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Achieving Effective Remote Working During the COVID‐19 Pandemic: A Work Design Perspective

1 Shanghai University, Shanghai China

2 Curtin University, Perth Western Australia, 6000 Australia

3 Beijing Normal University, Beijing 100875 China

Sharon K. Parker

Associated data.

Existing knowledge on remote working can be questioned in an extraordinary pandemic context. We conducted a mixed‐methods investigation to explore the challenges experienced by remote workers at this time, as well as what virtual work characteristics and individual differences affect these challenges. In Study 1, from semi‐structured interviews with Chinese employees working from home in the early days of the pandemic, we identified four key remote work challenges (work‐home interference, ineffective communication, procrastination, and loneliness), as well as four virtual work characteristics that affected the experience of these challenges (social support, job autonomy, monitoring, and workload) and one key individual difference factor (workers’ self‐discipline). In Study 2, using survey data from 522 employees working at home during the pandemic, we found that virtual work characteristics linked to worker's performance and well‐being via the experienced challenges. Specifically, social support was positively correlated with lower levels of all remote working challenges; job autonomy negatively related to loneliness; workload and monitoring both linked to higher work‐home interference; and workload additionally linked to lower procrastination. Self‐discipline was a significant moderator of several of these relationships. We discuss the implications of our research for the pandemic and beyond.

INTRODUCTION

As information and communication technologies (ICTs) have advanced in their capabilities, and especially with the greater availability of high‐speed internet, remote working (also referred to as teleworking, telecommuting, distributed work, or flexible work arrangements; Allen et al., 2015 ) has grown in its use as a new mode of work in the past several decades. Remote working is defined as “a flexible work arrangement whereby workers work in locations, remote from their central offices or production facilities, the worker has no personal contact with co‐workers there, but is able to communicate with them using technology” (Di Martino & Wirth, 1990 , p. 530).

However, prior to the pandemic, remote working was not a widely used practice (Kossek & Lautsch, 2018 ). Although the recent American Community Survey (2017) showed that the number of US employees who worked from home at least half of the time grew from 1.8 million in 2005 to 3.9 million in 2017, remote working at that time was just 2.9 percent of the total US workforce. Even in Europe, only around 2 percent of employees teleworked mainly from home in 2015 (Eurofound, 2017 ). Remote working has, in fact, been a “luxury for the relatively affluent” (Desilver, 2020 ), such as higher‐income earners (e.g., over 75% of employees who work from home have an annual earning above $65,000) and white‐collar workers (e.g., over 40% of teleworkers are executives, managers, or professionals).

Because of this situation, prior to COVID‐19, most workers had little remote working experience; nor were they or their organizations prepared for supporting this practice. Now, the unprecedented outbreak of the COVID‐19 pandemic in 2020 has required millions of people across the world into being remote workers, inadvertently leading to a de facto global experiment of remote working (Kniffin et al., 2020 ). Remote working has become the “new normal,” almost overnight.

As management scholars, we might assume that we already have a sufficient evidence base to understand the psychological challenges or risks that remote workers are facing during the pandemic, given the large body of research on remote working (e.g., Grant et al., 2013 ; Konradt et al., 2003 ). However, due to the fact that almost none of those studies was conducted at a time when remote working was practiced at such an unprecedented scale as it has been during the pandemic, coupled with unique demands at this time, some of the previously accumulated knowledge on remote working might lack contextual relevance in the current COVID‐19 crisis. At the least, we need to investigate how this context has shaped the experience of working remotely.

More specifically, existing knowledge on remote working has mostly been generated from a context in which remote working was only occasionally or infrequently practiced, and was only considered by some, but not all or most, of the workers within an organization. As criticized in Bailey and Kurland ( 2002 ), “[the] occasional, infrequent manner in which telework is practiced, likely has rendered mute many suspected individual‐level outcomes for the bulk of the teleworking population” (p. 396). In other words, there might be large differences in individual outcomes between those who do remote work extensively and those who do it infrequently, which likely affects the outcomes of this practice. In addition, because of the largely voluntary nature of prior remote working, in which people choose to work remotely at their own discretion, some of the previous findings on remote working have suffered from a selection bias (Lapierre et al., 2016 ). As such, the previously identified benefits of remote working might only, or especially, be true for those who are interested in, or able to engage in, remote working (Kaduk et al., 2019 ). In an unusual situation when remote working is no longer a discretionary option but rather a compulsory requirement or a mandatory order, there is a need to shift the research focus from understanding whether or not to implement remote working to understanding how to get the most out of remote working . Such a shift of research focus essentially requires a systematic understanding of the potential changed nature of the work itself in the different context.

For this endeavor, we draw on the theoretical perspective of work design. Work design refers to the content and organization of work tasks , activities , relationships , and responsibilities (Parker, 2014 ). Indeed, the concept of work design encompasses the notion of remote work (since working virtually represents a different “organization” of one's tasks compared to working in the office), and has been argued to be relevant to other contemporary work changes, such as the current digital era (e.g., Bélanger et al., 2013 ; Parker & Grote, 2020 ; Wang et al., 2020 ). Research from diverse theoretical perspectives on work design has generally converged to suggest that when work is designed in such a way as to result in particular “work characteristics,” then it will also generate well‐being, job satisfaction, performance, and other such positive outcomes. For example, a meta‐analysis by Humphrey et al. ( 2007 ) identified a range of motivational, knowledge, social, and physical work characteristics as predicting desirable employee outcomes (e.g., better performance and well‐being, positive psychological states, job satisfaction, etc.).

Applying the work design perspective to our investigation on the remote working practice during the pandemic, we expect to observe a powerful role of virtual work characteristics (i.e., work characteristics of one's remote work) in shaping working experiences. In the following sections, we briefly review existing knowledge about work design in the remote working literature and argue why exploratory research is required in the COVID‐19 context. We then present our mixed‐methods research to explore how virtual work characteristics shape working experiences in the unique context wrought by the pandemic. Finally, we discuss the theoretical and practical implications of our research beyond the context of the COVID‐19 pandemic.

WORK DESIGN AND REMOTE WORKING: AN OVERVIEW OF THE LITERATURE

Work design is one of the most influential theoretical perspectives in existing remote working literature. As shown in Table ​ Table1, 1 , based on a literature review, we identified three different types of positioning of work design in the existing literature, or three approaches.

Different Types of Positioning of Work Characteristics in the Remote Working Literature

In the first approach, remote working (i.e., remote working intensity and whether taking up this policy or not) is an independent variable that predicts remote worker outcomes, with perceived work characteristics as a moderator. For example, Golden and Gajendran ( 2019 ) found that the positive relationship between remote working intensity and job performance was stronger for employees low in social support at work. A second approach regards work characteristics as mediating between remote working as the independent variable and employee outcomes as the dependent variables, thus considering how engaging in remote working affects individuals through shaping the perceived nature of their work. Still taking relational aspects of work as an example, Vander Elst et al.’s ( 2017 ) study revealed that the extent of remote working negatively related to perceived social support, which in turn led to more emotional exhaustion. Both approaches regard one's work as a whole that encompasses both remote and non‐remote components, with the independent variable capturing the extent of each aspect. In contrast, in a third approach, the focus is on just the experience of remote work. Scholars in this stream of literature are interested in how virtual work characteristics shape work experiences within the context of remote work. Received social support during the period of working away from office, for instance, can help remote workers to overcome social isolation (Bentley et al., 2016 ).

These three approaches have different assumptions and serve to address distinct research questions. In what follows, we discuss each of the three approaches in more detail.

Approach 1: Work Characteristics as Moderating the Effect of Remote Work on Outcomes

In this approach, remote working intensity is the independent variable that affects individual outcomes, and (other) work characteristics are identified as moderators. This approach lends itself to identifying what sort of work is most suited to remote working. Thus, as Golden and Veiga ( 2005 ) stated, “whether individuals can fully benefit from telecommuting is likely to be influenced by the way in which they must perform their work activities” (p. 303). Building upon the premise that remote working policy is only suitable for certain types of jobs (Pinsonneault & Boisvert, 2001 ), this approach considers employees’ work characteristics as boundary conditions to reconcile the mixed impacts of engaging in remote working. The key implication from these studies is that managers should provide remote working for appropriate jobs and workers (Golden & Veiga, 2005 ).

Golden and colleagues have conducted several studies to support this argument. Taking their classical study as an example, based on a sample of 273 telecommuters and their supervisors, Golden and Gajendran ( 2019 ) found that the positive relationship between the extent of remote working (i.e., the percentage of time spent on remote working per week) and supervisor‐rated job performance was more pronounced for those working in complex jobs, those with lower task interdependence, and those receiving lower social support. Similar studies have shown that the impact of remote working on well‐being also depends on other work characteristics, including task interdependence and job autonomy (e.g., Golden & Veiga, 2005 ; Golden et al., 2006 ; Perry et al., 2018 ).

Approach 2: Work Characteristics as Mediating the Effect of Remote Work on Outcomes

The first approach builds on the assumption that the nature of the work will not be influenced by remote working practices and, therefore, one's work characteristics could be considered as criteria that managers use to design remote working policy. The second approach, in contrast, argues that—as most tasks, communications, and interpersonal collaborations are mediated by ICTs in remote working—how an individual experiences his/her work design (or one's work characteristics) is changed by taking up flexible working policy.

Specifically, engaging in remote work practices can significantly change job demands, autonomy, and relational aspects of work, which in turn influence employee outcomes. In Kelliher and Anderson’s ( 2010 ) qualitative study, most remote workers experienced work intensification, because they can stay away from interruptions in the office and work more intensely. A considerable number of studies have found positive impacts of remote working on autonomy (e.g., Gajendran et al., 2015 ; Ter Hoeven & Van Zoonen, 2015 ). Gajendran and Harrison’s ( 2007 ) meta‐analysis also supported the beneficial effect of remote working on perceived autonomy, which in turn was associated with desirable individual outcomes (e.g., task performance and job satisfaction). Finally, studies suggest that remote working is usually detrimental for the relational aspects of work. Based on 93 interviews, Cooper and Kurland’s ( 2002 ) qualitative study revealed that telecommuters experienced more professional isolation when they missed opportunities to engage in developmental activities at work.

Approach 3: Work Characteristics as Antecedents in the Context of Remote Work

The meaning of work design in the third approach is different from its counterparts in the first two approaches, because it particularly refers to characteristics of one's remote work (i.e., what does one's work look like during home office days). This stream of literature derives from the socio‐technical systems perspective (Trist, 1981 ; Trist & Bamforth, 1951 ), which regards remote work as a context rather than an independent variable, arguing that characteristics of remote work should fit the new way of working to achieve better performance and well‐being (Bélanger et al., 2013 ). Unintended outcomes might arise when virtual work characteristics fail to meet individual and/or task requirements. Work‐to‐family conflicts, for example, could occur where there are intolerable job demands and limited autonomy for remote workers during home days.

Overall, however, few studies have adopted this third approach. Existing research has mainly focused on impacts of virtual work characteristics on well‐being. For example, in one study, workplace support for teleworkers was positively associated with job satisfaction (Baker et al., 2006 ). Bentley et al. ( 2016 ) also found indirect effects of social support from supervisors and the organization on psychological strain and job satisfaction via reducing social isolation in remote working practices. In addition to social support, research has shown that perceived control over the location, timing, and process of work was negatively related to teleworkers’ work‐family conflict and turnover intentions (Kossek, Lautsch, & Eaton, 2009 ), and task‐related demands (e.g., time pressure and uncertainty) were positively associated with teleworkers’ experienced stress (Turetken et al., 2011 ).

Summary and the Current Research

The first two approaches have provided valuable evidence to evaluate and design remote working policy prior to the pandemic. For example, one crucial implication from those studies is that managers should provide such a policy to appropriate people and appropriate jobs. However, remote working was no longer optional during the pandemic; instead, the COVID‐19 outbreak has forced people to be working from home irrespective of their preferences, abilities, and the nature of their jobs. In other words, during the pandemic remote working has become a “new normal,” or a new context, rendering the third approach to be of high importance.

The advantage of this third approach is that it frames remote working as a context/setting (Bailey & Kurland, 2002 ), and focuses on the relationship between virtual work characteristics and working experiences. This approach has important theoretical and practical implications, and it is especially valuable for understanding remote working experiences in the COVID‐19 context.

From the theoretical standpoint, the effects of work characteristics vary with contexts (Morganson, Major, Oborn, Verive, & Heelan, 2010 ). Johns ( 2006 ) pointed out that context is “a shaper of meaning.” For example, people tend to evaluate their achievements more negatively when in a generally superior group versus in a generally inferior group (i.e., the frog pond effect). Similarly, the meaning of some work characteristics may have been shaped by the unique pandemic context. For instance, being socially connected with colleagues may have different meanings during the COVID‐19 lockdown, in which most social gatherings are not allowed, as opposed to being connected in the “normal” workplace. Potentially, even limited social support can have strong positive spillover effects when social resources people pursue are hard to obtain. Kawohl and Nordt ( 2020 ), for example, suggested that social support plays a crucial role in suicide prevention during the COVID‐19 outbreak. Moreover, in contrast to the scarcity of social resources, job autonomy is usually relatively high in the current context. According to Warr’s ( 1994 ) vitamin model, however, negative effects may result from too much of a good thing. Workers with higher autonomy might potentially be distracted by their family issues and unable to concentrate on their work at home. In sum, given the uniqueness and novelty of the pandemic, we should explore and examine the work design theory in the current extreme context, including what virtual work characteristics really matter and how they matter ( that is , which challenges do they help address ).

From the practical standpoint, existing studies from approaches 1 and 2 built on the premise that remote working is optional and aimed to identify which types of jobs and people are suitable for remote working. However, people were required to work from home due to the COVID‐19 outbreak. Some scholars even believe that the pandemic will make some jobs permanently remote (Sytch & Greer, 2020 ). Thus, it is also practically important and necessary to explore how to get the most out of remote working. The third approach, focusing on the role of virtual work characteristic and its associated outcomes, can provide valuable evidence for managers to boost employees’ productivity and well‐being via re‐designing remote work appropriately.

Accordingly, we adopted the third approach and conducted mixed‐methods research to explore how virtual work characteristics shape remote working experiences . Specifically, in Study 1 (a qualitative explorative study), we—based on interviews with 39 participants who worked from home during the pandemic—developed a theoretical framework to integrate the relationships among virtual work characteristics, remote work challenges, and individual outcomes. In Study 2, a cross‐sectional online survey study, we collected data from 522 employees having remote working experiences during the COVID‐19 pandemic to quantitatively examine the identified links.

STUDY 1: A QUALITATIVE EXPLORATIVE STUDY

To build the theoretical foundation of the current research, we adopted a grounded theory approach to capture remote workers’ first‐hand accounts of their experiences and challenges while they were working from home during the COVID‐19 outbreak.

Study 1 Method and Procedure

In mid‐February 2020, a significant proportion of workers across the major cities in mainland China were forced to work from home. As soon as we obtained ethics approval for our research, we recruited remote workers for interviews through social media (e.g., WeChat, QQ, etc.). We recruited 39 full‐time employees (15 of them were from Beijing) who were required by their organizations to work from home until further notice. The first author and two research assistants conducted semi‐structured interviews with each of the participants in Chinese using audio calls or video calls, which were recorded and then transcribed. Data collection was completed when we reached theoretical saturation; that is, we were not able to identify a new category/theme from the interviews (Strauss & Corbin, 1998 ).

Participants were employed in a wide range of industries (e.g., education, IT, media, finance, etc.) and occupations (e.g., managers, teachers, designers, etc.). They had an average age of 32.62 years ( SD = 9.43) and 23 of them were women; 15 of them were married and 18 of them had caring responsibilities. Participants worked 7.27 hours per day on average ( SD = 2.39) and by the time they were interviewed they had worked from home for an average of 20.41 days ( SD = 10.45). Notably, flexible work arrangements such as remote working are relatively new in China. In 2018, only 0.6 percent of the workforce (4.9 million Chinese employees) had remote working experiences. Most Chinese workers in our sample worked away from the office for the first time during the COVID‐19 situation. In our study, only one participant (#4) was an experienced remote worker.

Participants were asked to generally describe their working experiences (i.e., work performance and well‐being) during the period of working from home. As participants might narrowly focus on specific aspects of remote working experiences, we generated a list of questions before we conducted the interviews (for these questions, see Appendix A ), which helped us to get a comprehensive understanding of this phenomenon. Participants were then asked to indicate potential factors that shaped their work performance and well‐being during this period. On average, an interview lasted for 15.62 minutes (ranging from 10 to 42 minutes; SD = 7.11).

Study 1 Data Analysis

Following previous recommendations for coding qualitative data (Creswell, 2003 ), it is necessary for researchers to deeply immerse themselves in the research context. The first author had worked remotely in his hometown located in southern China for 3 weeks during the COVID‐19 outbreak. Thus, he was knowledgeable regarding remote working experiences in China and the COVID‐19 context.

We followed a three‐step approach in analyzing the qualitative data. The first author conducted open coding to analyze the raw interview data. With the first interview, he conducted open coding by going through the interview transcript line by line. He particularly focused on participants’ narratives (i.e., words, sentences, or paragraphs) about factors that were influencing their work performance and well‐being. In vivo codes (i.e., words, sentences, or paragraphs in participant's language) were identified in this step. Second, we considered the shared properties/dimensions among first‐order in vivo codes and then grouped similar first‐order codes into a more abstract second‐order category. Codes and categories emerging from the first interview were used to analyze the next interview transcript; newly identified codes in turn can help to refine, elaborate, and develop existing concepts and interrelationships. After coding all 39 interviews, we unified second‐order categories around central phenomena based on work design theories (e.g., job demands‐resources model, Demerouti et al., 2001 ) and existing literature on remote working (e.g., Allen et al., 2015 ). Throughout this process, co‐authors assessed the categories and themes identified by the first author. Conflicts were resolved through discussion.

Study 1 Findings

Table ​ Table1 1 provides representative first‐order in vivo codes, second‐order categories, and shows the three aggregated main themes that we identified from the categories. We identified that remote work challenges (theme 1), virtual work characteristics (theme 2), and individual factors (theme 3) were crucial for remote workers’ performance and well‐being during the pandemic (Table ​ (Table2 2 ).

Themes and Codes Identified from Study 1 Interviews

Theme 1: Remote Work Challenges

Remote work challenges reflect workers’ immediate psychological experiences in accomplishing tasks, interpersonal collaborations, and social interactions with family and friends. We identified four key challenges in the remote work context during the pandemic, namely procrastination, ineffective communication, work‐home interference, and loneliness. Generally, those four challenges exerted detrimental impacts on individuals’ work effectiveness and well‐being.

Work‐Home Interference

Most participants (26 out of 39) mentioned that they were struggling with home ‐ to ‐ work interference (HWI) and work ‐ to ‐ home interference (WHI). First, working at home means more interruptions from family, which may negatively influence work effectiveness. Notably, schools in China had been shut down during the COVID‐19 outbreak; working parents, therefore, faced a bigger challenge in balancing work and family roles. In addition, individuals’ work invaded their life domains during the period of working from home. These interferences from work domains could make people feel exhausted. A project manager (#23) shared her experience of being “always online”: “I’m basically always online…my supervisors and colleagues may come to me whenever they need something from me, and you have to give immediate response.” The need to be always online affected this project manager's ability to meet her family obligations.

