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• Published: 12 June 2024

Hybrid working from home improves retention without damaging performance

• Nicholas Bloom   ORCID: orcid.org/0000-0002-1600-7819 1   na1 ,
• Ruobing Han   ORCID: orcid.org/0000-0001-9126-5503 2   na1 &
• James Liang 3 , 4  

Nature ( 2024 ) Cite this article

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Working from home has become standard for employees with a university degree. The most common scheme, which has been adopted by around 100 million employees in Europe and North America, is a hybrid schedule, in which individuals spend a mix of days at home and at work each week 1 , 2 . However, the effects of hybrid working on employees and firms have been debated, and some executives argue that it damages productivity, innovation and career development 3 , 4 , 5 . Here we ran a six-month randomized control trial investigating the effects of hybrid working from home on 1,612 employees in a Chinese technology company in 2021–2022. We found that hybrid working improved job satisfaction and reduced quit rates by one-third. The reduction in quit rates was significant for non-managers, female employees and those with long commutes. Null equivalence tests showed that hybrid working did not affect performance grades over the next two years of reviews. We found no evidence for a difference in promotions over the next two years overall, or for any major employee subgroup. Finally, null equivalence tests showed that hybrid working had no effect on the lines of code written by computer-engineer employees. We also found that the 395 managers in the experiment revised their surveyed views about the effect of hybrid working on productivity, from a perceived negative effect (−2.6% on average) before the experiment to a perceived positive one (+1.0%) after the experiment. These results indicate that a hybrid schedule with two days a week working from home does not damage performance.

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Working from home (WFH) surged after the COVID-19 pandemic, with university-graduate employees typically WFH for one to two days a week during 2023 (refs. 2 , 6 ). Previous causal research on WFH has focused on employees who are fully remote, usually working on independent tasks in call-centre, data-entry and helpdesk roles. This literature has found that the effects of fully remote working on productivity are often negative, which has resulted in calls to curtail WFH 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 . However, there are two challenges when it comes to interpreting this literature. First, more than 70% of employees WFH globally are on a hybrid schedule. This group comprises more than 100 million individuals, with the most common working pattern being three days a week in the office and two days a week at home 2 , 8 , 9 . Second, most employees who are regularly WFH are university graduates in creative team jobs that are important in science, law, finance, information technology (IT) and other industries, rather than performing repetitive data-entry or call processing tasks 10 , 11 .

This paper addresses the gap in previous studies in two key ways. First, it uses a randomized control trial to examine the causal effect of a hybrid schedule in which employees are allowed to WFH two days per week. Second, it focuses on university-graduate employees in software engineering, marketing, accounting and finance, whose activities are mainly creative team tasks.

Our study describes a randomized control trial from August 2021 to January 2022, which involved 1,612 graduate employees in the Airfare and IT divisions of a large Chinese travel technology multinational called Trip.com. Employees were randomized by even or odd birthdays into the option to WFH on Wednesday and Friday and come into the office on the other three days, or to come into the office on all five days.

We found that in the hybrid WFH (‘treatment’) group, attrition rates dropped by one-third (mean control  = 7.20, mean treat  = 4.80, t (1610) = 2.02, P  = 0.043) and work satisfaction scores improved (mean control  = 7.84, mean treat  = 8.19, t (1343) = 4.17, P  < 0.001). Employees reported that WFH saved on commuting time and costs and afforded them the flexibility to attend to occasional personal tasks during the day (and catch up in the evenings or weekends). These effects on reduced attrition were significant for non-managerial employees (mean control  = 8.59, mean treat  = 5.33, t (1215) = 2.23, P  = 0.026), female employees (mean control  = 9.19, mean treat  = 4.18, t (568) = 2.40, P  = 0.017) and those with long (above-median) commutes (mean control  = 6.00, mean treat  = 2.89, t (609) = 1.87, P  = 0.062).

At the same time, we found no evidence of a significant effect on employees’ performance reviews, on the basis of null equivalence tests, and no evidence of a difference in promotion rates over periods of up to two years (‘Null results’ section of the Methods ). We did find significant differences in pre-experiment beliefs about the effects of WFH on productivity between non-managers and managers. Before the experiment, managers tended to have more negative views, reporting that hybrid WFH would be likely to affect productivity by −2.6%, whereas non-managers had more positive views (+0.7%) ( t (1313) = −4.56, P  < 0.001). After the experiment, the views of managers increased to +1.0%, converging towards non-managers’ views (mean non-manager  = 1.62, mean manager  = 1.05, t (1343) = −0.945, P  = 0.345). This highlights how the experience of hybrid working leads to a more positive assessment of its effect on productivity—consistent with the overall experience in Asia, the Americas and Europe throughout the pandemic, where perceptions of WFH improved considerably 13 .

The experiment

The experiment took place at Trip.com, the third-largest global travel agent by sales in 2019. Trip.com was established in 1999, was quoted on NASDAQ in 2003 and was worth about US$20 billion at the time of the experiment. It is headquartered in Shanghai, with offices across China and internationally, and has roughly 35,000 employees.

In the summer of 2021, Trip.com decided to evaluate the effects of hybrid WFH on the 1,612 engineering, marketing and finance employees in the Airfare and IT divisions, spanning 395 managers and 1,217 non-managers. All experimental participants were surveyed at baseline, with questions on expectations, background and their interest in volunteering for early participation in the experiment. The firm randomized employees with an odd-number birthday (born on the first, third, fifth and so on day of the month) into the treatment group.

Figure 1 shows two pictures of employees working in the office to highlight three points. First, in the second half of 2021, COVID incidence rates in Shanghai were so low that employees were neither masked nor socially distanced at the office. Although the COVID pandemic had led to lockdowns in early 2020 and during 2022, during the second half of 2021, Shanghai employees were free to come to work, and typically were unmasked in the office. Second, employees worked in modern open-plan offices in desk groupings of four or six colleagues from the same team, reflecting the importance of collaboration. Third, the office is a large modern building, similar to many large Asian, European and North American offices.

Pictures of Trip.com employees in the office during the experiment. The people in the experimental sample are typically in their mid-30s, and 65% are male. All of them have a university undergraduate degree and 32% have a postgraduate degree, usually in computer science, accounting or finance, at the master’s or PhD level. They have 6.4 years tenure on average and 48% of employees have children (Extended Data Table 1 ).

Effects on employee retention

One key motivation for Trip.com in running the experiment was to evaluate how hybrid WFH affected employee attrition and job satisfaction. The net effect was to reduce attrition over the experiment by 2.4%, which against the control-group base of 7.2% was a one-third (33%) reduction in attrition (mean control  = 7.20, mean treat  = 4.80, t (1610) = 2.02, P  = 0.043). Consistent with this reduction in quit rates, employees in the treatment group also registered more positive responses to job-satisfaction surveys (mean control  = 7.84, mean treat  = 8.19, t (1343) = 4.17, P  < 0.001). Employees were anonymously surveyed on 21 January 2022, and employees in the treatment group showed significantly higher scores on a scale from 0 (lowest) to 10 (highest) in ‘work–life balance’, ‘work satisfaction’, ‘life satisfaction’ and ‘recommendation to friends’, and significantly lower scores in ‘intention to quit’ (Extended Data Table 2 ).

One possible explanation for the lower quit rates in the treatment group is that quit rates in the control group increased because the individuals in this group were annoyed about being randomized out of the experiment. However, quit rates in the same Airfare and IT divisions were 9.8% in the six months before the experiment—higher than the rate for the control group during the experimental period. Quit rates over the experimental period in the two other Trip.com divisions for which we have data (Business Trips and Marketing) were 10.5% and 9.8%—again higher than that for the control group during the experimental period. This suggests that, if anything, the control-group quit rates were reduced rather than increased by the experiment, possibly because some of them guessed (correctly) that the policy would be rolled out to all employees once the experiment ended.

Figure 2 shows the change in attrition rates by three splits of the data. First, we examined the effect on attrition for the 1,217 non-managers and 395 managers separately. We saw a significant drop in attrition of 3.3 percentage points for the non-managers, which against a control-group base of 8.6% is a 40% reduction (mean control  = 8.59, mean treat  = 5.33, t (1215) = 2.23, P  = 0.026). By contrast, there was an insignificant increase in attrition for managers (mean control  = 2.96, mean treat  = 3.13, t (393) = −0.098, P  = 0.922). We also found that non-managers were more enthusiastic before the experiment, with a volunteering rate of 35% (versus 22% for managers), matching the media sentiment that although non-managerial employees are enthusiastic about WFH, many managers are not ( t (1610) = 4.86, P  < 0.001).

Data on 1,612 employees’ attrition until 23 January 2022. Top left, all employees. Only 1,259 employees filled out the baseline survey question on commuting length, so the commute-length (two ways) sample is for 1,259 employees. Sample sizes are 820 and 792 for control and treatment; 1,217 and 395 for non-managers and managers; 570 and 1,042 for women and men; and 648 and 611 for short and long commuters, respectively. Two-tailed t -tests for the attrition difference within each group between the control and treatment groups are (difference = 2.40, s.e. = 1.18, confidence interval (CI) = [0.0748, 4.72], P  = 0.043) for all employees; (difference = 3.26, s.e. = 1.46, CI = [0.392, 6.12], P  = 0.026) for non-managers; (difference = −0.169, s.e. = 1.73, CI = [−3.57, 3.23], P  = 0.922) for managers; (difference = 5.01, s.e. = 2.08, CI = [0.915, 9.10], P  = 0.017) for women; (difference = 0.997, s.e. = 1.43, CI = [−1.82, 3.81], P  = 0.487) for men; (difference = 2.61, s.e. = 1.93, CI = [−1.19, 6.41], P  = 0.178) for employees with median (90 min, two-way) or shorter commutes; and (difference = 3.11, s.e. = 1.66, CI = [−0.156, 6.37], P  = 0.062) for above-median (90 min, two-way) commuters.

Second, we examined the effect on attrition by total commute length, splitting the sample into people with shorter and longer total commutes on the basis of the median commute duration (two-way commutes of 1.5 h or less versus those exceeding 1.5 h, with 648 and 611 employees, respectively). We found that there was a larger reduction in quit rates (52%) for those with a long commute (mean control  = 6.00, mean treat  = 2.89, t (609) = 1.87, P  = 0.062). The reduction in quit rates was similarly large for employees with a long commute if we instead defined a long commute as a two-way commute time exceeding 2 h (mean control  = 7.33, mean treat  = 1.89, t (307) = 2.31, P  = 0.021). Employees who volunteered to take part in the experiment had longer one-way commute durations (Extended Data Table 3 ; mean non-volunteer  = 0.80, mean volunteer  = 0.89, t (1257) = −3.68, P  < 0.001). This is not surprising given that the most frequently cited benefit of WFH is no commute 1 .

Third, we examined the effect on attrition by gender, examining the 570 female and 1,042 male employees separately. We found that there was a 54% reduction in quit rates for female employees (mean control  = 9.2, mean treat  = 4.2, t (568) = 2.40, P  = 0.017). For male employees, there was an insignificant 16% reduction in quit rates (mean control  = 6.15, mean treat  = 5.15, t (1040) = 0.70, P  = 0.487). This greater reduction in quit rates among female individuals echoes the findings of previous studies 6 , 14 , 15 , 16 , which suggest that women place greater value on remote work than men do. Notably, although the treatment effect of WFH was significantly larger for female employees, volunteers were less likely to be female (mean non-volunteer  = 0.37, mean volunteer  = 0.32, t (1610) = −2.02, P  = 0.043); this might suggest that women have greater concerns about negative career signalling by volunteering to WFH.

Employee performance and promotions

Another key question for Trip.com was the effect of hybrid WFH on employee performance. To assess that, we examined four measures of performance: six-monthly performance reviews and promotion outcomes for up to two years after the start of the experiment, detailed performance evaluations, and the lines of code written by the computer engineers. We also collected self-assessed productivity effects of hybrid working from experimental participants before and after the experiment to evaluate employee perceptions.

Performance reviews are important within Trip.com as they determine employees’ pay and career progression, so are carefully conducted. The review process for each employee is built on formal assessments provided by their managers, co-workers, direct reports and, if appropriate, customers. They are reviewed by employees, collated by managers and by the human resources team, and then discussed between the manager and the employee. This lengthy process takes several weeks, providing a well-grounded measure of employee performance. Although these reviews are not perfect, given their tight link to pay and career development, both managers and employees put a large amount of effort into making these informative measures of performance.

Figure 3 reports the distribution of performance grades for treatment and control employees for the four half-year periods: July to December 2021, January to June 2022, July to December 2022 and January to June 2023. These four performance reviews span a two-year period from the start of the experimental period. Across all review periods, we found no difference in reviews between the treatment and control groups (Extended Data Table 4 and ‘Null results’ section of the Methods ).

Results from performance reviews of 1,507 employees in July–December 2021, 1,355 employees in January–June 2022, 1,301 employees in July–December 2022 and 1,254 employees in January–June 2023. Samples are lower over time owing to employee attrition from the original experimental sample. Two-tailed t -tests for the performance difference within each period between the control and treatment groups, after assigning each letter grade a numeric value from 1 (D) to 5 (A), are (difference = 0.056, s.e. = 0.043, CI = [−0.029, 0.14], P  = 0.198) for July–December 2021; (difference = 0.034, s.e. = 0.044, CI = [−0.0529, 0.122], P  = 0.440) for January–June 2022; (difference = −0.019, s.e. = 0.046, CI = [−0.11, 0.072], P  = 0.677) for July to December 2022; and (difference = 0.046, s.e. = 0.051, CI = [−0.054, 0.146], P  = 0.369) for January–June 2023. The null equivalence tests are included in the ‘Null results’ section of the Methods .

Figure 4 reports the distribution of promotion outcomes for the treatment and control employees for the same periods. We see no evidence of a difference in promotion rates across treatment and control employees. This is an important result given the evidence that fully remote working can damage employee development and promotions 14 , 17 , 18 .

Promotion outcomes for 1,522 employees in July–December 2021, 1,378 employees in January–June 2022, 1,314 employees in July–December 2022 and 1,283 employees in January–June 2023. Samples are lower over time owing to employee attrition from the original experimental sample. Two-tailed t -tests for the promotion difference within each period between the control and treatment groups are (difference = −0.86, s.e. = 1.34, CI = [−3.51, 1.74], P  = 0.509) for July–December 2021 promotions; (difference = 0.12, s.e. = 0.85, CI = [−1.54, 1.78], P  = 0.892) for January–June 2022 promotions; (difference = −0.51, s.e. = 1.12, CI = [−2.72, 1.70], P  = 0.651) for July–December 2022 promotions; and (difference = −0.99, s.e. = 1.02, CI = [−2.99, 1.00], P  = 0.328) for January–June 2023 promotions. The null equivalence tests are included in the ‘Null results’ section of the Methods .

We also analysed the effects of treatment on performance grades and promotions for a variety of subgroups, including managers, employees with a manager in the treatment group, longer-tenured employees, longer-commuting employees, women, employees with children, computer engineers and those living further away, as well as looking at whether internet speed had any effect. We found no evidence of a difference in response to treatment across these groups (Extended Data Table 5 ).

The experiment also analysed two other measures of employee performance. First, the performance reviews at Trip.com have subcomponents for individual activities such as ‘innovation’, ‘leadership’, ‘development’ and ‘execution’ (nine categories in all) when these are important for an individual employee’s role. We collected these data and analysed these scores for the four six-month performance review periods. We found no evidence of a difference across these nine major categories over the four performance review periods (Extended Data Table 6 ). This indicates that for categories that involve softer skills or more team-focused activities—such as development and innovation—there is no evidence for a material effect of being randomized into the hybrid WFH treatment. Second, for the 653 computer engineers, we obtained data on the lines of code uploaded by each engineer each day. For this ‘lines of code submitted’ measure, we found no difference between employees in the control and treatment groups (Extended Data Fig. 1 and ‘Null results’ section of the Methods ).

Self-assessed productivity

All experiment participants were polled before the experiment in a baseline survey on 29 and 30 July 2021, which included a two-part question on their beliefs about the effects of hybrid WFH on productivity. Employees were asked ‘What is your expectation for the impact of hybrid WFH on your productivity?’, with three options of ‘positive’, ‘about the same’ or ‘negative’. Individuals who chose the answer ‘positive’ were then offered a set of options asking how positive they felt, ranging from [5% to 15%] up to [35% or more], and similarly so for negative choices. For aggregate impacts we took the mid-points of each bin, and 42.5% for >35% and –42.5% for <−35%. Employees were resurveyed with the same question after the end of the experiment on 21 January 2022.

The left panel of Fig. 5 shows that employees’ pre-experimental beliefs about WFH and productivity were extremely varied. The baseline mean was –0.1%, but with widespread variation (standard deviation of 11%). This spread should be unsurprising to anyone who has been following the active debate about the effects of remote work on productivity. At the end-line survey conducted on 21 January 2022, the mean of these beliefs had significantly increased to 1.5%, revealing that the experience of hybrid working led to a small improvement in average employee beliefs about the productivity impact of hybrid working (mean baseline  = −0.06%, mean endline  = 1.48%, t (2658) = −3.84, P  < 0.001). This could be because hybrid WFH saves employees commuting time and is less physically tiring, and, with intermittent breaks between group time and quiet individual time, can improve performance 19 , 20 , 21 , 22 .

Sample from 1,315 employees (314 managers, 1,001 non-managers) at the baseline and 1,345 employees (324 managers, 1,021 non-managers) at the end line. Two-tailed t -tests for the difference in productivity expectations between baseline and end line, after assigning a numeric value corresponding to the midpoint of the bucket, are (baseline mean = −0.058, end-line mean = 1.48, difference = −1.54, s.e. = 0.40, CI = [−2.33, −0.753], P  < 0.001). Two-tailed t -tests for the baseline difference between the productivity expectations of managers and non-managers are (difference = −3.28, s.e. = 0.72, CI = [−4.69, −1.86], P  < 0.001), and the t -tests for the end-line difference are (difference = −0.571, s.e. = 0.604, CI = [−1.76, 0.615], P  = 0.345).

The right panel of Fig. 5 shows that in the baseline survey, managers were negative about the perceived effect of hybrid work on their productivity, with a mean effect of −2.6%. Non-managers, by contrast, were significantly more positive, at +0.7% in the baseline survey (mean non-manager  = 0.7%, mean manager  = −2.6%, t (1313) = −4.56, P  < 0.001). At the end of the experiment, the views of managers improved to 1.0%, with no evidence of a difference from the non-managers’ mean value of 1.6% (mean non-manager  = 1.62%, mean manager  = 1.05%, t (1343) = −0.95, P  = 0.345). Hence, the experiment led managers to positively update their views about how hybrid WFH affects productivity, and to more closely align with non-managers.

Of note, we saw that employees in the treatment and control groups had similar increases in self-assessed productivity (difference 0.58%, s.d. = 0.59%). Employees from four other divisions in Trip.com were also polled about the productivity impact of hybrid WFH after the end of the experiment in March 2022, with a mean estimate of +2.8% on a sample of 3,461 responses—similar to the 1.5% end line for the experimental sample. This suggests that even close exposure to hybrid WFH is sufficient for employees to change their views, consistent with previous evidence of a positive society-wide shift in perceptions about WFH productivity after the 2020 pandemic 8 .

Once the experiment ended, the Trip.com executive committee examined the data and voted to extend the hybrid WFH policy to all employees in all divisions of the company with immediate effect. Their logic was that each quit cost the company approximately US$20,000 in recruitment and training, so a one-third reduction in attrition for the firm would generate millions of dollars in savings. This was publicly announced on 14 February 2022, with wide coverage in the Chinese media. Since then, other Chinese tech firms have adopted similar hybrid policies 23 .

