Occupant responses on satisfaction with window size in physical and virtual built environments

Building and Environment 166 (2019) 106409

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Occupant responses on satisfaction with window size in physical and virtual built environments

T

Hong Taehoona, Lee Minhyuna,∗, Yeom Seungkeuna, Jeong Kwangbokb a b

Department of Architecture and Architectural Engineering, Yonsei University, Seoul, 03722, Republic of Korea Department of Industrial Policy Research, Construction & Economy Research Institute of Korea, Seoul, 06050, Republic of Korea

ARTICLE INFO

ABSTRACT

Keywords: Occupant satisfaction Virtual reality (VR) Experimental study Built environment Window size Windowed office space

The satisfaction of occupants with a built environment can vary depending on their response to certain design variables, such as window size. However, relevant studies are limited because of the necessity for immense resources and the technical difficulty of creating a physical environment with different window sizes under the same experimental conditions. To resolve this problem, a randomized crossover study design and a new method for virtual reality modeling are implemented to conduct two sets of experiments in the physical and virtual environments. By investigating the satisfaction of 50 participants in different built environments, this study identifies the responses of occupants not only to changes in the window-to-wall ratio (WWR) (i.e., 15%, 30%, 45%, and 60%) but also to differences in the physical and virtual office spaces. The results of this experimental study confirm the following. (i) The virtual environment is an adequate representation of the physical environment of windowed spaces; it exhibits no significant difference in occupant satisfaction between physical and virtual spaces. (ii) The participants express a significantly higher occupant satisfaction with the senses of visual comfort, inner space, and openness with higher WWRs (i.e., 30%, 45%, and 60%) than that with a lower WWR (i.e., 15%) by up to 1.86 times. However, although it is not statistically significant, the increase in the WWR decreases occupant satisfaction in terms of sense of privacy. By applying the proposed experimental approach of utilizing a virtual environment, it is possible to investigate various occupant responses to different window design variables.

1. Introduction With the growing number of workers performing various office tasks using computers and other equipment in indoor spaces, the suitable design of office spaces is increasingly becoming more significant. In particular, in designing office spaces, it is necessary to sufficiently consider the physical and psychological satisfaction of office workers who spend prolonged periods in such spaces [1]. Among the various design variables for office spaces, the window is a key element that performs the basic functions of a building, i.e., lighting and ventilation [2]. Recently, however, high-performance artificial lighting and heating, ventilation, and air conditioning system have made it necessary to enhance other window characteristics that, for example, can

∗

provide a view of the outside or satisfy an occupant's sense of openness [3,4]. Thus, it is not difficult to appreciate why certain buildings have glass curtain walls, which not only improve constructability and aesthetic value, but also offer a sense of openness [5]. The careless expansion of windows, however, can cause anxiety and privacy problems [1,4,6,7] as well as low visual comfort because of excessive sunlight [8–10]; this may also increase heating and cooling energy demands because of high thermal transmittance [11–13]. It is therefore crucial to determine the appropriate window size for office spaces by considering various occupant requirements. Various studies have focused on energy consumption, thermal and visual comfort, and ventilation relative to windowed spaces [12–15]. Bokel [13] calculated the heating, cooling, and lighting energy de-

Corresponding author. Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. E-mail address: [email protected] (M. Lee).

https://doi.org/10.1016/j.buildenv.2019.106409 Received 27 April 2019; Received in revised form 29 August 2019; Accepted 10 September 2019 Available online 11 September 2019 0360-1323/ © 2019 Elsevier Ltd. All rights reserved.

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Fig. 1. Research framework.

mands based on the location, size, and shape of the window and proposed a strategy to improve the design of office building façades. Certain studies focused on visual comfort [8,9] or proposed window design criteria considering the energy consumption and visual comfort based on window size [16]. Zhai et al. [17] have set factors, such as energy consumption, thermal and visual comfort, and ventilation as parameters; they also presented a method to determine an optimal window design. Nevertheless, these previous studies are limited; the optimal window design is determined based only on factors with objective measures although the satisfaction or emotional responses of occupants may differ in relation to window specifications (i.e., the location, size, and shape of the window). Some of the previous studies have investigated the aforementioned occupant responses to windowed office spaces; however, these were generally focused on the satisfaction with different views outside the

window (e.g., natural or urban landscapes and indoor or outdoor views) rather than with the physical elements of the window such as its size [4,18–20]. To conduct an experimental study on occupant satisfaction based on window size, it is necessary to build an environment under the same experimental conditions with different window sizes. Physically creating the same indoor spaces with different window sizes, however, is extremely difficult when compared with the manipulation of other design variables (e.g., color, material, lighting, and furniture), because this requires a considerable amount of resources, such as time, money, and labor. In view of this, previous studies conducted in physical environments lacked analysis on the effect of window size under the same experimental conditions. As a potential solution to this problem, virtual reality (VR) technology through real-time rendering has emerged as a popular alternative for experiencing various indoor spaces without creating

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(i) Step 1: Experimental design; (ii) Step 2: Experimental variable setting; (iii) Step 3: Virtual reality modeling; (iv) Step 4: Experimental procedure; (v) Step 5: Comparative analysis of experimental results.

physically them [21,22]. With the rapid growth in the performance of graphics processing units, the VR technology has enabled occupants to experience and evaluate indoor spaces before they are built, making it easier for them to determine spaces that they may prefer or be satisfied with [23–26]. As such, the utilization of the VR technology in the built environment has not only saved time, money, and labor to create indoor spaces, but has also made it possible to find satisfactory design alternatives for office spaces in a simple and easy way. Experiments on different window sizes can be conducted accordingly under identical conditions in a virtual environment via VR instead of a physical environment. There are generally two VR modeling methods that can create a virtual environment: (i) the use of a VR three-dimensional (3D) or a 360-degree camera based on the physical environment [27]; (ii) the use of 3D modeling tools based on the two-dimensional (2D) plans or actual measurements [24,26,28]. Of the two methods, most previous studies that adopted the VR for experiments in various built environments created a virtual environment through 3D modeling using building information modeling (BIM) and 3ds Max [24,25,29]. In particular, Zhang et al. [29] and Heydarian et al. [24–26,28] examined the task performance of occupants according to various design variables (e.g., interior color and lighting) in the virtual office space created using Revit (i.e., BIM software from Autodesk) and 3dsMax. These previous studies, however, had the following limitations relative to VR modeling. First, the VR modeling using a 3D or a 360-degree camera requires a physical environment; thus, this VR modeling method cannot create a virtual environment without an actual environment; moreover, these VR 3D or 360-degree cameras are considerably expensive. Second, 3D modeling using BIM software is less accessible to non-specialists than 3D modeling tools, such as SketchUp. Moreover, this VR modeling method is performed based on a 2D plan using AutoCAD; thus, to change certain design variables in an office space, it is necessary to recreate the 2D plan, which can cause considerable inconvenience. It also creates a virtual environment that is somewhat unrealistic in terms of setting the materials or lighting indoor spaces. To apply an advanced and improved VR modeling method for examining occupant satisfaction, which has not been covered by most of the previous studies on determining the optimal window size or design, this study investigates the responses of occupants relative their satisfaction with window sizes in physical and virtual built environments. Towards this end, two sets of experiments in the physical and virtual environments are performed in this study (i) to evaluate whether the virtual environment is an adequate representation of the physical environment of a windowed office space and (ii) to determine whether there are differences among the occupant responses pertaining to their satisfaction with different window sizes in a virtual environment. By incorporating an improved VR modeling method using SketchUp, 3ds Max, and Unreal engine to the investigation of windowed spaces, this study can (i) improve the accessibility of 3D modeling (ii) facilitate change in design variables (i.e., window size), for office spaces, (iii) make it possible to conduct an experiment in a more realistic virtual environment, and (iv) create an environment under identical experimental conditions for investigating the effect of the different window sizes.