Ineffective Communication

Remote workers rely heavily on ICTs to communicate and collaborate with colleagues, supervisors, and clients. Especially during the pandemic, ICT‐mediated communications almost become the only option because workers were not able to engage in face‐to‐face meetings. Twenty‐one participants identified that they suffered from low productivity caused by poor communications during this period. For example, a manager (#32) described experiencing lower efficiency in ICT‐mediated communications: “I feel that online communication is not as efficient as face‐to‐face communications in the office. [Online] communication has a time cost.”

Procrastination

Procrastination, defined as the irrational delay of behavior (Steel, 2007 ), is one of the biggest productivity killers at work. Procrastination is common in the office‐based workplace (Kühnel et al., 2016 ) and it can become even worse when people work from home. Although most participants were committed to working productively as usual, they sometimes were struggling with self‐regulation failure. Fourteen participants indicated procrastination as a challenge whilst working from home. We found that these participants delayed working on their core tasks via spending time on non‐work‐related activities during working hours, such as using social media and having long breaks (#1).

Remote working means fewer face‐to‐face interactions with colleagues and supervisors. Given the restrictions on non‐essential social gatherings during the pandemic, people also lost social opportunities to meet their friends or colleagues, which inevitably contributed to the feeling of loneliness. Ten participants indicated loneliness as a challenge. For instance, participant #4 suggested that though individuals can connect with colleagues via ICTs, conversations with colleagues were more task‐focused, which could not meet her psychological needs for belongingness or relatedness.

Theme 2: Virtual Work Characteristics

Virtual work characteristics reflect the nature or quality of the worker's job during the period of working from home. We identified four crucial virtual work characteristics: social support, job autonomy, monitoring, and workload. Our participants suggested that virtual work characteristics usually influenced their work effectiveness and well‐being in an indirect manner, that is, via shaping their experienced challenges in remote working.

Job Autonomy

Thirteen participants suggested the role of job autonomy in remote working. Job autonomy means employees can decide when and how to accomplish their tasks. Individuals’ performance and well‐being benefit from job autonomy, as those with higher job autonomy can balance work and rest and choose the most productive ways to do their work. Job autonomy was also identified as beneficial for work‐family balance. For example, participant 14 stated: “I can control the rhythms of work and rest. If it is not during the meeting, I can have a short break, around ten to thirty minutes, and then continue to work. That also means more time to spend time with my family.”

Monitoring in remote work has rarely been discussed (Lautsch et al., 2009 ). Ten participants reported that they experienced different forms of monitoring from their supervisors, including daily reports, clocking in/out via applications such as DingTalk, and being required to have a camera on whilst working. In the current sample, most comments about monitoring were positive. Some participants reported that monitoring can help them to cope with procrastination and to concentrate on their core tasks. A business analyst (#1), for instance, described his experiences of extra morning meetings, which was previously not a routine activity in the office: “After this morning meeting, you will feel a sense of ritual and you will devote yourself to work.”

Ten participants mentioned workload during remote working. Participants indicated that workload influenced their work‐home balance. Participant #39 complained about heavy workload during this period: “I don't think remote working can give me more personal time; instead, I feel that remote work increases my working time.” Workload also relates to procrastination. Participant 3 noted that low workload means more opportunities to procrastinate. Also suggesting a link between workload and focus, a top‐level manager (#36) who had to deal with lots of urgent business caused by COVID‐19 stated: “I cannot stop even if I wanted to.”

Social Support

Seven participants mentioned social support in remote working, and they indicated social support as necessary job resources to accomplish tasks during the period of working from home. More importantly, social support is conducive to overcome loneliness. Participants whose organization provided online platforms to boost social interactions among workers usually reported less loneliness. For instance, participant 2 stated: “We discussed about work on enterprise social media [DingTalk] and chatted in WeChat. I do not feel isolated.”

Theme 3: Individual Factors (Personal Traits)

Although we were primarily interested in how virtual work characteristics shape remote working experiences, one powerful individual factor (or personal trait) emerged from the interview data—self‐discipline. Twelve participants highlighted the importance of this aspect. Participants who indicated they were less disciplined reported experiencing more self‐control failures, such as procrastination (#9) and cyberloafing (#4), making them less productive in remote working. Those participants who identified themselves as more disciplined, in contrast, reported that they completed their work in a more efficient and timely manner (#2). Participant #36 also emphasized the benefit of self‐discipline for work‐family balance.

Interestingly, disciplined and less‐disciplined people evaluated the impact of some aspects of work design differently. Notably, monitoring was mentioned as particularly useful for less‐disciplined workers. As participant #18 mentioned: “I’m not a self‐disciplined person. If there is no external pressure [monitoring], I will be very indolent.”

Study 1 Summary and Discussion

Findings generated from the interview study reveal that a set of challenges in remote working during the pandemic negatively affect individuals’ work effectiveness and well‐being. In addition, virtual work characteristics and self‐discipline jointly shape the extent of these experienced challenges. We recognize that many of the work characteristics that we identified are important and indeed overlap to some extent with prior research on flexible working. However, this was in part the point: to explore whether this would be so, and to assess the applicability of work design theory, in the very different context of the pandemic.

Crucially, we also identified some unique findings. First, existing studies have showed that taking up remote working policy can reduce work‐family conflict (e.g., Allen et al., 2015 ; Gajendran & Harrison, 2007 ). However, this conclusion is challenged by our findings, that is, work‐home interference was the most‐mentioned challenge in remote working during the pandemic for this sample. In addition, previous research suggested that extra monitoring would be harmful for remote workers (Lautsch et al., 2009 ). That might be possible because flexible working arrangement is only made available for the “right” workers (e.g., disciplined people), and they can work productively in their home offices even without supervisory controls. However, in the interview study, we found that remote workers (at least in our sample) believed monitoring was necessary for coping with procrastination, which is different from results that were identified in the pre‐pandemic context.

Based on the work design perspective, we now integrate the above findings into a theoretical model to explain how virtual work characteristics matter in the current remote work context (see Figure ​ Figure1 1 ).

Theoretical framework identified from Study 1. Note . Although we did not analyze the relationship between the four virtual work characteristics and the challenge of ineffective communication in Study 1, we still include it in our framework because this challenge might be influenced by other virtual work characteristics such as technical support, task interdependence, and task complexity (e.g., Bélanger et al., 2013 ; Marlow et al., 2017 ).

Building upon our interviews, in conjunction with work design theories (e.g., Demerouti et al., 2001 ), we expect that social support will be a key work characteristic in this unique COVID‐19 context. Though some scholars have raised concern about the loss of social connections in remote work practices (e.g., Olszewski & Mokhtarian, 1994 ), the social distancing policy limited employees’ opportunities to obtain social resources, rendering social support from work of ever increasing importance. Individuals who receive considerable social support at work will suffer less from loneliness, because social support can bring desirable online social interactions to meet their needs for belonging (Bavik et al., 2020 ). In addition, social support also can provide necessary emotional and instrumental resources for people to handle challenges in interactions with their family (e.g., Kossek et al., 2011 ). Therefore, people with higher social support will experience less work‐home conflict.

We also propose that social support from work can help to reduce procrastination. Individuals sometimes procrastinate for a relief from stress (Lavoie & Pychyl, 2001 ; Wan et al., 2014 ). Social support is particularly important in this extraordinary context, because it can act as a “negativity buffer” (Bavik, Shaw, & Wang, 2020 ), helping workers cope with stress and focus on tasks. Moreover, previous research has shown that social support can lead to more commitment to the organization (Rousseau & Aubé, 2010 ). Thus, employees with higher social support tend to repay their organizations by concentrating more on their work (i.e., showing less procrastination) (Buunk et al., 1993 ). Altogether, we propose that:

Proposition 1: Employees who receive more social support from work will experience less procrastination, work‐home interference, and loneliness during the period of working from home, and, therefore, will report higher levels of performance and well‐being.

Autonomy is another important job resource in the remote work context. During home office days, individuals usually experience frequent role transitions (both work‐to‐home and home‐to‐work transitions), making the challenge of work‐home interference become more pronounced (Delanoeije et al., 2019 ). As participants stated, workflows during the regular working hours were frequently interrupted by demands from the family domain (e.g., taking care of children). In addition, some people were also expected to be “always online,” resulting in intrusions of unintended tasks or communications after hours (e.g., responding to client or supervisor needs). Job autonomy allows employees to decide when and how to accomplish their tasks. Thus, employees high on job autonomy can more effectively balance different responsibilities or demands across domains. Accordingly, we argue that:

Proposition 2: Employees with higher levels of job autonomy will experience less work‐home interference during the period of working from home, and, therefore, will have higher levels of performance and well‐being.

Based on our qualitative analyses, we argue that two demands—workload and monitoring—exert mixed effects on individuals. On the bright side, workload and monitoring can reduce workers’ procrastination. As summarized in Steel’s ( 2007 ) review, the timing of rewards and punishments predicts procrastination. Individuals are more likely to procrastinate if they can obtain immediate rewards with delayed punishments. In contrast, procrastination diminishes as punishments approached (e.g., deadline). Workload and monitoring are expected to decrease procrastination, because punishments would approach immediately if people cannot accomplish tasks in time or are found to be spending time on non‐work‐related issues at work.

On the negative side, workload and monitoring, acting as job demands, can easily invade individuals’ personal lives during home office days (Kossek et al., 2006 ; Lautsch et al., 2009 ). In other words, work‐related demands caused by workload and monitoring will hinder employees to fulfill their family responsibilities, which in turn eventually hurt their well‐being (Grant‐Vallone & Donaldson, 2001 ). Consequently, we propose that:

Proposition 3: (a) Employees with higher workload and those who are under more intensive monitoring will experience less procrastination during the period of working from home and, therefore, will have higher levels of performance; but (b) these employees will experience more work‐to‐home interference and, therefore, will have lower levels of well‐being.

We also propose that virtual work characteristics might not hold the same value for everyone. Specially, the effects of social support, monitoring, and workload on procrastination will be more significant for less‐disciplined individuals. That is because less‐disciplined people need external driving forces to “push” them (Steel, 2007 ). For people lacking discipline, social support can provide the psychological resources for self‐regulation (Pilcher & Bryant, 2016 ). Workload and monitoring, moreover, will increase the costs of procrastination, which motivate them to concentrate on their tasks to avoid potential punishments (Steel, 2007 ). In contrast, disciplined individuals can more effectively control their own behaviors and may not necessarily rely on external forces.

Proposition 4: The effects of social support, monitoring, and workload on procrastination will be stronger for less‐disciplined employees.

In the work place, informal interactions can simply “happen”; the so‐called “water cooler” effect (Fayard & Weeks, 2007 ). However, such interactions need to be more deliberately orchestrated when working from home. Individuals need to actively participate in such interactions, either by initiating them, or by consciously joining in to such an activity arranged by someone else. Given the unique nature of the social support in this context, we suspect that people need self‐discipline to utilize the social resources from work to reduce loneliness. That is, individuals low in self‐discipline are likely to be distracted by various temptations in cyberspace (O’Neill et al., 2014 ), and fail to consciously or proactively orchestrate and engage in informal communication activities. Hence, we propose that:

Proposition 5: The effects of social support on loneliness will be stronger for disciplined employees.

STUDY 2: AN EMPIRICAL STUDY

Study 2 sample and procedure.

We recruited participants via www.wjx.cn , a Chinese online data collection platform that is similar to Amazon Mechanical Turk (MTurk) and Prolific Academic. It has been widely used in previous studies conducted in the Chinese context (e.g., Buchtel et al., 2015 ; Lu et al., 2020 ). WJX has a large participant pool with 2.6 million participants from China, which allowed us to recruit niche samples on demand. We recruited participants who were working from home or had recently come back to the normal office‐based workplace after a period of working from home during the COVID‐19 outbreak. Like the pricing policy of Prolific Academic, monetary compensation was calculated by WJX based on the sample size, the length of the survey, and screening conditions. Following the quote from WJX, each participant was compensated 15 Chinese yuan (equivalent to about 2.1 US dollars).

Our final sample consisted of 522 participants, with 271 being female (51.9%). Participants were from a wide range of industries including IT (26.6%), education (15.5%), and manufacturing (12.5%). They were employed as managers, teachers, editors, engineers, and so forth. The average age of participants was 31.67 years old ( SD =6.09); 306 participants (58.6%) lived with their children; 161 participants (30.84%) held management positions; participants had worked from home for an average of 21.25 days ( SD =17.25); and they worked 7.02 hours per workday on average ( SD =1.98).

Study 2 Measures

Virtual work characteristics.

We used the four‐item scale adapted from Morgeson and Humphrey ( 2006 ) to measure social support whilst working at home. A sample item is “During the period of working from home, people I worked with were friendly.” Job autonomy was measured using the three‐item scale developed by Hackman and Oldham ( 1980 ), and a sample item is “During the period of working from home, I had considerable autonomy in determining how I did my job.” The average number of their daily working hours during the period of working from home was used as a relatively objective indicator to operationalize workload.

Based on interviews in Study 1, we developed a four‐item checklist to measure employees’ received monitoring during the period of working from home. Our scale covered three frequently mentioned techniques, that is, “providing daily reports,” “clocking in/out via APPs such as DingTalk,” and “keeping cameras switched on during working time”; the fourth item, “other methods to monitor my work performance during the period of working home,” was used to capture other potential techniques. Participants were asked to indicate whether their organizations/managers adopted these techniques to monitor employees’ work performance by checking “Yes” or “No.” The intensity of monitoring was calculated by summing the number of techniques adopted by their organizations/managers.

Self‐Discipline

Self‐discipline was measured by the three‐item scale adapted from Lindner et al. ( 2015 ). A sample item is “I am good at resisting temptation.”

Remote Work Challenges: Work‐Home Interference, Procrastination, Loneliness, and Communication Effectiveness

A six‐item scale developed by Carlson et al. ( 2000 ) was used to measure work‐to‐home interference (WHI; a sample item is “During the period of working from home, my work kept me from my family activities more than I would like”) and home‐to‐work interference (HWI; a sample item is “During the period of working from home, the time I spent on family responsibilities often interfered with my work responsibilities”).

We used the three‐item scale adapted from Tuckman ( 1991 ) to measure procrastination. A sample item is “During the period of working from home, I needlessly delayed finishing jobs, even when they were important.”

Loneliness during the period of working from home was captured by three items from the well‐established UCLA loneliness scale (Russell et al., 1980 ). Items are “I felt close to others” (reverse coded), “I did feel alone,” and “I felt isolated from others.”

Participants were asked to recall their experiences in virtual communications during the period of working from home, and a three‐item scale adapted from Lowry et al. ( 2009 ) was used to measure communication effectiveness. A sample item is “The time spent in virtual communications was efficiently used.”

Remote Worker Outcomes: Self‐Reported Performance and Well‐Being

We used a three‐item scale adapted from Williams and Anderson ( 1991 ) to measure task performance in remote working. A sample item is “During the period of working from home, I adequately completed my assigned duties.”

We also focused on two main well‐being outcomes, that is, emotional exhaustion and life satisfaction. Emotional exhaustion was captured by a two‐item scale adapted from Maslach and Jackson ( 1981 ). A sample item is “During the period of working from home, I felt emotionally drained from my work.” Life satisfaction was measured by a three‐item scale adapted from Diener et al. ( 1985 ). A sample item is “During the period of working from home, I was satisfied with my life.”

Previous studies have shown that age, gender, caring responsibility, and remote working experience can influence remote workers’ productivity and well‐being (e.g., Gajendran & Harrison, 2007 ; Kossek et al., 2006 ; Martin & MacDonnell, 2012 ). Thus, we controlled for these variables while testing our proposed model. Specifically, gender was coded as a dummy variable (0 = male, 1 = female). Following Kossek et al. ( 2006 ), caring responsibility was coded as a dummy variable (0 = no caring responsibility, 1 = living with children). To assess remote worker experience, we asked participants to report the frequency of working from home before the lockdown with a 5‐point rating scale ranging from 1 = never to 5 = always . Finally, as our study was conducted in the COVID‐19 context, individuals’ psychological experience (e.g., life satisfaction) might be influenced by the pandemic. Hence, the severity of COVID ‐ 19 was controlled. We used the number of confirmed cases in each participant's city to indicate the severity of COVID‐19. To reduce the skewness of the severity distribution, we conducted a natural logarithmic transformation of the number of confirmed cases.

Study 2 Data Analysis

We estimated proposed relationships simultaneously in two path‐analytical models through Mplus 7.4 (Muthén & Muthén, 1998–2015). To examine the mediating effects (Propositions 1–4), we first estimated a path‐analytical model (Model 1) without self‐discipline as a moderator. Specifically, we regressed employee outcomes on all remote working challenges, virtual work characteristics, self‐discipline, and control variables. We also regressed remote working challenges (except for communication effectiveness) on all virtual work characteristics, self‐discipline, and control variables. To further examine the indirect effects of work design and self‐discipline on employees via remote working challenges, we used the Model Constraint command in Mplus to calculate the product of path coefficients a and b . Path coefficient a indicates the effect of the predictor on the mediator, while path coefficient b indicates the effect of the mediator on the outcome.

To examine the moderating effects of self‐discipline (Propositions 4 and 5), we estimated another path‐analytical model (Model 2) based on Model 1. Self‐discipline and virtual work characteristics were mean centered to generate the interaction terms.

We did not model the link between virtual work characteristics and communication effectiveness in the above model for two reasons. First, Study 1 did not suggest such a pathway. Second, even though prior research suggested some aspects of work design might be important for communication quality during remote working, these studies considered different work characteristics. For example, Marlow et al.’s ( 2017 ) theoretical framework suggested that interdependence and task complexity could influence communication in virtual teams; and Bélanger et al. ( 2013 ) found that technical support could shape teleworkers’ communication experiences. Instead, in our study, we controlled for the effects of communication effectiveness on performance and well‐being.

Study 2 Results

Table ​ Table3 3 summarizes the means, standard deviations, reliabilities, and correlations among study variables.

Correlations of Study Variables

N  = 515–522; Gender was coded as a dummy variable (0 = male, 1=female); With children was coded a dummy variable (0 = not, 1 = live with children); Management position was coded as dummy variable (0 = not, 1 = manager); The severity of COVID‐19 was measured by the natural logarithm of confirmed cases in participant's city; WHI =work‐to‐home interference; HWI =home‐to‐work interference.

Virtual Work Characteristics and Remote Working Challenges

The analysis showed that social support was the most powerful work design factor in terms of its breadth of impact. As shown in Table ​ Table4, 4 , social support was negatively associated with procrastination, WHI, HWI, and loneliness. Job autonomy was negatively related to loneliness. Monitoring was positively related to WHI, but the relation between monitoring and procrastination was not significant, in contrast to what we expected from the interviews. The effects of workload on remote work experiences were mixed. Workload was negatively related to procrastination, but it was positively related to WHI.

