Building occupants are continuously exposed to multiple indoor environmental stimuli, including thermal, visual, acoustic, and air quality related factors. Moreover, personal and contextual aspects can be regarded as additional domains influencing occupants' perception and behaviour. The scientific literature in this area typically deals with these multiple stimuli in isolation. In contrast to single-domain research, multi-domain research analyses at least two different domains, for example, visual and thermal. The relatively few literature reviews that have considered multi-domain approaches to indoor-environmental perception and behaviour covered only a few dozen articles each. The present contribution addresses this paucity by reviewing 219 scientific papers on interactions and cross-domain effects that influence occupants' indoor environmental perception and behaviour. The objective of the present review is to highlight motivational backgrounds, key methodologies, and major findings of multi-domain investigations of human perception and behaviour in indoor environments. The in-depth review of these papers provides not only an overview of the state of the art, but also contributes to the identification of existing knowledge gaps in this area and the corresponding need for future research. In particular, many studies use "convenience" variables and samples, there is often a lack of theoretical foundation to studies, and there is little research linking perception to action.

In light of recent research, it is evident that occupants are playing an increasingly important role in building energy performance. Around the world, a driving factor for how buildings are designed-and operated in some cases-is the local building codes. Yet, occupant-related aspects of building energy codes have traditionally been simple because: 1) occupants are often seen as a source of uncertainty that cannot be reconciled by current code methodologies and language, and 2) the codes have not kept up with the recent surge of interest and importance of occupants. This paper provides a review of 22 international building energy codes and standards by first comparing quantitative aspects and then analyzing rules and approaches mandated by the codes. The review of requirements for prescriptive and performance path requirements revealed a wide range of occupant-related values, approaches, and attitudes. For example, a key value such as occupant density varies by nearly a factor of three between countries' codes, which among other things underlines the need for development of locally tailored occupant behaviour models for future occupant-centric building performance standards and codes. Moreover, occupants are often referred to only implicitly; the level of optimism that occupants make energy-saving actions varies greatly; and, only a few codes address occupant feedback and system usability. Based on the findings, a set of initial recommendations for future building energy codes is made. The focus in this paper is offices, though the general recommendations are applicable to other building types.

Extended literature reviews confirm that the accurate evaluation of occupant energy-related behaviour is a key factor for bridging the gap between predicted and actual energy performance of buildings. One of key energy-related human behaviour is window control actions that have been modelled by different probabilistic modelling approaches. In recent years, Bayesian Networks (BNs) have become a popular representation based on graphical models for modelling stochastic processes with consideration of uncertainty in various fields, from computational biology to complex engineering problems. This study investigates the potential applicability of BNs to capture underlying complicated relationships between various influencing factors and energy-related behavioural actions of occupants in residential buildings: in particular, window opening/closing behaviour of occupants in residential buildings is investigated. This study addresses five key research questions related to modelling window control behaviour: (A) variable selection for identifying key drivers impacting window control behaviour, (B) correlations between key variables for structuring a statistical model, (C) target definition for finding the most suitable target variable, (D) BN model with capabilities to treat mixed data, and (E) validation of a stochastic BN model. A case study on the basis of measured data in one residential apartment located in Copenhagen, Denmark provides key findings associated with the five research questions through the modelling process of developing the BN model.

This study investigates human-building interaction in office spaces across multiple countries including Brazil, Italy, Poland, Switzerland, the United States, and Taiwan. We analyze social-psychological, contextual, and demographic factors to explain crosscountry differences in adaptive thermal actions (i.e. cooling and heating behaviors) and conformity to the norms of sharing indoor environmental control features, an indicator of energy consumption. Specifically, personal adjustments such as putting on extra clothes are generally preferred over technological solutions such as adjusting thermostats in reaction to thermal discomfort. Social-psychological factors including attitudes, perceived behavioral control, injunctive norms, and perceived impact of indoor environmental quality on work productivity influence occupants' intention to conform to the norms of sharing environmental control features. Lastly, accessibility to environmental control features, office type, gender, and age are also important factors. These findings demonstrate the roles of social-psychological and certain contextual factors in occupants' interactions with building design as well as their behavior of sharing environmental control features, both of which 2 significantly influence building energy consumption, and thus, broader decarbonization.