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Here’s What We Do and Don’t Know About the Effects of Remote Work

Three years into a mass workplace experiment, we are beginning to understand more about how work from home is reshaping workers’ lives and the economy.

By Emma Goldberg

When workplaces are remade by a tectonic shift — women flooding into the work force, the rise of computing — it typically takes some time for economists, psychologists, sociologists and other scholars to gather data on its effects.

So when employers moved suddenly to adopt remote work during the pandemic, with the share of employed Americans working exclusively from home rising to 54 percent in 2020 from 4 percent in 2019, researchers leaped to examine the effects of remote work on employees and the economy at large. Now the early results are emerging. They reveal a mixed economic picture, in which many workers and businesses have made real gains under remote work arrangements, and many have also had to bear costs.

Broadly, the portrait that emerges is this: Brick-and-mortar businesses suffered in urban downtowns, as many people stopped commuting. Still, some kinds of businesses, like grocery stores, have been able to gain a foothold in the suburbs. At the same time, rents rose in affordable markets as remote and hybrid workers left expensive urban housing.

Working mothers have generally benefited from the flexibility of being able to work remotely — more of them were able to stay in the work force. But remote work also seems to bring some steep penalties when it comes to career advancement for women.

Studies of productivity in work-from-home arrangements are all over the map. Some papers have linked remote work with productivity declines of between 8 and 19 percent , while others find drops of 4 percent for individual workers; still other research has found productivity gains of 13 percent or even 24 percent .

Nick Bloom, an economist at Stanford and a prolific scholar on remote work, said the new set of studies showed that productivity differed among remote workplaces depending on an employer’s approach — how well trained managers are to support remote employees and whether those employees have opportunities for occasional meet-ups.

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The Evolution of Working from Home

Working from home rose five-fold from 2019 to 2023, with 40% of US employees now working remotely at least one day a week. The productivity of remote work depends critically on the mode. Fully remote work is associated with about 10% lower productivity than fully in-person work. Challenges with communicating remotely, barriers to mentoring, building culture and issues with self-motivation appear to be factors. But fully remote work can generate even larger cost reductions from space savings and global hiring, making it a popular option for firms. Hybrid working appears to have no impact on productivity but is also popular with firms because it improves employee recruitment and retention. Looking ahead we predict working from home will continue to grow because of the expansion in research and development into new technologies to improve remote working. Hence, the pandemic generated both a one-off jump and a longer-run growth acceleration in working from home.

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• Published: 15 July 2023

Family–work conflict and work-from-home productivity: do work engagement and self-efficacy mediate?

• Seng-Su Tsang 1 ,
• Zhih-Lin Liu 1 &
• Thi Vinh Tran Nguyen 1 , 2  

Humanities and Social Sciences Communications volume  10 , Article number:  419 ( 2023 ) Cite this article

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The shift towards remote work has been expedited by the COVID-19 pandemic, and COVID-19 has increased the need to understand the factors affecting remote work productivity such as family–work conflict, work engagement, and self-efficacy. However, the previous research may not comprehensively capture the intricacies associated with remote work amidst the pandemic. This study proposes a model to explore the relationship between family–work conflict and work-from-home productivity based on role conflict and resource drain theories as well as the family–work-conflict literature. The quantitative approach was used. A questionnaire was distributed using a convenience sampling technique and a response rate of 90.1% (1177 respondents) was achieved. After data cleaning, 785 valid cases were analysed. SPSS 22 and AMOS 20 were used to test the descriptive statistics, reliability, and validity, and the proposed hypotheses were evaluated using Process Macro (Model 5). The findings found that family–work-conflict negatively affected work engagement, self-efficacy, and work-from-home productivity. The negative effect of family–work-conflict on work-from-home productivity was stronger for employees with more work-from-home days than those with fewer. The partial mediation of work engagement and self-efficacy was established. This study contributes to the understanding of remote work productivity during the pandemic, particularly for small and medium-sized enterprise employees. It highlights the regulatory role of working hours when working from home and examines the mediation of self-efficacy in the association between family–work conflict and work-from-home productivity. This study also confirms the gender differences in work-from-home productivity which has been previously inconsistent in the literature. Managerially, the research has practical implications for employers, managers, and the government. Employers should adopt family-friendly policies and offer training programmes to enhance work-from-home productivity. Employers need to pay extra attention to their female employees’ work and family responsibilities and guarantee positive working outcomes through online surveys and two-way communication strategies. Professional training and work-from-home skill development programmes should be provided to boost employee confidence and self-efficacy. Governments and employers should also consider implementing regulations on the duration of working-from-home to avoid negative impacts on work efficiency and family–work conflict.

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Introduction.

This study investigated the association between family–work conflict (FWC) and work-from-home productivity (WFHP) among Taiwanese work-from-home employees in the COVID-19 context. Although Taiwan is recognised as having one of the most successful pandemic response models in Asia and worldwide, the country experienced a COVID-19 outbreak during the time of the study, with more than 14,634 cases recorded as of June 2021. This was considered to be the first wave of COVID-19 in Taiwan. Many preventive measures were implemented during this period including mandatory social distancing, which included a requirement to work from home for many employees. Taiwanese companies and schools adapted to remote work and learning, respectively, and working from home became a key means of social distancing.

Various enterprises worldwide, especially leading companies in developed countries, had long considered the work-from-home (WFH) model as one of the new forms of work, even before COVID-19 appeared (Vyas and Butakhieo, 2021 ). Academics have been interested in the topic of WFH and have undertaken associated studies (Bloom et al., 2014 ; Crosbie and Moore, 2004 ; Dockery and Bawa, 2014 ; Nakrošienė et al., 2019 ). WFH has been a work option for both employers and employees for some time (Rupietta and Beckmann, 2018 ). However, with the COVID-19 outbreak, WFH became mandatory in some countries (Bonacini et al., 2021 ; Wong et al., 2020 ; Yabe et al., 2020 ), attracting the attention of many scholars around the world (Davies, 2021 ). The present research on WFH focuses not only on policy aspects but also on the quantitative aspects that explore the effects of WFH on human psychology (Galanti et al., 2021 ; Song and Gao, 2020 ), job satisfaction, work engagement (WE) (Ahmadi et al., 2022 ; Irawanto et al., 2021 ; Purwanto et al., 2020 ), and work-life balance (WLB) (Putri and Amran, 2021 ).

Other studies have investigated employee performance and WFHP (Afrianty et al. 2022 ; Farooq and Sultana, 2021 ; Feng and Savani, 2020 ; Morikawa, 2022 ; Ramos and Prasetyo, 2020 ; Sutarto et al., 2021 ). Feng and Savani ( 2020 ), for example, examined the gender gaps in WFH outcomes under pandemic conditions. The authors found that the pandemic generated a gender gap in perceived WFHP. The authors argued that women were expected to dedicate more time to the family when both parents worked from home during the day and schools were closed. On the other hand, Morikawa’s ( 2022 ) research on WFH in Japan during the pandemic revealed that WFHP reached ~60–70% of normal workplace productivity. The study also found that productivity was lower for people and businesses who had begun practicing WFH only after the pandemic had spread. The potential impact of the pandemic on working from home (WFH) and productivity was further investigated by Farooq and Sultana ( 2021 ). They found a negative association between WFH and productivity, including a moderating effect of gender on the relationship. Sutarto et al. ( 2021 ) explored the association between employee mental health and productivity during the crisis to ascertain whether the relationship differed depending on select socio-demographic characteristics. The authors found a negative correlation between the WFH employees’ psychological wellbeing and productivity. Further, gender, age, education level, job experience, marital status, and number of children were found to have no association with productivity. In contrast, the issue of working hours has been shown to be negatively related to productivity (Collewet and Sauermann, 2017 ). Nonetheless, based on our literature review, it appears that only a few works have assessed the effect of working hours on WFH productivity within the COVID-19 context.

Although various studies have focused on WFH in the COVID-19 period, as discussed above, and even though many have explored WFHP and the mediating effect of WE, no works have explored the mediating effect of self-efficacy (SE) in terms of predicting WFHP, especially when family–work conflict (FWC) is treated as an antecedent. In terms of the effect that demographic variables have when predicting WFH performance, the productivity effect remains inconsistent. Hanaysha ( 2016 ) suggested broadening the sample to different industry employees in WE and productivity studies to generalise the findings. Additionally, based on our literature review, few studies to date relate to WFHP in Taiwan during the pandemic period, especially for the employees of small and medium-sized enterprises (SMEs). During the first wave of the pandemic, the Taiwanese Government applied strict social distancing policies, including WFH (Cheng et al., 2020 ). This study is therefore pioneering in exploring WFHP in Taiwan during the pandemic period.

Consequent to these research gaps, the differences present in the findings in the literature, and answering the call of Hanaysha ( 2016 ), the present study is based on role conflict and resource drain theories, the FWC literature, and previous empirical studies. It proposes a multiple mediator model to predict the WFHP of employees in Taiwan’s SMEs during the COVID-19 level 3 alert. The primary purpose of this research is to expand on what is currently known about the effects of FWC on WFHP by investigating the mediating effects of WE and SE to determine their effect mechanism. The secondary purpose of the research is to investigate whether the element of working hours moderates the effects of FWC on WFHP to address the research gap in the existing literature concerning the role of working hours in work-from-home productivity, and the below research questions (RQs) which served as a roadmap for the current study:

RQ1: How does Family–Work Conflict affect Work-from-Home Productivity, and what is the mechanism behind their effect?

RQ2: How do working hours moderate the negative association between Family–Work Conflict and Work-from-Home Productivity?

The remainder of the paper is organised as follows: the section “Literature review” provides a comprehensive review of the pertinent literature, including the theoretical background, contextual literature, and core literature, and also presents the research model and hypotheses. Section “Methodology” outlines the research methodology and details the data collection process, while the section “Findings” presents the findings of the study. Finally, the section “Discussion” presents the discussion, conclusions, and comments on the significance and limitations of this research.

Literature review

Working from home: from a flexible working method to a mandatory requirement in the covid-19 era.

WFH refers to the practice of working from home (away from the main office) on one or more days per week (Hill et al., 2003 ). WFH offers employees a multitude of advantages such as flexibility and autonomy, balancing work, performing non-work activities, saving on commuting time, and the additional conveniences of WFH (Afrianty et al., 2022 ; O’Hara, 2014 ). The concept of WFH, first advanced in the 1970s as telework, is the option to perform work at different locations based on technological assistance (van Meel, 2011 ). WFH is a flexible working method for employees that many enterprises and organisations have used for some time (Farooq and Sultana, 2021 ). It has long been linked to workplace programmes that promote WLB and has been frequently used by large corporations in many Western countries to support WLB (Mestre, 1998 ). From a human resource management (HRM) perspective, the positive influence of WFH on employee work attitudes, behaviour, and performance is widely recognised (Crosbie and Moore, 2004 ).

With the COVID-19 outbreaks, WFH has been implemented in 213 countries and territories worldwide (Mukhtar, 2020 ). The ongoing pandemic has brought about significant changes in the way that people work and, in some cases, whether they work at all. A considerable number of individuals have chosen to stay in their homes, either to protect themselves from the disease or due to government-imposed shelter-in-place orders (Farooq and Sultana, 2021 ). Furthermore, many governments have strictly applied social distancing policies, limited mass gatherings, reduced the number of workers in offices, promoted WFH, and applied information technology media to work online (Brodeur et al., 2021 ). Following the implementation of social distancing policies, numerous companies worldwide are still planning to reduce the number of employees working in traditional office settings, thereby enabling and promoting remote work opportunities for their workforce (Xiao et al., 2021 ). As a result, the pandemic has prompted governments and organisations to reconsider their perspectives on WFH and its effectiveness (Farooq and Sultana, 2021 ), with WFH becoming a mandatory government requirement during the pandemic period (Vyas and Butakhieo, 2021 ; Waizenegger et al., 2020 ).

Work from home during the COVID-19 Level 3 Alert in Taiwan

As with other countries and territories worldwide, Taiwan is not immune to the impacts of the pandemic (Lei and Klopack, 2020 ). Although considered one of the more successful countries in fighting the disease (Chien et al., 2020 ; Shokoohi et al., 2020 ) with only 1244 cases recorded up to May 2021, Taiwan faced the first wave of the pandemic with 14,634 cases as reported in June 27 (Taiwan Centers for Disease Control, 2022 ). Currently, the COVID-19 pandemic is a level 3 alert. Prevention solutions are being strictly applied, social distancing is required, and WFH is being promoted by the government and businesses (Kuo, 2021 ; Tan et al., 2021 ).

Theoretical background and hypothesis development

Theoretical foundation, role conflict theory.

Kahn et al. ( 1964 ) proposed the Role Conflict Theory, wherein role conflicts address the “simultaneous occurrence of two (or more) sets of pressures, such that compliance with one would make more difficult compliance with the other” (Kahn et al., 1964 ). FWC is rooted in role conflict theory and posits that individuals possess a limited pool of resources, such as time and energy, which must be allocated among various roles. Consequently, conflicts arising from multiple roles can lead to stress and subsequently diminish employee engagement, efficiency, and productivity (Foy et al., 2019 ; Garg, 2015 ; Wang et al., 2022 ).

Resource drain theory

Resource Drain Theory states that individuals are unable to match the expectations of an additional domain because they must make compromises when distributing their time and energy across two domains (Rothbard and Edwards, 2003 ). According to this theory, the conflict between family and work roles arises frequently due to the finite resources that individuals have, such as energy and time, which must be allocated between the demands of their personal lives and any professional responsibilities (Bozoğlu Batı and Armutlulu, 2020 ). Investing resources in one domain increases the likelihood of not being able to meet the expectations of the other domain. This notion is based on the understanding that work and family are interconnected and intertwined, rather than being separate and distinct entities (Greenhaus and Beutell, 1985 ; Windeler et al., 2017 ). Role conflict theory and resource drain theory constitute the theoretical background underpinning the present study.

Hypothesis development

Family–work conflict and work-from-home productivity.

Work and family, formerly examined as two independent systems, have been investigated as one system more recently, referred to as the work–family system (Tsang et al., 2023 ). Working parents can suffer from stress due to the intersection between the family and work domains which manifests as a sense of FWC. This is when the demands or expectations of one role are incompatible with the demands or expectations of another role, and conflicts arise (Ren and Foster, 2011 ). The more time and energy individuals allocate to one role, the less time and energy they have available for the other role. Insufficient time and energy to fulfill the demands of both family and job responsibilities are therefore key factors contributing to FWC (Marks, 1977 ). In the setting of FWC, various studies have identified two distinct types of role conflict: work interfering with family duties, known as work–family conflict (WFC), and family interfering with work responsibilities, known as FWC (Gutek et al., 1991 ). For research purposes, this research explores FWC as a separate factor. Meanwhile, productivity is commonly defined as the measure of output or quantity of production that results from performance behaviours along with external contextual factors and opportunities (Farooq and Sultana, 2021 ). In the current study, it refers to the employees’ perceived work productivity during the practice of WFH.

FWC has been explored to date in studies on employee satisfaction, engagement, performance, and productivity, including during the COVID-19 period (Graham et al., 2021 ; Karakose et al., 2021 ; Kulik and Ramon, 2022 ). Several studies have found that conflict between family and work had negative consequences on emotional health, physical well-being, and life satisfaction (Cohen and Liani, 2009 ; Schieman et al., 2003 ; Singh and Nayak, 2015 ). As a result, FWC can lower employee productivity and performance (Mohsin and Zahid, 2012 ). For example, an employee’s personal issues spilling into the workplace can cause the employee to waste time and lose focus on the job (Perry, 1982 ). Therefore, the person must rearrange their schedule to accommodate the competing demands of family and work (Barnett, 1994 ).

Another issue that arises is psychological interference which refers to the transfer of moods or emotional states generated in the work domain to the family domain (Hughes et al., 1992 ). At home, psychological interference has an impact on a worker’s mood and energy levels which can subsequently contribute to role conflicts, in turn negatively impacting the employee’s performance at work. Home-to-work spillover, according to Crouter ( 1984 ), is defined as the employee’s distressing objective demands and thoughts on family matters. Additionally, several prior research es have identified a significant negative association between FWC and work productivity (Anderson et al., 2002 ; Reina et al., 2017 ; Witt and Carlson, 2006 ). Based on this theorisation, it is hypothesised that:

H1: FWC has a significant negative effect on WFHP

Work engagement and self-efficacy as mediators

“ WE refers to employees emotional commitment to their company. Engagement is described as the ‘harnessing of the self of organisation members to their job roles; people employ and express themselves physically, cognitively, and emotionally in engagement during role performances” (Nguyen et al., 2021 , p. 205). Moreover, WE is recognised as a positive and fulfilling state of mind related to work. It is characterised by vigour, dedication, and absorption in one’s job or tasks (Nguyen et al., 2021 ; Schaufeli et al., 2002 ). Employees are considered to be engaged with their organisations when they put their all into their work (Nguyen et al., 2021 ). In this study, the definition was adapted to the WFH context. Previous research found that employees who work in a resourceful workplace were energised, enthusiastic, and immersed in their tasks (Bakker and Demerouti, 2014 ; Suan and Nasurdin, 2014 ). Stressful, conflictual, and demanding settings, on the other hand, can undermine employee WE (Coetzee and De Villiers, 2010 ). As a result, FWC is able to negatively affect WE. Therefore, it is hypothesised that:

H2: FWC has a significant negative effect on WE.

Additionally, WE is a critical motivational concept that leads to positive outcomes (C. Barnes and E. Collier, 2013 ), and research suggests that engaged employees contribute to positive organisational outcomes. Business leaders acknowledge that highly engaged employees can significantly enhance productivity and improve a firm’s performance, especially in rapidly evolving markets (Tsang et al., 2023 ). In simpler terms, engaged employees exhibit enthusiasm toward their work, feel a sense of happiness when working for their company, and demonstrate an eagerness to come to work each day (Hanaysha, 2016 ). Furthermore, engaged employees are critical to their organisations’ ability to maintain a competitive advantage and increase work productivity (Albrecht et al., 2015 ; Hanaysha, 2016 ; Takahashi et al., 2022 ). Studies also indicate that WE positively affect employee performance and productivity. Enhancing employee engagement is a positive way to improve work performance and productivity (Demerouti and Cropanzano, 2010 ; Geldenhuys et al., 2014 ). Aryee et al. ( 2016 ) and Şahin and Yozgat ( 2021 ) found that WE mediate the significant negative relationship between FWC and work performance. Based on the above discussion, we argue that in a WFH setting, employee engagement plays a mediating role in the negative effect of FWC on WFHP. Hence, it is hypothesised that:

H3: WE has a significant positive effect on WFHP.

H4: WE mediates the negative relationship between FWC and WFHP.

SE is a critical personal resource that mitigates the negative effects of job demands (Mihalca et al., 2021 ; Perrewé et al., 2002 ) because SE pertains to the individual’s beliefs in their own capabilities to meet the demands of a given situation and successfully perform specific tasks (Mihalca et al., 2021 ). In this study, SE is defined as occupational self-efficacy based on the self-efficacy energy concept of Rigotti et al. ( 2008 ), which describes the level of SE during WFH. As mentioned above, resource drain theory proposes that people who are heavily invested in one position will inevitably lack the resources required to fulfil their other responsibilities. People with FWC devote more time and attention to their family responsibilities, leaving them with fewer resources to meet their professional demands (Peng et al., 2010 ). Cohen and Kirchmeyer ( 1995 ) suggest that having inadequate resources available for work may jeopardise an employee’s ability to fulfil job tasks, lowering their sense of personal competence. Additionally, research findings indicate that trainees who experience more situational constraints, such as conflicting time demands, were less likely to believe that they could master the training materials successfully (Mathieu et al., 1993 ). Prior research also indicates a negative association between FWC and SE (Netemeyer et al., 1996 ; Peng et al., 2010 ). Therefore, the below hypothesis is stated:

H5: FWC has a negative effect on SE.

Previous studies have demonstrated that employees with high self-efficacy (SE) beliefs are more likely to possess confidence in their ability to effectively fulfil the job requirements, even in the presence of various job-related stressors (Nguyen et al., 2021 ; Stetz et al., 2006 ). Therefore, their productivity also tends to be relatively high. According to Walumbwa et al. ( 2005 ), a higher level of job self-efficacy is associated with more positive work attitudes. Additionally, employees with a high level of self-efficacy are more likely to enhance their work performance and productivity (Tabatabaei et al., 2013 ). Therefore, the below hypothesis is stated:

H6: SE has a significant positive effect on WFHP.