This highlights how, contrary to the previous causal research focused on fully remote work, which found mostly negative effects on productivity 5 , 6 , 7 , hybrid remote work can leave performance unchanged. This suggests that hybrid working can be profitably adopted by organizations, given its effect on reducing attrition, which is estimated to cost about 50% of an individual’s annual salary for graduate employees 24 . Hybrid working also offers large gains for society by providing a valuable amenity (perk) to employees, reducing commuting and easing child-care 6 , 25 , 26 .

The experiment was conducted in a Chinese technology firm based in Shanghai. Although it might not be possible to replicate these results perfectly in other situations, Trip.com is a large multinational firm with global suppliers, customers and investors. Its offices are modern buildings that look similar to those in many American, Asian and European cities. Trip employees worked 8.6 h per day on average, close to the 8 h per day that is usual for US graduate employees 27 . The business had a large drop in revenue in 2020 (see Extended Data Fig. 4 ), followed by roughly flat revenues through the 2021 experiment period into 2022, so this was not a period of exceptionally fast or slow growth. As such, we believe that these results— that is, the finding that allowing employees to WFH two days per week reduces quit rates and has a limited effect on performance—would probably extend to other organizations. Also, this experiment analysed the effects of working three days per week in the office and two days per week from home. So, our findings might not replicate to all other hybrid work arrangements, but we believe that they could extend to other hybrid settings with a similar number of days in the office, such as two or four days a week. We are not sure whether the results would extend to more remote settings such as one day a week (or less) in the office, owing to potential challenges around training, innovating and culture in fully remote settings.

Finally, we should point out two implications of the experimental design. First, full enrolment into hybrid schemes is important because of concerns that volunteering might be seen as a negative signal about career ambitions. The low volunteer rate among female employees, despite their high implied value (from the large reductions in quit rates observed), is particularly notable in this regard. Second, there is value in experimentation. Before the experiment, managers were net-negative in their views on the productivity impact of hybrid working, but after the experiment, their views became net-positive. This highlights the benefits of experimentation for firms to evaluate new working practices and technologies.

Location and set-up

Our experiment took place at Trip.com in Shanghai, China. In July 2021, Trip.com decided to evaluate hybrid WFH after seeing its popularity amongst US tech firms. The first step took place on 27 July 2021, when the firm surveyed 1,612 eligible engineers, marketing and finance employees in the Airfare and IT divisions about the option of hybrid WFH. They excluded interns and rookies who were in probation periods because on-site learning and mentoring are particularly important for those individuals. Trip.com chose these two divisions as representative of the firm, with a mix of employee types to assess any potentially heterogeneous impacts. About half of the employees in these divisions are technical employees, writing software code for the website, and front-end or back-end operating systems. The remainder work in business development, with tasks such as talking to airlines, travel agents or vendors to develop new services and products; in market planning and executing advertising and marketing campaigns; and in business services, dealing with a range of financial, regulatory and strategy issues. Across these groups, 395 individuals were managers and 1,217 non-managers, providing a large enough sample of both groups to evaluate their response to hybrid WFH.

Randomization

The employees were sent an email outlining how the six-month experiment offered them the option (but not the obligation) to WFH on Wednesday and Friday. After the initial email and two follow-up reminders, a group of 518 employees volunteered. The firm randomized employees with odd birthdays—those born on the first, third, fifth and so on of the month—into eligibility for the hybrid WFH scheme starting on the week of 9 August. Those with even birthdays—born on the second, fourth, sixth and so on of the month—were not eligible, so formed the control group.

The top management at the firm was surprised at the low volunteer rate for the optional hybrid WFH scheme. They suspected that many employees were hesitating because of concerns that volunteering would be seen as a negative signal of ambition and productivity. This is not unreasonable. For example, a previous study 28 found in the US firm they evaluated that WFH employees were negatively selected on productivity. So, on 6 September, all of the remaining 1,094 non-volunteer employees were told that they were also included in the program. The odd-birthday employees were again randomized into the hybrid WFH treatment and began the experiment on the week of 13 September. In this paper we analyse the two groups together, but examining the volunteer and non-volunteer groups individually yields similar findings of reduced quit rates and no impact on performance.

Employee characteristics and balancing tests

Figure 1 shows some pictures of employees working in the office (left side). Employees all worked in modern open-plan offices in desk groupings of four or six colleagues from the same team. By contrast, when WFH, they usually worked alone in their apartments, typically in the living room or kitchen (see Extended Data Fig. 2 ).

The individuals in the experimental sample are typically in their mid-30s. About two-thirds are male, all of them have a university undergraduate degree and almost one-third have a graduate degree (typically a master’s degree). In addition, nearly half of the employees have children (details in Extended Data Table 1 ).

In Extended Data Table 7 we confirm that this sample is also balanced across the treatment and control groups, by conducting a two-sample t -test. The exceptions are from random variation given that the sampling was by even or odd day-of-month birthday—the control sample is 0.5 years older ( P  = 0.06), and this is presumably linked to why those in this group have 0.06% more children ( P  = 0.02) and 0.4 years more tenure ( P  = 0.09).

In Extended Data Table 3 , we examine the decision to volunteer for the WFH experiment. We see that volunteers were significantly less likely to be managers (mean non-volunteer  = 0.28, mean volunteer  = 0.17, t (1610) = −4.85, P  < 0.001) and had longer commute times (hours) (mean non-volunteer  = 0.80, mean volunteer  = 0.89, t (1257) = 3.68, P  < 0.001). Notably, we don’t find evidence of a relationship between volunteering and previous performance scores (mean non-volunteer  = 3.81, mean volunteer  = 3.81, t (1580) = −0.02, P  = 0.985), highlighting, at least in this case, the lack of evidence for any negative (or positive) selection effects around WFH.

Extended Data Fig. 3 plots the take-up rates of WFH on Wednesday and Friday by volunteer and non-volunteer groups. We see a few notable facts. First, take-up overall was about 55% for volunteers and 40% for non-volunteers, indicating that both groups tended to WFH only one day, typically Friday, each week. At Trip.com, large meetings and product launches often happen mid-week, so Fridays are seen as a better day to WFH. Second, the take-up rate even for non-volunteers was 40%, indicating that Trip.com’s suspicion that many employees did not volunteer out of fear of negative signalling was well-founded, and highlighting that amenities like WFH, holiday, maternity or paternity leave might need to be mandatory to ensure reasonable take-up rates. Third, take-up surged on Fridays before major holidays. Many employees returned to their home towns, using their WFH day to travel home on the quieter Thursday evening or Friday morning. Finally, take-up rates jumped for both treatment-group and control-group employees in late January 2022 after a case of COVID in the Shanghai headquarters. Trip.com allowed all employees at that point to WFH, so the experiment effectively ended early on Friday 21 January. The measure of an employee’s daily WFH take-up excludes leave, sick leave or occasions when they cannot come to the office owing to extreme bad weather (typhoon) or to the COVID outbreak in the company.

Null results

To interpret the main null results, we conduct null equivalence tests using the two one-sided tests (TOST) procedure in R (refs. 29 , 30 ). This test required us to specify the smallest effect size of interest (SESOI). For the results pertaining to performance review measures, we use 0.5 as the SESOI. This corresponds to half of a consecutive letter grade increase or decrease, because we had assigned numeric values to performance letter grades in increments of 1, with the lowest letter grade D being 1, and the highest letter grade A being 5. We performed equivalence tests for a two-sample Welch’s t -test using equivalence bounds of ±0.5. The TOST procedure yielded significant results using the default alpha of 0.05 for the tests against both the upper and the lower equivalence bounds for the performance measures for July–December 2021 ( t (1504) = −10.20, P  < 0.001)), January–June 2022 ( t (1353) = −10.57, P  < 0.001)), July–December 2022 ( t (1299) = 10.34, P  < 0.001)) and January–June 2023 ( t (1248) = −8.80, P  < 0.001)). The equivalence test is therefore significant, which means we can reject the hypothesis that the true effect of the treatment on performance is larger than 0.5 or smaller than −0.5. So, we interpret the performance effects of the treatment to be actually null on the basis of the SESOI we used, as opposed to no evidence of a difference in performance.

We conducted null equivalence results for the effect of the treatment on promotions using 2 as the SESOI, corresponding to ±2 percentage points (pp) difference in promotion rates. Although we can reject the null hypothesis that the true effect of treatment on promotion is larger than 2 pp or smaller than −2 pp in January–June 2022 ( t (1376) = −2.22, P  = 0.013) and July–December 2022 ( t (1306) = 1.33, P  = 0.092), we fail to reject the null equivalence hypothesis in July–December 2021 ( t (1513) = 0.83, P  = 0.203) and January–June 2023 ( t (1250) = 0.98, P  = 0.163). Thus, we interpret the results on promotion as no evidence of a difference between promotion rates across treatment and control employees.

We also conducted the equivalence test for lines of code using 29 lines of code per day as the SESOI, which corresponds to 10% of the mean number of lines of code for the control group. We arrive at this SESOI on the basis of rounding down the productivity effects of previous findings 8 , 10 . We can reject the equivalence null hypothesis for lines of code ( t (92362) = −2.74, P  = 0.003)) so we interpret the effect of the treatment as a null effect.

Volunteer versus non-volunteer groups

In the main paper we pool the volunteer and non-volunteer groups. In Extended Data Table 5 we examine the impacts on performance and promotions and we see no evidence of a difference in performance and promotion treatment effects for volunteer versus non-volunteer groups (column 9).

Performance subcategories

The company has a rigorous performance-reviewing process every six months that determines employees’ pay and promotion, so is carefully conducted. The review process for each employee is built on formal reviews provided by their managers, project leaders and sometimes co-workers (peer review). Managers are more like an employee’s direct managers for organizational purposes, but for a particular project, the project leader could be another higher-level employee. In such a case, the manager of the employee would ask that project leader for an opinion on the employee’s contribution to the project. An individual’s overall score is a weighted sum of scores from various subcategories that managers have broad flexibility over defining, because tasks differ across employees, and managers would give a score for each task. For example, an employee running a team themselves will have subcategories around developing their direct reports (leadership and communication), whereas an employee running a server network will have subcategories around efficiency and execution. The performance subcategory data come from the text of the performance review. We first used the most popular Chinese word segmentation package in Python, named Jieba, to identify the most frequent Chinese words from task titles across four performance reviews. We also removed meaningless words and incorporated common expressions such as key performance indicators (‘KPI’), objectives and key results (‘OKR’), ‘rate’ and ‘%’. This process resulted in a total of 236 unique words and expressions. We then manually categorized those most frequent keywords into nine major subcategories (see below) by meanings and relevance. Finally, on the basis of the presence of keywords in the task title, tasks were grouped into the following subcategories:

Communication tasks are those that involve communication, collaboration, cooperation, coordination, participation, suggestion, assistance, organization, sharing and relationships.

Development tasks are those that involve coding or codes, data or datasets, systems, techniques and skills.

Efficiency tasks are those that involve cost reduction, ratios, return on investment (ROI), rate, %, improvement, growth, lifting, adding, optimizing, profit, receiving, gross merchandise value (GMV), OKR, KPI, work and goal.

Execution tasks are those that involve execution, conducting, maintenance, delivery, output, quality, contribution and workload.

Innovation tasks are those that involve development, R&D and innovation.

Leadership tasks are those that involve leadership, managing or management, approval, internal, strategy, coordination and planning.

Learning tasks are those that involve learning, growing, maturing, talent, ability, value competitiveness and personal improvement.

Project tasks are those that involve project, supply, product, business line, cooperation and clients.

Risk tasks are those that involve risk, compliance, supervision, recording and monitoring, safety, rules and privacy.

Data sources

Data were provided by a combination of Trip.com sources, including human resources records, performance reviews and two surveys. All data were anonymized and coded using a scrambled individual ID code, so no personally identifiable information was shared with the Stanford team. The data were drawn directly from the Trip.com administrative data systems on a monthly basis. Gender is collected by Trip.com from employees when they join the company.

The full sample has 1,612 experiment participants, but we have 1,507, 1,355, 1,301 and 1,254 employees, respectively, in the subsamples for the four performance reviews from July–December 2021, January–June 2022, July–December 2022 and January–June 2023. These smaller samples are due to attrition. In addition, for the first performance review in July–December 2021, 105 employees did not have sufficient pre-experiment tenure to support a performance review (they had joined the firm less than three months before the experimental draw). The review text data covers 1,507,1,339,1,290 and 1,246 people, as some employees do have an overall score and review text but do not have additional and task-specific scores. The reason is that these employees do not have the full range of all tasks, so their managers did not write the full review script. For the two surveys, Trip.com used Starbucks vouchers to incentivize response and collected responses from 1,315 employees (314 managers, 1,001 non-managers) at the baseline on the left, and that of 1,345 employees (324 managers, 1,021 non-managers) at the end line.

All tests used two-sided Student t -tests unless otherwise stated. Analysis was run on Stata v17 and v18, R version 4.2.2. Unless stated otherwise, no additional covariates are included in the tests. The null hypothesis for all of the tests excluding null equivalence tests is a coefficient of zero (for example, zero difference between treatment and control).

Inclusion and ethics statement

The design and execution of the experiment was run by Trip.com. No participants were forced to WFH owing to the experiment (the entire firm was, however, forced to WFH during the pandemic lockdown). The treatment sample had the option but not the obligation to WFH on Wednesday or Friday. The experiment was designed, initiated and run by Trip.com. N.B. and R.H. were invited to analyse the data from the experiment, with consent for data collection coming from Trip.com internally. The experiment was exempt under institutional review board (IRB) approval guidelines because it was designed and initiated by Trip.com, before N.B. and R.H. were invited to analyse the data. Only anonymous data were shared with the Stanford team. Trip.com based the experimental design and execution on their previous experience with WFH randomized control trials 17 .

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The data necessary to reproduce the primary results of this study can be found at https://doi.org/10.7910/DVN/6X4ZZL . These data have been anonymized and split into individual files to ensure that no individual is identifiable. All figures and tables can be replicated using this data.

Code availability

The code necessary to reproduce the primary results of this study can be found at https://doi.org/10.7910/DVN/6X4ZZL .

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Acknowledgements

We thank the Smith Richardson Foundation for funding; J. Cao, T. Zhang, S. Ye, F. Chen, X. Zhang, Y. He, J. Li, B. Ye and M. Akan for data, advice and logistical support; D. Yilin for research assistance; S. Ayan, S. Buckman, S. Gurung, M. Jackson and P. Lambert for draft feedback; and J. Sun for project leadership.

Author information

These authors contributed equally: Nicholas Bloom, Ruobing Han

Authors and Affiliations

Department of Economics, Stanford University, Stanford, CA, USA

Nicholas Bloom

Shenzhen Finance lnstitute, School of Management and Economics, The Chinese University of Hong Kong, Shenzhen, China

Ruobing Han

National School of Development, Peking University, Beijing, China

James Liang

Trip.com, Shanghai, China

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Contributions

N.B. oversaw the analysis, presented the results and wrote the main drafts of the paper. He was the principal investigator on the research grant supporting the research. R.H. supervised data collection and analysed the data, presented the results and helped to draft the paper. J.L. initiated and designed the study, discussed the results and analysis and facilitated the Trip.com engagement. N.B. and R.H. are co-first authors.

Corresponding authors

Correspondence to Nicholas Bloom , Ruobing Han or James Liang .

Ethics declarations

Competing interests.

No funding was received from Trip.com. J.L. is the co-founder, former CEO and current chairman of Trip.com, with equity holdings in Trip.com. No other co-author has any financial relationship with Trip.com. Neither the results nor the paper was pre-screened by anyone. The experiment was registered with the American Economic Association on 16 August 2021 after the experiment had begun but before N.B. and R.H. had received any data. Only anonymous data were shared with the Stanford team.

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Extended data figures and tables

Extended data fig. 1 wfh had no effect on lines of code written..

The data coves the experimental period starting on 9 August 2021 for the first wave and 13 September for the second wave, running to 23 January 2022, for both waves. Lines of code submitted per day is available for 653 employees whose primary role was writing code, spanning a total of 95,494 days. Lines are those uploaded to trip.com on a daily basis. Data plotted on a log-2 scale for readability. Reported P value is calculated using a two-sided t -test on the number of code lines and the difference is for control minus treatment. When using log 2 (code lines) the difference has a P value of 0.750 (noting the sample is 27,605 days because of dropping 0 values). When using log 2 (1 + code lines) the difference has a P value of 0.0103, with treatment having the higher average values. The null equivalence tests are included in the ‘Null results’ section of the Methods .

Extended Data Fig. 2 Home (October 2021).

Employees set up basic working environments in their living rooms, studies, or kitchens, and bring back company laptops if necessary.

Extended Data Fig. 3 Take-up rate for WFH treatment and control by volunteer status.

Data for 1,612 employees from 9 August 2021 (volunteers) and 13 September (non-volunteers) to 23 January 2022. Public holidays, personal holidays and excused absence (for example, sick leave) are excluded. Take-up rate is percentage of Wednesday and Friday each week they WFH.

Extended Data Fig. 4 Trip.com revenues.

Trip.com revenues from 2000 to 2023.

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Bloom, N., Han, R. & Liang, J. Hybrid working from home improves retention without damaging performance. Nature (2024). https://doi.org/10.1038/s41586-024-07500-2

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What’s next for remote work: An analysis of 2,000 tasks, 800 jobs, and nine countries

For many workers, COVID-19’s impact has depended greatly on one question: Can I work from home or am I tethered to my workplace? Quarantines, lockdowns, and self-imposed isolation have pushed tens of millions around the world to work from home, accelerating a workplace experiment that had struggled to gain traction before COVID-19 hit.

Now, well into the pandemic, the limitations and the benefits of remote work are clearer. Although many people are returning to the workplace as economies reopen—the majority could not work remotely at all—executives have indicated in surveys that hybrid models of remote work  for some employees are here to stay. The virus has broken through cultural and technological barriers that prevented remote work in the past, setting in motion a structural shift in where work takes place, at least for some people.

Now that vaccines are awaiting approval, the question looms: To what extent will remote work persist ? In this article, we assess the possibility for various work activities to be performed remotely. Building on the McKinsey Global Institute’s body of work on automation, AI, and the future of work, we extend our models to consider where work is performed. 1 The future of work in Europe: Automation, workforce transitions, and the future geography of work , McKinsey Global Institute, June 2020; The future of work in America: People and places, today and tomorrow , McKinsey Global Institute, July 2019; Jobs lost, jobs gained: Workforce transitions in a time of automation , McKinsey Global Institute, December 2017. Our analysis finds that the potential for remote work is highly concentrated among highly skilled, highly educated workers in a handful of industries, occupations, and geographies.

More than 20 percent of the workforce could work remotely three to five days a week as effectively as they could if working from an office. If remote work took hold at that level, that would mean three to four times as many people working from home than before the pandemic and would have a profound impact on urban economies, transportation, and consumer spending, among other things.

The virus has broken through cultural and technological barriers that prevented remote work in the past, setting in motion a structural shift in where work takes place, at least for some people.

More than half the workforce, however, has little or no opportunity for remote work. Some of their jobs require collaborating with others or using specialized machinery; other jobs, such as conducting CT scans, must be done on location; and some, such as making deliveries, are performed while out and about. Many of such jobs are low wage and more at risk from broad trends such as automation and digitization. Remote work thus risks accentuating inequalities at a social level.

The potential for remote work is determined by tasks and activities, not occupations

Remote work raises a vast array of issues and challenges for employees and employers. Companies are pondering how best to deliver coaching remotely and how to configure workspaces to enhance employee safety, among a host of other thorny questions raised by COVID-19. For their part, employees are struggling to find the best home-work balance and equip themselves for working and collaborating remotely.

In this article, however, we aim to granularly define the activities and occupations that can be done from home to better understand the future staying power of remote work. We have analyzed the potential for remote work—or work that doesn’t require interpersonal interaction or a physical presence at a specific worksite—in a range of countries, China, France, Germany, India, Japan, Mexico, Spain, the United Kingdom, and the United States. We used MGI’s workforce model based on the Occupational Information Network (O*NET) to analyze more than 2,000 activities in more than 800 occupations and identify which activities and occupations have the greatest potential for remote work.

