TY - GEN
T1 - Completing the Missing Puzzle Piece of the Building Design Process
T2 - Construction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016
AU - Mostavi, Ehsan
AU - Asadi, Somayeh
AU - Ramaji, Issa J.
N1 - Publisher Copyright:
© ASCE.
PY - 2016
Y1 - 2016
N2 - Occupants' satisfaction is becoming a more important issue in our modern competitive work system. Satisfaction is largely a state of mind depending on many different parameters. There are various strong evidences indicating that building characteristics and the quality of indoor environment significantly influence the level of satisfaction and efficiency of occupants in commercial buildings. In order to increase the overall satisfaction level, decision makers should face the challenge to identify and apply those strategies that have the highest probability to satisfy building occupants. While the benefits of occupants' satisfaction improvement are acknowledged, the impacts of different strategies and their expected results have not been quantitatively described. This paper presents a methodology for developing a quantitative model to measure the overall satisfaction of occupants in commercial buildings associated with indoor environment quality such as lighting, temperature satisfaction, etc. A survey is design to collect the associated data. In addition, three different models including simple multi-variate regression model, model based on the normalized averages of weightings, and refined normalized weightings have been developed to quantify the overall satisfaction of occupants. These models will help to identify the most influential factors affecting their satisfaction. In addition, a probability distribution of weighing for each aspect through the studied population is presented which will be a beneficial tool to estimate the outcomes of different strategies.
AB - Occupants' satisfaction is becoming a more important issue in our modern competitive work system. Satisfaction is largely a state of mind depending on many different parameters. There are various strong evidences indicating that building characteristics and the quality of indoor environment significantly influence the level of satisfaction and efficiency of occupants in commercial buildings. In order to increase the overall satisfaction level, decision makers should face the challenge to identify and apply those strategies that have the highest probability to satisfy building occupants. While the benefits of occupants' satisfaction improvement are acknowledged, the impacts of different strategies and their expected results have not been quantitatively described. This paper presents a methodology for developing a quantitative model to measure the overall satisfaction of occupants in commercial buildings associated with indoor environment quality such as lighting, temperature satisfaction, etc. A survey is design to collect the associated data. In addition, three different models including simple multi-variate regression model, model based on the normalized averages of weightings, and refined normalized weightings have been developed to quantify the overall satisfaction of occupants. These models will help to identify the most influential factors affecting their satisfaction. In addition, a probability distribution of weighing for each aspect through the studied population is presented which will be a beneficial tool to estimate the outcomes of different strategies.
UR - http://www.scopus.com/inward/record.url?scp=84976343021&partnerID=8YFLogxK
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U2 - 10.1061/9780784479827.112
DO - 10.1061/9780784479827.112
M3 - Conference contribution
AN - SCOPUS:84976343021
T3 - Construction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016
SP - 1112
EP - 1121
BT - Construction Research Congress 2016
A2 - Perdomo-Rivera, Jose L.
A2 - Lopez del Puerto, Carla
A2 - Gonzalez-Quevedo, Antonio
A2 - Maldonado-Fortunet, Francisco
A2 - Molina-Bas, Omar I.
PB - American Society of Civil Engineers (ASCE)
Y2 - 31 May 2016 through 2 June 2016
ER -