Journal of Management Research and Analysis

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Get Permission Banga and Mahajan: Work from home and changing dynamics


Introduction

COVID-19 has been a major cause of concern not just because of the absence of an effective treatment or vaccine but also due to its highly contagious nature. This had been the reason that, in 2020, most of the economies in the world preferred a nationwide lockdown to reduce its transmission. Although this measure helped in preventing the spread of the disease but it adversely affected the economic health of the countries. Global demand and supply chains were affected and there was a halt in the production units.

In India, the first case of COVID-19 was reported on 30th January 2020. On 24th March 2020, Prime Minister of India announced 21 days complete lockdown for 1.3 billion Indians immediately from midnight as a way to contain the spread of the disease. But since it was not feasible to shut down the economy and all sorts of production units and service sector, WFH came as a rescuer. Although, production work of the factories was impacted, the service sector had an advantage due to this. Now, the employees have been able to work sitting in their homes with all the comforts.

COVID-19 has led to a new era of transformation and digitalisation. Not just the working sector but also the educational sector has shifted towards WFH. Different online teaching platforms have emerged assisting in teacher-student interaction. Within a year, WFH has become a major part of people’s life. This transformation has a huge impact on the lifestyle and behavior of general public. Some companies are now even planning to make WFH mandatory for some of its workforce. Keeping this objective in mind, we aim to analyse the impact of WFH and how the general public perceives it.

Literature review

Since the last year there have been a number of studies highlighting the impact of WFH on the employees personal and professional life.

A paper by Ramos, J.P., & Prasetyo, Y.T. (September 27-29, 2020). The Impact of Work-Home Arrangement on the Productivity of Employees during COVID-19 Pandemic in the Philippines: A Structural Equation Modeling Approach have analysed the changes in productivity of employees under the WFH arrangement. The study talks about the interrelationship between job satisfaction,1 job performance, commuting satisfaction, job stress and productivity using Structural Equation Modeling. They concluded by saying that ‘Job performance’ decreases ‘Productivity’ while ‘Job Satisfaction’ increases it and ‘Job Satisfaction’ and ‘Job Performance’ are inversely related.

The research paper by Raju, S.2, & Kumar, V.K. (September 2020). Quality of life of women working from home in COVID-19 lockdown: a questionnaire survey showed the impact on physical and psychological health and social relationships done by cross-sectional, structured closed questionnaire survey. They concluded by saying that lockdown made women more active, mobile and that they balanced their official work along with family setup.

Another Italian research paper by Renzo,3 L.D.; Gualtieri, P.4 Pivari, F.; Soldati, L.; Attina, A.; Cinelli, G.; Leggeri, C.; Caparello, G.; Barrea, L.; Scerbo, F.; Esposito, E.; & Lorenzo, A.D. (08 June 2020). Eating Habits and lifestyle changes during COVID-19 lockdown: An Italian Survey,with a total of 3533 respondents found that the perception of weight gain was observed in 48.6% of the population; 3.3% of smokers decided to quit smoking; a slight increased physical activity has been reported in 38.3% of respondents; the population group aged 18–30 years resulted in having a higher adherence to the Mediterranean diet when compared to the younger and the elderly population; 15% of respondents turned to purchasing organic fruits and vegetables, especially in the North and Centre of Italy, where BMI values were lower.

The research paper ‘Impact of work from home on employee well-being during pandemic’ by Dr. Benita. S.5 Monica and Ms. Ghayathri N focused on the impact on employee well-being due to WFH for the IT industry using the Multiple Linear Regression Equation concluded that the work demand has more influence on well-being of employees than home demand, work interfere family, family interfere work. The company can reduce the workload for their employees and that the work demand has a greater influence on the well-being of the employees.

Working from home has increased the burden on the working women significantly according to BhattacharjeeS.6 in her research paperwork from home as an alternative to daily commuting for working women and in the research paper by Dubey, A.7, & Tripathi, S. (28 April 2020). Analysing the Sentiments towards Work-From-Home Experience during COVID-19 Pandemic, around 73% had a positive sentiment towards WFH.