The potential for remote work depends on the mix of activities undertaken in each occupation and on their physical, spatial, and interpersonal context. We first assessed the theoretical extent to which an activity can be done remotely. This depends on whether a worker needs to be physically present on-site to do a task, interact with others, or use location-specific machinery or equipment.

Many physical or manual activities, as well as those that require use of fixed equipment, cannot be done remotely. These include providing care, operating machinery, using lab equipment, and processing customer transactions in stores. In contrast, activities such as information gathering and processing, communicating with others, teaching and counseling, and coding data can theoretically be done remotely.

Additionally, employers have found during the pandemic that although some tasks can be done remotely in a crisis, they are much more effectively done in person. These activities include coaching, counseling, and providing advice and feedback; building customer and colleague relationships; bringing new employees into a company; negotiating and making critical decisions; teaching and training; and work that benefits from collaboration, such as innovation, problem-solving, and creativity. If onboarding were to be done remotely, for instance, it would require significant rethinking of the activity to produce outcomes similar to those achieved in person.

For instance, while teaching has moved to remote work during the pandemic, parents and teachers alike say that quality has suffered. Similarly, courtrooms have functioned remotely but are unlikely to remain online going forward out of concern for legal rights and equity—some defendants lack adequate connectivity and lawyers, and judges worry about missing nonverbal cues in video conferences.

So we have devised two metrics for remote work potential: the maximum potential, including all activities that theoretically can be performed remotely, and a lower bound for the effective potential for remote work, which excludes activities that have a clear benefit from being done in person (Exhibit 1).

To determine the overall potential for remote work for jobs and sectors, we use the time spent on different activities within occupations. We find that remote work potential is concentrated in a few sectors. Finance and insurance has the highest potential, with three-quarters of time spent on activities that can be done remotely without a loss of productivity. Management, business services, and information technology have the next highest potential, all with more than half of employee time spent on activities that could effectively be done remotely (Exhibit 2). These sectors are characterized by a high share of workers with college degrees or higher.

Remote work potential is higher in advanced economies

The potential for remote work varies across countries, a reflection of their sector, occupation, and activity mix. Business and financial services are a large share of the UK economy, for example, and it has the highest potential for remote work among the countries we examined. Its workforce could theoretically work remotely one-third of the time without a loss of productivity, or almost half the time but with diminished productivity. (Exhibit 3). Other advanced economies are not far behind; their workforces could dedicate 28 to 30 percent of the time to working remotely without losing productivity.

In emerging economies, employment is skewed toward occupations that require physical and manual activities in sectors like agriculture and manufacturing. The potential for time spent on remote work drops to 12 to 26 percent in the emerging economies we assessed. In India, for instance, the workforce could spend just 12 percent of the time working remotely without losing effectiveness. Although India is known globally for its high-tech and financial services industries, the vast majority of its workforce of 464 million is employed in occupations like retail services and agriculture that cannot be done remotely.

Although India is known globally for its high-tech and financial services industries, the vast majority of its workforce of 464 million is employed in occupations like retail services and agriculture that cannot be done remotely.

A hybrid model that combines some remote work with work in an office is possible for occupations with high remote work potential

For most workers, some activities during a typical day lend themselves to remote work, while the rest of their tasks require their on-site physical presence. In the US workforce, we find that just 22 percent of employees can work remotely between three and five days a week without affecting productivity, while only 5 percent could do so in India. In contrast, 61 percent of the workforce in the United States can work no more than a few hours a week remotely or not at all. The remaining 17 percent of the workforce could work remotely partially, between one and three days per week (Exhibit 4).

Consider a floral designer. We estimate that between half and one-quarter of his job can be done remotely. He can take orders by phone or online and contract for delivery through an app, but floral arrangement itself requires being in a shop where the flowers are stored in a refrigerated case and ribbons, moss, vases, and other materials used to create a floral design are at hand. To make a floral designer’s job more remote would require dividing his various tasks among all employees in a flower shop. In contrast, credit analysts, database administrators, and tax preparers, among others, can do virtually all of their work remotely. In general, workers whose jobs require cognitive thinking and problem solving, managing and developing people, and data processing have the greatest potential to work from home. These employees also tend to be among the highest paid.

The ability to work remotely also depends on the need to use specialized equipment. According to our analysis, a chemical technician could work remotely only a quarter of the time because much of her work must be done in a lab housing the equipment she needs. Among healthcare occupations, general practitioners who can use digital technologies to communicate with patients have a much greater potential for remote work than surgeons and x-ray technicians, who need advanced equipment and tools to do their work. Thus, among health professionals overall, the effective remote work potential is just 11 percent.

Even for the same activity, the context in which a job is done matters. Consider the activity “analyzing data or information,” which can be done remotely by a statistician or financial analyst but not by a surveyor. Crime scene analysts and workers who analyze consumer trends both engage in what O*NET describes as “getting, processing, analyzing, documenting and interpreting information,” but the former must go to the location of, say, a murder while the latter can do his work in front of a computer at home. A travel agent can calculate the cost of goods or services from a kitchen table, but a grocery clerk does that from behind a counter in a store.

And then there are jobs that require workers to be on-site or in person more than four days a week. Due to the physical nature of most of their work activities, occupations such as transportation, food services, property maintenance, and agriculture offer little or no opportunity for remote work. Building inspectors must go to a building or construction site. Nursing assistants must work in a healthcare facility. Many jobs declared essential by governments during the pandemic—nursing, building maintenance, and garbage collection, for example—fall into this category of jobs with low remote work potential.

This mixed pattern of remote and physical activities of each occupation helps explain the results of a recent McKinsey survey of 800 corporate executives  around the world. Across all sectors, 38 percent of respondents expect their remote employees to work two or more days a week away from the office after the pandemic, compared to 22 percent of respondents surveyed before the pandemic. But just 19 percent of respondents to the most recent survey said they expected employees to work three or more days remotely. This suggests that executives anticipate operating their businesses with a hybrid model  of some sort, with employees working remotely and from an office during the workweek. JPMorgan already has a plan for its 60,950 employees to work from home one or two weeks a month or two days a week, depending on the line of business.

Hybrid remote work has important implications for urban economies

Currently, only a small share of the workforce in advanced economies—typically between 5 and 7 percent—regularly works from home. A shift to 15 to 20 percent of workers spending more time at home and less in the office could have profound impacts on urban economies. More people working remotely means fewer people commuting between home and work every day or traveling to different locations for work. This could have significant economic consequences, including on transportation, gasoline and auto sales, restaurants and retail in urban centers, demand for office real estate, and other consumption patterns.

A McKinsey survey of office space managers conducted in May found that after the pandemic, they expect a 36 percent increase in worktime outside their offices, affecting main offices and satellite locations. This means companies will need less office space, and several are already planning to reduce real estate expenses. Moody’s Analytics predicts that the office vacancy rate in the United States will climb to 19.4 percent, compared to 16.8 percent at the end of 2019, and rise to 20.2 percent by the end of 2022. A survey of 248 US chief operating officers found that one-third plan to reduce office space in the coming years as leases expire.

The impact of that will reverberate through the restaurants and bars, shops, and services businesses that cater to office workers and will put a dent in some state and local tax revenues. For example, REI plans to sell off its new corporate headquarters before even moving in and instead begin operating from satellite offices. In contrast, Amazon recently signed leases for a total of 900,000 feet of office space in six cities around the United States, citing the lack of spontaneity in virtual teamwork.

As tech companies announced plans for permanent remote work options, the median price of a one-bedroom rental in San Francisco dropped 24.2 percent compared to a year ago, while in New York City, which had roughly 28,000 residents in every square mile at the start of 2020, 15,000 rental apartments were empty in September, the most vacancies in recorded history.

Nor is residential real estate immune from the impact of remote work. As tech companies announced plans for permanent remote work options, the median price of a one-bedroom rental in San Francisco dropped 24.2 percent compared to a year ago, while in New York City, which had roughly 28,000 residents in every square mile at the start of 2020, 15,000 rental apartments were empty in September, the most vacancies in recorded history. Conversely, bidding wars are breaking out in suburbs and smaller cities as remote workers seek less harried, less expensive lifestyles and homes with a room that can serve as an office or gym—though it is unclear how successful companies will be with workers scattered in far-flung locales.

Remote workers may also shift consumption patterns. Less money spent on transportation, lunch, and wardrobes suitable for the office may be shifted to other uses. Sales of home office equipment, digital tools, and enhanced connectivity gear have boomed.

Whether the shift to remote work translates into spreading prosperity to smaller cities remains to be seen. Previous MGI research in the United States and Europe has shown a trend toward greater geographic concentration of work  in megacities like London and New York and high-growth hubs, including Seattle and Amsterdam . These locales have attracted many of the same type of younger, highly educated workers who can best work remotely. It remains to be seen whether the shift to remote work slows that trend, or whether the most vibrant cities remain magnets for such people.

Organizations will have to adjust their practices to capture potential productivity gains from remote work

Is remote work good for productivity? Ultimately, the answer may determine its popularity, especially given the long period of waning labor productivity  that preceded the pandemic. So far, there is scant clarity—and widespread contradiction—about the productivity impact. Some 41 percent of employees who responded to a McKinsey consumer survey in May said they were more productive working remotely than in the office. As employees have gained experience working remotely during the pandemic, their confidence in their productivity has grown, with the number of people saying they worked more productively increasing by 45 percent from April to May.

With nine months of experience under their belts, more employers are seeing somewhat better productivity from their remote workers. Interviews with chief executives about remote work elicited a mixed range of opinions. Some express confidence that remote work can continue, while others say they see few positives to remote work.

With nine months of experience under their belts, more employers are seeing somewhat better productivity from their remote workers.

One impediment to productivity may be connectivity. A researcher at Stanford University found that only 65 percent of Americans surveyed said they had fast enough internet service to support viable video calls, and in many parts of the developing world, the connectivity infrastructure is sparse or nonexistent. Developing digital infrastructure will require significant public and private investment.

For women in particular, remote work is a mixed blessing. It boosts flexibility—not needing to be physically co-located with fellow workers enables independent work and more flexible hours—as well as productivity, with less time wasted commuting. Yet remote work also may increase gender disparity in the workplace, exacerbating the regressive effects of COVID-19. The female workforce in many economies is more highly concentrated in occupational clusters like healthcare, food services, and customer service that have relatively low potential for remote work. Previous MGI research on gender parity found that jobs held by women are 19 percent more at risk than jobs held by men simply because women are disproportionately represented in sectors most negatively affected by COVID-19.

Some forms of remote work are likely to persist long after COVID-19 is conquered. This will require many shifts, such as investment in digital infrastructure, freeing up office space, and the structural transformation of cities, food services, commercial real estate, and retail. It also risks accentuating inequalities and creating new psychological and emotional stresses among employees, including from isolation. For most companies, having employees work outside the office  will require reinventing many processes and policies. How long before someone invents the virtual watercooler?

The authors wish to thank Olivia Robinson, Gurneet Singh Dandona, and Alok Singh for their contributions to this article.

This article was edited by Stephanie Strom, a senior editor at the McKinsey Global Institute.

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The massive surge in the number of people working from home may be the largest change to the U.S. economy since World War II, says Stanford scholar Nicholas Bloom .

And the shift to working from home, catalyzed by the pandemic, is here to stay, with further growth expected in the long run through improvements in technology.

Looking at data going back to 1965, when less than 1% of people worked from home, the number of people working from home had been rising continuously up to the pandemic, doubling roughly every 15 years, said Bloom, the William D. Eberle Professor in Economics in the School of Humanities and Sciences and professor, by courtesy, at Stanford Graduate School of Business.

Before the pandemic, only around 5% of the typical U.S. workforce worked from home; at the pandemic’s onset, it skyrocketed to 61.5%. Currently, about 30% of employees work from home.

“In some ways, one of the biggest lasting legacies of the pandemic will be the shift to work from home,” said Bloom.

Bloom shared his research on working from home at the Stanford Distinguished Careers Institute ’s “The Future of Work” Winter 2023 Colloquium, which focused on how the ways we work are changing.

DCI Director Richard Saller moderated the event , which featured scholars from Stanford and beyond discussing working arrangements and attitudes, challenges to office real estate, learned lessons about the power of proximity, and more.

Below are seven takeaways from Bloom’s discussion:

• The employees. About 58% of people in the U.S. can’t work from home at all, and they are typically frontline workers with lower pay. Those who work entirely from home are primarily professionals, managers, and in higher-paying fields such as IT support, payroll, and call centers. The highest paid group includes the 30% of people working from home in a hybrid capacity, and these include professionals and managers.
• The move. Almost 1 million people left city centers like New York and San Francisco during the pandemic. Those who used to go to the office five days a week are now willing to commute farther because they are only in the office a couple days a week, and they want larger homes to accommodate needs such as a home office. This has changed property markets substantially with rents and home values in the suburbs surging, Bloom said. Home values in city centers have risen but not by much.
• The commute. Public transit journeys have plummeted and are currently down by a third compared to pre-pandemic levels. This sharp reduction is threatening the survival of mass transit, Bloom said. These are systems that have relatively fixed costs because the hardware and labor, which is largely unionized, are relatively hard to adjust. A lot of the revenues come from ticket sales, and these agencies are losing a lot of money.
• The office. Offices are changing, with cubicles becoming less popular and meeting rooms more desirable. As some companies incorporate an organized hybrid schedule in which everyone comes in on certain days, they are redesigning spaces to support more meetings, presentations, trainings, lunches, and social time.
• The startups. Startup rates are surging, up by 20% from pre-pandemic numbers. The reasons: working from home provides a cheaper way to start a new company by saving a lot on initial capital and rent. Also, people can more easily work on a startup on the side when their regular job offers the option to work from home.
• The downtime. The number of people playing golf mid-week has more than doubled since 2019. People used to go before or after work, or on the weekends, but now the mid-day, mid-week golf game is becoming more common. The same is probably true for things like gyms, tennis courts, retail hairdressers, ski resorts, and anything else that consumers used to pack into the weekends.
• The organization. More and more, firms are outsourcing or offshoring their information technology, human resources, and finance to access talent, save costs, and free up space. There has been a big increase in part-time employees, independent contractors, and outsourcing. “After seeing how well it worked with remote work at the beginning of the pandemic, companies may not see a need to have employees in the country,” Bloom said.

Interested in hearing more about the future of work? Stanford Continuing Studies will feature Bloom as he discusses “The Future of and Impact of Working from Home” on May 1 as part of the Stanford Monday University web seminar series .

Bloom is also co-director of the Productivity, Innovation, and Entrepreneurship program at the National Bureau of Economic Research, a fellow at the Centre for Economic Performance, and a senior fellow at the Stanford Institute for Economic Policy Research .

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About a third of U.S. workers who can work from home now do so all the time

Roughly three years after the COVID-19 pandemic upended U.S. workplaces, about a third (35%) of workers with jobs that can be done remotely are working from home all of the time, according to a new Pew Research Center survey. This is down from 43% in January 2022 and 55% in October 2020 – but up from only 7% before the pandemic.

While the share working from home all the time has fallen off somewhat as the pandemic has gone on, many workers have settled into hybrid work. The new survey finds that 41% of those with jobs that can be done remotely are working a hybrid schedule – that is, working from home some days and from the office, workplace or job site other days. This is up from 35% in January 2022.

Among hybrid workers who are not self-employed, most (63%) say their employer requires them to work in person a certain number of days per week or month. About six-in-ten hybrid workers (59%) say they work from home three or more days in a typical week, while 41% say they do so two days or fewer.

Related: How Americans View Their Jobs

Many hybrid workers would prefer to spend more time working from home than they currently do. About a third (34%) of those who are currently working from home most of the time say, if they had the choice, they’d like to work from home all the time. And among those who are working from home some of the time, half say they’d like to do so all (18%) or most (32%) of the time.

Pew Research Center conducted this analysis to study how the COVID-19 pandemic has affected the workplace and specifically how workers with jobs that can be done from home have adapted their work schedules. To do this, we surveyed 5,775 U.S. adults who are working part time or full time and who have only one job or who have more than one job but consider one of them to be their primary job. All the workers who took part are members of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses.

Address-based sampling ensures that nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis, along with responses, and the survey’s methodology .

The majority of U.S. workers overall (61%) do not have jobs that can be done from home. Workers with lower incomes and those without a four-year college degree are more likely to fall into this category. Among those who do have teleworkable jobs, Hispanic adults and those without a college degree are among the most likely to say they rarely or never work from home.

When looking at all employed adults ages 18 and older in the United States, Pew Research Center estimates that about 14% – or roughly 22 million people – are currently working from home all the time.

The advantages and disadvantages of working from home

Workers who are not self-employed and who are teleworking at least some of the time see one clear advantage – and relatively few downsides – to working from home. By far the biggest perceived upside to working from home is the balance it provides: 71% of those who work from home all, most or some of the time say doing so helps them balance their work and personal lives. That includes 52% who say it helps them a lot with this.

About one-in-ten (12%) of those who are at least occasionally working from home say it hurts their ability to strike the right work-life balance, and 17% say it neither helps nor hurts. There is no significant gender difference in these views. However, parents with children younger than 18 are somewhat more likely than workers without children in that age range to say working from home is helpful in this regard (76% vs. 69%).

A majority of those who are working from home at least some of the time (56%) say this arrangement helps them get their work done and meet deadlines. Only 7% say working from home hurts their ability to do these things, and 37% say it neither helps nor hurts.

There are other aspects of work – some of them related to career advancement – where the impact of working from home seems minimal:

• When asked how working from home affects whether they are given important assignments, 77% of those who are at least sometimes working from home say it neither helps nor hurts, while 14% say it helps and 9% say it hurts.
• When it comes to their chances of getting ahead at work, 63% of teleworkers say working from home neither helps or hurts, while 18% say it helps and 19% say it hurts.
• A narrow majority of teleworkers (54%) say working from home neither helps nor hurts with opportunities to be mentored at work. Among those who do see an impact, it’s perceived to be more negative than positive: 36% say working from home hurts opportunities to be mentored and 10% say it helps.

One aspect of work that many remote workers say working from home makes more challenging is connecting with co-workers: 53% of those who work from home at least some of the time say working from home hurts their ability to feel connected with co-workers, while 37% say it neither helps nor hurts. Only 10% say it helps them feel connected.

In spite of this, those who work from home all the time or occasionally are no less satisfied with their relationship with co-workers than those who never work from home. Roughly two-thirds of workers – whether they are working exclusively from home, follow a hybrid schedule or don’t work from home at all – say they are extremely or very satisfied with these relationships. In addition, among those with teleworkable jobs, employed adults who work from home all the time are about as likely as hybrid workers to say they have at least one close friend at work.

Feeling connected with co-workers is one area where many workers who rarely or never work from home see an advantage in their setup. About four-in-ten of these workers (41%) say the fact that they rarely or never work from home helps in how connected they feel to their co-workers. A similar share (42%) say it neither helps nor hurts, and 17% say it hurts.

At the same time, those who rarely or never work from home are less likely than teleworkers to say their current arrangement helps them achieve work-life balance. A third of these workers say the fact that they rarely or never work from home hurts their ability to balance their work and personal lives, while 40% say it neither helps nor hurts and 27% say it helps.

When it comes to other aspects of work, many of those who rarely or never work from home say their arrangement is neither helpful nor hurtful. This is true when it comes to opportunities to be mentored (53% say this), their ability to get work done and meet deadlines (57%), their chances of getting ahead in their job (68%) and whether they are given important assignments (74%).

Most adults with teleworkable jobs who work from home at least some of the time (71%) say their manager or supervisor trusts them a great deal to get their work done when they’re doing so. Those who work from home all the time are the most likely to feel trusted: 79% of these workers say their manager trusts them a great deal, compared with 64% of hybrid workers.

Hybrid workers feel about as trusted when they’re not working from home: 68% say their manager or supervisor trusts them a great deal to get their work done when they’re not teleworking.