2.1. Step 1: Experimental design Instead of creating different window sizes in a physical environment, an experimental study is performed in a virtual environment to analyze the variation among the responses of occupants pertaining to their satisfaction with different window sizes. Two sets of experiments in the physical and virtual environments are designed, as follows. (i) Experiment (1): Comparison of occupant responses to window size between physical and virtual environments; (ii) Experiment (2): Comparison of occupant responses to different window sizes in a virtual environment (Fig. 2). A 17.44 m2 office space in “Y” University is selected as the experimental case. Through Experiment (1), this study compares occupant responses on the sense of presence and satisfaction in the physical and virtual environments of windowed spaces to determine whether the virtual environment is an appropriate representation of the physical environment. Through Experiment (2), this study compares occupant responses regarding their satisfaction with different window sizes in virtual environments based on the findings from Experiment (1) (i.e., the virtual environment can adequately represent the physical environment of windowed spaces). To measure occupant satisfaction in Experiments (1) and (2), a satisfaction questionnaire survey is conducted. Apart from this, a presence questionnaire survey is also performed in Experiment (1) to measure and evaluate the sense of presence in a virtual environment. To accurately compare occupant responses in terms of their satisfaction with different window sizes in Experiment (2), appropriate variations of window sizes are selected based on the following criteria. First, window-to-wall ratio (WWR) in percent is used to express the window size numerically. Second, the minimum criterion of the WWR is set to 15% based on the minimum window area criteria provided by Article 17, “Window, etc. for lighting and ventilation” of the Enforcement Regulation on the Standard for the Evacuation and Fire Prevention, etc. of Buildings under the Building Act of South Korea. Third, the maximum criterion of the WWR is set to 60% based on the actual window area of the office space in “Y” University. Finally, a pilot test with 10 pre-participants is conducted to determine the appropriate variations of the WWR by dividing the area between the minimum (i.e., 15%) and maximum (i.e., 60%) criteria of the WWR into (i) 5% (eight variations), (ii) 10% (six variations), and (iii) 15% (four variations) intervals. Here, only the WWR is changed to maintain the height-towidth ratio (height:width = 3:7) of the window in the actual office space in “Y” University. As a result, the variations of the WWR at 5% and 10% intervals are found to be negligible so as to consider their difference. Apart from this, because the variations are numerous, these would require overly long experiments that may be exhaustive for participants and may make it difficult to obtain meaningful experimental results. Therefore, the four following variations of the WWR at 15% intervals within its minimum and maximum criteria are used to create the virtual environment and conduct Experiment (2): (i) WWR = 15%; (ii) WWR = 30%; (iii) WWR = 45%; (iv) WWR = 60% (Fig. 3). To conduct Experiments (1) and (2), the study analyzes the withingroup effects using a randomized crossover study design (a type of repeated measures design), where a subject is randomly assigned to

2. Materials and methods An experimental study is designed and performed to investigate occupant responses pertaining to their satisfaction with window sizes in physical and virtual built environments by following five steps (Fig. 1):

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Fig. 2. Experimental design and hypotheses.

Fig. 3. Four variations of WWR for Experiment (2).

Table 1 Items of presence questionnaire [36]. Factors

Item No.

Items

Seven-point Likert scale

Item sources

General presence

G1

In the computer-generated world, I had a sense of “being there.”

0 = not at all/6 = very much

Slater and Usoh [37]

Spatial presence

SP1 SP2 SP3 SP4

I somehow felt that the virtual world surrounded me. I felt like I was just looking at pictures. I did not feel present in the virtual space. I had a sense of acting in the virtual space, rather than operating something from the outside. I felt present in the virtual space.

0 = not at all/6 = very much 0 = not at all/6 = very much 0 = did not feel/6 = felt present 0 = fully disagree/6 = fully agree

Schubert Schubert Schubert Schubert

0 = fully disagree/6 = fully agree

Schubert et al. [35]

How aware were you of the real-world surroundings (i.e., sound, room temperature, etc.) while navigating in the virtual world? I was not aware of my real environment. I still paid attention to the real environment. I was completely captivated by the virtual world.

0 = extremely aware/6 = not aware at all

Witmer and Singer [38]

0 = fully disagree/6 = fully agree 0 = fully disagree/6 = fully agree 0 = fully disagree/6 = fully agree

Schubert et al. [35] Schubert et al. [35] Schubert et al. [35]

0 = completely real/6 = not real at all 0 = not consistent/6 = very consistent

REAL3

How real did the virtual world seem to you? Did your experience in the virtual environment seem consistent with your real-world experience? How real did the virtual world seem to you?

Hendrix [39] Witmer and Singer [38] Carlin et al. [40]

REAL4

The virtual world seemed more realistic than the real world.

SP5 Involvement

INV1 INV2 INV3 INV4

Experienced realism

REAL1 REAL2

4

0 = about as real as an imagined world/6 = indistinguishable from the real world 0 = fully disagree/6 = fully agree

et et et et

al. al. al. al.

[35] [35] [35] [35]

Schubert et al. [35]

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Table 2 Literature reviews on satisfaction factors for windowed spaces. Authors

Country

Year

Sense of visual comfort

Sense of privacy

Sense of inner space

Sense of openness

Dogrusoy and Tureyen [2] Farley and Veitch [4] Ozdemir [3] Yildirim et al. [41] Barbara [42] Lyu [7] Kim et al. [5]

Turkey Canada Turkey Turkey Norway Korea Korea

2007 2001 2010 2007 2008 1997 2014

● ● ● ● ● ● ●

● ● – ● – ● –

● ● ● ● ● ● ●

● ● ● – – ● ●

different experimental exposures. A randomized crossover study design minimizes the order effect to guarantee sufficient statistical power with a small number of subjects. To further prevent this study design from being hindered by external factors, the respondent participates in Experiments (1) and (2) in a single visit; this precludes the possible influence of change in the respondent's health or weather conditions. With the above experimental design, the following hypotheses are tested for comparison in the within-group effects.

2.2.2. Step 2.2: Measuring occupant satisfaction using satisfaction questionnaire This study measures and compares the occupant satisfaction in the physical and virtual environments using the satisfaction questionnaire in Experiments (1) and (2). To construct this questionnaire, the following four satisfaction factors are identified based on previous studies on occupant satisfaction, perception, and emotional responses to windowed spaces [2–5,7,13,41]: (i) sense of visual comfort; (ii) sense of privacy; (iii) sense of inner space; (iv) sense of openness (Table 2). As listed in Table 2, most of the previous studies constructed their satisfaction questionnaire by considering all of these four factors. The specific question items of the satisfaction questionnaire are therefore designed according to the aforementioned four factors. Each item is constructed based on the items presented in relevant previous studies; overlapping items are excluded. Table 3 summarizes the items of the satisfaction questionnaire used in this study along with the Likert scale and sources of each item. As listed in Table 3, the satisfaction questionnaire consists of 28 items, all of which are measured on a sevenpoint Likert scale (mostly 1 = strongly disagree and 7 = strongly agree).