Path Analysis Results for Testing Main Effects and Mediating Effects (Model 1)

N  = 515. WHI =work‐to‐home interference; HWI =home‐to‐work interference; Standard error is indicated in bracket; Calculations are based on logarithmic values for workload (i.e., working hours).

Remote Working Challenges and Employee Outcomes

As shown in Table ​ Table4, 4 , worker's performance was significantly influenced by procrastination and HWI. Emotional exhaustion was predicted by each remote working challenge, including procrastination, WHI, HWI, and loneliness. Finally, life satisfaction was negatively associated with WHI and loneliness.

Indirect Effects of Virtual Work Characteristics on Employee Outcomes via Remote Work Challenges

We further examined the indirect effects of virtual work characteristics on employee outcomes via remote working challenges using the Model Constraint command in Mplus . As shown in Table ​ Table4, 4 , social support had a positive effect on performance via lower procrastination and HWI; social support had a negative effect on emotional exhaustion via lower procrastination, WHI, and loneliness; and social support had a positive effect on life satisfaction via lower WHI and loneliness. Thus, Proposition 1 was supported. Besides, WHI mediated the indirect effects of monitoring and workload on emotional exhaustion and life satisfaction and, therefore, Proposition 3(b) was supported.

Though Proposition 2 (i.e., job autonomy →work‐home interference →individual outcomes) was not supported, we found that loneliness mediated the indirect effects of job autonomy on emotional exhaustion and life satisfaction. Proposition 3(a) suggested the indirect effects of workload and monitoring on individuals via reducing procrastination, but this proposition was not supported by our data (Table ​ (Table5 5 ).

Indirect Effects of Virtual Work Characteristics on Employee Outcomes via Remote Working Challenges

WHI =work‐to‐home interference; HWI =home‐to‐work interference; Indirect effects in bold were not significant with 95% CI.

Moderating Effects of Self‐Discipline

As shown in Table ​ Table6, 6 , the interaction term of social support and self‐discipline was positively associated with procrastination ( B  = .10, SE = .05, p  < .05). As shown in Figure ​ Figure2, 2 , social support was negatively associated with procrastination when self‐discipline was low (simple slope = −.25, p  < .001) but unrelated to procrastination when self‐discipline was high (simple slope = −.07, ns ). However, self‐discipline cannot moderate the effects of monitoring and workload on procrastination. Thus, Proposition 4 was partially supported.

Path Analysis Results for Testing Moderating Effects (Model 2)

N  = 515. WHI = work‐to‐home interference; HWI = home‐to‐work interference; Standard error is indicated in brackets; Calculations are based on logarithmic values for workload (i.e., working hours).

The moderating role of self‐discipline on the relationship between social support and procrastination.

The relationship between social support and loneliness also depended on the extent of self‐discipline. The interaction term of social support and self‐discipline was negatively related to loneliness ( B  = −.17, SE = .05, p  < .001). As shown in Figure ​ Figure3, 3 , social support was negatively associated with loneliness when self‐discipline was high (simple slope = −.34, p  < .001) but unrelated to loneliness when self‐discipline was low (simple slope = −.06, ns ), indicating that the relationship between social support and loneliness was stronger for self‐disciplined workers. Thus, Proposition 5 was supported.

The moderating role of self‐discipline on the relationship between social support and loneliness.

GENERAL DISCUSSION

The COVID‐19 outbreak has created a unique context in which many employees were involuntarily required to work from home intensively, thus questioning the applicability of existing knowledge on remote working. Consequently, we argued that it is necessary to conduct exploratory research to identify the major challenges remote workers were struggling with in this unique context, and the role of virtual work characteristics in shaping these challenges. We discuss key implications of our findings next.

Work Characteristics as a Vehicle for Improving Remote Workers’ Experiences

Work design is one of the most influential theoretical perspectives in remote working literature. The current research identified that existing research has predominantly regarded remote work as an independent variable (e.g., remote work intensity) and investigated how work characteristics moderate or mediate the effects of remote work on individual outcomes. We argued that these two dominant approaches provide restricted insights for remote working practice during the COVID‐19 outbreak, because theoretical meanings and relationships may have been shaped or changed by the unique context (Johns, 2006). Thus, we advocate that it is theoretically and practically important to regard remote working during the pandemic as a context and explore/examine what virtual work characteristics really matter and how they matter (i.e., Approach 3).

Based on two studies conducted in this unique context, we identified four key remote work challenges (i.e., work‐home interference, ineffective communication, procrastination, and loneliness), as well as four virtual work characteristics that affected the experience of these challenges (i.e., social support, job autonomy, monitoring, and workload) and one key individual difference factor (i.e., workers’ self‐discipline). Generally, our findings are consistent with well‐established work design and remote working literature. Results from our two studies support the argument that virtual work characteristics can be, and are, a powerful vehicle for improving remote workers’ work effectiveness and well‐being. In particular, social support and job autonomy, acting as job resources, help employees to deal with challenges in remote working. Workload and monitoring, however, both functioned as demands, increasing remote workers’ work‐home interference, and thereby undermining employee well‐being.

Importantly, we also identified some findings that appear to be unique to the pandemic context. First, scholars and managers usually believe remote working can provide employees with autonomy to alleviate work‐family conflicts (Gajendran & Harrison, 2007 ). However, our research shows that remote workers were struggling with work‐home interference as a major challenge, and work‐home interference in this context cannot even be mitigated by job autonomy. Besides, procrastination has been framed as a trait‐like variable in remote working literature (Allen et al., 2015 ), and, therefore, managers tend to provide flexible work arrangements for individuals with greater abilities to avoid distractions. Our study shows that procrastination was one of the concrete challenges in remote working; more importantly, it can be mitigated by work characteristics (i.e., social support and workload).

In addition, the nuanced effects of work characteristics on individuals are unique in the pandemic context. The role of social support appears to have become much more pronounced during the pandemic. In other words, social support appears to be the most powerful virtual work characteristic because it had positive indirect impacts on performance and well‐being via its associated beneficial effects on all the identified challenges. Moreover, although job autonomy did not relate to work‐home interference as expected, it was conductive to reduce loneliness during the home office days, which was not a finding we hypothesized. Finally, self‐discipline emerged as an important moderating individual difference factor. Self‐discipline, however, has been largely omitted in previous remote work studies, most likely because flexible work arrangements are usually provided only to employees with higher self‐discipline. When people are required to work from home irrespective of their abilities and preferences, we find that self‐discipline can significantly shape remote working experiences.

Overall, the current research has gained contextually relevant insights by exploring how virtual work characteristics shape remote working experiences in the unique COVID‐19 outbreak context. We discuss these findings more deeply next.

Re‐Theorizing Home‐Work Conflict During Remote Work

To date, in the remote working literature, flexible work arrangements are predominantly framed as a useful policy for balancing work and personal life. That is, compared with these who have no opportunities to engage in flexible work, some degree of teleworking helps to reduce work‐family conflict (Gajendran & Harrison, 2007 ). These studies usually treat remote working as an independent variable, resulting in a natural confound because they focus on people who, largely, have chosen this form of working, perhaps because their potential for work‐home conflict is lower in the first place (that is, lower conflict means they prefer flexible working) or because they have the resources to be better able to balance work‐family conflict at home. However, when individuals do not choose remote working, as in our study, their lack of preference or resources to do so might mean that working from home creates a significant challenge. In other words, it is possible that previous research says more about the people who choose flexible working than it does about the real experience of working from home. However, the current research might question this conclusion. Framing remote working as a context, our qualitative analyses showed work‐home interference is the most frequently mentioned challenge in the home office, and its negative effects were shown in Study 2.

Our research shows that job autonomy did not predict work‐home interference as expected. Theoretically, we would expect job autonomy to be important for work‐home interference because autonomy gives people latitude to manage the demands in a flexible way (Kahn & Byosiere, 1992 ; Bakker, Demerouti, & Euwema, 2005 ). Empirical research also supports the positive role of job autonomy in the remote work context (e.g., Kossek et al., 2009 ). How to explain our finding? On the one hand, it might simply be that job autonomy is less important for managing home demands in a remote worker context in which everyone works from home, not just the elite few. On the other hand, it might also be due to the unique nature of home‐work conflict in this study. If some of the home‐work conflict is self‐induced because people cannot maintain home/work boundaries, we would not expect autonomy to be especially helpful. One might even then theorize that, in the pandemic context, autonomy might positively help manage home‐work stressors such as child‐care demands but might negatively affect home‐work boundary self‐management, with these countervailing forces explaining the weaker role of autonomy for home‐work conflict.

Finally, it is also possible our findings relate to the unusual context. We note that the mean for job autonomy in the sample was 4.03 (on a 5‐point scale), which is very high for Chinese workers who tend to usually have relatively lower levels of job autonomy (e.g., Xie, 1996 ). The high job autonomy might, in turn, reflect the unusual remote work situation in which workers had to very rapidly set up to work at home. Managers might not have had sufficient time to fully set up their “usual” controls. Thus, it is possible that in this case the level of job autonomy was artificially high, leading to a ceiling effect suppressing its impact. Further research is needed on this issue.

Although the autonomy findings were unexpected, it is perhaps not a surprise that monitoring and workload that are usually theorized as job demands at work, exerted negative impacts on employees’ home‐work conflicts in this remote work context. Our results show that individuals with higher levels of monitoring and workload reported greater WHI. While the positive relation between workload and work‐family conflict is consistent with the existing work‐family interface research, the finding that monitoring is also positively associated with work‐family conflict adds to the literature as a new form of work demands that leads to negative work‐family spillover.

Procrastination as a Challenge that Can Be Mitigated Through Work Design

Although procrastination has been acknowledged as an issue for remote workers in a recent review on telecommuting (Allen et al., 2015 ), to our knowledge, only one empirical study has considered this topic, and this study considered procrastination as a personality variable (O’Neill et al., 2014 ). In contrast, our qualitative and quantitative analyses led us to consider procrastination as a challenge as it can greatly hurt workers’ performance and cause emotional exhaustion.

Our findings showed that procrastination can be shaped by virtual work characteristics, and our results are different from those identified in normal contexts (Metin et al., 2016 ). Metin Taris and Peeters ( 2016 ) argued that employees high on job resources and demands will perceive less boredom at work, which in turn can reduce procrastination. Our findings are partially consistent with their study. Though the desirable effect of job autonomy on reducing procrastination was identified by Mentin et al. ( 2016 ), this effect was not supported in the current research. Social support is omitted in their research, but we find that remote workers who received more social support were less likely to procrastinate, and this association was stronger for less‐disciplined people. In other words, employees low in self‐discipline benefit more from social support in coping with procrastination in the home office.

The effect of workload on procrastination is consistent with Mentin et al.’s finding that employees with higher workload experience less procrastination (though the indirect effects of workload on performance and emotional exhaustion via procrastination were not supported). As for another major job demand in remote working, monitoring, its impact on reducing procrastination was frequently mentioned by participants in Study 1. However, results from Study 2 did not support this argument; instead, given the negative effects of monitoring on employee well‐being, it appears an unhelpful and potentially costly managerial practice.

As we argued above, the pandemic context has made some work characteristics pronounced, while others become less important. It is not surprising that we find these inconsistent results. In this unique context, our research reveals the importance of social support. Given that procrastination in the home office is a challenge for many, yet it hasn't been considered adequately in the remote working literature, we suggest the need for research to investigate the nuanced relationship between virtual work characteristics and procrastination, including boundary conditions (moving beyond self‐discipline in this research) and underlying mechanisms (Wan et al., 2014 ).

Loneliness and the Surprising Role of Job Autonomy

We identified the feeling of loneliness as an important challenge among remote workers during the pandemic. Earlier studies have identified a concern about professional isolation among remote workers because of the reduction in informal social interactions with colleagues in the home office (Cooper & Kurland, 2002 ). Advanced ICTs (e.g., WhatsApp) nowadays afford users the opportunity to engage in large‐scale and real‐time social interactions (McFarland & Ployhart, 2015 ), which potentially contributes to keeping people socially connected and overcoming isolation. However, our study shows that online social interactions are not necessarily sufficient for reducing loneliness; “a psychological pain of perceived relational deficiencies in the workplace” (Ozcelik & Barsade, 2018 ; Wright & Silard, 2020 ). As our participants indicated in Study 1, they were not satisfied with the quality of online social interactions due to restricted “intimacy” and “closeness,” and such a feature might relate to loneliness.

We find a somewhat surprising link between job autonomy and loneliness. The idea that virtual social interactions require some degree of self‐initiation may help to explain this association. That is, social interactions in the remote working context cannot simply “happen”; instead, individuals need to proactively initiate or engage in online interactions. Previous theory and research argues that job autonomy is crucial for fueling proactive behavior because autonomy enhances people's internalized motivation, builds their self‐confidence, and fosters activated positive affect; all of which can drive proactive behavior (e.g., Parker, Bindl, & Strauss, 2010 ). For example, being proactive involves some degree of interpersonal risk because it means self‐initiating a behavior that no one has instructed one to do, which heightens the need for individual self‐efficacy. Considerable research shows the role of job autonomy for enhancing employees’ self‐efficacy, and thereby increasing their proactive behaviors (e.g., Ohly & Fritz, 2009 ; Parker et al., 2006 ). Although the focus of the current study is on proactive behavior that is socially oriented, it is possible that job autonomy is important for building individuals’ proactive motivation to self‐initiate contact with others, and thereby reduce feelings of loneliness.

Communication Quality Beyond its Remote Attributes

A fourth observation regarding working from home challenges concerns the quality of communication, which was identified as a key challenge in the interview study. Although remote working literature has acknowledged the limitations of ICT‐mediated communication and has assumed it is a hindrance relative to face‐to‐face interaction (Raghuram et al., 2019 ), poor communication experience in virtual collaboration has been empirically addressed mainly in virtual team and computer‐mediated communication literature (e.g., Chang et al., 2014 ) rather than the literature on remote working. This situation might be because ICT‐related communication experience is logically related to the technical system at work (Bélanger et al., 2013 ; Dennis, Fuller, & Valacich, 2008 ), which is not the primary research focus in remote working literature. However, our study suggests such an omission is problematic because many interpersonal processes are mediated by ICTs in the current digital workplace (Wang et al., 2020 ), and, therefore, communication quality is an important experience to consider for remote workers. Poor communication will not only hinder performance, as suggested in our research, but can also impair professional relationships (Camacho et al., 2018 ) and increase work stress (Day et al., 2012 ). Thus, our findings inspire scholars and practitioners to re‐think how to facilitate high quality virtual communications for remote workers.

The Power of Self‐Discipline

As an attribute that helps remote workers to mitigate the destructive effects of interruptions, self‐discipline has been widely considered as an important and necessary skill for achieving remote working effectiveness (e.g., Haddon & Lewis, 1994 ; Kinsman, 1987 ). However, largely due to the fact that remote working has always been a luxury among a small proportion of workers, as we mentioned earlier, self‐discipline as a desirable attribute was more used merely as a criterion to select the right people as remote workers (Baruch, 2000 ). This, on the one hand, might have rendered most remote workers to be those having relatively higher levels of self‐discipline, possibly leading to people's limited understanding as to the broader influences of self‐discipline; and, on the other hand, might have downplayed the role of self‐discipline in remote working (i.e., it should not be merely used as a selection criterion).

In a context wherein remote working becomes the normal and everyone started working remotely, self‐discipline is no longer just a selection criterion but becomes something that every remote worker strives to gain or improve on. By showing the moderating role of self‐discipline in the relationship between virtual work characteristics and experienced challenges in remote working, this research underscored the critical role of self‐discipline among all individuals practicing remote working. We believe this finding is critical as it may greatly enhance remote working practitioners’ awareness of the importance of self‐discipline and may also motivate many remote workers to try to develop their self‐discipline to achieve work effectiveness and well‐being.

Practical Implications

Insights from working at home during COVID‐19 can, beyond the immediate context of the pandemic, guide flexible work practice after crisis. Here, we distill three lessons for managers and employees in future practice.

First, our findings can help organizations and managers to manage remote work effectively. The predominantly positive view of remote working in the literature to date might make managers ignore the need to consider how flexible workers jobs are designed. As Baruch ( 2000 ) articulated, organizations and managers should “find new ways to manage…, develop innovative career paths, and put in place proper support mechanisms for teleworkers” (p. 46). The current research revealed the crucial role of virtual work characteristics. Although further research is needed, our study suggests managers can boost remote workers’ productivity and well‐being via designing high‐quality remote work. The work design perspective can guide managers to design a better job for remote workers during the pandemic or even in future flexible work practices. For example, managers might incur a lot of cost in setting up monitoring systems (Groen et al., 2018 ), but the desirable effect of monitoring on work effectiveness was not supported by our data. Managers should instead engage more supportive management practices especially in this extraordinary context, such as communicating with subordinates using motivating language (Madlock, 2013 ), building trust within the distributed team (Grant et al., 2013 ), and sharing information rather than close monitoring (Lautsch et al., 2009 ).

Second, employees and managers should be aware of the challenges in practicing remote work. Remote working is attractive to organizations and individuals in the current digital age, because of space savings, the opportunity to utilize a global labor market, less time spent on commuting, and so forth (Baruch, 2000 ). Many commentators are speculating that remote working will become even more attractive after COVID‐19 (Hern, 2020 ). However, scholars and practitioners might overstate the bright side of remote working, especially if they rely on the established research. For example, our research indicated less‐disciplined people experienced more challenges while working from home and, therefore, teleworking may not be suitable for them. Given that such challenges will influence individuals’ performance and well‐being, employees and employers need to consider the fit between flexible work arrangements and the person (Golden et al., 2006 ; Perry et al., 2018 ).

Finally, a work design perspective potentially helps individuals to cope with challenges in remote working. In addition to the top‐down approach (i.e., re‐designing remote work), individuals can proactively craft their jobs (Tims & Bakker, 2010 ; Wrzesniewski & Dutton, 2001 ; Zhang & Parker, 2019 ). For instance, engaging in informal communication with colleagues in a high‐intensity telecommuting setting has been shown to be positively related to job satisfaction (Fay & Kline, 2011 ). Thus, remote workers can proactively utilize current advanced enterprise social media (e.g., Slack) to socialize with others in an informal manner to overcome loneliness.

Limitations and Future Research

Our research inevitably has limitations. First, our qualitative and quantitative data were both collected in China, which may raise concerns about generalizability. Remote working in China and other developing countries is relatively new, which means we can capture individuals’ unique experiences during the sudden transition from the onsite office to home. However, one's remote work experience and acceptance of remote working can influence the impact of working from home (Gajendran & Harrison, 2007 ). Thus, it will be interesting to compare remote working during the pandemic between developing countries and developed countries in which flexible work arrangements are more widespread (e.g., exploring differences in coping strategies and perceived challenges). Our findings might also be influenced by cultural factors. For example, participants in Study 1 mentioned the necessity of monitoring in remote working, which might not generalize across countries. Although limited empirical work has examined the potential influences of national culture on individuals’ attitudes toward workplace electronic monitoring (see Ravid et al., 2019 for a systematic review), Panina and Aiello ( 2005 ) proposed a theoretical model that emphasized how cultural factors (e.g., individualism‐collectivism, uncertainty avoidance, and power distance) are likely to mitigate the acceptance of electronic monitoring. Accordingly, cross‐cultural studies are needed to explore the generalizability of these findings, as well as how cultural factors shape the impacts of virtual work characteristics on remote worker outcomes.