Note: Here are the questions used for this analysis, along with responses, and the survey’s methodology .

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How Companies Benefit When Employees Work Remotely

Companies that let their workers decide where and when to do their jobs—whether in another city or in the middle of the night—increase employee productivity, reduce turnover, and lower organizational costs, new research suggests.

Prithwiraj Choudhury , an associate professor in the Technology and Operations Management Unit at Harvard Business School, and fellow researchers compared the outcomes of flexible work arrangements at the US Patent and Trademark Office (USPTO). The team found that employees with liberal “work from anywhere” arrangements, similar to those offered at Akamai, NASA, and Github, among others, were 4.4 percent more productive than those following a more traditional “work-from-home” policy that gives schedule flexibility but requires workers to live near the office.

“While prior academic research has studied productivity effects of ‘working from home’ that gives workers temporal flexibility, ‘work from anywhere’ goes a step further and provides both temporal and geographic flexibility,” says Choudhury, who co-authored the paper, (Live and) Work from Anywhere: Geographic Flexibility and Productivity Effects at the United States Patent Office, with HBS doctoral student Cirrus Foroughi and Barbara Larson , executive professor of management at Northeastern University.

While digital technology has made workers more efficient and accessible than ever before, many companies have been slow to let employees work from home regularly, let alone from anywhere at any time. The study’s findings can help firms understand the effects of various flex-work options, and support certain types of employees as they negotiate with employers. Choudhury says the results have important implications for workers, who could potentially move to lower-cost areas, reduce commuting costs, and live closer to family and friends.

Isolating the benefits of remote work

To study the productivity effects of work-from-anywhere policies, Choudhury looked for a setting that would allow the researchers to isolate productivity changes among workers with similar job functions under different remote-work conditions. The USPTO provided the perfect opportunity.

Seeking to increase efficiency, the agency implemented the Telework Enhancement Act Pilot Program (TEAPP) in 2012. The program transitioned patent examiners to a work-from-anywhere policy over 24 months, shifting new examiners each month based on union-negotiated quotas. This implementation process enabled Choudhury and his co-authors to avoid what is known as the selection problem in social science research.

“The concern is that there is some underlying characteristic of people that is driving whether one wants to become a remote worker, and that characteristic is also correlated to productivity,” explains Choudhury.

Prior to TEAPP, examiners could work from home as long as they were within 50 miles of the USPTO headquarters in Alexandria, Virginia, but they had to report to the office once a week. The agency eventually allowed them to work beyond 50 miles away, but still required weekly trips to the office. TEAPP provided full autonomy.

Choudhury and his coauthors compared 600 examiners’ productivity under these various conditions. While working remotely, productivity increased among all examiners and continued to rise with each step toward the full work-from-anywhere policy, the researchers found. Productivity increased 4.4 percent when employees moved from working at home on a limited basis to the location of their choice. Based on a patent's average value, this productivity gain could add $1.3 billion of value to the US economy each year, the researchers estimate.

Many of the examiners also benefited financially by bringing their Greater Washington, DC, salaries to less costly regions, effectively increasing their real incomes. Early- and mid-career workers tended to choose locations based on future career considerations, while workers with longer tenures flocked to “retirement-friendly” destinations, such as Florida.

Work from anywhere isn’t for everyone

To put their findings in perspective and offer a framework for future research, the researchers emphasized the nature of a patent examiner’s work, which requires little coordination with co-workers on a daily basis. Examiners perform their work independently, adhering to the same best practices of patent searches—a style of work that prior research has termed “pooled interdependence.” Choudhury stresses that the research results apply only to companies or units that employ this type of worker.

“For the vast majority of such employers, remote work is a win-win, because the employee can move to a location of choice and save money in cost of living, and the employer will see higher productivity and lower attrition, and save on real estate costs,” says Choudhury.

Choudhury and his fellow researchers contrast pooled interdependence with “reciprocal interdependence,” which requires continued interaction between co-workers, and “sequential interdependence,” which involves a series of tasks performed by different employees.

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Employees with jobs that require minimal coordination could potentially use these findings in negotiations with a prospective employer, says Choudhury. However, work-from-anywhere policies could increase costs in work environments that require brainstorming and project-based interaction, says Choudhury, adding that more research is needed to fully understand the implications of remote work in more collaborative settings.

Looking ahead

As some companies move to adopt broader telecommute policies, others such as Yahoo! have publicly retreated from allowing workers to perform their jobs away from headquarters. Companies have cited the need for office “face time” and the benefits of spontaneous interaction among reasons to avoid remote work, even for highly skilled, autonomous employees. To Choudhury, a deeper factor might underlie their reluctance.

“It’s trust—it’s the fear that people will shirk, and I think it’s the lack of clarity from the academic research as well,” Choudhury says.

The potential for this new research to help inform discussions about remote work policies excites Choudhury. Giving knowledge workers, particularly those who work solitarily, the freedom to choose their location could benefit not only employees, but companies and the environment, too.

“People will gravitate to a location where they want to live, rather than where they have to live,” predicts Choudhury. “This was the big promise of digital technology, that it would allow people to move away from the urban clusters.”

For companies seeking to expand their remote work policies, the USPTO program offers several other considerations for executives:

• Gradual transitions might help employees adjust . The USPTO required in-office examiners to work from home before shifting to the fully autonomous option. A gradual shift might give employees time to set up their own processes for working remotely while they're still close enough to seek their employer's support in person.
• Technology tools can support light supervision . The USPTO's program focused on examiners who worked independently. However, when an employee's work needed a supervisor's review, the agency required employees to use its IT tools to coordinate virtually, bolstering productivity.
• A period of in-office work can provide a strong foundation . Only patent examiners with two years of in-office experience were eligible for the USPTO's remote work programs. These employees had the opportunity to learn from working alongside more experienced examiners before moving away.

About the Author

Kristen Senz is a writer and social media creator for Harvard Business School Working Knowledge. Ailyn Pestana , junior designer and photo coordinator at Harvard Business School, created the charts above. [Image: NoSystem Images ]

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Are We Really More Productive Working from Home?

Data from the pandemic can guide organizations struggling to reimagine the new office..

• By Rebecca Stropoli
• August 18, 2021
• CBR - Economics
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Facebook founder and CEO Mark Zuckerberg isn’t your typical office worker. He was No. 3 on the 2020 Forbes list of the richest Americans, with a net worth of $125 billion, give or take. But there’s at least one thing Zuckerberg has in common with many other workers: he seems to like working from home. In an internal memo, which made its way to the Wall Street Journal , as Facebook announced plans to offer increased flexibility to employees, Zuckerberg explained that he would work remotely for at least half the year.

“Working remotely has given me more space for long-term thinking and helped me spend more time with my family, which has made me happier and more productive at work,” Zuckerberg wrote. He has also said that he expects about half of Facebook’s employees to be fully remote within the next decade.

The coronavirus pandemic continues to rage in many countries, and variants are complicating the picture, but in some parts of the world, including the United States, people are desperate for life to return to normal—everywhere but the office. After more than a year at home, some employees are keen to return to their workplaces and colleagues. Many others are less eager to do so, even quitting their jobs to avoid going back. Somewhere between their bedrooms and kitchens, they have established new models of work-life balance they are loath to give up.

This has left some companies trying to recreate their work policies, determining how best to handle a workforce that in many cases is demanding more flexibility. Some, such as Facebook, Twitter, and Spotify, are leaning into remote work. Others, such as JPMorgan Chase and Goldman Sachs, are reverting to the tried-and-true office environment, calling everyone back in. Goldman’s CEO David Solomon, in February, called working from home an “aberration that we’re going to correct as quickly as possible.” And JPMorgan CEO Jamie Dimon said of exclusively remote work: “It doesn’t work for those who want to hustle. It doesn’t work for spontaneous idea generation. It doesn’t work for culture.”

This pivotal feature of pandemic life has accelerated a long-running debate: What do employers and employees lose and gain through remote work? In which setting—the office or the home—are employees more productive? Some research indicates that working from home can boost productivity and that companies offering more flexibility will be best positioned for success. But this giant, forced experiment has only just begun.

An accelerated debate

A persistent sticking point in this debate has been productivity. Back in 2001, a group of researchers from the Human-Computer Interaction Institute at Carnegie Mellon, led by Robert E. Kraut , wrote that “collaboration at a distance remains substantially harder to accomplish than collaboration when members of a work group are collocated.” Two decades later, this statement remains part of today’s discussion.

However, well before Zoom, which came on the scene in 2011, or even Skype, which launched in 2003, the researchers acknowledged some of the potential benefits of remote work, allowing that “dependence on physical proximity imposes substantial costs as well, and may undercut successful collaboration.” For one, they noted, email, answering machines, and computer bulletin boards could help eliminate the inconvenience of organizing in-person meetings with multiple people at the same time.

Two decades later, remote-work technology is far more developed. Data from the US Bureau of Labor Statistics indicate that, even in pre-pandemic 2019, more than 26 million Americans—approximately 16 percent of the total US workforce—worked remotely on an average day. The Pew Research Center put that pre-pandemic number at 20 percent, and in December 2020 reported that 71 percent of workers whose responsibilities allowed them to work from home were doing so all or most of the time.

The sentiment toward and effectiveness of remote work depend on the industry involved. It makes sense that executives working in and promoting social media are comfortable connecting with others online, while those in industries in which deals are typically closed with handshakes in a conference room, or over drinks at dinner, don’t necessarily feel the same. But data indicate that preferences and productivity are shaped by factors beyond a person’s line of work.

The productivity paradigm

Before the COVID-19 pandemic, Stanford’s Nicholas Bloom  was bullish on work-from-home trends. His 2015 study, for one—with James Liang , John Roberts , and Zhichun Jenny Ying , all then at Stanford—finds a 13 percent increase in productivity among remotely working call-center employees at a Chinese travel agency.

But in the early days of the pandemic, Bloom was less optimistic about remote work. “We are home working alongside our kids, in unsuitable spaces, with no choice and no in-office days,” Bloom told a Stanford publication in March 2020. “This will create a productivity disaster for firms.”

To test that thesis, Jose Maria Barrero  of the Mexico Autonomous Institute of Technology, Bloom, and Chicago Booth’s Steven J. Davis  launched a monthly survey of US workers in May 2020, tracking more than 30,000 workers aged 20–64 who earned at least $20,000 per year in 2019.

Companies that offer more flexibility in work arrangements may have the best chance of attracting top talent at the best price.

The survey measured the incidence of working from home as the pandemic continued, focusing on how a more permanent shift to remote work might affect not only productivity but also overall employee well-being. It also examined factors including how work from home would affect spending and revenues in major urban centers. In addition to the survey, the researchers drew on informal conversations with dozens of US business executives. They are publishing the results of the survey and related research at wfhresearch.com .

In an analysis of the data collected through March 2021, they find that nearly six out of 10 workers reported being more productive working from home than they expected to be, compared with 14 percent who said they got less done. On average, respondents’ productivity at home was 7 percent higher than they expected. Forty percent of workers reported they were more productive at home during the pandemic than they had been when in the office, and only 15 percent said the opposite was true. The researchers argue that the work-from-home trend is here to stay, and they calculate that these working arrangements will increase overall worker productivity in the US by 5 percent as compared with the pre-pandemic economy.

“Working from home under the pandemic has been far more productive than I or pretty much anyone else predicted,” Bloom says.

No commute, and fewer hours worked

Some workers arguing in favor of flexibility might say they’re more efficient at home away from chatty colleagues and the other distractions of an office, and that may be true. But above all, the increased productivity comes from saving transit time, an effect overlooked by standard productivity calculations. “Three-quarters or more of the productivity gains that we find are coming from a reduction in commuting time,” Davis says. Eliminate commuting as a factor, and the researchers project only a 1 percent productivity boost in the postpandemic work-from-home environment, as compared with before.

It makes sense that standard statistics miss the impact of commutes, Davis explains. Ordinarily, commuting time generally doesn’t shift significantly in the aggregate. But much like rare power outages in Manhattan have made it possible for New Yorkers to suddenly see the nighttime stars, the dramatic work-from-home shift that occurred during the pandemic made it possible to recognize the impact traveling to and from an office had on productivity.

Before the pandemic, US workers were commuting an average of 54 minutes daily, according to Barrero, Bloom, and Davis. In the aggregate, the researchers say, the pandemic-induced shift to remote work meant 62.5 million fewer commuting hours per workday.

People who worked from home spent an average of 35 percent of saved commuting time on their jobs, the researchers find. They devoted the rest to other activities, including household chores, childcare, leisure activities such as watching movies and TV, outdoor exercise, and even second jobs.

Infographic: People want working from home to stick after the pandemic subsides

With widespread lockdowns abruptly forcing businesses to halt nonessential, in-person activity, the COVID-19 pandemic drove a mass social experiment in working from home, according to Jose Maria Barrero  of the Mexico Autonomous Institute of Technology, Stanford’s Nicholas Bloom , and Chicago Booth’s Steven J. Davis . The researchers launched a survey of US workers, starting in May 2020 and continuing in waves for more than a year since, to capture a range of information including workers’ attitudes about their new remote arrangements.

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Aside from commuting less, remote workers may also be sleeping more efficiently, another phenomenon that could feed into productivity. On days they worked remotely, people rose about 30 minutes later than on-site workers did, according to pre-pandemic research by Sabrina Wulff Pabilonia  of the US Bureau of Labor Statistics and SUNY Empire’s Victoria Vernon . Both groups worked the same number of hours and slept about the same amount each night, so it’s most likely that “working from home permits a more comfortable personal sleep schedule,” says Vernon. “Teleworkers who spend less time commuting may be happier and less tired, and therefore more productive,” write the researchers, who analyzed BLS data from 2017 to 2018.

While remote employees gained back commuting time during the pandemic, they also worked fewer hours, note Barrero, Bloom, and Davis. Hours on the job averaged about 32 per week, compared with 36 pre-pandemic, although the work time stretched past traditional office hours. “Respondents may devote a few more minutes in the morning to chores and childcare, while still devoting about a third of their old commuting time slot to their primary job. At the end of the day, they might end somewhat early and turn on the TV. They might interrupt TV time to respond to a late afternoon or early evening work request,” the researchers explain.

This interpretation, they write, is consistent with media reports that employees worked longer hours from home during the pandemic but with the added flexibility to interrupt the working day. Yet, according to the survey, this does not have a negative overall effect on productivity, contradicting one outdated stereotype of a remote worker eating bonbons, watching TV, and getting no work done.

Remote-work technology goes mainstream

The widespread implementation of remote-working technology, a defining feature of the pandemic, is another important factor for productivity. This technology will boost work-from-home productivity by 46 percent by the end of the pandemic, relative to the pre-pandemic situation, according to a model developed by Rutgers’s Morris A. Davis , University of North Carolina’s Andra C. Ghent , and University of Wisconsin’s Jesse M. Gregory . “While many home-office technologies have been around for a while, the technologies become much more useful after widespread adoption,” the researchers note.

There are significant costs to leaving the office, Rutgers’s Davis says, pointing to the loss of face-to-face interaction, among other things. “Working at home is always less productive than working at the office. Always,” he said on a June episode of the Freakonomics podcast.

One reason, he says , has to do with the function of cities as business centers. “Cities exist because, we think, the crowding of employment makes everyone more productive,” he explains. “This idea also applies to firms: a firm puts all workers on the same floor of a building, or all in the same suite rather than spread throughout a building, for reasons of efficiency. It is easier to communicate and share ideas with office mates, which leads to more productive outcomes.” While some employees are more productive at home, that’s not the case overall, according to the model, which after calibration “implies that the average high-skill worker is less productive at home than at the office, even postpandemic,” he says.

How remote work could change city centers

What will happen to urban business districts and the cities in which they are located in the age of increasing remote work?

About three-quarters of Fortune 500 CEOs expect to need less office space in the future, according to a May 2021 poll. In Manhattan, the overall office vacancy rate was at a multidecade high of 16 percent in the first quarter of 2021, according to real-estate services firm Cushman & Wakefield.

And yet Davis, Ghent, and Gregory’s model projects that after the pandemic winds down, highly skilled, college-educated workers will spend 30 percent of their time working from home, as opposed to 10 percent in prior times. While physical proximity may be superior, working from home is far more productive than it used to be. Had the pandemic hit in 1990, it would not have produced this rise in relative productivity, per the researchers’ model, because the technology available at the time was not sufficient to support remote work.

A June article in the MIT Technology Review by Stanford’s Erik Brynjolfsson and MIT postdoctoral scholar Georgios Petropoulos corroborates this view. Citing the 5.4 percent increase in US labor productivity in the first quarter of 2021, as reported by the BLS, the researchers attribute at least some of this to the rise of work-from-home technologies. The pandemic, they write, has “compressed a decade’s worth of digital innovation in areas like remote work into less than a year.” The biggest productivity impact of the pandemic will be realized in the longer run, as the work-from-home trend continues, they argue.

Lost ideas, longer hours?

Not all the research supports the idea that remote work increases productivity and decreases the number of hours workers spend on the job. Chicago Booth’s Michael Gibbs  and University of Essex’s Friederike Mengel  and Christoph Siemroth  find contradictory evidence from a study of 10,000 high-skilled workers at a large Asian IT-services company.

The researchers used personnel and analytics data from before and during the coronavirus work-from-home period. The company provided a rich data set for these 10,000 employees, who moved to 100 percent work from home in March 2020 and began returning to the office in late October.

Total hours worked during that time increased by approximately 30 percent, including an 18 percent rise in working beyond normal business hours, the researchers find. At the same time, however, average output—as measured by the company through setting work goals and tracking progress toward them—declined slightly. Time spent on coordination activities and meetings also increased, while uninterrupted work hours shrank. Additionally, employees spent less time networking and had fewer one-on-one meetings with their supervisors, find the researchers, adding that the increase in hours worked and the decline in productivity were more significant for employees with children at home. Weighing output against hours worked, the researchers conclude that productivity decreased by about 20 percent. They estimate that, even after accounting for the loss of commuting time, employees worked about a third of an hour per day more than they did at the office. “Of course, that time was spent in productive work instead of sitting in traffic, which is beneficial,” they acknowledge.

Regardless of what research establishes in the long run about productivity, many workers are already demanding flexibility in their schedules.

Overall, though, do workers with more flexibility work fewer hours (as Barrero, Bloom, and Davis find) or more (as at the Asian IT-services company)? It could take more data to answer this question. “I suspect that a high fraction of employees of all types, across the globe, value the flexibility, lack of a commute, and other aspects of work from home. This might bias survey respondents toward giving more positive answers to questions about their productivity,” says Gibbs.

The findings of his research do not entirely contradict those of Barrero, Bloom, and Davis, however. For one, Gibbs, Mengel, and Siemroth acknowledge that their study doesn’t necessarily reflect the remote-work model as it might look in postpandemic times, when employees are relieved of the weight of a massive global crisis. “While the average effect of working from home on productivity is negative in our study, this does not rule out that a ‘targeted working from home’ regime might be desirable,” they write.

Additionally, the research data are derived from a single company and may not be representative of the wider economy, although Gibbs notes that the IT company is one that should be able to optimize remote work. Most employees worked on company laptops, “and IT-related industries and occupations are usually at the top of lists of those areas most likely to be able to do WFH effectively.” Thus, he says, the findings may represent a cautionary note that remote work has costs and complexities worth addressing.

As he, Mengel, and Siemroth write, some predictions of work-from-home success may be overly optimistic, “perhaps because professionals engage in many tasks that require collaboration, communication, and innovation, which are more difficult to achieve with virtual, scheduled interactions.”

Attracting top talent

The focus on IT employees’ productivity, however, excludes issues such as worker morale and retention, Booth’s Davis notes. More generally, “the producer has to attract workers . . . and if workers really want to commute less, and they can save time on their end, and employers can figure out some way to accommodate that, they’re going to have more success with workers at a given wage cost.”