• Hypothesis (1): A virtual environment is an adequate representation of the physical environment of windowed spaces. • Hypothesis (1a): A sufficient sense of presence is expected in the • •

virtual environment that shows a sense of presence score (i.e., p’ score in Fig. 2) above a value, which is equivalent to the moderate level (i.e., 3) on a seven-point Likert scale ranging from 0 to 6. Hypothesis (1b): There is no significant difference in occupant satisfaction with window size between physical and virtual environments (i.e., a ≈ a’ in Fig. 2). Hypothesis (2): There is a significant difference in occupant satisfaction with different WWRs (i.e., x’ ≠ y’ in Fig. 2).

• Sense of visual comfort (SVC): Sense of visual comfort represents the

2.2. Step 2: Experimental variable setting 2.2.1. Step 2.1: Measuring sense of presence using presence questionnaire This study measures and evaluates the sense of presence in a virtual environment using the presence questionnaire in Experiment (1). To construct this questionnaire, the items from Igroup Presence Questionnaire (IPQ), which has been widely used by researchers from diverse fields and verified for its effectiveness in measuring the sense of presence in the virtual environment, are used [30–34]. The IPQ was developed by Schubert et al. [35] using a factor analysis based on the questionnaire from previously published studies, the author's previous studies, and newly developed questions. The latest version of the IPQ contains a total of four presence factors (one general factor and three sub-factors): (i) general presence (G); (ii) spatial presence (SP); (iii) involvement (INV); (iv) experienced realism (REAL) [36]. Table 1 summarizes the items of the presence questionnaire used in this study along with the Likert scale and sources of each item. As listed in Table 1, the presence questionnaire consists of 14 items, all of which are measured on a seven-point Likert scale (mostly 0 = fully disagree and 6 = fully agree).

• • •

5

degree of visual comfort perceived by occupants in a built environment, not the visual comfort itself which generally refers to an actual measurement of light intensity, such as illuminance and brightness. This factor includes six items that indicate the satisfaction towards visual perception (i.e., SVC1 to SVC6) and the other six items that indicate satisfaction towards visual fatigue (i.e., SVC7 to SVC12). Sense of privacy (SPV): Sense of privacy represents the degree of anxiety or comfort that occupants feel in a built environment resulting from the isolation or disconnection from the external environment. Sense of inner space (SIS): Sense of inner space represents the degree of emotion or spaciousness that occupants feel towards the indoor space [4]. Sense of openness (SOP): Sense of openness represents the degree of emotion or friendliness that occupants feel in a built environment resulting from the connection with the external environment [4].

Item No.

SVC1 SVC2 SVC3 SVC4 SVC5 SVC6 SVC7 SVC8 SVC9 SVC10 SVC11 SVC12

SPV1 SPV2 SPV3 SPV4

SIS1 SIS2 SIS3 SIS4 SIS5 SIS6

SOP1 SOP2 SOP3 SOP4 SOP5 SOP6

Factors

Sense of visual comfort

Sense of privacy

Sense of inner space

Sense of openness

Table 3 Items of satisfaction questionnaire.

6

I I I I I I

feel feel feel feel feel feel

that this space is (narrow/wide). that this space has (a dark ambience/a bright ambience). that this space is (tight/loose). that this space is (closed/open). that this space is (uncomfortable/comfortable). the openness of this space is (unsatisfactory/satisfactory).

This space (room or interior) is pleasant. Motivation is good because of this space (room or interior). This space (room or interior) feels large or small. This space (room or interior) is distracting. This space (room or interior) tires the mind and body. I am satisfied with this space (room or interior).

I think people are going to be looking in from the outside. It gives an isolated feeling. It feels like my own space. In looking out of the window, I feel (anxious/comfortable).

Are you satisfied with the current illumination? Are you satisfied with the color temperature of light? Do you feel visual comfort in this space? Are you satisfied with the current light source? Did you sense direct glare from a light fixture? Did you sense glare from the wall, floor, or desktop? Is the lighting space bright enough for you? Is the text clearly visible? Do you feel fatigue in your eyes? Are you stressed by reflected light? Did the lighting condition make you visually uncomfortable? Do you think your concentration has weakened?

Items disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly

agree agree agree agree agree agree agree agree agree agree agree agree

1 = very 1 = very 1 = very 1 = very 1 = very 1 = very

disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly disagree/7 = strongly

agree agree agree agree agree agree narrow/7 = very wide dark ambience/7 = very bright ambience tight/7 = very loose closed/7 = very open uncomfortable/7 = very comfortable unsatisfactory/7 = very satisfactory

1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly

1 = strongly disagree/7 = strongly agree 1 = strongly disagree/7 = strongly agree 1 = strongly disagree/7 = strongly agree 1 = very anxious/7 = very comfortable

1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly 1 = strongly

Seven-point Likert scale

Farley Farley Farley Farley Farley Farley

Farley Farley Farley Farley Farley Farley

Farley Farley Farley Farley

and and and and and and

and and and and and and

and and and and

Veitch Veitch Veitch Veitch Veitch Veitch

Veitch Veitch Veitch Veitch Veitch Veitch

Veitch Veitch Veitch Veitch

[4], [4], [4], [4], [4], [4],

[4], [4], [4], [4], [4], [4],

et et et et et et

al. al. al. al. al. al.

al. al. al. al.

[41] [41] [41] [41]

Kim Kim Kim Kim Kim Kim

et et et et et et

al. al. al. al. al. al.

[5], [5], [5], [5], [5], [5],

Koizumi Koizumi Koizumi Koizumi Koizumi Koizumi

et et et et et et

al. al. al. al. al. al.

[45] [45] [45] [45] [45] [45]

Stone [19] Stone [19] Houser et al. [43], Stone [19] Stone [19] Stone [19] Houser et al. [43], Stone [19]

et et et et

[44] [44] [44] [44] [44] [44]

Yildirim Yildirim Yildirim Yildirim

Kim Kim Kim Kim Kim Kim

[4], [4], [4], [4],

Houser et al. [43], Houser et al. [43], Houser et al. [43], Houser et al. [43], Houser et al. [43], Houser et al. [43], Kim et al. [44] Kim et al. [44] Kim et al. [44] Kim et al. [44] Kim et al. [44] Kim et al. [44]

Item Sources

T. Hong, et al.

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Fig. 4. 3D modeling procedure using SketchUp and 3ds Max.