Second, our research was conducted in an extraordinary context. This was to some extent the point of our research—the COVID‐19 outbreak provides a unique opportunity to address theoretical gaps and expand theory. This context provides extra pressure for employees, such as worry about the pandemic, social isolation, financial pressure, greater family interferences, and the like, which likely shaped the findings. Despite this difference in context, we believe our approach and findings will be important in future remote working research and practice. Sytch and Greer (2020) argued that the post‐pandemic work will be hybrid, that is, remote work will be more prevalent in the future. Indeed, Facebook and Twitter have announced that their employees can choose to work from home “forever” after the pandemic. Thus, future research still need to consider people's experiences at home versus the office. We see particular value in examining people's virtual work characteristics (when working remotely) as well as their work characteristics when working at home, and using these two sets of assessments to really understand people's holistic work experiences.

Finally, the cross‐sectional nature of Study 2 means it suffers from common method bias (CMB; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003 ) and the possibility of reverse causality, which means that we were unable to establish causality in this study. Considering this limitation, we recommend the use of longitudinal or experimental research designs in future research. A longitudinal design will also contribute to tracking dynamic processes, such as how individuals adapt to flexible work arrangements. In particular, given that working from home is becoming a day‐to‐day practice in many organizations, we recommend future researchers conduct daily diary studies to investigate the intraindividual processes of remote working. For example, it will be interesting to examine the antecedents and consequences of the remote working challenges identified in the current research on a daily basis. Future research also can benefit from collecting data from multiple sources. For example, although individuals themselves might be the more suitable raters for their own challenges, their work effectiveness and well‐being can be usefully assessed by their supervisors and spouses, respectively, to alleviate issues of common method bias.

Supporting information

Supplementary Material

APPENDIX A. 

Interview protocol.

Can you describe your work, life, or general psychological experiences during the period of working from home?

• Positive aspects (e.g., collaborations, personal life, emotion, etc.)
• Negative aspects

Can you describe the potential factors that had influenced your work effectiveness and well‐being?

• Work‐related factors (e.g., workload, colleagues, supervisors, etc.)
• Other factors (e.g., personal traits, caring responsibilities, family, etc.)

Do you think your work is suitable to work from home in the future?

• If yes, why?
• If no, why?

This study was supported by an Australian Research Council Australian Laureate Fellowship (Grant Number: FL160100033), National Natural Science Foundation of China (Grant Number: 71672012), and Curtin International Postgraduate Research Scholarship (CIPRS) and Research Stipend Scholarship.

1 The job autonomy →WHI and job autonomy →HWI path coefficients changed to be significant when we estimated this model without any controls. Except for that, other relationships were not significantly influenced by removing control variables.

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• Published: 09 September 2021

The effects of remote work on collaboration among information workers

• Longqi Yang   ORCID: orcid.org/0000-0002-6615-8615 1 ,
• David Holtz   ORCID: orcid.org/0000-0002-0896-8628 2 , 3 ,
• Sonia Jaffe   ORCID: orcid.org/0000-0001-8924-0294 1 ,
• Siddharth Suri   ORCID: orcid.org/0000-0002-1318-8140 1 ,
• Shilpi Sinha 1 ,
• Jeffrey Weston 1 ,
• Connor Joyce 1 ,
• Neha Shah 1 ,
• Kevin Sherman   ORCID: orcid.org/0000-0001-5793-3336 1 ,
• Brent Hecht   ORCID: orcid.org/0000-0002-7955-0202 1 &
• Jaime Teevan   ORCID: orcid.org/0000-0002-2786-0209 1  

Nature Human Behaviour volume  6 ,  pages 43–54 ( 2022 ) Cite this article

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An Author Correction to this article was published on 05 October 2021

This article has been updated

The coronavirus disease 2019 (COVID-19) pandemic caused a rapid shift to full-time remote work for many information workers. Viewing this shift as a natural experiment in which some workers were already working remotely before the pandemic enables us to separate the effects of firm-wide remote work from other pandemic-related confounding factors. Here, we use rich data on the emails, calendars, instant messages, video/audio calls and workweek hours of 61,182 US Microsoft employees over the first six months of 2020 to estimate the causal effects of firm-wide remote work on collaboration and communication. Our results show that firm-wide remote work caused the collaboration network of workers to become more static and siloed, with fewer bridges between disparate parts. Furthermore, there was a decrease in synchronous communication and an increase in asynchronous communication. Together, these effects may make it harder for employees to acquire and share new information across the network.

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Before the COVID-19 pandemic, at most 5% of Americans worked from home for more than three days per week 1 , whereas it is estimated that, by April 2020, as many as 37% of Americans were working from home (WFH) full-time 2 , 3 . Thus, in a matter of weeks, the pandemic caused about one-third of US workers to shift to WFH and nearly every American that was able to work from home did so 4 . Many technology companies, such as Twitter, Facebook, Square, Box, Slack and Quora, have taken this shift one step further by announcing longer term and, in some cases permanent, remote work policies that will enable at least some employees to work remotely, even after the pandemic 5 , 6 . More generally, COVID-19 has accelerated the shift away from traditional office work, such that even firms that do not keep full-time remote work policies in place after the pandemic has ended are unlikely to fully return to their pre-COVID-19 work arrangements 7 . Instead, they are likely to switch to some type of hybrid work model, in which employees split their time between remote and office work, or a mixed-mode model, in which firms are comprised of a mixture of full-time remote employees and full-time office employees. For example, some scholars predict a long-run equilibrium in which information workers will work from home approximately 20% of the time 1 . For long-term policy decisions regarding remote, hybrid and mixed-mode work to be well informed, decision makers need to understand how remote work would impact information work in the absence of the effects of COVID-19. To answer this question, we treat Microsoft’s company-wide WFH policy during the pandemic as a natural experiment that, subject to the validity of our identifying assumptions, enables us to causally identify the impact of firm-wide remote work on employees’ collaboration networks and communication practices.

Previous research has shown that network topology, including the strength of ties, has an important role in the success of both individuals and organizations. For individuals, it is beneficial to have access to new, non-redundant information through connections to different parts of an organization’s formal organizational chart and through connections to different parts of an organization’s informal communication network 8 . Furthermore, being a conduit through which such information flows by bridging ‘structural holes’ 9 in the organization can have additional benefits for individuals 10 . For firms, certain network configurations are associated with the production of high-quality creative output 11 , and there is a competitive advantage to successfully engaging in the practice of ‘knowledge transfer,’ in which experiences from one set of people within an organization are transferred to and used by another set of people within that same organization 12 . Conditional on a given network position or configuration, the efficacy with which a given tie can transfer or provide access to novel information depends on its strength. Two people connected by a strong tie can often transfer information more easily (as they are more likely to share a common perspective), to trust one another, to cooperate with one another, and to expend effort to ensure that recently transferred knowledge is well understood and can be utilized 10 , 13 , 14 , 15 . By contrast, weak ties require less time and energy to maintain 8 , 16 and are more likely to provide access to new, non-redundant information 8 , 17 , 18 .

Our results show that the shift to firm-wide remote work caused business groups within Microsoft to become less interconnected. It also reduced the number of ties bridging structural holes in the company’s informal collaboration network, and caused individuals to spend less time collaborating with the bridging ties that remained. Furthermore, the shift to firm-wide remote work caused employees to spend a greater share of their collaboration time with their stronger ties, which are better suited to information transfer, and a smaller share of their time with weak ties, which are more likely to provide access to new information.

Previous research has also shown that the performance of workers is affected not only by the structure of the network and the strength of their ties, but also by the temporal dynamics of the network. Not only do the benefits of different types of ties vary with their age 19 , but people also benefit from changing their network position 20 , 21 , 22 , adding new ties 23 , 24 and reconnecting with dormant ties 25 . We find that the shift to firm-wide remote work may have reduced these benefits by making the collaboration network of workers more static—individuals added and deleted fewer ties from month-to-month and spent less time with newly added ties.

Existing theoretical perspectives and empirical results suggest that knowledge transfer and collaboration are also affected by the modes of communication that workers use to collaborate with one another. On the theoretical front, media richness theory 26 , 27 posits that richer communication channels, such as in-person interaction, are best suited to communicating complex information and ideas. Moreover, media synchronicity theory 28 proposes that asynchronous communication channels (such as email) are better suited for conveying information and synchronous channels (such as video calls) are better suited for converging on the meaning of information. There is also a rich body of empirical research that documents the myriad implications of communication media choice for organizations. For example, previous research has shown that establishing a rapport, which is an important precursor to knowledge transfer, is impeded by email use 29 , and that in-person and phone/video communication are more strongly associated with positive team performance than email and instant message (IM) communication 30 .

Remote work obviously eliminates in-person communication; however, we found that people did not simply replace in-person interactions with video and/or voice calls. In fact, we found that shifting to firm-wide remote work caused an overall decrease in observed synchronous communication such as scheduled meetings and audio/video calls. By contrast, we found that remote work caused employees to communicate more through media that are more asynchronous—sending more emails and many more IMs. Media richness theory, media synchronicity theory and previous empirical studies all suggest that these communication media choices may make it more difficult for workers to convey and/or converge on the meaning of complex information.

There is a large body of academic research across multiple disciplines that has studied remote work, virtual teams and telecommuting (see ref. 31 for a review of much of this work), including previous research studies that examined the network structure of virtual teams and how individual network position in virtual teams correlates with performance 32 , 33 , 34 . During the COVID-19 pandemic, there has been renewed public and academic interest in how virtual teams function. Recent analyses of telemetry and survey data show that the pandemic has affected both the who and the how of collaboration in information firms—while working remotely during the pandemic, workers are spending less time in meetings 35 , communicating more by email 35 , collaborating more with their strong ties as opposed to their weak ties 36 , and exhibiting patterns of communication that are more siloed and less stable 37 . However, these analyses, like much of the previous research on remote work, virtual teams and telecommuting, are non-causal 31 and are therefore unable to separate the effects of remote work from the effects of pandemic-related confounding factors, such as reduced focus due to COVID-19-related stress or increased caregiving responsibilities while sheltering in place. Although previous research on the causal effects of remote work does exist, this work has mainly studied employees who volunteer to work remotely, and has focused on settings such as call centres and patent offices 38 , 39 where, relative to the majority of information work, tasks are more easily codifiable and are less likely to depend on collaboration or the transfer of complex knowledge.

In this article, we contribute to the research literatures on remote work, virtual teams and telecommuting by analysing the large-scale natural experiment created by Microsoft’s firm-wide WFH policy during the COVID-19 pandemic. As remote work was mandatory during the pandemic, we are able to quantify the effects of firm-wide remote work, which are most relevant for firms considering a transition to an all-remote workforce. Furthermore, as our model specification decomposes the overall effects of firm-wide remote work into ego remote work and collaborator remote work effects, our results also provide some insight into the possible impacts of remote work policies such as mixed-mode work and hybrid work.

We analysed anonymized individual-level data describing the communication practices of 61,182 US Microsoft employees from December 2019 to June 2020—data from before and after Microsoft’s shift to firm-wide remote work (our data on workers’ choice of communication media goes back only to February 2020). Our sample contains all US Microsoft employees except for those who hold senior leadership positions and/or are members of teams that routinely handle particularly sensitive data. Given the scope of our dataset, the workers in our sample perform a wide variety of tasks, including software and hardware development, marketing and business operations. For each employee, we observe (1) their remote work status before the COVID-19 pandemic, and what share of their colleagues were remote workers before the COVID-19 pandemic; (2) their managerial status, the business group they belong to, their role and the length of their tenure at Microsoft as of February 2020; (3) a weekly summary of the amount of time spent in scheduled meetings, time spent in unscheduled video/audio calls, emails sent and IMs sent, and the length of their workweek; and (4) a monthly summary of their collaboration network. Before the COVID-19 pandemic, managers at Microsoft used their own discretion in deciding whether an employee could work from home, which was the exception rather than the norm.

The natural experiment that we analysed came from the company-wide WFH mandate Microsoft enacted in response to COVID-19. On 4 March 2020, Microsoft mandated that all non-essential employees in their Puget Sound and Bay Area campuses shift to full-time WFH. Other locations followed suit and, by 1 April 2020, all non-essential US Microsoft employees were WFH full-time. Before the onset of the pandemic, 18% of US Microsoft employees were working remote from their collaborators. For this subset of employees, the shift to firm-wide remote work did not cause a change in their own remote work status, but did induce variation in the share of their colleagues who were working remotely. For the remaining 82% of US Microsoft employees, the shift to firm-wide remote work induced variation in both their own remote work status and in the remote work status of their coworkers.

We analysed this natural experiment using a modified difference-in-differences (DiD) model. Standard DiD is an econometric approach that enables researchers to infer the causal effect of a treatment by comparing longitudinal data from at least two groups, some of which are ‘treated’ and some of which are not. Provided that the identifying assumptions of the DiD model are satisfied, the causal effect of the treatment is obtained by comparing the magnitude of the gap between the treated and untreated groups after the treatment is delivered with the magnitude of the gap between the groups before the treatment is delivered. Our modified DiD model extends the standard DiD model by estimating the causal effects of changes in two different treatment variables (one’s own remote work status and the remote work status of one’s colleagues) and by introducing additional identifying assumptions such that it is possible to draw causal inferences in the presence of an additional shock (in our case, the non-WFH-related aspects of COVID-19) that affects both treated and untreated units, and is concurrent with the exogenous shock(s) to our treatment variables. The time series trends shown in Fig. 1 suggest that the identifying assumptions of our modified DiD model are plausible; further details on the model are provided in the Methods .

a – d , The average number of bridging ties per month ( a , c ) and the average unscheduled video/audio call hours per week ( b , d ) for different groups of employees, relative to the overall average in February. These plots establish the plausibility of the ‘parallel trends’ assumption that is required by our modified DiD model. The error bars show the 95% CIs and are in some places thinner than the symbols in the figure; s.e. values are clustered at the team level. a , b , The graphs show employees who, before COVID-19, worked from the office (blue; n  = 50,268) and a matched sample of employees who worked remotely (orange; n  = 10,914). c , d , The graphs show two subgroups of the blue lines in a and b —employees who, before COVID-19, had less than 10% of their collaborators working remotely (dashed; n  = 36,008) and those who had more than 50% of their coworkers working remotely (dotted; n  = 1,861). Both variables were normalized by subtracting and dividing by the average across the entire sample of that variable in February. Most employees transitioned to WFH during the week of 1 March 2020, although our analysis omits the month of March as a transition period.

In all of the analyses that follow, we cannot report the actual level of our outcome variables due to confidentiality concerns. Instead, throughout the paper we report outcomes and effects in terms of February value (FV)—the average level of that variable (for example, number of bridging ties) for all US employees in February.

Effects of remote work on collaboration networks

We start by presenting the non-causal time-series trends for different collaboration network outcomes across our entire sample. These trends provide insights into how work practices have changed during the COVID-19 pandemic, and also represent the type of data that many executives may use when making decisions regarding their firm’s long-term remote work policy.

Descriptive statistics

Figure 2 shows the average monthly time series for various aspects of workers’ collaboration egocentric (ego) networks from December 2019 to June 2020: the number of connections, the number of groups interacted with, the number of and share of time with cross-group connections, the number and share of time with bridging connections, the clustering coefficient, the share of time with weak connections, the number of churned and added connections, and the share of time with added connections. Mathematical definitions for these measures are provided in the Methods . Although we did not find evidence of a clear pattern of change around the shift to firm-wide remote work for many of these measures, we did observe large changes in the average shares of monthly collaboration hours spent with cross-group ties, bridging ties, weak ties and added ties, which all decreased precipitously between February and June.

a – k , The monthly averages for the collaboration network variables for all employees relative to the February average. Each variable was normalized by subtracting and dividing by the average FV for that variable. The vertical bars show the 95% CIs, but are in most places not much taller than the data points; s.e. values are clustered at the team level. The variables are employees’ average number of network ties ( a ), distinct business groups in which they have a collaborator ( b ), cross-group ties ( c ), ties that bridge structural holes in the network ( e ), individual clustering coefficient ( g ), collaborators from the previous month that they did not collaborate with that month ( i ) and added collaborators they did not collaborate with the previous month ( j ), as well as the share of time spent with cross-group ties ( d ), bridging ties ( f ), weak ties ( h ) and added ties ( k ). n  = 61,279 for each panel.

Causal analysis

We next used our modified DiD model to isolate the effects of firm-wide remote work on the collaboration network, which are shown in Fig. 3 . Although we found no effect on the number of collaborators that employees had (the size of their collaboration ego network), we did find that firm-wide remote work decreased the number of distinct business groups that an employee was connected to by 0.07 FV ( P  < 0.001, 95% confidence interval (CI) = 0.05–0.10). Firm-wide remote work also decreased the cross-group connections of workers by 0.04 FV ( P  = 0.008, 95% CI = 0.01–0.07) and the share of collaboration time workers spent with cross-group connections by 0.26 FV ( P  < 0.001, 95% CI = 0.23–0.29). In other words, firm-wide remote work caused an overall decrease in the number of cross-group interactions and the fraction of attention paid to groups other than one’s own.

The estimated causal effects of both an employee and that employee’s colleagues switching to remote work on the number of collaborators an employee has, the number of distinct groups the employee collaborates with, the number of cross-group ties an employee has, the share of time an employee spends collaborating with cross-group ties, the number of bridging ties an employee has, the share of time an employee spends collaborating with bridging ties, the individual clustering coefficient of an employee’s ego network, the share of time an employee spent collaborating with weak ties, the number of churned collaborators, the number of added collaborators and the share of time spent with added collaborators. The reported effects are ( β  +  δ ) from equation ( 1 ), normalized by dividing by the average level of that variable in February. The symbols depict point estimates and the lines show the 95% CIs. n  = 61,182 for all variables. The full results are provided in Supplementary Tables 1 and 2 .