Furthermore, there are currently few studies investigating the mediation of SE in the association between FWC and WFHP, especially in the context of the pandemic. However, several studies found that there is a mediation due to SE in the association between FWC and job satisfaction (Peng et al., 2010 ) and between job performance and other input variables (Beltrán-Martín et al., 2017 ). As a result, we argue that SE is a mediator in the relationship between FWC and WFHP, and we hypothesise that:

H7: SE mediates the negative relationship between FWC and WFHP.

Working hours as a moderator between family–work conflict and work-from-home productivity

Collewet and Sauermann ( 2017 ) found that working hours negatively relate to productivity. Moreover, role conflict theory and resource drain theory maintain that people have limited resources, such as time and energy, to distribute across several responsibilities (Kahn et al., 1964 ). Based on this view, an increase in working hours can cause conflicts that affect productivity (Greenhaus and Beutell, 1985 ). In the present study, working hours are measured by the number of assigned WFH days (WFHDs) per week per employee. Therefore, we hypothesise that:

H8: The negative relationship between FWC and WFHP is stronger for employees with more work-from-home days than for the employees with less work-from-home days.

Control variables

Some demographic variables, including gender, age, work experience, the work field, and a number of children, may significantly affect WFHP (Kattenbach et al., 2010 ; Schieman and Glavin, 2008 ; White et al., 2003 ). According to traditional views, work is the role of men while housework and family responsibilities are the duties of women (Gutek et al., 1981 ). This custom has survived despite changes in recent decades. Women continue to devote more time to their children, the household, and the family than men do (Peng et al., 2010 ). Taiwan is strongly influenced by Confucianism, so the view that housework is the duty of women is very evident (Takeuchi and Tsutsui, 2016 ). Therefore, the present study also examines whether WFHP varies between the different categories of these variables. The research model is drawn in Fig. 1 .

A framework for analysing the relationship between family–work conflict and work-from-home productivity, with work engagement and self-efficacy as mediators and work-from-home days (WFHDs) as moderators.

Methodology

Research design.

On the basis of the existing literature, the current study plans to tackle two research questions: ‘How does FWC affect WFHP and what is the mechanism behind the effect?’ and ‘How do working hours moderate the negative association between FWC and WFHP?’ To answer these two research questions, the present study adopted the form of descriptive research because the prior studies have demonstrated that descriptive research explores the relationships between the selected variables (de Vaus, 2001 ; Dulock, 1993 ). Based on two well-known theories, namely the role conflict and resource drain theories, we propose a multiple mediator model to investigate whether FWC has a negative effect on WFHP through the mediating role of WE and SE, as well as whether working hours play a moderating role in the negative association between FWC and WFHP. The research findings will have some theoretical and practical implications in the field.

Research approach

Based on the research design, our study adopted a quantitative approach. The primary data was collected based on a questionnaire survey and then processed using specialised statistical software, SPSS, and AMOS, to test the proposed hypotheses. We adopted the quantitative approach for the following reasons:

Firstly, quantitative research is a systematic and empirical approach that gathers and analyses data using statistical and numerical methods in order to test hypotheses and make generalisations about a population (Mohajan, 2020 ). Through the moderating roles of work engagement and self-efficacy, this method is good for studying complex relationships between the selected variables, such as the association between FWC and WFHP.

Secondly, using a quantitative approach in the current study allowed the authors to determine the strength and direction of the relationships between the variables (Choy, 2014 ; Nardi, 2018 ; Queirós et al., 2017 ) as well as to test the mediating effect of work engagement and self-efficacy on the relationship between family–work conflict and work from home productivity. This was achieved through statistical methods such as regression analysis and path analysis, which helped us identify the relationships between the variables and estimate their effects (Bazeley, 2004 ; Somekhe and Lewin, 2005 ).

Thirdly, a quantitative approach allowed the authors to gather data from a large sample of the population compared to the qualitative approach, which increased the external validity of the findings (Yilmaz, 2013 ).

A printed questionnaire was developed to have two sections. The first section measured the respondents’ basic information. The second section included subscales to measure four constructs, namely FWC, WE, SE, and WFHP.

The first section was comprised of seven questions. The first question, gender, was categorised as (1) female and (2) male. The second question asks for the participant’s age, with four levels (1) 18–30, (2) 31–40, (3) 41–50, and (4) more than 50. The third question, working experience, was divided into four categories, including (1) <2 years, (2) 2–5 years, (3) 6–10 years, and (4) more than 10 years. The fourth question, the working field, included five options, namely: (1) production management, (2) marketing, (3) administrative affairs, (4) financial accounting, and (5) other. The fifth question, the number of children, consisted of four categories including (1) no child, (2) 1 child (3) 2 children, and (4) more than 2 children. The sixth question asked the respondents for the number of WFH days they worked during the COVID–19 level 3 alert in 2021 with four options, specifically (1) <2 days, (2) 2–3 days, (3) 4–5 days, and (4) more than 5 days. The final question, a yes/no question, asked the respondents whether they WFH during the COVID-19 level 3 alert from May 2021 onward. The purpose of this question was to eliminate from our research sample respondents with the answer “no” to ensure that the research object, employees with WFH experiences during the COVID-19 period, was valid.

The second section comprised four subsections. The first subsection, FWC, included five items adapted from Netemeyer et al. ( 1996 ): “My home life interferes with my responsibilities at work, such as getting to work on time, accomplishing daily tasks, and working overtime”, for example. The second subsection was comprised of nine items adapted from Schaufeli et al. ( 2006 ) to assess WE. An example item is “When I work from home, I feel full of energy.” The third subsection, SE, consisted of six items adapted from Rigotti et al. ( 2008 ). An example item is “I can stay calm when I encounter difficulties at work because I can rely on my own abilities.” The final subsection, WFHP, included seven items adapted from Irawanto et al. ( 2021 ): for example, “I’m productive when I work from home.”

In this study, all of these constructs were self-reporting scales using a five-point Likert scale ranging from 1 to 5. The original Cronbach’s Alpha value for the constructs was >0.6 (Nunnally, 1978 ).

Instrument validity and reliability

The instrument’s validity and reliability were ensured. In the beginning, the constructs were chosen from prior studies. After that, they were adjusted for the current investigation. To collect data in Taiwan, the research team employed a multi-step process. Firstly, two high school English teachers translated the original English questionnaire into Chinese. Subsequently, two different English teachers performed a back-translation to ensure the validity of the instrument. Additionally, three professionals in the field of human resource management were invited to assess the suitability of the questions. To enhance face validity, five employees completed the survey and provided feedback for further improvements. A pilot test involving 50 participants was then conducted to ensure comprehensibility and ease of answering the questions. It’s important to note that these participants were excluded from the official survey. Prior to administering the official survey, Cronbach’s alpha value was pre-tested using the pilot test data. The item’s total correlation exceeded 0.3, and Cronbach’s alpha values for the four constructs in the pilot test surpassed the minimum acceptable value of 0.60 (Nunnally, 1978 ).

Sampling method

In the current study, we adopted a non-probability convenience sampling technique to recruit the research participants and select the sample size. Although probability sampling techniques are generally preferred in quantitative research due to their ability to ensure representativeness and to reduce the risk of bias in the sample (DeVellis and Thorpe, 2021 ), other researchers also argue that in some circumstances, non-probability sampling may be used when the population of interest is difficult to define or when the sample size is small and the research question is exploratory in nature (Creswell and Creswell, 2017 ).

In the present study, our population of interest was difficult to define. Moreover, our study was in the context of COVID-19, which can change rapidly within hours, so we, therefore, needed to obtain data quickly for the exploratory research questions. Moreover, other researchers have argued that despite its limitations, non-probability sampling can still provide valuable insights and serve as a starting point for future studies that utilise probability sampling (Creswell and Creswell, 2017 ). Therefore, we believe that it was the most appropriate method for our study given the specific circumstances and research questions.

Data collection and procedure

The questionnaire was developed specifically for the purpose of gathering data from WFH employees in Taiwan. Because it is impossible to know the total number of the target population, we calculated the minimum sample size using the formula proposed by Tabachnick and Fidell ( 1996 ) in addition to regression analysis: n  = 50 + 8 ∗ m (where m is the number of independent variables). Other researchers have similarly noted that larger sample sizes provide a more accurate representation of the characteristics of the populations that they are drawn from (Cronbach et al., 1972 ; Marcoulides and Heck, 1993 ). Therefore, the present study collected higher than the minimum sample size suggested. With the support of the Rotary International Group in Taiwan, a questionnaire was sent directly to 1307 employees of SMEs in Taipei (8 enterprises), New Taipei (7 enterprises), Taichung (7 enterprises), and Tainan (8 enterprises). The questionnaire was distributed between November 11 and December 29, 2021. Returned questionnaires numbered 1177, with a response rate of 90.1%. In order to increase the response rate, besides support from the Rotary International Group, we also gave the respondents gifts, such as medical masks or convenience store vouchers of 20 NTD.

Because of the purpose of the research, the research participants had to be employees who had WFH during the COVID-19 period. As a result, after collecting the data, we eliminated cases where there was no work-from-home status, cases where data was missing, and other outliers; 785 valid cases were used for the analysis. The participants’ information is shown in Table 1 .

Data analysis strategy

The SPSS v.22 programme was used to conduct the primary analysis and descriptive statistical analysis. To assess univariate normality, cases with z scores exceeding ±3.29 ( p  < 0.001) were identified as outliers, following the approach outlined by Tabachnick et al. ( 2007 ). In order to mitigate issues of multicollinearity, all variance inflation factors (VIFs) needed to be <5 (Hair et al., 2019 ), as recommended by Hair et al. ( 2019 ). Confirmatory factor analysis (CFA) was conducted using the AMOS v.20 software to examine the convergent and discriminant validity. Finally, the proposed hypotheses were tested using Process Macro (Model 5).

Common method variance and descriptive statistics

Common method variance (CMV) refers to the potential bias that arises when data for two or more variables are collected from the same source, leading to a correlation between the variables that may be misleadingly inflated (Podsakoff et al., 2003 ). This study collected data from the same source utilising self-reported data which could lead to common technique bias. Harman’s single-factor matrix was used to determine the CMV of all items. The results show that the factor with the highest variance was 30.42%, which is less than the threshold of 50% (Podsakoff et al., 2003 ). Hence, there was no CMV in the present study. All VIFs were <5 (Hair et al., 1995 ). Table 2 shows the descriptive statistics of the study construct.

Measurement model evaluation

To evaluate the measurement model, a two-step analysis was conducted. Firstly, principal component analysis (PCA) was employed to assess the construct validity of the variables included in the study. A factor loading of 0.5 or higher (Hair et al., 1995 ) was used as the threshold to determine satisfactory construct validity. Additionally, an eigenvalue of at least 1 was considered, and the Varimax rotation method with Kaiser normalisation was applied during the analysis. The results of the PCA are presented in Table 3 with no items omitted.

After performing the PCA, we also checked the Cronbach’s alpha values of the main variables. The results indicate that all Cronbach’s alphas were higher than 0.8, thus exceeding the minimum permitted value of 0.60 (Nunnally, 1978 ). In the second step, confirmatory factor analysis (CFA) was utilised to evaluate the convergent and discriminant validity. Construct reliability was assessed by examining the composite reliability (CR) values with a threshold of 0.70 commonly considered acceptable (Bagozzi and Yi, 1988 ). All factor loadings were higher than 0.6, and all were significant (Hair et al., 2010 ). All average variance extracted (AVE) estimations exceeded 0.50, indicating convergent validity (Hair et al., 2010 ) (see Table 4 ).

Table 5 further demonstrates that the CFA measurement model (fit indices: CMIN/df < 3, RMSEA < 0.05, Comparative Fit Index (CFI) > 0.90, Incremental Fit Index (IFI) > 0.90) implies a good level of fitness. Table 6 shows that all correlations between each pair of constructs were less than the square root of the AVE, indicating that the discriminant validity was sufficient.

Hypothesis testing

Preacher and Hayes’s ( 2004 ) mediation analysis, i.e. PROCESS Macro (model 5), was employed to test the proposed hypotheses. The results show that FWC was negatively related to WFHP ( β  = −0.26, p  < 0.001), supporting H1. This finding is in accordance with the previous findings demonstrating the effect of FWC on WFHP (Anderson et al., 2002 ; Reina et al., 2017 ; Witt and Carlson, 2006 ). FWC negatively influenced WE ( β  = −0.30, p  < 0.001), supporting H2. Although this relationship has been identified in previous studies (Bakker and Demerouti, 2014 ; Suan and Nasurdin, 2014 ), our results confirm the negative relationship between FWC and WE in the context of COVID-19. Furthermore, WE was positively related to WFHP ( β  = 0.11, p  < 0.01), supporting H3. This finding is in line with the previous studies (Bakker and Demerouti, 2008 ; Markos and Sridevi, 2010 ). Additionally, the PROCESS (model 5) showed that WE mediated the relationship between FWC and WFHP ( β  = −0.03 , LLCI = −0.0634 , ULCI = −0.0063), supporting H4. This study has explored the mediator of WE in relation to the association between FWC and WFHP (Aryee et al., 2016 ; Şahin and Yozgat, 2021 ), and this mediating role was also evident in the COVID-19 context. On the other hand, FWC was negatively associated with SE ( β  = −0.25, p  < 0.001), confirming H5 and the previous findings (Netemeyer et al., 1996 ; Peng et al., 2010 ). SE positively affects WFHP ( β  = 0.37, p  < 0.001), supporting H6. This result echoes the previous findings (Tabatabaei et al., 2013 ). In addition, SE mediated the association between FWC and WFHP ( β  = −0.09, LLCI = −0.1242 , ULCI = −0.0621), confirming H7. This is one of the notable findings of our study. As a result, these research findings indicate that FWC negatively affects WFHP and that this effect’s mechanism includes both direct and indirect effects through the partial mediation roles of WE and SE. The findings solve the first research question.

The results of the PROCESS also indicate that the interaction between FWC and WFHDs ( β  = −0.07, SE  = 0.02, t  = −2.87, p  < 0.01, LLCI = −0.1150, ULCI = −0.0216) negatively affected WFHP. The slope test indicated that the negative effect of FWC on WFHP was stronger for employees with more work-from-home days than for those with less, supporting H8. The findings show the role of WFHDs in the negative relationship between FWC and WFHP. According to the research findings, the negative relationship between FWC and WFHP will reduce when the employees are assigned fewer WFHDs. The moderating role of WFHDs can be attributed to the employees’ limited resources, such as time and energy, that they need to distribute across several responsibilities (Kahn et al., 1964 ). As a result, an increase in working hours may result in conflicts that reduce productivity (Greenhaus and Beutell, 1985 ). We examined the conditional effect of FWC on WFHP at three values of WFHDs: at the mean value ( β  = −0.28, p  < 0.001), at 1 SD below ( β  = −0.14, p  < 0.01), and at 1 SD above the mean ( β  = −0.35, p  < 0.001). The interaction plot is depicted in Fig. 2 .

WFHDs strengthen the negative relationship between FWC and WFHP. Note: Work-from-home days: WFHDs, family–work conflict: FWC, work-from-home productivity: WFHP.

The effect of the control variables, such as gender, age, work experience, working field, and the number of children, on WFHP, was investigated to determine whether there were any significant differences between the levels of the control variables. The ANOVA results indicated that there were no significant differences between the levels of work experience, working field, and number of children in relation to WFHP. In contrast, there were significant differences between males ( M  = 3.60, SE = 0.03) and females ( M  = 3.37, SE = 0.04) in relation to WFHP ( F (1, 783) = 20.478, p  < 0.001, η 2  = 0.03). This difference can be attributed to the strong influence of Confucianism in Taiwan which results in many believing that housework is the duty of women (Takeuchi and Tsutsui, 2016 ). Therefore, the WFHP among women was lower than that among men. Table 7 presents the ANOVA table, and Fig. 3 presents the study’s model for the results.

Work engagement and self-efficacy mediate the relationship between family–work conflict and work-from-home productivity. Work-from-home days (WFHDs) strengthen the negative relationship between family–work conflict and work-from-home productivity. Note: *** p  < 0.001, ** p  < 0.01, coefficients for indirect effects are in parentheses.

This study has proposed a new model to investigate the association between FWC and WFHP in Taiwan during the COVID-19 period. All proposed hypotheses in the research were found to be supported. The findings indicate that FWC negatively affects WE, SE, and WFHP because, according to role conflict theory and resource drain theory, people have a limited number of resources (in terms of time and energy) to allocate to various roles. Consequently, conflicting roles can cause stress and reduce employee engagement, efficiency, and productivity (Foy et al., 2019 ; Garg, 2015 ; Wang et al., 2022 ). Moreover, resource drain theory indicates that investing resources in one function raises the likelihood of not being able to fulfil the expectations of the other. Therefore, employees with FWC may exhibit reduced productivity. These findings echo the prior studies (Anderson et al., 2002 ; Bakker and Demerouti, 2014 ; Coetzee and De Villiers, 2010 ; Suan and Nasurdin, 2014 ; Mohsin and Zahid, 2012 ; Peng et al., 2010 ; Reina et al., 2017 ).

The results show that when WFH during the COVID-19 pandemic, employees could encounter conflicts with their family responsibilities which influenced their productivity, SE and WE (Graham et al., 2021 ; Karakose et al., 2021 ; Kulik and Ramon, 2022 ; Peng et al., 2010 ). In contrast, when these conflicts were controlled, SE, WE, and productivity were enhanced (Schieman et al., 2003 ). Furthermore, our study found that WE was an antecedent of WFHP, in that WE positively affects WFHP. This can be attributed to employees with a higher level of WE being enthusiastic about their work and happy to work every day (Hanaysha, 2016 ). Engaged employees are thus critical to increased work productivity in their organisations (Albrecht et al., 2015 ; Hanaysha, 2016 ; Takahashi et al., 2022 ). These findings echo the previous findings that work productivity and work performance are influenced by WE (Demerouti and Cropanzano, 2010 ; Geldenhuys et al., 2014 ). Similarly, the positive association between SE and WFHP was confirmed in our study. Various studies on HRM determined that a higher level of SE will increase a positive work attitude, performance, and productivity (Lim and Loo, 2003 ; Tabatabaei et al., 2013 ; Walumbwa et al., 2005 ), and our research confirms the relationship in the WFH context under COVID-19 conditions.

Our findings explored the partial mediation of WE in the relationship between FWC and WFHP. WE has been identified as a mediator between FWC and work performance or productivity (Aryee et al., 2016 ; Şahin and Yozgat, 2021 ). One of the interesting results of our research was the partial mediation of SE in the negative association between FWC and WFHP. As discussed in the literature review, there is currently little research assessing the mediation of SE in the link between FWC and WFHP, particularly in light of the current pandemic situation. Limited studies have discovered that SE plays a mediating function in the relationship between FWC and job satisfaction (Peng et al., 2010 ) or that there is a mediation function due to SE in the association between job performance and other input factors (Beltrán-Martín et al., 2017 ; Walumbwa and Hartnell, 2011 ). This is a striking finding in our research, specifically how SE mediates the negative association between FWC and WFHP, especially in the COVID-19 context.

Although not yet noted in studies on WFH in the pandemic context, our research has established the moderating role of working hours. The present study indicates that during the COVID-19 situation in Taiwan, an increase in FWC caused a decrease in WFHP and that this negative relationship was stronger for employees with more work-from-home days than for those with less. This is in line with the role conflict theory and resource drain theory perspectives (Greenhaus and Beutell, 1985 ), and previous HRM studies (Collewet and Sauermann, 2017 ; Kattenbach et al., 2010 ). Further, WFHP was found to be higher for Taiwanese male employees than for females. This echoes the prior research on HRM (Bezabih et al., 2016 ; Sandström and Hällsten, 2008 ). However, although Taiwanese society is modernising, the responsibility of taking care of the family still belongs to women (Takeuchi and Tsutsui, 2016 ). This is one of the main causes of the differences in the results.

In conclusion, our findings have determined that WE and SE partially mediate the negative association between FWC and WFHP. The findings provide evidence for the importance of psychological factors when it comes to explaining the impact of family–work conflict on WFHP during the pandemic. Specifically, employees with higher levels of WE and SE are less likely to experience negative effects on their productivity as a result of FWC. One of our new findings, which has filled in the research gaps in the existing literature, is the partial mediating role of SE in the association between FWC and WFHP.

