© IAEME Publication

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International Journal of Advanced Research in Engineering and Technology (IJARET)
Volume 11, Issue 4, April 2020, pp. 372-389, Article ID: IJARET_11_04_037
Available online at />ISSN Print: 0976-6480 and ISSN Online: 0976-6499
Scopus Indexed

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ORGANIZATIONAL CLIMATE,
OPPORTUNITIES, CHALLENGES AND
PSYCHOLOGICAL WELLBEING OF THE
REMOTE WORKING EMPLOYEES DURING
COVID-19 PANDEMIC: A GENERAL LINEAR
MODEL APPROACH WITH REFERENCE TO
INFORMATION TECHNOLOGY INDUSTRY IN
HYDERABAD
Dr. KDV Prasad
International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Telangana, India

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Dr. Mruthyanjaya Rao Mangipudi
Karvy Stock Broking Limited, Financial District, Gachibowli, Hyderabad, India

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Dr. Rajesh W. Vaidya
Assistant Professor, Faculty In-charge Training and Placement, (DMT)
Shri Ramdeobaba College of Engineering & Management, Nagpur, India
Budumuru Muralidhar
International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Telangana, India

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ABSTRACT
In this empirical study we are presenting the results of our survey research on
remote working by employees of IT and E-Commerce industry employees during the
Coronavirus (Covid-19) Pandemic with reference to Hyderabad Metro. An empirical
survey was carried out during the lockdown period, 25 March 2020 - 20 April 2020
using research survey instrument, an undisguised questionnaire. The eight independent
factors Team work, Communication, Peer, Job related factors, Organization Policies,
Organization Climate, Job Satisfaction, Psychological factors dependent factor
psychological wellbeing of the employees. The Psychological wellbeing was measured
using the modified and shortened version of 18-item version scale of Ryff and Keyes
using six factors - Self-acceptance, Personal growth, Purpose in life, Environmental
mastery, Autonomy and Positive relations with others. The survey instrument validity

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad

and reliability was assessed using Cronbach alpha (overall C-alpha measured at 0.92)
for all the items and Split-Half (odd-even) Correlation 0.82 whereas Split-Half with
Spearman-Brown Adjustment at 0.94. The results from the General Linear Model
Multivariate analysis indicate Communication, Organization climate, Organization
Policies, Job Satisfaction and Psychological factors significantly influencing the
psychological wellbeing of employees in information technology sector during the
survey period of Covid-19 pandemic.
Keywords: COVID-19, psychological wellbeing, Cronbach alpha, Remote working,
Autonomy

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Cite this Article: Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W.
Vaidya, Budumuru Muralidhar, Organizational Climate, Opportunities, Challenges and
Psychological Wellbeing of the Remote Working Employees during Covid-19

Pandemic: A General Linear Model Approach with Reference to Information
Technology Industry in Hyderabad, International Journal of Advanced Research in
Engineering and Technology (IJARET), 11(4), 2020, pp. 372-389.
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1. INTRODUCTION

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The recent Covid-19 outbreak changed working landscape to a great extent. The institutions
and organizations of both public and private sector should reflect on their learnings from
employees working remotely and its arrangements. The institutions and the organizations to
give more liberty to the employees to adjust their working schedules to suit to their well-being.
It is not only for the employee, individually, but to every organization and the society, and the
world as a whole to get tuned to this new situation. The working class slowly emerges and tries
to adjust and deliver its best as responsible members of a natural ecosystem. Every human
resource within a working landscape attempts to balance his/her own needs with the needs of
the environment.
The work from home has become a buzz phrase, in particular with the Information
Technology (IT) and the IT enabled Sector, mainly to ensure engaging the workforce, to reach
out to the internal and the external stakeholders, to retain the talent and maintain attrition rate
to its low on one hand. The situation throws down challenges for many of the people to either
up-skilling or re-skilling on a war-foot basis without giving any time, else they may become
vulnerable to the exercise of trimming the team size by the companies. Remote working has

become an essential work-practice. It saves the commuting time, the overheads and the
resources associated with physical office management. The work practice in all the sectors,
where the productivity, services and solutions can be managed without the necessity of being
physically present, such as information technology, pharma, healthcare, research and
development, eCommerce, etc., However, it is not possible to manage the workforce belong to
unskilled and unorganized sector, which constitute a considerable number of total workforce.
As far as information technology sector is concerned, they are finding the ways and means
to figure out the activities that can be accomplished remotely using latest communication
technologies like Microsoft Teams, Zoom, Skype, WhatsApp, bluejeans, Webex, Hangouts etc.
Several organizations irrespective of the sector convenes virtual meetings/conferences/
workshops/seminars via the above mentioned communication tools. It is expected that some of
the people would suffer from post-pandemic stress and some of the people might realize their
inner strengths and display a great amount of gratitude with what they have. This would mean
the employees would go through a lot of emotional journey, and their psychological well-being
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Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru
Muralidhar

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would have its own impacts, which will be revealed, studied and understood only by
undertaking another research post-pandemic and compare the situation.