Although formal organizational boundaries shape informal interactions 40 , the formal organization of firms and their informal social structure are two distinct, interrelated concepts 41 . Connections that provide access to diverse teams may not bridge structural holes in the network sense 9 , and connections that bridge structural holes in the network sense may not provide access to different parts of the formal organizational chart. We therefore also analysed how the shift to firm-wide remote work affected the structural diversity of employees’ ego networks with respect to the firm’s observed communication network, as opposed to the formal organizational chart. We label each tie as ‘bridging’ or ‘non-bridging’ on the basis of its local network constraint, which is a measure of the extent to which a given tie bridges structural holes in a network 9 , 42 . We then measured the effect of firm-wide remote work on the number of bridging ties that each worker had and the amount of time that each worker spent with their bridging ties. We found that, on average, firm-wide remote work decreased the number of bridging ties by 0.09 FV ( P  < 0.001, 95% CI = 0.06–0.13) and the share of time with bridging ties by 0.41 FV ( P  < 0.001, 95% CI = 0.35–0.47). The fact that firm-wide remote work caused workers to have fewer bridging ties, and to spend less time with their remaining bridging ties, suggests that firm-wide remote work may have reduced the ability of workers to access new information in other parts of the network. These results, in conjunction with our finding that firm-wide remote work reduced workers’ cross-group interactions, also suggest that firm-wide remote work caused the collaboration network to become more siloed, both in a formal sense and in an informal sense.

We also found that firm-wide remote work caused a 0.06 FV ( P  = 0.005, 95% CI = 0.02–0.10) increase in the individual clustering coefficient, which provides a measure of what proportion of an individual’s network connections are also connected to each other (the higher a person’s individual clustering coefficient, the more dense their ego network). Given the fact that we did not observe a statistically significant effect of remote work on the number of colleagues with whom workers collaborate, this result suggests that, on average, firm-wide remote work caused workers to substitute ties that were not connected to one another for those that were. In other words, different portions of the network, which became less interconnected, also became more intraconnected.

The ability of a worker to effectively access knowledge from other parts of an organization is a function of not only the organizational and/or topological diversity of their connections, but also the strength of those connections. For each month, we classified ties as strong when they were in the top 50% of an employee’s ties in terms of hours spent communicating, and as weak otherwise. Although we have not seen strong and weak ties defined in this exact way elsewhere in the research literature on social networks, the research community has not, to our knowledge, converged on a standard way to measure tie strength. Our operationalization is similar to a common tie strength definition that simply counts the amount of contact between ties 43 , 44 , 45 and allows tie strength to vary over time on the basis of the relative amount of contact between two people 46 . Also, it is consistent with Granovetter’s original notion that tie strength is determined by a combination of “the amount of time, the emotional intensity, the intimacy (mutual confiding) and the reciprocal services which characterize the tie” 8 .

Although weak ties by definition will always get less of an employee’s time than strong ties in a given month, we found that the shift to remote work reduced the share of time that workers spent collaborating with weak ties by 0.32 FV ( P  < 0.001, 95% CI = 0.29–0.35). As the median is just one possible cut-off to distinguish between strong and weak ties, we also analysed the entire distribution of collaboration time for each worker and confirmed that the average ego-level-normalized Herfindahl–Hirschman index (HHI) 47 of the collaboration time is increased by remote work, and that the average ego-level Shannon entropy 48 of collaboration time is decreased by remote work. The effects of firm-wide remote work on both of these outcomes are provided in Supplementary Table 2 . In total, these results indicate that, above and beyond the impact of firm-wide remote work on the organizational and structural diversity of workers’ ego networks, the shift to firm-wide remote work also made the allocation of workers’ time more heavily concentrated.

We also found that the shift to firm-wide remote work caused workers’ ego networks to become more static; firm-wide remote work reduced the number of existing connections that churned from month-to-month by 0.05 FV ( P  = 0.006, 95% CI = 0.02–0.09), and decreased the number of connections workers added month-to-month by 0.04 FV ( P  = 0.015, 95% CI = 0.01–0.07). Furthermore, the shift to firm-wide remote work decreased the share of time that workers spent collaborating with the connections they did add by 0.29 FV ( P  < 0.001, 95% CI = 0.24–0.34). Of the added ties we observed in June 2020, 40% existed in at least one month between January 2020 and May 2020, whereas the remaining 60% did not. This suggests that the added ties that we observed are a mixture of dormant ties 25 and ties that are truly new. Overall, the changes that we observed in the temporal dynamics of ego networks may have made it more difficult for workers to capture the benefits associated with forming new connections 23 , 24 , reconnecting with dormant connections 25 and modulating their network position 20 , 21 , 22 . These results are robust to the use of alternative definitions of added and deleted ties (full details are provided in the Supplementary Information ).

In summary, our results suggest that firm-wide remote work ossified workers’ ego networks, made the network more fragmented and made each fragment more clustered. We tested for heterogeneity in the effects of the shift to firm-wide remote work on collaboration ego networks with respect to a worker’s managerial status (manager versus individual contributor), tenure at Microsoft (shorter tenure versus longer tenure) and role type (engineering versus non-engineering), and did not find meaningful heterogeneity across any of these dimensions (Supplementary Figs. 1 , 2 and 4 ).

The effects of remote work on the use of communication media

In addition to estimating the effects of firm-wide remote work on workers’ collaboration networks, we also estimated the impact of firm-wide remote work on workers’ choice of communication media.

Figure 4 shows the non-causal time-series trends for workweek hours and different communication media outcomes across our entire sample. Detailed definitions for each of these outcomes are provided in the Methods . For unscheduled call hours, meeting hours, total video/audio hours and IMs sent, we observed considerable increases around the time of the switch to firm-wide remote work; these increases are sustained through our data timespan. The change in email volume is much smaller and shorter-lived. Figure 4f shows the change in workweek hours, a metric that measures the total amount of time between the first observed work activity and the last observed work activity on each work day in a given week. Although there was a sustained increase in workweek hours, it was too small to account for the large increases that we observed in the use of various communication media without a simultaneous shift in the way that employees were conducting work.

a – f , The weekly averages for each variable, relative to the February average. Each variable was normalized by subtracting and dividing by the average FV for that variable. The vertical bars show the 95% CIs, but are in most places not much taller than the data points; s.e. values are clustered at the team level. The variables are the employees’ average number of unscheduled audio/video call hours ( a ), scheduled meeting hours ( b ), total hours in scheduled meetings and unscheduled calls (the sum of a and b ) ( c ), IMs sent ( d ), emails sent ( e ), and hours between the first and last activity (sent email, scheduled meeting, or Microsoft Teams call or chat) in a day, summed across the workdays ( f ). The dips in all six metrics during the weeks of 16 February, 24 May and 14 June were due to four-day workweeks, in observance of Presidents’ Day, Juneteenth and Memorial Day, respectively. n  = 61,279 for all variables.

Figure 5 shows the estimated causal effects of firm-wide remote work on the amount of communication conducted through different media, as well as the length of workers’ workweeks. Relative to the baseline case of all coworkers working in an office together, we found that firm-wide remote work decreased scheduled meeting hours by 0.16 FV ( P  < 0.001, 95% CI = 0.13–0.19) and increased unscheduled video/audio call hours by 1.6 FV ( P  < 0.001, 95% CI = 1.5–1.8). The increase in unscheduled calls was more than offset by the decrease in scheduled meeting hours. To observe that, we defined the sum of unscheduled call hours and scheduled meetings hours as the synchronous video/audio communication hours. We estimate that firm-wide remote work caused a slight decrease of 0.05 FV ( P  = 0.006, 95% CI = 0.01–0.08) in the total amount of synchronous video/audio communication. Given that, by definition, a shift to firm-wide remote work causes in-person interactions to drop to zero and synchronous video/audio communication decreased overall, our results also indicate that firm-wide remote work led to a decrease in the total amount of synchronous collaboration, both in-person and through Microsoft Teams.

The estimated causal effects of both an employee and their colleagues switching to remote work on the employee’s hours spent in scheduled meetings, hours spent in unscheduled calls, the sum of meetings and call hours, IMs sent, emails sent and estimated workweek hours. The reported effects are ( β  +  δ ) from equation ( 1 ), normalized by dividing by the average level of that variable in February. The symbols depict point estimates and lines depict 95% CIs. n  = 61,182 for all variables. The full results are provided in Supplementary Table 3 .

Although firm-wide remote work caused a decrease in synchronous communication, it also caused an increase in the amount of asynchronous communication. Firm-wide remote work increased the number of emails sent by workers by 0.08 FV ( P  < 0.001, 95% CI = 0.05–0.12) and the number of IMs sent by workers by 0.50 FV ( P  < 0.001, 95% CI = 0.46–0.55). Firm-wide remote work also increased the average number of workweek hours by 0.10 FV ( P  < 0.001, 95% CI = 0.09–0.11); however, this effect is small relative to the effect on IM volume. This suggests that the increase in IMs reflects a change in workers’ collaboration patterns while working, as opposed to changes in how much workers were working. The fact that shifting to firm-wide remote work increased the number of workweek hours also makes the negative effect of firm-wide remote work on synchronous collaboration more notable. The increase in workweek hours could be an indication that employees were less productive and required more time to complete their work, or that they replaced some of their commuting time with work time; however, as we are able to measure only the time between the first and last work activity in a day, it could also be that the same amount of working time is spread across a greater share of the calendar day due to breaks or interruptions for non-work activities.

Heterogeneous effects of firm-wide remote work on communication media choice

Although the effects of firm-wide remote work on collaboration networks did not exhibit heterogeneity across the worker attributes that we observed, the effects of firm-wide remote work on communication media were in some cases larger for managers and engineers. We found that the switch to firm-wide remote work caused larger increases for managers than individual contributors in IMs sent, emails sent and unscheduled video/audio call hours (Fig. 6 , left). This is probably because, relative to individual contributors, a larger share of managers’ time is dedicated to communicating with others, that is, their direct reports (for example, to address issues blocking progress or conduct performance reviews), and representatives of other groups within the organization (for example, to coordinate activity and goals across different groups). We also find that the shift to firm-wide remote work caused larger increases for engineers than non-engineers in the number of IMs sent and the number of unscheduled call hours (Fig. 6 , right). This may be reflective of the fact that software development teams are particularly reliant on informal communication 49 , 50 , 51 , much of which may have taken place in-person before the shift to firm-wide remote work. We did not find meaningful heterogeneity with respect to employee tenure at Microsoft.

The causal effects, estimated separately for managers ( n  = 9,715) and individual contributors (ICs) ( n  = 51,467) (left) and engineers (n = 29, 510) and non-engineers ( n  = 31,672) (right), of an employee and their colleagues switching to remote work on hours spent in scheduled meetings, the sum of scheduled meetings and unscheduled call hours, IMs sent, emails sent and estimated workweek hours ( a ), and hours spent in unscheduled calls ( b ). The reported effects are ( β  +  δ ) from equation ( 1 ), normalized by dividing by the average level of that variable for all employees in February. The symbols depict point estimates and the lines show the 95% CIs. The full results are provided in Supplementary Tables 8 , 9 , 22 and 23 .

Decomposing the effects of firm-wide remote work

One benefit of our empirical approach is that it enables us to decompose the causal effects of firm-wide remote work into two components: the direct effect of an employee working remotely on their own work practices (ego effects) and the indirect effect of all an employee’s colleagues working remotely on that employee’s work practices (collaborator effects). The model is linear, so the predicted effects from having half of one’s collaborators switch to remote work would be half as large.

Figure 7 shows the ego and collaborator effects of firm-wide remote work on people’s collaboration networks. Notably, the remote work status of an employee and that employee’s collaborators both contributed to the total effect of firm-wide for most network outcomes. An employee’s collaborators switching to remote work seems to have had a particularly large impact on the amount of time that workers spent with ties that are most likely to provide access to new information, that is, cross-group ties, bridging ties, weak ties and added ties. As seen in Fig. 8 , collaborator effects also dominate ego effects when we decomposed the effects of firm-wide remote work on communication media usage. More than half of the increase in IMs sent and emails sent was due to collaborators switching to remote work, and approximately 90% (+0.09 FV, P  < 0.001, 95% CI = 0.07–0.10) of the increase in workweek hours was due to collaborators switching to remote work. Overall, we found that collaborators switching to remote work caused workers to spend less time attending to sources of new information, communicate more through asynchronous media and work longer hours. Looking to the future, these findings suggest that remote work policies such as mixed-mode and hybrid work may have substantial effects not only on those working remotely but also on those remaining in the office.

The estimated causal effects of either an employee ( δ from equation ( 1 )) or their colleagues ( β from equation ( 1 )) switching to remote work on the number of collaborators that an employee has, the number of distinct groups the employee collaborates with, the number of cross-group ties an employee has, the share of time an employee spends collaborating with cross-group ties, the number of bridging ties an employee has, the share of time an employee spends collaborating with bridging ties, the individual clustering coefficient of an employee’s ego network, the share of time an employee spent collaborating with weak ties, the number of churned collaborators, the number of added collaborators and the share of time spent with added collaborators. All effects were normalized by dividing by the average level of that variable in February. The symbols depict point estimates and the lines show the 95% CIs. n  = 61,182 for all variables. The full results are provided in Supplementary Tables 1 and 2 .

The estimated causal effects of either an employee ( δ from equation ( 1 )) or their colleagues ( β from equation ( 1 )) switching to remote work on hours spent in scheduled meetings, the sum of scheduled meetings and unscheduled call hours, IMs sent, emails sent and estimated workweek hours ( a ), and hours spent in unscheduled calls ( b ). All effects were normalized by dividing by the average level of that variable in February. The symbols depict point estimates and the lines show the 95% CIs. n  = 61,182 for all variables. The full results are provided in Supplementary Table 3 .

Our results suggest that shifting to firm-wide remote work caused the collaboration network to become more heavily siloed—with fewer ties that cut across formal business units or bridge structural holes in Microsoft’s informal collaboration network—and that those silos became more densely connected. Furthermore, the network became more static, with fewer ties added and deleted per month. Previous research suggests that these changes in collaboration patterns may impede the transfer of knowledge 10 , 12 , 13 and reduce the quality of workers’ output 11 , 23 . Our results also indicate that the shift to firm-wide remote work caused synchronous communication to decrease and asynchronous communication to increase. Not only were the communication media that workers used less synchronous, but they were also less ‘rich’ (for example, email and IM). These changes in communication media may have made it more difficult for workers to convey and process complex information 26 , 27 , 28 .

We expect that the effects we observe on workers’ collaboration and communication patterns will impact productivity and, in the long-term, innovation. Yet, across many sectors, firms are making decisions to adopt permanent remote work policies based only on short-term data 52 . Importantly, the causal estimates that we report are substantially different compared with the effects suggested by the observational trends shown in Figs. 2 and 4 . Thus, firms making decisions on the basis of non-causal analyses may set suboptimal policies. For example, some firms that choose a permanent remote work policy may put themselves at a disadvantage by making it more difficult for workers to collaborate and exchange information.

Beyond estimating the causal effects of firm-wide remote work, our results also provide preliminary insights into the effects of remote work policies such as mixed-mode and hybrid work. Specifically, the non-trivial collaborator effects that we estimate suggest that hybrid and mixed-mode work arrangements may not work as firms expect. The most effective implementations of hybrid and mixed-mode work might be those that deliberately attempt to minimize the impact of collaborator effects on those employees that are not working remotely; for example, firms might consider implementations of hybrid work in which certain teams come into the office on certain days, or in which most or all workers come into the office on some days and work remotely otherwise. Firms might also consider arrangements in which only certain types of workers (for example, individual contributors) are able to work remotely.

Although we believe these early insights are helpful, firms and academics will need to undertake a combination of quantitative and qualitative research once the COVID-19 pandemic has ended to better measure both the benefits and the downsides of different remote work policies. Large firms with the ability to collect rich telemetry data will be particularly well-positioned to build on the quantitative insights presented in this work by conducting large-scale internal field experiments. If published externally, these experiments could have the capacity to greatly further our collective understanding of the causal effects of both firm-wide remote work and other work arrangements such as hybrid work and mixed-mode work. Our results, which report both direct effects and indirect effects of remote work, suggest that such experimentation needs to be conducted carefully. Simply comparing the work practices and/or productivity levels of remote workers and office workers will likely yield biased estimates of the global treatment effects of different remote work policies, due to the causal effects of one’s colleagues working remotely. In conducting these experiments, it is crucial that firms use experiment designs that are optimized for capturing the overall effects of remote work policies, for example, graph cluster randomization 53 , 54 or switchback randomization 55 . Ideally, such field experiments would be complemented with high-quality qualitative research that can describe emergent processes and workers’ perceptions and, more generally, uncover insights beyond those that can be obtained through quantitative methods.

Our research is not without its limitations. First, our study characterizes the impacts of firm-wide remote work on the US employees of one major technology firm. Although we expect our results to generalize to other technology firms, this may not be the case. Caution should also be exercised in generalizing our results to other sectors and other countries. Second, the period of time over which we measured the causal effects of remote work are quite short (three months), and it is possible that the long-term effects of firm-wide remote work are different. For example, at the beginning of the pandemic, workers were able to leverage existing network connections, many of which were built in person. This may not be possible if firm-wide remote work were implemented long-term. Third, our analysis treats the effects of firm-wide remote work on peoples’ collaboration networks and communication media usage as separate, whereas these two types of effects may interact and exacerbate one another. Fourth, although we believe that changes to workers’ communication networks and media will affect productivity and innovation, we were unable to measure these outcomes directly. Even if we were able to measure productivity and innovation, the impacts of network structure and communication media choice on performance are likely contingent on a number of factors, including the type of task a given team/organization is trying to complete 56 , 57 , 58 , 59 . Finally, our ability to make causal claims is predicated on the validity of our modified DiD framework’s identifying assumptions: parallel trends, conditional exogeneity after matching and additively separable effects. Although we have taken steps to verify the plausibility of these assumptions and tested the robustness of our results to an alternative matching procedure 60 (details of which are provided in the Methods ), they are assumptions nonetheless.

There are multiple high-profile cases of firms such as IBM and Yahoo! enacting, but ultimately rescinding, flexible remote work policies before COVID-19, presumably due to the impacts of these policies on communication and collaboration 61 , 62 . On the basis of these examples, one might conclude that the current enthusiasm for remote work may not ultimately translate into a long-lasting shift to remote work for the majority of firms. However, during the COVID-19 pandemic, workers and firms have invested in the physical and human capital required to support remote work 63 and innovation has shifted toward new technologies that support remote work 64 . Both of these factors make it more likely that for many firms, some version of remote work will persist beyond the pandemic. In light of this fact, the importance of deepening our understanding of remote work and its impacts has never been greater.

Ethical review

This research was reviewed and classified as exempt by the Massachusetts institute of Technology (MIT) Committee on the Use of Humans as Experimental Subjects (that is, MIT’s Institutional Review Board), because the research was secondary use research involving the use of de-identified data.

Our data were passively collected and anonymized by Microsoft’s Workplace Analytics product 65 , which logs activity that takes place in employees’ work email accounts and in Microsoft Teams using de-identified IDs. Microsoft Teams is collaboration software that enables employees to video/audio call, video/audio teleconference, IM and share files. The use of the data is compliant with US employee privacy laws. Employee privacy restrictions in many countries prevent us from reporting on workers outside the US. However, an employee’s communication and collaboration with international coworkers is still included in the data and those employees are still counted as part of each employee’s network. No information on international coworkers except for counting interactions with US employees was obtained for research purposes or analysed. Microsoft provides employees with appropriate notice of its use of Workplace Analytics, and sets strict controls over the collection and use of such data.

