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Labor versus management perspectives on remote, in-person, and hybrid work: an examination of incongruences, challenges, and strategies for optimal workplace collaboration, motivation, and performance
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Labor versus management perspectives on remote, in-person, and hybrid work: an examination of incongruences, challenges, and strategies for optimal workplace collaboration, motivation, and performance
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Content
Labor Versus Management Perspectives on Remote, In-Person, and Hybrid Work:
An Examination of Incongruences, Challenges, and Strategies for Optimal Workplace
Collaboration, Motivation, and Performance
by
Robert Younger
Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
December 2024
© Copyright by Robert Younger 2024
All Rights Reserved
The Committee for Robert Younger certifies the approval of this Dissertation
Dr. Anthony Maddox
Dr. Helena Seli
Dr. Eric Canny, Committee Chair
Rossier School of Education
University of Southern California
2024
iv
Abstract
This study examines the incongruence of rank-and-file US workers and managing leaders within
organizations when it comes to remote, hybrid, and in-person working arrangements and how
changing working models affect employee performance and motivation. This study aims to aid
organizations in increasing job satisfaction through improvements in organizational practices
surrounding in-office versus remote-first worker-designated roles. These improvements will
lower organizational operating costs by reducing turnover, employee burnout, and absenteeism.
Ultimately all US workers will benefit through increased trust and the greater life quality that
comes from reduced mental stress for both workers and executive management. This matters as
79% of workers who expressed a wish to permanently work from home (WFH) or in a hybrid
model and employers will need to reconcile company wishes to return to the office against
employees’ desires to not give up the time they regained and repurposed by not commuting to an
office as a result of the global COVID-19 pandemic (Barrero et al., 2021).
v
Dedication
To my family, who have been my unwavering foundation through this entire journey. To
my parents and grandparents, who instilled the values of curiosity, resilience, and the joy of
learning in me. Your support has allowed me to reach heights I never imagined possible. To my
loving wife, who has believed in me even during the times I doubted myself, thank you for being
steadfast, for being my partner, my confidant, and my greatest cheerleader. To my children,
whose smiles and laughter kept me grounded and reminded me of what truly matters in life. This
work is a testament to the future I hope to help build for you. And finally, to all my friends,
mentors, and colleagues who offered their encouragement, feedback, and camaraderie
throughout this process. Your support made this dream a reality.
vi
Acknowledgments
I would like to express my gratitude to my dissertation committee for their support and
guidance which was invaluable during this journey. To my chair, Dr. Eric Canny, I thank you
from the bottom of my heard for your insightful feedback and unwavering support. Your deep
expertise and genuine care for me as a person guided me through the complexities of this
process. It also helped me to keep my perspective and to remain positive throughout this journey.
I also am extraordinarily appreciative of Dr. Helena Seli and Dr Anthony Maddox who made
both thoughtful and invaluable contributions during this process. Your knowledge, time, and
encouragement helped me to grow as a researcher and I am forever grateful for everything you
have done during this journey.
I would also like to thank Dr. Dennis Hocevar for helping me to see other pathways
during this journey. Your detailed feedback and unbridled enthusiasm helped set me on a new
direction where I would not have otherwise gone. So, thank you, I am truly grateful for your time
and expertise. Further, I’d like to extend a thank you to Dr. Christopher Riddick who has been so
unbelievably supportive throughout this journey from my very first class to the very end. Your
constructive feedback has been and will continue to be invaluable, so thank you.
I would be remiss if I did not also thank my amazing USC Cohort 23 members, we are
forever bonded in friendship through this journey that has reshaped us all in some way. To the
USC 6-Pack who were a part of the same section for every class of this journey, I can’t thank
you enough for contributing in the most positive way to my life! Each of you has been a
committed partner in this journey and I will always cherish our collective time. All the funny
jokes, difficult times, and celebrations were that much more special shared with you as friends.
So, thank you again for your ongoing support and friendship. Fight on!
vii
Table of Contents
Abstract.......................................................................................................................................... iv
Dedication....................................................................................................................................... v
Acknowledgments.......................................................................................................................... vi
List of Figures................................................................................................................................ ix
Chapter One: Introduction to the Problem of Practice.................................................................... 1
Background of the Problem ................................................................................................ 2
Purpose of the Study and Research Questions.................................................................... 6
Field Context and Mission.................................................................................................. 7
Importance of the Study...................................................................................................... 8
Overview of Theoretical Framework and Methodology .................................................... 8
Organization of the Dissertation ......................................................................................... 9
Chapter Two: Review of the Literature ........................................................................................ 10
Remote Work Adoption and Shifting Views.................................................................... 11
Employee Perspectives on Remote Work......................................................................... 15
Leadership Challenges in Remote Work .......................................................................... 21
Motivation and Performance in Remote and Hybrid Work Environments ...................... 25
Organizational Culture in Remote Settings ...................................................................... 31
Literature Review Conclusion .......................................................................................... 36
Conceptual Framework..................................................................................................... 36
Chapter Three: Methodology........................................................................................................ 40
Research Questions........................................................................................................... 40
Overview of Methodology................................................................................................ 41
Ethics and Role of the Researcher .................................................................................... 43
Chapter Four: Results ................................................................................................................... 45
viii
Demographic Data ............................................................................................................ 45
Research Question 1 ......................................................................................................... 46
Research Question 2 ......................................................................................................... 54
Research Question 3 ......................................................................................................... 65
Chapter Five: Discussion and Recommendations......................................................................... 74
Discussion of Findings...................................................................................................... 74
Recommendations for Practice ......................................................................................... 78
Integrated Recommendations............................................................................................ 80
Limitations and Delimitations........................................................................................... 84
Recommendations for Future Research............................................................................ 85
Chapter 5 Conclusion........................................................................................................ 88
References..................................................................................................................................... 91
Appendix A: Variable dictionary for “WFH Code and Data: May 2020 to June 2024”............. 115
ix
ix
List of Figures
Figure 1: The U.S. Surgeon General’s Six Pillars to Advance Social Connection .......................16
Figure 2: Lacking Social Connection is as Dangerous as smoking 15 Cigarettes a Day .............17
Figure 3: The Human Deal Framework ........................................................................................19
Figure 4: Connective Leadership Illustration Model.....................................................................23
Figure 5: Interplay Between Herzberg’s Two-Factor Theory and Maslow’s Hierarchy ..............38
Figure 6: How Much of a Raise/Pay Cut Would You Value to WFH 2 to 3 Days a Week?..........48
Figure 7: How Would You Respond if Your Employer Announced that all Employees Must
Return to the Worksite 5+ Days a Week Starting the Month-After-Next?.....................................49
Figure 8: Based on Your Current Working Status: How Would You Respond if Your Employer
Announced That All Employees Must Return to the Worksite 5+ Days a Week Starting the
Month-After-Next ..........................................................................................................................50
Figure 9: Based on Your Political Affiliation: How Would You Respond if Your Employer
Announced That All Employees Must Return to the Worksite 5+ Days a Week Starting the
Month-After-Next ...........................................................................................................................52
Figure 10: How Does your Efficiency Working From Home Compare to Your Efficiency
Working on Your Business’s Premises? (by Race)........................................................................57
Figure 11: How Does Your Efficiency Working From Home Compare to Your Efficiency
Working on Your Business's Premises? (by Age) ..........................................................................58
Figure 12: How Does Your Efficiency Working From Home Compare to Your Efficiency
Working on Your Business's Premises? (by Education)................................................................59
Figure 13: How Does Your Efficiency Working From Home Compare to Your Efficiency
Working on Your Business's Premises? (Current Working Status)...............................................61
x
Figure 14: How Does Your Efficiency Working From Home Compare to Your Efficiency
Working on Your Business's Premises? (by Red/Blue State).........................................................62
Figure 15: How Does Your Efficiency Working From Home Compare to Your Efficiency
Working on Your Business's Premises? (Census Division)...........................................................63
Figure 16: Desired Share of Paid Remote Working Days.............................................................67
Figure 17: Would You Start Seeking Work if You Were Guaranteed to Find a Job That Would
Allow You to Work From Home?...................................................................................................69
1
Chapter One: Introduction to the Problem of Practice
There is incongruence between rank-and-file workers and management within organizations
on the topic of remote, hybrid, and in-person work models and how changing work models affect
employee performance and motivation. This is a problem that organizations will need to
understand and solve to achieve optimal results. Employers are pursuing more return-to-office
mandates, with 90% having said that they plan to require workers in the office in either a full-time
or hybrid model by the end of 2024 (Lipman, 2024). Yet, employees favor remote work and on
average believe there should be up to 20% more work-from-home time than what most employers
are planning to provide (Barrero et al., 2021).
In 2019, the average United States worker spent nearly 56 minutes per day driving
themselves to an office and those taking public transportation spent more than one hour and thirtythree minutes (Bureau, 2021). This time was given back to office workers during the COVID-19
pandemic and this likely is a contributing factor in workers being reluctant to return to office fulltime. Companies that have previously told professional office workers that their roles would be
remote forever are now walking back on those promises even though workers moved and altered
their daily lives based on those edicts (P. Grant, 2023). As companies began announcing remote
work policies after the start of the pandemic many employees packed up and moved across the
country to purchase larger homes, create easier access to nature, take care of aging parents, or find
better schools for their children (Wamsley, 2021). Policy changes of this type erode trust and
American workers are now experiencing job stress at record levels compared to the rest of the
world with 52% of United States workers stating each day that they experienced a lot of stress at
work the previous day (Gallup, 2023).
2
Background of the Problem
Remote work is not a new post-COVID-19 phenomenon as it has been occurring regularly
since the 1973 OPEC oil embargo made commuting prohibitively expensive for some American
workers (Choudhury, 2020). Even from the beginning, there have been objections to remote work
(Schiff, 1979). Five decades ago, management commonly objected to the inability to monitor if
remote individuals were working (Schiff, 1979). Arguments were also made that remote work cuts
employees off from serendipitous interactions with their coworkers (Schiff, 1979). In these initial
arguments, it was also said that too many distractions at home will prevent workers from being
effective (Schiff, 1979). Since that time, organizations and employees have routinely engaged in a
push-pull battle over the expansion or contraction of remote work. This disagreement has primarily
been focused on where workers are most productive (Pearlman, 2023). Companies are forcing
workers back to physical offices even though there is no data to show decreases in productivity,
efficiency, or understood communication between managers and employees (Schuman, 2022).
What studies have shown is that remote workers are just as, if not more, effective than in-office
workers and that they work more hours (Owl Labs, 2022).
Remote Work Growth
The number of people working remotely between 2000 to 2010 increased from 9.2 million
to 13.4 million and by 2015 represented 20% of the United States labor force (Office of Personnel
Management, 2017). In 2023 a full 40.9% of United States employees work exclusively remotely
or in a planned hybrid model where remote work and in-office work both occur (Barrero et al.,
2021). Survey data from 1,000 U.S. hiring managers shows that both partially remote hybrid roles
and fully remote roles will continue to make up a greater percentage of the labor force with the
latest projections showing that 40.7 million employees will be fully remote by the end of 2025
(Ozimek, 2021). That 40.7 million would make up almost 25% of the United States labor force and
3
does not consider the percentage of individuals in hybrid roles who are working remotely at least
one day a week.
Remote Worker Happiness
A 2022 study of German banking employees showed that remote workers were happier than
their in-office counterparts with greater feelings of meaningfulness and self-actualization and that
they also felt they were more of a community professional and were more likely to discuss private
problems with a colleague (Kortsch et al., 2022). The same study also found that remote workers
felt significantly more committed to their job, their team, and their company. A 2023 study of
12,455 workers from across the globe showed that employees who had to come to the office daily
were 20% less happy than those who worked remotely 100% of the time (Huijer et al., 2022).
Another global study shows that remote workers are less likely to experience burnout in their jobs
with only 26% indicating that they experienced burnout signs often compared to their office
working counterparts who said they felt those signs 41% of the time (Jain & Conrad, 2023). This
same Jain and Conrad study also asked remote, hybrid, and in-office workers to rate their happiness
on a 10-point scale where an 8 or above score was interpreted to convey greater happiness. Inoffice workers rated themselves as happy 21% of the time versus their remote counterparts who
said they were happy 42% of the time (Jain & Conrad, 2023).
Remote Work Financial Impacts
Remote work also has advantages associated with the operational cost of running a
business. A recent study showed that for each remote worker, an average company will save
approximately $10,601 annually due to rents, utilities, perks, and other tangible infrastructure
(Mamonov, 2022). For a company with 50 employees, this would translate into savings of more
than a half million dollars annually. Of course, in the most congested metro areas, these numbers
can be several times higher than this amount. Remote workers also take fewer sick days than their
4
in-office counterparts which also produces savings (Page, 2021). Additionally, absenteeism which
is higher for in-office workers has negatively associated costs and is affected by feelings of
loneliness when a lack of social companionship is created and an attitude of unsatisfactory work
communication exists (Bowers et al., 2022).
September 2023 United States Chamber of Commerce data showed that there were 6.4
million unemployed workers in America, but there were 9.6 million job openings (Ferguson, 2023).
Labor shortages result in lost productivity for industry sectors and companies that are unable to
find enough qualified workers to fill necessary roles. Studies have shown that ongoing labor
shortages will continue to affect developed and developing economies and that conversely there
will be surpluses of talent in some developing markets (Binvel et al., 2018). Increasing labor pools
can potentially help organizations in industries affected by labor shortages to address these
shortfalls.
Employees Place Value on Time
Reducing or eliminating commute time for remote workers is directly impacting worker
satisfaction and attitudes about remote work. Employees consider remote work to be the same as a
pay raise and many would take a pay cut to remain remote (Workers Would Rather Work from
Home than Get a Raise, 2022). Workers rate a pleasant commute experience as highly or higher
than they rate a happy marriage or sex life, but it isn’t that workers want to eliminate commuting
entirely, as most enjoy a small daily commute or warm-up stroll of about 16 minutes on average
(Redmond & Mokhtarian, 2001). Workers have placed so much value on their time that a fiveyear-long University of West England study showed that increasing commute times by 20 minutes
has the same negative impact as receiving a 19% pay cut (B. Clark et al., 2020). A new study by
Gartner showed that employees are more focused on their personal value than ever when it comes
to time commitments and work outcomes and were more concerned than ever with what satisfies
5
them, what makes them happy, and where they have given away too much of themselves in the past
for little return (Turner, 2023). The perspectives of management are not always aligned with
employees.
Management Wants to Maintain Productivity
Up to 68% of managers have said that they believe productivity-tracking software would
improve employee performance if they were unable to personally view employees working
(Klemp, 2023). However, the same study showed that 72% of employees believed that tracking
software either had no impact or diminished performance. Additionally, 20% of all the employees
surveyed stated that they would look for a new job if their employer implemented productivity
tracking software. The deploying of these systems has been done under the auspice of monitoring
and maintaining productivity, but many employees in the previously mentioned study cited an
erosion of trust as the primary reason for their dissatisfaction with these types of systems.
Similarly, 4-day workweek experiments have often shown the same types of positive employee
benefits including: increased productivity, higher employee engagement, greater job satisfaction,
reduced costs, and lowered stress (Stewart, 2023). Processing overload factors can also impact
employee productivity in stimuli-rich virtual environments (Huang et al., 2010). In the previous
article, Huang states employee performance and monitoring for desired organizational outcomes
can be achieved through fostering experience sharing utilizing game-based interaction and learning
environments while at the same time minimizing cognitive overload.
Arguments have also been made that serendipitous moments that will positively influence
culture and outcomes will not transpire unless workers are occupying the same physical space
(Schultz, 2023). Arguments are made that depression from the isolation that remote workers have
experienced is causing harm to individuals and therefore employees should return to the office with
the Surgeon General of the United States even weighing in on this topic recently (Scott, 2023). He
6
went on to say that loneliness is an epidemic and a danger on par with smoking. Data has shown
that remote workers are experiencing greater degrees of loneliness, depression, suicidal thoughts,
and substance abuse to cope with stress than they were before COVID-19 (Czeisler, 2020).
However, the same study shows that in-person workers are experiencing upticks in all of these
categories as well. This all falls back to studies that have shown that physical, mental, and
emotional well-being are closely linked with optimal performance (Adams, 2019). Perspectives and
data that seem to be juxtaposed at times only add to the complexity of this problem.
Remote Work Complexity
Having employees located in disparate locations introduces complexity when it comes to
managing state employment taxes and labor laws. This has led to greater work for human resources
(HR) departments and has resulted in potential violations when employees did not keep their
physical location up to date (Flores et al., 2022). Remote workers have been and continue to be
some of the largest security vulnerabilities for organizations and their cybersecurity teams (Palmer,
2023). Managers have also routinely complained about communication breakdowns and what have
been perceived as increased occurrences of conflict due to the lack of in-person escalation (Jämsen
et al., 2022). However, the same study showed that when it comes to employee perceptions,
surveyed employees mentioned both increases and decreases in conflict as occurring at nearly
identical percentages.
Purpose of the Study and Research Questions
The purpose of this project was to examine what ways employees perceive changes to their
remote working arrangement as influencing their motivation, performance, and productivity. The
following research questions guided this study.
1. Is employee motivation affected by a change from a remote work model to hybrid, or inperson work arrangements or when a change has been announced?
7
2. Do perceptions of remote work's influence on performance vary significantly across
demographic groups (e.g., age, gender, or income level) in the survey responses?
3. How do employees' productivity ratings vary based on whether they have received an
announcement about upcoming changes to remote work arrangements or have been when
they have recently been subjected to a change?
Field Context and Mission
This dissertation focused on professional workers from the Survey of Working
Arrangements and Attitudes (SWAA) study that was initiated by WFH Research which was
founded in May 2020 in response to the dramatic impact of COVID-19 on working arrangements.
Survey respondents were US working age residents between 20 and 64 years of age. This study
covered 259,030 respondents who answered 711 unique question variations on working
arrangements, attitudes toward those arrangements, and non-identifying demographic data and
personal traits between May 2020 and June 2024. These members of this study were from multiple
gender, age, ethnic, and background groups. The large nature of this study’s data set allowed for a
more representative look at all groups while still protecting the anonymity of individuals. The study
did look at race, gender, and other demographic data categories, but lacks a linkage method to tie
questions back to individual participants to preserve anonymity.
