Many buildings underperform leading to up to 20% energy waste. Case studies on monitoring-based commissioning (MBCx) have shown that using energy management and information systems (EMIS) for continuous energy monitoring and analysis enables the identification of issues that cause energy waste and verifies energy conservation measures. However, MBCx is underutilized by organizations leading to an energy efficiency gap between the energy saving potential of technologies like EMIS and observed savings. This energy efficiency gap can be attributed to general barriers to MBCx and barriers caused specifically by cognitive bias in the decision-making process. Using qualitative data from over 40 organizations implementing and practicing MBCx, this manuscript provides a better understanding of these barriers. Chapter 1 synthesizes and codes the qualitative data to develop a framework of variables acting as barriers and enablers to MBCx. The framework highlights commonly experienced barriers like data configuration, and also variables with conflicting results like payback/return on investment, which was experienced as a barrier to some organizations and enabler to others. Chapter 2 examines the barriers to MBCx through a behavioral decision science lens and finds evidence of cognitive biases, specifically, risk aversion, social norms, choice overload, status quo bias, information overload, professional bias, and temporal discounting. The success of choice architecture in other energy efficiency decisions is used to offer suggestions for ways to overcome these cognitive biases. This manuscript can be used by practitioners to better understand potential barriers to MBCx and by researchers to prioritize gaps and find methods to overcome the barriers to MBCx. / Master of Science
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/81102 |
Date | 08 December 2017 |
Creators | Harris, Nora Elizabeth |
Contributors | Civil and Environmental Engineering, Shealy, Earl W., Reichard, Georg, Parrish, Kristen |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Thesis |
Format | ETD, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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