In our collaboration network, each worker is a node. For a tie to exist between two workers in a given month, those two workers must have had at least one meaningful interaction through two out of the following four communication media: email, IM, scheduled meeting and unscheduled video/audio call. A meaningful interaction is an email, IM, scheduled meeting or unscheduled video/audio call with a group of size no more than eight.

In our analysis, we classify a worker as working remotely if more than 80% of their collaboration hours in a given month are with colleagues remote to them. For employees WFH, all of their colleagues are considered to be remote from them, whereas, for those in an office, colleagues are remote to them if those colleagues are WFH or are located on a Microsoft campus in a different city. After March 2020, all US Microsoft employees are by definition working remotely, as they are WFH.

Modified DiD model

Our modified DiD model extends the standard DiD model in two ways. First, rather than measuring the effect of changes in one treatment variable, our model measures the effects of changes in two different treatment variables—(1) whether an employee is working remotely and (2) whether that employee’s colleagues are working remotely—and assumes that these two effects are additively separable. Second, our model allows the variation in our treatment variables to be induced by one exogenous shock that affects all workers in our sample, but affects some workers differently compared with others. More specifically, although all Microsoft employees were affected by COVID-19, only some employees experienced changes in their remote work status and/or the share of their collaborators that were working remotely due to Microsoft’s company-wide WFH mandate during the pandemic.

We estimate the average treatment effect for the treated (ATT) of ego remote work and collaborator remote work on all outcome measures using the following specification:

where Y i t denotes the work outcome, α i is an employee fixed-effect, τ t is a month fixed effect, D i t indicates whether employee i was a treated employee forced to work remotely in month t , s i t is the share of employee i ’s coworkers who were working remotely in month t and ϵ i t denotes the error term. Observations are weighted using coarsened exact matching (CEM) weights, and standard errors are clustered at the level of an employee’s manager. We estimate this model using data from February, April, May and June 2020. We omitted March because workers were transitioning from office work to WFH beginning in the first week of the month.

Our ability to causally identify both ATTs is predicated on a number of identifying assumptions, some of which are standard in DiD analyses and some of which are specific to our research setting. First, we assume that, for both of our ‘treatment’ variables, the time series for ‘treated’ and ‘untreated’ workers would have evolved in parallel absent the treatment. Time-series trends for different subsets of the matched sample are compared in Fig. 1 . These comparisons suggest that, for both of our treatment variables, the DiD model’s parallel trends assumption is plausible, both when measuring the effect of the treatment on network measures (Fig. 1a,c ) and when measuring the effect of the treatment on communication media measures (Figs. 1b,d ). Analogous figures for our full set of outcome variables are provided in Supplementary Figs. 5 – 19 . In all cases, the time series appear to move in parallel both before the transition to remote work, and once the transition to remote work concluded, suggesting that this identifying assumption is reasonable.

Second, we assume strict exogeneity, that is, that the timing of the switch to remote work must be independent of employees’ outcomes. As the ‘treatment group’ was all switched to WFH due to COVID-19, we are less concerned about endogeneity of treatment than we might be in other settings. However, we do need to assume that workers’ remote work status before the pandemic and the percentage of workers’ colleagues that work remotely before the pandemic are independent of how they are affected by the pandemic. This assumption would be violated if, for example, those who worked remotely before the pandemic were less likely to have unforeseen childcare responsibilities from school closures caused by the pandemic. To make this identifying assumption more plausible, we use the CEM procedure described below. If we wanted to interpret the ATTs that we estimate from those employees that started WFH due to the pandemic as average treatment effects, we would also need to assume that, conditional on the CEM procedure described below, employees’ pre-pandemic remote work status and the percentage of colleagues working remotely were independent of the effects of ego remote work and collaborator remote work on their work outcomes.

Finally, we assume that ego remote work effects, collaborator remote work effects and non-remote-work-related COVID-19 effects are additively separable. More precisely, we assume that Y i t can be written as

where RW i t is a binary variable that indicates whether employee i is working remotely at time t , s i t is the share of employee i ’s collaborators working remotely in month t , C i t is a binary variable indicating whether employee i was subject to the COVID-19 pandemic at time t and Y i t (0, 0, 0) is worker i ’s outcome at time t if all three variables were equal to 0. This assumption is an extension of the standard DiD assumption that treatment effects, cross-group differences and time-effects are additively separable and would be violated if, for example, the effects of ego remote work and/or collaborator remote work were amplified in a multiplicative manner due to other aspects of the COVID-19 pandemic (for example, childcare responsibilities or pandemic-induced changes to Microsoft’s product roadmaps). With our data, we are unable to validate the plausibility of this important identifying assumption; however, it is worth noting that causal estimates produced by standard DiD models also rely on the validity of parametric assumptions 66 .

The results from our modified DiD specification for the full set of outcomes are provided in Supplementary Tables 1 – 3 . Throughout the main text, we refer to results as insignificant when two-sided P  >0.05.

We make our results more robust by estimating our DiD model using weights generated using CEM 67 . This reweighting means that we can relax the parallel trends and exogeneity assumptions described above to only be required conditional on employee characteristics. In other words, provided that any differences in how the two groups would have evolved in the absence of the pandemic or how they are affected by the pandemic are entirely explained by the employee characteristics we match on, then the CEM-based results are valid.

The CEM procedure works as follows. Each US Microsoft employee is assigned to a stratum on the basis of their role, managerial status, seniority level and tenure at Microsoft as of February 2020. For each employee i in a stratum s that contains a mixture of employees that were and were not remote before the COVID-19 pandemic, we construct a CEM weight according to the following formula:

where n O ( n R ) is the total number of non-remote (remote) employees before the COVID-19 pandemic, \({n}_{O}^{s}\) ( \({n}_{R}^{s}\) ) is the total number of non-remote (remote) employees before the COVID-19 pandemic in stratum s and O s ( R s ) is the set of non-remote (remote) employees before the COVID-19 pandemic in stratum s . The 97 (<0.2%) employees in strata without both non-remote and remote employees before the COVID-19 pandemic were discarded from our sample. The final remote:non-remote sample ratio is 1:4.6.

Treatment effect heterogeneity

We measured treatment effect heterogeneity with respect to tenure at Microsoft (shorter tenure versus longer tenure), managerial status (manager versus individual contributor) and role type (engineering versus non-engineering). To do so, we estimated the DiD model separately for each subgroup. Our treatment effect estimates for each combination of outcome and subgroup are provided in Supplementary Tables 4 – 23 .

Alternative matching procedure

To test the robustness of our analysis, we re-estimate our main DiD specification on an alternate matched sample of employees who worked remotely before the COVID-19 pandemic, which is constructed using a more extensive matching procedure introduced in ref. 60 . In this matching procedure, we augment the set of observables that we match on to include not only time-invariant employee attributes (that is, role, managerial status, seniority and new-hire status as of February), but also time-varying behavioural attributes (that is, number of scheduled meeting hours, unscheduled call hours, IMs sent, emails sent, workweek hours, network ties, business groups connected to, cross-group connections, bridging ties, churned ties and added ties, share of time with cross-group ties, bridging ties, weak ties and added ties, and the individual clustering coefficient) as measured in June 2020. As we are matching on many more variables, there are more employees who cannot be matched, and our matched sample includes only 43,576 employees.

The motivation for this matching procedure is as follows. In a standard matched DiD analysis, control and treatment units would be matched on the basis of pretreatment behaviour. This type of matching is not appropriate in our context, given that employees who did and did not work remotely before the COVID-19 pandemic are by definition in different potential outcome states in February. Assuming that there is a treatment effect to detect, matching on pretreatment behavioural outcomes would actually make our identifying assumptions less likely to hold. However, in June 2020, both employees who were and were not working remotely before the COVID-19 pandemic were in the same potential outcome state (firm-wide remote work), and therefore matching on time-varying behavioural outcomes improves the credibility of our identifying assumptions.

Supplementary Figs. 20 and 21 show the results of our DiD model as estimated on this alternative sample. The results are qualitatively similar to those we present in our main analysis.

Collaboration network outcome definitions

Number of connections: The number of people with whom one had a meaningful interaction through at least two out of four possible communication media (email, IM, scheduled meeting and unscheduled video/audio call) in a given month. A meaningful interaction is an email, meeting, video/audio call or IM with a group of size no more than eight.

Number of business groups and cross-group connections: A business group is a collection of typically fewer than ten employees who report to the same manager and share a common purpose. We look at the number of distinct business groups that one’s immediate collaborators belong to, and the number of one’s collaborators that belong to a different business group than one’s own.

Bridging connections: Bridging connections are connections with a low value of the local constraint 9 , 18 , 42 in that period. To calculate the local constraint, we first calculate the normalized mutual weight, NMW i j t , between each pair of people i and j in each period t . If there is no connection between i and j in period t , then NMW i j t  = 0, otherwise \({\mathrm{NMW}}_{ijt}=\frac{2}{{n}_{it}+{n}_{jt}}\) , where n i t is the number of connections i has in period t . Then, for each i , j , t , we calculate the local constraint \({{\mathrm {{LC}}_{ijt}}} = {\mathrm {NMW}}_{ijt} + {\sum }_{k} {{{\mathrm {NMW}}}_{ikt}} \times {{\mathrm {NMW}}_{kjt}}\) . We define a global cut-off \(\widehat{\mathrm{LC}}\) on the basis of the median value of the constraint across all directed ties in February and categorize a connection as bridging if its local constraint is below that cut-off. We calculate the local constraint for each tie using the matricial formulae described in ref. 68 .

Individual clustering coefficient: The number of triads (group of three people who are all connected to each other) a person is a part of as a share of the number of triads they could possibly be part of given their degree. If a i j t is a dummy that equals 1 if and only if there is a connection between i and j in period t and n i t is the number of connections i has in period t , then individual i ’s clustering coefficient in period t is \({\mathrm{CC}}_{it}=\frac{2}{{n}_{it}({n}_{it}-1)}\mathop{\sum}\limits_{j,k}{a}_{ijt}\times {a}_{jkt}\times {a}_{kit}\) .

Number of churned connections: The number of people with whom a worker had a connection with in month t  − 1, but does not have a connection in month t .

Number of added connections: The number of people with whom a worker has a connection in month t , but did not have a connection in month t  − 1.

Distribution of collaboration time: In addition to unweighted network ties, we also measured the share of collaboration time that an individual spent with each of their collaborators. The number of collaboration hours is calculated by summing up the number of hours spent communicating by email or IM, in meetings and in video/audio calls. If h i j t is the number of hours that individual i spent with collaborator j in month t , then the share of collaboration time i spent with j is \({P}_{ijt}=\frac{{h}_{ijt}}{{\sum }_{k}{h}_{ikt}}\) , from which we can define the following metrics:

Share of time with own-group connections: The share of time spent with collaborators in the same business group (see the above definition), \({\mathrm{SG}}_{it}=\mathop{\sum}\limits_{j| {g}_{j}={g}_{i}}{P}_{ijt}\) , where g i is the business group that individual i belongs to.

Share of time with bridging connections: The share of collaboration time spent with collaborators with whom the local constraint (as defined under ‘bridging connections’) is below the February median \({\mathrm{BC}}_{it}=\mathop{\sum}\limits_{j| {\mathrm{LC}}_{ijt} < \widehat{\mathrm{LC}}}{P}_{ijt}\) .

Share of time with weak ties: The share of a person’s collaboration hours spent with the half of the people that they collaborate with the least during month t , \({\mathrm{ST}}_{it}=\mathop{\sum}\limits_{j| {P}_{ijt} < {P}_{it}^{m}}{P}_{ijt}\) , where \({P}_{it}^{m}\) is the time that i spends with their median connection in period t . We do not analyse the number of weak ties a person has in a given month as, by this definition, it is equal to half the number of ties they have in that month.

Share of time with added connections: The share of a person’s collaboration hours spent with people with whom they did not have a connection in the previous month, \({\mathrm{SA}}_{it}=\mathop{\sum}\limits_{j\notin {n}_{i,t-1}}{P}_{ijt}\) , where n i , t  − 1 is the set of i ’s collaborators in period t  − 1.

Entropy of an individual’s collaboration time (network entropy): The entropy 48 of the distribution of the hours spent with one’s collaborators, \({E}_{it}=-{\sum }_{j}{P}_{ijt}\times {{\mathrm{log}}}\,{P}_{ijt}\) .

Concentration of an individual’s collaboration time: A normalized version of the HHI 47 of the hours spent with one’s collaborators, \({\mathrm{HHI}}_{it}=\frac{1}{{n}_{it}-1}\left({n}_{it}\times {\sum }_{j}{P}_{ijt}^{2}-1\right)\) , where n i t is the number of i ’s collaborators in period t . The normalization ensures that HHI i t always falls between 0 and 1.

Communication media outcome definitions

Scheduled meeting hours: The number of hours that a person spent in meetings scheduled through Teams or Outlook calendar with at least one other person. Before firm-wide remote work, employees were able to participate in meetings both in-person and by video/audio call. After the shift to firm-wide remote work, all meetings take place entirely by video/audio call.

Unscheduled call hours: The number of hours a person spent in unscheduled video/audio calls through Microsoft Teams with at least one other person.

Emails sent: The number of emails a person sent through their work email account.

IMs sent: The number of IMs a person sent through Microsoft Teams.

Workweek hours: The sum across every day in the workweek of the time between a person’s first sent email or IM, scheduled meeting or Microsoft Teams video/audio call, and the last sent email or IM, scheduled meeting or Microsoft Teams video/audio call. A day is part of the workweek if it is a ‘working day’ for a given employee based on their work calendar.

Reporting Summary

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

Data availability

An anonymized version of the data supporting this study is retained indefinitely for scientific and academic purposes. The data are not publicly available due to employee privacy and other legal restrictions. The data are available from the authors on reasonable request and with permission from Microsoft Corporation.

Code availability

The code supporting this study is retained indefinitely for scientific and academic purposes. The code is not publicly available due to employee privacy and other legal restrictions. The code is available from the authors on reasonable request and with permission from Microsoft Corporation.

Change history

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Acknowledgements

This work was a part of Microsoft’s New Future of Work Initiative. We thank D. Eckles for assistance; N. Baym for illuminating discussions regarding social capital; and the attendees of the Berkeley Haas MORS Macro Research Lunch and the organizers and attendees of the NYU Stern Future of Work seminar for their comments and feedback. The authors received no specific funding for this work.

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Longqi Yang, Sonia Jaffe, Siddharth Suri, Shilpi Sinha, Jeffrey Weston, Connor Joyce, Neha Shah, Kevin Sherman, Brent Hecht & Jaime Teevan

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L.Y. analysed the data. L.Y., D.H., S.J. and S. Suri performed the research design, interpretation and writing. S. Sinha, J.W., C.J., N.S. and K.S. provided data access and expertise. B.H. and J.T. advised and sponsored the project.

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L.Y., S.J., S. Suri, S. Sinha, J.W., C.J., N.S., K.S., B.H. and J.T. are employees of and have a financial interest in Microsoft. D.H. was previously a Microsoft intern. All of the authors are listed as inventors on a pending patent application by Microsoft Corporation (16/942,375) related to this work.

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Yang, L., Holtz, D., Jaffe, S. et al. The effects of remote work on collaboration among information workers. Nat Hum Behav 6 , 43–54 (2022). https://doi.org/10.1038/s41562-021-01196-4

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DOI : https://doi.org/10.1038/s41562-021-01196-4

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Remote Working Dissertation Topic Ideas

Published by Owen Ingram at December 29th, 2022 , Revised On August 16, 2023

Due to the COVID-19 pandemic, remote working has become increasingly popular, and many businesses are considering implementing more remote employment contracts. Although working remotely offers apparent advantages for many people, it also has drawbacks and practical and legal difficulties.

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Remote employment is a new area of study, and so we have suggested some ideas for you to consider. So here is our list of remote working dissertation topics.

This Article Provides A List Of Remote-Working Dissertation Topics:

• What aspects do remote employees believe to be critical in deciding to work remotely?
• How does managing remote employees compare to managing employees who work on-site?
• How much does gender affect a worker’s decision to work remotely?
• Why are distant workers’ levels of productivity and quality
• Lower than those of on-site workers?
• What can be done to increase the output and standard of remote workers?
• Why can only tech professionals choose their place of employment?
• How can affiliate marketing make it possible for you to work from home?
• Does remote work increase or decrease the labour productivity of a company?
• The great remote work revolution winners and losers
• Back to the office or remote work? The statistics just changed
• The revolution in remote work: how to succeed from anywhere
• Why is yahoo not? Allow employees to work remotely
• Obtaining your boss, working remotely, and spending more time engaging in your favourite activities
• How can remote work be successful for everyone?
• Employee resources and advice for remote work
• Keeping the kids busy while you work from home
• Facts and figures about remote work that you should know
• Risks: Elon musk’s perspective on remote work has challenges
• The top websites for remote employment in 2022
• Genuine remote work does exist, so why did it only start to gain popularity during the covid-19 pandemic?
• Reasons why the value of remote work remains today
• The mysterious absence of remote work in job listings
• Is the “remote work window” privilege about to end? The phenomenon of remote work analysis
• The impact of distant work on information workers’ ability to collaborate
• Evaluating the expansion of remote work and its effects on effort, well-being, and work-life balance
• A review of the literature on the impact of working from home on British workers’ productivity and quality of life
• Research on the employee perceptions of remote work and cyber security in an international organization during the pandemic
• An examination of work-life balance and remote employment in the UK
• A work design perspective on practical remote work during the covid-19 pandemic
• Remote work affects women’s work-life balance and attitudes toward gender roles
• Effects of employer surveillance on distant employees
• The impact of remote work on information workers’ ability to collaborate
• An investigation into the attitudes of information technology professionals toward working from home
• An overview of the negative consequences working from home has on physical and mental health: how can we improve health?
• The effects of remote work and digital labour on individuals, businesses, and society

The success of your dissertation depends on how catchy and interesting your topic is. Take your time to consider various remote working issues before you make the final choice. Make sure that you find enough relevant material on the selected title before you start writing a dissertation . 

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• Examine effects on productivity.
• Explore work-life balance challenges.
• Investigate technology implications.
• Analyze remote team dynamics.
• Consider remote management strategies.
• Assess impacts on mental health. Choose a topic aligning with your field and research interests.

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The impact of remote working on employee productivity during COVID-19 in the UAE: the moderating role of job level

Journal of Business and Socio-economic Development

ISSN : 2635-1374

Article publication date: 19 January 2023

Issue publication date: 19 September 2023

The purpose of this study is to examine the various factors that influence the productivity (PR) of employees who worked remotely in the United Arab Emirates (UAE) during the COVID-19 pandemic.

Design/methodology/approach

This study adopts a quantitative approach to analyze data collected online from 110 respondents using the snowball sampling technique during the pandemic. The analysis of the data is conducted using the structural equation modeling (SEM) technique of Smart PLS (Partial least squares) to evaluate the direct and moderating variables.

