss, rather than a gain, in value can reduce the decision makers' acceptance of risk and, in turn, influence the outcome. The Envision rating system for sustainable infrastructure is presented to measure the influence of framing effects on engineering decision environments. Envision's current framework, starts users with zero points and points are achieved when design considerations move beyond conventional construction standards. In a modified version of Envision, a higher benchmark is set. Users are endowed points and can lose points for not maintaining high consideration for sustainability. Students (n=41) and professional engineers (n=65) were randomly assigned the replica Envision software or the modified version endowing points. Participants were asked to make design considerations for a redevelopment project using Envision. The results indicate, the endowed version significantly improved students' and professional engineers' consideration for sustainability design achievement. The student participants that were endowed points (n=16) scored 63 percent of possible points compared to the standard group's (n=25) 44 percent (p=0. 002). The professional engineers that were endowed points (n=32) achieved 66 percent of possible points compared to the standard group's (n=33) 51 percent (p=0. 002). Both students and professional engineers that were endowed points acted loss averse trying to maintain the initial points in sustainability given. These findings suggest engineers' process design decisions by comparing alternative options. And options framed as a loss or gain in value affects the decision outcome. This research underscores the advances possible at the intersection of behavioral science and engineering for sustainability. Slight changes in framing decision aids can lead to greater achievement in sustainability, and at a relatively low cost to implement. Future research should continue to explore how engineers make decisions and what behavioral and decision theories can merge with engineering to encourage more sustainable infrastructure outcomes.
Skipper, C O (2004) An analysis of leadership behaviors in the construction industry: Identification of influences that develop top performing project managers and engineers, Unpublished PhD Thesis, , Clemson University.
Valdes-Vasquez, R (2011) Social sustainability considerations during planning and design: A framework of processes for construction projects, Unpublished PhD Thesis, , Clemson University.