Additionally, the findings show that working hours moderate the association between FWC and WFHP, with the negative effects of FWC being stronger for employees who spend more time working from home. These findings are important for organisations and employees as they navigate the challenges of WFH arrangements in light of the pandemic.

Theoretical implications

Firstly, our study is one of the pioneers in terms of proposing a predictive model for WFHP among small and medium-sized enterprise employees in Taiwan during the COVID-19 period. We propose that our research adds to the knowledge base on remote work and remote worker productivity during the pandemic. Furthermore, the research results are notable because they show how family and work problems affect the productivity of workers who have had to switch to full-time WFH.

Secondly, our research answered Hanaysha’s ( 2016 ) call to focus on a larger sample of SME employees, a factor that is often neglected in previous studies on WFH, especially in relation to the COVID-19 pandemic. This research fills in a gap in the literature on the regulatory role of working hours in the context of WFH, especially in terms of the association between FWC and WFHP during the pandemic, by showing that working hours are different when it comes to the relationship between FWC and WFHP. Although prior research has reported inconsistent results concerning whether WFHP differs between men and women, our study demonstrates that WFHP does vary between men and women, adding to the body of evidence for a gender difference in WFHP.

Thirdly, an important extension of our study can be found in the inclusion of SE in the predictive model of WFHP for workers in Taiwan during the pandemic. Our study adds to the body of knowledge about the mediation of SE in the negative association between FWC and WFHP that has largely been overlooked in previous research.

Managerial implications

Our findings provide some practical implications for managers, the government, and management.

Firstly, FWC was found to be one of the determinants of the decrease in WFHP. This implies that the harmonious resolution of family and work conflicts will contribute to improving the employees’ working productivity in the process of WFH. Therefore, it is necessary for Taiwanese SMEs to transfer family-friendly human resource management practices and related policies from Western contexts to Taiwan. Moreover, employers who consider their employees to be a competitive resource may consider implementing family-friendly policies to help their employees balance work and family tasks. Our results show that employers and managers should pay extra attention to how women employees balance their work and family responsibilities.

Secondly, the current study provides evidence that WE improve employee productivity significantly, even in an emergency situation like COVID-19. Therefore, companies should place a high value on employee engagement and monitor their progress on a regular basis to ensure positive working outcomes. To do so, we strongly recommend employers undertake frequent online surveys during WFH to gain a thorough understanding of their employees’ levels of job engagement and FWC. As a result of such actions, employers will be able to establish appropriate methods for addressing emergent difficulties more quickly. Employers should use an online two-way communication strategy with their employees throughout the WFH time to allow employees to communicate their thoughts on their employment, challenges, and any concerns that may impair their productivity. If such attention were paid to employees, they would be more interested in and motivated by their work.

Thirdly, SE was found to be a mediator in the negative association between FWC and WFHP. Hence, employers should recognise their employees’ SE and provide support to improve it during their WFH time. Schunk et al. ( 2012 ) indicated that verbal persuasion and vicarious modelling are two sources of SE that employers can focus on. Offering professional training and WFH skills development programmes can greatly boost employee confidence and SE (verbal persuasion) and by assigning mentors and team leaders who exhibit highly self-efficacious behaviours during the WFH period (vicarious modelling). Companies can also provide employees with continual encouragement and emotional support by setting up communication channels to hear their voices during WFH time. In addition, companies can prioritise SE in their recruitment process by conducting staff selection interviews and requiring candidates to complete SE tests. This will assist businesses in attracting strong-SE employees.

Finally, although WFH is considered to be an effective solution in the context of the pandemic, our study reported a stronger negative relationship between FWC and WFHP in employees with an excessive WFH duration. It may therefore be advisable for governments and employers to consider implementing specific regulations on how long each person should work from home in a week. The duration should not be too long to avoid affecting work efficiency or an increase in FWC.

Limitations and suggestions for further study

There were several limitations in the research. Firstly, we adopted a non-probability convenience sampling technique, which limits the generalisability of our findings. We recommend that future studies employ a random sampling technique. Secondly, the cross-sectional design was a limitation because while it allowed us to trace the links between the investigated constructs, it did not allow us to determine whether there were any causal links between the variables. In addition, future studies should also test the moderating role of some of the demographic variables such as gender and number of children. This study only examined employees in Taiwan, and future research can include samples from more than one country to enable researchers to compare and contrast the results in light of the differences in national contexts and levels of socioeconomic development.

Data availability

The datasets generated or analysed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/SL0ZQD or upon reasonable request from the corresponding author.

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Tsang, SS., Liu, ZL. & Nguyen, T.V.T. Family–work conflict and work-from-home productivity: do work engagement and self-efficacy mediate?. Humanit Soc Sci Commun 10 , 419 (2023). https://doi.org/10.1057/s41599-023-01929-y

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The future of work after COVID-19

The COVID-19 pandemic disrupted labor markets globally during 2020. The short-term consequences were sudden and often severe: Millions of people were furloughed or lost jobs, and others rapidly adjusted to working from home as offices closed. Many other workers were deemed essential and continued to work in hospitals and grocery stores, on garbage trucks and in warehouses, yet under new protocols to reduce the spread of the novel coronavirus.

This report on the future of work after COVID-19 is the first of three MGI reports that examine aspects of the postpandemic economy. The others look at the pandemic’s long-term influence on consumption and the potential for a broad recovery led by enhanced productivity and innovation. Here, we assess the lasting impact of the pandemic on labor demand, the mix of occupations, and the workforce skills required in eight countries with diverse economic and labor market models: China, France, Germany, India, Japan, Spain, the United Kingdom, and the United States. Together, these eight countries account for almost half the global population and 62 percent of GDP.

Jobs with the highest physical proximity are likely to be most disrupted

Before COVID-19, the largest disruptions to work involved new technologies and growing trade links. COVID-19 has, for the first time, elevated the importance of the physical dimension of work. In this research, we develop a novel way to quantify the proximity required in more than 800 occupations by grouping them into ten work arenas according to their proximity to coworkers and customers, the number of interpersonal interactions involved, and their on-site and indoor nature.

This offers a different view of work than traditional sector definitions. For instance, our medical care arena includes only caregiving roles requiring close interaction with patients, such as doctors and nurses. Hospital and medical office administrative staff fall into the computer-based office work arena, where more work can be done remotely. Lab technicians and pharmacists work in the indoor production work arena because those jobs require use of specialized equipment on-site but have little exposure to other people (Exhibit 1).

We find that jobs in work arenas with higher levels of physical proximity are likely to see greater transformation after the pandemic, triggering knock-on effects in other work arenas as business models shift in response.

The short- and potential long-term disruptions to these arenas from COVID-19 vary. During the pandemic, the virus most severely disturbed arenas with the highest overall physical proximity scores: medical care, personal care, on-site customer service, and leisure and travel. In the longer term, work arenas with higher physical proximity scores are also likely to be more unsettled, although proximity is not the only explanation. For example:

• The on-site customer interaction arena includes frontline workers who interact with customers in retail stores, banks, and post offices, among other places. Work in this arena is defined by frequent interaction with strangers and requires on-site presence. Some work in this arena migrated to e-commerce and other digital transactions, a behavioral change that is likely to stick.
• The leisure and travel arena is home to customer-facing workers in hotels, restaurants, airports, and entertainment venues. Workers in this arena interact daily with crowds of new people. COVID-19 forced most leisure venues to close in 2020 and airports and airlines to operate on a severely limited basis. In the longer term, the shift to remote work  and related reduction in business travel, as well as automation of some occupations, such as food service roles, may curtail labor demand in this arena.
• The computer-based office work arena includes offices of all sizes and administrative workspaces in hospitals, courts, and factories. Work in this arena requires only moderate physical proximity to others and a moderate number of human interactions. This is the largest arena in advanced economies, accounting for roughly one-third of employment. Nearly all potential remote work is within this arena.
• The outdoor production and maintenance arena includes construction sites, farms, residential and commercial grounds, and other outdoor spaces. COVID-19 had little impact here as work in this arena requires low proximity and few interactions with others and takes place fully outdoors. This is the largest arena in China and India, accounting for 35 to 55 percent of their workforces.

COVID-19 has accelerated three broad trends that may reshape work after the pandemic recedes

The pandemic pushed companies and consumers to rapidly adopt new behaviors that are likely to stick, changing the trajectory of three groups of trends. We consequently see sharp discontinuity between their impact on labor markets before and after the pandemic.

Remote work and virtual meetings are likely to continue, albeit less intensely than at the pandemic’s peak

Perhaps the most obvious impact of COVID-19 on the labor force is the dramatic increase in employees working remotely. To determine how extensively remote work might persist after the pandemic, we analyzed its potential  across more than 2,000 tasks used in some 800 occupations in the eight focus countries. Considering only remote work that can be done without a loss of productivity, we find that about 20 to 25 percent of the workforces in advanced economies could work from home between three and five days a week. This represents four to five times more remote work than before the pandemic and could prompt a large change in the geography of work, as individuals and companies shift out of large cities into suburbs and small cities. We found that some work that technically can be done remotely is best done in person. Negotiations, critical business decisions, brainstorming sessions, providing sensitive feedback, and onboarding new employees are examples of activities that may lose some effectiveness when done remotely.

Some companies are already planning to shift to flexible workspaces after positive experiences with remote work during the pandemic, a move that will reduce the overall space they need and bring fewer workers into offices each day. A survey of 278 executives by McKinsey in August 2020 found that on average, they planned to reduce office space by 30 percent. Demand for restaurants and retail in downtown areas and for public transportation may decline as a result.

Remote work may also put a dent in business travel as its extensive use of videoconferencing during the pandemic has ushered in a new acceptance of virtual meetings and other aspects of work. While leisure travel and tourism are likely to rebound after the crisis, McKinsey’s travel practice estimates that about 20 percent of business travel, the most lucrative segment for airlines, may not return. This would have significant knock-on effects on employment in commercial aerospace, airports, hospitality, and food service. E-commerce and other virtual transactions are booming.

Many consumers discovered the convenience of e-commerce and other online activities during the pandemic. In 2020, the share of e-commerce grew at two to five times the rate before COVID-19 (Exhibit 2). Roughly three-quarters of people using digital channels for the first time during the pandemic say they will continue using them when things return to “normal,” according to McKinsey Consumer Pulse  surveys conducted around the world.

Other kinds of virtual transactions such as telemedicine, online banking, and streaming entertainment have also taken off. Online doctor consultations through Practo, a telehealth company in India, grew more than tenfold between April and November 2020 . These virtual practices may decline somewhat as economies reopen but are likely to continue well above levels seen before the pandemic.

This shift to digital transactions has propelled growth in delivery, transportation, and warehouse jobs. In China, e-commerce, delivery, and social media jobs grew by more than 5.1 million during the first half of 2020.

COVID-19 may propel faster adoption of automation and AI, especially in work arenas with high physical proximity

Two ways businesses historically have controlled cost and mitigated uncertainty during recessions are by adopting automation and redesigning work processes, which reduce the share of jobs involving mainly routine tasks. In our global survey of 800 senior executives  in July 2020, two-thirds said they were stepping up investment in automation and AI either somewhat or significantly. Production figures for robotics in China exceeded prepandemic levels by June 2020.

Many companies deployed automation and AI in warehouses, grocery stores, call centers, and manufacturing plants to reduce workplace density and cope with surges in demand. The common feature of these automation use cases is their correlation with high scores on physical proximity, and our research finds the work arenas with high levels of human interaction are likely to see the greatest acceleration in adoption of automation and AI.

The mix of occupations may shift, with little job growth in low-wage occupations

The trends accelerated by COVID-19 may spur greater changes in the mix of jobs within economies than we estimated before the pandemic.

We find that a markedly different mix of occupations may emerge after the pandemic across the eight economies. Compared to our pre-COVID-19 estimates, we expect the largest negative impact of the pandemic to fall on workers in food service and customer sales and service roles, as well as less-skilled office support roles. Jobs in warehousing and transportation may increase as a result of the growth in e-commerce and the delivery economy, but those increases are unlikely to offset the disruption of many low-wage jobs. In the United States, for instance, customer service and food service jobs could fall by 4.3 million, while transportation jobs could grow by nearly 800,000. Demand for workers in the healthcare and STEM occupations may grow more than before the pandemic, reflecting increased attention to health as populations age and incomes rise as well as the growing need for people who can create, deploy, and maintain new technologies (Exhibit 3).

Before the pandemic, net job losses were concentrated in middle-wage occupations in manufacturing and some office work, reflecting automation, and low- and high-wage jobs continued to grow. Nearly all low-wage workers who lost jobs could move into other low-wage occupations—for instance, a data entry worker could move into retail or home healthcare. Because of the pandemic’s impact on low-wage jobs, we now estimate that almost all growth in labor demand will occur in high-wage jobs. Going forward, more than half of displaced low-wage workers may need to shift to occupations in higher wage brackets and requiring different skills to remain employed.

As many as 25 percent more workers may need to switch occupations than before the pandemic

Given the expected concentration of job growth in high-wage occupations and declines in low-wage occupations, the scale and nature of workforce transitions required in the years ahead will be challenging, according to our research. Across the eight focus countries, more than 100 million workers, or 1 in 16, will need to find a different occupation by 2030 in our post-COVID-19 scenario, as shown in Exhibit 4. This is 12 percent more than we estimated before the pandemic, and up to 25 percent more in advanced economies (Exhibit 4).

Before the pandemic, we estimated that just 6 percent of workers would need to find jobs in higher wage occupations. In our post-COVID-19 research, we find not only that a larger share of workers will likely need to transition out of the bottom two wage brackets but also that roughly half of them overall will need new, more advanced skills to move to occupations one or even two wage brackets higher.

The skill mix required among workers who need to shift occupations has changed. The share of time German workers spend using basic cognitive skills, for example, may shrink by 3.4 percentage points, while time spend using social and emotional skills will increase by 3.2 percentage points. In India, the share of total work hours expended using physical and manual skills will decline by 2.2 percentage points, while time devoted to technological skills will rise 3.3 percentage points. Workers in occupations in the lowest wage bracket use basic cognitive skills and physical and manual skills 68 percent of the time, while in the middle wage bracket, use of these skills occupies 48 percent of time spent. In the highest two brackets, those skills account for less than 20 percent of time spent. The most disadvantaged workers may have the biggest job transitions ahead, in part because of their disproportionate employment in the arenas most affected by COVID-19. In Europe and the United States, workers with less than a college degree, members of ethnic minority groups, and women are more likely to need to change occupations after COVID-19 than before. In the United States, people without a college degree are 1.3 times more likely to need to make transitions compared to those with a college degree, and Black and Hispanic workers are 1.1 times more likely to have to transition between occupations than white workers. In France, Germany, and Spain, the increase in job transitions required due to trends influenced by COVID-19 is 3.9 times higher for women than for men. Similarly, the need for occupational changes will hit younger workers more than older workers, and individuals not born in the European Union more than native-born workers.

Companies and policymakers can help facilitate workforce transitions

The scale of workforce transitions set off by COVID-19’s influence on labor trends increases the urgency for businesses and policymakers to take steps to support additional training and education programs for workers. Companies and governments exhibited extraordinary flexibility and adaptability in responding to the pandemic with purpose and innovation that they might also harness to retool the workforce in ways that point to a brighter future of work.

Businesses can start with a granular analysis of what work can be done remotely by focusing on the tasks involved rather than whole jobs. They can also play a larger role in retraining workers, as Walmart, Amazon, and IBM have done. Others have facilitated occupational shifts by focusing on the skills they need, rather than on academic degrees. Remote work also offers companies the opportunity to enrich their diversity by tapping workers who, for family and other reasons, were unable to relocate to the superstar cities where talent, capital, and opportunities concentrated before the pandemic.

Policymakers could support businesses by expanding and enhancing the digital infrastructure. Even in advanced economies, almost 20 percent of workers in rural households lack access to the internet. Governments could also consider extending benefits and protections to independent workers and to workers working to build their skills and knowledge mid-career.

Both businesses and policymakers could collaborate to support workers migrating between occupations. Under the Pact for Skills established in the European Union during the pandemic, companies and public authorities have dedicated €7 billion to enhancing the skills of some 700,000 automotive workers, while in the United States, Merck and other large companies have put up more than $100 million to burnish the skills of Black workers without a college education and create jobs that they can fill.

The reward of such efforts would be a more resilient, more talented, and better-paid workforce—and a more robust and equitable society.

Go behind the scenes and get more insights with “ Where the jobs are: An inside look at our new Future of Work research ” from our New at McKinsey blog.

Susan Lund and Anu Madgavkar are partners of the McKinsey Global Institute, where James Manyika and Sven Smit are co-chairs and directors. Kweilin Ellingrud is a senior partner in McKinsey’s Minneapolis office. Mary Meaney is a senior partner in the Paris office. Olivia Robinson is a consultant in the London office.

This report was edited by Stephanie Strom, a senior editor with the McKinsey Global Institute, and Peter Gumbel, MGI editorial director.

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As more workplaces reopen, most teleworkers say they are working from home by choice rather than necessity

Table of contents.

• Acknowledgments
• Methodology

Pew Research Center conducted this study to better understand the work experiences of employed adults nearly two years into the coronavirus outbreak. This analysis is based on 5,889 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. The data was collected as a part of a larger survey conducted Jan. 24-30, 2022. Everyone who took part is a member of Pew Research Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way 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 .

See here to read more about the  questions used for this report and the report’s  methodology .

References to workers or employed adults include those who are employed 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.

References to White and Black adults include only those who are not Hispanic and identify as only one race. Hispanics are of any race.

References to college graduates or people with a college degree comprise those with a bachelor’s degree or more. “Some college” includes those with an associate degree and those who attended college but did not obtain a degree.

All references to party affiliation include those who lean toward that party. Republicans include those who identify as Republicans and those who say they lean toward the Republican Party. Democrats include those who identify as Democrats and those who say they lean toward the Democratic Party.

“Middle income” is defined here as two-thirds to double the median annual family income for panelists on the American Trends Panel. “Lower income” falls below that range; “upper income” falls above it. See the  methodology  for more details.

Nearly two years into the  COVID-19 pandemic , roughly six-in-ten U.S. workers who say their jobs can mainly be done from home (59%) are working from home all or most of the time. The vast majority of these workers (83%) say they were working from home even before the  omicron variant  started to spread in the United States, according to a new Pew Research Center survey. This marks a decline from  October 2020 , when 71% of those with jobs that could be done from home were working from home all or most of the time, but it’s still much higher than the 23% who say they teleworked frequently before the coronavirus outbreak. 

The impetus for working from home has shifted considerably since 2020. Today, more workers say they are doing this by choice rather than necessity. Among those who have a workplace outside of their home, 61% now say they are choosing not to go into their workplace, while 38% say they’re working from home because their workplace is closed or unavailable to them. Earlier in the pandemic, just the opposite was true: 64% said they were working from home because their office was closed, and 36% said they were choosing to work from home. 

For those who do have access to their workplaces but are opting to work mainly from home, their reasons for doing so have changed since fall 2020. Fewer cite concerns about being exposed to the coronavirus – 42% now vs. 57% in 2020 say this is a major reason they are currently working from home all or most of the time. And more say a preference for working from home is a major reason they’re doing so (76% now vs. 60% in 2020). There’s also been a significant increase since 2020 (from 9% to 17%) in the share saying the fact that they’ve relocated away from the area where they work is a major reason why they’re currently teleworking.

Working from home is a relatively new experience for a majority of workers with jobs that can be done remotely – 57% say they rarely or never worked from home prior to the coronavirus outbreak. For those who have made the switch to telework, their work lives have changed in some significant ways. On the plus side, most (64%) of those who are now working from home at least some of the time but rarely or never did before the pandemic say it’s easier now for them to balance work with their personal life. And many (44%) say working from home has made it easier for them to get their work done and meet deadlines, while very few (10%) say it’s been harder to do this. At the same time, 60% say they feel less connected to their co-workers now. Most (72%) say working from home hasn’t affected their ability to advance in their job.

Looking to the future, 60% of workers with jobs that can be done from home say when the coronavirus outbreak is over, if they have the choice, they’d like to work from home all or most of the time. This is up from 54% who said the same in 2020. Among those who are currently working from home all or most of the time, 78% say they’d like to continue to do so after the pandemic, up from 64% in 2020.