The results indicate that direct variables such as workload, job satisfaction, work–life balance and social support have a significant positive impact on employee PR in the UAE. However, the analysis of the moderating variable indicates that job level is not a significant moderator of the above relationships. The findings, generally, provide support for social exchange theory.

Practical implications

The findings of this study will help businesses of various domains in a variety of industries in understanding the core factors that should be considered to enhance the overall PR of their employees while working from home. Businesses can achieve their organizational goals by ensuring steady growth even during uncertain times.

Originality/value

This paper answers the question of whether remote working affects employee PR during the pandemic in an emerging market, namely the UAE. The current study contributes to the existing literature by combining the variables investigated in previous studies into a single study and by considering job level as a moderator variable.

• Remote working
• Productivity
• COVID-19 pandemic

Kurdy, D.M. , Al-Malkawi, H.-A.N. and Rizwan, S. (2023), "The impact of remote working on employee productivity during COVID-19 in the UAE: the moderating role of job level", Journal of Business and Socio-economic Development , Vol. 3 No. 4, pp. 339-352. https://doi.org/10.1108/JBSED-09-2022-0104

Emerald Publishing Limited

Copyright © 2023, Dania M. Kurdy, Husam-Aldin Nizar Al-Malkawi and Shahid Rizwan

Published in Journal of Business and Socio-economic Development . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

With the outbreak of the COVID-19 pandemic, several governments throughout the world were forced to implement lockdown measures to curb the spread of Coronavirus. Remote working was one of the measures implemented during the lockdown. It was adopted by all firms in developing and developed countries across a wide range of industries to protect their employees, while also maintaining business operations to mitigate any possible losses as much as possible. Except for a few businesses that relied on remote working before the pandemic, virtually, everyone was unfamiliar with this decision. This topic has not been adequately addressed in the literature, and few studies have examined the impact of remote working on the productivity (PR) of employees working in the private and public sectors in general, and in the United Arab Emirates (UAE) in particular.

Businesses in a variety of industries have faced challenges over the past few years as a result of the COVID-19 pandemic. The pandemic affected households, organizations and societies at all levels ( Carroll and Conboy, 2020 ). Thus, to maintain businesses' PR, an adequate framework has been created by employers to continue operations remotely. Consequently, the fast adoption of working remotely has impacted employees' daily lives as well as their relationships with their families and colleagues. This has resulted in numerous types of depression, and studies have shown that depression is closely related to employee PR ( Matli, 2020 ). Besides this, studies conducted during the pandemic have identified a wide range of other problems that have impacted employees' PR. Such issues include excessive workload (WKL), low job satisfaction (JS) and poor work–life balance (WLB). Therefore, this study aims at examining the impact of working remotely on employee PR using potential variables such as (WKL), JS, WLB and social support (SS), while using job level (JL) as a moderator for the direct relationships of the above variables with employee PR. It is worth mentioning that JL has rarely been utilized as a moderator variable in previous studies, making the present study more significant. In addition, the analysis of the participants' responses about their remote working experiences will contribute to existing studies on the effectiveness of remote working.

More specifically, this study intends to provide insights into the impact of working remotely on employee PR by studying the relationship between WKL, JS, WLB and SS during COVID-19 within the UAE context. This is because working remotely during COVID-19 affected the personal and professional lives of employees across the globe ( Donnelly and Johns, 2021 ).

The purpose of this study is to answer the central research question of whether remote working affects employee productivity during the pandemic in the United Arab Emirates. Although previous studies investigated the impact of the variables included in this study (WKL, JS, WLB and SS) individually, no study combined all of these variables in a single study and tested the moderating role of JL. For instance, Dick et al . (2020) , Matli (2020) and Wang et al . (2021) investigated the impact of WKL on remote working, whereas other studies including Bailey and Kurland (2003) and Bartel et al . (2007) examined the relationship between JS and remote working. Similarly, Lowry et al. (2006) investigated communication during remote working, while Dubrin (1991) linked JS with teleworker PR vs. in-house workers. Feldman and Gainey (1997) investigated WLB, while Koehne et al . (2012) and Raišienė et al . (2020) addressed SS. Furthermore, Baudot et al. , 2020 and Toscano and Zappalà (2020) investigated the impact of remote working on social isolation and stress during COVID-19.

An extensive review of relevant studies conducted in different parts of the world shows that several studies were conducted to examine various factors that influence employee PR when working remotely. However, potential factors such as WKL, JS, WLB and SS were previously tested separately and not combined in a single study. Moreover, there is a significant gap in the previous literature since employee PR was not tested using “job level” as a moderating variable (MV). Thus, this study attempts to address the gap in the literature by including JL as a moderator to determine its significance for the relationship between WKL, JS, WLB and SS and employee PR. This enhances the significance of this study as it will help businesses in understanding the PR of their employees operating at different levels within an organization, such as operational, tactical and strategic levels among others.

2. Literature review and hypothesis development

Remote working, often known as distance working, is a type of work process in which employees operate away from their office, either from home or from any other location. According to Elshaiekh et al . (2018) , employees who work from home are self-disciplined and self-motivated and they choose to work remotely either to stay close to family or to avoid issues related to social distancing. However, challenges frequently encountered while working remotely include poor time management, social isolation from colleagues and change in daily routine. Moreover, it is difficult to control the working hours at home, which could have a detrimental impact on family relationships ( Elshaiekh et al ., 2018 ). The concept of remote working is not new, and it has been employed for a long time, as evidenced by various studies before the pandemic that erupted in 2019. The first instance of remote work occurred in 1970 amid the oil crisis when Jack Nilles and his colleagues published their report calculating the potential savings from the decreased locomotion ( Golden et al ., 2008 ). Because remote workers operate away from their managers and leaders, they are supervised and assessed differently than other employees who work face-to-face with their managers. According to past studies, remote workers face fewer institutional controls than face-to-face workers ( Elshaiekh et al ., 2018 ). Recently, using a sample of 526 respondents from the information technology (IT) industry in India, Patanjali and Bhatta, 2022 discovered that nearly two-thirds of IT employees report greater PR while working from home. The authors attributed this result to various factors, including the Hawthorne effect, increased working hours and a better working environment (because of lesser meetings, more flexible working hours and a better WLB). The next sub-sections discuss the different variables included in this study and develop the research hypotheses.

2.1 Workload (WKL)

Following previous studies such as Dick et al . (2020) , Matli (2020) and Wang et al . (2021) , this study explores the impact of WKL on employee PR. The WKL is one of the variables employed in those studies to examine the impact of remote working. Wu and Chen (2020) examined the impact of working from home on WKL and PR. The authors revealed the results of a nationwide survey to assess the WKL and PR of workers working from home. According to the findings, an increase in working hours of around three hours per week produces a decline in employee PR due to stress and pressure. However, Felstead and Henseke (2017) found that remote workers tend to work harder and longer and “are more committed to the organization, are more enthusiastic about the job, and exhibit higher levels of job satisfaction, and therefore expend more effort (as suggested by social exchange theory)” (p. 200). More recently, Wang et al. (2021 , p. 33) stated that “employees with higher workload and those who are under more intensive monitoring will experience less procrastination during the period of working from home and, therefore, will have higher levels of performance”.

Workload significantly affects employee productivity during remote working.

2.2 Job satisfaction (JS)

Previous research has employed the expectation disconfirmation theory (EDT) in different settings, including marketing, education, information technology, hospitality and tourism ( Carraher-Wolverton, 2022 ). Carraher-Wolverton (2022) recently applied EDT for remote work. The author proposed that EDT can be used to better understand remote work, employees' level of satisfaction, and their intention to continue working remotely. Working from home is one of the teleworking features that is associated with JS as it promotes employees' flexibility and independence, which usually leads to a high level of JS ( Bailey and Kurland, 2003 ; Yu and Wu, 2021 ), and, as a result, PR. For instance, Bartel et al . (2007) and Kowalski et al . (2022) found that employees working from home report higher levels of JS than those working face-to-face.

Job satisfaction significantly affects employee productivity during remote working.

2.3 Work–life balance (WLB)

According to Clark (2000, p. 751) , work–family balance can be defined as “satisfaction and good functioning at work and at home, with a minimum of role conflict”. Clark (2000) developed the work–family border theory (W-FBT), which proposes that “‘work’ and ‘family’ constitute different domains or spheres which influence each other” (p. 750). This theory provides a useful theoretical insight into the relationship between WLB and remote working. Moreover, considering the social exchange theory (SET), Hasan et al . (2021) argued that when employees feel autonomous, they have a better life-work balance and are more committed to their organizations.

According to Feldman and Gainey (1997) , employees choose to telework to spend more time with their families and maintain a WLB. This largely causes an increase in employees' desire for teleworking and drives them to look for jobs at companies that offer the option of teleworking. Shareena and Mahammad (2020) found that remote working offers time flexibility, especially by saving time spent driving to and from the office or meetings. Therefore, the time saved can be spent with family, resulting in a better WLB. Furthermore, Amabile and Kramer (2013) concluded that remote working saves travel time that may be spent on personal matters, which improves PR. Patanjali and Bhatta, 2022 recently provided evidence that working from home creates a better work environment and WLB, improving employee performance (see also Haridas et al ., 2021 ).

Work-life balance significantly affects employee productivity during remote working.

2.4 Social support (SS)

Despite the advancements in technology and telework's technical progress, teleworkers still miss the “social support”. According to the social exchange theory, organizations can optimize their employees' satisfaction and commitment by showing that they care about them and support their family lives ( Hasan et al. , 2021 ). Bentley et al . (2016) reported that during teleworking, organizational SS mitigates social isolation, which in turn increases JS and performance. Koehne et al . (2012) conducted a comprehensive study using semi-structured interviews to identify the various challenges that teleworkers face during distance working. The study's findings showed a negative effect of SS owing to the absence of face-to-face communication since employees have no interaction with colleagues. The lack of SS reduces their PR. This suggests that providing SS to teleworking employees will significantly improve their PR.

Social support significantly affects employee productivity during remote working.

2.5 Job level

Generally, an organization has three levels of control, including operational (basic level), tactical (middle level) and strategic (highest level). Since each employee's contribution is important to achieving organizational objectives, businesses need to evaluate employees at all levels. As a result, JL has grown in importance in recent years in business research. This is because a better evaluation of employees for their roles, responsibilities and PR can significantly contribute to the overall success of businesses in various sectors. JL has been used as a moderator variable in various studies. For instance, Nguyen and Malik (2022) employed JL to examine its moderating effect in analyzing the impact of artificial intelligence (AI) service quality on AI satisfaction and JS. The study found that AI service quality influences AI satisfaction only in the nonsupervisory group, although it has an impact on JS at both nonsupervisory and supervisor/managerial levels.

Although prior studies have shown that JL affects employee PR during remote work ( Matli, 2020 ; Spagnoli et al ., 2020 ; Dick et al ., 2020 ; Wang et al ., 2021 ), little attention has been paid to the moderating role of JL on the relationship between employee PR and other variables included in this study (i.e. WKL, JS, WLB and SS).

Previous studies have examined JL in terms of its direct relationship with the PR of employees ( Skitmore and Sariathi, 2003 ; Ilies et al ., 2007 ; Lee and Choo, 2011 ; Zhao and Namasivayam, 2012 ; Mihelič, 2014 ; Lu et al ., 2016 ), while other studies have explored various types of conflicts that employees face at different JLs ( Skitmore and Sariathi, 2003 ; Johns, 2006 ; Bhar and Padmaja, 2014 ). Hence, there is a dearth of literature that has examined the moderating role of JL as pointed out by earlier studies.

Job level moderates the relationship between WKL/JS/WLB/SS and employee productivity during remote working.

2.6 Productivity (PR)

Several studies have previously explored the impact of remote working on PR. Baudot et al. , 2020 conducted a comprehensive study among Amazon employees in the United States. The primary purpose was to evaluate employee and subordinate PR during the obligatory teleworking throughout the COVID-19 lockdown. The study revealed that when participants telework, their PR and the PR of their subordinates improve. Moreover, employees are willing to spend more time on job tasks as they are working from home and can save time commuting. In addition, when given the chance to select the working mode, respondents indicate a preference for remote working.

It is important to highlight that various study outcomes have been seen throughout the past few years. For example, Toscano and Zappala (2020) investigated the impact of remote working on employee PR from various perspectives. The data were collected from 265 respondents from various areas of life. They found that employee PR decreases while working remotely during the pandemic. However, other studies such as Patanjali and Bhatta, 2022 and Prasetyaningtyas et al . (2021) showed that working from home increases employee PR.

To measure employee PR, respondents were asked whether remote working during the pandemic affected the following: (1) personal work PR, (2) subordinate work PR, (3) actual working hours before COVID, (4) formal working hours before COVID, (5) actual working hours after COVID and (6) formal working hours after COVID.

Based on the aforementioned literature review and consistent with the relevant underpinning theories such as social exchange theory, expectation disconfirmation theory, and work-family border theory, we propose the following conceptual framework (see Figure 1 ).

3. Methodology

3.1 data collection, sampling and demographic profile of respondents.

The data for this study were collected online through Google Forms, while the questionnaire was distributed to participants via WhatsApp. Before questionnaire dissemination, as an ethical consideration, participants were informed that their responses will be treated continentally and no details will be shared with any third parties. The questionnaire included the following statement “By returning the questionnaire fully answered, your consent is implied in this instance and all answers will be analyzed solely for the purpose of this study”.

In this study, a nonprobability sampling technique known as the snowball sampling technique was used, as is common in most business research. First, we invited a selected set of participants who met the study's requirements. Participants were also encouraged to spread the questionnaire to others who fit the respondents' profile and are eager to participate. The distribution of the questionnaire was halted when the target number of respondents was attained.

In this research, a total of 110 respondents who worked remotely during the pandemic were included. The sample size is deemed appropriate as similar studies such as Haridas et al . (2021) who used a sample of 115 respondents to examine the impact of telecommuting on IT employee PR in India during the COVID-19 pandemic. All respondents in our study worked in the public and private sectors. It is important to note that the study's respondents were chosen from the two major emirates of the United Arab Emirates, namely Abu Dhabi and Dubai. Since the study was conducted at the outset of the pandemic, a small number of staff began working remotely at that time. A total of 41% of respondents were employed in the education sector, 33% in the financial sector, 19% in different government entities and 7% in IT. In terms of JL, 53 of the 110 respondents worked at the managerial level, 35 at the supervisory level and 22 at the entry-level. Almost 68% of respondents were between the ages of 28 and 40 years and lived in the UAE with their families and children.

3.2 Questionnaire and measurement scales

Before the final survey, a pilot test was conducted to test the validity and reliability of each question (item). A total of 12 respondents were approached and all pilot test participants confirmed their understanding of the questionnaire before starting the final survey.

The questionnaire was divided into two sections, five measurement scales and 20 items (questions). Respondents were asked at the beginning of the questionnaire if they worked remotely during the COVID-19 pandemic. Only those who answered “yes” were allowed to proceed with the main survey. The questionnaire was divided into two sections. Section 1 included fourteen items, with three of which related to “job satisfaction (JS)”, “work–life balance (WKL)” and “productivity (PR)” and two each related to “workload (WKL)” and “social support (SS)”. Similarly, Section 2 included seven items related to the respondents' demographic profile and JL. To collect data, a five-point Likert scale was used with 1 denoting “strongly disagree” and 5 denoting “strongly agree”.

4. Data analysis

The structural equation modeling (SEM) technique of Smart PLS was used to analyze the study's data. Data analysis in Smart PLS was conducted in two stages. The first stage comprises the evaluation of the measurement model also known as the outer model, while the second stage consists of evaluating the structural model, also known as the inner model.

4.1 Evaluation of the measurement (outer) model

Hair et al . (2014) suggest that the measurement model evaluation comprises four main assessments. These include indicator reliability (outer loadings), composite reliability, convergent validity (also known as average variance extracted (AVE)) and discriminant validity. These four assessments of the measurement model are discussed below.

According to Urbah and Ahleman (2010) , Hair et al . (2014) and Hair et al. (2017) , values of 0.70 and above are acceptable for indicator reliability and composite reliability, while 0.50 and above for convergent validity. Similarly, discriminant validity is measured by the strength of outer loadings, i.e. items in a variable should load strongly on intended constructs and weakly on unintended constructs. Consolidated results for the first three assessments of the measurement model of the study are combined in Table 1 , where the values of outer loadings, Cronbach's alpha, and composite reliability exceeds 0.70, while convergent validity (AVE) exceeds 0.5 and above.

Similarly, as shown in Table 2 , all the items of variables loaded strongly on intended constructs and weakly on unintended constructs, confirming the discriminant validity of the measurement model.

As shown in Tables 1 and 2 , the values of the four key assessments of the measurement model are in line with the standard evaluation criteria, confirming the study's measurement model's reliability and validity.

4.2 Evaluation of the structural (inner) model

The second stage of data analysis in Smart PLS is the evaluation of the structural model which aims to test the relationships between the dependent, independent, and MVs. The structural model is evaluated using path coefficients ( β ), t -statistics and p -values derived from the Smart PLS bootstrapping method. The assessments indicate the strength of the relationship between different variables to test the study's various hypotheses ( Rifai and Hasan, 2016 ). Cohen (1992) defines the evaluation of path coefficient significance as 0.02 being weak, 0.15 being acceptable and 0.35 being strong. The acceptable values of t -statistics and p -values are 1.96 and 0.05, respectively, as suggested by Rifai and Hasan (2016) .

4.2.1 Moderation (interaction effect)

The MV or the moderator as defined by Hair et al . (2014) is a third variable that impacts the relationship between two variables. In Smart PLS, the moderating role of a variable is measured through the value of the interaction effect ( Latan and Ramli, 2013 ). According to the standard evaluation criteria of Ghozali and Latan (2015) and Chin et al . (2003) , interaction effect values of 0.02, 0.15, and 0.35 are considered as weak, moderate and strong, respectively.

It is important to note that including a moderator variable is crucial in business research for testing the relationship between independent and dependent variables. One of the study's main contributions is the inclusion of “job level” as a MV, to determine how WKL, JS, WLB and SS affect the PR of employees working at different levels of an organization. This study includes four hypotheses of moderating relationships to find out the significance of JL as a moderator.

Table 3 presents the results of the structural model evaluation to test all eight hypotheses of this study. This includes four direct relationship hypotheses and four indirect (moderating) relationship hypotheses. Results show that all four direct relationship hypotheses are significant which means that WKL, JS, WLB and SS have a significant positive impact on employee PR during remote work in the UAE.