The US SWAA WFH Research group is a six-member team. Mert Akan, a Predoctoral
Research Fellow at the Stanford Institute for Economic Policy Research (SIEPR). Jose Maria
Barrero is an Assistant Professor of Finance at Instituto Tecnológico Autónomo de México
(ITAM). Shelby Buckman is an Economics PhD student at Stanford University. Steven J. Davis is
the William H. Abbott Distinguished Service Professor at the University of Chicago Booth School
of Business and Senior Fellow at the Hoover Institution. Hyoseul Kim is a Research Analyst at the
Hoover Institution. Nicholas (Nick) Bloom is the William Eberle Professor of Economics at
8
Stanford University, a Senior Fellow of SIEPR and the Co-Director of the Productivity, Innovation
and Entrepreneurship program at the National Bureau of Economic Research. Together they
manage the US SWAA survey project with the hope that their data and research will be useful to
economists, businesses, and policymakers.
Importance of the Study
Studying the effect that perception of work location policy had on the motivation and
productivity of American workers was important to understand so that companies can design and
implement policies that lead to the most productive outcomes. More importantly, it was essential to
understand how changes to work arrangements impacted worker motivation and productivity.
There is much misinformation and conflicting data that seemingly point to incongruent conclusions
when it comes to the benefits and drawbacks of remote work, hybrid models, and returning to the
office (Francis, 2023).
Hybrid work models were also something examined in this study. The goal of this was to
better understand what workers' views on hybrid work were and what hybrid models most
motivated employees and which created the greatest performance. Nearly every company is
implementing a different type of hybrid model and having a greater understanding of what workers
desire and dislike in current hybrid models will be crucial for creating policies of future success.
Failing to address this issue through scientific principles and academic study will result in lost
productivity through the application of much guesswork from managers who are not certain what
the impacts of their working arrangement decisions will be when they are applied (Pazzanese,
2022).
Overview of Theoretical Framework and Methodology
The theoretical framework that guided this study was Herzberg’s Two-Factor Theory which
is also referred to as Motivation-Hygiene Theory. The theory’s main concept is that all elements
9
can be divided into two category sets when measuring job satisfaction. There are “hygiene” factors
which are based upon the need to avoid unpleasantness and there are “motivation” factors which
lead to job satisfaction based on the need of individuals for self-growth and self-actualization
(Herzberg et al., 2017). This framework was relevant for this study as it will directly shows what
employees see as detractors in changed work environments and what items were potential
motivators.
The study was a quantitative study. It evaluated quantitative survey data to determine if
race, gender, geography, or other demographic factors impacted attitudes and perceptions when
remote working arrangements were changed to hybrid or in-person work models. This analysis
attempted to elucidate greater clarity on the feelings and preferences indicated during the
quantitative survey to gain insights on how Herzberg’s Two-Factor Theory was influencing
workers in the United States.
Organization of the Dissertation
This dissertation consists of five chapters. Chapter one provides the reader with overarching
context about the problems that were under study, stakeholders, and how the problem impacts
them. Chapter two focused on scholarly literature and relevant news articles on remote and hybrid
work and company mandated return to office policies. Chapter two also looked at assumed
influences and the conceptual framework that guides this study. Study methodologies, collection
methods, and analysis are discussed in Chapter three. Then in Chapter four data is presented and
analyzed. The study concludes with Chapter Five where suggestions for improvement are laid out,
recommended actions are presented, and implications for policy and practice are examined.
10
Chapter Two: Review of the Literature
The rise of remote work, driven by global events, has brought about a significant shift in the
dynamics of the workplace. This literature review aimed to explore the incongruent feelings of
employees and leaders regarding the return to the physical office and the resulting impact on
employee motivation and performance. Drawing upon a wide range of academic sources, this
review synthesizes the existing literature to provide an in-depth understanding of the complex
relationship between remote work, leadership expectations, employee sentiments, and its
implications for motivation and performance. By examining the relevant research, this review
sought to identify critical gaps in the existing knowledge and guide future research efforts in
understanding this emerging problem of practice. Additionally, the final section of this review
examined how a conceptual framework guided this study.
The evolution of work practices in the 21st century has seen a seismic shift towards remote
work, catalyzed by global events such as the COVID-19 pandemic (Barrero et al., 2021). As
organizations contemplate the transition from remote work to a return to physical workspaces, a
complex interplay of emotions and perspectives has emerged between employees and leaders (90%
of Companies Will Return to Office By the End of 2024, 2023). This literature review section aimed
to navigate this multifaceted landscape of remote work, exploring divergent perspectives,
motivational intricacies, and subsequent performance implications.
Shifting attitudes about the way workers have worked are not new and have changed many
times over the years (Licht, 1988). Workers who have lobbied and fought for change have rarely
been willing to give back enrichments like shorter work weeks, fewer working hours, and safety
standardizations (Rosenfeld, 2014). Once these types of quality-of-life enhancements became
commonplace in the workplace employees by and large have just not been willing to return to the
previous model. Possibly the rise in remote work which despite being accelerated by the COVID-
11
19 pandemic was not a new trend will turn out much the same. Remote work has in fact been rising
and had already reversed and surpassed the 1960s levels that had been in decline through the 1980s
(Silver, 2023).
Remote Work Adoption and Shifting Views
The views held by organizational leaders for remote work had already started to shift
dramatically years before the COVID-19 pandemic arrived (Allen et al., 2015). Companies and
organizations are always looking for strategic advantages and reducing costs through a reduction in
office space is one way to achieve that goal (Silverman, 2023). There is the physical infrastructure
of the office space and the rents required for it, but there are also other costs for things like
furniture, equipment, janitorial services, physical security, and perks items like food and snacks for
office workers (Barrero et al., 2021). When eliminating the office, a business can be freed from all
these costs and more.
Remote work attitudes have also shifted tremendously due to advances in technology. Pew
research shows, fully remote workers use online conferencing services like Zoom or Webex a full
66% of their days and if they did not start remote working until the COVID-19 outbreak they use it
77% of the time (Igielnik, 2022). This same Pew Research article states that the in-office workers
are utilizing conferencing services often only 35% of the time. Another change occurred when
nearly everyone was forced to work remotely for a period and as such, much of the stigma that had
previously surrounded remote workers simply vanished. Though presenteeism stigma still exists
and 28% of workers said remote work makes career growth more difficult(Gascoigne et al., 2023).
Answering whether remote working arrangements will work best for an organization can be
difficult to ascertain as much of the evaluative criteria can be highly subjective.
12
The Future of Work: Remote Work and Its Implications for Leaders and Organizations
Leaders need to plan for a future that includes at least some element of remote work in their
organizations. Reimagining the spaces that people work from is very much a part of this as
employees are not eager to go back to a world of cubicles (Havelin, 2019). Many companies are
already embarking on this journey and placing a big emphasis on making spaces comfortable,
flexible, open, and airy (Smith, 2023). Smith also highlighted that leaders need to accommodate a
diversity of working styles, and that employees who have become comfortable working from home
are just not eager to return to sturdy industrial surfaces and garish lighting. Companies can no
longer have just one type of space. There needs to be a variety of spaces to accommodate various
types of work and working styles (Musser, 2023). According to a 2022 study by CBRE small
nooks and private spaces that are often referred to as focus spaces are the most requested item that
would make employees want to visit an office (Isner et al., 2022). Workers in 2024 have found it
difficult to work without some level of quiet space where video conference meetings can be held
(Wasmund et al., 2023).
Leaders in 2024 have also needed to adapt and proactively shape organizational strategies
to accommodate the changing dynamics of the modern workforce. Failing to adjust and meet the
needs and desires of a changing workforce could place an organization at an unnecessary
disadvantage (Laker, 2023). Additionally, dispersed virtual teams allow for members to work on
multiple projects regardless of their proximity, a level of business continuity, and substantially
broader recruiting pools (Cascio, 2000). Organizations can also make more work temporary or
project-based from these larger talent pools with contract-based workers who are not a part of the
organizations, but who still hold expertise that is valuable to work and projects the organization
needs to or wants to undertake (Ozimek & Stanton, 2022).
13
Beyond the Pandemic: Remote Work as a Strategic Imperative
This new approach presented by Ozimek and Stanton is a unique look at strategies that can
be used thanks to remote work and changes in the global employment landscape (Ozimek &
Stanton, 2022). They point out that the new open talent model can be considered by organizations
for the following reasons.
• Insiders cannot be redeployed easily
• Outsiders are less expensive than hiring a new insider or paying overtime to existing ones
• Highly specialized skills are needed, and they are not available internally
• Returns on exceptional solutions are high.
Talent flexibility of this type allows companies to consider the level of firm-specific knowledge
required for a project, whether it is present in the organization if it will be utilized regularly, and if
it might be better to outsource it through an open talent arrangement. As Ozimek and Stanton have
pointed out, this is radically different from the way individuals have traditionally been hired to do
work for companies. This change from traditional hiring models is likely to stick as the previous
model can’t provide this level of access and there is therefore significant potential for this model to
continue.
Remote work studies have also shown a significant correlation to worker happiness
measures (Robinson, 2022). A study examining four happiness indicators conducted at a German
bank showed that remote employees were happier as these workers scored higher in all four
categories (Kortsch et al., 2022). The four areas studied were:
• Self-actualization
• Meaningfulness
• Community professional
• Community familiar
14
In the study community professional meant that even in tense situations workers did not feel as if
responsibility was shifted onto someone else. The area labeled as community familiar meant that
employees, when faced with problems, were more likely to discuss their personal problems with
their colleagues. The study also showed that remote employees were more committed to the
organization than their in-office counterparts. Above all else, what the study has shown is that there
is evidence that self-selected work environments and working hours can make work more
conducive to happiness.
Technological Infrastructure and Remote Work Efficacy
Understanding the role of technology is pivotal in comprehending the nuances of remote
work adoption and its impact on organizational processes. Video conferencing and other
collaborative communication tools have helped workers feel more connected to their teams and
provided ways to work collaboratively (Saura et al., 2022). It can be very challenging to get the
insertion of new technology into work right and it is something that can easily start to feel invasive
(Baruch & Nicholson, 1997). Being the most effective manager for virtual teams requires a shift to
more results-oriented measurement and the retraining of managers and how they manage teams
because the supervisory skills that are most effective for remote teams are often different from
what managers would utilize when in person (Cascio, 2000). Technological framework is and
needs to be supported by organizational and environmental influences as well because remote work
arrangements that can achieve an optimal balance between those three dimensions can benefit both
companies and employees (Ng et al., 2022). Some companies, like Spotify, have harnessed
technology and pushed their chips all in on remote arrangements. “Work is not a place you come
to, it’s something you do,” Katarina Berg, the Spotify Chief Human Resources Officer explains as
she discusses the company’s flexible workplace location policy (Hogg, 2024).
15
Employee Perspectives on Remote Work
Employees do their best work within environments where they can thrive and what they
need to thrive can vary based on the environment (Spreitzer et al., 2005). According to Spreitzer et
al., thriving means that individuals “feel progress and momentum, marked both by a sense of
learning (greater understanding and knowledge) and a sense of vitality (aliveness)” (p. 538). The
same authors also point out that the antithesis of this would be languishing where “one feels they
are stuck, caught in a rut, or failing to make progress” (p. 537). The importance of a positive family
environment in the new world of work, and how it can help individuals thrive, and consequently
help the business to also perform better cannot be underestimated and has been shown to have a
tremendous impact on employee satisfaction (Merkuž & Mihelič, 2023). Of course, the opposite of
this could also be true and could result in unfavorable outcomes.
The greatest perceived benefits of remote work in a recent survey by Upwork were no
commute, reduction of non-essential meetings, and fewer distractions than in the office (Ozimek,
2020). Working anytime from anywhere can also equal more stress, less sleep, and a bleed-over of
work-related stresses into one’s personal life and vice versa (Messenger et al., 2017). However, not
all remote work items are positive. Female employees spending more time at home also found
themselves at increased risk of domestic violence (Wilson, 2021). Remote working also can bring
on feelings of loneliness, especially if an individual lives by themselves with no family support
network (Goredema, 2023).
The Impact of Isolation on Professional Remote Workers
The COVID-19 pandemic forced the closure of offices and foisted remote work onto many
for the first time. It also created greater feelings of loneliness among many as shown by a Canadian
study of 3,772 adults that revealed severe loneliness was developed by 34.7% of respondents (Lin,
16
2023). The data from this study also showed that women, teens, and those experiencing pandemictriggered job insecurity were the most at risk of developing severe loneliness (2023). Male
respondents in the 15 to 24 age band had the highest overall feelings of severe loneliness with
55.1% reporting such while female respondents were highest at 45.8% in the 25 to 44 age
demographics showing that age nor gender alone can be utilized as a predicting factor (2023). The
U.S. Surgeon General, Dr. Vivek Murthy, recently revealed a six-pillar strategy to advance social
connections as illustrated in Figure 1 in response to the increased risk of adverse physical health
conditions that are associated with lacking those social connections (Golant, 2023).
Figure 1
The U.S. Surgeon General’s Six Pillars to Advance Social Connection
Note. https://www.hhs.gov/surgeongeneral/priorities/connection/index.html
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There have long been debates on the effect of isolation on the human psyche and Dr. Stuart
Grassian who is credited for identifying a specific psychiatric syndrome associated with solitary
confinement, termed the SHU Syndrome has helped to bring attention to this through his work
studying inmates in solitary confinement (Grassian, 2006). The work of Grassian shows that
individuals isolated for long enough can experience paranoia, impulse control, and even delirium
(2006). Thus, the Surgeon General has placed significant importance on this problem of isolation
and the governmental office has even produced data showing that the consequences of lacking
social connections are greater than smoking, binge drinking, and several other health risk factors as
shown in Figure 2 (Holt-Lunstad et al., 2017).
Figure 2
Lacking Social Connection is as Dangerous as smoking 15 Cigarettes a Day
Note. United States. American Psychology. 2017;72(6):517-530. doi:10.1037/amp0000103
18
Remote Work and Work-Life Balance
Many employees in 2024 have been trying to figure out what makes them happy and where
are they giving away too much of themselves for little return (Turner, 2023). Part of this likely
stems from 82% of employees having stated that it is important to be seen as a person and not just
an employee, data that Turner gathered in his research for Gartner’s 2023 Future of Work Trends
report (2023). The same research revealed that only 45% of individuals felt they were seen this way
by their organizations (2023). Employees also believe that it is important for their companies and
organizations to share in caring for their communities and families and in fact, 60% of employees
want employers to know about their commitments and to make accommodations to support them
where possible(Wong, 2022). This same research went on to show that despite Fortune 500
companies spending $2,500 per employee on wellness in 2022, employee engagement has
remained flat since 2016 (2022). Gartner’s research points to individuals examining their choices in
how they have spent time, energy, and social capital to gain more value from their jobs in what it
called “The Human Deal” as illustrated in Figure 3 (2023).
19
Figure 3
The Human Deal Framework
Note. https://www.gartner.com/en/articles/employees-seek-personal-value-and-purpose-at-workbe-prepared-to-deliver
The 2023 Greenhouse Candidate Experience Report surveyed 1,200 U.S. employees and
the results point to employees being most interested in two things, flexible work policies and pay
transparency (Suzuno, 2023). The Greenhouse data showed that 76% of candidates are likely to
look for a new role if their company were to roll back flexible work policies (2023). Also of note,
was the fact that historically underrepresented groups were 22% more likely to look for a job when
these policies change. Employee preferences have been changing and Greenhouse shows that
employees are looking for fairness and that is achieved predominately through flexibility in work
policies and salary transparency (2023).
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Employee Preferences in Work Models
In 2021 and 2022 nearly 100 million workers quit their jobs to take on new ones to gain
greater work-life balance, increased compensation, stronger company culture, and to add flexibility
(Hoover & Ferguson, 2024). In fact social media marketing company Buffer’s annual survey of
3,000 remote workers shows that 98% of respondents wish to work remotely for the rest of their
career(Gascoigne et al., 2023). The same 98% said they would recommend remote work to others
and 99% of these workers describe their work experience as positive or neutral (2023). This same
survey shows that 91% of workers favor fully remote or remote-first with optional in-office hybrid
as an available option (2023).
One challenge for employees in 2024 has been the ability to maintain clear boundaries
between home and work life as work shifted to remote and hybrid working models. In 2024 there is
an interconnection between work and life as the two have further blended based on having a shared
location (Steffens et al., 2023). In bringing these domains closer together individuals’ risk having
elements of their personal or work life more easily bleeding over into the other domain. To a
degree, this new concept of work-life-blending now replaces the previous concepts of work-life
balance and work-life conflict as these are no longer adequate to comprehensively address the
complexities of contemporary work arrangements and the interface between work and life (Kelliher
et al., 2019). Flexible work is believed to influence positive attitudes because it symbolizes an
organization’s concern for employees and the availability of flexible work arrangements can also
increase the perception of psychological control, which can help to alleviate the conflict between
work and personal life (Sánchez-Hernández et al., 2019). Employee preferences are of course only
one element of work model selection and adoption that organizations and leaders must grapple with
as they attempt to construct an optimal model for a given organization.
21
Leadership Challenges in Remote Work
Many companies are utilizing marketing, and branding as a part of their recruitment process
to show value to prospective employees. In 2024 making the Fortune 100 Best Companies to Work
For list required organizations to create a psychologically and emotionally healthy workplace,
something employees of those 100 companies said is happening 83% of the time (Bush, 2023).
That is 31% higher than the 52% average rate for companies from the more than half a million
survey responses received.
Leadership also has had to contend with changing laws and regulations at the federal, state,
and local levels. While keeping tabs on things federally and within the jurisdiction of the
company’s headquarters is well within the scope of reason for most HR professionals, it can
become extraordinarily difficult for leaders if or when employees change their home or working
state without notification (Flores et al., 2022). At the very least, as Flores states, most organizations
should create a documented process of how they wish to handle and approve changes of these types
to ensure compliance with various legislation and tax laws.