2.3. Step 3: Virtual reality modeling

colors of the building façade are already set in SketchUp, the material properties, such as speculus, roughness, opacity, and metallic are determined based on the actual materials of the buildings using Blueprints (i.e., the visual scripting system with node-based interface in Unreal Engine). To create the light and shadows based on the actual position of the sun, the altitude and azimuth data of the sun (provided by the sun altitude and azimuth calculation tool from Korea Astronomy and Space Science Institute) during the experiment period are averaged and used as the altitude and azimuth of the directional light in Unreal Engine [46]. To represent the building surroundings (such as mountains and trees) realistically, tree objects from Autodesk 3ds Max Asset Library are exported to Unreal Engine. Fig. 5 shows the aforementioned VR modeling procedure using Unreal Engine to create a more realistic virtual environment. Second, as mentioned in Step 3.1, when the indoor space is modeled in SketchUp and exported to Unreal Engine, the VR player cannot access the indoor space, which makes the VR experience impossible. To resolve this, the static meshes in Unreal Engine (i.e., the basic unit of geometry consisting of multiple polygons used in Unreal Engine) are employed to perform the 3D and VR modeling of the office space. By considering the number of floors and the height of the actual office space in “Y” University, the virtual office space is created 57 m from the ground. The window frames, blinds, and furniture, including desks in the office space, are modeled in SketchUp and exported to Unreal Engine. To express the materials of the exported furniture more realistically, the texture and properties of the material (e.g., the speculus of desks, roughness of wood, metallicness of frames, and opacity of windows) are set according to the actual materials of the furniture. The number, location, radius, length, and intensity of light sources in the indoor space are determined based on the actual lighting equipment and its level of illuminance. Fig. 6 compares the physical office space and the virtual office space used in the experiments: the physical office space shown in Fig. 6(a) is an actual physical built environment located in “Y” University, whereas the virtual office space shown in Fig. 6(b) is a created virtual built environment in Unreal Engine. Third, for Experiment (2), the virtual office spaces are created based on the four variations of WWR (i.e., 15%, 30%, 45%, and 60%). In changing the WWRs of the virtual office space in Unreal Engine, the height-to-width ratio of the window is maintained to be identical to that of the physical office space (i.e., height:width = 3:7). Wood materials

To perform the experiment in a virtual environment based on different WWRs, the virtual office space in “Y” University and the view outside its window are created using three modeling programs: SketchUp, 3ds Max, and Unreal engine. 2.3.1. Step 3.1: 3D modeling using SketchUp and 3ds Max To create the virtual office space in “Y” University and the view outside its window, SketchUp and 3ds Max are used to perform the 3D modeling of the view outside the window that consists of nine buildings. First, based on the actual view from the office space in “Y” University, 3D modeling is conducted using SketchUp. The information required for 3D modeling (e.g., size and location of the nine buildings that can be observed outside the window) is collected from the actual measurement provided by Google Earth. Meanwhile, the VR player in Unreal Engine cannot enter the indoor space when the space is modeled with SketchUp and thereafter exported to Unreal Engine. To solve this problem, the indoor office space in “Y” University is modeled using the static mesh in Unreal Engine; further details are discussed in Step 3.2. Second, the 3D model of the nine buildings from SketchUp is revised using 3ds Max for VR modeling. If the 3D model is composed of polygons with front faces facing inward instead of facing outward, then Unreal Engine cannot recognize such polygons. Accordingly, the 3D modeling file in SketchUp is exported to 3ds Max to check whether the front faces of polygons in the 3D model are all facing outward. If they are not, then the front faces should be reversed to face outward. Apart from this, the number of polygons used in the 3D model is also adjusted to reduce the data size. Fig. 4 shows the aforementioned 3D modeling procedure using SketchUp and 3ds Max, where the 3D model is shown to be ready for export to Unreal Engine. 2.3.2. Step 3.2: Virtual reality modeling using Unreal Engine To convert the 3D model created in SketchUp and 3ds Max into a virtual environment, Unreal Engine is employed to finalize the 3D modeling for real-time rendering. First, the location, materials, light, shadow, and surroundings of the 3D model are set in Unreal Engine to make the view outside the window more realistic. The latitude and longitude (37°33′39.77″N, 126°56′10.26″E, respectively) are determined based on the actual location of the buildings. As the overall

Fig. 5. VR modeling procedure using Unreal Engine. 7

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Fig. 6. Actual physical office space and created virtual office space for the experiment.

Fig. 7. Four virtual office spaces with different WWRs for Experiment (2).

that are the same as those of the existing interior wall are used for parts that are not windows. The other parts are constructed the same as the physical office space. Fig. 7 shows the four virtual office spaces in Unreal Engine with different WWRs.

the actual experiment, a pilot study is conducted with 10 pre-participants to ensure that the experimental details are properly designed and experimental results are reliable. Based on this pilot study, the size, material, and lighting of the virtual environment are complemented to enhance the sense of presence; moreover, the items from the questionnaire that the participants found difficult to understand are revised. To ensure the statistical power of the experimental results of this study, a total of 50 participants (male: 29; female: 21) are recruited based on the number of participants from similar previous experimental studies with a crossover study design (i.e., at least 30 participants)

2.4. Step 4: Experimental procedure To test Hypotheses (1) and (2), Experiments (1) and (2) are performed in the virtual environment created in Step 3 based on the experimental design and variables established in Steps 1 and 2. Prior to

Fig. 8. Procedure of experiment (1). 8

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Fig. 9. Procedure of experiment (2).

asked to assume that the experimental space is their own office space and perceive the sense of openness, closeness, comfort, and anxiety in that space. Secondly, they are asked to familiarize themselves with the experimental space freely. To minimize the influence of the first exposure, a 3-min rest (i.e., “Washout” in Fig. 8) is afforded between the two exposures. Once the exposure to the two experimental conditions and the satisfaction questionnaire survey are completed, the participants accomplish the presence questionnaire survey to measure the sense of presence in the virtual environment.

[27,47–52]. The participants are recruited through postings on the “Y” University community website and flyers posted on campus; all participants voluntarily participated in the experiment. The personal details obtained from recruited participants include the following: (i) age: from 21 to 34 (mean (M) = 25.1, standard deviation (SD) = 2.73); (ii) major: engineering majors including architecture (20% of the participants) and non-engineering majors including management, economics, psychology, and language (80% of the participants); (iii) VR experience: experienced participants (64% of the participants) and non-experienced participants (36% of the participants). Prior to the experiment, the participants are provided an overall introduction to the experimental procedure as well as explanations on the side-effects of VR hardware (e.g., dizziness, motion sickness or heating from the device) and other matters of which to be aware of. The participants are thereafter advised to read and sign a participation agreement. To ensure that the eyesight and color-blindness of all participants would not cause any problem with their VR experience, these are tested using LogMAR chart [53] for visual acuity and Ishihara test [54] for color perception. The experiment was conducted with recruited participants for one month in January 2019, between 11 a.m. and 4 p.m., during which the daylight conditions were similar; the experiment was not performed when the outside view was not visible because of rain or fog. The detailed experimental designs of Experiments (1) and (2) are described in 2.4.1 and 2.4.2, respectively.