The first hypothesis ( H1 ) was used to measure the impact of WKL on PR. The Smart PLS analysis shows a beta value of 0.16 and a t -statistic and a p -value of 2.96 and 0.01, respectively. All three values are significant and meet match the standard evaluation criteria of Cohen (1992) and Rifai and Hasan (2016) . Thus, H1 is supported, consistent with Wu and Chen (2020) , and in line with allocation of time and social exchange theories. Similarly, the second hypothesis ( H2 ) was utilized to test the relationship between JS and PR. This relationship has a β value of 0.873, a t -statistic of 4.294 and a p -value of 0.00, consistent with the foregoing evaluation criteria. This confirms that H2 is also significant, in line with previous studies ( Dubrin, 1991 ; Haloks and Bousinakis, 2010 ) and consistent with EDT. The third hypothesis ( H3 ) examined the relationship between WLB and PR. Results show that this relationship has a β value of 0.372, a t -statistic of 4.294 and a p -value of 0.00. This hypothesis is also supported and in line with the previous studies of Feldman and Gainey (1997) , Shareena and Mahammad (2020) and Hasan et al . (2021) . The finding also provides support for the SET. The last hypothesis of direct relationship ( H4 ) explored the impact of SS on employee PR. The analysis provided a beta value of 0.120, a t -statistic of 2.30, and a p -value of 0.00. Thus, H4 is significant, similar to earlier findings by Baruch-Feldman et al . (2002) and Park et al . (2004) . This finding is also in line with the SET, which predicts that organizations can optimize employee satisfaction and commitment by caring for them and providing them with support for their family lives, which in turn improves their PR.

After the evaluation of direct relationships, the indirect (moderating) relationships are assessed. An analysis of Smart PLS confirms that all four moderating relationships of moderating role are insignificant with t-statistics being less than 1.96 and p -values greater than 0.05. These results do not meet the standard evaluation criteria of moderation (interaction effect) as suggested by Chin et al . (2003) and Ghozali and Latan (2015) , concluding that JL does not moderate the relationship between WKL, JS, WLB and SS and employee PR during remote working in the UAE. Figure 2 depicts a diagrammatic illustration of the testing of all eight hypotheses of the study, with the green color denoting significant hypotheses and the red color representing nonsignificant hypotheses.

5. Conclusion and implications of the study

The primary objective of this study was to examine the various factors that influence employees' PR while working remotely in the UAE during the pandemic. For this purpose, based on relevant theories and a thorough assessment of the literature, potential variables such as WKL, JS, WLB and SS were identified and a total of eight hypotheses were formulated, four of which were direct relationships and four were indirect (moderating) relationships.

The result of this study reveals a positive impact of WKL, JS, WLB and SS on employee PR. The analysis, however, shows that the JL does not play a moderating role between the independent variables (WKL, JS, WLB and SS) and the dependent variable (employees' PR).

The findings of this study provide several policy implications for employers in the UAE's private and public sectors. Firstly, employers should facilitate their employees with such measurements that contribute to overall JS, since a higher level of JS positively affects employee PR. Secondly, flexible work settings/timings should be provided to ensure that employees have ample time for both their personal and professional lives, as WLB is positively associated with employee PR. Moreover, SS for employees is also essential since it contributes to the on-job PR of the employees. Lastly, the study's findings reveal that during remote working, employees can take on additional WKLs, increasing their PR. This means that employers should allow employees to work from home if the nature of their job does not need their presence in the office. This can enhance their overall PR because the time spent commuting can be utilized to perform office tasks. This suggests that firms might consider adopting a hybrid working model to enhance employee PR.

6. Limitations and future research

Inevitably, the current study has some limitations. For instance, the findings of this study cannot be generalized to other countries that lack similar features as the UAE. It is important to note that the UAE has one of the most advanced workplace infrastructures among Arab countries. Therefore, teleworking was easily adopted and implemented during the pandemic. However, this does not apply to other countries that lack technological infrastructures and even struggle with electricity and Internet connectivity. Thus, we recommend extending this study to other countries in the MENA region to ensure that the findings are generalized. Moreover, we recommend a “cross-cultural” study to examine the cultural factors that may have an impact on teleworking.

Finally, the research was conducted during a period when teleworking was mandatory rather than voluntary, thus, there was no choice but to work remotely during the pandemic. A detailed study with comparative analyses of teleworking before, during and after the COVID-19 pandemic is recommended so that more reliable results on several dimensions to test the PR of employees working in different sectors can be obtained.

Conceptual framework of the study

Graphical representation of direct and indirect relationships

Outer loadings, composite reliability and convergent validity of the measurement model

Discriminant validity of the measurement model

Evaluation of the structural model of the study

Amabile , T. and Kramer , S. ( 2013 ), “ Working from home: a work in progress ”, Harvard Business Review , available at: https://hbr.org/2013/07/working-from-home-a-work-in-pr ( accessed 15 July 2020 ).

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Acknowledgements

The authors thank the anonymous reviewer's diligent reading of the manuscript as well as the insightful comments and suggestions. The authors would also like to acknowledge and thank Swasan Al Khayyat and Ali El Khatib of the University of Wollongong in Dubai for their assistance in data collection.

Corresponding author

About the authors.

Dania M. Kurdy is a PhD scholar at the British University in Dubai. She is the founder and CEO of Dr. Business Consultant. She holds a bachelor degree in Business Administration and Commerce (accounting major) and a master degree in Business Administration. Dania is an adjunct lecturer in accounting, finance, and auditing at a well-known university in the UAE and a trainer in accounting, finance and taxation. She is a Certified Fraud Examiner (CFE) and a registered Tax Agent with the Federal Tax Authority (FTA) of UAE. Dania is a consultant for the Financial Reorganization Committee under the Ministry of Finance; she is participating in the amendment of the bankruptcy law in UAE with the World Bank.

Husam-Aldin Nizar Al-Malkawi is a Professor of Finance at the Faculty of Business and Law, The British University in Dubai, UAE. He received his Ph.D. from the University of Western Sydney, Australia. Prof. Al-Malkawi is a Certified Islamic Finance Executive (CIFE). He has worked in various capacities at different institutions in the UAE, Saudi Arabia, Jordan and Australia. He has received several awards for excellence in research including Emerald Literati Award and outstanding contribution in reviewing. He has published over 40 research papers in international journals and conference proceedings. Prof. Al-Malkawi serves as a reviewer for several international journals. His works have appeared in journals such as Economic Modeling, Research in International Business and Finance, Physica A: Statistical Mechanics and its Applications, Managerial Finance, Business Ethics: A European Review, Humanomics, Journal of Emerging Market Finance, African Journal of Economic and Management Studies, and Journal of Risk and Financial Management , among others. His research interests include Islamic finance, corporate governance, corporate financial policy, FinTech, financial economics and applied econometrics.

Shahid Rizwan, PhD, is a UAE-based business management professional having over 15 years of industry experience with leading business organizations of various domains. He completed his PhD in Management from the Universiti Kuala Lumpur Business School, Malaysia. Prior to this, he completed an MBA (Master of Business Administration) and a PGD (Post Graduate Diploma) in Islamic Finance, both from Abu Dhabi, UAE. His research interests include retail business, consumer behavior, marketing and religiosity.

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THREE ESSAYS ON REMOTE WORK AND REGIONAL DEVELOPMENT

Ryan Wallace , University of Massachusetts Amherst Follow

Author ORCID Identifier

https://orcid.org/0000-0003-4723-9409

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Regional Planning

Year Degree Awarded

Month degree awarded, first advisor.

Henry C. Renski

Second Advisor

Ina Ganguli

Third Advisor

Fourth advisor.

Charles S. Colgan

Subject Categories

Regional Economics | Urban Studies and Planning

This dissertation is comprised of three papers that collectively explore the relationship between remote work, or people that work from anywhere, and regional economic development. The first paper measures remote occupational employment in the United States with Census microdata and a shift-share model to decompose the share of occupational growth attributed to remote work. Findings indicate remote work has grown significantly since 2000, with the most pronounced growth in high skill jobs. The second paper uses a mixed-methods design to understand the role of remote work in migration decisions. It concludes that remote work arrangements enable access to employment opportunities that are unavailable locally and supports certain migration. The third paper uses a cross-sectional design and spatial econometrics to investigate the influence of amenities on the concentration of remote workers across a sample of US counties. The findings indicate that amenities, especially recreational and cultural, play a powerful role in explaining variations of remote worker concentrations across counties and that amenities play different roles in the hierarchy of county sizes. The dissertation concludes with a discussion of the implications for place and offers avenues for future inquiry.

https://doi.org/10.7275/15232842

Recommended Citation

Wallace, Ryan, "THREE ESSAYS ON REMOTE WORK AND REGIONAL DEVELOPMENT" (2019). Doctoral Dissertations . 1774. https://doi.org/10.7275/15232842 https://scholarworks.umass.edu/dissertations_2/1774

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Guo, Jiabao, Emilio Ergovan, and Victor Seitl. "Remote work and leadership during the Covid-19 Pandemic : An exploratory study on how remote work is affecting leadership styles and employee motivation." Thesis, Jönköping University, IHH, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-52953.

Hedström, Philip, and Munoz Mario Gonzalez. "Remote Work’s Effect on Motivation : A study of how remote work during the covid-19 pandemic has affected employee motivation." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301642.

Tunholm, Hanna, and Johanna Lindor. "Distansarbete efter covid-19- ett sätt att öka organisationens attraktivitet : En kvalitativ fallstudie gällande anställdas upplevelser av distansarbete i kontexten av covid-19." Thesis, Jönköping University, Högskolan för lärande och kommunikation, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53158.

Sernhede, Saralie. "Apart not alone while we #workfromhome: Tweeters Online Communal Coping with Involuntary Remote Work During COVID-19." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23730.

Kurtagic, Anessa. "Working With Agile Methodologies During The Covid-19 Pandemic : A qualitative study of an agile teams' transition to remote work from home as a result of the Covid-19 pandemic." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-106923.

Jacob, Lindström, and Flou Julia. "How enforced remote work during Covid-19 affects employee engagement and how remote work could be used in the future. : a case study exploring the effects of remote work on engagement in two banks." Thesis, Högskolan Kristianstad, Fakulteten för ekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-22182.

SIETSES, SAMANTHA, and FERIDE DIKME. "Client Relations on the Digital Workplace : A case study on how the consultant-client relationship is affected by remote work during Covid-19." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300079.

Thorstensson, Esra. "The impact of Working from Home on productivity during COVID-19 : A Survey with IT Project Managers." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84703.

Sigeman, Henrik, and My Adolfsson. "Maintaining well-being when working remotely : Work habits of employees at a geographical IT office in Sweden during the COVID-19 pandemic, their perceived well-being and productivity." Thesis, Malmö universitet, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43184.

Light, Mark D. "Exploring the Adaptability of Ohio State University Extension County 4-H Professionals to an All-Digital Setting During the COVID-19 Remote Work Period Based on Selected Variables and Their Relationship to Change Style Preferences." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu161895890913408.

Eriksson, Elias, and Arpine Petrosian. "Remote Work - Transitioning to Remote Work in Times of Crisis." Thesis, Umeå universitet, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172779.

Hallin, Henning. "Home-Based Telework During the Covid-19 Pandemic." Thesis, Mälardalens högskola, Akademin för hälsa, vård och välfärd, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-49180.

Abdullah, Nabil, Linnéa Rossander, and Damilola Samuel. "Telecommuting and Motivation during the COVID-19 pandemic." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54441.

KARACHATZIS, XENOFON, and LIKHIT PARAMESHWARAPPA. "Innovation & Remote Work: A window of opportunity or an inevitable compromise? : An identification and evaluation of innovation aspects in remote work conditions." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300122.

Brorsson, Malin, and Philip Karlsson. "Chefers inställning till fortsatt distansarbete efter covid-19-pandemin." Thesis, Högskolan Väst, Avdelningen för psykologi, pedagogik och sociologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-16624.

Abrahamsson, Evelina, and Axelsson Jonathan Ollander. "Virtual leadership: Moving teams online during the covid-19 crisis." Thesis, Linnéuniversitetet, Institutionen för organisation och entreprenörskap (OE), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-95329.

Telin, Steven, and Nebil Esmail. "Managing Remote Projects During a Crisis : Game-development and Manufacturing Projects Response to COVID-19." Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185058.

Assaf, Nebras, and Ashish Singh. "The Role of Homecare services to Empower Elderly during COVID-19." Thesis, Högskolan i Gävle, Avdelningen för socialt arbete och kriminologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-36654.

Kokutensa, Angelica. "Stress and coping strategies among distance working employees during covid-19 : 1. What kind of stressors are perceived among distance working employees associated with their work situation during the covid-19 crisis?2. How do employees cope with stress associated with their work situation during the covid-19 crisis?" Thesis, Mälardalens högskola, Akademin för hälsa, vård och välfärd, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-55973.

Jonsson, Masnikosa Clara. "Studenthälsa på distans : En intervjustudie om omställningen under covid-19." Thesis, Malmö universitet, Malmö högskola, Institutionen för socialt arbete (SA), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43365.

Gerdin, Beatrice, and Emilia Johansson. "Chefers inställning till distansarbete : Hur vill företag arbeta efter Covid-19?" Thesis, Jönköping University, Högskolan för lärande och kommunikation, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53159.

Chen, Yulu. "Spatial Temporal Analysis of Traffic Patterns during the COVID-19 Epidemic by Vehicle Detection using Planet Remote Sensing Satellite Images." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1609843145639886.

Rosquist, Oscar. "Adapting to the new remote work era : Improving social well-being among IT remote workers through scheduled digital social interactions." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298027.

Hallin, Henning. "Leadership at a distance : A qualitative study of managerial work at a distance during the COVID-19 pandemic." Thesis, Mälardalens högskola, Akademin för hälsa, vård och välfärd, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-56024.

Bakic, Jovan. "Supporting informal awareness in order to facilitate informal communication in remote work contexts." Thesis, Malmö universitet, Institutionen för konst, kultur och kommunikation (K3), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43188.

Oyegun, Caleb. "Supporting social workers transition to remote work : A design concept for tackling communication challanges on social workers digital practices." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-44965.

Bankel, Selma, and Tove Rosengren. "Onboardingprocessen under Covid-19-pandemin : en kvalitativ fallstudie kring introduktionen av nyanställda på distans." Thesis, Högskolan Väst, Avd för företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-16589.

Karlsson, Johan, and Fredrik Meyer. "Säljarbete på distans, hur fungerar det? : En kvalitativ tvärsnittsstudie om Covid-19 pandemins påverkan på säljkårer." Thesis, Linköpings universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176944.

Bruhner, Carl Magnus, and Frida Carlstedt. "Arbetsplatsen efter pandemin : En studie om medarbetares upplevelse av distansarbete." Thesis, Linköpings universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176524.

Andersson, Oscar, and Genefra Pamin. "FROM ABRUPT CHANGE TO DAILY ROUTINES : The organizational effect of one year with COVID-19." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185664.

Garrison, Debora. "“We’re Sinking and We’re Sinking Quick”: Family and Feeding Work During the COVID-19 Pandemic for Single, White, Middle-Class Mothers." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/etd/3893.

Möll, Theodor, and Joakim Arnberg. "Communication Over Virus-Induced Distance : A Qualitative Study on the Implications of English Language Teaching During the COVID-19 Pandemic." Thesis, Högskolan i Halmstad, Akademin för lärande, humaniora och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44593.

Dackeby, Johan, and Johanna Hagbom. "Att leda på distans : En kvalitativ studie om styrning inom kunskapsorganisationer vid omställning till distansarbete." Thesis, Linköpings universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-179474.

Ingemarsson, Johanna. "EFL Teachers’ Experiences Teaching Online using ICT : A Case Study of the Transition from Classroom Teaching to Online Teaching during the COVID-19 Pandemic." Thesis, Karlstads universitet, Institutionen för språk, litteratur och interkultur (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84446.

Brooks, Philip. "Motivation in Crisis? : An investigation of L2 English teacher perceptions of both learner and teacher motivation and teachers’ approaches for prompting student motivation during emergency remote teaching in Sweden." Thesis, Malmö universitet, Malmö högskola, Institutionen för kultur, språk och medier (KSM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43509.

Maparzadeh, Milad. "Patients’ perspective of digital healthcare : Social implications during a digital healthcare meeting." Thesis, Högskolan Väst, Avd för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-16811.

Lindgren, Frida, and Emma Nyberg. "HOW TO MANAGE SELF-LEADERSHIP IN REMOTE ENVIRONMENTS : A qualitative study made on Swedish medium and large-sized organizations." Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184992.

Berglund, Oscar, Hugo Widorson, and Viktor Segerqvist. "Aspects of Crisis Management to Consider when Operating Remotely : A multiple case study on how companies adjust into a remote setting as a result of the COVID-19 pandemic." Thesis, Jönköping University, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53062.

Viklund, Carolin. "Nyanställd på distans : Introduktion i en kunskapsorganisation med begränsad tillgång till fysiska möten." Thesis, Stockholms universitet, Institutionen för pedagogik och didaktik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-194468.

Persson, Filip, and Daniel Karlsson. "Ett förändrat samarbete mellan kollegor : En fallstudie av Maxkompetens Växjökontor och hur distansarbete påverkat deras samarbete under Covid-19 pandemin." Thesis, Linnéuniversitetet, Institutionen för organisation och entreprenörskap (OE), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104797.

Arriola, Guillén Marcela, and Motta Hermelinda Clemencia Neyra. "Análisis en la eficiencia del trabajo remoto en el Poder Judicial." Master's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/654024.

Looström, Axel, and William Alouch. "Är covid-19 en katalysator för ett paradigmskifte gällande distansarbete? : En jämförande kvantitativ surveyundersökning mellan chefers och medarbetares vilja till digitalt distansarbete." Thesis, Uppsala universitet, Informationssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-434790.

Schützler, Felicia, and Oscar Reis. "Are you in the mood for a virtual fika? : A single-case study on Jönköping International Business School." Thesis, Jönköping University, IHH, Organisation, Ledarskap, Strategi och Entreprenörskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-52609.

Frisk, Sebastian, and Andreas Fransson. "How the pandemic triggered digital transformation madness." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185665.

Rylander, Samuel. "The new normal for Swedish Municipalities : Assessing the impact of working from home." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-188005.

Kakoulidis, Sharmineh, and Dekyi Hederstedt. "How the Covid-19 pandemic has affected the leadership and the direction of the organization." Thesis, Mittuniversitetet, Institutionen för kvalitets- och maskinteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42964.

Björkman, Anna, and Rebecka Waxler. "Stödjande samtal på distans : en kvalitativ studie om hur hälso- och sjukvårdskuratorer inom akutsjukvården upplever den terapeutiska relationen vid samtal på distans." Thesis, Ersta Sköndal Bräcke högskola, Institutionen för socialvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:esh:diva-9028.

Knorr, Endimione, and Christina Schreml. "You Are on Mute : A study on the impact of the digitalisation of communication on experienced interactions in organisations." Thesis, Linnéuniversitetet, Institutionen för organisation och entreprenörskap (OE), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-103778.

Forsberg, Ehn Sofia, and Filippa Mossberg. "Från kaffeautomaten till digitala mötesrum : Mjukvaruutvecklares upplevelser av att arbeta med agila utvecklingsmetoder under rådande pandemi." Thesis, Högskolan Väst, Avd för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-16539.

Terra, Inês Filipa da Silva. "Gestão de recursos humanos em época de emergência : o impacto nos colaboradores do Hospital da Horta, E.P.E.R." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20648.