1.1. What is Remote Work?

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Remote work is a working practice that encourages professionals to work beyond the
conventional office setting. This is based on the idea that there is no need for work to be
performed in a particular location. When compared of commuting to workplace every day and
work from a fixed desk, remotely working by the people carrying out their activities and tasks,
and achieve their goals anywhere they opt yields much more productivity. The employees have
reasonable control to plan their days to see that their professional and personal lives can be
existed to their fullest potential and satisfaction and coexist peacefully (Remote year, 2020).
This is a conceptual shift and remote work has capitalized on that independence. The beauty
of remote work is the fact that an employee can choose to work in a way that makes work-life
balance perfect. However, some employees need to visit to the office monthly/fortnight to have
face to face peer meetings with an opportunity to work remotely for the majority of the working
week, but have to commute to in-person meetings at the office one day a week. Another concept
co working spaces and sharing economies are on rise where an organization or an employee.
The co working spaces are hubs of productivity, community, and technology, offering great
scope for network connectivity to get the work done. The co working spaces fall between full
traditional workplace and remote work or work from home.
The benefits and advantages of remote work increase productivity, work-life balance,
saving the commuting time and office resources, and provide more flexible lifestyle. This helps

women to overcome genetic/gynecology challenges so she can attend the office tasks at her
comfort. An employee also could pursue his/her long standing hobbies, professional pursuits
etc., which could not be fulfilled due to time constraints or due to lack of freedom at workplace
to pursue them. Remote employees are less stressed compared to in-office counter parts with
decreased absenteeism and better health and well ness (Royal Society for Public Health in the
UK, 2014, PGi 2014). It was also observed a renewed passion for their with motivation in the
employees working remotely.
As part of benefits to the employer higher productivity as the employee puts more effort,
increased cost savings as the decrease in office rent, infrastructure and maintenance costs, and
higher employee engagement. One study report that the employees are ready to quit the present
job one that offer remote working (in a survey by TINYpulse)

3. REVIEW OF LITERATURE

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A remote employee who is hired by a company but operates beyond the conventional office
environment-working from a nearby coworking room, from home, in any city around the globe.
This idea requires a lot of consideration about a competent, working style employee with a
meaningful discussion with the boss. Employees can create a remote work case to get peer
acceptance (Remote work 2020). Several remote work challenges like different time zones,
over working, bead health habits, distractions in the home,
The world has turned into remote working or work from home concept wherever possible
due to Coronavirus disease 2019 (COVID-19) an infectious disease caused by a severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2) a mutated virus which is less virulent in
India. The disease was first identified in December 2019 in Wuhan, China and spread globally,
resulting into pandemic. The availability of tools like team viewer, splashtop, Microsoft remote
desktop, zoom, Microsoft teams, and owl are some of the communication tools essential for

remote working, work prioritization are reported and solutions were provide by (Melanie

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad

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Pinola, 2020.) The SCIKEY MindMatch stud reported that 99.8% workforce in IT sector
incapable of remote working as reported in Economic Times. Felstead and Henseke (2017)
critically assessed the win-win situation when more and more work is being detached from
place for both employers and employees. The results were reported analyzing labour market

data, based on the factors knowledge economy, the growth in flexible employment and
organizational responses.
Daniel Wheatley (2017) reported the positive impact of of flexible working arrangements
(FWAs), and positive effects for men and women on job satisfaction using the British
Household Panel Survey and Understanding Society, 2001–10/11. Standy Stples (2001)
reported the differences remote working employees and non-remote workers, and mentioned
that Interpersonal trust of the employee in the peer is strongly associated with higher selfperceptions of performance, higher job satisfaction and lower job stress and weak support of
physical connectivity and its impact. (i. e., the availability of IT) on job satisfaction, supporting
the enabling role of IT. The remote workers and peer of higher level of interpersonal trust due
to frequent communications. The remote working can improve employee improve employee
productivity, creativity and morale when it right done and perfectly planned Zara Greenbaum
(2019). Kristen Senz 2019 reported the benefits of the remote working to the companies the
gain could add $1.3 billion in each year Based on a patent's average value, this productivity
gain could add $1.3 billion of value to the US economy in an year based on the patent average.
Adam Hickman and Jennifer Robison (2020) reported from Gallup Research data that
remote work improves business outcomes, attracts talent and an engaged workforce has the best
financial outcomes. Hickman A reported the how the workplace isolation will influence a
remote worker because of lack of management acumen, organizational expertise, to
development implement strategies on remote work policies and procedures. Based on the above
literature survey the following research gap is identified.
What are the common understandings about how workplace isolation may influence a
remote employee’s performance in a customer service organization in the United States?the
Social Exchange Theory (Emerson 1976), which is dependent on mutually agreement and
gratifying among both the sides involving communication is the basis of this theory. Emerson’s
(1976) theory, explains that a social exchange is needed among remote workers and their
employer to preserve a remote employee from experiencing workplace isolation. This
conceptual framework is essential for employee psychological wellbeing and remote worker
experience stress because the absence of social exchange with in-office worker). The free access
to technology, peers, and more free communication can avoid the risk of remote working
challenges (Greer and Payne, 2014). Therefore, psychological wellbeing of a remote worker

depends human interaction, a social aspect and missing elements remote working. Therefore,
the outcome variable psychological wellbeing also included.