Companies that offer more flexibility in work arrangements may have the best chance of attracting top talent at the best price. The data from Barrero, Bloom, and Davis reveal that some workers are willing to take a sizable pay cut in exchange for the opportunity to work remotely two or three days a week. This may give threats from CEOs such as Morgan Stanley’s James Gorman—who said at the company’s US Financials, Payments & CRE conference in June, “If you want to get paid New York rates, you work in New York”—a bit less bite. Meanwhile, Duke PhD student John W. Barry , Cornell’s Murillo Campello , Duke’s John R. Graham , and Chicago Booth’s Yueran Ma  find that companies offering flexibility are the ones most poised to grow.

Working policies may be shaped by employees’ preferences. Some workers still prefer working from the office; others prefer to stay working remotely; many would opt for a hybrid model, with some days in the office and some at home (as Amazon and other companies have introduced). As countries emerge from the pandemic and employers recalibrate, companies could bring back some employees and allow others to work from home. This should ultimately boost productivity, Booth’s Davis says.

Or they could allow some to work from far-flung locales. Harvard’s Prithwiraj Choudhury  has long focused his research on working not just from home but “from anywhere.” This goes beyond the idea of employees working from their living room in the same city in which their company is located—instead, if they want to live across the country, or even in another country, they can do so without any concern about being near headquarters.

Does remote work promote equity?

At many companies, the future will involve remote work and more flexibility than before. That could be good for reducing the earnings gap between men and women—but only to a point.

“In my mind, there’s no question that it has to be a plus, on net,” says Harvard’s Claudia Goldin. Before the pandemic, many women deemphasized their careers when they started families, she says.

Research Choudhury conducted with Harvard PhD student Cirrus Foroughi  and Northeastern University’s Barbara Larson  analyzes a 2012 transition from a work-from-home to a work-from-anywhere model among patent examiners with the United States Patent and Trademark Office. The researchers exploited a natural experiment and estimate that there was a 4.4 percent increase in work output when the examiners transitioned from a work-from-home regime to the work-from-anywhere regime.

“Work from anywhere offers workers geographic flexibility and can help workers relocate to their preferred locations,” Choudhury says. “Workers could gain additional utility by relocating to a cheaper location, moving closer to family, or mitigating frictions around immigration or dual careers.”

He notes as well the potential advantages for companies that allow workers to be located anywhere across the globe. “In addition to benefits to workers and organizations, WFA might also help reverse talent flows from smaller towns to larger cities and from emerging markets,” he says. “This might lead to a more equitable distribution of talent across geographies.”

More data to come

It is still early to draw strong conclusions about the impact of remote work on productivity. People who were sent home to work because of the COVID-19 pandemic may have been more motivated than before to prove they were essential, says Booth’s Ayelet Fishbach, a social psychologist. Additionally, there were fewer distractions from the outside because of the broad shutdowns. “The world helped them stay motivated,” she says, adding that looking at such an atypical year may not tell us as much about the future as performing the same experiment in a typical year would.

Before the pandemic, workers who already knew they performed better in a remote-working lifestyle self-selected into it, if allowed. During the pandemic, shutdowns forced remote work on millions. An experiment that allowed for random selection would likely be more telling. “The work-from-home experience seems to be more positive than what people believed, but we still don’t have great data,” Fishbach says.

Adding to the less optimistic view of a work-from-home future, Booth’s Austan D. Goolsbee says that some long-term trends may challenge remote work. Since the 1980s, as the largest companies have gained market power, corporate profits have risen dramatically while the share of profits going to workers has dropped to record lows. “This divergence between productivity and pay may very well come to pass regarding time,” he told graduating Booth students at their convocation ceremony. Companies may try to claw back time from those who are remote, he says, by expecting employees to work for longer hours or during their off hours.

And author and behavioral scientist Jon Levy argues in the Boston Globe that having some people in the office and others at home runs counter to smooth organizational processes. To this, Bloom offers a potential solution: instead of letting employees pick their own remote workdays, employers should ensure all workers take remote days together and come into the office on the same days. This, he says, could help alleviate the challenges of managing a hybrid team and level the playing field, whereas a looser model could potentially hurt employees who might be more likely to choose working from home (such as mothers with young children) while elevating those who might find it easier to come into the office every day (such as single men).

Gibbs concurs, noting that companies using a hybrid model will have to find ways to make sure employees who should interact will be on campus simultaneously. “Managers may specify that the entire team meets in person every Monday morning, for example,” he says. “R&D groups may need to make sure that researchers are on campus at the same time, to spur unplanned interactions that sometimes lead to new ideas and innovations.”

Sentiments vary by location, industry, and culture. Japanese workers are reportedly still mostly opting to go to the office, even as the government promotes remote work. Among European executives, a whopping 88 percent reportedly disagree with the idea that remote work is as or more productive than working at the office.

Regardless of what research establishes in the long run about productivity, many workers are already demanding flexibility in their schedules. While only about 28 percent of US office workers were back onsite by June 2021, employees who had become used to more flexibility were demanding it remain. A May survey of 1,000 workers by Morning Consult on behalf of Bloomberg News finds that about half of millennial and Gen Z workers, and two-fifths of all workers, would consider quitting if their employers weren’t flexible about work-from-home policies. And additional research from Barrero, Bloom, and Davis finds that four in 10 Americans who currently work from home at least one day a week would look for another job if their employers told them to come back to the office full time. Additionally, most employees would look favorably upon a new job that offered the same pay as their current job along with the option to work from home two to three days a week.

The shift to remote work affects a significant slice of the US workforce. A study by Chicago Booth’s Jonathan Dingel  and Brent Neiman  finds that while the majority of all jobs in the US require appearing in person, more than a third can potentially be performed entirely remotely. Of these jobs, the majority—including many in engineering, computing, law, and finance—pay more than those that cannot be done at home, such as food service, construction, and building-maintenance jobs.

Barrero, Bloom, and Davis project that, postpandemic, Americans overall will work approximately 20 percent of full workdays from home, four times the pre-pandemic level. This would make remote work less an aberration than a new norm. As the pandemic has demonstrated, many workers can be both productive and get dinner started between meetings.

Works Cited

• Jose Maria Barrero, Nicholas Bloom, and Steven J. Davis,  “Why Working from Home Will Stick,”  Working paper, April 2021.
• ———,  “60 Million Fewer Commuting Hours per Day: How Americans Use Time Saved by Working from Home,” Working paper, September 2020.
• ———,  “Let Me Work From Home Or I Will Find Another Job,”  Working paper, July 2021.
• John W. Barry, Murillo Campello, John R. Graham, and Yueran Ma,  “Corporate Flexibility in a Time of Crisis,”  Working paper, February 2021.
• Nicholas Bloom, James Liang, John Roberts, and Zhichun Jenny Ying,  “Does Working from Home Work? Evidence from a Chinese Experiment,”   Quarterly Journal of Economics , October 2015.
• Prithwiraj Choudhury, Cirrus Foroughi, and Barbara Larson,  “Work-from-Anywhere: The Productivity Effects of Geographic Flexibility,”   Strategic Management Journal , forthcoming.
• Morris A. Davis, Andra C. Ghent, and Jesse M. Gregory,  “The Work-at-Home Technology Boon and Its Consequences,”  Working paper, April 2021. 
• Jonathan Dingel and Brent Neiman,  “How Many Jobs Can Be Done at Home?”  White paper, June 2020.
• Allison Dunatchik, Kathleen Gerson, Jennifer Glass, Jerry A. Jacobs, and Haley Stritzel,  “Gender, Parenting, and the Rise of Remote Work during the Pandemic: Implications for Domestic Inequality in the United States,”   Gender & Society , March 2021.
• Michael Gibbs, Friederike Mengel, and Christoph Siemroth,  “Work from Home & Productivity: Evidence from Personnel & Analytics Data on IT Professionals,”  Working paper, May 2021.
• Robert E. Kraut, Susan R. Fussell, Susan E. Brennan, and Jane Siegel, “Understanding Effects of Proximity on Collaboration: Implications for Technologies to Support Remote Collaborative Work,” in  Distributed Work , eds. Pamela J. Hinds and Sara Kiesler, Cambridge: MIT Press, 2002.
• Sabrina Wulff Pabilonia and Victoria Vernon,  “Telework and Time Use in the United States,”  Working paper, May 2020.

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Research Article

Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words

Roles Conceptualization, Methodology, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Social Sciences, The Education University of Hong Kong, Tai Po, Hong Kong

Roles Formal analysis, Writing – original draft

Affiliation Department of Information Systems, Business Statistics and Operations Management, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

Roles Conceptualization, Methodology, Writing – review & editing

• Amanda M. Y. Chu, 
• Thomas W. C. Chan, 
• Mike K. P. So

• Published: January 13, 2022
• https://doi.org/10.1371/journal.pone.0261969
• Reader Comments

During the 2019 novel coronavirus disease (COVID-19) pandemic, many employees have switched to working from home. Despite the findings of previous research that working from home can improve productivity, the scale, nature, and purpose of those studies are not the same as in the current situation with the COVID-19 pandemic. We studied the effects that three stress relievers of the work-from-home environment–company support, supervisor’s trust in the subordinate, and work-life balance–had on employees’ psychological well-being (stress and happiness), which in turn influenced productivity and engagement in non-work-related activities during working hours. In order to collect honest responses on sensitive questions or negative forms of behavior including stress and non-work-related activities, we adopted the randomized response technique in the survey design to minimize response bias. We collected a total of 500 valid responses and analyzed the results with structural equation modelling. We found that among the three stress relievers, work-life balance was the only significant construct that affected psychological well-being. Stress when working from home promoted non-work-related activities during working hours, whereas happiness improved productivity. Interestingly, non-work-related activities had no significant effect on productivity. The research findings provide evidence that management’s maintenance of a healthy work-life balance for colleagues when they are working from home is important for supporting their psychosocial well-being and in turn upholding their work productivity.

Citation: Chu AMY, Chan TWC, So MKP (2022) Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words. PLoS ONE 17(1): e0261969. https://doi.org/10.1371/journal.pone.0261969

Editor: Mohammad Hossein Ebrahimi, Shahrood University of Medical Sciences, ISLAMIC REPUBLIC OF IRAN

Received: June 1, 2021; Accepted: December 14, 2021; Published: January 13, 2022

Copyright: © 2022 Chu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Due to ethical restrictions, data are available from The Education University of Hong Kong for researchers who meet the criteria for access to sensitive data. Data requests will need to be submitted to Dr. Amanda Chu, Principal Investigator ( [email protected] ) for access to sensitive data.

Funding: This work was partially supported by the Hong Kong University of Science and Technology research grant “Big Data Analytics on Social Research” (grant number CEF20BM04). The funding recipient was MKPS. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Covid-19 leads to working from home.

Before the 2019 novel coronavirus disease (COVID-19) outbreak, most companies had not adopted the work-from-home (or working from home, WFH) approach. Employees needed to go to their offices on every working day. During the COVID-19 pandemic, individuals have been and are continuing to be advised to maintain social distancing to minimize the chance of infection [ 1 ]. To control the crisis, some countries and cities even need to institute lockdown measures to restrict the activities of their citizens [ 2 ]. However, under social distancing and lockdown policies, many employees are not able to go to their offices as usual. To maintain business operations, a majority of companies have responded improvisationally by introducing new WFH arrangements, although most of them have had little experience with such arrangements [ 3 , 4 ]. Because WFH can reduce infection rates and is accompanied by the low economic costs of confinement [ 5 ], it should be a suitable measure for facing the COVID-19 challenge. However, not everyone is happy with working from home or is able to carry it out [ 6 ].

Consequences of working from home

The WFH arrangements during the COVID-19 pandemic may have an impact on employees’ psychological well-being and, by extension, on their work performance. Because many employees have been forced to make WFH arrangements as a result of social distancing or lockdown policies during the COVID-19 pandemic, their WFH experiences may differ from those of employees in earlier studies, who were voluntarily working from home for a variety of reasons [ 4 , 7 , 8 ].

Indeed, the forced home confinement during lockdowns to control COVID-19 might affect individuals’ psychological well-being, including increasing their chances of disturbed sleep and insomnia because of the stressful situation and lack of positive stimuli [ 9 ]. Previous studies have confirmed the association between lockdown and negative psychological outcomes [ 10 ], such as higher stress levels [ 11 ]. However, the impact of WFH on workers’ psychological well-beings is not yet known. Being forced to engage in WFH but also unprepared for it may cause added stress on employees. On the positive side, remote employees have a high control of their working schedule and are able to work flexibly, which may have a positive impact on their job satisfaction [ 7 ]. They can adjust their working time so that they can fulfill other demands in their life, including family matters. A study [ 12 ] revealed that job flexibility could reduce work-to-home conflicts (conflicts caused by work issues interrupting home issues), and those reduced conflicts may help employees lower the distress of not fulfilling their family responsibilities.

Previous research has also suggested that positive psychological well-being is important for maintaining productivity in the workplace [ 13 ] although relatively little research has been done to study negative psychological well-being on employees’ job performance, especially during the WFH period. In addition, giving employees autonomy at home, along with controlling their boundaries, such as whether they conduct non-work-related activities during working hours, may be a great concern for employers [ 14 ]. According to the stress mindset theory, stress can be either enhance or debilitate one’s productivity [ 15 ] and growing evidence has shown that mindset shapes one’s stress response [ 16 ]. If employees hold the mindset that stress is debilitating, they will tend to focus on negative information from stressors, and that in turn will reinforce their negative beliefs and cause them to take action to avoid the stressors. In contrast, if employees hold the mindset that stress is enhancing, they will focus on positive information about stressors and will face their stresses and cope well with them [ 17 ]. By applying the stress mindset theory, we believe that when employees face stress, some can cope with it and maintain their focus on their work tasks while others may move on to other tasks to avoid the stress, instead of focusing on their work tasks. Those other tasks could be non-work-related activities, such as playing sports, shopping, and handling family matters. However, little empirical research has been conducted in these areas because they involve sensitive questions, such as whether the respondent is feeling stressed, and whether the respondent is conducting non-work-related activities during working hours [ 18 ]. Respondents are less willing to provide honest responses when they are asked such sensitive questions directly, and that dishonesty leads to response bias [ 19 ]. Therefore, we adopted the modified randomized response technique (RRT) to collect data on stress and non-work-related activities during working hours.

This research sought to investigate how the WFH environment affects individuals’ psychological well-being, and in turn how WFH impacts their work productivity and the frequency with which they conduct non-work-related activities during working hours when they are working from home.

Materials and methods

Methodology, participants..

A purposeful sample of 500 full-time employees in Hong Kong who experienced WFH for the first time during the COVID-19 pandemic was recruited online. The survey took place in early September 2020, which was near the end of the second period of growth in the number of confirmed COVID-19 cases in Hong Kong [ 20 ]. Table 1 shows a summary of the respondents’ demographic data. Such a diversity of participants reduces potential bias caused by the influence of socioeconomic backgrounds.

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https://doi.org/10.1371/journal.pone.0261969.t001

Survey design.

We identified our target respondents through personal networks and referrals, and then contacted them via emails and informed them of the study’s rationale. After confirming that the individuals were indeed our target respondents, we invited them to complete our self-administrated online questionnaire. All respondents were informed of the following in the first page of the online questionnaire: (1) the researcher’s name, affiliation, and contact details; (2) the topic and the aim of the study; and (3) the assurance that information about participation was anonymous and would be gathered on a voluntary basis. We obtained the respondents’ consent by asking them to click a button on the screen before starting the questionnaire. The study was conducted according to the prevailing guidelines on ethics in research, and it was approved by the Human Research Ethics Committee of The Education University of Hong Kong (reference number 2019-2020-0104).

Sensitive questions and confidentiality.

To ensure full confidentiality of the participants’ responses, we made the survey anonymous, and applied the RRT for the sensitive questions about stress and non-work-related activities during working hours. We followed the guidance of Chong et al. (2019) and Chu et al. (2020) [ 18 , 21 ] by implementing the RRT and constructing a covariance matrix for the responses. For details of the RRT procedure and application of RRT, readers may refer to Chong et al. (2019) and Chu et al. (2020) [ 18 , 21 ].

To ensure that the respondents understood the purpose of using the RRT to further protect their privacy and clearly understood how to answer the RRT questions, we also included a brief introduction to the RRT procedures before we asked the RRT questions.

All items in the survey were measured on a seven-point Likert scale. Unless otherwise specified, we provided seven options for each item, ranging from 1 (strongly disagree) to 7 (strongly agree), and we asked each respondent to pick the option that best described the situation.

Constructs and items

To build the research model, we constructed our survey questions on the basis of seven constructs, with each construct consisting of two to three items. A complete list of items is available in the S1 Table .

Company support.

Communication with colleagues and access to technical support are important for enabling a smooth transition to WFH [ 22 ]. Following the work of Sull et al. (2020) [ 22 ], we developed three items to measure company support. A high score indicated strong support from the company for employees who were working from home.

Supervisor trust.

When employees work from home, they have little opportunity to meet with their supervisors [ 23 ]. In the absence of supervisors and employees working face-to-face, supervisors’ trust in their subordinates is an important contribution to successful WFH [ 24 ]. We used three items to measure supervisor trust, with a high score indicating a high level of supervisors’ trust in their employees during WFH.

Work-life balance.

A favorable environment and a healthy balance between working time and personal time could be an advantageous result of WFH [ 25 ]. With reference to Chaiprasit and Santidhirakul (2011) [ 26 ], we developed three items to measure work-life balance during WFH, with a high score indicating a good work-life balance.

On the basis of the existing literature, we developed three items to measure employees’ level of stress: sleep quality [ 27 ], loss of energy [ 28 ], and depressed mood [ 29 ]. A high score indicated a high level of stress during WFH.

For the current study, we modified the three items relating to happiness that were developed by Chaiprasit and Santidhirakul (2011) [ 26 ]. The original items were in a five-point Likert scale, but we converted them into a seven-point Likert scale for measurement consistency in our study. A high score indicated a high level of happiness during WFH.

Non-work-related activities.

During WFH, family issues and entertainment activities can distract employees from their work [ 30 ]. Following Ford et al. (2020) and Javed et al. (2019) [ 31 , 32 ], we developed two items referring to these two possible distractions to measure the respondents’ non-work-related activities and we used a seven-point scale, ranging from 1 (never) to 7 (very many times), to quantify the respondents’ engagement in non-work-related activities [ 33 ]. A high score indicated a high frequency of conducting non-work-related activities during working hours when working from home.

Work productivity.

We adopted the top three factors from the Endicott Work Productivity Scale [ 34 ] as items for measuring work productivity. The items were originally in a five-point scale, ranging from 1 (“never”) to 5 (“almost always”), but we modified the wording to adapt the scale to our context on WFH and our seven-point Likert scale approach. A high score indicated a high level of perceived productivity during WFH.

Research model and hypotheses

Wfh environment and psychological well-being..

Employees have had no choice but to work from home when their companies or government policies have required it in response to the COVID-19 outbreak. For WFH to be successful, company support is necessary in three areas. First, some employees have insufficient equipment for WFH, and some may lack sufficient knowledge of the use of telecommunication technology [ 35 ]. Companies need to support their employees by providing them with the necessary equipment [ 36 ] and training them in the use of new technology [ 37 ]. Second, to avoid any impact of WFH on employees’ home time, companies have to set clear guidelines for distinguishing between work time and home time [ 38 ]. Third, companies have to decide when to start WFH and when to resume the normal working mode, and then they have to give their employees sufficient notice about the need to switch modes. We expected that company support during WFH would enhance job happiness [ 39 ] and would moderate the stresses from work and family. Therefore, we developed the following hypotheses:

• Hypothesis 1a : Company support will negatively affect employees’ stress when they are working from home during the COVID-19 pandemic.
• Hypothesis 1b : Company support will positively affect employees’ happiness when they are working from home during the COVID-19 pandemic.

