TY - JOUR KW - Office buildings KW - Occupant behavior KW - Machine learning KW - Human-building interaction KW - Five factor model KW - Personality type AU - Tianzhen Hong AU - Chien-Fei Chen AU - Zhe Wang AU - Xiaojing Xu AB -

Occupant behavior influences office building energy performance. The level of human-building interactions (HBIs) in shared offices strongly influences building energy use and occupant well-being. This study explored the link between occupant personality types and their behaviors of sharing energy and environment control systems and interactions with their colleagues. Inspired by the Five-Factor Model (FFM), we classified HBI behaviors into four dimensions: willingness to share controlknowledge of controlgroup decision behavior, and adaptive strategies. These four variables can be mapped to the four personality traits proposed by the FFM: agreeableness, openness, extraversion, and conscientiousness. Our cluster analysis identified six behavioral patterns: average (17.7%), reserved (15.3%), environmentally friendly (16.6%), role model (24.2%), self-centered (17.2%), and mechanist (9.0%). We further applied association rules, a widely utilized machine learning technique, to discover how demographics, building-related contextual factors, and perception-attitudinal factors influence HBI behaviors. Country, control feature accessibility, and group dynamics were found to be the three most influential factors that determine occupants’ HBI behaviors. The study provides insights about building design and operation, as well as policy to promote socially and environmentally desirable HBI behaviors in a shared office environment.

BT - Building and Environment DA - 01/2020 DO - 10.1016/j.buildenv.2019.106602 LA - eng N2 -

Occupant behavior influences office building energy performance. The level of human-building interactions (HBIs) in shared offices strongly influences building energy use and occupant well-being. This study explored the link between occupant personality types and their behaviors of sharing energy and environment control systems and interactions with their colleagues. Inspired by the Five-Factor Model (FFM), we classified HBI behaviors into four dimensions: willingness to share controlknowledge of controlgroup decision behavior, and adaptive strategies. These four variables can be mapped to the four personality traits proposed by the FFM: agreeableness, openness, extraversion, and conscientiousness. Our cluster analysis identified six behavioral patterns: average (17.7%), reserved (15.3%), environmentally friendly (16.6%), role model (24.2%), self-centered (17.2%), and mechanist (9.0%). We further applied association rules, a widely utilized machine learning technique, to discover how demographics, building-related contextual factors, and perception-attitudinal factors influence HBI behaviors. Country, control feature accessibility, and group dynamics were found to be the three most influential factors that determine occupants’ HBI behaviors. The study provides insights about building design and operation, as well as policy to promote socially and environmentally desirable HBI behaviors in a shared office environment.

PY - 2020 EP - 106602 ST - Building and Environment T2 - Building and Environment TI - Linking human-building interactions in shared offices with personality traits VL - 170 SN - 03601323 ER -