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4. RESEARCH QUESTION

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There is any correlation between the organisational and individual factors psychological wellbeing of remote working employees during Covid19-Pandemic?
Is there are any challenges and opportunities of the employees working remotely and
psychological well-being during Covid-19 lockdown?

4.1. Research Gap
The Government of Indian announced a three-week lock during 24 March to 14 April and
extended till 3 May 2020. The idea behind the lock down is to contain the spread of the virus

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Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru
Muralidhar

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maintaining social distance among the human beings. Therefore, several organisations decided
wherever possible, that their employees will be allowed to work remotely. The remote working
options was followed almost all sectors of employees. As the Covid-19 Pandemic was reported
during December 2019, there no specific research articles, reviews of reports available in
particular, related to remote working during Covid-19 or any similar situation in the past.
Further, there is not a single article reported on the psychological wellbeing of the remote
working employees during any pandemic time in the past. Therefore, the authors considered to
carry out this study surveying the remote working employees during March 24 to 20 April 2020
and reported the results.

5. RESEARCH METHODOLOGY

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Theoretical Framework: The author followed the modified version of the model proposed by
Anderson et al. (2015) with challenges and opportunities as predictors of the Psychological
wellbeing of Remote worker.

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Figure 1 This diagram depicts how an employee is subjected to his/her well-being and the factors that
affect the ecosystem within and outside the organization.


Hypotheses

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After reviewing the research an identifying the problem the following hypotheses were framed
Ho1: Employee individual, organisational, and external factors significantly influence the
psychological well-being of an employee during Covid-19 Pandemic
H11: Employee individual, organisational, and external factors does not significantly influence
the psychological well-being of an employee during Covid-19 Pandemic

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad

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H02: There are significant gender and age differences on factors effecting the psychological
wellbeing of the employees in IT sector
H12: There are no significant gender and age differences on factors effecting the psychological
wellbeing of the employees in IT sector
Estimation of sample size: As the population size is unknown the researchers used Cochran
(1977) formula to estimate the sample size for this empirical study. Cochran (1977) developed
a formula to calculate a representative sample for proportion as
z2pq
no= -----e2
where no is the sample size, z is the selected critical value of desired confidence level, p is
the estimated proportion of an attribute that is present in the population, q 1 p and e is the desired
level of precision and this formula was used as IT sector where population is unknown assuming
the maximum variability which is equal to 50% (p=0.5) and taking 95% confidence level with
±5% precision, the required sample size is
p = 0.5 and hence q = 1-0.5 = 0.5; e = 0.05 and z = 1.96
(1.96)2(0.5)(0.5)
no =

-------------------- = 384.16 = 384
(0.05)2

Therefore, we have chosen a sample size of > 384 i.e. 400
The sample demography and description are presented in Tables 1 and 2 and the study
variables both dependent and independent are presented in Table 3.

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Table 1 Demography of the sample

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Gender
Men
Women
Total
Source: Primary data

Frequency
228
172
400

Percent
57
43
100

Table 2 Sample description

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Age group
20-30
31-40
41-50
51-60
Source: Primary data

Number of respondents

160
100
80
60

Table 3 Independent factors that measured dependent factor psychological wellbeing
Description

No items
4
5
3
5
6
5

Team Work
Communication
Peer
Job related factors
Organization Policies
Organization climate

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Factor
1
2
3
4

5
6

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Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru
Muralidhar

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Factor
Description
No items
7
Job Satisfaction
4
8
Psychological factors
5

Dependent factors - psychological wellbeing
Factor Description
No items
1
Environment Mastery
3
2
Positive Growth
3
3
Positive Relations
3
4
Self-Acceptance
3
5
Autonomy
3
6
Purpose of Life
3
Based on shortened version psychological wellbeing scale Ryff and Keyes (1995)

6. RESEARCH INSTRUMENT

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Measurement of internal, external, and organization factors: A standardized, undisguised
research instrument based on five point Likert Type scale, with rating scale of Strongly agree
=5; Agree = 4; Neutral =3; Disagree =2; Strongly disagree 2 were used to measured Team work,
Peer, Organizational climate, Organizational policies, Job related factors Communication, Job
satisfaction and Psychological factors following the model of Prasad et al. (206, 2017, 2018).
The total items measured are 37
Measurement of psychological wellbeing based factors: A shortened version of 18-point scaler
developed by Ryff and Keyes (1995) was used. This is a 7-point rating scale with Strongly
agree = 7, Somewhat agree = 6, A little agree = 5, Neither agree nor disagree = 4, A little
disagree = 3, Somewhat disagree = 2, Strongly disagree =1 and the factors measured are
Autonomy, Environmental Mastery, Personal Growth, Positive Relations, Purpose in Life and
the Self-Acceptance with 3 items for each factors.
There are some items worded in the opposite way on measurement scale. Reverse-scored
measured using the following method
((Number of points on the scale) + 1) - (Answer from the respondent)
For example, if Question 1 is a 7-point scale and the respondent answered 3 on Question 1,
the recoded answer was: (7 + 1) - 3 = 5, therefore 5 was entered for this response.
As we have used to types of Likert scales one with 5 point and other with 7-point scale. For
easy analysis we have transformed the two Likert scales used into one 5-point common scale
of Likert type. The linear transformation procedure was used to convert the 7 point scale to a
5-point scale. In the 7-point liker type scale minimum is 1 and maximum is 7 and using a two
stage calculation 1) first finding linear transformation to make the new scale 0 as minimum and
1 as. maximum, and following this method transformation was made to make 7-point scale to
a five-point scale using the following formula.
X = (x - a) / (b - a)
Just substitute a for x to make the result as 0, and then substitute b for x to see that the result