2.4.2. Step 4.2: Procedure of Experiment (2) To compare the occupant responses to different window sizes in the virtual environment, Experiment (2) is conducted according to the following procedure (Fig. 9); it is performed after the same paricipants complete Experiment (1). Prior to the experiment, the device setup is conducted similar to that in Experiment (1). At this stage, the map file built according to different WWRs is prepared in Unreal Engine. After the completion of the device setup, the experiment can begin. In the experiment, the participants are randomly assigned to one of the four experimental conditions (i.e., Exposures 1 to 4 in Fig. 9): (i) virtual environment with a WWR of 15%; (ii) virtual environment with a WWR of 30%; (iii) virtual environment with a WWR of 45%; (iv) virtual environment with a WWR of 60%. Similar to Experiment (1), the participants are exposed to each experimental condition for 5 min, and after the completion of this experience, they are given 8 min to complete the satisfaction questionnaire survey; the participants are given the same instructions as those in Experiment (1). Between two exposures, the participants are given a 3-min rest (i.e., “Washout” in Fig. 9) similar to that in Experiment (1). During each break, the experimenter prepares the map file of the virtual environment with a different WWR in the computer. Once the exposure to the four experimental conditions and the satisfaction questionnaire survey are completed, all the procedures of Experiments (1) and (2) are accomplished.

2.4.1. Step 4.1: Procedure of Experiment (1) To compare the occupant responses to window size between the physical and virtual environments, Experiment (1) is conducted according to the following procedure (Fig. 8). Prior to the experiment, the device is set up and a baseline survey is conducted. The device setup is a preparatory step for the VR experience; it requires installing the base station sensors and connecting the VR headset (i.e., HTC VIVE) to a computer. In the baseline survey, the participants are requested to provide personal details, such as gender, age, major, health condition of the day, and any previous VR experience. Once the device setup and baseline survey are completed, the main experiment can start. In the experiment, the participants are randomly assigned to one of two experimental conditions (i.e., Exposures 1 and 2 in Fig. 8): (i) a physical environment with a WWR of 60% and (ii) a virtual environment with a WWR of 60%. The participants are exposed to each experimental condition for 5 min; thereafter, they are requested to fill-out the satisfaction questionnaire survey for 8 min. The following instructions are provided during the experiment and satisfaction questionnaire survey under each experimental condition. Firstly, the participants are

2.5. Step 5: Comparative analysis of experimental results 2.5.1. Step 5.1: Comparative analysis of occupant responses to window size between physical and virtual environments To determine whether the virtual environment is an adequate representation of the physical environment of windowed office spaces (i.e., Hypothesis (1)), the two questionnaire survey results of Experiment (1) are analyzed. First, the analysis of the presence questionnaire survey results allows the evaluation of the sense of presence of 9

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Table 4 Comparison of IPQ scores of four presence factors. Classification

Authors

Country

Year

IPQ score G

SP

INV

REAL

This study

Lee et al.

South Korea

2019

4.98 (1.02)

4.58 (1.46)

4.35 (1.55)

3.59 (1.57)

Previous studies

Kern and Ellermeier [30] Bessa et al. [31] Shiban et al. [34] Kinateder et al. [55] Alsina-Jurnet et al. [33]

Germany Portugal Germany Germany Spain

2018 2017 2016 2015 2010

- (−) 3.30 (−) 3.14 (1.01) 4.14 (1.24) 4.68 (0.78)

3.33 1.43 3.49 4.08 4.14

3.26 1.00 3.04 4.15 3.78

2.39 0.91 2.36 3.39 3.29

(0.48) (−) (1.56) (0.80) (0.71)

(0.75) (−) (1.09) (1.03) (1.08)

(1.18) (−) (1.46) (0.86) (1.65)

Note: G is general presence; SP is spatial presence; INV is involvement; REAL is experienced realism; values indicate mean and standard deviation (in parentheses).

occupants in the virtual environment (i.e., Hypothesis (1a)). The higher the scores, the more sufficient the sense of presence the virtual environment created in this study can provide. Second, the statistical analysis of the satisfaction questionnaire survey results using paired sample t-test makes it possible to determine whether occupants express similar satisfaction with window size in the physical and virtual environments (i.e., Hypothesis (1b)). If the paired sample t-test does not exhibit a significant difference in the satisfaction questionnaire survey results between the physical and virtual environments, then it can be stated that the occupant's levels of satisfaction with window size in the physical and virtual environments do not differ.

environment, the satisfaction questionnaire survey results of Experiment (2) are analyzed (i.e., Hypothesis (2)). The statistical analysis of results using repeated measures ANOVA makes it possible to determine whether the occupant satisfaction by different WWRs has a statistical difference. If the repeated measures ANOVA exhibits a significant difference, then it is presumed that occupant satisfaction would change according to the WWRs. 3. Results and discussion 3.1. Comparative analysis of occupant responses to window size between physical and virtual environments

2.5.2. Step 5.2: Comparative analysis of occupant responses to different window sizes in virtual environment To determine whether occupant satisfaction varies depending on different WWRs (i.e., 15%, 30%, 45%, and 60%) in the virtual

3.1.1. Analysis of presence questionnaire survey results of virtual environment To evaluate the sense of presence of the 50 participants in the

Table 5 Results of paired sample t-test of occupant satisfaction in the physical and virtual environments. Items

Paired Differences Mean

Std. Deviation

Std. Error Mean

t

df

Sig. (2-tailed)

