Abstract:Since occupant behaviour impacts the energy performance of buildings, its study is relevant in order to bridge the performance gap. While the factors influencing occupant behaviour have been established, most studies have focused on those factors that motivate the action, such as environmental and temporal conditions. Contextual factors including spatial and occupant characteristics, which act as action moderators, remain a subject to explore. In this way, this article aims to identify patterns in the occupant… Show more
“…Vega et al [8] assessed various factors, including seven spatial factors (e.g., urban-rural gradient, city center, and village center), to develop a suitable policy for increasing the uptake of carbon emission reduction measures, and highlighted the importance of using spatial factors for designing energy policy frameworks. Marín-Restrepo et al [23] identified OB patterns in office environments through data analysis and the Chi-squared test based on spatial (e.g., spatial layout and occupant orientation relative to control elements) and human factors. Wilke et al [24] considered an independent variable that indicated whether an occupant lives in an urban/suburban area to simulate the starting probability of activities through a multinomial logit model.…”
Section: Review Of Methods For Considering Spatial Variation In Ob An...mentioning
confidence: 99%
“…Each group was homogenized to avoid the influence of sociodemographic factors in the spatial variation as shown in Table 1. The conditions for segmentation were the type of day (i.e., weekdays and weekends) and employment status-commonly used parameters in previous studies [19,20,23,24,50]. Groups 1 and 4 represent women with fulltime jobs; Groups 2 and 5 represent women with part-time jobs; Groups 3 and 6 represent unemployed women.…”
“…Vega et al [8] assessed various factors, including seven spatial factors (e.g., urban-rural gradient, city center, and village center), to develop a suitable policy for increasing the uptake of carbon emission reduction measures, and highlighted the importance of using spatial factors for designing energy policy frameworks. Marín-Restrepo et al [23] identified OB patterns in office environments through data analysis and the Chi-squared test based on spatial (e.g., spatial layout and occupant orientation relative to control elements) and human factors. Wilke et al [24] considered an independent variable that indicated whether an occupant lives in an urban/suburban area to simulate the starting probability of activities through a multinomial logit model.…”
Section: Review Of Methods For Considering Spatial Variation In Ob An...mentioning
confidence: 99%
“…Each group was homogenized to avoid the influence of sociodemographic factors in the spatial variation as shown in Table 1. The conditions for segmentation were the type of day (i.e., weekdays and weekends) and employment status-commonly used parameters in previous studies [19,20,23,24,50]. Groups 1 and 4 represent women with fulltime jobs; Groups 2 and 5 represent women with part-time jobs; Groups 3 and 6 represent unemployed women.…”
“…Relationships between adaptation and spatial and adaptable building characteristics have already been investigated in other contexts (e.g. Schweiker and Wagner 2016, Marín-Restrepo et al 2020aand 2020b and in hospitals (Willems et al 2021). More insight is needed into the relationship between adaptation and building physical and spatial characteristics.…”
Section: Future Researchmentioning
confidence: 99%
“…It builds upon existing research in order to understand the influence of adaptation and perceived control on how indoor conditions are experienced (e.g. Humphreys et al 2013, Schweiker and Wagner 2016, Marín-Restrepo et al 2020a, 2020b. More specifically, it aims to contribute to filling the knowledge gap about whether and how different adaptation strategies influence the experience of indoor conditions differently.…”
Hospitals' indoor conditions affect patients' comfort. Comfort is predicted based on threshold values for indoor environmental quality (IEQ) indicators, but discrepancies with actual (dis)comfort occur. Current prediction methods ignore the role of patients' adaptation or treat it as a 'black box'. Therefore, we investigated how distinguishing between adaptation strategies may help explain discrepancies. We combined sensor measurements of IEQ indicators (sound, light, temperature) at two hospital wards with a questionnaire among 238 patients. After grouping respondents according to their adaptation strategy, we investigated relationships between strategies, respondents' experiences of indoor conditions, and measured values of IEQ indicators. Experiences differ when respondents' adaptation strategy differs. Satisfaction votes are higher when sensation votes are more neutral or more as preferred. This occurs when respondents adapt behaviourally (i.e. adapt indoor conditions) or do not wish to adapt indoor conditions (e.g. adapt sensations), rather than when adapting psychologically (i.e. by choice or imposed). Adaptation strategies influence measured values differently, but this cannot explain differences in experiences.Adaptation strategies therefore seem to influence experiences in a psychological way, which current methods cannot predict. Attending to how adaptation influences experiences of indoor conditions, and how this differs between adaptation strategies, can thus contribute to reducing discrepancies.
“…Results from the questionnaire were analyzed using hierarchical cluster analysis. A field study covering 85 office spaces within 11 buildings in Chile showed that occupants' preferences and behavior might also be influenced by their spatial location within a room or building, considering their opportunities (Marín-Restrepo, Trebilcock, & Gillott, 2020).…”
Debido a la actual crisis energética mundial y como resultado de los acuerdos de las naciones participantes, se han establecido medidas por las Naciones Unidas para superar los desafíos relacionados. A pesar de los esfuerzos para incluir a los países subdesarrollados en dicho proceso de decisión, la mayoría de las contribuciones continúan estando inclinadas al hemisferio norte. Así, este trabajo se enfoca en destacar los esfuerzos realizados por los países Latinoamericanos (LA), entre 2018-2020, para contribuir específicamente en las mejoras en el desempeño energético en edificaciones para abordar los desafíos actuales del lado de la demanda. Dichos desafíos están relacionados con la gestión de la demanda: (i) picos de demanda no controlados y (ii) capacidad de transmisión y distribución insuficiente en la red eléctrica. Las contribuciones de LA se clasifican en independientes, colaboración y aplicación. Los estudios también se clasificaron en teóricos, experimentales, ambos y revisiones. La metodología de filtrado de dos etapas implementada dio como resultado un total de 176 documentos como lista inicial. Al centrarse sólo en los aspectos relacionados con los ocupantes, las soluciones pasivas y de bajo consumo y las técnicas de previsión para edificios inteligentes, la lista procesada dio como resultado un total de 73 estudios. Los resultados mostraron que los esfuerzos realizados por los países LA residen en su mayoría en la implementación de estrategias previamente desarrolladas y propuestas por países desarrollados, para realizar estudios de caso como independiente o en colaboración. Finalmente, se presenta un análisis FODA para analizar más los resultados.
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