Most U.S. workers (60%)  don’t  have jobs that can be done from home, and others who do have these types of jobs are going into their workplace at least sometimes. For a large majority of these workers, their jobs continue to involve at least some in-person interaction with others at their workplace. About half of those who ever interact with other people at their workplace say they’re very (19%) or somewhat (32%) concerned about being exposed to the coronavirus. This is virtually unchanged from October 2020. Roughly one-in-four (26%) say they are more concerned about this now than they were before the omicron variant started to spread, and the same share say they are less concerned now. A plurality (47%) say they are about as concerned now as they were before omicron.

The nationally representative survey of 10,237 U.S. adults (including 5,889 employed adults who have only one job or who have multiple jobs but consider one to be their primary) was conducted Jan. 24-30, 2022, using the Center’s  American Trends Panel . 1 Among the other key findings: 

Workers with jobs that can be done from home who are choosing to go into their workplace cite preference and productivity as major reasons why they rarely or never work from home.  Six-in-ten of these workers say a major reason they rarely or never work from home is that they prefer working at their workplace, and a similar share (61%) cite feeling more productive at their workplace as a major reason. Relatively few say major reasons for working in-person are that they don’t have the proper space or resources at home (21%), that there are more opportunities for advancement if they’re at their workplace (14%) or that they feel pressure from their supervisor or co-workers to be there (9%).

About half of workers who are working from home all or most of the time and whose offices are closed say they would be comfortable going into their workplace if it were to reopen in the next month.  One-in-five say they’d be very comfortable returning to their workplace, and 29% say they’d be somewhat comfortable doing this. In October 2020, a smaller share of workers (36%) said they would feel comfortable returning to their workplace in the next month.

Most workers who are not working exclusively from home (77%) say they are at least somewhat satisfied with the measures their employer has put in place to protect them from coronavirus exposure, but only 36% say they are  very  satisfied.  As was the case earlier in the pandemic, White workers are more likely than Black or Hispanic workers to say they are very satisfied with the safety measures that have been put in place. And upper-income workers are more likely to be very satisfied than middle- and lower-income workers. 2

Roughly one-in-five workers who are not working exclusively at home (22%) say their employer has required employees to get a COVID-19 vaccine.  About three-quarters (77%) say their employer has not required vaccination (47% say their employer has encouraged it and 30% say they have not). Regardless of what their employer requires, 30% of these workers think their employer should require vaccines, while most say their employer should not (39% say their employer should encourage but not require vaccines and 30% say their employer shouldn’t do either). These views are sharply divided along partisan lines: 47% of Democrats and those who lean to the Democratic Party who are not working exclusively from home think their employer should require employees to get a vaccine, compared with just 10% of Republicans and Republican leaners. 

Frequency of telework differs by education, income

There are  key demographic differences  between workers whose jobs can and cannot be done from home. Among those who say the responsibilities of their job can mainly be done from home, some groups are teleworking more frequently than others. 

College graduates with jobs that can be done from home (65%) are more likely than those without a four-year college degree (53%) to say they are working from home all or most of the time. And higher shares of upper-income workers (67%) are working from home compared with middle- (56%) and lower-income (53%) workers.

A plurality (44%) of all employed adults who are currently working from home all or most of the time say this is because they are choosing not to go into their workplace. About three-in-ten (28%) say their workplace is currently closed or unavailable to them, and a similar share (27%) say they don’t have a workplace outside of their home. The share saying they don’t have a workplace outside of their home is up significantly from 2020, when 18% said this. Adults without a four-year college degree are much more likely to fall into this category than those with a bachelor’s degree or more education (40% vs. 19%, respectively). 

Workers who are currently teleworking all or most of the time because their workplace is closed or unavailable to them are divided over whether they’d be comfortable returning there in the near future. One-in-five say, if their workplace reopened in the next month, they’d be very comfortable working there; 29% say they would be somewhat comfortable. About half say they’d be either somewhat (26%) or very (25%) uncomfortable returning to their workplace in that timeframe.

In October 2020, workers had more trepidation about returning to their workplaces. At that time, only 36% of workers who were working from home because their office was closed said, if it were to reopen in the next month, they’d be comfortable returning (13% said they’d feel very comfortable working in their workplace, 22% said they’d feel somewhat comfortable). Roughly two-thirds said they’d be somewhat (33%) or very (31%) uncomfortable doing this.

Those who are teleworking by choice are less likely to be doing so because of health concerns, more likely to say they prefer it, compared with 2020

The reasons workers give for working from home when they could otherwise go into their workplace have changed considerably from October 2020. Today, a preference for working from home is driving these decisions rather than concerns about the coronavirus. Fully 76% of workers who indicate that their workplace is available to them say a major reason why they are currently teleworking all or most of the time is that they prefer working from home. An additional 17% say this is a minor reason why they are working from home, and 7% say this is not a reason. The share citing this as a major reason is up significantly from 60% in 2020.

At the same time, the share pointing to concerns about being exposed to the coronavirus as a major reason for working from home has fallen from 57% in 2020 to 42% today. About one-in-four teleworkers (27%) say this is a minor reason they are working from home, and 30% say it’s not a reason. Women (48%) are more likely than men (37%) to say this is a major reason they are working from home. There’s also a partisan gap: Half of Democrats and Democratic leaners cite concerns about exposure to the coronavirus as a major reason why they’re currently working from home all or most of the time, compared with 25% of Republicans and Republican leaners.

A smaller but growing share of workers (17%) say relocation to an area away from their workplace, either permanently or temporarily, is a major reason why they are working from home. An additional 8% say this is a minor reason they are working from home, and 75% say this is not a reason.

Among teleworking parents whose workplaces are open and who have at least one child younger than 18, 32% say child care is a major reason why they are working from home all or most of the time, down from 45% in October 2020. Some (15%) say a major reason why they are currently working from home is that there are restrictions on when they can have access to their workplace, similar to the share who said this in 2020 (14%).

Most workers who could work from home but are opting not to say a major reason is that they feel more productive at their workplace

About one-in-five workers (22%) who say the responsibilities of their job can mostly be done from home also say they rarely or never telework. For most (64%), this is because their employer doesn’t allow them to work from home more often. But for some (36%), there are other reasons why they’re opting to go into their workplace rather than working from home.

Again, personal preference is a driving force behind these choices. Six-in-ten of these workers say a major reason why they rarely or never work from home is that they prefer working at their workplace. An additional 19% say this is a minor reason why they don’t work from home more often, and 21% say this is not a reason. A similar share (61%) say a major reason why they rarely or never work from home is that they feel more productive at their workplace. Some 16% say this is a minor reason and 23% say it’s not a reason. 

Relatively few (21%) say not having the space or resources at home to work effectively is a major reason why they rarely or never work from home; 23% say this is a minor reason and 55% say it’s not a reason. 

When it comes to having more opportunities to advance at work if they are there in person or feeling pressure from supervisors or co-workers to be in the office, large majorities say these are not reasons why they rarely or never work from home. Only 14% point to opportunities for advancement as a major reason and 9% cite pressure from their colleagues. 

A majority of new teleworkers say their current arrangement makes it easier to balance work and personal life

For those new to working from home, the pandemic-related shift to telework has changed some things while leaving others relatively the same. For example, among employed adults whose job can be done from home and who are currently working from home at least some of the time but rarely or never did before the pandemic, 64% say working from home has made it easier to balance work and their personal life. Two-in-ten of these adults say balancing work and their personal life is about the same, and 16% say it is harder. 

Some 44% of those who shifted to telework at least some of the time during the pandemic say their new work arrangement makes it easier for them to get their work done and meet deadlines; a similar share (46%) say it’s about the same, while one-in-ten say it is now harder to get their work done and meet deadlines.  

Some aspects of telework have been less positive, according to those who are now working from home at least some of the time but rarely or never did so before the pandemic. Six-in-ten of these workers say they now feel less connected to their co-workers. Some 36% say it’s about the same, and 4% say they are more connected to their co-workers.

Most workers new to telework (72%) say their ability to advance at work while working from home is about the same as it was before. Fewer than one-in-five say working from home has made it easier or harder to advance.

Assessments of how working from home has changed some elements of work life vary by gender. Women are about twice as likely as men to say working from home has made it easier to advance in their job (19% vs. 9%). And while about half of women who are new to telework (51%) say working from home has made it easier to get their work done and meet deadlines, 37% of men say the same. Men and women are about equally likely to say working from home has made it easier for them to balance work and their personal life.

For those who have at least some in-person interactions at work, concerns about COVID-19 exposure vary across demographic groups

Fully 86% of workers who are not working exclusively from home – either by choice or because they can’t work remotely – say they have at least some in-person interactions with other people at their workplace. Among these workers, 52% say they are at least somewhat concerned about being exposed to the coronavirus from the people they interact with at work, including 20% who are  very  concerned. A similar share (48%) say they are either not too or not at all concerned. This is virtually unchanged from  October 2020 . 

Black and Hispanic workers are more likely than White workers to express at least some concern about being exposed to the coronavirus at work (72% and 65% vs. 43%, respectively). But Black workers are particularly concerned: 42% say they are very concerned about COVID-19 exposure at work, compared with 24% of Hispanic workers and an even smaller share of White workers (14%). 

Concerns about COVID-19 exposure at work also vary by gender, age and income. Women (59%) are more likely than men (45%) to say they are concerned about being exposed to the coronavirus from people they interact with at work. A majority of workers younger than 30 (60%) express at least some concern, compared with 52% of those ages 30 to 49, 47% of those ages 50 to 64 and 44% of those ages 65 or older. And workers with lower incomes (59%) are more likely than those with middle (52%) and upper (40%) incomes to say they are concerned about being exposed to COVID-19 from the people they interact with in person at work. 

Workers who are fully vaccinated against COVID-19 and have received a booster shot are the most likely to express concerns about being exposed to the coronavirus from those they interact with in person at work: 66% of these workers say they are at least somewhat concerned, compared with 52% of those who are fully vaccinated but have not gotten a booster shot and just 25% of those who have not gotten any COVID-19 shots.  

About half say they are as concerned about being exposed to the coronavirus at work as they were before the omicron surge 

About a quarter of workers who are not working exclusively from home and who have at least some in-person interactions at work (26%) say they are more concerned about being exposed to the coronavirus at work than they were before the omicron variant started to spread in the U.S. in December 2021. The same share (26%) say they are now  less  concerned than they were before the new variant started to spread. About half (48%) say they are about as concerned as they were before. 

Black (40%) and Hispanic (32%) workers are more likely than White workers (21%) to say they are more concerned about being exposed to the coronavirus from people they interact with at work than they were before the omicron surge. About three-in-ten employed women (28%) say they are more concerned now than before the new variant started to spread, compared with 23% of employed men.

A third of those who are fully vaccinated against COVID-19 and have received a booster shot say they are more concerned about being exposed to the coronavirus at work than they were before omicron started to spread. A quarter of those who are vaccinated but have not gotten a booster and just 10% of those who haven’t gotten any COVID-19 shots say the same. 

Fewer than half of workers are very satisfied with the steps that have been taken in their workplace to keep them safe from COVID-19

Most workers who are not exclusively working from home (77%) say they are at least somewhat satisfied with the measures their workplace has put in place to protect them from coronavirus exposure, but just 36% say they are  very  satisfied. These assessments vary considerably by race and ethnicity, income and age. 

As was the case earlier in the pandemic, White workers who are spending time in their workplace (42%) are far more likely than Black (27%) and Hispanic (26%) workers to say they are very satisfied with the measures that have been put in place to protect them from being exposed to COVID-19 at work. And while 44% of upper-income workers say they are very satisfied, smaller shares of those with middle (36%) and lower (32%) incomes say the same.

Across age groups, those younger than 30 are the least likely to say they are very satisfied with COVID-19 safety measures at their workplace, while those ages 65 and older are the most likely to say this. A quarter of workers ages 18 to 29 say they are very satisfied, compared with 35% of those ages 30 to 49, 44% of those ages 50 to 64, and 53% of workers 65 and older. 

Vaccination requirements don’t seem to be related to these views. Some 39% of those whose employers have required employees to get a COVID-19 vaccine, and 35% of those in workplaces without a vaccination requirement say they are very satisfied with the measures that have been put in place to protect them from being exposed to the coronavirus.  

Most workers say their employer doesn’t require COVID-19 vaccination

About one-in-five workers who are not working exclusively from home (22%) say their employer has required employees to get a COVID-19 vaccine. About three-quarters (77%) say their employer has not required vaccination (47% say their employer has encouraged it and 30% say they have not). 

Workers with upper incomes (31%) are more likely than those with middle (19%) and lower (23%) incomes to say their employer has required employees to get a COVID-19 vaccine. Among workers with a postgraduate degree, 36% say their employer has a vaccination requirement, compared with 27% of those with a bachelor’s degree, 22% of those with some college and an even smaller share of those with a high school diploma or less education (13%). 

Vaccination requirements are also more common in urban and suburban areas than in rural communities. About a quarter of workers in cities (26%) and suburbs (23%) say their employer requires employees to get the COVID-19 vaccine, compared with 16% in rural areas. 

Democrats and those who lean Democratic (27%) are more likely than Republicans and Republican leaners (17%) to say their employer has required COVID-19 vaccination. These differences remain even after accounting for differences in education and income levels among these groups. 

About nine-in-ten workers who say their employer has required employees to get a COVID-19 vaccine (92%) say they are fully vaccinated, including 58% who say they have received a booster shot. A smaller share of those who don’t have a vaccination requirement at work (65%) say they are fully vaccinated, with 38% saying they have received a COVID-19 vaccine booster. 

Most workers don’t think their employer should require COVID-19 vaccination

The survey also asked employed adults who are not working exclusively from home what they think their employer  should do  when it comes to COVID-19 vaccinations, regardless of what their employer  is  doing. Three-in-ten say their employer should require the vaccine, while most (69%) say their employer should not (including 39% who say their employer should encourage but not require it and 30% who don’t think their employer should do either). 

Somewhat similar shares of White, Black and Hispanic workers think their employers should require employees to get a COVID-19 vaccine, but Black workers are more likely than those who are Hispanic or White to say their employer should encourage employees to get vaccinated (55% vs. 43% and 37%, respectively). 

Views on COVID-19 vaccination requirements vary widely along party lines. Some 47% of Democrats and Democratic leaners who are not exclusively working from home think their employer should require employees to get a vaccine, compared with just 10% of Republican and Republican-leaning workers. In turn, 53% of Republicans say their employer should neither require nor encourage employees to get vaccinated; only 10% of Democrats say the same. 

Among those who say they think their employer should require employees to get the COVID-19 vaccine, 43% say their employer has, in fact, required it; 41% say their employer has encouraged it but not required it, and 15% say their employer has neither required nor encouraged vaccination. By contrast, a majority of those who think their employer should encourage but not require vaccination (64%) and those who say their employer should neither require nor encourage it (61%) say what their employer is doing is in line with what they personally think should be done. 

• For more details, see the  Methodology  section of the report. ↩
• Family incomes are based on 2020 earnings and adjusted for differences in purchasing power by geographic region and for household sizes. Middle income is defined here as two-thirds to double the median annual family income for all panelists on the American Trends Panel . Lower income falls below that range; upper income falls above it. See Methodology section of the report for more details. ↩

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More From Forbes

3 new studies end debate over effectiveness of hybrid and remote work.

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Experts say hybrid and remote working are signs of the future, and new science-backed studies show ... [+] mental health benefits to "the new normal."

The debate over remote and hybrid work continues to grow. Some companies resisted, and iron-fisted leaders pulled the old hat trick (“It’s your job to work hard and deal with stress, so grin and bear it.”), arguing against the concept of remote work. Others cited productivity concerns and tactical problems that limited a supervisor’s ability to observe and coach employees. A handful of business leaders pushed back. Josh Feast, CEO of Cognito Corporation, argued that supervisors could find innovative ways to connect with and manage workers from afar “by ensuring their colleagues feel heard and know they are not alone. Exhibiting heightened sensitivity to emotional intelligence—particularly in a time where physical isolation has become a necessity—is vital.” Alice Hricak, managing principal of corporate interiors at Perkins and Will, said working from home showcases new approaches and debunks old ideas that it leads to low productivity, less visibility and little opportunity for collaboration.

What Does The Scientific Data Show?

To resolve the debate, it’s time to go beyond subjective opinion and look at the objective science. David Powell, president of Prodoscore said their data showed that if an employee was highly productive in-office, they’ll be productive at home; if an employee slacked off at the office, they’ll do the same a home. “After evaluating over 105 million data points from 30,000 U.S.-based Prodoscore users, we discovered a five percent increase in productivity during the pandemic work from home period,” he said. “Although, as we know, any variant of the Covid-19 virus is unpredictable, employee productivity is not.”

Two studies in early 2022 validated the views of remote/hybrid work advocates. Research from Owl Labs found that remote and hybrid employees were 22% happier than workers in an onsite office environment and stayed in their jobs longer. Plus, remote workers had less stress, more focus and were more productive than when they toiled in the office. Working from home led to better work/life balance and was more beneficial for the physical and mental well-being of employees.

A study from Ergotron sampled 1,000 full-time workers. It found that as workers become more acclimated to hybrid and remote office environments since the onset of Covid-19, the hybrid workplace model has empowered employees to reclaim physical health, and they are seeing mental health benefits, too.   A total of 56% of employees cited mental health improvements, better work-life balance and more physical activity. Key highlights from the study include:

• Job Satisfaction. Continuing to embrace flexibility is essential. Most employees (88%) agree that the flexibility to work from home or the office has increased their job satisfaction.
• Physical health. The hybrid workplace has empowered employees to reclaim physical health. Three-quarters of respondents (75%) stated that they move more frequently and have a more active work style when working remotely.
• Work-life balance . Three quarters of respondents say their work-life balance has improved as a result of hybrid or remote working. Even though some employees are dedicating more time to their work, if they’re able to fit it in and around other aspects of their lives, they say they feel the positive effects of a better work-life balance.
• Comfortable work environments. Of the workers surveyed, 62% said improved workspaces with comfortable, ergonomic furniture are important and improve company culture. 
• Wellness programs. More than three-quarters of respondents (76%) revealed that their employers implemented wellness programs to support mental and physical health, with 30% of those being brand new since the onset of the pandemic.

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“Promoting health and wellness among employees can improve well-being and productivity,” said Chad Severson, CEO of Ergotron. “Over the past two years, employees have adapted to the hybrid and remote work landscape—and they now prefer it. As employers look to attract and retain talent, focusing on practices that promote well-being and help employees thrive wherever they work will be critical.”

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The Impact of Enforced Working from Home on Employee Job Satisfaction during COVID-19: An Event System Perspective

Associated data.

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

During the COVID-19 pandemic, working from home (WFH) became the only option for many organizations, generating increasing interest in how such arrangements impact employee job satisfaction. Adopting an event system perspective, this study employed an online survey to capture the WFH experiences of 256 workers from 66 Chinese enterprises during the pandemic. Using fuzzy-set qualitative comparative analysis (fsQCA), the study examined how satisfaction was affected by five job characteristics when working from home: longevity (time), home workspace suitability (space), job autonomy (criticality), digital social support (novelty) and monitoring mechanisms (disruption). The findings reveal that three configurations promote employee job satisfaction and that a suitable home workspace is a core condition. In the absence of a suitable workspace, digital social support and an appropriate monitoring mechanism, long-term WFH was found to undermine job satisfaction. However, job autonomy is not a necessary condition for employee job satisfaction. These findings have clear implications for theory and practice.

1. Introduction

As a consequence of the COVID-19 pandemic, about 72% of employees worldwide were required to switch overnight to working from home (WFH) [ 1 ]. According to a Survey Monkey report, more than 89% of employees surveyed ( n = 9059) were satisfied with their WFH arrangements [ 2 ]. However, a Martec Group 2020 study reported that only 32% of respondents ( n = 1214) were satisfied with their WFH arrangements during the COVID-19 pandemic [ 3 ]. Similarly, a survey conducted by the Institute for Employment Studies found that 50% of respondents ( n = 500) were dissatisfied with their current WFH arrangements; of those, 46% attributed their dissatisfaction to irregular working hours, while 33% cited loneliness and 21% expressed concerns about job security [ 4 ]. It seems important, then, to understand why job satisfaction experiences differ among the employees who engaged in WFH during the COVID-19 pandemic and how WFH might be designed to improve those experiences.

