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In our lives, work plays a crucial role in everybody’s lives for which working environment quality needs to be upgraded as it has a great impact on employee's mental and physical health and also in well-being. In recent years it is seen that a great focus is given to workplace designs by companies to improve the productivity of a worker, especially in offices that are openly planned. Several kinds of research have been conducted on this trending topic of improving indoor workspace (Naujoks et al. 2021). Workplace design is determined using the terminology of commonplace where a flexible and agile working environment is given priority. These workplace styles up-gradation improved office utilization and maximize the floor space value that is available. Workplace design can impact both physical responses to the quality of the internal environment, and also to the psychological responses to these environmental processes.
The space which is provided in the workplace per person is known as Spatial density while the number of people present in the office at that particular time is known as Social density. The spatial density concept can be very helpful to the well-being of the individual employee (Maier et al. 2022). It is observed that too little space between employees can make individuals feel crowded and on the other hand, if the space between them increases too much then they can feel a sense of disconnectedness. This was also seen that spatial density arrangement can influence the cognitive ability of the employee and sense of personal space in the workplace. Environment control has shown that it can influence well-being and satisfaction in the workplace. This refers to the ability of the individual employee to adapt to the change in the workplace or be efficient in choosing the suitable space for doing the work. In a single occupancy room, it was observed that if the participants are given a room that has an outside view, their productivity further increased. This type of space helps in doing work with focus and without any or less distraction. Behavioral measures are common types of measures in the work environment which include the satisfaction of the employees and their feelings of the employees. The functional comfort of the notion of the employees goes beyond the concepts which are traditional of comfort based on users' response measurement. Sometimes the functional comfort concept gets linked with the aspects of employees psychologically
Method
The main objective here of SPSS analysis is to analyze the collected data which is from 138 participants here for the generation of the statistical information according to Study 2. The first task here is to collect a sample of brief descriptive statistics (Meinal et al. 2022). Then the next thing which needs to be done is to analyze using a paired t-test the collected data. After that SPSS software is opened and the nominal dataset is downloaded and an analysis of the data was performed. It contains two types of sheets first one is raw data which contains individual scores of the participants at both the levels for each particular image.
The mean score and standard deviation are covered in this datasheet. Another sheet consists of the mean of the participants removing the data of 14 participants as it was the incomplete response. The five variables are entered into the dataset. Each of the variables takes up a row under each of the name columns in the view of the data. Some of them are like age, and gender which are of four categories. It was noted by following way 1=male, 2=female, 3=non-binary, 4=prefer not to say. Then Mean Likert Score was obtained for both individual participants of OF(only feature level) and also of EF(Extra feature level). Then the descriptive statistics were created for the variable which was nominal such as gender or students. Then the variables are moved to analyze and then descriptive statistics and also the frequencies are checked.
Participants
There were a total of 138 participants and 58 of them were non-students and 14 data of the participant could not be taken as it was incomplete. A piece of detailed information about the gender identity was taken for each individual whether they are male, female, non-binary, or they do not prefer to say. The mean and standard deviation was collected according to the data.
Design
The designs are made according to the requirement of the company. However, it can be improved by keeping the focus on the space delineation so that collaboration and focus can be allowed. IT is being suggested instead of a fully open floorplan space, it is essential to think about spaces separated for groups as well as for individual works (Bedenlier et al. 2021). Facilitating group work was found to be more important than workstations separated using large spaces. Also, it is kept on the focus that workplace designs must be such that flexibility can be maintained. It is recommended that spaces that are for only one individual should have innovation and creativity by locked-in groups so that effectiveness in the workplace can be maintained.
Material
The materials which were used to do the experiments were collected from the data and put into an Excel file for future requirements. The SPSS software was used to analyze the data. The questionnaire was made about the indoor workspace and whether they think change is needed or not. Likert scale was used to record the responses given by the participants and the following question like whether the photo shown is an indoor workspace example or not. Also noted is whether the photograph reflects their expectation of the workplace. Almost 24 responses were collected from this questionnaire. 8 Photographs were chosen for the indoor workspace which includes features and extra features for every 4 levels.