As we have already noted, employers and employees do not see each other face-to-face in the WFH working environment. Thus, on one hand, employees have to show their employers that they are self-disciplined in completing their tasks on time and maintaining the expected quality of work [ 40 ] and, on the other hand, employers have to trust their employees that they have already tried their best in working on their assigned tasks [ 41 ]. In fact, some previous literature has mentioned that trust is the most critical factor in making WFH a success [ 42 ]. Therefore, we expected that supervisors’ trust in their subordinates would be important in maintaining employees’ happiness and reducing their stress on work [ 43 ]. Correspondingly, we developed the following hypotheses:

• Hypothesis 2a : Supervisor trust will be negatively related to employees’ stress level when the employees are working from home during the COVID-19 pandemic.
• Hypothesis 2b : Supervisor trust will be positively related to employees’ happiness when the employees are working from home during the COVID-19 pandemic.

A previous study of managers and fitness trainers discovered that loss of work-life balance could potentially boost the level of work-related stress because the workers spent extra time on work and did not have sufficient time for other life matters [ 44 ]. The association between a poor work-life balance and perceived job stress, which is caused by conflict between one’s job and other life activities, was further confirmed in a previous study on Australian academics [ 45 ]. The researchers explained that difficulty in maintaining work-life balance caused employees to feel additional stress. Moreover, research by Haar et al. (2014) [ 46 ] revealed that work-life balance was negatively related to depression across seven cultures in Asia, Europe, and Oceania, whereas work-life balance was positively associated with job and life satisfaction. Another study on healthcare employees also discovered a positive relationship between work-life balance and job satisfaction [ 47 ]. In addition, Fisher (2003) [ 44 ] found that having a good work-life balance could minimize the interference between employees’ work life and their personal life, thus allowing them to maintain their job engagement and family involvement at the same time, and fostering greater happiness in their work. Thus, we formulated the following two hypotheses:

• Hypothesis 3a : Work-life balance will be negatively related to employees’ stress level when they are working from home during the COVID-19 pandemic.
• Hypothesis 3b : Work-life balance will be positively related to employees’ level of happiness when they are working from home during the COVID-19 pandemic.

Psychological well-being, non-work-related activities, and productivity.

Previous studies have revealed the causal relationship that increased stress leads to a reduction in employees’ productivity [ 48 – 50 ]. Indeed, chronic stress can have several negative effects on employees, including insomnia, concentration difficulty, and increased risk of depression, all of which are likely to reduce productivity.

Some employees may choose to conduct non-work-related activities (e.g., non-work-related computing) while at work [ 33 ]. In our context, non-work-related activities are not referring to necessary activities such as going to the washroom or having a short break. We are considering situations in which an employee chooses to conduct non-work-related activities during work hours even if he or she could do those activities later. The reasons for conducting non-work-related activities during work hours are varied. Some studies have suggested that non-work-related activities can be caused by resistance and lack of management [ 51 , 52 ]. If an employee has a negative impression of the company or of management, that worker will have a low level of working engagement. In other words, a stressful working environment or management style can generate negative feelings in employees, and those negative feelings may motivate them to do something unrelated to their work during work hours. Accordingly, we formulated Hypotheses 4a and 4b as follows:

• Hypothesis 4a : Employees’ stress level will be negatively related to their work productivity when they are working from home during the COVID-19 pandemic.
• Hypothesis 4b : Employees’ stress level will be positively related to employees’ participation in non-work-related activities during working hours when they are working from home during the COVID-19 pandemic.

In contrast, happiness can have a positive impact on employees’ productivity. Under a classic piece rate setting, happier individuals have greater productivity than less happy individuals do, no matter whether the happiness derives from long-term or short-term events [ 53 ]. If employees think that they can achieve happiness by performing better at work, they will work harder for that reinforcement [ 54 ]. Therefore, the following hypothesis was also included:

• Hypothesis 5 : Employees’ happiness will be positively related to their work productivity when they are working from home during the COVID-19 pandemic.

Moreover, employees may have difficulty in concentrating on their work when they are working from home because of the lack of an organizational climate and in response to interruptions from family members [ 55 ]. In particular, employees who have children need to shoulder extra child care duties because of school closures [ 56 , 57 ]. At the same time, a feeling of insecurity because of rising numbers of COVID-19 cases also can distract employees [ 10 ], perhaps promoting them to conduct non-work-related activities during working hours at home to drive themselves out from the feeling of insecurity. Two major types of non-work-related activities are (1) activities fulfilling some demand in one’s life, such as caring for children, doing housework, or other activities that the person cannot escape when working from home; and (2) entertainment activities, such as playing video games and sports during working hours [ 31 , 32 ]. Some previous research has suggested that conducting non-work-related activities at work, such as using the Internet for personal purposes in the workplace, can affect job performance [ 52 , 58 ]. Hence, the final hypothesis we postulated was as follows:

• Hypothesis 6 : Employees’ participation in non-work-related activities during working hours will be negatively related to their work productivity when they are working from home during the COVID-19 pandemic.

Statistical analysis

We tested our hypotheses using structural equation modeling (SEM) in AMOS statistical software. The main purpose of using SEM in our analysis was to test the hypotheses about the constructs that we determined from the observed items we collected from the respondents [ 59 ].

To ensure that our model had a consistent construction, we analyzed the convergent validity and discriminant validity of the constructs by considering their Cronbach’s alpha values, average variance extracted (AVE) values, and square root of AVE values, on the respective constructs and the item loadings. Cronbach’s alpha measures the internal consistency of constructs [ 60 ]. The average variance extracted provides the average of variation explained by a construct [ 61 ].

Moreover, we assessed the model fit using (1) absolute fit indexes, including the goodness-of-fit index (GFI) and the root mean square error of approximation (RMSEA), and (2) incremental fit indexes, including the comparative fit index (CFI) and the normed fit index (NFI) [ 62 ].

After confirming that the model was consistent and had a good fit, we examined the model by SEM. We then calculated the significance of each path using a two-tailed t -test to test the cause and effect relationships among the constructs.

Model consistency

We list the summary statistics, including the mean and standard deviation of each item, the item loadings, and the Cronbach’s alpha of each construct in Table 2 . The correlations between constructs, average variances extracted (AVEs), and the square roots of the AVEs are listed in Table 3 . The Cronbach’s alpha of each construct was above the benchmark value of acceptable reliability 0.7 [ 63 ], thus suggesting a good internal consistency of each construct. In order to ensure that each item represented its construct, each item needed to have a loading larger than 0.4 [ 64 , 65 ]. All of the item loadings in our research exceeded 0.4, and the AVE value for each construct was larger than 0.5 (except one, which was 0.5), thus demonstrating that the items satisfied the requirements for convergent validity [ 66 , 67 ]. In addition, the square root of the AVE of each construct was larger than its correlations with all of the other constructs [ 67 ] meaning that the discriminant validity was at an acceptable level.

https://doi.org/10.1371/journal.pone.0261969.t002

https://doi.org/10.1371/journal.pone.0261969.t003

Model goodness of fit

The cut-off criteria of a good model fit are: RMSEA < 0.06, and GFI, CFI, and NFI ≥ 0.9 [ 68 – 71 ]. In this case, the study’s model demonstrated a satisfactory fit (RMSEA = 0.061; CFI = 0.947; GFI = 0.919; NFI = 0.922).

Testing of hypotheses

We report the standardized path coefficients and the significance of each of the hypotheses in Fig 1 . Based on a significance level of 5%, four hypotheses were significant and six were not significant.

N.S. represents not significant. *** indicates a p -value less than 0.01. The numbers to the right of the hypotheses’ numbers are the standardized path coefficients.

https://doi.org/10.1371/journal.pone.0261969.g001

The research findings supported Hypotheses H3a, H3b, H4b, and H5. Hypothesis H3a was supported ( β = -0.222, p < 0.001), indicating that work-life balance was negatively related to the employees’ stress level when those employees were working from home during the COVID-19 pandemic. Hypothesis H3b was also supported ( β = 0.750, p < 0.001), indicating that employees’ work-life balance was positively related to their happiness when those employees were working from home during the COVID-19 pandemic. Hypothesis H4b was supported ( β = 0.626, p < 0.001), indicating that employees’ stress level was positively related to the employees’ participation in non-work-related activities during working hours when those employees were working from home during the COVID-19 pandemic. Hypothesis H5 was supported ( β = 0.418, p < 0.001), indicating that employees’ happiness had a positive effect in promoting their work productivity.

The COVID-19 pandemic has forced many employees who were accustomed to working in the office and did not have previous WFH experience to do their work from home during part of the pandemic, because of social distancing or lockdown policies. In this research, we sought to investigate the effects that switching to WFH in response to the COVID-19 pandemic had on employees’ psychological well-being and, by extension, on their work productivity. We applied the stress mindset theory to study the relationships between three stress relievers (company support, supervisor trust, and work-life balance) on the positive and negative sides of employees’ psychological well-being (happiness versus stress), which in turn affected their job performance (productivity and non-work-related activities during working hours) when they were working from home during the COVID-19 pandemic. Interestingly, among the three stress relievers we studied, work-life balance is the only reliever that have influenced on the employees’ psychological well-being. At the same time, this reliever has a positive effect on one’s psychological well-being by promoting happiness and relieving stress. Our research findings also suggest that when employees feel happy in their WFH arrangements, their work productivity increases. Surprisingly, when the employees encountered stress in their WFH arrangements, they still maintained their work productivity, but at the same time, they participate more in non-work-related activities to relieve their stress. The good news is that their non-work-related activities did not affect their work productivity. Our study takes the lead in developing a research model that shapes the relationship between employees’ WFH environment and their psychological well-being and performance in relation to sudden and forced WFH during the COVID-19 pandemic. As a methodological contribution, our study adopted the modified randomized response technique to ask the sensitive questions involved in the study, including queries about the employees’ negative psychological well-being status and their engagement in non-work-related activities. We provided extra protection to their privacy by using this survey method, so as to encourage them to provide truthful responses when answering such sensitive questions. Management may wish to consider adopting the same methodology in an effort to collect honest responses when sensitive questions are involved in the workplace.

Regarding the effect of stress relievers on psychological well-being, we found that having a healthy work-life balance promotes happiness and also relieves stress. However, WFH does not imply an improvement in work-life balance, especially when the employees do not have a suitable environment to work. Employees should have a private workspace, which allows access to a strong and stable Internet connection, and has sufficient equipment to carry out their work at home. If employees encounter difficulties when they are working from home, management should provide the employees with flexible arrangements and alternative approaches to work. For example, if an employee does not have a comfortable environment to work, management may arrange a private space or room in the office for the employees given that a proper social distance is maintained.

As is the case in other fast-paced metropolises, Hong Kong has long followed the standard practice of employees working in a formal office environment and offering them no flexible working options [ 72 ]. During the pandemic, when the employees are allow to work from home, some companies have also set strict rules, such as requiring staff to stay at home during working hours or to answer calls from supervisors within three tones. However, a blurred boundary between work space and home space can make it difficult for employees to set a clear line of separation between their work and their home life [ 73 ]. Under a work-life balance working approach, it is assumed that employees can reserve enough time to handle non-work-related life issues and activities while managing their work tasks. Although some previous studies have suggested that non-work-related activities in the workplace affect work productivity [ 52 , 58 ], our research findings did not support that argument in regard to WFH. In other words, performing non-work-related activities during work hours at home does not necessarily appear to impact work productivity. In fact, when employees are feeling burned-out, they could relieve stress via such non-work-related activities and hence maintain their work engagement. For example, at the time when use of the Internet was just emerging in the workplace, Internet recreation in the workplace was found to make employees more creative [ 74 ] and help employees to become accustomed to the new and advanced systems [ 75 ].

Therefore, management may wish to offer their employees a flexible working hour to help the employees to meet their needs when they are working from home [ 57 ]. Management could also encourage employees to set boundaries, as long as the committed working hours per week are achieved, thereby enabling them to secure the balance between their work and home life. Feeling happy, satisfied, and enthusiastic when working from home can help workers maintain a high level of productivity [ 76 ].

Limitations and future research

The present study had certain limitations. First, the significance of the research findings is dependent on the reliability of self-reports. To minimize bias, in this study we attempted to collect the most representative responses, including through application of the RRT for sensitive questions and through use of an anonymous, web-based survey, as well as through the choice of highly diverse participants. A pretest and pilot test were also conducted before the actual survey, to ensure the quality of the study. Second, this study was based on 500 employees in Hong Kong, a group that certainly cannot represent the worldwide population. In addition, the working and living environments in Hong Kong may be significantly different from those in other regions or countries. Additionally research among more heterogeneous samples will be needed to test the research model.

Conclusions

Although managers are trying their best to maintain their employees’ work productivity at the same level as that prior to the COVID-19 pandemic, it is also important for them to maintain a good balance for their employees between work and life and provide flexibility in their working time and arrangements. Our research findings suggest that a healthy balance between work and home life makes employees feel happier, and in turn has a significant effect on them maintaining a good level of work productivity when they are required to switch to WFH. Meanwhile, an imbalance between work and life would have a negative impact on employees’ psychological well-being, spurring them to carry out non-work-related activities during working hours. Interestingly, those non-work-related activities apparently do not influence WFH employees’ work productivity. We conclude that balance is the key to successful implementation of sudden and forced WFH during the COVID-19 pandemic and achieving a smooth transition from working at the office to working from home.

Supporting information

S1 table. list of all items and measures..

Suffixes with–S and–U indicate that the items are sensitive questions and are paired with unrelated questions.

https://doi.org/10.1371/journal.pone.0261969.s001

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Working from home: Assessing the research evidence

Preliminary recommendations arising from enforced homeworking during the COVID-19 lockdown

The COVID-19-induced lockdown offered unprecedented opportunities for UK employers to trial working from home at scale. This prompted the CIPD to conduct research into the lessons that employers can take from the period of enforced homeworking to improve their flexible working offering in the future.

This eight-month research project aimed to understand the opportunities and challenges from this period of enforced homeworking and to offer recommendations that seek to overcome these challenges and take advantage of the opportunities. The full findings of the research can be found in our report Flexible working: Lessons from the pandemic .

While these findings are based on UK data, the broader trends and implications should be of interest wherever you are based.

What do we hope to learn from this research?

The aim of this research is to:

• Identify the opportunities and challenges presented by widespread homeworking during the COVID-19 pandemic.
• Explore how the COVID-19 pandemic has affected the willingness of employers, and of line managers, to allow or encourage homeworking and other forms of flexible working.

The first phase of this research is a review of existing research on homeworking. The recommendations from this first phase are outlined below and you can also download a copy of the interim report to find out more about these preliminary recommendations.

The next stage of the research involves conducting qualitative and quantitative research with workers in different occupations and settings. The findings from this research are outlined in our report  Flexible working: Lessons from the pandemic .

Preliminary findings 

The first phase of this research identified eight key themes from the review of existing research on homeworking during the COVID-19 lockdown:

• Increased productivity among homeworkers is often achieved through work intensification.
• For some workers, homeworking can provide a more productive environment because there are fewer distractions.
• Knowledge sharing and team relationships often suffer – unless task-related processes are designed to take location into account.
• Innovation can suffer if knowledge sharing and team relationships deteriorate.
• Social isolation can be a problem for some workers, but this depends on personality and lifestyle.
• Avoiding the commute is a major benefit for most. 
• Attention to work-life boundaries is helpful not just for homeworkers but for anyone in the digital age.
• The career downsides are real and need to be managed. 

Preliminary recommendations for employers 

1. Be aware of the differences between ‘standard’ and COVID-enforced homeworking

Employers need to distinguish between homeworking experiences that are specific to the pandemic, and those lessons that can be taken forward into the post-pandemic era. The specific challenges we saw during COVID-enforced homeworking (poor planning, lack of choice, total homeworking and lack of childcare) are not as prevalent during usual homeworking arrangements (and in more usual circumstances) and while employers can learn from these challenges they should not be used to judge the effectiveness of homeworking arrangements. Instead, employers should work with employees on an individual level to understand and overcome any challenges of individual homeworking arrangements and build on any opportunities presented.

2. Homeworking is here to stay – design your working practices to suit all locations

Employers should design work processes that support both homeworkers and conventionally-sited employees, concentrating particularly on knowledge sharing, coordination of work, task-related communications and team relationships to encourage performance and innovation. Work intensification and homeworkers’ career development need to be monitored and managed.

Employers should provide support for homeworkers to manage work-home boundaries and avoid isolation, as well as making the cost-benefit calculations around the ‘hard’ elements of technology and office space.

3. Concentrate on partial, voluntary homeworking as part of designing high quality jobs

The appropriate balance of home and office work depends on the type of work, the team processes in place, the manager’s capability, and the degree of cultural support within the organisation, as well as the individual’s home circumstances and the support the employer can provide for technology and equipment.

As with any kind of flexible working – or indeed any kind of job design – a person-centred approach is most likely to result in a solution that suits the individual, the team and the organisation.

Download the report below

Working from home – Assessing the research evidence

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Discover our practice guidance and recommendations to tackle bullying and harassment in the workplace.

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A Wales summary of the CIPD Good Work Index 2024 survey report

Dedicated analysis of job quality and its impact on working lives in Scotland

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The CIPD Good Work Index provides an annual snapshot of job quality in the UK, giving insight to drive improvement to working lives

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This New Hybrid Work Study Could Help Reconcile The War Over Work From Home

A randomized controlled trial published in the leading academic journal Nature finds two days of working from home improved job satisfaction and reduced turnover when compared to those working in offices five days a week.

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A new study in the academic journal Nature used a randomized controlled trial to look at the impact of hybrid work schedules on turnover, job satisfaction and performance.

T he long-simmering debate over whether remote work hurts productivity or dampens worker performance has reached the peak of academic prestige: A study in the journal Nature.

Leaders eager to get workers back to the office often believe it leads to things like lower worker output and an erosion of workplace culture. But a new paper to be published Wednesday in the leading academic journal by Stanford University economist Nicholas Bloom and his co-authors suggests new evidence for advantages to hybrid schedules. A randomized controlled trial of employees in a tech firm based in China found that two days of work from home and three days in the office reduced quit rates, improved job satisfaction and had no impact on performance, when compared with employees who worked full-time in the office.

“Everyone’s heard of Nature ,” says Bloom. If you’re talking about flexible work arrangements with a CEO who wants people back full time, “having a large, randomized controlled trial—they can still ignore it, but it gets a lot harder.”

The study randomly divided 1,612 workers at Trip.com, a large global travel firm, by whether they had even or odd birthdates. One group was able to work from home on Wednesdays and Fridays; the other worked in the office all five days. The researchers found that for those with hybrid schedules, attrition rates dropped by one-third over the six-month experiment period—and were even greater for non-managers, female employees and those with long commutes—while work satisfaction scores improved. The hybrid group also did not have significant differences on performance reviews or promotion rates, even for up to two years after the start of the experiment, and there were not significant differences in the lines of code submitted by the software engineers between the two groups.

That trial method—a real-life experiment on two employee groups randomly split by nothing other than birthdate—allowed the researchers to conclude it was the hybrid work schedule that caused the improvements in retention and job satisfaction, Bloom says, rather than simply being coincidental to other factors. “In many studies you don’t [have that],” Bloom says. “There are no differences between people born on even and odd birthdays.”

The study did not look specifically at workers who are full-time remote, or at arrangements where employees have personal choice over where and when they work, which remains a priority for many workers. That debate will likely continue. But the current study offers additional evidence to support the value of employees getting to work from home at least part of the time as opposed to full-time in the office.

In the paper, Bloom and his co-authors note that some may wonder if a possible explanation for the reduced turnover in the hybrid work group is that members of the full-time office group were frustrated they didn’t get the flexible schedule during the experiment. However, turnover rates for full-time office workers were slightly reduced from the six-month period before the experiment, the researchers write in the paper, suggesting that some may have “guessed (correctly) that the policy would be rolled out to all employees once the experiment ended.”