Materials and Methods

This research paper used primary research surveys/questionnaire through Google Forms for data collection. It was a web-based survey with total number of respondents as 110, out of which only 100 were valid participants and were the ones considered in this study. The Questionnaire was sent via mail or WhatsApp to the respondents and was divided into two parts, the first one consisting of the basic demographic information and the second part relating to the objectives of the study. The privacy of the respondents was ensured, and they were provided with the option to know the results if they were interested in it. The survey was carried out from February 20,2021 to March 15, 2021.The responses received were then analysed through Cross Tabulations and Graphical Methods.The descriptive statistics of the respondents is given in,Table 1 where 58% of the respondents were male and 42% were female.

  1. Table 3 andFigure 1 summarizes the Demographic statistics of the respondents received through the survey showing the count of the respondents belonging to different gender with a subdivision of age; and with different qualifications with a subdivision of income levels.

  2. It is a representative sample.

  3. Preferences have been analysed with respect to various socioeconomic indicators and other attributes through cross tabulations and graphical methods. The results of which are given below.

Figure 1

Summary of demograohic statistics

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/0914c077-fed2-48fd-948e-5281af5e1524-uimage.png

Figure 2

Wish to continue work

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/d67201e2-f37f-42cf-afba-7ee6d63d17ba-uimage.png

Figure 3

Preference for work from home

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/d830e645-f1e4-43d3-9777-70cd893a80b5-uimage.png

Figure 4

Differences in perception towards WFH by different age groups

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Figure 5

Differencesin perception towards WFH by different gender

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Figure 6

Differences in perception towards WFH with different income levels

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Figure 7

Relation between travel time and work from home

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Figure 8

Productivity and preference of work

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Figure 9

Do you wish to relocate from metros to small towns/scenic destination? (Work from anywhere instead of work from home)

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/ae74fb4b-8f7f-4dc8-9de5-501bc5a6d9cb-uimage.png

Figure 10

Will you take a pay cut for the option of work from any where?

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Figure 11

Gender specific preferences To wards relocation

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/fdf2ff26-a930-4d8d-a68e-1a7725656b5a-uimage.png

Figure 12

Relocation and age groups

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/af7d72f7-337d-4df7-ada9-38fddae1c20f-uimage.png

Figure 13

Relocation and income levels

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Figure 14

Pay cut and income levels

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Figure 15

Pay cut and age croups

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Figure 16

Pay cut and gender

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/85464a17-e7f7-4eed-a6f4-46c55bfa7f54-uimage.png

Figure 17

Psycho-social impacts

https://typeset-prod-media-server.s3.amazonaws.com/article_uploads/5f42cc75-10a2-449f-aafb-135e8156c383/image/7351e412-b7bf-4148-b3ae-95396083077c-uimage.png

Results

How do people wish to continue?

More than 75% of people wish to continue with remote work at least some of the time.

How different age groups perceive work from home?

  1. 18-25 does not prefer hybrid in comparison to others

  2. 26-40 are least willing to resort to only work from office.

  3. 41-60 are least willing to resort to only work from home

How different gender perceive work from home?

Males are more likely to prefer work from home than females.

How people with different income levels perceive work from home?

The preference for hybrid mode goes up phenomenally with increase in income. It’s clearly visible from Figure 6 that as we move from the income level of less than 5 lakhs to income level of 25 lakhs and above there is a substantial increase in the preference towards the hybrid model i.e., the percentage of people preferring the blended mode of predominantly WFH and predominantly WFO increases.

What is the relationship between travel time and preference for work from home?

  1. Extremely strong relation of preference for Work from Home and travel time

  2. Increase in travel time increases inclination for work from home

  3. More than 75% of people who travel for more than 2 hours a day want to either work completely from home or predominantly.

Those who believe work from home increased productivity want to continue with it

Around 76% of respondents who believe that work from home has increased productivity wants to continue with it while around 73% of respondents who believe that WFH has not increased productivity wants to continue with WFO. Thus, there is no clash of opinions shown by the respondents.

Response towards relocation and pay cut

In this part of the questionnaire a clash in the opinions of the respondents was seen. 57% of the respondents wished to relocate from metros and accept the option of Work from Anywhere instead of WFH, but they were not ready to take a Pay Cut for that. 75% of the respondents are unwilling to take a pay cut while 57% responded with a yes for the option of work from anywhere.

Relocation and gender specific preferences

Women are more willing to relocate as compared to men.