As a work practice, WFH means that an employee performs work-related activities from their home rather than being physically present at an employer location, typically using digital technology [ 5 ]. Previous findings regarding the relationship between WFH and employee job satisfaction are inconclusive [ 6 ]. WFH falls into the category of remote work; existing research has identified factors that increase employee job satisfaction of remote work, including income, working hours, free time, appropriate physical activity [ 7 ], the frequency of remote work [ 8 ], work location [ 9 ], social interaction and technical support [ 10 ], position, company training, relationship with supervisors and environmental conditions at work [ 11 ]. Beyond that, scholars initially investigated the associations between WFH and employee job satisfaction in terms of individual needs. According to signalling theory, observable organizational actions can be interpreted as a signal of unobservable characteristics, such as the organization’s concern for employee welfare. After receiving the signal, employees tend to adopt a more positive attitude [ 12 ]. Research based on this theory proposes that WFH is traditionally presented as an employee benefit that contributes to a positive work attitude [ 13 ] and is usually seen as a work–family enrichment measure [ 14 ]. Role balance theory suggests that individuals who can successfully balance multiple roles (employee, spouse, etc.) will experience more positive effects than those who achieve less balance [ 15 ]. According to these studies, WFH enhances job satisfaction by contributing to work–family life balance [ 16 ]. On the other hand, self-determination theory emphasizes how WFH fulfils personal psychological needs (e.g., autonomy, competence, relatedness) as a driver of job satisfaction [ 17 ]. Scholars have subsequently noted that individual and job characteristics can moderate the relationship between WFH and job satisfaction. Both social exchange theory and organizational justice theory posit that people seek a balance between an investment in a relationship and what they receive in return [ 18 , 19 ]. Studies based on social exchange theory contend that social support in the workplace can strengthen home-based workers’ job satisfaction and sense of embeddedness [ 20 ]. According to justice theory, employees who are unable to participate in WFH because of technical or management issues tend to compare their situation with that of home office workers, perceive inequity and unfairness, and attempt to remove such feelings by reducing their job satisfaction and intention to stay [ 21 ]. The essence of job characteristic theory is that certain job characteristics may increase the probability that individuals will find their work meaningful, take responsibility for work outcomes, and have trustworthy knowledge of the results of their work, which can motivate task completion and enhance job satisfaction [ 22 ]. On that basis, job demands–resources theory divides job characteristics into demands and resources [ 23 ]. Studies based on these theories identify a suitable home workspace [ 24 ] and job autonomy [ 25 ] as likely sources of high-level job satisfaction. Role theory notes that individuals play multiple different roles in daily life that make different demands on time and energy commitments. These roles are often incompatible, which may lead to “inter-role conflict” [ 26 ], and WFH mitigates work–family conflict by reducing “inter-role conflict”, therefore increasing job satisfaction [ 27 ].

However, WFH also poses certain risks [ 28 ]. Boundary theory emphasizes the boundary between an individual’s work and non-work domains and the transition between various roles. The degree of segmentation or integration between employees’ work and non-work domains determines the success or failure of their role transitions [ 29 ]. Research informed by this perspective suggests that WFH can blur work–family boundaries and exacerbate work–family conflict if employees are unable to avoid working overtime or work-related disruption during breaks, which has been found to affect job satisfaction insignificantly [ 30 ] or negatively [ 31 ]. According to organizational support theory, employees tend to evaluate their performance more positively if the organization meets their social-emotional needs, rewards their work achievements and helps them in times of need [ 32 ]. Nonetheless, social isolation when WFH can undermine relationships with colleagues, resulting in job dissatisfaction [ 33 ]. The relationship between WFH and job satisfaction is also thought to be moderated by extent [ 34 ] or longevity [ 35 ] and by individual personalities and preferences [ 36 , 37 ].

These equivocal findings can be attributed to three deficiencies in existing studies on the relationship between WFH and employee job satisfaction. First, studies conducted prior to the pandemic focused mainly on voluntary home-based workers and sought to determine the type of employees who were suitable for working from a home office [ 38 ]. However, the enforcement of WFH during the COVID-19 pandemic deprived employees of choice [ 39 ]. For enterprises, existing management initiatives might not be sufficient to help employees cope with the extra pressure [ 40 ] due to inadequate operating conditions and organizational support for WFH implementation [ 41 ]. The existing literature cannot fully explain the impacts of enforced WFH during the COVID-19 pandemic [ 39 ], and this matters because organizations need to redesign and optimize WFH arrangements, taking account of how the job characteristics associated with enforced WFH affect job satisfaction.

A second deficiency is that previous studies typically explored the net effect of WFH on job satisfaction by treating job characteristics as moderating or mediating variables [ 5 ]. However, the uniqueness and novelty of COVID-19 altered some characteristics of WFH [ 42 ], given that the effect on job satisfaction is the result of multiple interacting job characteristics rather than a single factor [ 30 ]. As job characteristics also vary with context [ 9 ], it seems useful to explore which characteristics of WFH are most important and how they can be configured to maximize utility by treating WFH as an event [ 6 ].

Finally, a majority of existing studies emphasize the issues of job autonomy and social isolation associated with WFH [ 28 ] but fail to examine monitoring mechanisms. Compared with employees who work in the office, home-based workers are less likely to be subject to organizational supervision and control [ 43 ]. While the use of various technologies to monitor home-based workers can reduce employee procrastination [ 38 ], surveillance tools can also undermine productivity if workers feel untrusted or have concerns about privacy and security, which in turn can have a devastating impact on job satisfaction [ 44 ]. Indeed, the extensive use of technology may lead to an “autonomy paradox”: the greater the autonomy offered by WFH and technology, the more employees are likely to feel controlled [ 45 ]. It follows that the effective monitoring of home-based workers must balance autonomy and control, and this is crucial for understanding any improvements in WFH job satisfaction during the COVID-19 pandemic.

On that basis, we formulated the following research question: How should enterprises configure the different job characteristics of WFH to improve employee job satisfaction during the COVID-19 pandemic? Based on event system theory (EST) [ 46 ], the present study analyses optimal configurations in terms of how the longevity of WFH (LWFH), home workspace suitability (HWSS), job autonomy (JA), digital social support (DSS) and monitoring mechanisms (MM) affect employee job satisfaction (EJS). To that end, we employed fuzzy-set qualitative comparative analysis (fsQCA) to analyse the experiences of home-based workers from 66 Chinese enterprises during the COVID-19 pandemic.

The study makes four main contributions. First, by analysing how key characteristics of enforced WFH can be configured to enhance EJS, the study extends the WFH literature beyond voluntary contexts and informs the design of future office models. Second, the study enriches the literature on WFH supervision strategies by introducing the concept of MM for EJS. Third, the study augments existing research on job design and EJS by employing fsQCA to explore configurations of WFH job characteristics as antecedents of job satisfaction. Finally, the study contributes to EST by situating it proactively in the context of enforced WFH.

2. Theoretical Background and Literature Review

2.1. event system theory.

According to EST, event strength, time and space determine an event’s degree of influence on an entity. Event strength comprises criticality (the event’s importance), novelty (the extent to which an event differs from current and past events) and disruption (the extent to which the event obstructs or subverts routine activities). Temporal characteristics, which distinguish events from constant features of the work environment, include event duration, timing and changes in strength. Finally, event space refers to the specific location where an event originates and how its effects spread; spatial characteristics include event origin, spatial dispersion and spatial proximity [ 46 ].

Depending on their source, events are categorized as reactive (if entities are forced to accept their occurrence) or proactive (if entities actively create them) [ 46 ]. As strong environmental events are more likely to alter behaviours [ 47 ], EST is typically used to determine the impact of reactive events on organizational outcomes, such as team knowledge absorption [ 48 ], team leadership [ 49 ] and organizational evolution [ 50 ]. Research on the individual-level mostly focuses on the impact of the strength of the COVID-19 event on individual innovation behaviour [ 51 ], job search behaviour [ 52 ], public emotional response [ 47 ], employees’ sense of job insecurity [ 53 ] and vaccination intention [ 54 ], but there is still a lack of studies on EJS during the COVID-19 pandemic based on EST. Among the few studies applying EST to proactive events, Lu et al. [ 55 ] explored the impact of tourism development on urban economies, and Hu et al. [ 56 ] investigated which attributes of enterprise safety training programmes promote employee safety behaviours.

The premise of the present study is that, from an EST perspective, WFH can be regarded as a proactive event for several reasons. First, we can fully comprehend the impact of enforced WFH on employee attitudes only by taking account of the interactions between WFH job characteristics [ 30 ]. Second, WFH fully conforms to the definition of an event as described by EST: WFH (1) is external to employees, (2) has a clear beginning and end point (This study relates to China, where prevention and control has entered the normalization stage. Employees can continue to work in the office after lockdown restrictions are completely lifted, working from home again following a sporadic outbreak. In that sense, there is a clear beginning and end time for WFH during the pandemic, and WFH has become a discrete event), (3) involves the intersection of organization and employees and (4) commands employees’ attention. On that basis, it is justifiable to conceptualize enforced WFH as an event. More specifically, EST offers a systematic perspective for exploring the combined effects of the job characteristics of enforced WFH on EJS during the COVID-19 pandemic.

2.2. Literature Review

Job characteristics are the essential attributes inherent in a task or job performed by an employee [ 22 ]. The characteristics of WFH refer to the nature of the job during the period of working from home [ 38 ]. According to job demands–resources (JD-R) theory, job characteristics can be categorized as job demands or job resources [ 23 ]. Job demands are elements that can cause stress, including workload [ 57 ], working hours [ 58 ] and working conditions, such as noise and temperature [ 59 ]. Job resources are physical, psychological, social or organizational aspects of work that can support employees and help them to maintain well-being. These include the suitability of the home workspace [ 60 , 61 ], the availability of digital resources and the Internet [ 61 ], job autonomy, social support [ 62 ], supervisory coaching and performance feedback [ 63 ] and promotion opportunities [ 64 ].

Based on EST and JD-R theory, the present study proposes the concept of MM to characterize the disruptive component of pandemic-enforced WFH as an event alongside JA (criticality) and DSS (novelty) as other aspects of event strength, and considers LWFH and HWSS as temporal and spatial features of the event, respectively. The focus on these five job characteristics relates to the two knowledge gaps addressed here.

(1) According to JD-R theory, job demands interact with job resources to predict EJS. Job demands can reduce satisfaction if excessive work demands and pressure undermine workers’ health. However, if job resources are sufficient to balance those demands, employees are likely to be satisfied with their job [ 64 ]. In this regard, LWFH during the pandemic reflects the evolutionary nature of WFH when it is enforced by the crisis [ 59 ] and employee perceptions of work duration as an aspect of workload. To that extent, LWFH can be understood as a key job demand during this period. Along with HWSS, JA, DSS and MM as physical, psychological, social and organizational job resources, these five elements are crucial for any enterprise effort to improve EJS. (2) Job characteristics can interact with each other [ 64 ], inviting a study of their configurations. For example, long-term WFH is likely to aggravate occupational isolation and limit employee access to social support [ 65 ], as well as create work pressure and an “autonomy paradox” [ 66 ]. Social support in the workplace can increase employee autonomy and mitigate the negative effects of stress on satisfaction [ 67 ].

In light of how the COVID-19 pandemic has fundamentally changed our ways of working, the present study focuses on the effects of enforced WFH on job satisfaction in terms of individual evaluations and feelings [ 14 ] rather than specific job aspects [ 34 ]. The sections that follow discuss the mechanisms that determine the impact of the five conditions on EJS.

2.2.1. Longevity of Working from Home and Job Satisfaction

Crisis-induced WFH events are evolutionary in nature [ 59 ], and most of the relevant studies argue that the relationship between LWFH and EJS is non-linear [ 34 ]. Short-term WFH reflected organizational concerns about employee health during the COVID-19 pandemic [ 68 ], causing employees to feel more positive about their work [ 69 ]. However, the isolation associated with long-term WFH limits social contact within and outside work [ 37 ], which increases the risk of frustration among home-based workers and so undermines job satisfaction [ 34 ]. Surprisingly, Golden et al. [ 65 ] found that individuals with high-quality monitoring mechanisms and undergoing long-term WFH reported the highest job satisfaction.

2.2.2. Home Workspace Suitability and Job Satisfaction

The suitability of home working conditions encompasses “physical” elements (e.g., dedicated workplace, essential IT tools) and “mental” conditions (e.g., freedom from distractions and noise) [ 59 ] which impact significantly on employee satisfaction [ 57 ]. According to self-determination theory, IT tools enable home-based workers to share information across time and space boundaries [ 70 ] and help to fulfil the psychological need for interpersonal interaction, thus helping to improve job satisfaction [ 71 ]. Work adjustment theory asserts that a separate home workspace ensures clear structural boundaries between work and home and maintains job satisfaction by controlling distractions, such as children and noise [ 59 ]. On the other hand, Bellmann et al. [ 30 ] found no association between blurred home–work boundaries and job satisfaction.

2.2.3. Job Autonomy and Job Satisfaction

Job autonomy is the permitted extent of independence and discretion when performing professional tasks [ 22 ], including time and scheduling, and this is a key determinant of job satisfaction [ 72 ]. A majority of existing studies explain the relationship between employee JA and EJS in terms of JD-R theory and the resource-based view. Autonomy is an important job resource because it enables employees (1) to coordinate their work time to suit their preferences and schedule their work to ensure personal productivity and (2) to self-organize their work tasks to cope more effectively with stressful job demands [ 25 ], ensuring greater job satisfaction [ 23 ]. However, an opposing view suggests that flexible working hours can create insecurities related to performance evaluation criteria and supervisor expectations, adding to working time and stress and reducing job satisfaction [ 73 ].

2.2.4. Digital Social Support and Job Satisfaction

Social support refers to assistance or emotional support provided by communication with others, especially in stressful situations [ 74 ]. Because of the quarantine measures introduced by the Chinese government during the pandemic, almost everyone must rely on online platforms for digital social support both in and outside of work [ 75 , 76 ]. According to social support theory, DSS during work provides the necessary emotional and instrumental resources to mitigate work–family conflicts, therefore promoting job satisfaction [ 77 ]. Similarly, DSS outside of work improves job satisfaction by compensating employees for the lack of interpersonal interaction during working hours and by providing a release from work pressure [ 76 ]. However, others have argued that the low-quality communication afforded by digital technologies may undermine job satisfaction by amplifying information uncertainty [ 20 ].

2.2.5. Monitoring Mechanism and Job Satisfaction

Monitoring and evaluating employees is an essential component of WFH arrangements [ 78 ]. Control theory suggests that managers may place more emphasis on output control to address the challenges of monitoring homeworkers’ behaviour [ 79 ]. Output control emphasizes target-related performance [ 80 , 81 ], and behavioural control emphasizes task scheduling, with frequent monitoring of employee compliance with regulations. Organizations commonly use these two control methods to guide and communicate with employees. By helping to relieve their stress and improve their adaptability, these methods can contribute to increased job satisfaction [ 81 ]. In contrast, social exchange theory advocates for clan control, which seeks to promote appropriate behaviours by committing employees and managers to shared beliefs and values [ 82 ]. As this sharing is based on regular interactions between employees and managers, clan control helps to build healthy relationships between superiors and subordinates, thereby enhancing employee satisfaction [ 83 ]. On the other hand, Piccoli et al. [ 84 ] reported that strict control of home-based workers may reduce the effectiveness of coordination and communication and does not ensure job satisfaction.

In light of the intricate interactions among these five factors and the lack of research analysing the configurations of EJS, the present study can only review direct links between these factors and EJS, which are undoubtedly no more than a subset of all possible configurations. In addition, as existing studies of this relationship are inconsistent and contradictory, a new method of configuration analysis is needed to resolve these conflicts and explore unknown complementary sets. Figure 1 depicts the proposed research model.

Research model.

3. Methodology

3.1. sample and procedure.

To collect the data, we conducted an online questionnaire survey during the period June to September 2021. At the outset, each questionnaire was divided into two parts: Part A measured MM, and Part B measured LWFH, HWSS, JA, DSS and EJS, as well as control variables ( Appendix A ).

The sample was drawn from two sources. The main source comprised Executive Master of Business Administration (EMBA) students (who came from different provinces of China) at universities in Shanghai. With the help of Master of Business Administration education centres, 200 part-time EMBA students (who worked on weekdays as human resource (HR) managers) were randomly selected and informed by e-mail about the survey’s purpose. This group was chosen as the main target sample because they were likely to have a comprehensive knowledge of WFH and issues related to job satisfaction. For the other part of the sample, we chose 50 HR managers at random from the LinkedIn network of professional profiles, using HR manager as the filter criterion. We sent them a brief description of the study and an invitation to participate in the survey. It is worth noting that respondents were not known to the authors and were not drawn from the authors’ profiles. To improve the survey’s accuracy, we added the following filtering questions: (1) Did your enterprise practise enforced working from home during the COVID-19 pandemic? (2) Are you a HR manager? We excluded respondents whose company had not implemented enforced WFH or who were not HR managers. After confirming that the respondent qualified, we sent them the questionnaire, assuring them that their responses would remain anonymous and confidential. Of the HR managers who agreed to participate in the survey ( n = 66), 52 were EMBA students, and 14 were LinkedIn users, mainly from manufacturing (31.5%), aerospace (21.2%), information technology (15.2%), internet services (13.9%), education (9.1%) and banking (7.6%). All respondents were asked to complete Part A of the questionnaire and e-mail Part A of the questionnaire directly to the authors after completion; they were then asked to send Part B of the questionnaire (with the company’s identifying code and the authors’ email addresses) to 4–6 employees who were working from home during the pandemic. After completing Part B of the questionnaire, employees e-mailed Part B directly to the authors. This process ensured that there was no chance that the HR managers might see their employees’ responses, and for that reason there is no risk of bias. Finally, Parts A and B were combined into a single questionnaire identified by a code for each company. Each HR manager was offered a gift worth USD 30 for their efforts.

In total, 281 questionnaires were returned (219 from EMBA students’ companies and 62 from LinkedIn respondents’ companies); of these, 256 valid responses (91.1%) were included in the data analysis. Using Harman’s single-factor test, we found that seven factors had eigenvalues that were greater than 1.0, and the first factor accounted for only 26.16% of the variance, meeting the criterion of less than 50% for no significant common method bias.

Of those sampled, 52.3% were female, and more than 90% were aged between 18 and 44 years and held a bachelor’s degree or higher. Table 1 details the respondents’ characteristics.

The descriptive statistics of respondents’ characteristics.

3.2. Measurement

To ensure the reliability and validity of the survey instrument, items representing the relevant constructs were developed from established scales [ 56 , 59 , 60 , 78 , 85 , 86 , 87 , 88 , 89 , 90 ] and were adapted for the purposes of this study. All items were measured on a five-point Likert scale (from 1 = strongly disagree to 5 = strongly agree ).

3.2.1. Dependent Variable

As our focus is on employees’ overall emotional response to working from home rather than specific work issues (such as salary, promotion or colleagues), we measured EJS by using four items representing employee overall job satisfaction from Brayfield et al. [ 85 ]. This short form is reliable and has been used in previous research [ 91 ]. Sample items include the following: “I feel fairly satisfied with my present job working from home” and “I consider my job rather unpleasant”. To ensure validity, respondents were also asked “How many times have you recommended working from home for people who are used to having you around since this practice was introduced?” and “How many quarrels have you had with your colleagues since working from home was enforced?” Correlation analysis indicated that the two items were significantly correlated with respondents’ subjective evaluations (r = 0.43, p < 0.01 and r = −0.46, p < 0.01, respectively).

3.2.2. Independent Variables

As WFH may in reality last for anywhere from a few days to permanently, items 1 and 2 that measure LWFH were taken from Hu et al. [ 56 ], while the remaining items were adapted from Briscese et al. [ 86 ]. We deleted two items from the LWFH scale because of low standardized factor loadings (less than 0.5). Sample items include the following: “The practice of working from home will be extended by a few months”; “The practice of working from home will be extended indefinitely for as long as is deemed necessary”.

We used one item from Nakrošienė et al. [ 60 ] to measure perceived overall HWSS and four items from Carillo et al. [ 59 ] to measure “physical” and “mental” elements of HWSS. Sample items include the following: “My home workspace is suitable for my work”; “I am bothered by noise while working at home”.