Another effect: The study found that managers at the company shifted their views of hybrid work over the experiment period. Before it started, managers at the company perceived that hybrid work would reduce productivity by 2.6%; by its close, they believed flexible arrangements could improve productivity by 1%. “There is value in experimentation,” the study authors write.

The paper follows months of debate over the impact of remote work on company culture, employee productivity and potential downsides to innovation or collaboration. Bloom, who has studied remote work for decades, prompted a stir last year when a working paper that reviewed existing studies on the topic pointed to research showing that fully remote workforces appeared to have slightly reduced productivity on average. But the studies also showed that when the work schedule was well-managed and hybrid at least some of the time, the effect was flat or slightly positive, Bloom told Forbes at the time .

Indeed, an early paper by Bloom looked at the same company, Trip.com (one of its co-founders, James Liang , is a co-author and former PhD student of Bloom’s). It found that among a group of remote call center agents who worked in person just one day a week, productivity increased 13% and turnover fell by half.

The newer study looked at workers in fields like marketing, software engineering, finance and accounting, helping to address concerns that past studies on lower-paid employees doing repetitive tasks with more objective measurements may not be generalizable to the workforce at large. “These are creatives, they’re in graduate or professional jobs, and they’re innovating, creating, training,” Bloom says of participants in the current study.

Trip.com, Bloom says, was seeking a way to reduce costs in doing the experiment, estimating that each employee who quit cost the company $20,000 in recruiting and training, the paper reports. As a result of the study, the company decided to extend the hybrid policy to all employees.

“There are good and bad things about working from home, but it turns out with hybrid they roughly net each other out,” says Bloom. “Employees were dramatically happier if they get to work from home two days a week, and as a result their quit rates fell by a third. ... The company looked at this and said, ‘what’s not to like?’ ”

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Researchers working from home: Benefits and challenges

Balazs Aczel

1 Institute of Psychology, ELTE Eotvos Lorand University, Budapest, Hungary

Marton Kovacs

2 Doctoral School of Psychology, ELTE Eotvos Lorand University, Budapest, Hungary

Tanja van der Lippe

3 Department of Sociology, Utrecht University, Utrecht, The Netherlands

Barnabas Szaszi

Associated data.

All research materials, the collected raw and processed anonymous data, just as well the code for data management and statistical analyses are publicly shared on the OSF page of the project: OSF: https://osf.io/v97fy/ .

The flexibility allowed by the mobilization of technology disintegrated the traditional work-life boundary for most professionals. Whether working from home is the key or impediment to academics’ efficiency and work-life balance became a daunting question for both scientists and their employers. The recent pandemic brought into focus the merits and challenges of working from home on a level of personal experience. Using a convenient sampling, we surveyed 704 academics while working from home and found that the pandemic lockdown decreased the work efficiency for almost half of the researchers but around a quarter of them were more efficient during this time compared to the time before. Based on the gathered personal experience, 70% of the researchers think that in the future they would be similarly or more efficient than before if they could spend more of their work-time at home. They indicated that in the office they are better at sharing thoughts with colleagues, keeping in touch with their team, and collecting data, whereas at home they are better at working on their manuscript, reading the literature, and analyzing their data. Taking well-being also into account, 66% of them would find it ideal to work more from home in the future than they did before the lockdown. These results draw attention to how working from home is becoming a major element of researchers’ life and that we have to learn more about its influencer factors and coping tactics in order to optimize its arrangements.

Introduction

Fleeing from the Great Plague that reached Cambridge in 1665, Newton retreated to his countryside home where he continued working for the next year and a half. During this time, he developed his theories on calculus, optics, and the law of gravitation—fundamentally changing the path of science for centuries. Newton himself described this period as the most productive time of his life [ 1 ]. Is working from home indeed the key to efficiency for scientists also in modern times? A solution for working without disturbance by colleagues and being able to manage a work-life balance? What personal and professional factors influence the relation between productivity and working from home? These are the main questions that the present paper aims to tackle. The Covid-19 pandemic provides a unique opportunity to analyze the implications of working from home in great detail.

Working away from the traditional office is increasingly an option in today’s world. The phenomenon has been studied under numerous, partially overlapping terms, such as telecommuting, telework, virtual office, remote work, location independent working, home office. In this paper, we will use ‘working from home’ (WFH), a term that typically covers working from any location other than the dedicated area provided by the employer.

The practice of WFH and its effect on job efficiency and well-being are reasonably well explored outside of academia [ 2 , 3 ]. Internet access and the increase of personal IT infrastructure made WFH a growing trend throughout the last decades [ 4 ]. In 2015, over 12% of EU workers [ 5 ] and near one-quarter of US employees [ 6 ] worked at least partly from home. A recent survey conducted among 27,500 millennials and Gen Z-s indicated that their majority would like to work remotely more frequently [ 7 ]. The literature suggests that people working from home need flexibility for different reasons. Home-working is a typical solution for those who need to look after dependent children [ 8 ] but many employees just seek a better work-life balance [ 7 ] and the comfort of an alternative work environment [ 9 ].

Non-academic areas report work-efficiency benefits for WFH but they also show some downsides of this arrangement. A good example is the broad-scale experiment in which call center employees were randomly assigned to work from home or in the office for nine months [ 10 ]. A 13% work performance increase was found in the working from home group. These workers also reported improved work satisfaction. Still, after the experiment, 50% of them preferred to go back to the office mainly because of feeling isolated at home.

Home-working has several straightforward positive aspects, such as not having to commute, easier management of household responsibilities [ 11 ] and family demands [ 12 ], along with increased autonomy over time use [ 13 , 14 ], and fewer interruptions [ 15 , 16 ]. Personal comfort is often listed as an advantage of the home environment [e.g., 15 ], though setting up a home office comes with physical and infrastructural demands [ 17 ]. People working from home consistently report greater job motivation and satisfaction [ 4 , 11 , 18 , 19 ] which is probably due to the greater work-related control and work-life flexibility [ 20 ]. A longitudinal nationally representative sample of 30,000 households in the UK revealed that homeworking is positively related with leisure time satisfaction [ 21 ], suggesting that people working from home can allocate more time for leisure activities.

Often-mentioned negative aspects of WFH include being disconnected from co-workers, experiencing isolation due to the physical and social distance to team members [ 22 , 23 ]. Also, home-working employees reported more difficulties with switching off and they worked beyond their formal working hours [ 4 ]. Working from home is especially difficult for those with small children [ 24 ], but intrusion from other family members, neighbours, and friends were also found to be major challenges of WFH [e.g., 17 ]. Moreover, being away from the office may also create a lack of visibility and increases teleworkers’ fear that being out of sight limits opportunities for promotion, rewards, and positive performance reviews [ 25 ].

Importantly, increased freedom imposes higher demands on workers to control not just the environment, but themselves too. WFH comes with the need to develop work-life boundary control tactics [ 26 ] and to be skilled at self-discipline, self-motivation, and good time management [ 27 ]. Increased flexibility can easily lead to multitasking and work-family role blurring [ 28 ]. Table 1 provides non-comprehensive lists of mostly positive and mostly negative consequences of WFH, based on the literature reviewed here.

Compared to the private sector, our knowledge is scarce about how academics experience working from home. Researchers in higher education institutes work in very similar arrangements. Typically, they are expected to personally attend their workplace, if not for teaching or supervision, then for meetings or to confer with colleagues. In the remaining worktime, they work in their lab or, if allowed, they may choose to do some of their tasks remotely. Along with the benefits on productivity when working from home, academics have already experienced some of its drawbacks at the start of the popularity of personal computers. As Snizek observed in the ‘80s, “(f)aculty who work long hours at home using their microcomputers indicate feelings of isolation and often lament the loss of collegial feedback and reinforcement” [page 622, 29 ].

Until now, the academics whose WFH experience had been given attention were mostly those participating in online distance education [e.g., 30 , 31 ]. They experienced increased autonomy, flexibility in workday schedule, the elimination of unwanted distractions [ 32 ], along with high levels of work productivity and satisfaction [ 33 ], but they also observed inadequate communication and the lack of opportunities for skill development [ 34 ]. The Covid-19 pandemic provided an opportunity to study the WFH experience of a greater spectrum of academics, since at one point most of them had to do all their work from home.

We have only fragmented knowledge about the moderators of WFH success. We know that control over time is limited by the domestic tasks one has while working from home. The view that women’s work is more influenced by family obligations than men’s is consistently shown in the literature [e.g., 35 – 37 ]. Sullivan and Lewis [ 38 ] argued that women who work from home are able to fulfil their domestic role better and manage their family duties more to their satisfaction, but that comes at the expense of higher perceived work–family conflict [see also 39 ]. Not surprisingly, during the COVID-19 pandemic, female scientists suffered a greater disruption than men in their academic productivity and time spent on research, most likely due to demands of childcare [ 40 , 41 ].

In summary, until recently, the effect of WFH on academics’ life and productivity received limited attention. However, during the recent pandemic lockdown, scientists, on an unprecedented scale, had to find solutions to continue their research from home. The situation unavoidably brought into focus the merits and challenges of WFH on a level of personal experience. Institutions were compelled to support WFH arrangements by adequate regulations, services, and infrastructure. Some researchers and institutions might have found benefits in the new arrangements and may wish to continue WFH in some form; for others WFH brought disproportionately larger challenges. The present study aims to facilitate the systematic exploration and support of researchers’ efficiency and work-life balance when working from home.

Materials and methods

Our study procedure and analysis plan were preregistered at https://osf.io/jg5bz (all deviations from the plan are listed in S1 File ). The survey included questions on research work efficiency, work-life balance, demographics, professional and personal background information. The study protocol has been approved by the Institutional Review Board from Eotvos Lorand University, Hungary (approval number: 2020/131). The Transparency Report of the study, the complete text of the questionnaire items and the instructions are shared at our OSF repository: https://osf.io/v97fy/ .

As the objective of this study was to gain insight about researchers’ experience of WFH, we aimed to increase the size and diversity of our sample rather than ascertaining the representativeness of our sample. Therefore, we distributed our online survey link among researchers in professional newsletters, university mailing lists, on social media, and by sending group-emails to authors (additional details about sampling are in S1 File ). As a result of the nature of our sampling strategy, it is not known how many researchers have seen our participation request. Additionally, we did not collect the country of residence of the respondents. Responses analyzed in this study were collected between 2020-04-24 and 2020-07-13. Overall, 858 individuals started the survey and 154 were excluded because they did not continue the survey beyond the first question. As a result, 704 respondents were included in the analysis.

We sent the questionnaire individually to each of the respondents through the Qualtrics Mailer service. Written informed consent and access to the preregistration of the research was provided to every respondent before starting the survey. Then, respondents who agreed to participate in the study could fill out the questionnaire. To encourage participation, we offered that upon completion they can enter a lottery to win a 100 USD voucher.

This is a general description of the survey items. The full survey with the display logic and exact phrasing of the items is transported from Qualtrics and uploaded to the projects’ OSF page: https://osf.io/8ze2g/ .

Efficiency of research work

The respondents were asked to compare the efficiency of their research work during the lockdown to their work before the lockdown. They were also asked to use their present and previous experience to indicate whether working more from home in the future would change the efficiency of their research work compared to the time before the lockdown. For both questions, they could choose among three options: “less efficient”; “more efficient”, and “similarly efficient”.

Comparing working from home to working in the office

Participants were asked to compare working from home to working from the office. For this question they could indicate their preference on a 7-point dimension (1: At home; 7: In the office), along 15 efficiency or well-being related aspects of research work (e.g., working on the manuscript, maintaining work-life balance). These aspects were collected in a pilot study conducted with 55 researchers who were asked to indicate in free text responses the areas in which their work benefits/suffers when working from home. More details of the pilot study are provided in S1 File .

Actual and ideal time spent working from home

To study the actual and ideal time spent working from home, researcher were asked to indicate on a 0–100% scale (1) what percentage of their work time they spent working from home before the pandemic and (2) how much would be ideal for them working from home in the future concerning both research efficiency and work-life balance.

Feasibility of working more from home

With simple Yes/No options, we asked the respondents to indicate whether they think that working more from home would be feasible considering all their other duties (education, administration, etc.) and the given circumstances at home (infrastructure, level of disturbance).

Background information

Background questions were asked by providing preset lists concerning their academic position (e.g., full professor), area of research (e.g., social sciences), type of workplace (e.g., purely research institute), gender, age group, living situation (e.g., single-parent with non-adult child(ren)), and the age and the number of their children.

The respondents were also asked to select one of the offered options to indicate: whether or not they worked more from home during the coronavirus lockdown than before; whether it is possible for them to collect data remotely; whether they have education duties at work; if their research requires intensive team-work; whether their home office is fully equipped; whether their partner was also working from home during the pandemic; how far their office is from home; whether they had to do home-schooling during the pandemic; whether there was someone else looking after their child(ren) during their work from home in lockdown. When the question did not apply to them, they could select the ‘NA’ option as well.

Data preprocessing and analyses

All the data preprocessing and analyses were conducted in R [ 42 ], with the use of the tidyverse packages [ 43 ]. Before the analysis of the survey responses, we read all the free-text comments to ascertain that they do not contain personal information and they are in line with the respondent’s answers. We found that for 5 items the respondents’ comments contradicted their survey choices (e.g., whether they have children), therefore, we excluded the responses of the corresponding items from further analyses (see S1 File ). Following the preregistration, we only conducted descriptive statistics of the survey results.

The summary of the key demographic information of the 704 complete responses is presented in Table 2 . A full summary of all the collected background information of the respondents are available in S1 File .

The results showed that 94% (n = 662) of the surveyed researchers worked more from home during the COVID-19 lockdown compared to the time before. Of these researchers, 47% found that due to working more from home their research became, in general, less efficient, 23% found it more efficient, and 30% found no difference compared to working before the lockdown. Within this database, we also explored the effect of the lockdown on the efficiency of people living with children (n = 290). Here, we found that 58% of them experienced that due to working more from home their research became, in general, less efficient, 20% found it more efficient, and 22% found no difference compared to working before the lockdown. Of those researchers who live with children, we found that 71% of the 21 single parents and 57% of the 269 partnered parents found working less efficient when working from home compared to the time before the lockdown.

When asking about how working more from home would affect the efficiency of their research after the lockdown, of those who have not already been working from home full time (n = 684), 29% assumed that it could make their research, in general, less efficient, 29% said that it would be more efficient, and 41% assumed no difference compared to the time before the lockdown ( Fig 1 ).

Focusing on the efficiency of the subgroup of people who live with children (n = 295), we found that for 32% their research work would be less efficient, for 30% it would be no different, and for 38% it would be more efficient to work from home after the lockdown, compared to the time before the lockdown.

When comparing working from home to working in the office in general, people found that they can better achieve certain aspects of the research in one place than the other. They indicated that in the office they are better at sharing thoughts with colleagues, keeping in touch with their team, and collecting data, whereas at home they are better at working on their manuscript, reading the literature, and analyzing their data ( Fig 2 ).

The bars represent response averages of the given aspects.

We also asked the researchers how much of their work time they spent working from home in the past, and how much it would be ideal for them to work from home in the future concerning both research efficiency and well-being. Fig 3 shows the distribution of percentages of time working from home in the past and in an ideal future. Comparing these values for each researcher, we found that 66% of them want to work more from home in the future than they did before the lockdown, whereas 16% of them want to work less from home, and 18% of them want to spend the same percentage of their work time at home in the future as before. (These latter calculations were not preregistered).

Taken all their other duties (education, administration, etc.) and provided circumstances at home (infrastructure, level of disturbance), of researchers who would like to work more from home in the future (n = 461), 86% think that it would be possible to do so. Even among those who have teaching duties at work (n = 376), 84% think that more working from home would be ideal and possible.

Researchers’ work and life have radically changed in recent times. The flexibility allowed by the mobilization of technology and the continuous access to the internet disintegrated the traditional work-life boundary. Where, when, and how we work depends more and more on our own arrangements. The recent pandemic only highlighted an already existing task: researchers’ worklife has to be redefined. The key challenge in a new work-life model is to find strategies to balance the demands of work and personal life. As a first step, the present paper explored how working from home affects researchers’ efficiency and well-being.

Our results showed that while the pandemic-related lockdown decreased the work efficiency for almost half of the researchers (47%), around a quarter (23%) of them experienced that they were more efficient during this time compared to the time before. Based on personal experience, 70% of the researchers think that after the lockdown they would be similarly (41%) or more efficient (29%) than before if they could spend more of their work-time at home. The remaining 30% thought that after the lockdown their work efficiency would decrease if they worked from home, which is noticeably lower than the 47% who claimed the same for the lockdown period. From these values we speculate that some of the obstacles of their work efficiency were specific to the pandemic lockdown. Such obstacles could have been the need to learn new methods to teach online [ 44 ] or the trouble adapting to the new lifestyle [ 45 ]. Furthermore, we found that working from the office and working from home support different aspects of research. Not surprisingly, activities that involve colleagues or team members are better bound to the office, but tasks that need focused attention, such as working on the manuscript or analyzing the data are better achieved from home.

A central motivation of our study was to explore what proportion of their worktime researchers would find ideal to work from home, concerning both research efficiency and work-life balance. Two thirds of the researchers indicated that it would be better to work more from home in the future. It seemed that sharing work somewhat equally between the two venues is the most preferred arrangement. A great majority (86%) of those who would like to work more from home in the future, think that it would be possible to do so. As a conclusion, both the work and non-work life of researchers would take benefits should more WFH be allowed and neither workplace duties, nor their domestic circumstances are limits of such a change. That researchers have a preference to work more from home, might be due to the fact that they are more and more pressured by their work. Finishing manuscripts, and reading literature is easier to find time for when working from home.

A main message of the results of our present survey is that although almost half of the respondents reported reduced work efficiency during the lockdown, the majority of them would prefer the current remote work setting to some extent in the future. It is important to stress, however, that working from home is not equally advantageous for researchers. Several external and personal factors must play a role in researchers’ work efficiency and work-life balance. In this analysis, we concentrated only on family status, but further dedicated studies will be required to gain a deeper understanding of the complex interaction of professional, institutional, personal, and domestic factors in this matter. While our study could only initiate the exploration of academics’ WFH benefits and challenges, we can already discuss a few relevant aspects regarding the work-life interface.

Our data show that researchers who live with dependent children can exploit the advantages of working from home less than those who do not have childcare duties, irrespective of the pandemic lockdown. Looking after children is clearly a main source of people’s task overload and, as a result, work-family conflict [ 46 , 47 ]. As an implication, employers should pay special respect to employees’ childcare situations when defining work arrangements. It should be clear, however, that other caring responsibilities should also be respected such as looking after elderly or disabled relatives [ 48 ]. Furthermore, to avoid equating non-work life with family-life, a broader diversity of life circumstances, such as those who live alone, should be taken into consideration [ 49 ].

It seems likely that after the pandemic significantly more work will be supplied from home [ 50 ]. The more of the researchers’ work will be done from home in the future, the greater the challenge will grow to integrate their work and non-work life. The extensive research on work-life conflict, should help us examine the issue and to develop coping strategies applicable for academics’ life. The Boundary Theory [ 26 , 51 , 52 ] proved to be a useful framework to understand the work-home interface. According to this theory, individuals utilize different tactics to create and maintain an ideal level of work-home segmentation. These boundaries often serve as “mental fences” to simplify the environment into domains, such as work or home, to help us attend our roles, such as being an employee or a parent. These boundaries are more or less permeable, depending on how much the individual attending one role can be influenced by another role. Individuals differ in the degree to which they prefer and are able to segment their roles, but each boundary crossing requires a cognitive “leap” between these categories [ 53 ]. The source of conflict is the demands of the different roles and responsibilities competing for one’s physical and mental resources. Working from home can easily blur the boundary between work and non-work domains. The conflict caused by the intrusion of the home world to one’s work time, just as well the intrusion of work tasks to one’s personal life are definite sources of weakened ability to concentrate on one’s tasks [ 54 ], exhaustion [ 55 ], and negative job satisfaction [ 56 ].