Digital transformation for companies forced into remote work as a result of the COVID-19
pandemic has presented challenges for leaders and managers who lacked technological
collaboration tools, video conferencing platforms, and needed investments in other digital
infrastructure (Błaszczyk et al., 2023). Leaders also have been continually fearful that remote work
will negatively impact productivity, but many studies have shown boosts in productivity by as
much as 13.5%, less quitting or absenteeism, and employees who rated themselves happier when
surveyed (Bloom, 2014). A Texas A&M study by the School of Public Health showed that the
productivity of remote workers quickly met and then exceeded office productivity following
Hurricane Harvey necessitating remote work for a month in 2007 (Mitchell, 2022). Still, there are
more things leaders can do in this new world of life blending to be effective.
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Connective Leadership in the New Remote Economy
Connective Leadership (CL) and its achieving styles can significantly aid leaders in
addressing challenges in remote work environments through various strategies, including
understanding, recognizing, and optimizing to select the appropriate achieving style for the task at
hand (Cartwright et al., 2023). Through alignment of human resource management practices,
technology, and organizational culture, CL can foster employee engagement, collaboration, and
organizational agility which are all essential for remote work efficiency (Arunprasad et al., 2022).
The strategies, checklists, and recommendations provided by CL in virtual or hybrid work
environments help in navigating leadership challenges, thereby improving team performance and
cohesion (Pullan, 2022). The CL styles enhance dimensions of job performance such as openness,
problem-solving orientation, and participatory decision-making, which are especially beneficial in
virtual work environments (Susita et al., 2023). Identifying skills relevant to remote work,
designing training, and suggesting organizational culture changes are solutions that can support
remote workers and help ensure their success (Henke et al., 2022). During a crisis, like the
COVID-19 pandemic, the CL styles promote collaboration, inspire dedication, and ensure fairness
amongst team members, which are crucial for maintaining productivity and morale (Cartwright et
al., 2023). Implementation of these strategies can contribute to a more engaged, motivated, and
productive remote workforce, highlighting the versatility and effectiveness of CL and its achieving
styles in tackling the unique challenges of remote work environments.
23
Figure 4
Connective Leadership Illustration Model
Note. https://doi.org/10.3390/merits3030035
Leading Virtual Teams: Strategies for Success
Leading virtual teams requires a multifaceted approach, the integration of various strategies
to address unique challenges posed by remote and hybrid work environments. It is a necessity to
embrace technology and effective communication for managing virtual teams and remote project
offices effectively (Tripathy et al., 2023). As Tripathy et al. have stated, clear communication
protocols are crucial, as they help to establish trust and ensure that team members are aligned with
a team's goals (Tripathy et al., 2023). Focusing on results-based performance rather than hours
worked can lead to better outcomes for virtual teams as it emphasizes the importance of meeting
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project goals and deliverables over strict adherence to a traditional work schedule (Freeman, 2017).
Engaging in active mentorship while focusing on career momentum can help maintain motivation
and job satisfaction among team members and is especially important as remote work becomes
more prevalent (Cronley & Ravi, 2021).
Leading virtual teams can sometimes be perceived as more challenging than leading on-site.
So, leaders need to address issues proactively and implement strategies to counter any perceptions
of imbalance to maintain team efficiency and morale (Connaughton & Daly, 2004). Utilizing
contemporary leadership and change management principles can help leaders overcome challenges
posed by geographically distributed teams, ultimately enhancing a leader's ability to manage
effectively in a virtual environment (Levasseur, 2001).
The Role of Trust in Virtual Leadership: Strategies for Success
Creating an environment where team members feel comfortable sharing their ideas and
concerns is vital for the success of virtual teams as building trust and promoting open
communication both significantly enhance productivity and team culture (Gazor, 2012).
Overcoming and leveraging the similarities and differences inherent in multicultural virtual teams
can facilitate communication, resolve conflicts, and form and maintain trust among team members.
Embracing diversity and building competencies related to cultural awareness is essential for the
cohesive functioning of distributed virtual teams (Cagiltay et al., 2015). Training global virtual
teams and their leaders in cross-cultural competencies can help to bridge cultural gaps and improve
team dynamics as it displays respect for different cultural norms and practices (Wildman &
Griffith, 2015). Still, much of what dictates success or failure for virtual and hybrid teams boils
down to trusting that employees are hard working adults. Katarina Berg, the Chief Human
Resource Officer of Spotify says, “You can’t spend a lot of time hiring grownups and then treat
25
them like children,” when she explains the company’s position on remote and hybrid work and the
role trust must play within that continuum (Hogg, 2024).
Motivation and Performance in Remote and Hybrid Work Environments
Motivation and performance in remote work environments have been extensively studied
over the years (P. Clark, 2010). The COVID-19 pandemic abruptly shifted even more workers into
remote working arrangements in a sudden fashion. Studies have shown that work environment can
have a significant impact on employee motivation, the pride they have for their work, and the
resulting quality of output (Basalamah & As’ad, 2021). Moving from traditional office
environments to remote work shined a spotlight on the importance of having ergonomically sound
workspaces at home to maintain physical health and reduce musculoskeletal pain which could
impact motivation and performance (Argus & Pääsuke, 2021). Workspace plays a major role in
employee motivation and remote work can create challenges workers will need to solve, including
ergonomic issues, dedicated workspace location, and overall indoor environmental quality (IEQ)
(Awada et al., 2021). This same study from Awada et al. shows that worker demographic
characteristics play a role in productivity as those who were earning at higher income levels, those
who were older, and those who were female experienced the most significant increases in
productivity as the WFH arrangements created needed balance between work-family-home
responsibilities and therefore increased motivation (2021). Flexible work arrangements (FWA)
have shown many positive impacts including reduced work-family conflict, better psychological
health, increased role satisfaction, and better physical health (Shifrin & Michel, 2022).
A critical factor for enhancing motivation and performance in remote work arrangements is
to ensure that management supports employees and provides access to all necessary tools and
information at the organizational level as these items significantly impact work engagement
(Lesener et al., 2020). While team building and regular check communication can help, remote
26
workers can experience greater feelings of social and professional isolation which can negatively
impact the social and professional life of employees and affect motivation (Charalampous et al.,
2019). Worker choice also plays a significant role in employee motivation in remote arrangements
as those who work at least 20% of their hours remotely and report moderate or high choices over
where they work tended to have lower stress levels, lower intention to leave the organizations, and
also had greater motivation and performance (Kaduk et al., 2019). These studies and more have
continually shown a high correlation between employee motivation and employee productivity yet
very few studies have been conducted on forced return to office (RTO) mandates and their impacts
to date.
Redesigning Work Design Theories: The Rise of Relational and Proactive Perspectives
Work design theories are frameworks that describe how job roles and work environments
can be structured to improve employee satisfaction, motivation, productivity, and overall
organizational effectiveness (Torraco, 2005). The premise of these theories is that the way work is
organized has a significant impact on employee behavior and performance. Many work design
theories have been authored over the years. Still, perspectives on work design theories are
continually shifting and evolving as new relational and proactive perspectives shape job roles and
behaviors.
One historical model is the Job Characteristics Model (JCM) which identifies five core job
characteristics (skill variety, task identity, task significance, autonomy, and feedback) that affect
three critical psychological states (experienced meaningfulness of the work, experienced
responsibility for outcomes, and knowledge of the actual results of the work activities) (Hackman
& Oldham, 1975). This Hackman and Oldham model portends that these states lead to increased
work motivation, job satisfaction, performance, and reduced absenteeism and turnover (1975).
Another historical work theory is the Two-Factor Theory developed by Frederick Herzberg which
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distinguishes between hygiene factors (that can only lead to dissatisfaction, but are not necessarily
motivators) and motivators (which are the factors that can lead to higher job satisfaction and
motivation (Herzberg et al., 2017). There is also the Social Information Processing (SIP) Model by
Salancik and Pfeffer that suggests that employees adapt their attitudes and behavior based on the
social cues and information from others within their environment (Salancik & Pfeffer, 1978). SIP
shows that the way individuals perceive and interpret their job and working conditions can be
influenced by social context and interactions (1978).
Then there is the approach of considering both the social and technical aspects of
organizational work design as is done with Socio-Technical Systems Theory which suggests that
work systems should be designed to optimize both the social system (work structure, team
dynamics, and employee needs) and the technical system (equipment, technology, and processes),
ensuring that they are mutually supportive (Trist & Trist, 1993). The psychological processes of
employees during work activities are the focus of Action Regulation Theory which emphasizes
goal-directed behavior and suggests that tasks should be designed to enhance employees' skills,
knowledge, and autonomy, allowing them to regulate their actions effectively toward achieving
work goals (Raabe et al., 2007). The moderating effects of Ergonomic Job Design and employee
reactions to that environment are also crucial to consider as it examines the interaction between
employees and their work environment and aims to design jobs in a way that minimizes physical
strain and maximizes comfort and efficiency to reduce injury risk and thereby increase job
satisfaction and productivity (May et al., 1997). All of these theories and models are in essence
explorations of employee motivation and ways to increase it.
New relational and proactive perspectives have significantly influenced recent work design
theories as well. Workplace design frameworks supporting user-centered workplace co-design and
evaluation processes have indicated a role for Need-Supply Fit Theory and how it impacts
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workplace satisfaction (Markkanen & Herneoja, 2024). The increasing social embeddedness of
various jobs and the importance of employees taking initiative in their work is shifting the nature of
work in service and knowledge economies and highlights the growing importance of relational and
proactive behavior perspectives (A. M. Grant & Parker, 2009). This shifting of work places more
emphasis on open systems and “Crowdwork” which highlights the need for work design theories to
evolve with the changing organizational landscapes (Anya, 2015). Shifting the focus of work
design from structural elements to individual characteristics has shown how relational and
proactive perspectives highlight the role of personality traits like proactive personality and
psychological capital in fostering innovative work behaviors (Ullah et al., 2023).
Exploration of the interconnectedness of work and home life and how relational and
proactive management of vitality and work-home enrichment can reciprocally affect each other and
ultimately benefit entrepreneurial performance is important in showing how malleable behavioral
mechanisms are related to entrepreneurial well-being and success (Tisu & Vîrgă, 2022). Another
new variation introduced by Yuri Scharp and colleagues is the concept of playful work design,
which is an approach that uses elements of competition or fun to mitigate the negative impacts of
job demands, demonstrating how relational perspectives can inform innovative solutions to
traditional work design problems (Scharp et al., 2021). Zuberi and Khattak have also examined
how relational and proactive perspectives can be integrated into leadership studies, showing how
leader-member exchanges and proactive personalities interact within work design to impact
innovative work behaviors (Zuberi & Khattak, 2021). These developments all underscore the
dynamic evolution of work design theories, which now incorporate relational and proactive
dimensions to address the complexities of modern work environments, emphasizing the importance
of social relations, employee initiative, and the broader organizational context in shaping job roles
and behaviors to positively impact employee motivation and performance.
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The Impact of Remote Work on Employee Engagement
Historically, remote work was a privilege or an occasional perk rather than a norm and it
was typically limited to certain job roles or industries and often associated with higher autonomy
and job satisfaction due to the flexibility it offered (Nyberg et al., 2021). The sudden shift to
remote work brought about by the COVID-19 pandemic has necessitated a reevaluation of
traditional employee engagement strategies, highlighting the critical role of Human Resource
Development (HRD) in addressing the new challenges posed by 'enforced' remote working (Pass &
Ridgway, 2022). Remote work now has a more structured form with established policies and tools,
aimed at sustaining or improving employee engagement by ensuring a balance between flexibility
and productivity as the focus has shifted towards enhancing well-being, boundary control, reducing
professional isolation, and maintaining engagement through high-quality virtual interactions
(Jaiswal & Prabhakaran, 2023). One thing that hasn’t changed, with everything that has, is that all
of these adjustments and changes are designed to in one way, or another enhance employee
motivation and ultimately productivity.
Remote working has not been all positive news for employees and their engagement. The
current remote working environment has shown positive relations with loneliness and work
engagement, but a negative relation with bullying, which differs from the past when remote work
was less prevalent and less understood (Bollestad et al., 2022). Historically, remote work’s
effectiveness was often compared with conventional office work, focusing on productivity and
work-life balance. Now, the impact on employee engagement also emphasizes psychological
aspects such as job control, professional isolation, and the need for supportive leadership to
mitigate the challenges posed by remote work (Becker et al., 2022). The COVID-19 pandemic led
to redefining remote work, making it potentially the next new normal, a shift has led to a positive
impact on employee engagement as remote employees are more likely to be engaged compared to
30
those without such options historically, highlighting a significant change in the perception and
implementation of remote work (Negi et al., 2023). Historical perspectives on remote work focused
more on its novelty and flexibility, the current context which is largely shaped by the pandemic has
brought more attention to the impact on employee well-being, engagement, and the need for
effective management and support systems as Negi et al. have stated. The evolution of these
perspectives reflects a shift from viewing remote work as a supplementary option to an integral part
of modern work culture, with significant implications for employee engagement and motivation
strategies.
Performance Metrics in Remote and Hybrid Work Environments
Performance metrics have been utilized for many years to measure worker productivity and
optimally measuring remote work performance requires some shifting in how these metrics are
obtained and viewed (Pillai & Prasad, 2023). Shifting the managerial focus to self-efficacy, social
support, resource improvement, and job nature satisfaction can have measurable changes in
employee well-being, perceived productivity, engagement levels, and job satisfaction and enhance
key productivity components overall (Straus et al., 2023). Cyberslacking or the taking of too many
unauthorized breaks on too often of a basis is a problem that some organizations want to solve
(Oravec, 2023). As such AI-enabled spyware, sometimes coined boss-ware, is now a method for
surveilling employee behaviors to ensure they are aligned with the company’s expected outcomes
Oravec also explains (2023). Implementing strategies that foster a sense of belonging within
remote teams to align with overall productivity and well-being goals requires an organization to
assess the sense of belonging created and how that impacts productivity by examining team
communication functions such as coping, learning, plotting, and positioning (Hafermalz & Riemer,
2021). From a practical perspective, Hafermalz and Riemer also argue that surreptitious
communications play an important part in building the collective resource of belonging and that
31
management should be cautious in interventions into candid spaces where workers may share
views contrary to their official work personas (2021).
Using assessment tools and the data they produce can be effective instruments for
evaluating employee mental health and well-being as can physical activity levels which help to
give a comprehensive understanding of remote worker well-being and productivity (Hernández et
al., 2021). The Hernández study goes on to promote the combining of this strategy with stress level
assessments, communication efficiency, and work environment quality evaluations (2021).
Companies can also implement passive sensing and behavioral data analysis from items like email
activity and calendar fullness to passively assess stress levels and work habits in real-life settings
without the intrusiveness of spyware monitoring (Morshed et al., 2022). Focusing on employee
well-being in these ways can be an effective way to boost employee motivation.
Organizational Culture in Remote Settings
Organizational culture can significantly impact remote work in various ways. In remote
settings, where the sense of belonging and aligned values can enhance performance and satisfaction
an organization should work to foster a positive and cohesive atmosphere by promoting positive
relationships and a strong organizational culture., which can significantly improve business
performance (Krajcsák & Kozák, 2022). Organizations adapting communication techniques for
remote settings can help foster acceptance of cultural differences in communication and promote
increased cultural diversity, particularly in multinational corporations (Rao et al., 2023).
Organizational culture influences worker productivity, engagement, and motivation and when a
positive association exists between employees and an organization viewed as supportive, cultural
effectiveness can be enhanced (Khan & Lopez, 2023). Company culture can have both a positive
and negative influence on employee effectiveness and when direct oversight is reduced that culture
plays an even more crucial role in guiding employee behavior and performance (Fridan &
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Maamari, 2023). In remote work environments where physical separation can lead to feelings of
isolation creating and maintaining a strong organizational culture ensures a unified connection
among remote workers, addressing challenges in engaging employees and promoting team
collaboration (Haque, 2023). Dimensions of organizational culture such as involvement and
mission can significantly enhance overall satisfaction levels among remote workers as these
dimensions foster engagement and teamwork which are essential for maintaining alignment and
motivation in remote work settings (Denison et al., 2014). In summary, organizational culture plays
a critical role in shaping the remote work experience by influencing communication, adaptation,
diversity, employee engagement, productivity, and team cohesion. Fostering a positive
organizational culture can help overcome some of the inherent challenges of remote work while
enhancing overall business performance and employee motivation and satisfaction.
Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams
Managing conflicts in geographically disbursed teams can be challenging, and managers
need to understand both the types of conflict that can exist and how to solve them (Hinds & Bailey,
2003). The unique antecedents of conflict caused by geographic distance and technology reliance
can lead to misunderstandings and miscommunications in distributed teams, but emphasizing
shared identity and context while utilizing spontaneous communication among team members can
help to moderate conflict dynamics and aid in resolution (Hinds & Mortensen, 2005).
Organizations can also turn their focus to managing issues of coordination, promoting healthy
conflict-handling norms, ensuring open communication, and fostering the ability to deal with
conflict as it arises within the team (Hinds & Mortensen, 2005). However, the absence of conflict
should not be viewed as universally positive as the absence of conflict can impact learning
outcomes in partially distributed teams and some level of conflict may be necessary for optimal
team performance and learning (Ocker & Hiltz, 2012).
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Encouraging cooperative activities amongst remote team members can lead to more
effective real-world collaborations stimulating discussions and fostering greater understanding
through cooperative activities under time pressure in virtual environments (Lewis et al., 2010).
Building trust in global teams takes work on how organizations overcome shortcomings like poor
socialization, cultural fit, communication challenges, and conflict-handling mechanisms when they
are suboptimal can be imperative in establishing and then building that trust (Moe & Šmite, 2008).
Creating a positive group atmosphere significantly impacts the development of shared
understanding and mitigates perceived team conflict, especially in short-duration virtual teams, and
therefore should be a focus of remote teams (Paul et al., 2018). By adopting these strategies,
organizations can better understand and manage conflicts in distributed teams, leading to improved
collaboration, productivity, and team cohesion.
Fostering Organizational Culture in Virtual Work Environments: Lessons from Successful
Companies
Successful companies have adopted various strategies designed to build organizational
culture in virtual working environments. Utilizing technology can open new opportunities to
develop and maintain a strong organizational culture and communication platforms are one area
where organizations can leverage technology like the metaverse to enhance social engagement,
cooperation, and communication (Ramachandran et al., 2023). Ensuring fair and transparent
compensation, fostering collaborative corporate culture, and training leaders on transformational
leadership are all elements that successful companies are utilizing to positively impact employee
engagement and contribute to a positive virtual work environment (Jogulu & Ferkins, 2012).