is 1. This will be continued in the stage two using new minimum to be A and the new maximum
to be B. The transformation will be:
Y = (B - A) * X + A
Substitute 0 for X to see that the result is A, and 1 for X to see that the result is B.
Combining all whole first transformation in place of X in the second:
Y = (B - A) * (x - a) / (b - a) + A.

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This preprint research paper has not been peer reviewed. Electronic copy available at: />

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad

For converting 7-point scale to be converted to a 5-point scale. Since the minimum of the
7-point scale is 1, we have a=1, b=7 in the first transformation. Similarly, for the second
transformation, we have A=1, B=5. Putting them together we get:

7. DATA ANALYSIS

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1
2
3
4
5

x1 x2
1.0 Strongly agree
2.5 (average of 2+3) = somewhat agree and A little agree
4.0 Neither Agree and Nor disagree
5.5 Somewhat disagree and A little disagree
7.0 Strongly disagree
In particular, notice that 1 is sent to 1, and 7 to 5

We have applied statistical techniques that suits for the study to draw the inferences and
conclusions from primary data. We used descriptive statistics, standard deviation and dispersion
methods. Psychological wellbeing was categorized as low, medium and high level. All the data
analysis was carried out using statistical package for social sciences ver 26.

7.1. Reliability Methods

The internal consistency, reliability of the questionnaire was measured estimating Cronbach
alpha values, Split-Half (odd-even) Correlation, Split-Half with Spearman-Brown Adjustment.
The values in the Table 4 indicate the survey instrument is reliable and consistent.
Table 4 Independent and dependent factors of the study
C-alpha

Split-Half (odd-even)

Correlation

0.66
0.44
0.70
0.63
0.78
0.63
0.66
0.59
0.81
0.67
0.75
0.51
0.85
0.75
0.81
0.63
Psychological wellbeing (Dependent factors)

Description
Environment Mastery
Personal Growth
Positive Relations
Self-Acceptance
Autonomy
Purpose of Life
Overall-Psychological Wellbeing
Overall-Independent Factors


0.80
0.73
0.87
0.81
0.85
0.80
0.96
0.92

0.58
0.54
0.66
0.71
0.63
0.64
0.92
0.88

Split-Half with
Spearman-Brown
Adjustment
0.61
0.77
0.77
0.74
0.80
0.67
0.86
0.77


0.73
0.70
0.79
0.83
0.77
0.78
0.96
0.94

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Factor
1
2
3
4
5
6
0.78

Team Work
Communication
Peer
Job related factors
Organization Policies
Organization climate
Job Satisfaction
Psychological factors


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1
2
3
4
5
6
7
8

Description

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Factor

Overall C-alpha :0.93

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This preprint research paper has not been peer reviewed. Electronic copy available at: />

Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru
Muralidhar


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8. RESULTS

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General Linear Model (GLM) Multivariate analysis: In our empirical study the dependent
variable psychological wellbeing an outcome variable is measured with six subscales,
Environment Mastery, Personal Growth, Positive Relations
Self-Acceptance, Autonomy and Purpose of Life against 8 independent variables Team
Work
Communication, Peer, Job related factors, Organization Policies, Organization climate, Job
Satisfaction, Psychological factors that effecting the psychological wellbeing of the employees
in Information Technology Sector.
The General Liner Model multivariate analysis was carried as we are interested to measure
effect of independent variable on each of the psychological wellbeing factors as described
earlier. In GLM model more than one dependent variable can be predicted using independent
variables, and we also studied to observe if there are any significant age group and gender
differences that effect the psychological wellbeing of the employees. The detailed results are
presented below

Test of Homogeneity of Variances

Table 5 Box's Test of Equality of Covariance Matricea


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Box's M
44.771
F
2.056
df1
21
df2
97921.377
Sig.
0.290
a
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups.
a. Design: Intercept + Team Work + Communication + Peer + Job Related +
Organisation Policy + Organization Climate + Psychological + Job Satisfaction +
Gender

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The null hypothesis for this test is that the observed covariance matrices for the dependent
variables are equal across groups. As the result for the test is non-significant test result (i.e. one
with a large p-value) indicates that the covariance matrices are equal (Table 5).
We have used the Bartlett's test (Snedecor and Cochran, 1989) to test all the samples have
equal homogeneity of variances to carry out the GLM analysis. The results indicate Bartlett’s
test of Sphericity significant (0.00) indicates the matrices for all the three variables are not
identity matrix (Table 6), so the null hypothesis is rejected. The data generated through the
responses are fit for carrying our further analysis.

