What study designs can isolate lighting effects from other differences between office spaces in daylight and window research?

Why is it hard to separate lighting from everything else in an office?

In a real office, daylight comes bundled with other features: the view out the window, the size and position of the window, the room layout, and the presence of artificial lighting. A post-occupancy evaluation of an office building in Jaffna found that occupants preferred natural light and that window views were seen as enriching, but the study could not isolate whether those preferences were driven by the light itself, the view, or other aspects of the space [1]. The authors used mapping and perceptual surveys to correlate responses with physically observed spaces, but that design describes associations rather than causes [1].

A critical review of 76 studies on window views, daylighting, and lighting found that the most common predictors were qualitative features of artificial lighting and windows, followed by light-source properties such as color temperature and illuminance [5]. Because methods for data collection, predictors, outcomes, and measurement varied widely, many results were inconclusive or limited to the specific study [5]. That variability is exactly why isolating lighting effects requires designs that control the non-lighting differences.

Can controlled experiments and virtual reality hold other differences constant?

Virtual reality offers a way to vary lighting while keeping the rest of the office identical. A systematic review of VR studies on indoor daylight visual comfort found that most focused on office environments and identified four clusters of factors that influence emotional, physiological, cognitive, and perceptual responses: window properties, light properties, natural properties, and spatial properties [4]. Because these factors can be manipulated separately in an immersive virtual environment, VR experimental designs can, in principle, change one factor at a time—such as light level—while holding window size, view, and layout fixed [4].

The same review analyzed experimental designs, protocols, and measurement tools from the selected studies to recommend best practices for future research [4]. That is the key advantage over field studies: a VR experiment can present the same room with different lighting conditions to different participants, or to the same participant in sequence, so that differences in responses are more plausibly attributable to the lighting manipulation rather than to unrelated office differences. The review does not claim that VR perfectly reproduces real offices; it presents VR as a tool for controlled assessment of visual comfort [4].

What can simulation studies tell us about window design and daylight?

Simulation studies isolate the physical effect of window design on daylight metrics, not on people. One study examined five common window shapes in two positions on a south-facing side across three Iranian cities, running thirty simulations per city to calculate spatial daylight autonomy (the percentage of space that meets a daylight threshold), annual sunlight exposure (a measure of potential glare), and useful daylight illuminance [2]. It found that window design significantly affected dynamic daylight performance: a centrally positioned square window had the lowest annual sunlight exposure at 14.4%, while higher-positioned horizontal windows reached the highest values of spatial daylight autonomy, useful daylight illuminance, and annual sunlight exposure—up to 77%, 59%, and 30%, respectively [2].

Another simulation study optimized window size, orientation, and wall reflectance for an office room with respect to daylight metrics and lighting energy demand [3]. Together, these simulation studies show that specific physical variables—window shape, position, size, orientation, and reflectance—can be varied systematically while other building features are held fixed [2][3]. That makes them useful for isolating how design choices change daylight availability, but they do not measure occupant responses, so they cannot by themselves tell us how lighting affects comfort or performance.

What can field studies contribute if they cannot isolate lighting?

Field studies remain useful for describing what occupants experience in real offices, even though they cannot cleanly separate lighting from other differences. The Jaffna post-occupancy evaluation found that occupants agreed natural light was the preferred mode of lighting for the workspace, and that window views were deemed to enrich the working environment, though preference for views did not strongly correlate among all respondents [1]. Those findings are about perceptions in a specific environmentally rated building in one locality, so they describe that setting rather than establish a general cause [1].

The critical review's attempt to build a simple model predicting occupant performance from illuminance and correlated color temperature illustrates both the promise and the limit of synthesizing field data: the data points were few and scattered, and the model suffers from considerable uncertainties [5]. In practice, the strongest evidence for isolating lighting effects comes from combining approaches—controlled VR experiments to test causal effects of specific lighting variables [4], simulations to quantify how design variables change daylight [2][3], and field studies to check whether those effects matter in real offices [1].

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