Thermo-specific self-efficacy (specSE) in relation to perceived comfort and control

Hawighorst, Maren; Schweiker, Marcel; Wagner, Andreas

doi:10.1016/j.buildenv.2016.03.014

Cited by 37 publications

(20 citation statements)

References 11 publications

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“…Three papers considered other psychological factors than personal control: thermo-specific selfefficacy [100], personality [49], and the anticipated cost of cooling [101]. They are each in turn described below.…”

Section: Other Psychological Factorsmentioning

confidence: 99%

“…Hawighorst et al [100] tested the impact of thermo-specific self-efficacy (specSE), defined as the expectation to be able to execute desired actions with respect to the control of indoor thermal conditions, on the perception of thermal comfort, assumed temperature, perceived control and physiological parameters. A median split on survey responses was used to separate participants into a group with high specSE and low specSE.…”

Section: Other Psychological Factorsmentioning

confidence: 99%

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Drivers of diversity in human thermal perception – A review for holistic comfort models

et al. 2018

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Understanding the drivers leading to individual differences in human thermal perception has become increasingly important, amongst other things due to challenges such as climate change and an ageing society. This review summarizes existing knowledge related to physiological, psychological, and context-related drivers of diversity in thermal perception. Furthermore, the current state of knowledge is discussed in terms of its applicability in thermal comfort models, by combining modelling approaches of the thermoneutral zone (TNZ) and adaptive thermal heat balance model (ATHB). In conclusion, the results of this review show the clear contribution of some physiological and psychological factors, such as body composition, metabolic rate, adaptation to certain thermal environments and perceived control, to differences in thermal perception. However, the role of other potential diversity-causing parameters, such as age and sex, remain uncertain. Further research is suggested, especially regarding the interaction of different diversity-driving factors with each other, both physiological and psychological, to help establishing a holistic picture.

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Section: Other Psychological Factorsmentioning

confidence: 99%

Section: Other Psychological Factorsmentioning

confidence: 99%

Drivers of diversity in human thermal perception – A review for holistic comfort models

et al. 2018

Self Cite

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“…For instance, in residential buildings, occupants have greater control over the thermal environment than in office buildings, as they do not need to share thermostat or other controls with their coworkers [62]. The higher perceived control has a psychological effect [63] that might lead to a wider acceptable temperature range [32]. Additionally, occupants need to pay the utility bills for heating and cooling in residential but not in offices, which constitutes an economic motivation to accept a wider temperature range in residential buildings.…”

Section: Limitationsmentioning

confidence: 99%

Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States

Wang

Hong

2020

Renewable and Sustainable Energy Reviews

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A carefully chosen indoor comfort temperature as the thermostat set-point is the key to optimizing building energy use and occupants' comfort and well-being. ASHRAE Standard 55 or ISO Standard 7730 uses the PMV-PPD model or the adaptive comfort model that is based on small-sized or outdated sample data, which raises questions on whether and how ranges of occupant thermal comfort temperature should be revised using more recent larger-sized dataset. In this paper, a Bayesian inference approach has been used to derive new occupant comfort temperature ranges for U.S. office buildings using the ASHRAE Global Thermal Comfort Database. Bayesian inference can express uncertainty and incorporate prior knowledge. The comfort temperatures were found to be higher and less variable at cooling mode than at heating mode, and with significant overlapped variation ranges between the two modes. The comfort operative temperature of occupants varies between 21.9 and 25.4°C for the cooling mode with a median of 23.7°C, and between 20.5 and 24.9°C for the heating mode with a median of 22.7°C. These comfort temperature ranges are similar to the current ASHRAE standard 55 in the heating mode but 2-3°C lower in the cooling mode. The results of this study could be adopted as more realistic thermostat set-points in building design, operation, control optimization, energy performance analysis, and policymaking.

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“…They found significant relationships between personality traits with thermal sensation and thermal preference of the respondents. Further interdisciplinary research on thermal comfort and psychology shows that thermal control and the feel of control have a great impact on the thermal comfort status of the occupant [66]. Kim et al [47] investigated users' preferences through a longitudinal field study of using PCS in the workplace.…”

Section: Individual Differences In Perceiving the Thermal Environmentmentioning

confidence: 99%

Patterns of thermal preference and Visual Thermal Landscaping model in the workplace

et al. 2019

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The main purpose of research on occupant behaviour is to enhance building energy performance. However, it is difficult to reduce the energy use without understanding the occupant, their needs and preferences. Individual differences and preferences for the thermal environment in relation to the spatial context are overlooked in the main stream of research. This study investigates the patterns of occupant thermal preference based on individual differences in perceiving the thermal environment to enhance user comfort and energy performance. A novel method of Visual Thermal Landscaping is used, which is a qualitative method to analyse occupant comfort and user behaviour according to the spatial context. This method drives away from the notion of 'thermal neutrality' and generic results, rather it opens to details and meaning through a qualitative analysis of personal-comfort, based on individual differences and spatial context information. Field test studies of thermal comfort were applied in five office buildings in the UK, Sweden and Japan with overall 2,313 data sets. The primary contribution of the study was the recognition of four patterns of thermal preference, including consistent directional preference; fluctuating preference; high tolerance and sensitive to thermal changes; and high tolerance and not-sensitive to thermal changes. The results were further examined in a longitudinal field test study of thermal comfort. In several cases, occupant thermal comfort and preferences were observed to be influenced by the impact of outdoor conditions, when the windows were fixed. Practical solutions for research, practice and building design were recommended with direct implications on occupant comfort and energy use.

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Thermo-specific self-efficacy (specSE) in relation to perceived comfort and control

Cited by 37 publications

References 11 publications

Drivers of diversity in human thermal perception – A review for holistic comfort models

Drivers of diversity in human thermal perception – A review for holistic comfort models

Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States

Patterns of thermal preference and Visual Thermal Landscaping model in the workplace

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