Table 6 KMO and Bartlett's Test statistic of independent factors

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Bartlett’s test pf Sphericitya
Likelihood Ratio
0.000
Approx. Chi-Square
875.923
Df
20
Sig.
0.000
Tests the null hypothesis that the residual covariance matrix is proportional to an
identity matrix.
a. Design: Intercept + Team Work + Communication + Peer + Job Related +
organization Policy + Organization Climate + Psychological + Job Satisfaction +
Gender

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad

The homogeneity of variance in the same is measured using Leven’s test of equality of error
variances. The significance of Levene's test is > 0.05, which suggests that the equal variances
assumption is not violated (Table 7)
Table 7 Levene's Test of Equality of Error Variancesa

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F
df1
df2
Sig.
Environment Mastery
1.424
1
380
0.234
Personal Growth
0.261
1
380
0.610
Autonomy

0.602
1
380
0.439
Self-Acceptance
0.564
1
380
0.453
Purpose Of Life
0.382
1
380
0.537
Positive Relations
0.417
1
380
0.519
Tests the null hypothesis that the error variance of the dependent variable is equal
across groups.
a. Design: Intercept + Team Work + Communication + Peer + Job Related +
Organisation Policy + Organization Climate + Psychological + Job Satisfaction +
Gender
Table 8 General Linear Model: Multivariate testsa
Effect
Intercept

F


Hypothesis df

Error df

Sig.

Pillai's Trace
Wilks' Lambda
Hotelling's
Trace
Roy's Largest
Root
Pillai's Trace
Wilks' Lambda
Hotelling's
Trace
Roy's Largest
Root
Pillai's Trace
Wilks' Lambda
Hotelling's
Trace
Roy's Largest
Root
Pillai's Trace
Wilks' Lambda
Hotelling's
Trace
Roy's Largest
Root

Pillai's Trace
Wilks' Lambda
Hotelling's
Trace
Roy's Largest
Root
Pillai's Trace

0.128
0.872
0.146

4.295b
4.295b
4.295b

6.000
6.000
6.000

375.000
375.000
375.000

0.000
0.000
0.000

Partial Eta
Squared

0.128
0.128
0.128

0.146

4.295b

6.000

375.000

0.000

0.128

0.024
0.976
0.024

.715b
.715b
.715b

6.000
6.000
6.000

375.000
375.000

375.000

0.638
0.638
0.638

0.024
0.024
0.024

0.024

.715b

6.000

375.000

0.638

0.024

0.077
0.923
0.083

2.449b
2.449b
2.449b


6.000
6.000
6.000

375.000
375.000
375.000

0.027
0.027
0.027

0.077
0.077
0.077

0.083

2.449b

6.000

375.000

0.027

0.077

0.057
0.943

0.060

1.764b
1.764b
1.764b

6.000
6.000
6.000

375.000
375.000
375.000

0.109
0.109
0.109

0.057
0.057
0.057

0.060

1.764b

6.000

375.000


0.109

0.057

0.020
0.980
0.020

.596b
.596b
.596b

6.000
6.000
6.000

375.000
375.000
375.000

0.733
0.733
0.733

0.020
0.020
0.020

0.020


.596b

6.000

375.000

0.733

0.020

0.097

3.141b

6.000

375.000

0.006

0.097

Wilks' Lambda

0.903

3.141b

6.000


375.000

0.006

0.097

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Team Work

Value

Communication

Peer

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Job Related

Organisation
Policy


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Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru
Muralidhar

Psychological
factors

Job
Satisfaction

F

Hypothesis df

Error df

Sig.

Hotelling's
Trace
Roy's Largest
Root
Pillai's Trace


0.107

3.141b

6.000

375.000

0.006

Partial Eta
Squared
0.097

0.107

3.141b

6.000

375.000

0.006

0.097

0.086

2.755b


6.000

375.000

0.014

0.086

Wilks' Lambda
Hotelling's
Trace
Roy's Largest
Root
Pillai's Trace

0.914
0.094

2.755b
2.755b

6.000
6.000

375.000
375.000

0.014
0.014


0.086
0.086

0.094

2.755b

6.000

375.000

0.014

0.086

0.069

2.170b

6.000

375.000

0.048

0.069

Wilks' Lambda
Hotelling's
Trace

Roy's Largest
Root
Pillai's Trace

0.931
0.074

2.170b
2.170b

6.000
6.000

375.000
375.000

0.048
0.048

0.069
0.069

0.074

2.170b

6.000

375.000


0.048

0.069

0.166

5.826b

6.000

375.000

0.000

0.166

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Organization
Climate

Value

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Effect


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Wilks' Lambda
0.834
5.826b
6.000
375.000
0.000
0.166
Hotelling's
0.199
5.826b
6.000
375.000
0.000
0.166
Trace
Roy's Largest
0.199
5.826b
6.000
375.000
0.000
0.166
Root
Gender
Pillai's Trace
0.019
.581b