Relocation and age groups

Majority of all age groups are willing to relocate.

Relocation and income levels

The people belonging to the income slabs of less than 5 lakhs and above 25 lakhs are most willing to relocate. In short, the people with low income and the ultra-rich are the most willing to relocate while the mediacrats with the income level of 5-10 lakhs and 10-25 lakhs are less willing to relocate.

Pay cut and income levels

The poor and ultra-rich are most willing to shell out for the flexibility of work from anywhere and relocation

Pay cut and age groups

Majority of the respondents irrespective of the age groups are unwilling to take a pay cut. However, the youth is most willing out of the other age groups to take pay cut for work from home flexibility, that is about 29%.

Pay cut and gender

Females are more willing to take a pay cut as compared to men for the option of work from anywhere. Overall, both the genders are reluctant for this option.

Psycho-social impacts

  1. Every 2 out of 3 people believe WFH improved their Family Relations.

  2. 54% of the respondents believe that WFH improved their Productivity.

  3. 58% believe that WFH increased their sleep.

  4. 59% believe they were able to exercise more with WFH.

  5. 68% say that they experienced Loneliness due to WFH.

Table 1

Summary of responses

Questions

Options

N

Percentage

Gender

Male

58

58

Female

42

42

Age

18-25

28

28

26-40

54

54

41-60

18

18

60yrs.+

0

0

Qualification

Graduate

52

52

Post graduate

43

43

PHD/Doctorate

5

5

Annual Family Income

Less than 5 Lakhs

22

22

5-10 Lakhs

31

31

10-25 Lakhs

31

31

25 Lakhs+

16

16

Frequency of work from home before covid

No work from Home

70

70

Once/Twice a week

16

16

More than twice a week

4

4

Only Work from home

10

10

Still working from home

At all time

54

54

Sometimes

32

32

Completely back to office

14

14

Frequency of working from home right now

No Work from Home

19

19

Once/Twice a week

14

14

More than twice a week

15

15

Only Work from home

52

52

Wish to continue

Work from home

28

28

Work from office

23

23

Blended with predominantly work from home

28

28

Blended with predominantly work from office

21

21

Time spent daily on travelling to work before covid

Less than 1 hour

44

44

1-2 hour

26

26

more than 2 hours

23

23

Not Applicable

7

7

Work from home improved family relations

Yes

66

66

No

14

14

Cant say

20

20

Increased productivity due to work from home

Yes

54

54

No

33

33

Cant say

13

13

Able to sleep more with work from home

Yes

58

58

No

32

32

Cant say

10

10

Able to do more physical activity / exercise

Yes

59

59

Table 0

No

36

36

Cant say

5

5

Work from home increased loneliness and missing social gathering, meetings

Yes

68

68

No

27

27

Cant say

5

5

Impact on savings

Increased

63

63

Decreased

11

11

No Change

26

26

Relocation from metros to small towns/scenic destinations ( Work from anywhere instead of work from home)

Yes

57

57

No

43

43

Will you take a pay cut for the option of work from anywhere

Yes

25

25

No

75

75

Table 2

Demographic statistics

18-25

Female

26-40

Female

41-60

Female

Male

18-25

Male

26-40

Male

41-60

Grand Total

Graduate

8

9

14

19

2

Less then 5 lakhs

3

4

4

2

13

5-10 lakhs

4

4

7

6

1

22

10-25 lakhs

1

3

8

12

25 lakhs+

1

3

1

5

Postgraduate

5

9

8

1

15

5

Less then 5 lakhs

1

2

1

3

2

9

5-10 lakhs

2

2

3

1

8

10-25 lakhs

4

4

3

4

1

16

25 lakhs+

1

2

1

5

1

10

Phd/Doctorate

2

1

2

5-10 lakhs

1

1

10-25 lakhs

1

2

3

25 lakhs+

1

1

(blank)

(blank)