Creating cultures that emphasize teamwork, process orientation, and continuous quality
improvement aligned with the principles of total quality management (TQM has been shown to
improve competitive positioning and successful implementation of business strategies (Irani et al.,
34
2004). All these adoptions are physically structured, but there are non-systems-based
implementations companies can make to build culture and increase employee motivation.
Successful companies analyze the characteristics and challenges specific to virtual contexts
and teams. They implement best practices to strengthen the social element, connecting these
practices with elements of organizational culture to maintain cohesion and effectiveness (Miklosh,
2022). Companies that promote remote work arrangements enhancing employee flexibility and
idea generation tend to cultivate positive workplace relationships and in turn, these practices
enhance business performance and assist in maintaining a strong organizational culture, improving
overall cohesion and the atmosphere within the company (Palibutan et al., 2023). Initiatives that
make employees feel heard, provide tools to cope with stress, and emphasize the importance of
well-being, particularly in the post-COVID-19 era, have been integral in fostering and sustaining
employee happiness which contributes to increased employee engagement, loyalty, and
productivity (Alzain et al., 2023). Successful companies develop a positive culture by fostering a
sense of community, providing opportunities for employee development and growth, and
promoting a supportive and inclusive work environment (Alkhodary, 2023). A pro-innovative
leadership style encompassing traits of transformational, authentic, servant, and cooperative
leadership, along with the promotion of openness, and embracing the possibility of making
mistakes, has been an essential approach to foster cultures that facilitate creativity and innovation
in remote teams (Jolanta, 2023). By adopting these strategies, successful companies can create and
maintain robust organizational cultures that not only adapt to but thrive in virtual work
environments.
Leveraging Technology for Cultural Integration in Remote Teams
Companies have been experiencing both success and failure in leveraging technology to
produce cultural integration in remote teams. Companies that fail, often do so by not recognizing
35
softer cultural dimensions influencing information and communication technology (ICT)
engagement, leading to suboptimal outcomes in remote team integrations, especially in
environments with adversarial or clannish aspects (Gajendran & Brewer, 2007). Deficiencies in
project management practices and a lack of strategic technology tools for monitoring projects often
contribute to failures in leveraging technology for cultural integration (Ramos & Mota, 2015).
Logistical complexities can create struggles for companies and often there are limited opportunities
for intervention post-technical failure or adverse event, especially in digitalized remote
environments (Zahradka et al., 2022). Failure to consider the dynamic evolution of technological
interventions and stakeholder actions can lead to limited success as the intervention often can
become an independent variable, and its effects upon individuals become dependent variables that
require continuous improvement and validation (Saxe & de Kirby, 2018). Increased dependence on
technology for remote collaboration brings heightened cybersecurity risks and potential system
failures, posing significant challenges to cultural integration efforts (Varun et al., 2023). These
difficulties highlight the challenges companies face in enhancing cultural integration for remote
teams through the utilization of technology, but not all companies are failing.
Success in fostering cultural integration in remote teams through technology and tools
largely depends on addressing cultural, technical, and managerial challenges. Companies have
successfully adapted digital health programs, such as mobile phone-based heart failure programs,
for remote communities, demonstrating effective adaptation to different cultural contexts.
However, success depends on considering the cultural context and community involvement (Wali
et al., 2023). The use of remote wireless intelligent layered water injection technology for two-way
communication in the oilfield industry exemplifies successful technological adaptation, resulting in
improved operational efficiency in remote teams (Song et al., 2023). In-house development can
play a major role in solving organizational challenges while also fostering cultural integration in
36
virtual work environments as Sabri discusses in examining Petronas Corporation’s use of this
strategy (Sabri, 2022). Overcoming barriers like multitasking, power imbalances, technical
challenges, and communication pitfalls is crucial and companies that effectively address these
challenges enhance team cohesion and productivity in virtual settings (Mortezaee & Sinclair,
2023). Companies have found success by engaging in strategic collaborations between IT firms and
stakeholders creating win-win cooperative mentalities, anticipated alignment, and ultimately
identity alignment which in turn boost employee motivation and create cultural integration through
the use of technology in remote teams (Ungureanu et al., 2020).
Literature Review Conclusion
This comprehensive literature review spanned diverse aspects of remote work,
encapsulating the historical evolution, employee perspectives, leadership challenges, motivational
dynamics, and the influence on organizational culture. The amalgamation of theoretical
frameworks, empirical studies, and practical insights offers a robust foundation for understanding
the incongruent feelings surrounding a return to work. As organizations grapple with the
complexities of transitioning between remote and physical workspaces, the synthesized knowledge
herein serves as a guidepost for future research endeavors and practical strategies to navigate the
intricate dynamics of the modern workplace.
Conceptual Framework
The modern workforce has been in a state of flux, with technological advancements and
recent global events prompting organizations to reevaluate traditional working models. Shifts like
return-to-office mandates, hybrid arrangements, and full remote work setups have necessitated a
deeper examination of the factors influencing employee motivation and performance. To navigate
this complex landscape, it was essential to draw on established psychological theories of
motivation. This dissertation leaned on Herzberg's Two-Factor Theory (1959) and Maslow's
37
Hierarchy of Needs (1943) to construct a conceptual framework that addressed the impact of
changes in working environments on employee motivation and performance.
Herzberg's Two-Factor Theory Overview
Herzberg's Two-Factor Theory, also known as the Motivation-Hygiene Theory, posits that
there are two sets of factors influencing work motivation: hygiene factors and motivators (Herzberg
et al., 2017). Hygiene factors, like company policies, supervision, salary, interpersonal relations,
and working conditions, do not inherently motivate employees but, if inadequate, can lead to
dissatisfaction. In contrast, motivators like achievement, recognition, the work itself, responsibility,
and growth or advancement are intrinsic to the job and can generate significant levels of motivation
and job satisfaction.
In the context of changing working models, hygiene factors may include the logistical and
emotional impacts of shifts, like commuting concerns or work-life balance, while motivators might
encompass the empowerment and flexibility that new working arrangements can afford.
Maslow's Hierarchy of Needs Overview
Maslow's Hierarchy of Needs is a theory in psychology that prioritizes human needs into
five levels in a pyramid structure, ranging from basic (physiological) needs to higher-level (selfactualization) needs (Maslow, 1943). The five levels are:
1. Physiological Needs: Basic survival needs like food, water, and shelter.
2. Safety Needs: The need for security, stability, and freedom from fear.
3. Love and Belonging Needs: The desire for relationships, affection, and companionship.
4. Esteem Needs: The aspiration for respect, self-esteem, status, and recognition.
5. Self-Actualization Needs: The pursuit of self-fulfillment and realizing personal potential.
When organizations shift working models, they can inadvertently affect different levels of
Maslow's Hierarchy. For instance, a return to the office may heighten safety needs due to health
38
concerns, whereas remote work arrangements can influence the fulfillment of love and belonging
needs through reduced social interaction. The proposed conceptual framework integrates these two
theories to analyze the motivational responses of employees to these transitions in working models.
The framework assesses the interaction between hygiene factors and basic safety needs, as well
as the alignment between motivators and higher-level needs like esteem and self-actualization. This
framework also aimed to help organizations understand the complex dynamics of employee
motivation and performance, especially in the face of mandatory changes to work arrangements. It
provides insights into the psychological drivers of workforce engagement and offers a platform for
developing informed strategies to manage transitions effectively.
Below, in Figure 5, is a representation of the conceptual framework illustrating the interplay
between Herzberg’s Two-Factor Theory and Maslow’s Hierarchy of Needs in the context of
evolving working models.
Figure 5
Interplay Between Herzberg’s Two-Factor Theory and Maslow’s Hierarchy
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Understanding the dualistic nature of Herzberg's hygiene factors and motivators, alongside
the stages of Maslow's Hierarchy, presents a robust framework for analyzing changes in employee
motivation and performance. The integrated application of these theories offers a valuable lens
through which organizations can approach the challenges and opportunities posed by evolving
working models. This conceptual framework serves as the cornerstone for this dissertation, guiding
the exploration of empirical phenomena within the contemporary corporate setting.
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Chapter Three: Methodology
Research Questions
This study’s purpose was to examine the ways employees perceived changes to their remote
working arrangement or the idea that changes could impact their working arrangement and how
that influenced their motivation, performance, and productivity. The following research questions
guided this study to gain understanding on these thoughts from US workers.
1. Is employee motivation affected by a change from a remote work model to hybrid, or inperson work arrangements or when a change has been announced?
2. Do perceptions of remote work's influence on performance vary significantly across
demographic groups (e.g., age, gender, or income level) in the survey responses?
3. How do employees' productivity ratings vary based on whether they have received an
announcement about upcoming changes to remote work arrangements or have been when
they have recently been subjected to a change?
This dissertation was a non-empirical study of the Survey of Working Arrangements and
Attitudes (SWAA) conducted by the WFH Research project, which began in May of 2020 in
response to the impacts of COVID-19 (Barrero et al., 2021). The goal of further evaluating SWAA
for the period that ran from May 2020 through June 2024 was to find how employee motivation
was being impacted by changes or theoretical changes to remote, hybrid, or in-person work
arrangements. SWAA encompassed 259,030 respondents and asked 711 questions across more
than four years. The decision to further evaluate the WFH Research project data was made to limit
Type II errors in this research as any conducted survey would be small and variability would have
been large (Faber & Fonseca, 2014).
41
Overview of Methodology
Herzberg’s Motivation theory was the key theoretical framework used to examine this
problem in the workplace as it looked at employee needs and broke them into two factors. There is
motivation or the desire to personally develop and there is hygiene or the need to avoid
unpleasantness and discomfort (Herzberg et al., 2017). In this case, conceptually there was a desire
to see if work model and work location have an impact on employee motivation, performance, and
effectiveness.
Data Collection: Existing SWAA Surveys
The WFH Research project began in May of 2020 in response to the severe impact of
COVID-19 on workplace arrangements(Barrero et al., 2021). The Survey of Working
Arrangements and Attitudes (SWAA) is a monthly survey of between 2,500 to 10,000 US residents
aged between 20 and 64 from that project (2021). Respondents who were younger than 20 and
older than 64 were both blocked from participating in the survey project due to their limited
working experience and closeness to retirement age. The SWAA researchers believed the responses
from these demographic groups would be of limited value based on the youngest individuals
having limited work experience and the oldest respondents potentially creating outlier data due to
their closeness to retirement age. The study was compiled into two versions of the data based on
annual earnings. The first compiled version was restricted to persons who earned $10,000+ in the
prior year, going back to May 2020. The second version had no earnings restriction, going back to
quarter two of 2022 (2021). All survey respondents were United States-based workers.
Participants: SWAA Surveys
SWAA respondents were working-age persons in the United States who reported workrelated earnings over a threshold. Between May 2020 and March 2021, a threshold of $20,000 in
earnings for 2019 was used (Barrero et al., 2021). Between April and September 2021 that
42
threshold transitioned to $10,000 in 2019. Between January and March of 2022 there was a final
transition to $10,000 in earnings for the prior year.
Instrumentation: Survey
The first survey wave was conducted in May of 2020. Data collection continues monthly
today, but for this study the last wave of data included was from June of 2024. Each survey wave
collects between 2,500 and 10,000 responses. Initial waves were 2,500, but that increased
permanently to 5,000 monthly responses in April 2021, and later to 10,000 responses in 2022.
The US SWAA research team designed the survey questions and then used commercial
survey providers to field the survey on their behalf via the internet. Those providers recruited
respondents via panel aggregators who had access to potential respondents from various sources.
Potential respondents signed up to receive internet surveys generally and then received invitations
to individual surveys. Respondents did not sign up for the SWAA survey specifically. Because
commercial providers were used there were no direct interactions with respondents. In the survey
questionnaires, there were no asks for any private identifying information, and the SWAA team is
not otherwise able to identify its respondents.
Data Analysis: Survey
Post survey the SWAA data was re-weighted to match the share of individuals in the
Current Population Survey (CPS) of a given age, gender, educational attainment, and earnings
level. Therefore, the data matched the population in the CPS along those dimensions. The
reweighted distribution, in the words of the SWAA team, was also not far off for other variables
like the industry of the current or most recent job and the Census Division (i.e. region).
Further data analysis I conducted as a researcher focused on narrative analysis to build a
master narrative that guided this study. Efforts were put into uncovering any thematic elements that
were present from the SWAA survey data. Cluster analysis was performed to see if any patterns or
43
trends were revealed from the various demographic groups within the survey pool that could be
areas for deeper exploration (Everitt, 2011).
Additionally, as a researcher I attempted to utilize modern large language model (LLM)
computing from ChatGPT and other technology companies to further uncover thematic elements or
data relationships that were not made apparent. However, the dataset was too large to be processed
by ChatGPT, Claude, Gemini, LlaMa, Anthropic, or MetaAI. So, that attempt was abandoned and
instead the data was evaluated using the Statistical Product for the Social Sciences (SPSS) tool
from IBM to run correlation and significance tests.
Validity and Reliability: Survey
The initial goal of the further examination of this study was to best capture opinions that
represented and coalesced with the reality of the American worker’s experience in dealing with a
changed or changing work location. This reality is, of course, an ever-changing construct that is
nearly impossible to capture. Therefore, the goal was to present a contextual framework that
presented a holistic interpretation of what is and was happening (Merriam & Tisdell, 2015). The
data set was so large and extensive that all analysis variables could be validated at a 95%
confidence interval. Utilizing Anova test consistently led to rejections of the null hypothesis that all
population means from the survey were equal.
Ethics and Role of the Researcher
I always have been a person who has felt a bit stuck in the middle of a transition or space. I
grew up in Kentucky, but I’m not a Southerner. I’ve lived in the Seattle area for the last 23 years,
yet I’m not a Seattleite. There are however some things I have pinned down. I am the following: a
man, a heterosexual, a husband, a father, a son, a brother, a friend, an executive, a worker, and a
White person. I am 47 years old, and I am the first male in my family lineage to have graduated
from college. My Grandfathers finished the 2nd and 3rd grades respectively. My great-
44
grandparents before them were illiterate. Still, though, it is not lost on me that I live a life of
privilege. My parents made more money than most and as such, I never wanted for anything, went
hungry, or suffered the burdens of poverty in my childhood. This is my positionality, or “how one
is situated through the intersection of power and the politics of gender, race, class, sexuality,
ethnicity, culture, language, and other social factors” (Douglas & Nganga, 2015). Mitigating
potential issues that come from my positionality for this study could have proved difficult, but
simply being conscious of these factors and that they could have influenced me subconsciously
made a positive step towards removing bias.
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Chapter Four: Results
This study examined a multitude of factors, feelings, and demographic data points and how
these items impact employee motivation, performance, and productivity. The examination delved
into how this quantitative data illustrates the feelings of American worker’s when it comes to
employee motivation, performance, and productivity when there is a change, or the announcement
of a change, to employee work location arrangements. This chapter provides insights for leaders
and organizations wishing to create work environments that enhance motivation, performance, and
productivity. The completed data analysis showed clear preferences for remote and hybrid working
models from survey respondents and that employees presently in remote or hybrid roles as having
had the strongest preferences for continuing in those arrangements. Many demographic data
categories were also examined to see if remote and hybrid work preferences were systemic or if
various factors consistently lead to higher preferences for these arrangements. Of these factors, the
ones that seemed to have the highest correlation to a respondent’s feelings on remote, hybrid, and
in-person working arrangements were income, years of education, and how effective someone
believed themselves to be when working remotely amongst others.
Demographic Data
Quantitative surveys from the Survey of Working Arrangements and Attitudes (SWAA)
were used to collect demographic data, feelings on remote, hybrid, and in-person working models,
and a compendium of other data points that may have impacted a respondent’s feelings on these
subjects. Some of these additional questions looked at whether one owned a pet, had children at
home, and what daily grooming habits were like on both work from home and work in office days.
The Work From Home Research Project began its Survey of Working Arrangements and Attitudes
in May of 2020 and this survey project is still ongoing (Barrero et al., 2021).
46
Evaluation of the data for possible correlations was conducted using Cluster Analysis, OneWay ANOVA, P-Plot Analysis, One Sample t-Tests, Pearson Correlation Tests, Paired-Samples tTests, Relationship Mapping, 2-Tailed Tests, Frequency Analysis, and Linear Regressions. While
these tests could not allow for causality to be determined, but the hope was that themes would
emerge and that this thematic data would help to elucidate areas of similarity and difference
amongst demographic subgroups that may help shed light onto the feelings that employees have
and may hold in the future about remote, hybrid, and in-person working models. These learnings
may also be useful in the future to study how any changes to these models may impact employee
motivations. Finding corollary data in such a large dataset has challenges, but utilizing SPSS was
helpful in evaluating such a large amount of data.
Research Question 1
Data was examined using the tests mentioned in the demographic data section of this
chapter to attempt to answer the first research question which asked, is employee motivation
affected by a change from a remote work model to hybrid, or in-person work arrangements or when
a change has been announced? The motivation questions, listed in the appendix, focused on
employees' preferences, reactions to work arrangements, and factors influencing their desire to stay
or seek new opportunities. These questions assessed how remote work, hybrid, and in-person
working arrangements and changes to them affect employee motivation or satisfaction with their
job.
Valuation of Remote Work as Motivation
One of the ways to examine the motivation of workers is through a survey question that
assesses employees’ valuation of remote work. It effectively shows how much the flexibility of
remote work is valued by employees and how much it motivates them. The motivation questions of
the study further assess how remote, hybrid, or in-person work and changes to those arrangements
47
impact an employee's motivation and desire to do their job. Further, these motivation questions
help show the value employees placed in these working arrangements and how changes to them
impacted their motivation and desire to do their job duties.