What can researchers do to mitigate this challenge? Various tactics have been identified for controlling one’s borders between work and non-work. One can separate the two domains by temporal, physical, behavioral, and communicative segmentation [ 26 ]. Professionals often have preferences and self-developed tactics for boundary management. People who prefer tighter boundary management apply strong segmentation between work and home [ 57 , 58 ]. For instance, they don’t do domestic tasks in worktime (temporal segmentation), close their door when working from home (physical segmentation), don’t read work emails at weekends (behavioral segmentation), or negotiate strict boundary rules with family members (communicative segmentation). People on the other on one side of the segmentation-integration continuum, might not mind, or cannot avoid, ad-hoc boundary-crossings and integrate the two domains by letting private space and time be mixed with their work.

Researchers, just like other workers, need to develop new arrangements and skills to cope with the disintegration of the traditional work-life boundaries. To know how research and education institutes could best support this change would require a comprehensive exploration of the factors in researchers’ WFH life. There is probably no one-size-fits-all approach to promote employees’ efficiency and well-being. Life circumstances often limit how much control people can have over their work-life boundaries when working from home [ 59 ]. Our results strongly indicate that some can boost work efficiency and wellbeing when working from home, others need external solutions, such as the office, to provide boundaries between their life domains. Until we gain comprehensive insight about the topic, individuals are probably the best judges of their own situation and of what arrangements may be beneficial for them in different times [ 60 ]. The more autonomy the employers provide to researchers in distributing their work between the office and home (while not lowering their expectations), the more they let them optimize this arrangement to their circumstances.

Our study has several limitations: to investigate how factors such as research domain, seniority, or geographic location contribute to WFH efficiency and well-being would have needed a much greater sample. Moreover, the country of residence of the respondents was not collected in our survey and this factor could potentially alter the perception of WFH due to differing social and infrastructural factors. Whereas the world-wide lockdown has provided a general experience to WFH to academics, the special circumstances just as well biased their judgment of the arrangement. With this exploratory research, we could only scratch the surface of the topic, the reader can probably generate a number of testable hypotheses that would be relevant to the topic but we could not analyze in this exploration.

Newton working in lockdown became the idealized image of the home-working scientist. Unquestionably, he was a genius, but his success probably needed a fortunate work-life boundary. Should he had noisy neighbours, or taunting domestic duties, he might have achieved much less while working from home. With this paper, we aim to draw attention to how WFH is becoming a major element of researchers’ life and that we have to be prepared for this change. We hope that personal experience or the topic’s relevance to the future of science will invite researchers to continue this work.

Supporting information

Acknowledgments.

We would like to thank Szonja Horvath, Matyas Sarudi, and Zsuzsa Szekely for their help with reviewing the free text responses.

Funding Statement

TVL's contribution is part of the research program Sustainable Cooperation – Roadmaps to Resilient Societies (SCOOP). She is grateful to the Netherlands Organization for Scientific Research (NWO) and the Dutch Ministry of Education, Culture and Science (OCW) for their support in the context of its 2017 Gravitation Program (grant number 024.003.025).

Data Availability

• PLoS One. 2021; 16(3): e0249127.

Decision Letter 0

PONE-D-20-30010

Dear Dr. Aczel,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Johnson Chun-Sing Cheung, D.S.W.

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Comments to the Author

Reviewer #1: PONE-D-20-30010

Title: Researchers working from home: Benefits and challenges

Reviewer’s article summary: This manuscript provides results from a survey on work-life balance among academics who switched to remote work-from-home during the Covid-19 pandemic. I believe the article contributes insight on both the work-life balance among academics and how researchers have experienced their work during the pandemic, and will be of interest to the PloS One audience. Below, please see suggestions for improving the manuscript.

Abstract: Please include a brief statement about methodology, including sample size of the survey population, how the survey was conducted (convenience sample? Recruitment strategy?).

Introduction: The authors questions, “Is the relation between working from home and productivity influenced by personal and professional factors?” This question seems like a non-starter – how could working from home not be influenced by personal and professional factors? Advise revising this question to better focus your key arguments (i.e. what personal and professional factors most influence the productivity of working from home?).

“just as well increased autonomy over time use” – awkward sentence; please revise to clarify.

“physical and social distance to teal members” – do you mean team members?

Table 1 – please refer to the table in the text to guide the audience to this comparison of pros/cons in context of the introduction. It may also better position this manuscript within the literature to include more details from the studies that list these pros/cons (i.e. include the % of people who have reported each of the pros/cons within the table itself, and include a reference to the study where each % was derived).

Reference to Snizek in the 80’s – the benefit of including this quote is questionable; it would be more helpful to include more recent literature on this point since generational changes have perhaps changed this experience.

“just as well high levels of work productivity and satisfaction” – awkward sentence, please revise for clarity.

Materials and Methods: Please provide the study number for IRB approval.

The authors do include links to their study procedure, but it would be helpful for a more complete overview of the procedure within the manuscript so the audience can more easily ascertain the methodology employed. In comparison, the “Materials” section provides intricate detail that may not be necessary (in this reviewer’s opinion, it would be more efficient to simply list the types of questions asked—i.e. “Survey questions asked participants to report on changes that occurred in relation to research work efficiency, comparison of home to office work, amount of time spent…”(etc. or something of this nature)–with a link to the actual survey instrument).

There is no section or statement regarding data analysis. Please describe your analytical procedure (descriptive statistics, any regressions?) and software used for analysis.

Results – Recommend providing a demographics table in the manuscript that displays sample size and % for the information described in the “background information” section. Please include data about the countries where respondents live, if available; if not available, please include a statement regarding residence in the Methods section (i.e. was the sample all within a single country?).

Figures – please include sample size (n = ) in the figure titles.

” From these values we can assume that some of the obstacles of their work were specific to the pandemic lockdown and not directly to working from home” – please explain and clarify.

“…seems to be a generally wanted and beneficial model of work” – this statement seems to ignore the result that nearly half of respondents reported being less efficient during the pandemic. Recommend revising this statement, and including a summary that the results indicate although almost half of the respondents reported reduced work efficiency, they would prefer the current remote work setting to some extent in the future. May also be useful to note that the implications of this require further investigation – what is it about this new work situation that people prefer? What amount of time did people previously spend in commute that they now can use for other tasks or personal interests? What other factors have changed that make the current situation more preferred?

#5 – incomplete reference

There are several references that are now quite old (1987, 1996, 1999, 2001, 2002, 2003, 2006, 2007, 2008, 2009…) – Recommend reviewing these carefully to ensure that there is not more recent literature that would shed better light on the subject.

Figure 1 – recommend revising the X axis to show sample size, and the bar labels to show % to increase clarity of results.

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at  gro.solp@serugif . Please note that Supporting Information files do not need this step.

Author response to Decision Letter 0

17 Feb 2021

Dear Dr. Johnson Cheung,

We are happy to submit a revised version of our manuscript to PLOS One.

We would like to thank you and the reviewer for their comments and suggestions.

Below, you can find the detailed responses to all comments in bold.

Balazs Aczel, on behalf of all co-authors

Reviewer #1

We have added these aspects to the Abstract.

We agree with the reviewer and changed that question as suggested.

Table 1 is referred to in the text, just above the table. After due consideration of this suggestion, we judged that three paragraphs about the pros/cons provide sufficient details on the given topic. We found no sound way to merge the empirical reports of the referred studies to provide overall percentages of people reporting each pros/cons.

The old Snizek reference serves as an indicator that academics have already experienced some of the drawbacks of working from home at the start of the popularity of personal computers. We have now extended our Introduction with more studies from the recent literature, especially with those conducted during the pandemic.

We have now placed the Procedure section before the Materials section. At the beginning of the Materials section, we provide a link to the original content of our Qualtrics survey. This file contains the wording of the items and the display logic of the questions. We would also prefer to keep the detailed description of the survey items in the manuscript as most of the items were developed by the authors for the study. Should the Editor prefer that, we could move the Materials section to the Supporting Information and leave just the link to the exact survey questions in the manuscript.

Now, we state in the Data preprocessing and Analyses section that we used the R statistical software for the analyses and that we report only descriptive statistical results in this study.

The table with the sample size and proportions for all the levels of all the survey items is provided in the Supplementary Materials. However, as the whole table is more than 4 pages long, we think that by including the table in the main text we would corrupt the readability of the manuscript.

Now, we state in the Sampling section that the country of residence of the respondents is not known.

The sample sizes are now included in the figure titles.

We would like to thank the reviewer for pointing out the vagueness of this section. We rephrased the sentence and added one more sentence to the section to clarify our point.

We have now updated this sentence incorporating the reviewer’s suggestion. The updated paragraph is on page 16.

We fixed the incomplete reference.

We agree that some of our references are from the ‘80s or ‘90s, yet they are still good sources of our claims (e.g., how researchers found working from home when personal computers started or that setting up a home office comes with physical and infrastructural demands). Nevertheless, we have added more recent studies to our references, especially from the relevant literature that has been published since our initial submission 5 months ago:

Johnson N, Veletsianos G, Seaman J. US Faculty and Administrators’ Experiences and Approaches in the Early Weeks of the COVID-19 Pandemic. Online Learn. 2020;24(2):6–21.

Barrero JM, Bloom N, Davis SJ. Why Working From Home Will Stick. Univ Chic Becker Friedman Inst Econ Work Pap. 2020;(2020–174).

Korbel JO, Stegle O. Effects of the COVID-19 pandemic on life scientists. Genome Biol. 2020;21(113).

Ghaffarizadeh SA, Ghaffarizadeh SA, Behbahani AH, Mehdizadeh M, Olechowski A. Life and work of researchers trapped in the COVID-19 pandemic vicious cycle. bioRxiv. 2021;

Thank you for the recommendation. We have now modified this figure.

Submitted filename: Response to Reviewers.docx

Decision Letter 1

23 Feb 2021

PONE-D-20-30010R1

Please submit your revised manuscript by Apr 09 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at gro.solp@enosolp . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Reviewer #1:

Reviewer’s response to revisions: Overall, the authors have revised the manuscript to increase clarity and improve understanding of the contributions that this research provides regarding the future outlook for academics working from home. I have a few minor comments:

Limitations: This revised document brings to light the fact that 1) we do not know how the transition to working from home differs between countries since country was not a survey question (which could differ significantly given a number of social and technological/infrastructure factors), and 2) since the analysis only included descriptive statistics there is great potential in learning more from this dataset – and it is wonderful that the dataset will be publicly available. I do recommend adding a statement on limitations, both because it is a best practice, and because it shows that the authors have been thoughtful about the limits of their current analysis.

Results – Recommend providing a demographics table in the manuscript that displays sample size and % for the information described in the “background information” section. I appreciate the authors’ response to this request, but suggest that as a standard practice a shortened version of the key demographics could be provided in a table within the text, and the remainder of the demographics table could be in the supplemental material (having these results within the table is standard in my field since it provides the background information necessary for academics to easily understand the full scope of the results). In response to the question of length, I would suggest that the paragraph that lists the % of respondents who were male/female, etc. could be shortened and simply refer to the table instead.

Figure 1 – recommend revising the X axis to show sample size, and the bar labels to show % to increase clarity of results. The authors responded that this change was made in the revision, but I could not find the updated figure in the revised document.

Author response to Decision Letter 1

Overall, the authors have revised the manuscript to increase clarity and improve

understanding of the contributions that this research provides regarding the future outlook for

academics working from home. I have a few minor comments:

Limitations: This revised document brings to light the fact that 1) we do not know how the

transition to working from home differs between countries since country was not a survey

question (which could differ significantly given a number of social and

technological/infrastructure factors), and 2) since the analysis only included descriptive

statistics there is great potential in learning more from this dataset – and it is wonderful that

the dataset will be publicly available. I do recommend adding a statement on limitations, both

because it is a best practice, and because it shows that the authors have been thoughtful

about the limits of their current analysis.

We have now included a statement of limitations regarding the missing information

on country of residence and made it more clear in the limitations section that the

present study was only exploratory.

Results – Recommend providing a demographics table in the manuscript that displays

sample size and % for the information described in the “background information” section. I

appreciate the authors’ response to this request, but suggest that as a standard practice a

shortened version of the key demographics could be provided in a table within the text, and

the remainder of the demographics table could be in the supplemental material (having

these results within the table is standard in my field since it provides the background

information necessary for academics to easily understand the full scope of the results). In

response to the question of length, I would suggest that the paragraph that lists the % of

respondents who were male/female, etc. could be shortened and simply refer to the table

We have now included the key demographics as a table (Table 2) in the manuscript in

addition to the full summary of all the responses in the Supplementary information.

Figure 1 – recommend revising the X axis to show sample size, and the bar labels to show

% to increase clarity of results. The authors responded that this change was made in the

revision, but I could not find the updated figure in the revised document.

We made sure that all the figures are updated and uploaded with this submission

Submitted filename: Response to Reviewers.pdf

Decision Letter 2

12 Mar 2021

PONE-D-20-30010R2

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The next recession could boost working from home

Key takeaways.

• Levels of working from home are settling down toward about 25 percent of fully paid days. By 2035, we can expect that to rise to 35 percent.
• Technology and workplace culture will likely drive a growth.
• Research shows a mix of hybrid and fully remote working can cut costs and perhaps increase productivity.
• In recessions firms want to cut costs, suggesting a recession could induce a rise in remote working.

I often get asked by managers if working from home could be ended by the next recession. The question comes from the premise that CEOs are itching to drag their employees back to the office five days a week. But they are afraid their employees will jump ship for another remote-friendly job. If a recession hits, the thinking goes, job opportunities will shrivel and managers will be able to force workers back to their office desks without the risk of attrition.

If that scenario seems correct, then sorry. Theory and data suggest the exact opposite. A recession will likely boost the WFH trend.

Let’s start with the theory. Research shows that working from home improves employee recruitment and retention rates, driving down overall labor costs. In one recent randomized control trial working from home reduced quit rates by 35 percent (Bloom, Han and Liang 2024).  In global surveys, employees report that hybrid arrangements with a few WFH days combined with in-office days is worth about as much as an 8 percent pay increase (Aksoy et al. 2022). Working from home also cuts office costs for firms, from lower rent, security, energy and support costs.

On the output side, research shows organized hybrid research has a zero to small positive impact on productivity. Fully remote working has more mixed impacts on productivity but can lead to more than offsetting cost reductions by enabling national or global talent sourcing (Barrero, Bloom and Davis 2023).

In short, a mix of hybrid and fully remote working can cut costs and perhaps increase productivity. In recessions firms want to cut costs at least as much as in booms, suggesting that if anything a recession could induce a rise in remote working.

On the empirical side the industry with the highest levels of working from home in 2024 was the information (tech) sector (Figure 1). Tech has had a tough 18 months, undergoing a drastic slowdown from 2022 onwards, with layoffs across many major firms.

Figure 1. WFH is highest in the information sector

As a Stanford professor I have seen first-hand the swing from boom to bust in technology hiring in Silicon Valley. Outside of the red-hot AI sector it is now extremely hard to get hired in tech, with software job postings down by two-thirds since 2022 [1] . But tech is also leading the way in working from home, suggesting that business slowdowns do not lead to return-to-office mandates. Indeed, I interpret this data as supporting exactly the reverse. The industry facing perhaps the biggest slowdown over the last two years has the highest levels of working from home.

Turning to the longer run, what will  working from home look like a decade from now?

As Figure 2 shows, current U.S. levels of working from home are settling down towards about 25 percent of fully paid days. My prediction by 2035 is this will have risen to 35 percent. This is not a drastic change, but it is material. Two forces are driving my predictions for a longer-run growth of remote work.

Figure 2. WFH is stabilizing at about 27% of days

The first is technology. Technology is everything when it comes to the ability to work from home. As one of four children of two working parents, I grew up seeing what working from home was like in the 1980s. It was very bad.

Before the personal computer, working from home involved carrying around huge wads of paper and the occasional expensive phone call to the office. Conditions improved in the 1990s with the spread of the personal computer and improved again in the 2000s with the development of the internet. Two recent critical breakthroughs were cloud computing — allowing easy file sharing —and video calls that enable higher-quality online meetings.

This rate of technological progress is only going to increase. As economist Frederic M. Scherer noted in 1965, bigger markets induce faster innovation. And the market for working from home technology has increased five-fold. So, expect the rate of technological improvement to surge.

The future will see leaps and bounds in better audio and visual equipment, virtual reality, holograms and remote apps. Figure 3 shows one example of this, which is the share of new patent applications in the U.S. Patent and Trademark office containing three or more mentions of remote work based on Bloom, Davis and Zhestkova (2021). This attempts to count the number of new patents with a strong connection to remote working. We can see a striking growth after 2020 as hardware and software firms swiveled billions of dollars of R&D into improving remote technology. The momentum continues to grow, meaning the technology we use every day to work remotely will continue to improve at an accelerating rate.

Figure 3. Patents in WFH surged post-pandemic

The other major driver is cohort effects on firms and managers. In the monthly Survey on Workplace Attitudes and Arrangements, we poll almost 10,000 Americans a month. We see employees of younger firms have far higher levels of remote work (Figure 4). Younger firms have enthusiastically adopted hybrid and fully remote work. These firms and their managers will grow from today’s smaller and younger firms into tomorrow’s larger firms, expanding remote work with them.

Figure 4. Younger firms have much higher rates of WFH

So, the next time somebody claims the next recession will end remote work, push back with theory and data. The opposite is more likely true.

About the Author

Nick Bloom is a SIEPR Senior Fellow and the Eberle Professor in Stanford’s Department of Economics in the School of Humanities and Sciences. His research focuses on management practices and uncertainty.

[1] Federal Reserve Bank of St. Louis: Software Development Job Postings on Indeed in the United States  

Aksoy, Cevat Giray, Jose Maria Barrero, Nicholas Bloom, Steven J. Davis, Mathias Dolls and Pablo Zarate, 2022. “ Working from Home Around the World ,” Brookings Papers on Economic Activity, Fall.

Barrero, Jose Maria, Nicholas Bloom and Steven J. Davis, “ The Evolution of Working from Home ”, Journal of Economic Perspectives,  Fall 2023.

Bloom, Nicholas, Roubing Han and James Liang, 2024. “ Hybrid working from home improves retention without damaging performance ”, Nature June 2024.

Bloom, Nicholas, Steven J. Davis, and Yulia Zhestkova, 2021. "COVID-19 Shifted Patent Applications toward Technologies that Support Working from Home." American Economic Association, Papers & Proceedings, May.

Scherer, Frederic M, 1965, “Firm size, market structure, opportunity, and the effect of patented inventions”, American Economic Review, December.

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Research: How Remote Work Impacts Women at Different Stages of Their Careers

• Natalia Emanuel,
• Emma Harrington,
• Amanda Pallais

Data on software engineers at a Fortune 500 company revealed that junior and senior women saw contrasting costs and benefits.

While much has been said about the potential benefits of remote work for women, recent research examines how working from home affects the professional development of female software engineers at a Fortune 500 company, revealing that its impact varies by career stage. Junior women engineers benefit significantly from in-person mentorship, receiving 40% more feedback when sitting near colleagues, while senior women face reduced productivity due to increased mentoring duties. Male engineers also benefit from proximity, but less so. The authors suggest that recognizing and rewarding mentorship efforts could mitigate these disparities, ensuring junior women receive adequate support remotely and senior women are properly compensated for their mentoring contributions.

Since the pandemic began, work from home (WFH) has at times been pitched as a means of supporting women in the workplace. This argument often focuses on WFH’s potential to help women juggle the demands of their jobs with the demands of their families. However, WFH’s impact on women’s professional development may vary over their careers. In our research, we explored how WFH impacts young women as they try to get a foothold in their careers and how it affects the often-invisible mentorship work done by more senior women.

• NE Natalia Emanuel serves as a research economist at the New York Fed.
• EH Emma Harrington is a professor at the University of Virginia.
• AP Amanda Pallais is a professor at Harvard University.

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