6.000
375.000
0.745
0.019
Wilks' Lambda
0.981
.581b
6.000
375.000
0.745
0.019
Hotelling's
0.020
.581b
6.000
375.000
0.745
0.019
Trace
Roy's Largest
0.020
.581b
6.000
375.000
0.745
0.019
Root
a. Design: Intercept + Team Work + Communication + Peer + Job Related + Organisation Policy + Organization
Climate + Psychological + Job Satisfaction + Gender
b. Exact statistic; c. Computed using alpha = .05


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From the results of multivariate test it is evident that the independent factors Team work,
Job Related Factors and Peer not significantly contributing to psychological wellbeing of the
employees. The other five independent variables Communication Wilks λ=0.903, (F6,
176)=3.141, p=0.027, η2=0.077; Organisational Policies λ=0.923, (F6, 176)=2.449, p=0.006,
η2=0.097 Organisation Climate λ=0.914, (F6, 176)=2.755, p=0.014, η2=0.086 Job satisfaction
λ=0.834, (F6, 176)=5.826, p=0.005, η2=0.166 and Psychological Factors λ=0.931, (F6,
176)=2.170, p=0.005 η2=0.019 are influencing the psychological wellbeing of the employees
(Table 8).
A separate ANOVA was run for each dependent variable and with each independent factor
and the results are: The team work is not significantly influencing the psychological wellbeing.
Communication is influencing only the factor personal growth Personal Growth F(1, 181)=
4.735, p=0.031 η2=0.025; Peer = F(1, 181) = 6.408, p =0.012; η2=0.034; Organization policies
and organization climate are influencing all dependent factors except personal growth;
psychological factors are influencing all the psychological wellbeing factors, and so on. As the
results in Table No. Test of Between-subjects effects it is evident that statistically significant
gender differences were observed and influencing the psychological wellbeing of employees
(Table 9).

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad
Table 9 General Linear Model: Tests of Between-Subjects Effects
df

Mean
Square

9
9
9
9
9
9
1
1
1
1
1
1
1
1
1

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

4.877
5.430
6.054
4.933
5.094
4.450
13.246

10.945
8.797
10.351
7.859
12.079
0.252
0.394
0.000
0.304
0.833
0.030
0.105
2.824
0.011
0.528
0.007
0.698
1.994
0.859
4.640
2.494
2.603
5.398
0.294
0.073
0.015
0.093
0.149
0.511
6.093


7.026
4.498
1.265
3.386
5.119
6.401

1
1
1
1
1
1

8.318
3.830
3.239
4.275
5.957
0.021

1
1
1
1
1
1

Pr


ep

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Corrected Model Environment Mastery
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Intercept
Environment Mastery
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Team Work
Environment Mastery
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Communication Environment Mastery
Personal Growth

Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Peer
Environment Mastery
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Job Related
Environment Mastery
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Organisation
Environment Mastery
Policy
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Organization
Environment Mastery
Climate
Personal Growth

Autonomy
Self-Acceptance
Purpose of Life
Positive Relations
Psychological
Environment Mastery

Type III
Sum of
Squares
43.889a
48.868b
54.483c
44.397d
45.845e
40.046f
13.246
10.945
8.797
10.351
7.859
12.079
0.252
0.394
0.000
0.304
0.833
0.030
0.105
2.824

0.011
0.528
0.007
0.698
1.994
0.859
4.640
2.494
2.603
5.398
0.294
0.073
0.015
0.093
0.149
0.511
6.093

F

Sig.

Partial Eta
Squared

7.542
9.104
8.360
6.928
7.076

6.324
20.485
18.351
12.149
14.537
10.917
17.167
0.389
0.660
0.000
0.427
1.157
0.042
0.162
4.735
0.016
0.742
0.010
0.992
3.084
1.441
6.408
3.502
3.616
7.672
0.454
0.122
0.020
0.131
0.207

0.726
9.422

0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.001
0.000
0.001
0.000
0.534
0.418
0.989
0.514
0.284
0.838
0.687
0.031
0.901
0.390
0.921
0.321
0.081
0.232
0.012

0.063
0.059
0.006
0.501
0.728
0.888
0.718
0.650
0.395
0.002

0.273
0.312
0.294
0.256
0.260
0.239
0.102
0.092
0.063
0.074
0.057
0.087
0.002
0.004
0.000
0.002
0.006
0.000
0.001

0.025
0.000
0.004
0.000
0.005
0.017
0.008
0.034
0.019
0.020
0.041
0.003
0.001
0.000
0.001
0.001
0.004
0.049