95% Confidence Interval of the Difference Lower

Upper

SVC1 SVC2 SVC3 SVC4 SVC5 SVC6 SVC7 SVC8 SVC9 SVC10 SVC11 SVC12

−0.140 −0.240 −0.180 0.120 0.000 0.600 0.380 −1.060 0.940 0.660 0.160 −0.260

1.512 1.745 2.173 1.769 1.653 1.702 1.589 1.659 1.942 1.465 2.368 2.798

0.214 0.247 0.307 0.250 0.234 0.241 0.225 0.235 0.275 0.207 0.335 0.396

−0.570 −0.736 −0.798 −0.383 −0.470 0.116 −0.072 −1.531 0.388 0.244 −0.513 −1.055

0.290 0.256 0.438 0.623 0.470 1.084 0.832 −0.589 1.492 1.076 0.833 0.535

−0.655 −0.973 −0.586 0.480 0.000 2.492 1.691 −4.519 3.422 3.185 0.478 −0.657

49 49 49 49 49 49 49 49 49 49 49 49

0.516 0.335 0.561 0.634 1.000 0.016* 0.097 0.000*** 0.001*** 0.003** 0.635 0.514

SPV1 SPV2 SPV3 SPV4

0.140 0.280 −0.060 0.260

1.690 2.433 1.900 1.700

0.239 0.344 0.269 0.240

−0.340 −0.411 −0.600 −0.223

0.620 0.971 0.480 0.743

0.586 0.814 −0.223 1.081

49 49 49 49

0.561 0.420 0.824 0.285

SIS1 SIS2 SIS3 SIS4 SIS5 SIS6

0.300 0.280 0.320 0.120 0.580 0.200

1.843 1.807 1.236 1.674 2.031 1.852

0.261 0.256 0.175 0.237 0.287 0.262

−0.224 −0.234 −0.031 −0.356 0.003 −0.326

0.824 0.794 0.671 0.596 1.157 0.726

1.151 1.095 1.830 0.507 2.019 0.764

49 49 49 49 49 49

0.255 0.279 0.073 0.614 0.049* 0.449

SOP1 SOP2 SOP3 SOP4 SOP5 SOP6

0.540 0.420 0.020 0.220 −0.100 0.080

1.312 1.401 1.464 1.461 1.568 1.455

0.186 0.198 0.207 0.207 0.222 0.206

0.167 0.022 −0.396 −0.195 −0.546 −0.333

0.913 0.818 0.436 0.635 0.346 0.493

2.909 2.120 0.097 1.065 −0.451 0.389

49 49 49 49 49 49

0.005** 0.039* 0.923 0.292 0.654 0.699

Note: * indicates significance level (*p < 0.05, **p < 0.01, ***p < 0.001). 10

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virtual environment, the presence questionnaire survey results of Experiment (1) on four presence factors are analyzed. Table 4 summarizes the comparison of the mean and standard deviation of the IPQ scores from the presence questionnaire survey results of Experiment (1) with those from other previous studies that evaluated the sense of presence in a virtual environment using IPQ. The results show that the mean IPQ scores (i.e., G: 4.98, SP: 4.58, INV: 4.35, and REAL: 3.59) of all the four factors in this study are higher not only than the value equivalent to the moderate level (i.e., 3) on a seven-point Likert scale ranging from 0 to 6 but also than the mean IPQ scores from all the previous studies; these indicate a relatively higher sense of presence. The mean IPQ score of general presence, which represents the overall sense of presence, is 4.98; it is the highest among the mean IPQ scores of the four factors. The mean IPQ score of spatial presence, which represents the sense of presence in a physical space, is 4.58; it is similar to that of general presence. The mean IPQ score of experienced realism, which represents the sense of reality, is 3.59; it is the lowest among the mean IPQ scores of the four factors. In summary, the analysis shows that the mean IPQ scores are higher for factors that are related to the sense of presence (i.e., G and SP) than those related to reality (i.e., INV and REAL) in the virtual environment created and used in this study; the scores generally tend to decrease from G to SP, INV, and REAL. The IPQ scores in this study and those in previous studies exhibit this similar tendency because the question items with a more stringent standard in evaluating higher levels of presence and realism are assigned to factors related to reality. Overall, it is determined that the virtual environment created in this study offers a sufficient sense of presence to participants for the conduct of experiments on windowed spaces (i.e., Hypothesis (1a) confirmed in all the four presence factors).

Table 7 Tests of within-subjects effects. Factors

Type III Sum of Squares

df

Mean Square

F

Sig.

Sense of visual comfort Sense of privacy Sense of inner space Sense of openness

5.130

3

1.710

5.944

0.001***

2.937 38.710 135.828

3 3 3

0.979 12.903 45.276

1.692 17.064 41.587

0.171 0.000*** 0.000***

Note: * indicates significance level (*p < 0.05, **p < 0.01, ***p < 0.001).

satisfaction regarding visual fatigue. This significant difference can be explained by the visual fatigue from the screen on the VR headset and not from the lighting or the window; it has resulted in a lower occupant satisfaction in the virtual environment (SVC9: M = 3.56, SD = 1.61; SVC10: M = 2.7, SD = 1.25) than those in the physical environment (SVC9: M = 2.62, SD = 1.35; SVC10: M = 2.04, SD = 0.96). It is evident that two items, which are closely related to visual fatigue (i.e., SVC9 and SVC10), cannot accurately reflect the intention of the questionnaire and are therefore excluded from the statistical analysis of Experiment (2). For SVC8 (i.e., “Is the text clearly visible?”), the difference in occupant satisfaction can be explained by the difference between the resolution of the VR headset (i.e., HTC VIVE) and that of the actual monitor. The occupant satisfaction in the virtual environment (M = 5.16, SD = 1.49) is lower than that of the physical environment (M = 6.1, SD = 0.93) because of the lower resolution of HTC VIVE (i.e., 2160 × 1200) compared to that of the actual monitor (i.e., 3840 × 2160). As a result, the text can appear to be less clear in the virtual environment; accordingly, this item is excluded from the statistical analysis of Experiment (2). Meanwhile, in the case of SVC6 (i.e., “Did you sense glare from the wall, floor, or desktop?”), although the virtual environment appears to be realistic, it is difficult to represent exactly the same materials of the actual wall, floor, or desktop; therefore, these are also excluded from the statistical analysis of Experiment (2). Second, the item that has shown a significant difference in the sense of inner space between the physical and virtual environments is SIS5 (i.e., “How the space makes the mind and body tired”). Similar to SVC9 and SVC10, it can be deduced that most participants feel physical fatigue as they wear the VR headset and look at the screen; therefore, this item is excluded from the statistical analysis of Experiment (2). Third, the items that have shown a significant difference in the sense of openness between the physical and virtual environments are SOP1 and SOP2. The difference in the occupant satisfaction in SOP1 (i.e., “I feel that this space is very narrow or very wide”) between the physical and virtual environments can be explained by the difference between the field of view (FOV) of HTC VIVE and that of humans. The FOV of HTC VIVE (i.e., 110°) is narrower compared to that of humans (i.e., 180°); because the objects that enter into the FOV in the real world may possibly not enter into the FOV of HTC VIVE, the width of the object is perceived to be wider than it actually is. As a result, the occupant satisfaction in the virtual environment (M = 5.22, SD = 1.25) is higher than that in the physical environment (M = 4.74, SD = 0.96); therefore, this item is excluded from the statistical analysis of

3.1.2. Statistical analysis of satisfaction questionnaire survey results using paired sample t-test To identify the statistical similarity of occupant satisfaction with window size between the physical and virtual environments, the paired sample t-test is conducted for the satisfaction questionnaire survey results of 50 participants in Experiment (1). Table 5 summarizes the results of the paired sample t-test for all the 28 items of the satisfaction questionnaire surveys in the physical and virtual environments. As a result, 21 of the total 28 items (i.e., 75%) show no significant difference in occupant satisfaction with window size between the physical and virtual environments, with p-values above 0.05 (t, p > 0.05); this aspect of occupant satisfaction in the physical and virtual environments can be regarded as the same in the majority of items. Thus, the virtual environment can be considered an appropriate representation of the physical environment of windowed spaces (i.e., Hypothesis (1b) confirmed in 21 items). The conduct of a questionnaire survey in the virtual environment can lead to distorted results in seven items that exhibit a significant difference in the occupant satisfaction with window size between the physical and virtual environments at the 0.05 level. These seven items are therefore excluded from the statistical analysis of the satisfaction questionnaire survey results of Experiment (2). First, there is a significant difference in the sense of visual comfort between the physical and virtual environments in items SVC6, SVC8, SVC9, and SVC10; most of the items, i.e., from SVC8 to SVC10, pertain to the occupant Table 6 Mauchly's test of sphericity. Within Subjects Effect

Sense Sense Sense Sense

of of of of

visual comfort privacy inner space openness

Mauchly's W

0.885 0.858 0.877 0.959

Approximate Chi-Square

5.822 7.310 6.240 1.986

df

5 5 5 5

11

Sig.