JA was measured using nine items developed by Breaugh [ 87 ]. This scale is often used in studies of job autonomy (e.g., [ 92 ]). Sample items include the following: “I am allowed to decide how to get my job done”; “I have control over how I schedule my work”; “I am allowed to modify my job objectives”.

Based on the definition of DSS during WFH, the six-item scale measuring DSS was adapted from Liang et al. [ 90 ]. This scale, which is often used in research on digital social support (e.g., [ 93 ]), incorporates two dimensions: informational support and emotional support. Sample items include the following: “When I encountered a problem, people on the digital platform would provide information to help me overcome the problem”; “When I encountered difficulties, people on the digital platform would comfort and encourage me”.

Based on the definition of MM, we adapted items 1–3 from Lautsch et al. [ 78 ], items 4–6 from Kirsch et al. [ 88 ], and items 7–9 from Kirsch [ 89 ] to measure MM on three dimensions: behaviour, output and clan control. Sample items include the following: “Our company requires employees to work the standard hours for their work group”; “Employees were evaluated by their supervisor’s observation of their results”; “Employees could negotiate with the rest of the organization when necessary”. To ensure validity, HR manager participants were also asked to send Part A of the questionnaire to their supervisors for completion. Correlation analysis confirmed that HR managers’ evaluations were significantly correlated with those of their supervisors (r = 0.64, p < 0.01).

3.2.3. Control Variables

To reduce any variance caused by factors extraneous to the research question, we followed previous WFH studies (e.g., [ 34 , 60 , 94 ]) in controlling for employee gender, age, education level, marital status, number of children, functional specialization, organizational tenure, number of hours worked per week and experience of WFH. We used dummy variables to control for gender (1 = female, 2 = male), experience of WFH (1 = no experience, 2 = experienced) and functional specialization (1 = system analysis, 2 = marketing/sales, 3 = programming/engineering, 4 = accounting, 5 = other). Age was recorded on an interval scale using the following increments: 1 (18–24), 2 (25–34), 3 (35–44), 4 (45–54), 5 (55–65), 6 (65 and over). Education level was measured as the individual’s highest degree and was assigned to one of four groups: high school or technical secondary school, college, bachelor, master or above. Existing research also suggests that marital status and number of children may influence job satisfaction by adding to household chores [ 95 ]. For that reason, we controlled for marital status (1 = single, 2 = married or cohabiting) and number of children (0, 1, 2, 3 or more). Organizational tenure was classified in terms of five groups: 1 = less than one year; 2 = 1–2 years; 3 = 3–4 years; 4 = 5–10 years; 5 = more than 10 years. Finally, we controlled for number of hours worked per week using a four-point scale (from 1 = less than 40 h to 4 = more than 50 h).

4. Analysis and Results

4.1. scale evaluations.

SPSS Statistics 26 (IBM, Armonk, NY, USA) and Amos 26 (IBM, Armonk, NY, USA) were used to assess reliability and validity. As shown in Table 2 , the measurement model achieved goodness of fit.

Means, standard deviations, and assessment of convergent and discriminant validity of reflective constructs.

Note: Diagonal elements (in bold) are the square root of the AVE. Off-diagonal elements are the correlations among constructs; * p < 0.05, ** p < 0.01 (two-tailed). Abbreviations: EJS denotes employee job satisfaction; LWFH denotes longevity of WFH; HWSS denotes home workspace suitability; JA denotes job autonomy; DSS denotes digital social support; MM denotes monitoring mechanism; AVE denotes average variance extracted.

Values for Cronbach’s α (0.830–0.920) and composite reliability (0.836–0.921) for all indicators exceeded the standard thresholds of 0.6 and 0.7 [ 96 ], respectively, indicating satisfactory reliability. Convergent validity was also confirmed, as the average variance extracted (AVE) for all constructs exceeded 0.5. Correlation coefficients for all constructs were less than the minimum square root of AVE value, indicating acceptable discriminant validity.

4.2. Fuzzy-Set Qualitative Comparative Analysis

As a histological method of analysis based on a multi-case comparison, fsQCA identifies common configurations in multiple cases and provides multiple equivalent paths for the same result [ 97 ]. This method was considered appropriate here to unravel the complex associations that develop between independent and dependent variables.

In fsQCA, the first step is to calibrate all measures as fuzzy sets with values ranging from 0 to 1. Using the direct calibration method for the five-point Likert scale, we set full membership threshold, crossover point and fully non-membership scores at 4, 3 and 2, respectively [ 97 ].

The second step is a necessity analysis to determine whether the presence (or absence) of a single condition is necessary for the outcome variable. Table 3 shows that the consistency of each condition was below the recommended threshold of 0.9 [ 98 ], indicating that no single factor was necessary for EJS.

Analysis of necessary conditions.

Abbreviations: LWFH denotes longevity of WFH; HWSS denotes home workspace suitability; JA denotes job autonomy; DSS denotes digital social support; MM denotes monitoring mechanism.

In the third step of fsQCA, an algorithm produces a truth table of 2k rows (k = number of conditions), each of which represents a combination. The truth table is refined on the basis of frequency and consistency [ 98 ] (p. 44), where frequency refers to the number of observations for each combination—with a suggested threshold of 3 for samples over 150 [ 97 ]—and consistency is the extent to which cases correspond to the set-theoretic relationships expressed in a solution (which should not be less than 0.75) [ 98 ].

After analysing the truth table thus produced, the fsQCA software generates complex, intermediate and parsimonious solutions, and the intermediate solution output is analysed. “Core” conditions appear in both the parsimonious and intermediate solutions while “peripheral” conditions appear only in the intermediate solutions [ 97 ]. Table 4 reports three configurations for achieving high EJS, all of which have an acceptable consistency of more than 0.75.

Configurations for achieving high levels of EJS.

Note: Black circles (●) indicate the presence of a condition, and circles with “×” (⊗) indicate its absence. Large circles indicate core conditions, small ones indicate peripheral conditions. Abbreviations: EJS denotes employee job satisfaction; LWFH denotes longevity of WFH; HWSS denotes home workspace suitability; JA denotes job autonomy; DSS denotes digital social support; MM denotes monitoring mechanism.

The results identify HWSS, which appears in all three configurations, as the only core condition. Solution 1 shows that even in the case of long-term WFH and regardless of the presence or absence of JA, HWSS is assisted by DSS and MM in playing a core role in EJS enhancement. In solutions 2 and 3, JA is the peripheral condition, and LWFH is the inhibitory condition. In the presence of HWSS and JA (and the absence of LWFH), EJS can be achieved when these are combined with DSS (solution 2) or MM (solution 3).

The results of a comparative analysis based on the control variables are detailed in the Discussion section. For brevity, test results for the control variables are not provided in the text but are available on request from the corresponding author.

To test predictive validity, the sample was split randomly into a modelling sub-sample ( n 1 = 128) and a holdout sub-sample ( n 2 = 128). Solutions for the modelling sub-sample from fsQCA are shown in Table 5 . The model generated from this sub-sample was then tested using data from the holdout sub-sample, and Figure 2 confirms high levels of consistency and coverage (consistency > 0.75; coverage > 0.5). Predictive tests for all models confirm that the modelled sub-sample is highly predictive of the holdout sub-sample.

Test of Model 1 for EJS in sub-sample 1 using data from sub-sample 2.

Solutions for high EJS for sub-sample 1.

Abbreviations: EJS denotes employee job satisfaction; LWFH denotes longevity of WFH; HWSS denotes home workspace suitability; JA denotes job autonomy; DSS denotes digital social support; MM denotes monitoring mechanism.

5. Discussion

As described here, the three alternative configurations for achieving EJS represent “different routes to the same outcome”, confirming that EJS depends on configurations of job characteristics. This finding is consistent with JD-R theory, which posits that job satisfaction is the result of a combination of job demands and job resources [ 23 ] (p. 46). It also confirms the EST contention that event strength, time and space jointly determine individual emotional impacts [ 46 ].

These results also identify HWSS as a core condition for EJS. As Gray et al. [ 99 ] proposed, the workplace environment can contribute to increased job satisfaction by reducing employee depression and stress. This finding conflicts with the boundary theory argument that a weak or permeable WFH boundary between family and work will disrupt the family–work balance, with no significant impact on EJS [ 30 ]. One possible explanation is that Bellmann et al. [ 30 ] only considered minimizing the duration of WFH to offset the adverse effects of family–work conflicts on EJS while ignoring the positive effect on EJS of an appropriate combination of JA, DSS and MM.

The results also suggest that the HWSS*DSS*MM configuration can ensure EJS regardless of LWFH and JA when employees are simultaneously supported by a suitable home office, adequate digital social support and an appropriate monitoring mechanism to reduce job demands. This finding resonates with job demand–control–support theory, which posits that a combination of low demand, high support and high control can increase job satisfaction by preventing employee role overload [ 100 ].

On comparing the configurations HWSS*DSS*MM and ~LWFH*HWSS*JA*MM, it seems clear that DSS and ~LWFH*JA are interchangeable. This finding aligns with social exchange theory, which posits that a supportive work environment created by supervisors and co-workers will increase employee job autonomy, thus alleviating the pressure caused by LWFH [ 101 ].

A comparison of configurations ~LWFH*HWSS*JA*DSS and ~LWFH*HWSS*JA*MM also shows that DSS and MM have alternative effects, possibly because the performance information provided by frequent communication with work partners can reduce the need for feedback during the supervision process [ 76 ], and interaction with supervisors can reduce the loneliness caused by home isolation [ 102 ]. At the same time, HWSS*JA*DSS or HWSS*JA*MM can achieve high EJS during short-term WFH. This finding conflicts with Carillo et al.’s [ 59 ] argument that employees will become more acculturated and satisfied the longer that WFH lasts. One possible explanation is that they may be ignoring the adverse effects of social isolation during prolonged WFH, which offsets the impact of event strength.

Beyond the above, our findings suggest that JA is not a prerequisite for EJS. This challenges the traditional assumption that job autonomy—as a core job characteristic—is more likely to alleviate emotional exhaustion and promote positive attitudes [ 103 ]. One possible explanation is that COVID-19 exacerbates the hazards of WFH, such as social isolation, family–work conflict, role overload, after-hours work-related technology use and stress, which cannot be completely offset by JA alone [ 104 ]. A second possibility is that long-term WFH reduces or eliminates the constant supervision and interpersonal interaction with colleagues or supervisors associated with working in the office, and as such the importance of job autonomy was weakened in the minds of home workers. This means that EJS also depends on the synergy between ~LWFH, JA, HWSS and DSS (or MM).

Finally, the comparative analysis of control variables yielded a number of interesting results: (1) Female employees place more emphasis than males on DSS, possibly because social support serves to mitigate the adverse effects of pressure on women’s well-being [ 105 ]. (2) MM only inhibits EJS among employees aged 35–44, perhaps because family needs are a more significant issue for this age group and more autonomy is needed, as too much supervision may cause work–family conflicts and increase dissatisfaction [ 95 ]. (3) LWFH has a greater inhibitory effect on EJS among more highly educated employees, while HWSS for them is less important. This may reflect their pursuit of more spiritual satisfaction beyond their basic needs, as well as social needs that cannot be met by long-term WFH [ 58 ]. (4) The more children an employee has, the more important HWSS and JA become. One possible explanation is that employees may struggle with work and home boundary violations due to the collocation of work and home, increasing the number of unfinished tasks in both domains and decreasing satisfaction with both domains. Thus, an independent workspace enables employees to create a physical boundary between work and private life, thereby preventing blurring and conflicts between family–work boundaries [ 36 ]. For employees who need to look after their children, additional autonomy reflects supervisors’ care and trust, and employees are likely to be more engaged with their work [ 14 ]. (5) DSS is a limiting condition for married employees, perhaps because married employees receive social support from their partners (and children) outside of work, and too much social support may lead to information overload [ 106 ]. (6) DSS can also have an inhibiting effect, and MM is more important to employees with WFH experience. One possible explanation is that because they do not need extra social support to adapt to WFH [ 107 ], they are more concerned about increased workloads and supervisory neglect because their colleagues are unused to WFH. (7) LWFH is only a problem for employees who work less than 40 h per week and whose organizational tenure is less than 2 years or more than 10 years. This may be because they are more sensitive to issues of belonging, which may be affected by long-term WFH. (8) HWSS is a core condition for WFH marketing and sales employees; because digital tools are their only means of communicating with customers, a quiet workspace and access to essential IT tools determine their productivity [ 108 ].

6. Conclusions

Drawing on event system theory, this study employed fsQCA to explore how EJS is affected by the alternative configurations of five antecedents of WFH event strength, time and space. The findings indicate that three configurations promote EJS. While HWSS is a core condition for EJS, LWFH has an inhibitory effect unless HWSS, DSS and MM are appropriately combined. JA is not a necessary condition for high EJS, and the longer WFH lasts, the less important JA is to employees. These findings have a number of clear implications for theory and practice.

6.1. Theoretical Implications

• The study extends the WFH literature beyond voluntary contexts, given that few studies have investigated enforced WFH [ 41 ]. By analysing how different configurations of job characteristics have affected EJS during enforced WFH throughout the COVID-19 pandemic, the study’s findings enrich the WFH literature and offer new insights for the design of future hybrid office models.
• This study enriches the literature on WFH supervision strategy management by introducing the concept of MM. According to Wang et al. [ 38 ], appropriate monitoring can alleviate employee procrastination and enhance job satisfaction. In contrast, boundary and control theories contend that monitoring prevents employees from fulfilling family responsibilities, with adverse effects on well-being [ 109 ]. The present findings enrich the literature on monitoring mechanisms for enforced WFH by conceptualizing MM in terms of behaviour, output and clan control and exploring how MM interacts with other job characteristics to promote EJS. Our findings indicate that EJS during long-term WFH depends on the synergy between MM, HWSS and DSS. This new perspective illuminates the “black box” of MM’s impact on EJS in contexts where job autonomy becomes less important to employees, as in the case of working during the COVID-19 pandemic.
• The study augments the WFH literature on job characteristics by exploring antecedent configurations of job characteristics that promote EJS during enforced WFH. Unlike previous approaches that have focused on a single job characteristic, the present study draws on EST to deconstruct WFH characteristics along the dimensions of event strength, space and time. Using fsQCA, the study identifies the conditional combinations of job characteristics that promote EJS and responds to Rymaniak et al.’s [ 110 ] call for more research into the optimal implementation of WFH.
• While EST is typically applied to reactive events, many other events can be strategically framed in this way to produce desired outcomes [ 46 ]. The present study demonstrates an important extension of EST by treating WFH as proactive event.

6.2. Managerial Implications

This study also identifies a number of ways in which managers can enhance EJS during the COVID-19 pandemic.

• As HWSS is a core condition for achieving EJS, enterprises should instruct their employees to ensure that they maintain an undisturbed work environment by consciously avoiding family distractions, creating an independent workspace and keeping family members informed about their work schedule. For employees who lack the necessary resources, enterprises should provide assistance, including financial subsidies for essential office equipment.
• When implementing long-term enforced WFH, enterprises should ensure that MM, HWSS and DSS function together optimally as the basis for high EJS.
• During short-term WFH, ensuring HWSS and JA allows DSS and MM to be interchangeable. Enterprises with inadequate DSS can therefore supervise employees through multiple channels, using performance feedback and timely communication to reduce information uncertainty.
• The configurations ~LWFH*JA*DSS*~MM or ~LWFH*JA*~DSS*MM can help married employees to achieve EJS. This suggests that enterprises should avoid the simultaneous strengthening of DSS and MM for married employees when short-term WFH supports JA. Enterprises can improve married employees’ job satisfaction by adjusting the frequency of supervision in a timely fashion or by utilizing virtual technologies, such as artificial reality, to enhance interactivity. For employees who work less than 40 h per week or whose organizational tenure is less than 2 years or more than 10 years, LWFH tends to inhibit EJS. Enterprises should prioritize these workers for hybrid office arrangements and psychological support that mitigate the adverse effects of long-term WFH on physical and mental health. As employees with two children emphasize the importance of JA, enterprises should provide support in the form of (1) time management skills to help employees balance child-care and work and (2) online training in self-leadership to cultivate work engagement and autonomy. Finally, enterprises should take steps to improve EJS on the basis of individual characteristics. They should, for example, provide more DSS for female employees, reduce MM for employees aged 35–44, reduce LWFH for highly educated employees, reduce DSS and increase MM for employees with WFH experience and improve HWSS for marketing and sales employees.

6.3. Limitations and Future Research Directions

The limitations of the present study serve to highlight valuable directions for future research.

• These proposals for the rational design of a hybrid model combining office working and WFH that can effectively predict organizational and employee-level outcomes, such as the impact of workload on job satisfaction, invite further research in a post-pandemic era.
• While the study focuses on the impact of WFH at employee level, managers’ attitudes to WFH are equally important because they decide whether to implement WFH. Rose et al. [ 111 ] found that the long-term implementation of enforced WFH during the COVID-19 pandemic can change hostile managerial attitudes to WFH. Future research should investigate which WFH job characteristics affect the attitudes and behaviours of middle and senior managers.
• The use of cross-sectional data to explore the combined effects of WFH job characteristics in terms of event time, space and strength invites further investigation of the varying impacts of WFH event strength on EJS in relation to spatial and temporal change.
• Future studies should employ other measures aside from self-reporting to invite managers to assess employees’ JA. Other approaches might include asking family members to evaluate employees’ HWSS, using wearable devices, such as electronic watches, to measure noise when WFH in order to eliminate common method bias.
• While this study has controlled for a range of employee characteristics, future research on the relationship between WFH and EJS should take account of personality characteristics and individual preferences that were beyond the scope of the present article.
• This fsQCA-based exploration of antecedent configurations for optimizing EJS should be supplemented by other qualitative methods (e.g., interview, observation and field experience) to disclose the inherent causal logic of each configuration.

Part A of the questionnaire on working from home arrangements and job satisfaction during the COVID-19 pandemic.

Part B of the questionnaire on working from home arrangements and job satisfaction during the COVID-19 pandemic.

Author Contributions

Conceptualization, J.Y. and Y.W.; methodology, Y.W.; software, Y.W.; validation, J.Y. and Y.W.; formal analysis, Y.W.; investigation, J.Y.; resources, J.Y. and Y.W.; data curation, Y.W.; writing—original draft preparation, Y.W.; writing—review and editing, J.Y.; supervision, J.Y. All authors have read and agreed to the published version of the manuscript.

This research was supported by: The Natural Social Science Foundation of China (18ZDA052).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of School of Economics and Management Shanghai Maritime University (251 and 20200101).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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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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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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Who Really Benefits From the Great Remote-Work Experiment?

According to one study, women with more job experience suffer the most.

Four years after the great remote-work experiment began, the public debate has boiled down to: Bosses hate it and workers love it. That’s the story we’re told time and again in a zero-sum debate that leaves little room for nuance. In reality, remote work depends on all sorts of things—the industry, the occupation, and interests of employers and workers, not to mention the interests of government and the broader public. Somehow, remote work is both a remarkable boon and a tremendous loss.

In our first episode of Good on Paper , I talk with Natalia Emanuel, a labor economist at the Federal Reserve Bank of New York, who has co-authored a paper trying to tease out what happened to workers after they went remote. Her research focuses on software engineers at an unnamed Fortune 500 company, some of whom were functionally remote even before the pandemic because their teams were spread out over a large campus. When COVID-19 came and everyone was sent home, it created the perfect circumstances to assess what was really happening to workers once they went remote.

Our conversation delves into all sorts of questions. Do people understand the tradeoffs they are making when they choose to work remote? What’s the impact on a team if even one person goes remote? Does remote work benefit older women at younger women’s expense? What happens to people’s social lives in the era of remote work?

Listen to the conversation here:

The following is a transcript of the episode:

Jerusalem Demsas: My name is Jerusalem Demsas, and I’m a staff writer here at The Atlantic . And this is the first episode of Good on Paper .

Good on Paper is a policy show that questions what we really know about popular narratives. Narratives do a lot to drive what our world looks like—whether they exist in the broader media ecosystem or as a consensus within a specific group of people, like economists or policy wonks. But sometimes these narratives are built on shoddy ground. One fact, or a set of reasonable facts, spins out of control and is woven into a tale that goes well beyond what we actually know.