Grand Total

13

20

9

15

34

9

Table 3

Different age groups and preference for work from home

Age groups

Work from home

Blended with predominantly work from home

Blended with predominantly work from office

Work from office

Total

18-25

35.71%

14.29%

21.43%

28.57%

100%

26-40

25.93%

37.04%

18.52%

18.52%

100%

41-60

22.22%

22.22%

27.78%

27.78%

100%

Grand Total

28.00%

28.00%

21.00%

23.00%

100%

Table 4

Gender and preference for work from home

Gender

Work from home

Blended with predominantly work from home

Blended with predominantly work from office

Work from office

Total

Female

26.19%

26.19%

21.43%

26.19%

100%

Male

29.31%

29.31%

20.69%

20.69%

100%

Table 5

Income levels and preference for work from home

Income levels

Work from home

Blended with predominantly work from home

Blended with predominantly work from office

Work from office

Grand Total

Less than 5 lakhs

31.82%

18.18%

9.09%

40.91%

100.00%

5-10 lakhs

32.26%

35.48%

9.68%

22.58%

100.00%

10-25 lakhs

29.03%

19.35%

35.48%

16.13%

100.00%

25 lakhs+

12.50%

43.75%

31.25%

12.50%

100.00%

Grand Total

28.00%

28.00%

21.00%

23.00%

100.00%

Table 6

Travel time and preference for work from home

Travel Time

Work from home

Blended with predominantly work from home

Blended with predominantly work from office

Work from office

Grand Total

Less than 1 hour

20.45%

25.00%

27.27%

27.27%

100.00%

1-2 hour

19.23%

34.62%

26.92%

19.23%

100.00%

More than 2 hours

47.83%

30.43%

8.70%

13.04%

100.00%

Grand Total

28.00%

28.00%

21.00%

23.00%

100.00%

Table 7

Productivity and preference for work from home

Work from home

Blended with predominantly work from home

Blended with predominantly work from office

Work from office

Grand Total

No

9.09%

18.18%

24.24%

48.48%

100.00%

Yes

42.59%

33.33%

14.81%

9.26%

100.00%

Grand Total

28.00%

28.00%

21.00%

23.00%

100.00%

Table 8

Genderand relocation

Gender

No

Yes

Grand Total

Female

38.10%

61.90%

100.00%

Male

46.55%

53.45%

100.00%

Grand Total

43.00%

57.00%

100.00%

Table 9

Age and relocation

Age groups

No

Yes

18-25 Yrs.

42.86%

57.14%

26-40 Yrs.

42.59%

57.41%

41-60 Yrs.

44.44%

55.56%

Grand Total

43.00%

57.00%

Table 10

Income and relocation

Income levels

No

Yes

Grand Total

Less than 5 lakhs

36.36%

63.64%

100.00%

5-10 lakhs

51.61%

48.39%

100.00%

10-25 lakhs

41.94%

58.06%

100.00%

25 lakhs+

37.50%

62.50%

100.00%

Grand Total

43.00%

57.00%

100.00%

Table 11

Pay cut and income levels

Income levels

No

Yes

Grand Total

10-25 lakhs

83.87%

16.13%

100.00%

25 lakhs+

75.00%

25.00%

100.00%

5-10 lakhs

70.97%

29.03%

100.00%

Less then 5 lakhs

68.18%

31.82%

100.00%

Grand Total

75.00%

25.00%

100.00%

Table 12

Pay cut and age groups

Age groups

No

Yes

Grand Total

18-25 Yrs.

71.43%

28.57%

100.00%

26-40 Yrs.

75.93%

24.07%

100.00%

41-60 Yrs.

77.78%

22.22%

100.00%

Grand Total

75.00%

25.00%

100.00%

Table 13

Paycut and gender

Gender

No

Yes

Grand Total

Female

73.81%

26.19%

100.00%

Male

75.86%

24.14%

100.00%

Grand Total

75.00%

25.00%

100.00%

Table 14

Work from home and psycho-social indicators

Psycho-social indicators

Yes

No

Can't say

Better Family Relations

66

14

20

More Productivity

54

33

13

Better Sleep

58

32

10

More Exercise

59

36

5

Loneliness

68

27

5

Conclusion

This research study talks about the employee’s perception towards WFH considering their different age groups, income levels, qualification, gender, commuting time before COVID. It also talks about the relation between relocation and WFH and the psycho-social impacts of WFH.

  1. The final analysis states that males and the middle age group from 26-40 have showed preference towards work from home, exclusive or blended, as compared to their other counterparts.