0.324 0.199 0.284 0.851

Epsilon Greenhouse-Geisser

Huynh-Feldt

Lower-bound

0.922 0.905 0.919 0.973

0.983 0.963 0.979 1.000

0.333 0.333 0.333 0.333

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Table 8 Pairwise comparisons of senses of visual comfort, inner space, and openness. Factor

Sense of visual comfort

(I) WWR

15% 30% 45% 60%

Sense of inner space

15% 30% 45% 60%

Sense of openness

15% 30% 45% 60%

(J) WWR

Mean Difference (I-J)

Std. Error

Sig.b

95% Confidence Interval for Differenceb Lower Bound

Upper Bound

30% 45% 60% 15% 45% 60% 15% 30% 60% 15% 30% 45%

−0.185 −0.351** −0.413** 0.185 −0.166 −0.228 0.351** 0.166 −0.062 0.413** 0.228 0.062

0.103 0.102 0.123 0.103 0.101 0.097 0.102 0.101 0.116 0.123 0.097 0.116

0.464 0.007 0.009 0.464 0.643 0.137 0.007 0.643 1.000 0.009 0.137 1.000

−0.467 −0.631 −0.750 −0.097 −0.443 −0.494 0.071 −0.112 −0.382 0.075 −0.039 −0.258

0.097 −0.071 −0.075 0.467 0.112 0.039 0.631 0.443 0.258 0.750 0.494 0.382

30% 45% 60% 15% 45% 60% 15% 30% 60% 15% 30% 45%

−0.839*** −0.784*** −1.208*** 0.839*** 0.055 −0.369 0.784*** −0.055 −0.424 1.208*** 0.369 0.424

0.201 0.165 0.165 0.201 0.184 0.156 0.165 0.184 0.168 0.165 0.156 0.168

0.001 0.000 0.000 0.001 1.000 0.133 0.000 1.000 0.088 0.000 0.133 0.088

−1.392 −1.238 −1.662 0.286 −0.452 −0.799 0.330 −0.562 −0.885 0.754 −0.061 −0.037

−0.286 −0.33 −0.754 1.392 0.562 0.061 1.238 0.452 0.037 1.662 0.799 0.885

30% 45% 60% 15% 45% 60% 15% 30% 60% 15% 30% 45%

−1.335*** −1.392*** −2.312*** 1.335*** −0.057 −0.977*** 1.392*** 0.057 −0.920*** −1.335*** −1.392*** −2.312***

0.219 0.206 0.199 0.219 0.226 0.195 0.206 0.226 0.204 0.219 0.206 0.199

0.000 0.000 0.000 0.000 1.000 0.000 0.000 1.000 0.000 0.000 0.000 0.000

−1.938 −1.959 −2.859 0.732 −0.679 −1.514 0.825 −0.565 −1.481 −1.938 −1.959 −2.859

−0.732 −0.825 −1.764 1.938 0.565 −0.439 1.959 0.679 −0.359 −0.732 −0.825 −1.764

Note: Based on estimated marginal means, * indicates significance level (*p < 0.05, **p < 0.01, ***p < 0.001). b Indicates adjustment for multiple comparisons: Bonferroni.

Fig. 10. Boxplot of sense of visual comfort according to different WWRs.

12

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Fig. 11. Boxplot for sense of inner space according to different WWRs.

the smallest WWR (i.e., a WWR of 15%) is 4.42, which exceeds the value equivalent to the moderate level (i.e., 4) on a seven-point Likert scale ranging from 1 to 7; this shows that it is generally satisfactory with all WWRs. Overall, the participants tend to perceive less visual comfort when the WWR is 15% than when the WWRs are 45% and 60%; whereas if the WWR exceeds 30%, then it is determined that the increase in the WWR would not greatly affect the participants’ sense of visual comfort. Second, the sense of inner space with a WWR of 15% (M = 3.66, SD = 0.89) exhibits a significant difference from that with WWRs of 30% (M = 4.25, SD = 0.79), 45% (M = 4.26, SD = 0.84), and 60% (M = 4.53, SD = 0.69) (Table 8). Although the sense of inner space between WWRs of 30%, 45%, and 60% does not show a significant difference, the sense of inner space tends to increase as the WWR increases (Fig. 11). That is, when the WWR is 15%, the participants show a statistically lower sense of inner space than those with larger WWRs; when the WWR exceeds 30%, such an increase does not lead to a significant difference in the sense of inner space. Meanwhile, the average of the sense of inner space with a WWR of 15% (i.e., 3.66) does not exceed the value equivalent to the moderate level (i.e., 4); it is the only unsatisfactory response among the four variations of the WWR. Thus, the participants tend to perceive the inner space as smaller or feel dissatisfied with the space when the WWR is 15%. When the WWR is over 30%, they are generally satisfied with the inner space; any further increase in the WWR beyond 30%, however, would not cause a statistically significant effect on the participants’ sense of inner space. Third, there is a significant difference in the sense of openness between a WWR of 15% (M = 2.68, SD = 1.28), WWRs of 30% (M = 4.02, SD = 1.19) and 45% (M = 4.08, SD = 1.38), and a WWR of 60% (M = 5.00, SD = 1.07) (Table 8). The sense of openness only between WWRs of 30% and 45% does not show a significant difference because the views outside the windows do not considerably differ; the buildings and their number observed from the windows do not vary. Compared with other factors, the participants’ sense of openness is more affected by various visual abilities, such as FOV and depth perception (i.e., the ability to perceive an object in three dimensions and the distance between two points in space). The sense of openness is therefore shown to increase significantly as the WWR increases (except for the increase from 30% to 45%), unlike the senses of visual comfort and inner space, which are not significantly affected by the increase in WWR over 30% (Fig. 12).

Experiment (2). 3.2. Comparative analysis of occupant responses to different window-towall ratios in virtual environment 3.2.1. Statistical analysis of satisfaction questionnaire survey results using repeated measures analysis of variance (ANOVA) To identify the statistical difference in the occupant satisfaction with different WWRs in the virtual environment, the repeated measures ANOVA is conducted for the satisfaction questionnaire survey results of 50 participants in Experiment (2) regarding four satisfaction factors. Repeated measures ANOVA assumes sphericity; hence, it is tested using Mauchly's sphericity test. As shown in Table 6, the assumption of sphericity is not violated by any of the four factors, with a p-value above 0.05 (Mauchly's W, p > 0.05) [56]. Thus, the study analyzed the results of repeated measures ANOVA without correcting the degrees of freedom (df). Table 7 summarizes the results of repeated measures ANOVA for the four factors of the satisfaction questionnaire surveys in virtual environments with four different WWRs. As shown in Table 7, three factors (i.e., sense of visual comfort, sense of inner space, and sense of openness) show a significant difference in occupant satisfaction with different WWRs, at the 0.001 level (ANOVA, p < 0.001), whereas the sense of privacy factor with a p-value of 0.171 exhibits no significant difference. Except for the sense of privacy, therefore, the occupant satisfaction with different WWRs was statistically differs, indicating that there exists a difference in occupant satisfaction by window sizes (i.e., Hypothesis (2) confirmed in the three satisfaction factors). A post-hoc test is performed using the Bonferroni correction for the three factors in which the difference in the occupant satisfaction with different WWRs is significant. First, the sense of visual comfort with a WWR of 15% (M = 4.42, SD = 0.81) shows a significant difference from those with WWRs of 45% (M = 4.77, SD = 0.80) and 60% (M = 4.83, SD = 0.72); however, that with a WWR of 30% (M = 4.61, SD = 0.65) is not significantly different from those with other WWRs (Table 8). Although the difference in the sense of visual comfort between the WWRs of 30%, 45%, and 60% is not statistically significant, the sense of visual comfort tends to increase as the WWR increase. The degree of increase, however, gradually declines with the increase in the WWR (Fig. 10). Nevertheless, the average sense of visual comfort with 13

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Fig. 12. Boxplot of sense of openness according to different WWRs.