This show came about as an extension of my own writing and reporting here at The Atlantic because over the years, as I’ve written about a bunch of things—from why it’s so hard to build a wind farm in Alabama to why a bunch of people had babies during the pandemic—I’m struck time and again by the strength that certain narratives have. There are overly broad and often overly simplistic claims about the world that play a huge role in how our political system works.

And I’ll be completely honest. There are plenty of times where I’ve realized those kinds of ideas are playing a role in my own thinking. That’s sort of my beat. I dig in when I see something that seems off or undertheorized or at least not super fleshed out. And while there’s no one right answer, the goal of this show is to figure out what we really know about a topic and use research to get a deeper understanding of the truth.

This episode of Good on Paper is about the messy economics of remote work.

Behind the scenes in this whole debate is the presumption that remote work is good for employees and bad for employers and bosses. But is that true? For my part, I’ve been a bit disillusioned by the remote-work experiment. There are, of course, amazing benefits to remote work. For those with disabilities or dependents, remote work can be more than just convenient; it can open up opportunities that hadn’t been possible.

But at the same time, there have been some serious costs—missing out on the social part of work. Sure, there’s some annoying water-cooler chitchat, but I have a nagging feeling that I’ve lost out on important learning and connections by being remote.

Most of all, it’s not really clear to me how you make these decisions fairly. Can my desire to work in person with my colleagues trump another person’s desire to work from another city? It’s still something I’m working out.

A few weeks ago, I talked with Natalia Emanuel. She’s a labor economist working at the New York Federal Reserve Bank. And she wrote a really interesting paper that helps unlock the varied impacts of remote work.

All right, Natalia. Welcome to the show.

Natalia Emanuel: Thank you so much for having me. I’m really excited to be here. Before we begin, I do note that the views I would express today are my own. They don’t reflect those of the Federal Reserve Bank of New York or the Federal Reserve System at all, so they’re simply mine.

Demsas: Yeah. So you were finishing your Ph.D. when COVID hit, right?

Emanuel: That is correct.

Demsas: How was that? Did remote work feel that different to you? I kind of imagine academics siloed off in their offices, never speaking to each other.

Emanuel: Ah, well, my co-author on two remote-work papers—her name is Emma Harrington, who is now an awesome professor at University of Virginia—she and I were randomly put into the same office in a second year of graduate school, and then partly because of that, we ended up becoming co-authors. Because before that, we actually hadn’t really known each other particularly well. So there is an element of: Yes, we were siloed. Yes, we were in the basement with almost no light at all. But by being in the same windowless office together, we did form a nice bond that way.

Demsas: This feels like an econ paper that’s, like, come to life. Isn’t this like a finding?

Emanuel: Exactly.

Demsas: Academics that sit near each other tend to co-author or something.

Emanuel: Correct, yeah. In terms of the actual COVID during the job market, it had a very important impact on us, which is that all of our job market was done remotely. So we were doing interviews remotely. We were doing flyouts to visit the potential places we might take jobs. All of that was not an actual flyout. That was a Zoom flyout. And so that was the place where it had more impact, perhaps on the actual paper writing.

Demsas: Did you think it affected the interviews or anything?

Emanuel: So purely anecdotally, I would say the people who I have given talks to remotely remember me and remember my findings less than when we were in person.

Demsas: Wow. Just because everyone’s doing, I don’t know, The New York Times Connections game while they’re listening to you. That makes sense.

Emanuel: I imagine it was email, but I think you have a more enjoyable thing. Maybe they liked my talk more because at least they were doing something fun.

Demsas: Yeah. I feel like before we get into the meat of your study, there are very different estimates about how many people are actually remote working right now. And it led me to realize: How do we actually know what’s happening? Do you have a sense of how many are remote working? Why does it feel like we're getting different answers from different data sources?

Emanuel: There is a big difference among different ways that you could ask this question and exactly what you mean by remote work. Does that mean that there is no place you have to go to for your work? Does it mean that you have to be in your workplace’s office as opposed to a cafe shop? Does it simply mean that you have to have left your bedroom?

You also can get different answers when you’re asking, Are you fully remote ? versus, Are there certain days of the week when you are remote ? versus, How many hours a week are you remote ? And so those two dimensions can give a lot of variation in terms of exactly what number we’re getting.

Demsas: So the one that I’m going to just try to use in my head—and, for listeners, is what the BLS, Bureau of Labor Statistics, is doing—so in 2024, in February, their survey data shows that 77 percent of people did not telework at all. Around 11 percent of people teleworked all hours. And roughly 12 percent teleworked some hours. So it feels like this is a really big conversation, for 12 percent of the population to be fully remote working. Do you feel like that's an outsized conversation that we’re having about remote work?

Emanuel: Well, I think the 77 number of people who are not working remotely, that makes a lot of sense, insofar as some jobs are just really hard to do if you’re not on-site, right? Being a car mechanic: very hard to do if you are not actually at the car. Similarly, trauma surgery: Maybe one day it’ll be done by robots, and the robots are controlled by people who are far away; that’s not how trauma surgery is happening right now. Similarly, we’re not thinking about occupational therapists or nursery-school teachers. So many of those jobs, there just isn’t a possibility of them even being remote.

And so what we’re thinking about here are the jobs where there is a possibility of being remote. You can imagine sales, customer service, consultants, software engineer—many jobs that are more computer based, those are the ones where we should be thinking about remote work is a possibility.

Demsas: And the quintessential people who can work from home are probably software engineers and coders, which brings us to your study. So you have a working paper at the National Bureau of Economic Research—NBER—and it came out last November. Can you tell us about it?

Emanuel: Sure. We are looking at software engineers at a Fortune 500 company, and this is a sufficiently large company that they have on their main campus two buildings where the software engineers sit, and those buildings are about 10 minutes apart. Well, 12 minutes if you’re on Google Maps—10 minutes if you’re me.

We found that some of the people who were on teams where everybody could be in one building—whereas because there’s not as much desk availability, some teams actually had to be separated across those two buildings. And so the teams that were separated across the two buildings had most of their meetings online, because if you’re only having a 20-minute meeting, you’re not going to spend exactly the length of your meeting walking there and back.

And so we can see beforehand what happened to those particular teams. And then once the pandemic forced everybody to work remotely, we can see what happens thereafter. And so we can use the teams that were already meeting remotely, and they’re our control group: they’re remote before the pandemic; they’re remote after the pandemic. Whereas the people who are on one-building teams, they were with the rest of their colleagues, and then after the pandemic, they’re working remotely.

Demsas: Mm-hmm.

Emanuel: That’s an interesting context to look at, from our perspective, because it allows us to understand there is a measure of productivity, and then there’s also a measure of digital collaboration. And so we were trying to understand what remote work does for the pieces that you might learn from colleagues, right?

There’s another study that finds that a sixth of all skills that one acquires over their lifetime are coming from colleagues. And so we were very interested in the impact of remote work on this collaboration and on-the-job training.

And so we also think that software engineers are particularly interesting because, in many ways, it’s the best-case scenario for remote work. So for one, all of their output is digital. Also, software engineers have established mechanisms for giving each other digital feedback on their code, and that was something that they had sort of industry standard and has been for decades before the pandemic.

Demsas: What are your main results? You’re observing these software engineers, and as you say, these software engineers are basically just coding full-time. They’re just writing a bunch of code, and they’re getting comments on that code, and that’s how you’re looking at feedback. So what are the findings of that observation?

Emanuel: Yeah, we’re finding that the folks who were in person with their teams, they were in the same building—we’re going to call them one-building teams—they were getting about 22 percent more feedback from their colleagues on their code. So they were just getting more skills, more mentorship when the offices were open.

And then when the offices closed and everybody was going remote, pretty immediately we see that gap closes. And so then everybody is getting less feedback than they were. And this is useful as a counterfactual because if you imagine you’re saying, Oh, well. They’re getting 22 percent more feedback. Well, maybe that’s just because they tend to be chattier, or maybe it’s because they really actually need that feedback a little bit more, the people who are on one-building teams . If that were the case, then even after the offices close, that would still persist, whereas if this is something really coming from being in person with your colleagues, then that gap would close. And that’s exactly what we find.

Demsas: So there are 11.5 percent more people commenting on engineers’ work if they’re in one-building teams than if they’re in the multi-building teams, right? So there are a lot more people commenting on your work if you’re in a one-building team. So what is happening there? Why is it that someone who’s in a one-building team is seeing more comments?

Emanuel: We look at this in terms of the exact type of comments. So part of this is they’re just getting more comments on the initial go, but then also they’re asking more follow-up questions and then getting more replies to the follow-up questions. And so we’re seeing the depth of conversation is partly driving this. We additionally see that this is happening in terms of speed—that they’re getting faster feedback, as well. And so there are many dimensions here.

I would also put a small asterisk here, which is that we’re measuring this in terms of the digital comments that they’re getting. But people who are in person, it is much easier to just turn to your neighbor and say, Hey, can we just talk about this for a quick second? And so if we think that that’s happening more among the people who are sitting next to each other, then the estimates that we’re getting are actually lower bounds.

Demsas: And so what’s the effect of all this? What’s the effect of getting more comments?

Emanuel: There are a number. The first is that, as you might imagine, if they’re working on building skills and responding to these comments, their actual output is a little bit lower, so they’re producing fewer programs overall. And, accordingly, because they are producing fewer programs, they also are less likely to get a pay raise.

But once the office is closed and that level of mentorship has now equalized, the people who have been working on building their skills, they’re actually more likely to be getting pay raises. And they’re actually twice as likely to be quitting to go to a higher-paying job or a job at a higher-paying company.

And so, it really depends on the time frame that you’re thinking about this. In the short run, it looks a little painful because they’re not doing as well. But in the long run, you’re seeing the fruits of their labor.

Demsas: I find this really interesting because what it indicates is that there’s this investment that happens early on in someone’s career, and then when they go remote, the people who had that kind of investment are able to still capitalize on it. But in time, they’re going to look less productive than their more remote peers. Those remote peers are just banging through code. They’re not having to respond or engage with their mentors or with the older engineers. It’s a strange finding because it would indicate that managers would really prioritize and see that remote work was doing well in the short term.

Emanuel: Totally. And I think that is consistent with what we saw at Meta, right? Early in the pandemic, Mark Zuckerberg was like, Yeah, this sounds great. People seem to actually be more productive when they’re remote . And then sort of three years in, that’s when Mark Zuckerberg was like, Actually, let’s come back to the office. It seems that people actually are more productive when we have some amount of in-person time . And so it does seem as though it does take a little bit of patience to be able to realize these different effects over different time horizons.

Demsas: Wait, you mentioned Meta. Is this Meta?

Emanuel: So I’m actually not allowed to share what company we’re studying.

Demsas: Okay, great. Well, I will just, in my head, imagine a giant campus in Silicon Valley that has multiple buildings where software engineers work far apart.

Emanuel: That sounds like a perfect thing to imagine.

Demsas: And people can draw their own conclusions.

And so do these findings contradict earlier findings in the space? Existing literature about remote work and productivity, as I’ve mentioned before, it’s kind of mixed. But there’s the seminal 2015 study from Nicholas Bloom where he looks at a 16,000-employee company in China. And the study design there, it’s employees that volunteer. They then randomly assign those to either be work from home or in the office. And they find that work from home leads to a 13-percent performance increase in productivity, so both more minutes per shift and more calls per—it’s a call center—so it’s more minutes per shift that they’re making calls and also more calls per minute. And so that feels very different than what you’re finding here.

Emanuel: Yeah, so first of all, I think that it is totally possible to have different findings in different settings. One of the things that makes Nick’s study particularly interesting is there it was, as you mentioned, all volunteers. Right? These were existing workers who had been at the company already, and they volunteered to go remote. So that’s not necessarily the case when we’re thinking about the pandemic. Not everybody volunteered to be remote.

Also, in that context, everybody had to have their own room to work in as a specific workspace, as separate from people who are working on their bed. And so that also could change it. And so you do see potentially different outcomes there.

Also at a travel agency, that is pretty siloed work, whereas as software engineers, they do need to understand what this code base is doing, how people have been thinking about that particular function already. And so there is a little bit more of a collaborative nature there.

Emanuel: The other thing I would note is that, eventually, remote work unraveled in that context because there were fewer promotions happening among the remote workers. And so people ended up wanting to come back to the office because that’s where they got the visibility to be able to get the promotions that that higher performance really warranted.

Demsas: And so they weren’t getting promotions, because they were doing worse work? Or they weren’t doing promotions, because managers had this attitude that people who are in person, who they’re talking to in the office—those people are just more worthy of promotions?

Emanuel: Well, I wouldn’t say that they were doing worse work. According to Nick’s paper, it seemed as though they were actually doing better work.

They were overall more productive. But it does seem as though there is a disconnect between pure productivity metrics and the human component of promotions.

Demsas: And so you have a 2023 study where you look at a call center. It’s a U.S.-based call center, and I’m not sure how else it may differ from Bloom’s study. But you find that pre-COVID, remote workers were answering 12 percent fewer calls per hour, and that feels like there’s something going on that’s stably less productive about remote work, even in the same work context. So what’s going on in understanding the differences in your findings versus Nick Bloom’s?

Emanuel: Yeah, so in our study, we were finding that before the pandemic, the people who elected to work remotely, at least in this company—which, again, as you mentioned, we were thinking about a Fortune 500 company and their customer-service workers—and there we found that the people who chose to work remotely tended to have lower productivity, on average, than the people who chose to be in person. And so that’s what economists would call negative selection.

But that is also consistent with, if you anticipate that the people who are going to get promotions are those who have closer connections to the managers and are those who are going to be in person and that you might be, not to use a horrible pun, but you might be phoning it in a little bit—

Demsas: ( Laughs .)

Emanuel: Then that would make sense that you would be more willing to be remote. Now, of course, I have no idea what was in each individual person’s mind, but that is consistent with understanding that there is a promotion penalty to being remote.

Demsas: Okay. So returning to your original new study also about remote work, but I think the thing that’s really interesting about the research you find is this junior-versus-senior benefits to remote work, right?

So I really want to talk about how different it is if you’re an early-career software engineer versus a late-career software engineer. What happens to people early career versus late career when it comes to remote work? How does that affect their productivity? How does it affect how they do their jobs, what research they’re getting, and their long-term outcomes?

Emanuel: In general, it’s the people who are most junior who have the most to learn and are getting the most comments and therefore having to do the most learning. And who’s giving this feedback? Well, that’s the more senior people. Those are the people who have been with the firm a lot longer.

We see that the hit to productivity is actually happening both among junior people, but then particularly it is concentrated among the senior people who then have to be really understanding somebody else’s code and thinking deeply about it and giving them feedback to try to think, Oh, how can I help this person grow? And how can I help make sure that this code is doing well?

And so that meant that for the senior people, there was a cost in their productivity from being in person and providing all of that feedback. And so that means when they go remote, particularly the senior people’s productivity actually increased. And so again, for them, you could see a boost in productivity right at the beginning of remote work. And then from the firm’s perspective, you could imagine that that might not persist forever if you're then getting your junior engineers who aren’t getting as upskilled as you might hope.

Demsas: So senior folks are just like, Thank God I don’t have to answer all these comments all the time. I can just do my job , and that benefits them. I wonder though—I think this is really interesting, right? Because popularly understood is that people who are young really want to work remote and that older people are more willing to come back to the office for whatever reason.

Why is there this disconnect if it is the case that young people are really missing out on this both productivity-enhancing but also, as you said, wage-enhancing and promotion-enhancing benefit of learning from senior engineers? Why aren’t they clamoring to get back in the office?

Emanuel: One hypothesis is that they simply don’t know, right? Maybe they are not aware of the benefits of mentorship from being in the office. Maybe they’re not aware about how that mentorship and the skill building actually translates into future jobs, future earnings. So that’s one possibility.

Another possibility is: Maybe they have a different value system, right? Maybe they’re willing to say, Look, my job is not the top priority for me, and it’s much more important for me that I am spending time with my roommates, my neighbor, my friends, my loved ones . That’s a possibility.

I think another possibility, and there our paper gives a little bit of evidence, is that if you have even one colleague who is remote, that yields about 30 percent of the loss from having everyone be remote.

Demsas: Wait, so if just one person on your team goes remote, you lose all of that benefit of being in person?

Emanuel: Well, a third of it, yeah.

Demsas: A third of it. That’s huge!

Emanuel: Right. It’s huge, from just one person.

Demsas: Does it scale up? If it’s a second person, did you find anything there?

Emanuel: We didn’t actually look at that. But it is a huge impact. Really, in some ways, that’s validating. It means every single person really matters.

But if it’s the case that when they come into the office, not everybody is there, and so they’re still doing some remote Teams meetings or Webex or whatever it is while in the office, then it’s possible that they’re not actually getting the whole benefit of being in the office. And so, perfectly rationally, they’re saying, Maybe it’s not so much. Maybe I’m not getting all of this mentorship .

And so there you go: three hypotheses.

Demsas: I am partial to the last two things you said. I don’t really buy hypotheses, usually, where someone’s just being dumb and they’re doing something that’s bad for them. I usually buy that they either are prioritizing something else—like, not everyone wants to be a productivity-maximizing machine. They may want to just not have a commute. They may want to live near their family. Whatever it is.

And I think also this last thing that you said is really important, too. Because The Atlantic offices are open, but there’s a lot of hybrid work, and so you’re coming in on a day where there might be 10 people on your team, and then coming in on a day where you’re like, Wow, I’m the only person on my team here . And those are very different days, and they are very different things you might get out of that. So that hits stronger for me.

Emanuel: One of the things that’s pretty interesting is that we find even when you’re in a building with colleagues who are not on your team, we still find a bump in the mentorship and the feedback that one gets. And it’s not from your teammates, then, of course. It’s from the non-teammates. But there still is an element of enhanced mentorship, feedback, collaboration simply by being around people.

Demsas: We’re going to take a quick break, but more with Natalia Emanuel when we get back.

Demsas: I think that probably the most interesting angle in your piece is the angle on gender. Can you tell us a little about this? What is different about how women in this firm receive feedback on their code?

Emanuel: Yeah, so before the pandemic, we find that female engineers are receiving about 40 percent more comments on their code than our male engineers, giving us an effect that’s roughly twice the size as it is for male engineers, overall. And so we’re finding that this mentorship is particularly important for female engineers. And to unpack where that’s coming from, we find that the female engineers are much more likely to ask questions when they are in person.

Demsas: So, when I first heard this, I was just like, Okay, are they getting more feedback because people are just nitpicking women’s code ? How did you decide whether or not this was actually actionable feedback or if it’s just people being sexist?

Emanuel: Yeah, this was one of our first concerns. One of the first people we presented to said, Are we sure this isn’t mansplaining? And so what we did is we took a subset of the code, of the comments, and we gave them anonymized to other engineers and said, Is this comment helpful? Is it actionable? Is it rude ? And we then took their reviews back, and we found that they are equally actionable, not differentially nitpicky for female engineers. And so it does really seem as though these are substantive, meaningful comments but not simply mansplaining—and interestingly, not differentially rude, either.

Demsas: That’s great to hear, actually. And, sorry, these external reviewers, they were blind to gender when they were looking at the code, right?

Emanuel: They were blind to gender. They were blind to seniority. They were blind to whether you were proximate or not proximate to your colleagues. All they saw was the comment.

Demsas: And what that raises for me, though, is this question: If women are disproportionately getting actionable feedback, is the claim that women’s code is just worse than men’s?

Emanuel: So we don’t actually see the code itself, but we can see that we’re not finding they’re more problematic overall. It’s not as though we’re seeing, Oh, there’s bigger issues brought up in the comments , or sort of, They will always break, or something like that.

Demsas: I find this interesting. And I also think it’s interesting because this is not the only plane on which women are affected differently than men in your study. You have this finding that junior women are receiving a lot more code and a lot more actionable feedback, and it’s benefiting them potentially down the line. But you’re also finding that the people who are giving them all that feedback tend to be senior women engineers who, for themselves, as you said before, giving all that feedback takes time. That’s something that hurts your productivity, so that cost seems disproportionately borne by senior women.

Emanuel: Yeah, I think you said it exactly right, that the feedback that’s going to both female and male junior engineers, a lot of that is coming from female senior engineers. And so the giving of the mentorship is also coming from female engineers. And so we see a lot of exaggerated effects on both the benefit sides for females, so junior women are getting the benefits, but also senior women are paying the price.