  2. Also, as the income level goes up the preference for hybrid model increases with 75% of people wanting the blended mode under the income group of 25 lakhs and above.

  3. An extremely strong relationship has been observed for the travel time and preference towards WFH. Those who took more commuting time to their offices before COVID want to continue with WFH or the blended mode, while those who took less commuting time want to continue either with the blended mode or WFO. There is one more important thing in this context that those who took more commuting time preferred the blended mode with predominantly WFH while there is not much difference for the blended mode for the ones who took less than an hour.

  4. Further, those who believed that WFH increased productivity want to continue with it while the others want to continue with WFO.

  5. We have found through our analysis that women are more willing to relocate as compared to men. Also, people with low income (below 5 lakhs) and the ultra-rich (25 lakhs+) are the most willing to relocate. Although 57% of the respondents are willing to relocate to their hometowns or scenic destinations but only 25% are ready to take a pay cut for that. From this 25% the people with low income and the ultra-rich are most willing to shell out for the flexibility of work from anywhere and relocation. Almost all the age groups, and both the genders are unwilling to take a pay cut for the option of Work from Anywhere.

  6. For the psycho-social impacts, every 2 out of 3 people believe WFH improved their family relations. 54%, 58%, 59% of the respondents believe it improved productivity, increased sleep and increased exercise respectively. However, 68% of the respondents experienced loneliness due to WHF.

Thus, we can conclude by saying that One Size Does Not Fit All. Productivity increases the most when the one who wants to work from office gets to work from office and the one who wants to work from home gets to work from home. Another way could be that the firms consider the blended mode and can fix some number of days when the person can or cannot choose to work from home.

Limitations

Service sector had an advantage over the production sector due to WFH. WFH catered mainly to the service sector. Thus, this study does not include all the sectors. People from all the sectors cannot work from home given the different inputs used in the production process. For instance, Industrial sector cannot produce anything with its labor sitting at home. Thus, this study excludes potential workers and students as they are not doing WFH. Moreover, this study is limited to the perspectives of workers and hence, does not include the perspectives of the firms.

Future prospects

This study shows how there are varied preferences among the employees towards WFH. Some are more comfortable with WFH, some are comfortable with WFO while some want a blended work culture. Thus, further studies can be conducted to choose Online, Offline, Hybrid work culture in organization and to understand the causes of varied preferences as shown by the respondents in the research conducted above. Along with that further study can be conducted on the possibility of pay cut and cost-cutting measures with WFH. This study is limited to the perspectives of the workers; thus, the further studies can involve the other side and the perspectives of the firm. It could also talk about the potential of co-working spaces.

Source of Funding

None.

Conflict of Interest

None.

References

1 

S Bhattacharjee Work from Home as an alternative to daily commuting for working womenJ Stud Res hum Geography20201421843658710.5719/hgeo.2020.142.5

2 

S Raju V K Kumar Quality of life of women working from home in COVID-19 lockdown: a questionnaire surveyInt J Community Med Public Health20207102394603210.18203/2394-6040.ijcmph20204359

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L D Renzo P Gualtieri F Pivari L Soldati A Attinà G Cinelli Eating habits and lifestyle changes during COVID-19 lockdown: an Italian surveyJ Transl Med202018122910.1186/s12967-020-02399-5

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J P Ramos Y T Prasetyo The Impact of Work-Home Arrangement on the Productivity of Employees during COVID-19 Pandemic in the Philippines: A Structural Equation Modelling ApproachResearchGate 202013540 10.1145/3429551.3429568

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N Ghayathri S M Benita Impact of work from home on employee wellbeing during pandemicJ Contemp Business Government202022442610.47750/cibg.2020.26.02.057

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I brief Working from Home: Estimating the worldwide potentialInt Labour OrganisationApril 2020https://www.ilo.org/wcmsp5/groups/public/---ed_protect/---protrav/---travail/documents/briefingnote/wcms_743447.pdf

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A D Dubey S Tripathi Analysing the Sentiments towards Work-From-Home Experience during COVID-19 PandemicJ Innov Manag202081131910.24840/2183-0606_008.001_0003



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Article type

Original Article


Article page

79-89


Authors Details

Anshita Banga, Fiza Mahajan


Article History

Received : 08-05-2021

Accepted : 12-05-2021


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