Employee Preferences for Remote Work as a Motivator
The questions in Figure 6 are from a two-part question-and-answer sequence. The first
question asks, “How would you feel about working from home 2 or 3 days a week?” the answer
possibilities are: a) Positive – I would view it as a benefit or extra pay, b) Neutral, and c) Negative
– I would view it as a cost or a pay cut (Barrero et al., 2021). Both those who answered in the
positive and negative were displayed a secondary question that asked how much of a pay raise (as a
percent of their current pay) would that respondent value as much as the option to work from home
2 or 3 days a week and for those who responded that it would be a negative they were asked the
same question, but the words pay raise were removed and pay cut was substituted in its place to
gain an understanding of how strongly respondents felt about this type of arrangement change. As
this question was not present on all survey waves there were 25,292 respondents. Using a T-Test it
was determined that the mean response on this question saw it viewed as an equivalent to an
8.408% pay raise, the standard deviation for this question was 12.7796, and the standard error of
the estimate was 0.0804.
Comparison of Remote Work Value to Financial Incentives
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Figure 6
How Much of a Raise/Pay Cut Would You Value to WFH 2 to 3 Days per Week?
Figure 6 Illustrates the fact that 67% of workers surveyed value remote work at least as
much as receiving a 15% pay raise. More than 22% of those surveyed valued remote work higher
than that and nearly 11% saw the benefits of remote work as having as much value as receiving a
pay raise of more than 25% at a significance level of t (25291) = 104.629, p = <.001. This is a
factor that is strongly motivating a portion of the workforce in a new and unique way.
Impact of Return-to-Office Mandates on Motivation
The survey shows that employee motivation is negatively impacted when organizations
announce a full return to the worksite where the expectation going forward is that all employees
will at a minimum work full on-site 5-day work week on-site. In fact, the data showed that 42% of
employees would start looking for a new job right away and that 7% would quit before the imposed
deadline.
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Negative Impact of Forced Return-to-Office Announcements
This is further illustrated in Figure 7, which was answered by 48,573 survey respondents.
The choices in the survey were 1) I would comply, 2) I would start looking for a new job that lets
me work from home at least 1 or 2 days a week, and 3) I would quit my job on or before the
imposed deadline. The mean average was nearly exactly in the middle of the three options at 1.48
with a standard deviation of 0.618 and standard error of the estimate of 0.003.
Figure 7
How Would You Respond if Your Employer Announced That All Employees Must Return to the
Worksite 5+ Days a Week Starting the Month-After-Next?
Employee Reactions to Mandatory In-Person Work
Further review of the analyzed data showed a couple of insights. One that is displayed in
Figure 8 illustrates the preferences of individuals to this same question but looked at from the
subgroups of those actively working onsite today, those working remotely today, and those not
working presently.
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Job-Seeking Intentions Linked to Motivation Decline
Interestingly, those who are not working presently showed the strongest desire to reject an
employer’s return to work mandate. A full 51% of those not working presently expressed that they
would start looking for a new job that allowed them to work 1 to 3 days remote or that they would
quit their job before the employer’s mandated deadline begins. The actively remote working group
was consistent with the average with 42% stating they would explore alternate employment or quit
before the mandated deadline arrived. This along with the data of the actively on-site respondents
is visible in Figure 8.
Figure 8
Based on Your Current Working Status: How Would You Respond if Your Employer Announced
That All Employees Must Return to the Worksite 5+ Days a Week Starting the Month-After-Next
Demographic Variations in Motivation Responses
This section examines how motivation levels differ across various demographic groups in
response to changes in work arrangements. By analyzing data on age, gender, education, and other
51
demographic factors, it aims to uncover key insights into how these differences shape employee
attitudes toward motivation.
Political Affiliation and Motivation in Response to Work Arrangement Changes
This subsection explores the role of political affiliation in shaping employees' motivation
when work arrangements change. It highlights how political perspectives may influence reactions
to remote, hybrid, or in-person work mandates, offering insights into differing attitudes based on
political beliefs. Political party affiliation showed that 38% of those identifying as Democrats
would look for a new job or quit their existing job. A full 50% of those identifying as Republicans
indicated that they would leave their job or look for a new one based on an announced change of
this type at a significance level of t (25118) = -19.132, p = <.001. This was the highest indicator of
all demographic and descriptive data for this survey question on employer mandates for those
actively working during the study. Categories of data analyzed included race, gender, level of
education, level of income, age, state of residence, census demographic location, work industry,
parental status, marital status, occupation, pet ownership, and grooming habits. The Republican
group also had the strongest aversion to return to the worksite with 10% of respondents saying they
would leave their current job before the first day of the forced mandate took effect. This is
displayed in Figure 9.
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Figure 9
Based on Your Political Affiliation: How Would You Respond if Your Employer Announced That
All Employees Must Return to the Worksite 5+ Days a Week Starting the Month-After-Next
Another factor the SWAA study measured was the likelihood of respondents to accept a job
offer if one were extended based on the number of remote workdays the employer offered. Survey
respondents indicated that when an employer scheduled at least 1 remote working day per week
that they would be 52% more likely to accept an offer of employment reported at a significance
level of t (2959) = 122,293, p = <.001. Although, 15% of respondents stated that this same
arrangement would make them 15% less likely to accept the job offer. When the number of remote
workdays changed to two or three days per week the likelihood of acceptance moved up to 60%
and the indications of less likely to accept moved down to 10% reported at a significance level of t
(2890) = 120.209, p = <.001. The survey data showed that employment offers promising four to
five remote working days would have a positive effect on the likelihood of acceptance and saw
favorable acceptance rate indications climb up to 64%. At the same time, the likelihood of this
53
arrangement making it less likely that a respondent would accept this type of offer stayed steadily
in a similar 11% range and was reported at a significance level of t (1200) = 74.661, p = <.001.
Other Demographic Factors Influencing Motivation
This question series elucidates that employees are motivated to find and retain remote
working arrangements and that it contributes to employee motivation. This series coalesces with
the top benefits of remote work that the 65,082 employees who responded to the question identified
during this survey. These benefits were a more flexible environment and schedule as identified by
42% of respondents, no commute for 38%, and lower expenditure on lunch and fuel for 46%. A
close second series of benefits were a greater ability to spend time with family which was
identified by 37%, less personal grooming time obligations was selected by 36% of respondents,
and easier access to quite workspaces which was included by 35% of respondents. All of these
items that afforded individuals with more time and freedoms all selected by respondents at a rate of
34% or greater. The top in-workplace benefits were the ability to more easily collaborate with
colleagues according to 43% of respondents and greater social interactions which was selected by
45% of the 65,088 respondents. The largest shortcomings of returning to the office were quite
places to work which only 20% of respondents indicated was a benefit, facetime with management
which 30% saw as a benefit, and boundaries between personal and professional lives which was
seen as a benefit by 36% of those who responded. Based on these percentage answers from the
surveys, employees seemed to value these remote work benefits more than they did the in-office
benefits that they also rated. These questions evaluated the impact of remote and hybrid working vs
in-office work and how these factors of importance impacted the motivation of the respondents.
Research Question 1 Summary
Research Question 1 explored whether employee motivation is affected by changes from a
remote work model to hybrid or in-person work arrangements or when such changes are
54
announced. Findings revealed that a significant proportion of employees perceive forced transitions
to in-person work negatively, with many citing increased commute times and loss of flexibility as
primary concerns. This aligns with Herzberg's Two-Factor Theory, where flexibility and autonomy
are motivators that foster job satisfaction, whereas enforced changes, particularly those that add
logistical complexity, like commuting, function as hygiene factors that can lead to dissatisfaction.
Employees valued the flexibility offered by remote and hybrid arrangements as equivalent
to or even more beneficial than a pay raise of up to 15-25%, indicating that autonomy in work
arrangements is a strong motivator. The announcement of return-to-office mandates was found to
diminish motivation, with a notable percentage of employees expressing an intention to leave their
positions. These findings emphasize that the ability to control one's work environment, both
physically and psychologically, play a crucial role in motivation. When employees perceive their
autonomy and psychological safety as being threatened by rigid policies, their motivation to stay
engaged and productive can be significantly impacted.
These insights suggest that organizational efforts to improve motivation and retain talent
must consider employees' desire for flexibility and psychological safety. This reflects the guiding
conceptual framework of this study, where both Herzberg's Motivation-Hygiene Theory and
Maslow's Hierarchy of Needs are integrated to show that autonomy and workplace flexibility fulfill
higher-level needs, such as esteem and self-actualization (Herzberg et al., 2017; Maslow, 1943).
Ultimately, these results emphasize that organizational policies regarding work location
significantly influence employee motivation, and inclusive leadership strategies that account for
individual needs, including psychological safety, are crucial for enhancing employee satisfaction.
Research Question 2
The second research question aims to explore employee perceptions regarding their
efficiency and productivity in remote work settings. This section provides an analysis of the data
55
collected to understand how working remotely impacts perceived work output, effectiveness, and
satisfaction.
Perceived Efficiency and Productivity in Remote Settings
This subsection further examines employee insights on their productivity and efficiency
while working in remote environments. It highlights the specific factors influencing these
perceptions, like work-life balance, technological support, and the flexibility offered by remote
arrangements.
Overall Self-Reported Efficiency in Remote Work
The second research question asked, in what ways do employees perceive remote work as
influencing their performance? The performance questions of the study assess how remote, or
hybrid work impacts an employee's ability to do their job efficiently. Further, these performance
related questions help shed light on the value employees placed upon remote, hybrid, and in-person
work arrangements and how these arrangements and changes thereunto are perceived to impact the
performance of one’s job duties.
Factors Contributing to Higher Productivity in Remote Work
The main question to be examined as a measure of self-reported efficiency of employees
working from home was, “How efficient are you at working from home?”. In answering this
question, it was obvious that individuals felt that they were more productive (48%) or as productive
(40%) working from home versus how they felt about working at their business premises. Still,
some individuals (12%) felt that they were less efficient at home as compared to their place of
business. The question was answered by 141,828 respondents with a mean average response of
1.63, a standard deviation of 0.680, and a standard error of the estimate at 0.002. The possible
responses to the question were: 1) Better -- I am more efficient at home than working on business
56
premises, 2) About the same -- I'm equally efficient in both places or 3) Worse -- I am less efficient
at home than working on business premises.
Demographic Insights on Remote Work Performance
This section analyzes the performance of remote work across different demographic groups,
including age, gender, and education level. The analysis aims to uncover any significant variations
in efficiency and productivity based on demographic characteristics.
Variations in Perceived Efficiency by Race
One of the noteworthy datapoints from this question was when the data was sorted into
racial demographic categories and then analyzed for being more efficient, as efficient, or less
efficient at home versus in the workplace. In all racial groups employees rated themselves as
efficient or more efficient when working from home. However, as the data was further evaluated
one thing that stood out as a statistically significant difference was that those identifying as any
race other than White were more likely to say that they were equally efficient in both settings,
home and the workplace. This data is displayed in Figure 10. In addition to race, categories
included: gender, level of education, level of income, age, state of residence, census demographic
location, work industry, parental status, marital status, occupation, political affiliation pet
ownership, and daily grooming habits. No demographic group indicated that they were less
efficient at home when compared to their employer’s physical location.
The White racial group however was the only group where a majority stated that they were
more efficient working remotely. This is illustrated in Figure 10 which shows that 51% of those
identifying as White also stated they were more efficient working from home vs. 38% who stated
that they were equally efficient, and 11% who said that they were less efficient and this was
reported at a significance level of t (120725) = -8.641, p = <.001. These three percentages were
higher, lower, and on par with the overall group which tended to break in a more even distribution
57
split between as efficient and more efficient while all groups hovered near the same percentages for
the less efficient response with two exceptions. Both, those who identified as Native American
(15%) and those who identified as Native Hawaiian (17%) rated themselves higher than the overall
average in that less efficient from home response which had averaged at 11%. This finding is likely
worth further exploration as it is possible that it could be the byproduct of cultural or historical
barriers present for those of these races. Native people of America have suffered from relentless
violence, upheaval, and the seizure of indigenous lands since the 1500s (Ostler, 2019)
Figure 10
How Does your Efficiency Working From Home Compare to Your Efficiency Working on Your
Business’s Premises? (by Race)
Age-Based Differences in Perceived Productivity
Reviewing this same question’s data through the categorical lens of age saw those who
were in the 30 to 39 and 40 to 49 age ranges answer that they were more efficient working
remotely. The data showed that 53% of the respondents in the 30 to 39 age range answered in this
way at a significance level of t (83569) =23.856, p = <.001 and that 49% of those in the 40 to 49
58
range did as well at a significance level of t (60926) =14.642, p = <.001. Those in the 20 to 29 age
range said they were more efficient only 38% of the time and were equally efficient 40% of the
time. The 50 to 64 age range ranked themselves as more efficient 41% of the time and as efficient
45% of the time. There was no age range where employees felt overwhelmingly that they were less
efficient as the 20 to 29 group said this was the case 22% of the time, the 30 to 39 group indicated
it was the case 10%, the 40 to 49 group was 11% and the 50 to 64 group was 15%. The youngest
grouping of workers by a percentage of respondents said they were less efficient working from
home more than any other group. This data is presented in Figure 11.
Figure 11
How Does Your Efficiency Working From Home Compare to Your Efficiency Working on Your
Business's Premises? (by Age)
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Educational Attainment and Productivity Perceptions
Attaining a college degree or beyond made respondents rate themselves as feeling that they
were more efficient. Inversely those who had not completed a 4-year degree rated that they were
equally efficient in both environments, but in each of the three measured subgroups each of these
non-degree holding groups did not rate themselves as high in the more efficient category as is
illustrated in Figure 12.
Figure 12
How Does Your Efficiency Working From Home Compare to Your Efficiency Working on Your
Business's Premises? (by Education)
Current Working Model, Geographic, and Other Demographic Data Impacts on
Performance Perceptions
This section aims to explore how various factors, like the current working model (remote,
hybrid, in-person), geographic location, and other demographic data, influence employee
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perceptions of their performance. The analysis focuses on understanding the nuances of how
different working conditions and demographic elements contribute to differences in perceived
productivity and effectiveness.
Current Work Model Impacts on Performance Perceptions
Examining this question by looking at those who are currently working on premises, those
who are currently fully remote, and those who are not working also causes anomalistic results for
the individuals who are currently working remotely and how they rate themselves as more efficient
when working remotely. Figure 13 shows that the currently working remote group believes
themselves to be more efficient by a margin that was higher than any of the other groups (59%).
This group that was remotely working rated itself as more efficient than the other two groups and
had a lower ratio of those answering they were less efficient remotely when compared with the
other two groupings. Those working on their company’s premises said that they were more
efficient remotely (36%), about the same (47%), and worse (17%) of the time. Remote workers
indicated that they were more efficient (58%), about the same (34%), and less efficient (8%) of the
time This less efficient percentage for the currently remote group was also a substantially lesser
percentage than the other two groups. For those not currently working the responses were more
efficient (40%, same efficiency (47%, and lesser efficiency (13%).
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Figure 13
How Does Your Efficiency Working From Home Compare to Your Efficiency Working on Your
Business's Premises? (Current Working Status)
Impact of Geographic Regions on Remote Work Efficiency
Those living in states that were identified by SWAA as politically “Red States” rated
themselves as slightly more likely to be equally efficient versus more efficient for this trimodal
question. While those who were identified as living in politically “Blue States” rated themselves as
more efficient when working remotely than when working on the business premises. The Red and
Blue state designations used by SWAA correspond to how a given US state’s electoral college
votes went for the Republican (Red State) or the Democrat (Blue State) presidential candidate in
the 2020 election. This information is illustrated in Figure 14.
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(Office, Remote, Not)
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Figure 14
How Does Your Efficiency Working From Home Compare to Your Efficiency Working on Your
Business's Premises? (by Red/Blue State)
Geography was also significant to whether one would indicate that they were more efficient
working remotely versus location not impacting that level of efficiency. Of the nine identified
census zones in the United States two showed a higher response rate for the greater efficiency
when working remotely question. These two areas were the Mid-Atlantic area, and the Pacific area
as is illustrated in Figure 15. The Mid-Atlantic Census Area includes the states of New York, New
Jersey, and Pennsylvania which includes the metro areas of New York City, Philadelphia, and
Pittsburgh. This Mid-Atlantic Census Area also has the Canadian metro areas of Montreal,
Waterloo, and Toronto within 50 miles of the New York border. As a result of having six large tech
people centers out of the top 50 as described by CBRE in their Scoring Tech Talent 2024 report, it is
possible that a reason for individuals feeling better about their efficiency when working remotely is
that they are also more comfortable with the technological requirements (Cottrell et al., 2024). The
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Pacific Census Area includes the metro areas of the San Francisco Bay Area, Seattle, Los Angeles,
San Diego, Portland, Inland Empire, and Sacramento and likely has the same factors in play as a
result.
Figure 15
How Does Your Efficiency Working From Home Compare to Your Efficiency Working on Your
Business's Premises? (Census Division)
Influence of Other Demographic Data on Productivity Perceptions
Many more demographic categories showed some level of influence over this survey
question though they did not rise to a level of statistical significance. Still, many did show a level
of statistical significance and included the following: men thought they were more efficient (53%)
versus the same (36%), while women were more split equally between same (45%) and more
(43%). People without children at home felt they were as efficient or more (88%) by a slightly
lower margin than those with children (92%). Those who had dogs (89% versus 86%) and those
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who identified as Democrats (91% versus 87%) also all rated themselves as or more efficient in
higher number than the rest of their corresponding demographic groups, but only by small margins.
Finally, when it came to morning routines, 8594 respondents answered questions on what routines
they did and did complete on remote workdays and how that impacted their efficiency when remote
working. From the responses: setting an alarm (47% versus 44%, wearing clean clothes (48%
versus 40%), bathing (47% versus 42%), shaving (51% versus 41%), putting on makeup (53%
versus 42%), and wearing deodorant (46% versus 44%) on work from home days all had a positive
impact on someone selecting that they were more efficient working remotely, but these results
came from relatively small sample sets when compared to the other elements of the SWAA study.
Brushing teeth did not produce this consistent result as individuals who performed this hygiene
routine each morning rated themselves more efficient at a slightly lower rate than their counterparts
(46% versus 48%),
Research Question 2 Summary
Research Question 2 aimed to explore how employees perceive remote work as influencing
their performance, with findings suggesting a nuanced interplay between flexibility, autonomy, and
psychological safety. The data highlighted that employees associate remote work with higher levels
of job satisfaction, a greater sense of psychological security, and an enhanced ability to focus, all of
which positively affected performance. Of the employees surveyed, 89% indicated that they were
as or more effective working remotely compared to on-site work, with almost half (48%) reporting
they felt more efficient in a remote environment. This supports Herzberg's Two-Factor Theory,
where flexibility and autonomy act as motivators rather than hygiene factors.