Demsas: And so when they go remote, do senior women get more productive?

Emanuel: Mm-hmm. Yeah.

Demsas: That’s really weird, right? Because I feel like the dominant frame for the pandemic and gender was mostly around this idea that women, when they were going remote, were being now doubly burdened, right? So you go home, and if you’re a mother, you have to do more child care. Often, you’re finding you have to share space with your male partner, in a lot of cases. And it was the sense that potentially women are now having to be doubly burdened by the responsibilities of home and the responsibilities of work. Obviously, it’s not contradicted by your evidence, but were you surprised by this finding?

Emanuel: I would make one technical point and then one overall comment. The first technical point is that this is why it’s really, really helpful to have a control group, right? Because in both of our groups—both the people who are working in one-building teams beforehand and the people who are in multi-building teams and therefore a little remote beforehand—both of them would be similarly burdened by the pandemic. And so we can difference out the impact of the pandemic and really just zero in on the effect that’s only coming from working remotely. So that’s one component there.

The other piece that I would mention is that in our sample of engineers, only 16 percent are parents, so that doesn’t seem to be the main component here. And in some ways, I think that, while not helpful in terms of thinking about the impact of the pandemic, it’s potentially helpful in terms of thinking about remote work long term. When we’re thinking about remote work post-pandemic, we’re not really thinking about Oh, but you will also be trying to supervise your fifth grader’s language-arts exam .

Demsas: It’s hard for me to know how generalizable these findings are. And basically every major study I see on remote work is mainly done in the context of software engineers or call-center employees. And those are just two very specific types of jobs and are not maybe similar to a lot of other jobs that are potentially work remote, whether you’re working in HR or you’re working in media or you’re working as a lawyer or anywhere in the legal profession. It’s hard for me to know how much you can take away from this and apply to other contexts. How do you think about that?

Emanuel: Yes, you are totally right that the existing literature feels as though it really focuses on sales, call center, and software engineers, partly because those are places where we have really good measures of productivity. I would love to be able to think about this for other occupations, but I do think that we have a bit of a quantification problem.

As I mentioned earlier, I think one of the things that’s useful in our context is to think that software engineering is probably most amenable to remote work, and that other contexts don’t have these established ways of giving each other feedback online, don’t have very structured systems for how to meet. Software engineers often work on the agile system of meeting, where they have daily standup meetings that happen regardless of whether you’re in person or not. They have very structured ways of exactly when they are going to be doing a sprint on exactly what type of work, and they have a lot of coordination around who’s doing what when. And so for occupations that don’t have either of those things—digital means of giving feedback and that meeting structure—you can imagine remote work is likely to work less well for them.

Demsas: That feels like something that a lot of different industries could innovate on, right? One of the things that I’ve heard pointed out is how many more patents there are now on remote-work technologies. Not even just those technologies that help make it possible for a lot more firms to work at home, but also just the cultural technology: the fact that you can just ping someone on Slack, the fact that you can just huddle quickly—clearly, I use Slack way too much—or you can figure out a way to have a standup with your manager. In a media environment, you usually just walk over in a newsroom, but people now have standing meetings that they will just have with their manager. So how much of that is not portable to other workplaces?

Emanuel: Oh, I totally think many of these are portable. And I do think that we’re going to have some growing pains as people realize, Oh, I could just have a standing meeting , and then realizing that, Oh, but now I have a standing meeting with 15 people, and it’s taking up half of my Friday . And so I do think there will be some growing pains, but that there is quite a lot to learn from other organizations that have already done remote work pretty effectively.

Demsas: And so, zooming out a bit, Adam Ozimek—he’s also a labor economist, and he’s also a longtime booster of remote work—he once half-jokingly said that skeptics of remote work could basically be described as either extroverts, urbanists, workers in obviously non-remote occupations, and downtown office-building owners.

And a Venn diagram of labor economists and urbanists has significant overlap, and so I wanted to ask you if you think your background as a labor economist biases you against remote work or thinking that it’s positive. Do you feel that you’re coming into the work feeling like it’s not going to go well? Or how do you think about that?

Emanuel: Well, I’m definitely not an extrovert, so we can cross out that one. I would not say I had strong priors going into this. It was one of those topics that I was genuinely extremely excited to see whatever the results would be and could totally have spun a story that it could go in either direction.

Demsas: But, I mean, do you think that you would be surprised if long-term remote work was viable at a large scale across these firms? Even what you said at the beginning, when we started chatting, about your ability to meet Emma, your co-author, and work with her—I mean, those kinds of findings are often really strong underlying belief systems for labor economists.

Emanuel: I do think there’s totally a world in which remote work really takes off and we can have massive productivity gains. I think that this comes with a lot of growing pains that we were discussing, of trying to figure out exactly how we can still make sure that we form deep connections, have a lot of mentorship.

And I think we see a lot of firms doing some incredibly creative things, whether that’s quarterly offsites or teams coming in at regular intervals and trying to do sort of a round-robin of who's meeting with what. And so I do think we’re in a period of experimentation while we’re trying to learn how this is going to work. But yes, I would definitely say that there is a world in which this does work and that we have to figure out exactly how it's going to work.

Demsas: So, we’ve talked a lot about productivity here, but life isn’t just about productivity. There are lots of reasons why someone may or may not want to work remote. What’s your sense of the impact of remote work on individual well-being?

Emanuel: This is the question in many ways. On the one hand, maybe it allows folks to live close to their family, their community, and so there’s a really wonderful gain in terms of people’s well-being because they have these strong social connections. On the other hand, in many decades past, a lot of people found their friends at work, and many enduring friendships, many marriages originated in work. And so if people are not making those connections at work, there has to be some other way that they are going to be able to make those social connections that are going to sort of fulfill their needs.

Maybe that substitution is happening. I don’t think we have a great idea yet. And so I think you, again, could imagine it going either way, and I am extremely excited to see research coming out that can give us insight as to which one we’ll weigh more strongly.

Demsas: I’m a little bit pessimistic about it and, in part, I am because I feel like the trend of work technology has been to just eat into more and more of our leisure hours. Email gets invented, and all of a sudden you leave the office, and it doesn’t mean that you’ve left the office. And Slack gets invented. Now you have to be instantly available; even if you’re in the bathroom, you know that your boss has messaged you.

And then there was a 2021 paper that looked at GitHub activity and found that users were more likely to work on weekends and outside 9-to-6 hours when they went remote. And it feels to me that this is just another step in the machine of, Okay, remote work means now that there aren’t even defined hours. And in some sense, theoretically, that could mean flexibility, but in another sense can mean your entire life is now work .

Emanuel: I think that’s totally possible. I would say that there’s a world in which that GitHub finding that you mentioned is actually a really good thing, right? So imagine the world in which I know exactly what my hours of output have to be. I know the product that I need to create. But I actually want to stop work at 3 p.m. so I can pick up my kids from school, hang out with them until, you know, 7:30 or 8, when they go to sleep. And then I want to put in my extra two hours that, you know, would have happened between 3 and 5 but now can happen after bedtime.

So maybe that extra flexibility is actually welfare enhancing, and the people they’re studying are actually really happy about that. And so I think simply based on that statistic, it’s not obvious to me whether we think of this as a good thing or a bad thing.

I do think work creeping and taking over one’s entire life so that there’s nothing else there and there’s no time for anything else—I think that’s almost certainly a bad thing. But again, I’m not sure exactly how to think about the welfare implications there.

Demsas: Before we close things out, our last question: What’s an idea that you’ve had that was good on paper?

Emanuel: So I sew a lot. I’ve sewn 17 quilts, several wedding dresses, only one of which was for me. And so one idea that I think tends to look good on paper is the home sewing machine that is computerized.

Demsas: Oh. What is that?

Emanuel: It’s just a sewing machine that has a screen on it and that you can say, Oh, do this embroidery pattern, and it’ll output that. And, I would say, for the type of sewing that I was doing, it was 100 percent useless. It meant that it was much harder to maintain, much harder to troubleshoot. You can’t do your own oiling and maintenance in the same way that you could for a mechanical sewing machine.

At one point, the sewing machine actually just decided to only run in reverse. And rather like driving in New York City in reverse, it’s possible, but it’s a little anxiety inducing—not the world’s safest thing. So I ended up reverting back to the sewing machine that’s fully mechanical, was made in 1910 by Singer sewing machine, is actually foot powered, hadn’t been used in the entirety of my lifetime but with a little bit of elbow grease was totally great. So it was one of those things that, in the abstract, seemed great and, in real life, was not.

Demsas: Well, this feels like a metaphor, a productivity-enhancing machine that actually reduced your output. On that note, well, thank you so much for coming on the show, Natalia.

Emanuel: Thank you so much for having me.

Demsas: Good on Paper is produced by Jinae West. It was edited by Dave Shaw, fact-checked by Ena Alvarado, and engineered by Erica Huang. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.

And hey, if you like what you’re hearing, please leave us a rating and review on Apple Podcasts. It’s how people hear about the show. Or you can let a couple of friends know on your own.

My name’s Jerusalem Demsas, and we’ll see you next week.

Top Work From Home Productivity Statistics

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The pandemic spurred one of the biggest changes ever, in the business world: the normalcy of remote work. While plenty of employees enjoyed the flexibility of working at home before COVID-19, remote work policies have since exploded, many organisations have adopted VoIP software and there are more companies offering remote work roles now than ever before.

In fact, from 2019 to 2021, the number of employees working from home (at least part of the time) tripled, from 5.7% to 17.9% , according to Census data . Remote workers shot up from approximately 9 million to around 27.6 million people , one of many work from home statistics that point to a new normal in the business world

But some companies still aren’t convinced. Most notably, Elon Musk has made a big push to get Tesla and Twitter employees back into the office, and some studies show that as many as 65% of employers want workers back in the office , citing everything from productivity to company culture.

Unfortunately for these employers, the data just doesn’t back it up. In this guide, we’ll cover a wide range of work from home statistics, which will reveal the truth about remote work benefits and downsides and whether productivity really is at risk by so-called telecommuting.

Key Stats to Know

• From 2019 to 2021, the number of employees working from home at least part of the time tripled from 5.7% to 17.9% ( US Census )
• 47% of businesses notice increased productivity levels amongst employees who work remotely (Tech.co survey)
• 78% of CEOs say remote collaboration is here to stay ( PwC )
• Employees that work from home are more optimistic about work (89%) than those working in the office (77%) ( ADP )

Key Remote Working Statistics

The benefits of telecommuting and remote working have been plentiful, from less commuting and flexible schedules to saving money and improving work-life balance. But has work from home productivity actually improved? Here are a few key statistics that shine a little light on the new normal of the business world:

• One third of survey respondents said they would take a pay cut of up to 5% in exchange for the option to work remotely at least some of the time; a quarter would take a 10% pay cut; and 20% would take an even greater cut. ( Owl Labs )
• 47% of businesses noticed increased productivity levels amongst employees who work remotely (Tech.co)
• Remote work is the number one priority for top talent ( Forbes )
• Performance boosted 22% when employees were allowed to work from home ( Stanford GSB )
• 30% of employees do more work in less time while working remotely ( SHRM )

Suffice it to say, remote work and telecommuting provide workers with incentive, flexibility, optimism, time, money, and an overall productivity boost, so it’s no wonder it’s popular among employees after the pandemic. After all, if you can dial in to work with technology such as VoIP software , there’s really no need to spend all that time and money coming into the office.

How Could Working From Home Increase Worker Productivity?

You might be asking yourself, what’s the difference between remote working and telecommuting? To be honest, it’s a fair question, as the difference between them as definitely been blurred since the start of the pandemic. According to experts, there are some key differences between remote working and telecommuting.

From a definition standpoint, telecommuting is the act of working remotely via the phone, email, or internet, while remote work is the act of working from anywhere but the office, whether digitally connected or not. Additionally, in most cases, telecommuters still live near the office, whereas remote workers might live anywhere in the world, and are more likely to work out of the office full-time, rather than part-time.

Other than those slight differences in definition, they’re colloquially the same things, particularly since the pandemic. The average person will use them interchangeably, with remote work now the decidedly more popular term in a typical business setting.

Remote working productivity statistics

As for how remote working can actually improve productivity at your business, here are a few statistics that should help motivate you:

• 32.2% of hiring managers said that productivity has increased since remote work policies have started  (Upwork)
• 30% of employees told researchers they were more productive and engaged while working remotely  (University of Chicago BFI)
• Businesses experienced a 22% performance boost when launching a hybrid work model  (Stanford GSB)
• 30% of employees did more work in less time, while working remotely  (SHRM)

Working From Home vs Office Working: How Can Each Benefit Your Business?

At this point in history, a lot of employees have had the chance to work both at home and in an office. From company culture and collaboration to flexible schedule and pajama pants, there are plenty of reasons to keep doing both, depending on your particularly situation.

There are obviously pros and cons for each, so let’s take a look at how office working and working from home differ.

Work from home statistics

• US employers can save an average of $11,000 per year for every half-time telecommuter. Savings are based on increased productivity, cheaper real estate costs, and reduced absenteeism and turnover.  (Global Workplace Analytics)
• Remote work is the number one priority for top talent  (Forbes)
• 79% of employees said they would be more loyal if an employer allowed for a more flexible schedule  (FlexJobs)
• Remote employees have more job satisfaction (90%) than those commuting to work (82%)  (ADP)
• Remote workers are 22% happier than in-office workers  (Owl Labs)

Office working statistics

• If employees were not allowed to work remotely after the pandemic, 54% of US employees said they would stay, but they would be less willing to go the extra mile, an approach also known as quiet quitting   (Owl Labs)
• 97% of employees say they don’t want to return to the office full-time  (Forbes)
• 51% of workers would outright quit if asked to give up their new hybrid working model  (YouGov and Microsoft)
• Employees that work from home are more optimistic about work (89%) than those working in the office (77%)  (ADP)
• 55% of employees say they work more hours remotely than they do in the office  (Owl Labs)
• 74% of professional expect remote work to become the standard  (Forbes)

Strategies to Increase Work From Home Productivity

Now that you understand the value of remote work in comparison to in-office work, it’s fair to say you should at least look into it for your business. After all, saving money, improving productivity, and contributing to employee work-life balance sounds pretty good to us.

In fact, the entire Tech.co team subscribes to the company’s hybrid work model, allowing us to flexibly work where we need to, while occasionally coming into the office. We’ve had great success facilitating work relationships, hitting productivity goals, and generally knocking it out of the park when it comes to remote work.

However, remote work won’t just immediately improve productivity overnight. We followed remote work best practices to ensure that remote employees felt like part of the team. That’s why we’d recommend taking note of these three strategies for increasing work from home productivity in your team.

Check in regularly

When employees work in the office, it’s easy to stop by and learn about what they’re doing, both in the office and at home. However, when employees work remotely, it can be hard to know exactly what’s going on with them, which is why we recommend checking in regularly to ensure that they don’t feel like they’re left out in the cold.

According to one study, remote workers have a tendency to feel left out compared to their in-office counterparts, while 46% believe that a good manager checks in frequently and regularly with remote employees. Simply put, you need to pay attention to your remote employees to get the desired productivity out of them.

Celebrate achievements

Everyone loves to feel like they’ve done a good job, and it’s easy to celebrate achievements when you’re in the office. In fact, 37% of workers think the biggest driver for great work is recognition , which means you need to prioritize this kind of action when it comes to remote workers.

Whether it be a simply shoutout system on Slack or a full-on reward system for those that go above and beyond, making remote workers feel appreciated for their work can go a long way in encouraging productivity across your business.

Use the right tools

In the modern age, it’s fair to assume that the majority of your business’ operations have been digitized in one way or another. Fortunately, this can make transitioning to a hybrid or remote work model easier, allowing those at home to access important data anywhere.

However, from a functionality standpoint, you’re going to need more than Google Docs and a good attitude to encourage productivity from remote workers. Tools like VoIP phones   and web conferencing platforms can make staying in touch with remote workers easy, while still allowing for flexible schedules. Big teams, such as ones working in call centers, will have different priorities than smaller teams working in offices.

Additionally, remote work comes with a lot of security issues that will need to be addressed before kicking off. Security breaches and ransomware attacks are far more viable when attacking those who are working outside of your direct system, which is where tools like VPNs , password managers , and antivirus software can help you nip those problems in the bud before your hybrid work model gets started.

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Research: The Growing Inequality of Who Gets to Work from Home

• Peter John Lambert,
• Nicholas Bloom,
• Steven Davis,
• Stephen Hansen,
• Yabra Muvdi,
• Raffaella Sadun,
• Bledi Taska

An analysis of online job postings found that remote-work opportunities increasingly skew toward the highly paid and highly educated.

There is a large and growing divide in terms of who gets to work from home. Research on job postings found that remote work is far more common for higher paid roles, for roles that require more experience, for full-time work, and for roles that require more education. Managers should be aware of this divide, as it has the potential to create toxic dynamics within teams and to sap morale.

Remote work has exploded since the pandemic struck, and employees like it. In speaking to hundreds of managers about this development, one concern crops up again and again: The shift to remote work is highly unequal. Front-line staff with modest paychecks rarely enjoy the benefits of working from home. Instead, they commute every workday to engage customers and coworkers, operate machinery, and look after facilities. In contrast, highly paid professionals and managers often work from home two or three days a week — saving time, money, and aggravation. Business leaders rightly worry that this divide could hurt morale among front-line staff, undermine perceived fairness, and create new rifts in the workforce.

• PL Peter John Lambert is a Ph.D candidate at the London School of Economics.
• Nicholas Bloom is a professor of economics at Stanford University.
• SD Steven Davis is a senior fellow at the Hoover Institution.
• SH Stephen Hansen is a professor of economics at University College London.
• YM Yabra Muvdi is a Ph.D. student at ETH Zürich’s Law, Economics, and Data Science Group.
• Raffaella Sadun is the Charles E. Wilson Professor of Business Administration at Harvard Business School and a co-chair of its Managing the Future of Work project.
• BT Bledi Taska is an economist at SkyHive.

Partner Center

Does Working from Home Work? Evidence from a Chinese Experiment

About 10% of US employees now regularly work from home (WFH), but there are concerns this can lead to "shirking from home." We report the results of a WFH experiment at CTrip, a 16,000- employee, NASDAQ-listed Chinese travel agency. Call center employees who volunteered to WFH were randomly assigned to work from home or in the office for 9 months. Home working led to a 13% performance increase, of which about 9% was from working more minutes per shift (fewer breaks and sick-days) and 4% from more calls per minute (attributed to a quieter working environment). Home workers also reported improved work satisfaction and experienced less turnover, but their promotion rate conditional on performance fell. Due to the success of the experiment, CTrip rolled-out the option to WFH to the whole firm and allowed the experimental employees to re-select between the home or office. Interestingly, over half of them switched, which led to the gains from WFH almost doubling to 22%. This highlights the benefits of learning and selection effects when adopting modern management practices like WFH.

We wish to thank Jennifer Cao, Mimi Qi and Maria Sun from Ctrip and Ran Abramitzky, Mirko Draca, Itay Saporta, Stephen Terry, John Van Reenen and Edison Yu from Stanford for their help and advice in this research project. We thank Chris Palauni for organizing our trip to JetBlue, and David Butler, Jared Fletcher and Michelle Rowan for their time discussing the call-center and home-working industries. We thank in particular our discussants Mushfiq Mobarak, Rachael Heath, Sabrina Pabilonia, Shing-Yi Wang and seminar audiences at the AEA, Brown, CEPR, Columbia, CORE, Erasmus University Rotterdam, the London School of Economics, Harvard, MIT, the NBER, Stanford GSB, Texas A&M, and the World Bank for comments. We wish to thank Stanford Economics, Stanford GSB and the Toulouse Network for Information Technology (which is supported by Microsoft) for funding for this project. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. To note: James Liang is the current CEO of CTrip.

No funding was received from CTrip. James Liang is the co-founder, former CEO and current Chairman of CTrip. No other co-author has any financial relationship (or received any funding) from CTrip. The results or paper were not pre-screened by anyone.

MARC RIS BibTeΧ

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Non-Technical Summaries

• Evidence from a Chinese Experiment on Working from Home Author(s): Nicholas Bloom James Liang John Roberts Zhichun Jenny Ying Home workers increased the minutes they worked on each shift by 9.2 percent. CTrip is China's largest travel agency, with 16,000...

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