In summary, the post-hoc test results show that the increase in the WWR leads to an increase in occupant satisfaction. In particular, in all the three factors, the participants exhibit a significantly lower occupant satisfaction with a WWR of 15% than with larger WWRs. Meanwhile, when the WWR exceeds 30%, the increase in the WWR does not cause any statistically significant changes in occupant satisfaction in most of the factors. This is because the actual and perceived differences in window areas between WWRs of 15% and 30% are relatively larger than those among other WWRs (i.e., actual and perceived differences in window areas between WWRs of (i) 30% and 45% or (ii) 45% and 60%). It is only in the sense of openness that the occupant satisfaction with a WWR of 60% exhibits a significant difference from all the other WWRs; this indicates that the sense of openness is the factor that is influenced the most by different WWRs.

Although the sense of privacy does not show any significant difference in occupant satisfaction with different WWRs, it tends to decrease with the increase in WWR (Fig. 13). This is because as the WWR increases, the participants are more probable to be exposed to the external environment that can in consequently increase the possibility to feel insecure; this decreasing tendency in the sense of privacy is highest when the WWR is increased from 30% (M = 5.01, SD = 0.72) to 45% (M = 4.80, SD = 0.82). In contrast, there is practically no change in the sense of privacy (i.e., a slight increase of 0.06) when the WWR is increased from 45% to 60%. This can be explained by the aforementioned actual and perceived difference in window areas; this difference in window areas between WWRs of 15% and 30% (or 30% and 45%) is relatively larger than that between WWRs of 45% and 60%. Despite these changes in the sense of privacy, the differences are not

Fig. 13. Boxplot of sense of privacy according to different WWRs. 14

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statistically significant; this implies that the increase in WWR does not highly impact the participants’ sense of privacy. The average value of the sense of privacy in all four variations of WWR exceeds the value equivalent to the moderate level (i.e., 4), indicating that the sense of privacy is generally satisfactory in all WWRs. This is because the buildings outside the window of the experimental case (i.e., an office space in “Y” University) selected in this study are sufficiently distant for the participants to feel secure and private; it is difficult for them to feel that someone is looking at them from the outside regardless of the window size (Fig. 7). Thus, the sense of privacy may be more affected by the view outside the window rather than the window size.

overall satisfaction factors can be expected. On the other hand, for (ii) public or common working areas in office spaces that do not necessarily require a certain level of occupant satisfaction with the sense of privacy, WWRs of 45% and 60% are determined to yield the suitable window sizes; with these WWRs, a relatively high level of occupant satisfaction with the senses of visual comfort, inner space, and openness can be expected. In particular, for (iii) resting, service, or meeting areas in office spaces that require higher occupant satisfaction with the sense of openness, a WWR of 60% affords the optimal window size. This study is novel and contributes to originality in terms of the following: (i) it proposes a method for non-specialists to easily and conveniently create a more realistic virtual environment using SketchUp (an easy-to-use 3D modeling tool) and Unreal Engine (a source-available software for non-commercial use); (ii) not only are the experiments conducted solely in a virtual environment according to different window sizes, but the validity of the virtual environment as an experimental environment is also verified; (iii) it yields highly reliable experimental results by considering only the influence of window sizes and offering an identical experimental condition for all design variables, except window sizes; (iv) it makes it possible to determine the suitable window size that could satisfy the various requirements of occupants if the occupant satisfaction with different window sizes proposed in this study is considered along with energy consumption, thermal and visual comfort, and ventilation proposed by previous studies. Despite the novelty and originality of this study, the following limitations have to be resolved in the future: (i) this study only focused on four different window sizes (i.e., WWRs of 15%, 30%, 45%, and 60%) among the several window sizes for the experiment; it did not determine the occupant satisfaction when the WWR is over 60%; (ii) apart from the occupant satisfaction, this study did not investigate other occupant responses, such as task performance which is an important ability in office spaces; (iii) apart from the satisfaction questionnaire, this study did not employ more objective methods, such as measuring the physiological responses (e.g., heart rate, blood pressure, galvanic skin response, and electroencephalography) of occupants, to evaluate the occupant satisfaction. This study is a first step towards the examination of various design variables for windowed office spaces. Further research and experiments will be conducted on the diverse responses of occupants (e.g., psychological, cognitive, physiological, and emotional) to different window sizes, shapes, and placements in a virtual environment.

4. Conclusion Two sets of experiments are performed to analyze the occupant responses on satisfaction with different window sizes: (i) Experiment (1): comparison of occupant responses on the sense of presence and satisfaction with window size between physical and virtual environments; (ii) Experiment (2): comparison of occupant responses on satisfaction with four different WWRs (i.e., 15%, 30%, 45%, and 60%) in a virtual environment. The experimental results are compared and analyzed as follows.

• Results of Experiment (1): as indicated by responses to the majority

•

(i.e., 75%) of question items, the virtual environment of windowed space created in this study not only provides a sufficient sense of presence in windowed spaces with mean IPQ scores higher than those obtained by previous studies using VR but also shows no significant difference in occupant satisfaction with the physical environment. The virtual environment is thus shown to be a suitable representation of the physical environment for windowed spaces. Results of Experiment (2): the occupant satisfaction with the senses of visual comfort, inner space and openness shows a significant difference based on different WWRs. Overall, the rise in WWR tends to increase the aforementioned occupant satisfaction. Among the three satisfaction factors, the sense of openness is influenced the most by different WWRs; the participants exhibit a significantly highest satisfaction with the largest WWR (i.e., a WWR of 60%). The increase in occupant satisfaction with the senses of visual comfort, inner space and openness, however, does not raise the occupant satisfaction with the sense of privacy. The rise in WWR rather decreases the occupant satisfaction with the sense of privacy; however, this decrease is not statistically significant. As the occupant satisfaction in terms of different satisfaction factors may vary according to the WWR, a suitable WWR considering the use and purpose of the office space should be proposed. Based on the analysis results, this study classifies the uses of office spaces into three main purposes and accordingly proposes a suitable WWR: (i) private or personal working areas in office spaces; (ii) public or common working areas in office spaces; (iii) resting, service, or meeting areas in office spaces. In the three satisfaction factors (i.e., senses of visual comfort, inner space, and openness), the participants indicate a significantly lower occupant satisfaction with a WWR of 15% than with larger WWRs; nevertheless, the increase in the WWR does not always result in a significant difference in occupant satisfaction with WWRs over 30%. It is only in the sense of openness that the occupant satisfaction with a WWR of 60% is significantly higher than those with smaller WWRs; this indicates that compared to other factors, the sense of openness is primarily affected by different WWRs. Unlike these results, the sense of privacy shows a higher occupant satisfaction with WWRs of 15% and 30% than with larger WWRs; however, it is not statistically significant. Thus, for (i) private or personal working areas in office spaces that require a certain level of occupant satisfaction with the sense of privacy along with other factors, a WWR of 30% is identified to provide the suitable window size; with this WWR, a certain level of occupant satisfaction with

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