Employees emphasized that working remotely allows for better work-life integration,
reduced commuting stress, and an increased sense of personal control, contributing to enhanced
engagement and performance outcomes. The remote environment also fostered a sense of
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psychological safety, as employees felt more secure in managing their responsibilities without the
added pressures of a rigid workplace structure. These findings align with the proposed conceptual
framework, integrating Herzberg's and Maslow's theories to suggest that autonomy in work
arrangements can fulfill higher-level needs of esteem and self-actualization, while psychological
safety serves as a foundational element for optimal performance.
Ultimately, the ability to choose one's work setting, along with a secure and supportive
environment, appears to play a crucial role in boosting employee motivation, productivity, and overall job
performance. This demonstrates that remote work is not merely a logistical adjustment but a critical factor in
fostering organizational effectiveness, as seen through the lens of Herzberg’s Motivation-Hygiene theory,
where supportive work conditions and psychological safety are essential motivators.
Research Question 3
The third research question investigates how mandatory return-to-office policies impact
employee productivity. This section presents an analysis of survey responses that reflect employee
reactions to these mandates, particularly focusing on perceived changes in efficiency, motivation,
and overall work output.
Impact of Mandatory Return-to-Office on Productivity
This subsection examines the specific effects of compulsory return-to-office policies on
employees' productivity. It aims to determine whether these policies lead to increased, decreased,
or unchanged levels of productivity, based on survey data and employee feedback. It asked, “How
is employee productivity affected when remote work arrangements change or when there has been
an announced plan for a change?”. As organizations have transitioned between remote, hybrid, and
in-person work models, productivity measurement has emerged as a key metric of interest to both
employers and employees. Of the survey questions asked, the one that examined this element the
most closely was asked to 48,573 individuals. Using a T-Test it was determined that the standard
deviation for this question was 0.618, and the standard error of the estimate was 0.003.
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The question asked, “How would you respond if your employer announced that all
employees must return to the worksite 5+ days a week starting the month after next?”. The possible
answers for the question were: “I would comply and return to the worksite” (59%), “I would start
looking for a job that lets me work remotely at least 1 to 3 days a week, but return to the worksite if
I don’t find one by the deadline” (34%), and “I would quit my job on or before the deadline,
regardless of whether I got another job” (7%). The question explored the effects of shifting work
arrangements, examining how employee productivity is influenced by factors like reduced
commute times, alterations in daily routines, and perceived stability in work policies.
Disparity Between Employer and Employee Preferences
Research Question 3 focused on how employee productivity is affected when remote work
arrangements change or when an announced plan for a change occurs. The data from the U.S.
Survey of Working Arrangements and Attitudes (SWAA) between May 2020 and June 2024
revealed insights into employee preferences, expectations, and their subsequent impact on
productivity. In particular, the gap between employer and employee preferences for the number of
remote workdays and the influence of choice over work arrangements are key components in
understanding productivity outcomes. Of the 259,030 respondents who were asked what percent of
days they wished to have as WFH. The mean answer for this question was 50% with a standard
deviation of 39.3545593 and an error of the estimate of 0.077325016. Further, a full 27% want full
remote work 100% of the time and all but 28% want remote work at least 20% of the time. This is
illustrated in Figure 16.
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Figure 16
Desired Share of Paid Remote Working Days
Gap Between Employer-Planned and Employee-Preferred Remote Workdays
Using Herzberg’s Two-Factor Theory as a guiding conceptual framework, this section
presents an analysis of the impact of changes in remote work policies on employee productivity
and job satisfaction. The study examined whether remote work arrangements act as motivators that
enhance productivity or as hygiene factors that contribute to dissatisfaction and reduced work
performance. Survey data was analyzed to assess employee perceptions regarding work
arrangement changes and their influence on productivity.
The analysis also incorporated Maslow's Hierarchy of Needs to explore the impact of
stability and control on employee productivity. The findings provide insights into the relationship
between changes in work arrangements and productivity, highlighting both the challenges faced by
employees and the opportunities that emerge under different work conditions.
Desired share of paid working days WFH after COVID (%)
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Impact of Lack of Alignment on Productivity
The SWAA data highlights a clear disparity between employer-planned and employeedesired remote workdays. Specifically, the employer-planned share of post-COVID remote
workdays was 36 % (mean), while the desired share by employees was significantly higher at 49%.
Furthermore, the median values revealed an even starker contrast, with employers planning for
20% of workdays as remote. At the same time, employees indicated that they wanted 40%. This
disparity underscores a misalignment between organizational policies and employee preferences,
which can have direct implications for productivity.
Autonomy as a Predictor of Productivity
This section explores how autonomy in the workplace influences productivity, particularly
in remote work settings. The analysis focuses on the relationship between employee freedom in
decision-making and their overall efficiency.
Employee Preference for Choosing Remote Workdays as a Productivity Factor
This subsection evaluates how the ability to choose remote workdays impacts employee
productivity. It looks to see if providing employees with flexibility contributes to better time
management, satisfaction, and perceived efficiency in their work. The SWAA data does show that
70% of employees prefer to choose their own remote working days rather than having these days
set by their employer. This finding emphasizes the importance of autonomy as a motivational
driver in remote work settings. The ability to choose work arrangements directly contributes to
fulfilling higher-level needs in Maslow's Hierarchy, such as esteem and self-actualization. When
employees have control over their work schedules, they experience a greater sense of
empowerment and personal efficacy, leading to higher engagement and productivity. This interplay
between Herzberg's motivators and Maslow's higher-level needs forms the foundation of the
conceptual framework proposed within this dissertation.
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Autonomy Driven Career Path Motivation
Employees also indicated that they would look for new employment if they were
guaranteed to find a job allowing them to work remotely. When asked this question, respondents
indicated 54% of the time that they definitely or possibly would look for a new employer if this
guarantee could be met. In all, 12,128 respondents answered this question and the mean answer
was 2.25 where an answer of 1) was definitely yes, 2) was probably yes, and 3) was No. The
standard deviation for this question was 0.772 and the standard error of the estimate was 0.007. The
results of this question are illustrated in Figure 17.
Figure 17
Would You Start Seeking Work if You Were Guaranteed to Find a Job That Would Allow You to
Work From Home?
Research Question 3 Summary
This question examined how employee productivity is impacted when remote work
arrangements change or when there is an announced plan for a change. The findings revealed that
sudden or mandated transitions to in-person work can have a significant negative impact on
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productivity, as a considerable number of employees view these enforced shifts unfavorably. The
survey responses indicate that when employers announce full return-to-office mandates, more than
a third of employees consider looking for other job opportunities that offer remote work flexibility.
Furthermore, a notable portion of respondents stated they would resign rather than comply with
rigid, in-office requirements, underscoring the importance of choice in work location as a driver of
productivity.
The analysis also highlighted a significant gap between employer and employee preferences
for remote workdays. Employees on average desired a larger share of remote workdays than
employers planned, which has direct implications for productivity. This misalignment signals a
critical need for organizations to consider employee preferences in work arrangement policies, as a
lack of alignment between employer mandates and employee expectations may result in decreased
engagement and motivation. The study found that 70% of employees preferred to choose their own
remote workdays rather than have them dictated by employers, suggesting that autonomy in
scheduling not only enhances employee satisfaction but also supports sustained productivity.
Ultimately, these findings reinforce the conceptual framework of this study, which
combines Herzberg's Two-Factor Theory and Maslow's Hierarchy of Needs. The autonomy to
choose one's work arrangement meets higher-level psychological needs, fostering a sense of
control and satisfaction that positively impacts productivity. The data indicate that when
organizations impose rigid work models without accommodating employee needs, productivity
may suffer. Therefore, the results suggest that adaptive and employee-centric work policies are
essential for optimizing productivity in a modern, post-pandemic workplace.
Summary of Results and Findings
Respondents in this study displayed a strong preference for working models that provided
greater individual autonomy and a sense of psychological safety. Those already participating in a
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remote or hybrid working arrangement showed an even greater preference for these models,
highlighting the connection between work location flexibility and employee satisfaction. The
purpose of this study was to provide deeper insights into these preferences and to explore how
changes to work arrangements impact employee motivation, performance, and productivity,
especially when transitioning from remote or hybrid models. The findings align with the
conceptual framework that guided this study, indicating that employees perceive themselves as
more motivated and productive in remote or mostly remote environments, which afford them
flexibility in managing the inseparability of their personal and professional lives. Chapter 5 will
build on these findings by presenting recommendations for how organizations can bridge the gap
between management and labor to cultivate a motivated, high-performing, and productive
workforce.
Chapter 4 presented a comprehensive analysis of results derived from the U.S. Survey of
Working Arrangements and Attitudes (SWAA) and related studies, which examined the influence
of remote work arrangements on employee motivation, performance, and productivity. The
findings underscored several key themes, including the misalignment between employer and
employee preferences, the critical role of autonomy in work arrangements, the impact of
psychological safety on well-being and productivity, and the value of flexible work models in
helping employees fulfill higher-level needs.
A notable finding from the study is the clear misalignment between employer-planned and
employee-preferred remote work arrangements. This disparity has negatively impacted motivation
and productivity, as employees overwhelmingly prefer more remote workdays than employers are
generally willing to offer. Autonomy emerged as a crucial factor influencing productivity, with the
ability to choose remote workdays being highly valued by employees. This aligns with Herzberg's
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Two-Factor Theory, where autonomy acts as a strong motivator that enhances motivation,
engagement, and overall productivity.
The findings also highlighted the vital importance of psychological safety in remote work
settings. Employees who felt supported in choosing their work arrangements reported feeling more
secure, valued, and engaged, leading to higher productivity levels. This underscores the need for
organizational policies that foster a psychologically safe and inclusive environment, where
employees feel empowered to voice their preferences and make autonomous choices about their
work arrangements.
Furthermore, the analysis demonstrated that flexible work arrangements not only address
basic hygiene factors, like reducing stress from commuting, but also fulfill higher-level needs,
including esteem and self-actualization, as described in Maslow's Hierarchy of Needs. Providing
flexibility in work arrangements enhances employee motivation and productivity, helping
employees achieve a more balanced, fulfilling work experience.
In summary, the findings from Chapter 4 provide strong evidence that employee
productivity is closely tied to the alignment or misalignment of work arrangement policies with
employee preferences, and to the presence of psychological safety in the work environment. The
key themes identified: misalignment of preferences, the importance of autonomy, psychological
safety, and flexible arrangements as pathways to higher-level needs all underscore the importance
of adaptive, employee-centric policies in creating a motivating and productive work environment.
Chapter 5 will delve further into these findings, offering evidence-based recommendations for
organizations to address the challenges identified. These recommendations will focus on enhancing
autonomy, fostering psychological safety, and aligning work policies with employee needs to
optimize motivation and productivity.
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Chapter Five: Discussion and Recommendations
The purpose of this study was to examine the feelings of workers on remote, hybrid, and inperson working models and how these models impact their motivation, performance, and
productivity. The study further examined how the announcement of a change to, or an actual
change from, a remote or hybrid model impacts employee motivation, performance, and
productivity. The study showed that US workers have a clear preference for remote and hybrid
models and believe these arrangements are adding value to their working and personal lives.
Employees of the study saw remote work as the reason for the elimination of time-consuming
activities, like commuting, while also providing a greater ability to manage family duties. These
time gains were shown to be valuable and are something that most of these workers do not wish to
give up.
Chapter 5 integrates the findings from Chapter 4 into actionable recommendations, explores
their broader implications, and proposes directions for future research. This chapter begins by
discussing the key findings in relation to the literature reviewed in Chapter 2, followed by
recommendations for organizational practice, an integrated plan for implementing these
recommendations, limitations, and future research directions. The chapter will conclude by
emphasizing how Inclusive Leadership, as described in Leadership: Theory and Practice
(Northouse, 2022) and recent articles like They Key to Inclusive Leadership (Bourke & Titus,
2020) can further enhance the successful adoption of flexible work policies.
Discussion of Findings
This section examines the key findings within the framework of Herzberg’s Two-Factor
Theory and Maslow’s Hierarchy of Needs, integrating additional insights from recent literature and
practical observations on employee motivation, productivity, and autonomy.
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Autonomy and Employee Productivity
A major finding of this study is the significant effect of autonomy on employee
productivity. Data showed that more than 70% of employees preferred to choose their own work
schedules and reported higher motivation and productivity as a result. This result aligns with the
work of Ryan and Deci (2000), who highlighted the critical role of autonomy in enhancing intrinsic
motivation. Moreover, similar findings were presented by Bloom et al. (2015), who showed that
providing choice and flexibility significantly increased productivity in remote work settings. This
supports the hypothesis that greater autonomy leads to better productivity outcomes.
Employees who could choose their work schedules reported higher levels of motivation,
engagement, and productivity. This finding is congruent with Herzberg’s Two-Factor Theory,
which posits that autonomy serves as a key motivator in the workplace, fostering a sense of
ownership and personal accountability that drives job satisfaction and intrinsic motivation
(Herzberg et al., 2017). Autonomy, as a motivational factor, addresses employees’ fundamental
need for control over their work environments, reinforcing their sense of purpose and engagement.
Data from the SWAA survey reinforces the critical role of autonomy. Specifically, 70% of
employees expressed a preference for selecting their own remote workdays. This overwhelming
preference for autonomy underscores that it is not merely a convenience but a psychological need
that enhances employees' productivity and satisfaction. Deci and Ryan’s Self-Determination
Theory (2000) supports this view, emphasizing that autonomy is a fundamental driver of intrinsic
motivation. Employees who lack autonomy may feel constrained or undervalued, which can reduce
engagement and diminish overall productivity.
This finding is consistent with Bloom et al. (2015), who reported a 13% productivity
increase among remote workers at a Chinese travel agency, Ctrip, due to greater scheduling
flexibility. The SWAA data similarly indicates that nearly half of respondents felt more efficient
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working from home, a sentiment also supported by recent data from Microsoft’s Work Trend Index
(Microsoft Work Trend Index Annual Report, 2022). Microsoft has observed that its remote
employees report both higher productivity and improved work-life balance, contributing to record
revenue levels in fiscal 2024 (Seattle Times, 2024). This alignment of autonomy with productivity
suggests that flexibility in work arrangements is not just a benefit but a strategic asset.
Misalignment Between Employer and Employee Preferences
The disparity between employer and employee preferences for remote work arrangements
was another key finding. Data showed that employers planned for fewer remote workdays
compared to what employees desired, which led to decreased motivation among employees. This
finding corresponds with previous literature, such as Bailey and Kurland (2002), which stressed the
importance of aligning organizational policies with employee needs to optimize satisfaction and
performance.
Another prominent finding from this study is the misalignment between employer and
employee preferences regarding remote work. SWAA data reveals a stark discrepancy: while
employers planned for 36% of remote workdays, employees preferred 49%. This gap highlights a
disconnect that can impact employee morale, motivation, and retention. Employers who mandate
in-office work without considering employee preferences risk disengagement, reduced
productivity, and, as seen with Amazon’s five-day return-to-office mandate, employee attrition
(WSJ, 2024).
The Wall Street Journal reported that Amazon’s strict in-office requirement, as advocated
by CEO Andy Jassy, sparked significant unrest among employees, many of whom voiced concerns
over work-life balance and the feasibility of full-time office returns. This policy illustrates the
implications of rigid mandates on employee motivation and productivity. Microsoft’s contrasting
approach—maintaining flexibility while monitoring productivity metrics—demonstrates that
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hybrid models can sustain organizational performance and engagement. The concept of flexibility
as an essential factor aligns with Bailey and Kurland (2002), who argue that organizations attuned
to employee preferences enjoy enhanced job satisfaction and productivity.
Maslow’s Hierarchy of Needs further illustrates this misalignment. Restricting remote work
options limits employees’ ability to achieve higher-order needs, such as self-esteem and selfactualization, by constraining their personal and professional development. Employees may
interpret rigid policies as a lack of organizational empathy, diminishing their sense of belonging
and reducing engagement (Linvill & Onosu, 2023). This insight is crucial for organizations aiming
to retain talent and sustain productivity: aligning work models with employee preferences is not
only a strategy for motivation but a fundamental psychological imperative.
Psychological Safety and Inclusive Leadership
Psychological safety emerged as a critical factor in productivity, particularly within remote
work settings. Employees who felt secure in their ability to choose their work arrangements and
who perceived a supportive organizational culture reported higher levels of productivity. This
finding aligns with Inclusive Leadership principles outlined by Northouse (2019), which emphasize
creating an environment where employees feel valued, heard, and supported. Bourke and Titus
(2020) further emphasize that inclusive leaders are uniquely positioned to cultivate psychological
safety, especially in work environments undergoing transitions.
The previously mentioned Amazon policy shift, and others like it, highlight a prevalent
concern among employees: the fear that rigid return-to-office mandates signal impending layoffs or
are a means of forced attrition in and of themselves (Rodman & Astmann, 2024). Such concerns
underscore the importance of psychological safety. When employees feel secure, they are more
likely to engage actively and productively (Ge, 2020). Microsoft’s strategy, as observed in the
Seattle Times (2024), leverages a more inclusive approach by accommodating individual work
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needs while maintaining organizational goals, a method that has contributed to its sustained
performance.
Additionally, psychological safety connects to Maslow’s Hierarchy of Needs, providing a
basis for understanding its importance in fostering employee engagement. Employees who feel
psychologically safe can satisfy needs related to belonging, esteem, and self-actualization, enabling
them to focus on their responsibilities without fear of repercussions. Inclusive Leadership practices,
therefore, support open communication and reinforce employees’ sense of value and contribution,
ultimately driving engagement and productivity (Northouse, 2022).
Recent research on empathetic communication, particularly in the context of Inclusive
Leadership, further supports these findings (Nakamura & Milner, 2023). Leaders who listen
empathetically to employees’ concerns and preferences help establish a foundation of trust,
reinforcing psychological safety and fostering organizational loyalty. By emphasizing open
communication, organizations can mitigate resistance to changes in work arrangements, enhancing
employee buy-in and engagement (Linvill & Onosu, 2023).