T-test
The T-tests are used to analyze the data. These are two first one is an independent sample t-test and another one is of paired sample t-test. The independent sample t-test is used when it is between the design of the participants and only when they are in one particular group or in another group but cannot come together (Ivry et al. 2021). The paired samples t-test is used when the designs are within participants. In the t-test, the samples are distributed normally and make use of box or histogram plot charts for checking data. The population needs to have equal variance and no extreme scores are used. Independent sample t-tests compare the two independent data sets and are calculated using the formula of the ratio between the variance of having a condition like the difference between the number of means to the variation within it. The relation between p-values and t-test distribution and degree of freedom is determined.
Levene’s Test
These are the tests that assess whether in the different samples equality of variance exists or not. This test is very important to be assumed as for running t-test this one is an important factor, one advantage of this type of test is that they can be applied to data which are distributed not-normally.
Hypothesis testing
This type of testing is based on predictions that can be tested on the relationship that is assumed between the variables and the difference can be determined which are between groups or which are on conditions (Geng et al. 2022). A specific prediction is made using a null hypothesis and a clear image is obtained.
Age |
OF |
EF |
||
N |
Valid |
138 |
138 |
138 |
Missing |
0 |
0 |
0 |
|
Mean |
35.7681 |
4.0821 |
2.1697 |
|
Median |
34.0000 |
4.2500 |
2.0000 |
|
Mode |
25.00a |
4.00a |
1.75 |
|
Std. Deviation |
13.52602 |
.67144 |
.93776 |
|
Sum |
4936.00 |
563.33 |
299.42 |
|
a. Multiple modes exist. The smallest value is shown |
Table 1: Data and variables
Among the 138 participants, the descriptive statistics showed none of them was missing where the mean value is 35.76 for age, 34 for median and 25 for mode. Following the statistics obtained for OF and EF, it can be seen that mean and median for OF are 4.08 and 4.25 and for EF are 2.167 and 2 respectively. The detrended P-plot for gender shows the parameters to be 0 hence no link is obtained between normal and cumulative. For The paired sample test pair 1 is composed of age and OF, pair 2 is composed of age and EF and age and pair 3 is composed of age and gender and the obtained values can be seen in table 2.
Mean |
N |
Std. deviation |
Std. Mean error |
||
Pair 1 |
age |
35.76 |
1.38 |
13.5 |
1.15 |
OF |
4.08 |
1.38 |
.67 |
.057 |
|
Pair 2 |
age |
35.76 |
1.38 |
13.5 |
1.15 |
EF |
2.1 |
1.38 |
.93 |
.07 |
|
Pair 3 |
age |
35.76 |
1.38 |
13.5 |
1.15 |
gender |
1.8 |
1.38 |
.52 |
.045 |
Table 2: paired sample test results
From The t-test paired sample it can be observed that 95% confidence interval is present in between lower and upper domain where the significance between the three pairs is zero and the value of t is 27.24, 35.87 and 36.2 respectively. The linear regression modelling of the dataset shows the accuracy to be 12.5%^ making the results worse for evaluation based on age.
Figure 1: Mean of OF
Figure 2: Mean of EF
Through this experiment we have got a brief idea about the workspace that needs to be created according to the response of the participant's through questionnaires and with the use of SPSS software we were able to analyze the data. The psychology of workspace environment is a vast field of study which is growing rapidly in recent years. As people spend more than half of the day in offices, a suitable workplace plays a very crucial role in daily lives (Zhang et al. 2022). The knowledge that was delivered through these reports will help in the future research field and also will help corporates to make their investment according to the theories suggested to make the workplace more suitable, and creative and helps in maintaining mental health as well as physical health balances. Business managers too need to understand about this workspace in order to grow their business to a higher extent (Lafe et al. 2019). This can be hoped in the future that more innovative ways will come up and the workspace productivity and efficiency of employees will also increase with time.
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