7.026
4.498
1.265
3.386
5.119
6.401

11.780
6.211
1.777
4.703

7.275
9.899

0.001
0.014
0.184
0.031
0.008
0.002

0.061
0.033
0.010
0.025
0.039
0.052

8.318
3.830
3.239
4.275
5.957
0.021

13.946
5.289
4.549
5.939
8.466
0.032


0.000
0.023
0.034
0.016
0.004
0.858

0.072
0.028
0.025
0.032
0.045
0.000

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Source

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Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru

Muralidhar
0.515
3.392
1.061
0.837
0.235
5.551
1.484
16.539
13.515
9.410
2.226
0.228
0.207
0.108
0.001
0.154
0.703
0.647
0.596
0.724
0.712
0.720
0.704

0.864
4.685
1.490
1.163
0.333

8.584
2.488
22.842
18.981
13.071
3.164
0.353
0.348
0.150
0.001
0.213
0.999

0.005
0.025
0.008
0.006
0.002
0.045
0.014
0.112
0.095
0.067
0.017
0.002
0.002
0.001
0.000
0.001
0.005


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0.354
0.032
0.224
0.282
0.564
0.004
0.116
0.000
0.000
0.000
0.077
0.553
0.556
0.699
0.976
0.645
0.319

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1
1
1

1
1
1
1
1
1
1
1
1
1
1
1
1
1
380
380
380
380
380
380
390
390
390
390
390
390
389
389
389
389

389
389

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Personal Growth
0.515
Autonomy
3.392
Self-Acceptance
1.061
Purpose of Life
0.837
Positive Relations
0.235
Job Satisfaction Environment Mastery
5.551
Personal Growth
1.484
Autonomy
16.539
Self-Acceptance
13.515
Purpose of Life
9.410
Positive Relations
2.226

Gender
Environment Mastery
0.228
Personal Growth
0.207
Autonomy
0.108
Self-Acceptance
0.001
Purpose of Life
0.154
Positive Relations
0.703
Error
Environment Mastery
117.037
Personal Growth
107.954
Autonomy
131.058
Self-Acceptance
128.880
Purpose of Life
130.308
Positive Relations
127.358
Total
Environment Mastery
2539.321
Personal Growth

2805.979
Autonomy
2521.799
Self-Acceptance
2530.552
Purpose of Life
2535.778
Positive Relations
2564.665
Corrected Total Environment Mastery
160.926
Personal Growth
156.823
Autonomy
185.541
Self-Acceptance
173.277
Purpose of Life
176.152
Positive Relations
167.404
a. R Squared = .273 (Adjusted R Squared = .237)
b. R Squared = .312 (Adjusted R Squared = .277)
c. R Squared = .294 (Adjusted R Squared = .259)
d. R Squared = .256 (Adjusted R Squared = .219)
e. R Squared = .260 (Adjusted R Squared = .223)
f. R Squared = .239 (Adjusted R Squared = .201)
g. Computed using alpha = .05

Pr


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The results of separate ANOVA for each psychological wellbeing factors against each
independent variable are presented in Table 10. The factor Team Work is not statistically
significant on influencing the psychological wellbeing of an employee, whereas organization
climate is statistically significant and influencing all the six factors of psychological wellbeing.
Likewise Organization policies are influencing all the five factors of psychological wellbeing
except Self-Acceptance, and so on. There were no significant gender differences were observed
on the results are not statistically significant and the gender is not the predictor of psychological
wellbeing.

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad
Table 10 Results of ANOVA for all the independent factors against dependent factors (psychological
wellbeing)a

Personal Growth
Autonomy

Self-Acceptance
Purpose of Life

ANOA results
Not significant
No significant gender differences
F(1, 380)=4.735, p=0.031, η2 =0.025
F(1, 380)=6.408, p=0.012, η2=0.034
F(1, 380)=5.398, p=0.006, η2=0.004
F(1, 380)=0.454, p=0.050, η2=0.003
F(1, 380)=9.422, p=0.002, η2=0.049
F(1, 380)=11.780, p=0.001, η2=0.061
F(1, 380)=6.211, p=0.014, η2=0.033
F(1, 380)=4.703, p=0.037, η2=0.025
F(1, 380)=7.275, p=0.008, η2=0.039
F(1,380)=9.899, p=0.002, η2= 0.052

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Independent factor
Dependent factor
Team Work
Gender
Communication
Personal Growth
Peer
Autonomy

Positive Relations
Job related
Environment Mastery
Organization Policies Environment Mastery
Personal Growth
Autonomy
Purpose of Life
Positive Relations
Organization Climate Environment Mastery

F(1,380)=5.289, p=0.023, η2=
0.028
F(1,380)=13.946, p=0.000, η2=0.072
F(1, 380)=4.549, p=0.034, η2=0.025
F(1,380)=5.939, p=0.016, η2=0.032

Positive Relations
F(1,380)=8.466, p=0.004, η2=0.045
Psychological factors Autonomy
F(1, 380)=4.685, 0.032, η2=0.025
Job Satisfaction
Environment Mastery
F(1, 380)=8.584, 0.004, η2=0.045
Autonomy
F(1, 380)=22.842, 0.00, η2=0.112
Purpose of Life
F(1, 380)=13.0712, 0.000, η2=0.67
a
Note: Only significant results are presented from General Linear Model: Tests of Between-Subjects Effects


ot

The Age Group is not statistically significant in influencing the psychological wellbeing of
the employees (Table 11).
Table 11 Effect of Age Group on psychological wellbeing of the employees
factor

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Source

Gender * Age Environment
Group
Mastery
Personal Growth
Autonomy
Self-Acceptance
Purpose of Life
Positive Relations

Type III
Sum of
Squares
4.449

df

Mean
Square


F

Sig.