Recommendations for Practice
Introduction
The following recommendations address the core issues identified in this study: the need for
enhanced autonomy, psychological safety, and alignment between employer policies and employee
preferences. These recommendations aim to build a work environment that meets employee needs,
thereby enhancing motivation, productivity, and engagement.
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Recommendation 1: Enhance Employee Autonomy
Given that over 70% of employees in the SWAA data? prefer autonomy in choosing remote
workdays, organizations should implement policies that empower employees to select their
schedules within defined parameters. Deci and Ryan’s (2000) Self-Determination Theory
underscores the importance of autonomy in driving job satisfaction and motivation. Providing
employees with flexibility in their work arrangements demonstrates organizational trust and respect
for individual needs.
A practical approach would involve a “core-hours” policy, in which employees must be
available for collaborative work during set hours but retain flexibility in structuring the remainder
of their workday. Microsoft’s model, which maintains productivity expectations while allowing
flexibility, serves as a potential template for organizations aiming to balance structure with
autonomy (Microsoft Work Trend Index, 2024).
Recommendation 2: Foster Psychological Safety Through Inclusive Leadership
To enhance psychological safety, organizations should promote Inclusive Leadership
practices that emphasize open communication and active listening. Northouse (2019) and Bourke
and Titus (2020) emphasize that inclusive leaders create environments where employees feel
valued and empowered to share their perspectives. Regular check-ins, where managers discuss
employees’ work arrangement experiences and gather feedback, foster a supportive culture that
enhances productivity.
A robust psychological safety strategy should include anonymous feedback mechanisms,
where employees can voice concerns without fear of retaliation (Cappone, 2020). Additionally,
leadership training in empathetic communication can strengthen managers’ ability to address
employee concerns regarding work arrangements (Nakamura & Milner, 2023). By fostering a
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culture of inclusion and safety, organizations can create an environment that encourages
productivity and engagement (Even & Christiansen, 2023).
Recommendation 3: Align Organizational Policies with Employee Preferences
The study’s findings highlight the negative impact of misaligned employer and employee
preferences on motivation and productivity. Organizations should implement regular surveys to
capture employee perspectives on work arrangements and adjust policies accordingly. Data from
the Microsoft Work Trend Index (2022) suggest that organizations that align policies with
employee preferences see greater engagement and satisfaction.
Employers could conduct quarterly surveys to assess satisfaction with current work
arrangements, and the feedback gathered can guide policy adjustments. An agile approach to policy
alignment ensures that work arrangements reflect employees’ evolving needs, supporting sustained
productivity and morale (Brown, 2022).
Integrated Recommendations
The proposed recommendations of enhancing employee autonomy, fostering psychological
safety, and aligning organizational policies with employee preferences can be synthesized into a
comprehensive program for workforce management. This integrated approach addresses the core
findings from this study and aligns with principles from Herzberg’s Two-Factor Theory and
Maslow’s Hierarchy of Needs, ensuring that both motivational and hygiene factors are considered
to optimize employee satisfaction and productivity. This multi-faceted program also draws from
Self-Determination Theory, emphasizing that meeting employees’ needs for autonomy,
competence, and relatedness can lead to higher motivation and engagement (Ryan & Deci, 2000).
An effective workforce management program should include a phased implementation
strategy that gradually introduces these changes, allowing employees and leaders to adjust while
providing measurable feedback at each stage (Kotter, 2012). Gradual implementation reduces
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resistance to change, fosters adaptation, and allows for adjustments that account for both employee
needs and organizational goals. The phased approach is divided into three stages: fostering
inclusive leadership, establishing autonomy-focused policies, and creating a responsive policy
feedback loop.
Phase 1: Leadership Training on Inclusive Leadership Principles
The first phase of this integrated approach emphasizes training organizational leaders in
inclusive leadership principles to foster a culture of psychological safety. Psychological safety is
fundamental for employees to feel comfortable expressing concerns, sharing ideas, and taking risks
without fear of negative consequences (Edmondson, 1999). Drawing on Northouse (2019) and
Bourke and Titus (2020), leaders should be trained to prioritize open communication, active
listening, and an environment where employees feel supported and valued. This phase directly
addresses the need for psychological safety, which is crucial for productivity in remote and hybrid
work settings, as highlighted by this study’s findings.
Leadership training sessions should include modules on emotional intelligence, active
listening, and conflict resolution, skills essential for nurturing an inclusive and psychologically safe
workplace (Goleman, 1998). Additionally, empathetic leadership exercises can help leaders
understand and respond effectively to employee concerns related to work arrangements (Kahn,
1990). Training programs should also include self-assessment tools for leaders to gauge their
competencies in inclusive behaviors, allowing them to identify areas for improvement. This
leadership approach aligns with transformational leadership theory, which emphasizes motivating
and engaging employees through respect and inclusion (Bass & Riggio, 2005).
Phase 2: Introducing Employee Autonomy Initiatives
Once inclusive leadership practices are established, the second phase involves
implementing policies that promote employee autonomy. As the study’s findings indicate,
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employee autonomy is highly valued, with 70% of employees preferring the ability to choose their
workdays. Autonomy is a crucial driver of motivation, fostering intrinsic motivation and higher job
satisfaction (Ryan & Deci, 2000). This phase aligns with research findings that underscore the
importance of flexibility and self-determination in enhancing employee productivity (Gagné &
Deci, 2005). Employee autonomy initiatives may include flexible scheduling options, core-hours
policies, and opportunities for remote work.
Organizations might consider introducing a “flexibility framework,” where employees can
choose their remote and in-office days within defined limits, such as a minimum number of office
days per month or specific hours for in-person meetings (Microsoft Work Trend Index Annual
Report, 2022). Ryan and Deci’s (2000) Self-Determination This approach meets business needs
while allowing employees to balance professional responsibilities with personal priorities. By
promoting autonomy, organizations tap into employees’ intrinsic motivation, as supported by SelfDetermination Theory, which asserts that autonomy is a fundamental psychological need (Ryan &
Deci, 2000).
Moreover, autonomy can also support skill development and innovation, as employees who
have control over their tasks are more likely to experiment with new methods and processes
(Hackman & Oldham, 1976). This phase may also involve creating clear guidelines and structures
to prevent misunderstandings or abuses of flexibility, ensuring that autonomy supports, rather than
hinders, organizational objectives.
Phase 3: Aligning Policies with Regular Employee Feedback
The third phase focuses on maintaining alignment between organizational policies and
employee preferences. Establishing a regular feedback loop allows organizations to monitor
employee satisfaction with current policies and make proactive adjustments based on evolving
83
needs. Studies show that ongoing feedback mechanisms improve employee engagement and foster
a culture of continuous improvement (Pfeffer & Sutton, 2006).
The feedback loop could involve quarterly surveys, focus groups, and open forums,
providing a structured way to gather insights into employee satisfaction with work arrangements
(Gallup, 2021). Feedback mechanisms contribute to psychological safety by demonstrating that
employees’ voices are valued, reinforcing a sense of belonging and respect. Moreover,
responsiveness to feedback aligns with agile organizational practices, allowing policies to evolve as
the workforce and work environment change (Rigby et al., 2016). A cross-functional team within
HR or workforce planning can be tasked with analyzing this feedback and making
recommendations, ensuring that the workforce management program remains relevant and
effective.
Regular assessment and adjustments based on feedback also align with Kirkpatrick’s New
World Model, which emphasizes evaluating organizational change initiatives across multiple
levels: reaction, learning, behavior, and results (Kirkpatrick & Kirkpatrick, 2016). By applying this
model, organizations can track the effectiveness of each phase and identify areas that need
refinement.
Timeline for Implementation
A recommended timeline for this integrated program is 12 to 18 months, allowing ample
time for each phase to be implemented thoroughly. Periodic evaluations can assess the
effectiveness of each phase and make necessary adjustments. This evaluation model considers
multiple levels of impact, reaction, learning, behavior, and results providing a holistic view of the
program’s success.
Phase 1 - Months 1–6: Leadership training on inclusive leadership principles.
Phase 2 - Months 6–12: Introduction of flexible scheduling and autonomy initiatives.
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Phase 3 - Months 12–18: Establishment of a regular employee feedback system and
alignment of policies.
Following this phased timeline, organizations can ensure a smooth transition to a more
employee-centric work model that enhances motivation, productivity, and satisfaction. By
integrating inclusive leadership, autonomy, and continuous feedback, organizations create an
adaptive, resilient culture that aligns with the values and needs of a modern workforce.
Limitations and Delimitations
This study focused on U.S.-based knowledge workers, limiting the generalizability of
findings to other demographics or industries. Additionally, the reliance on self-reported data may
introduce biases, like social desirability bias, affecting the accuracy of reported motivation,
performance, and productivity. The truthfulness of participants should also be considered as the
survey data relied upon the accuracy of the information provided by participants. Further, utilizing
an existing survey study may have limited the participation of individuals from certain groups who
were not signed up to receive surveys from one of the survey conducting entities. Individuals may
have not participated and therefore may not have had their views represented in the study for fear
of having their answers discovered by their employers. These factors should be considered when
interpreting the study’s implications.
The study’s delimitations included an intentional focus on knowledge workers and a
geographical scope limited to U.S. employees. This choice was made to explore the specific
preferences and challenges faced by this group in remote and hybrid work environments. Also, the
fact that the existing SWAA study was used as the basis for this study places borders on the
questions that could be asked and it is possible that it may not have asked enough questions to
establish the motivational impacts of changing work location policies. This could have led to
findings that are inconclusive or not fully aligned with the broader labor force.
85
Recommendations for Future Research
The rapidly evolving dynamics of work arrangements underscore the need for continued
research to deepen our understanding of remote, hybrid, and in-office work models. This study
highlighted critical areas such as autonomy, psychological safety, and the misalignment between
employee preferences and organizational policies, all of which significantly influence motivation,
performance, and productivity. However, as workplaces continue to transform, new questions
emerge that are vital for future exploration. To build on the insights of this study, future research
should examine these complex relationships across different contexts, sectors, and employee
demographics. Below are nine targeted areas of research that can further inform effective work
arrangements and help organizations meet both employee and business needs in a dynamic
environment.
1. Impact on Early-Career vs. Experienced Professionals
• Rationale: The transition from remote to hybrid or in-person work may affect employees at
different career stages uniquely. Early-career employees often benefit from in-person
mentorship, networking, and experiential learning, while experienced professionals may
prefer remote work for its flexibility.
• Focus: A comparative study could examine how autonomy in work arrangements
influences job satisfaction, skill development, and career progression differently for earlycareer and experienced professionals. This research could also explore if remote work
contributes to skill gaps or impedes career advancement for newer employees.
2. Effects of Hybrid Work on Team Dynamics and Collaboration Quality
• Rationale: While remote work offers flexibility, hybrid models present unique challenges
for collaboration, particularly in cross-functional or project-based teams.
86
• Focus: Research could analyze how hybrid arrangements influence team cohesion,
collaboration efficiency, and knowledge sharing. Specific variables could include
communication frequency, project completion rates, and team members’ perceptions of
collaboration effectiveness. This study could help identify the best practices for managing
hybrid teams.
3. Diversity, Equity, and Inclusion (DE&I) in Remote and Hybrid Work Settings
• Rationale: Remote and hybrid work may impact DEI efforts differently. For instance,
remote work can support individuals with disabilities or caregivers, but it may also create
disparities in visibility and advancement opportunities.
• Focus: Future studies could explore how remote and hybrid work models impact DEI
outcomes, specifically examining promotion rates, inclusion in team decision-making, and
perceptions of fairness among diverse demographic groups. This research could provide
insights into creating inclusive work environments that support diverse talent.
4. Effects of Remote and Hybrid Work on Mental Health and Work-Life Boundaries
• Rationale: Remote work can blur the lines between personal and professional life,
potentially leading to burnout and stress. Conversely, hybrid work may help establish
boundaries but can introduce stress from commute times and schedule changes.
• Focus: A study could focus on mental health outcomes associated with different work
arrangements, analyzing factors like stress levels, work-life balance, and job satisfaction. It
could also explore strategies to mitigate digital fatigue and improve work-life integration.
5. Impact of Return-to-Office Mandates on Talent Retention in Competitive Sectors
• Rationale: Industries like tech and finance often have highly mobile, in-demand talent who
may be resistant to full return-to-office mandates.
87
• Focus: This research could examine retention rates, turnover intentions, and productivity in
organizations that implement strict in-office requirements, comparing outcomes with those
maintaining flexible or hybrid policies. Specific industries or regions with competitive labor
markets, like tech hubs, could be analyzed to assess how mandates influence recruitment
and retention.
6. Differences in Remote Work Preferences Across Global Cultural Contexts
• Rationale: Cultural attitudes toward remote work vary widely, with some regions more
open to flexible arrangements than others. Understanding these differences can help global
organizations tailor policies to local preferences.
• Focus: Comparative studies could examine how cultural factors influence employee
satisfaction and productivity in remote settings. For example, a study could investigate how
employees in collectivist cultures respond to hybrid models compared to those in
individualist cultures, with a focus on team dynamics, autonomy, and communication.
7. Exploring Productivity Metrics in Fully Remote, Hybrid, and In-Person Models
• Rationale: Measuring productivity across work models is challenging, as traditional
metrics may not capture remote work nuances.
• Focus: Research could focus on developing and validating new productivity metrics
tailored to remote and hybrid environments. Variables like task completion, focus hours,
and creative output could provide more accurate insights into employee productivity in
different work settings.
8. Examination of Leadership Styles in Remote and Hybrid Work Environments
• Rationale: Different work arrangements may require distinct leadership approaches to
maintain engagement and productivity.
88
• Focus: This study could explore which leadership styles (e.g., transformational, inclusive,
transactional) are most effective in remote and hybrid settings. It could also assess the
impact of these styles on team morale, individual performance, and overall organizational
outcomes.
9. Effects of Remote Work on Employee Engagement and Organizational Loyalty
• Rationale: Engagement and loyalty may be influenced by physical proximity to the
workplace and frequency of in-person interaction.
• Focus: A study could examine how different work models impact employee loyalty,
commitment to organizational goals, and long-term engagement. For instance, researchers
could assess whether remote employees exhibit different levels of loyalty compared to
hybrid or in-person employees.
Chapter 5 Conclusion
The findings of this study make an unequivocal case for the critical importance of adaptive
work arrangements in today’s rapidly evolving workplace landscape. Organizations are at a pivotal
crossroads. Those that respond effectively to the shifting expectations of their workforce will likely
become leaders in productivity, innovation, and employee engagement. In contrast, companies that
cling to outdated, rigid models risk alienating talent, eroding morale, and facing higher turnover.
This research provides a clear message: employees highly value autonomy, flexibility, and
psychological safety, and when these needs are met, the result is a more motivated, productive, and
resilient workforce. This study showed that employees increasingly desire to gravitate toward
employers who respect and support their work-life balance, autonomy, and sense of belonging.
Organizations that ignore these priorities do so at their peril.
Further, this study underscores that aligning organizational policies with employee
preferences is no longer merely a “nice-to-have” but a strategic necessity. The data from the
89
Survey of Working Arrangements and Attitudes (SWAA), supported by extensive literature, shows
that autonomy in work arrangements is more than a logistical preference; it is a psychological need
that, when satisfied, leads to higher intrinsic motivation, lower stress levels, and stronger
organizational loyalty. Failing to meet these needs not only inconveniences employees but poses
tangible risks to engagement, productivity, and overall business performance. Organizations that
fail to adapt face the threat of increased burnout, diminished innovation, and a weakened reputation
in a competitive talent marketplace where flexibility has become a baseline expectation.
Adding a moral dimension to these findings, the Kantian perspective emphasizes that
remote and flexible work arrangements are not merely strategic or productivity-related decisions
but ethical imperatives (Fausto, 2022). According to Kant’s principle of treating individuals as ends
in themselves, organizations that restrict remote work without necessity disregard employees'
autonomy and personal welfare. This view holds that when companies can offer remote work
without incurring losses, failing to do so is morally wrong. In line with Fausto Corvino’s argument,
the freedom to choose work arrangements aligns with Kantian ethics by respecting employees’
dignity and individual goals. From this perspective, flexible work policies are not only
advantageous but morally necessary, especially when such policies enable employees to better
manage personal responsibilities and contribute meaningfully to the organization.
The stakes for getting this right are high, as exemplified by companies like Amazon and
Microsoft, whose contrasting approaches to remote work are being closely monitored by industry
peers (Talton, 2024). Amazon's insistence on in-office mandates contrasts with Microsoft’s flexible
stance, which has coincided with record performance and high employee engagement. These
examples suggest that adaptability and trust in employee-driven work arrangements are not just
advantageous but foundational to sustained success in today’s workplace. Organizations that
balance business needs with employee preferences are more likely to retain top talent, foster a
90
culture of inclusivity and psychological safety, and enable high performance. Conversely,
companies imposing one-size-fits-all policies risk losing high performers and critical institutional
knowledge to more progressive competitors. Even modest restrictions have already driven many
talented employees to seek roles better aligned with their professional and personal needs.
This study therefore advocates for a holistic, data-driven approach to designing work
models that prioritize flexibility, employee well-being, and long-term organizational health. By
embracing inclusive leadership practices, enhancing employee autonomy, and continually aligning
policies with employee feedback, companies can create sustainable work environments that foster
motivation, performance, and productivity. These are not simply operational adjustments; they
represent foundational shifts toward more ethical, employee-centered workplaces that in turn
support both organizational goals and personal well-being.
Ultimately, the evidence presented here signals a pivotal transformation in the modern
workplace: companies that take bold, adaptive steps to support their workforce will not only thrive
in the present but will also build resilient, future-ready organizations capable of navigating an
increasingly complex and competitive global economy. In an era where the balance of power is
shifting toward employees’ needs and values, organizations that fail to embrace this shift may find
themselves struggling to attract and retain talent, while those that embrace adaptive, ethically
grounded policies will cultivate a reputation as forward-thinking, compassionate employers. This
approach ensures a competitive edge and strengthens the moral foundation of the workplace,
fostering a culture where employees feel valued, engaged, and empowered to contribute their best
selves to the organization’s success.
