Cognitive barriers during monitoring-based commissioning of buildings

被引:11
|
作者
Harris, Nora [1 ]
Shealy, Tripp [1 ]
Parrish, Kristen [2 ]
Granderson, Jessica [3 ]
机构
[1] Virginia Tech, Charles Edward Via Jr Dept Civil & Environm Engn, 200 Patton Hall, Blacksburg, VA 24061 USA
[2] Arizona State Univ, Sch Sustainable Engn & Built Environm, 660 S Coll Ave, Tempe, AZ 85287 USA
[3] Ernest Orlando Lawrence Berkeley Natl Lab, Bldg Technol & Urban Syst Div, 1 Cyclotron Rd, Berkeley, CA 94720 USA
基金
美国国家科学基金会;
关键词
Monitoring-based commissioning; Energy management and information systems; Cognitive biases; Behavioral decision science; Risk aversion; ENERGY EFFICIENCY; CLIMATE-CHANGE; INFORMATION OVERLOAD; SOCIAL NORMS; DEFAULTS; PREFERENCE; FRAMEWORK; FEEDBACK; SCIENCE; CHOICE;
D O I
10.1016/j.scs.2018.12.017
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
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页数:8
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