Partial Eta
Squared

3

1.483

2.328

0.076

0.038

2.937
5.266
4.332
4.170
1.021

3
3
3
3
3


0.979
1.755
1.444
.1.390
0.340

1.637
2.454
2.046
1.932
0.474

0.182
0.065
0.109
0.126
0.701

0.027
0.040
0.034
0.032
0.008

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Therefore, we partially accept the null hypothesis Ho1: Employee individual, organisational,
and external factors significantly influence the psychological well-being of an employee during

Covid-19 Pandemic and accept the alternate hypothesis H12: There are no significant gender
and age dfferences on factors effecting the psychological wellbeing of the employees in IT
sector

9. DISCUSSION
We have carried out this study to measure the psychological wellbeing of the information
technology employees during the lockdown period (24 March – 24 April 2020) applying a

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This preprint research paper has not been peer reviewed. Electronic copy available at: />

Dr. KDV Prasad, Dr. Mruthyanjaya Rao Mangipudi, Dr. Rajesh W. Vaidya, Budumuru
Muralidhar

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survey questionnaire on the remote working employees. There are several literature is available
in general on remote work and its effects, however we have not found any single research study
on remote work and how it will effect employees psychological wellbeing during any pandemic
type of situations. We believe this is the first such type of study and to make the study more

comprehensive we have measured how the eight independent factors are effecting the every
factory of psychological wellbeing. Though, there is no research available using GLM
Multivariate model our results in line with the similar studies carried out by Gu et al. (2019)
and psychosomatic wellbeing among Chinese nurses; Adam Steptoe et al. (2015) psychological
wellbeing and ageing; and Brim et al. (2019) How healthy are we.
We have used several reliability methods like Cronbach alpha, Split-Half (odd-even)
Correlation and Split-Half with Spearman-Brown Adjustment to make the research instrument
more consistent and reliable. We have used a shortened version of psychological wellbeing
scale with 18 items with 6 factors developed by Ryff and Keyes (1995). The point scale was
converted to a 5 point Likert type scale using linear transformation procedures for easy data
analysis and interpretations.
We have identified the following challenges generally a remote employee can experience
which need to be mitigated by suitably modifying organizational policies so employee can work
with minimum disturbance during pandemic period. On the positive part of the side there are
several opportunities for the employer, elaborated as under
Communication

•

Remote workers will have communication problems because of internet glitches,
employee may be able to divulge his ideas/feeling to the peer in group communication,
and are not part of the routine person to person meetings, so the delay in communicating
of decisions.

•

Workplace isolation is another problem for the older employees who are not technology
savvy

•


Fear of 24/7 reporting and burnout

•

Some peers believe that they should work full 40 hrs for week however for in-office
employee the times includes the 2-Tea/Coffee and 1 lunch break. There is a chance of
employee burnout for unnecessary policing. The organization can overcome this
problem through time logins and allied mechanisms.

•

Employee really don’t work

•

There is a misconception that actually employee doesn’t work to his/her full potential,
and will work only to the targeted tasks which are important and other time the
employee will relax. Though the quantification of a service and intangible benefit is
difficult the managers should find a way out overcome this misconception.

•

Another challenge is some jobs can be worked remotely with frequent physical presence
in traditional office. The organizations should develop a policy document so to define
which job can be done remotely working at home and which tasks need employee
presence.

•


Working too much

•

Prioritizing work

•

Interruptions

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•


Lack of human interaction and loneliness

•

Different working zones

•

Bad health habits
Opportunities

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Organizational Climate, Opportunities, Challenges and Psychological Wellbeing of the Remote
Working Employees during Covid-19 Pandemic: A General Linear Model Approach with
Reference to Information Technology Industry in Hyderabad

Saving communication time

•

Saving in office costs

•

Social support

•


Flexible working hours

•

Must complete the job

•

Minimal supervision which increases the decision making knowledge of an employee

•

No workplace group politics

10. CONCLUSIONS

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Authors propose to carry out the similar type of study in other sectors in particular health and
banking sector. A study on occupational stress causing during the pandemic period will be
immensely beneficial for the organisations to modify the strategies and decide future course of
action. Another area of important is agricultural sector, in particular seed industry which is the
backbone of our country. The behavioral changes of employees need to be studied with

appropriate survey instrument.
The survey instrument i.e. survey questionnaire is available at:
/>gRQl-skmKX6e2Ug/viewform

ACKMNOWLEDGMENT

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We thank all respondents who took out their valuable time responded to our questionnaire.

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This preprint research paper has not been peer reviewed. Electronic copy available at: />