91
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Appendix A: Variable dictionary for “WFH Code and Data: May 2020 to June 2024”
Version of the Survey of Working Arrangements and Attitudes (SWAA) dataset
Downloadable after creating an account on www.wfhresearch.com/data
by Jose Maria Barrero, Nicholas Bloom, and Steven J. Davis
July 2024
1. Variable Labels. See below for a brief explanation of each variable in the main data files:
WFHdata_[MonthYY].csv and WFHdata _[MonthYY]_noincreq.csv. Our replication code in the
files WFH_updatedresults_Master_[MonthYY].do, WFH_WPresults_Master_[MonthYY].do and
WFH_noincreq_Master_[MonthYY].do label each of the variables using the same descriptions that
appear below.
§ cratio100 "Weights to match CPS on {age x sex x education x earnings} , modified so that the
relative weight of a given observation is 5 "
Note: Use these weights to produce updated statisticsthat use data from allsurvey waves of
the SWAA (including April 2021 and later). The included code file
“WFH_updatedresults_Master_[MonthYY].do” uses this variable to produce updated
results that are analogous to those in the 28 April 2021 working paper version of “Why
Working From Home Will Stick” by Barrero Bloom and Davis the paper results but use
additional months of data after April 2021. Starting with the 5 October 2021 data release
these are winsorized weights that avoid upweighting an individual observation by a large
amount.
§ icratio100 "Weights to match CPS on {age x sex x education x earnings} x earnings, where the
weights are modified before multiplying with earnings so that the relative weight of a given
observation is 5 "
Note: This is just the earnings-weighted version of “cratio100.”
§ cratio100_2021m3 "Weights to match CPS on {age x sex x education x earnings} using data
only up to March 2021 (all subsequent waves have a weight of zero)"
Note: Use these weights to reproduce the results from the 28 April 2021 working paper
version of “Why Working From Home Will Stick” by Barrero Bloom and Davis. The
included code file “WFH_WPresults_Master_May21.do” uses this variable to reproduce
the results from the paper.
§ icratio100_2021m3 "Weights to match CPS on {age x sex x education x earnings} x earnings,
using data only up to March 2021 (all subsequent waves have a weight of zero)"
Note: This is just the earnings-weighted version of “cratio100_2021m3.”
§ cratio100_nw "Weights to match CPS on {age x sex x education x earnings}"
116
Note: These are the “raw” weights to match the CPS before adjusting to avoid giving any
observation a relative weight of more than 1/N, where N = total number of raw observations.
§ icratio100_nw "Weights to match CPS on {age x sex x education x earnings} x
earnings" Note: This is just the earnings-weighted version of “cratio100_nw.”
§ date "YYYYmM - survey wave"
§ income "2019 Earnings, $ Thousand"
§ age_quant "Age in years"
§ agebin "Age - categorical bins"
§ educ_years "Years of education"
§ education "Education - categorical"
§ education_s "Education (simplified) - categorical"
§ wfhcovid "100 x 1(WFH this week, i.e. during COVID)"
§ wfhcovid_ever "100 x 1(Ever WFH during COVID)"
§ wfhcovid_frac "Share of paid working days WFH this week (%), i.e. during COVID"
§ numwfh_days_postCOVID_s_u "Desired share of paid working days WFH after COVID (%)"
§ numwfh_days_postCOVID_boss_s_u "Employer planned share of paid working days
WFH after COVID (%)"
§ commutetime_quant "Commute time (mins)"
§ wfh_feel_quant "How much of a raise/pay cut would you value WFH 2 to 3 days per week?
(%)"
§ wfh_expect_quant "Relative to expectations before COVID, how productive are you WFH
during COVID? (%)"
§ wfh_expect "Relative to expectations before COVID, how productive are you WFH during
COVID? - categorical"
§ wfh_able_quant "How efficient are you at working from home? (%)"
§ wfh_eff_COVID_quant "How efficient are you WFH during COVID, relative to on business
premises before COVID (%)"
§ wfh_invest_quant "Money you & your employer invested in equipment/infrastructure to
help you WFH effectively. This variable is winsorized during data preparation."
§ wfh_hoursinvest "Hours invested in learning how to WFH effectively"
§ work_spend_total "Total weekly spending on meals, entertainment, and shopping near work
in 2019. This variable is winsorized during data preparation."
§ female "100 x 1(Female)"
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§ redstate "100 x 1(Red State)"
§ workstatus_current "Current working status - categorical"
§ income_cat "2019 Earnings, $ Thousand - categorical (detailed)"
§ incomebin "2019 Earnings, $ Thousand - categorical (coarse), string form"
§ iincomebin "2019 Earnings, $ Thousand - categorical (coarse)"
§ ratio "Raw data weights, equal for all observations"
§ work_industry "Industry of current or most recent job"
§ censusdivision "Census Division of residence"
§ region "State of residence"
§ gender "Sex (binary)"
§ gender_d "Sex, including ‘Other or prefer not to say'"
§ wfh_days_postCOVID_s "Desired number of paid WFH days after COVID - categorical"
§ wfh_days_postCOVID_boss "Employer's planned number of paid WFH days after COVID -
categorical"
§ wfh_days_postCOVID_ss "Desired number of paid WFH days after COVID –
categorical, bundling together rarely and never"
o Note: The graphs in the paper use wfh_days_postCOVID_ss, our preferred variable,
instead of wfh_days_postCOVID_s
§ wfh_days_postCOVID_boss_ss "Employer's planned number of paid WFH days after
COVID
– categorical, bundling together rarely and never"
o Note: The graphs in the paper use wfh_days_postCOVID_boss_ss, our preferred
variable, instead of wfh_days_postCOVID_boss
§ wfh_able "Are you able to do your job from home? - categorical bins, only for May 2020, July
2020 survey waves"
§ wfh_able_qual "Are you able to do your job from home (at least partially)? - categorical
Yes/No, only for October 2020 and subsequent survey waves"
§ wfh_Dperception "How have perceptions of WFH changed among people you know since
the start of the pandemic? - categorical"
§ wfh_feel "How much of a raise/pay cut would you value WFH 2 to 3 days per week? -
categorical"
§ wfh_feel_detailed "How much of a raise/pay cut would you value WFH 2 to 3 days per week?
- categorical, this version is most disaggregated and includes data from Sept. 2020 to Feb. 2021"
§ wfh_feel_legacy "How much of a raise/pay cut would you value WFH 2 to 3 days per week?
- categorical, based on legacy question"
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§ wfh_feel_quant_actual "Raise/pay cut value of WFH 2 or 3 days per week x Employer
planned post-COVID WFH"
§ logpop_den_job_preCOVID "Log(Population density of the ZIP code of pre-COVID Job)"
§ logpop_den_Feb20 "Log(Population density of the ZIP code of February 2020 residence)"
§ logpop_den_current "Log(Population density of the ZIP code of current residence)"
§ logpop_den_job_current "Log(Population density of the ZIP code of current job business
premises)"
§ logpop_den_live_future "Log(Population density of the ZIP code of future (post-move)
residence"
§ wfh_eff_COVID "How efficient are you WFH during COVID, relative to on business
premises before COVID - categorical"
§ wfh_eff_COVID_legacy "How efficient are you WFH during COVID, relative to on
business premises before COVID - categorical, based on legacy question"
§ wfh_ownroom_notbed "100 x 1(Has their own room (not bedroom) to work in while WFH
during COVID)"
§ goodservices "Industry of current/most recent job is GOODS or SERVICES? - categorical"
§ redblue_cook "State of residence Red (Republican) or Blue (Democrat)? - categorical"
§ Dem_share_frac "Joe Biden vote share in 2020 GE - measured as of 12 Nov 2020 (%)"
§ haschildren "100 x 1(Living with children under 18)"
§ logincome "log(2019 labor earnings $'000s)"
§ internet_quality_quant "Internet quality - Fraction of time that internet works"
§ habits_postCOVID "If a COVID vaccine is discovered and made widely available, which of
the following would best fit your views on social distancing?"
§ concern_vaccine "100 x 1(Would not return to pre-COVID activities completely out of
concerns with vaccine safety/effectiveness/take-up) - select all that apply question"
§ concern_socdist "100 x 1(Would not return to pre-COVID activities completely, gotten used
to social distancing) - select all that apply question"
§ concern_otherdisease "100 x 1(Would not return to pre-COVID activities completely out of
concerns about other diseases) - select all that apply question"
§ concern_none "100 x (No concerns preventing the return to pre-COVID activities)"
§ child1_age "Age of child 1 - missing if fewer than 1 children. Only asked from 9/20 onwards"
§ child2_age "Age of child 2 - missing if fewer than 2 children. Only asked from 9/20 onwards"
§ child3_age "Age of child 3 - missing if fewer than 3 children. Only asked from 9/20 onwards"
§ child4_age "Age of child 4 - missing if fewer than 4 children. Only asked from 9/20 onwards"
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§ child5_age "Age of child 5 - missing if fewer than 5 children. Only asked from 9/20 onwards"
§ child6_age "Age of child 6 - missing if fewer than 6 children. Only asked from 9/20 onwards"
§ child7_age "Age of child 7 - missing if fewer than 7 children. Only asked from 9/20 onwards"
§ child8_age "Age of child 8 - missing if fewer than 8 children. Only asked from 9/20 onwards"
§ live_adults "Do you currently live with a partner or other adults"
§ live_children "Do you currently live with children under 18? -- categorical by youngest's age"
§ hours_cc_you "Currently, how many hours of childcare each week are provided by you?"
§ hours_cc_partner "Currently, how many hours of childcare each week are provided by your
partner?"
§ hours_cc_other "Currently, how many hours of childcare each week are provided by others,
e.g. grandparents, babysitters?"
§ hours_cc_you_precovid "Before COVID, how many hours of childcare each week were
provided by you?"
§ hours_cc_partner_precovid "Before COVID, how many hours of childcare each week were
provided by your partner?"
§ hours_cc_other_precovid "Before COVID, how many hours of childcare each week were
provided by others, e.g. grandparents, babysitters?"
§ wfh_invest_burs "Percent of money invested in equipment or infrastructure enabling WFH
that was paid for or reimbursed by employer. Missing if no WFH or zero investment"
§ occupation "Occupation (self-reported)"
§ occupation_other "User description when selecting 'Other' occupation"
§ race_ethnicity "Race/ethnicity -- categorical"
§ race_ethnicity_s "Race/ethnicity -- categorical combines several small categories into 'Other'"
§ hourly_wage "Hourly wage = (2019 income)/(pre-COVID weekly work hours * 50 weeks per
year)"
§ wfh_extraeff_comm_qual "Is time saved by not commuting part of your extra efficiency when
working from home? - categorical"
§ wfh_extraeff_comm_quant "How much of your extra efficiency when working from home is
due to the time you save by not commuting? -- This equals zero if commuting time savings
are not included, or if relative efficiency of WFH is negative "
§ workhours_preCOVID "Hours worked per week pre-COVID"
§ workhours_duringCOVID "Hours worked per week at the time of the survey (during COVID)
-- if currently working, otherwise missing"
120
§ extratime_1stjob "Percent of commute time savings spent working on primary or current
job"
§ extratime_2ndjob "Percent of commute time savings spent on a second or new secondary
job"
§ extratime_childcare "Percent of commute time savings spent on childcare"
§ extratime_chores "Percent of commute time savings spent on home improvement, chores, or
shopping"
§ extratime_indoorleisure "Percent of commute time savings spent on leisure indoors (e.g.
reading, watching TV and movies)"
§ extratime_outdoorexercise "Percent of commute time savings spent on exercise or outdoor
leisure"
§ wfh_feel_new_qual "Assuming it doesn’t matter for your pay, which working arrangements
would you prefer after COVID is under control? - categorical"
§ wfh_feel_pr_bp_quant0 "How much extra pay would it take for you to prefer working 5 days a
week on your employer’s premises after COVID is under control? - For those who prefer 2
days WFH and 3 days on premises. Equals zero if they already prefer 5 days per week on
premises"
§ wfh_feel_pr_hyb_quant0 "How much extra pay would it take for you to prefer working 3
days a week on your employer’s premises and 2 days at home after COVID is under control?
- For those who prefer 5 days on premises. Equals zero if they already prefer 2 days WFH and 3 on
premises."
§ vaccine_req_boss "Does or will your employer require you to be vaccinated to work on
business premises? - categorical"
§ vaccine_req_should_gen "Should employers require vaccination before letting workers
return to the employer’s worksite? - categorical"
§ vaccine_req_should_myboss "Should your employer require vaccination before letting you
and your co-workers return to the worksite? - categorical"
§ prom_eff_1day_qual "If you were to work from home one more day per week than your coworkers, how might this affect your chance of a promotion in the next 3 years? - categorical"
§ prom_eff_5day_qual "If you were to work from home 5+ days a week and your co-workers
work on the business premises 5+ days a week, how might this affect your chance of a
promotion in the next 3 years? - categorical"
§ prom_eff_1day_quant "How much of an increase in your chance of a promotion would
working from home one more day per week than your co-workers cause?"
§ prom_eff_5day_quant "How much of an increase in your chance of a promotion would
working from home 5+ days a week while your co-workers work on the business premises 5+
days a week cause?"
121
§ wfh_able_qual_May21 "Do you need to be physically present on business premises to
perform your job (current or most recent)? - categorical"
§ offer_employed_wfh1days "Would you be more or less likely to take the new job if it let
you work from home 1 day a week? - categorical, employed respondents"
§ offer_employed_wfh23days "Would you be more or less likely to take the new job if it let
you work from home 2 to 3 day a week? - categorical, employed respondents"
§ offer_employed_wfh45days "Would you be more or less likely to take the new job if it let
you work from home 4 to 5 day a week? - categorical, employed respondents"
§ offer_unemployed_wfh1days "Would you be more or less likely to take the job if it let you
work from home 1 day a week? - categorical, unemployed respondents"
§ offer_unemployed_wfh23days "Would you be more or less likely to take the job if it let you
work from home 2 to 3 day a week? - categorical, unemployed respondents"
§ offer_unemployed_wfh45days "Would you be more or less likely to take the job if it let you
work from home 4 to 5 day a week? - categorical, unemployed respondents"
§ wbp_react_qual "How would you respond if your employer announced that all employees
must return to worksite 5+ days a week starting [month-after-next]?"
Note: The question text typically specifies the 1st day of the month-after-next as the
required return date. For example, the June 2021 wave specified “August 1, 2021.”
However, the August 2021 wave mistakenly specified “September 1, 2021”, i.e. next month
rather than month-after-next.
§ videocall_ small _qual "How does the efficiency of video calls for one-on-one and small
group meetings (up to 4 people) compare to the efficiency of in-person meetings? -
categorical"
§ videocall_ small _quant "How does the efficiency of video calls for one-on-one and small
group meetings (up to 4 people) compare to the efficiency of in-person meetings? -
quantitative"
§ videocall_med_qual "How does the efficiency of video calls for medium sized group meetings
(up to 5 to 10 people) compare to the efficiency of in-person meetings? - categorical"
§ videocall_med_quant "How does the efficiency of video calls for medium sized group
meetings (up to 5 to 10 people) compare to the efficiency of in-person meetings? - quantitative"
§ videocall_large_qual "How does the efficiency of video calls for large sized group meetings
(up to 10 or more people) compare to the efficiency of in-person meetings? - categorical"
§ videocall_large_quant "How does the efficiency of video calls for large sized group meetings
(up to 10 or more people) compare to the efficiency of in-person meetings? - quantitative"
§ wfh_dow_preferM "Would choose Monday as one of 2 WFH days"
§ wfh_dow_preferT "Would choose Tuesday as one of 2 WFH days"
122
§ wfh_dow_preferW "Would choose Wednesday as one of 2 WFH days"
§ wfh_dow_preferT "Would choose Thursday as one of 2 WFH days"
§ wfh_dow_preferF "Would choose Friday as one of 2 WFH days"
§ wfh_dow_preferNA "No preference for 2 WFH days"
§ wfh_able_intcount "How much would your efficiency working from home increase if you had
perfect high-speed internet?"
§ employer_arr_qual "What plans does your employer have for working arrangements of fulltime employees after COVID, in 2022 or later?"
§ who_decides_wfhdays "Who decides which days and how many days employees work
remotely?"
§ wfh_days_postCOVID_boss_ty "After COVID, in 2022 and later, how many days a week will
that typical employee work on business premises? - categorical"
§ wfh_days_postCOVID_boss_ty_ss "After COVID, in 2022 and later, how many days a week
will that typical employee work on business premises? - caterogical bundling together rarely
and never"
§ choice_prefer "Which of the following would you prefer? a) Being able to choose which days
you work from home (if any) b) Your employer sets a policy..."
§ handshake_postCOVID "When you return to work in person, and you are introduced to
somebody will you...?"
§ handshake_preCOVID "Before COVID (in 2019), when you were introduced to somebody at
work what did you do?"
§ downloadspeed "Internet download speed from speed test. Winsorized at the 1st and 90th
percentiles within each category of the `internet_quality' variable"
§ uploadspeed "Internet download speed from speed test. Winsorized at the 1st and 90th
percentiles within each category from `internet_quality' variable"
§ self_employed "Which of the following best describes your current employment situation? -
categorical"
§ ownbusiness_sizecat "Excluding yourself but including employees and independent
contractors, how many staff members are part of your business?"
§ employer_sizecat "Counting all locations where your primary employer operates, what is the
total number of persons who work for your employer?"
Note: This variable is only available for respondents in the August 2021 and later waves
who reported being employed and do not own their own business or earn most of their
income as independent contractors.
§ workstatus_current_new "Currently (this week) what is your work status? - categorical.
Version of the question asked since November 2020"
123
Note: This variable is only available for respondents in the August 2021 and later waves
who reported owning their own small business.
§ numwfh_days_postCOVID_boss_pre "Employer planned share of paid working days WFH
after COVID, before the most recent announcement made in the past 6 months (%)"
§ wfh_postCOVID_boss_ann "In the last six months, has your employer announced new plans
about working from home after the pandemic ends, in 2022 or later? - categorical"
§ wfh_eff_COVID_qual "How does your efficiency working from home during the COVID-19
pandemic compare to your efficiency working on business premises before the pandemic? -
categorical"
§ wfh_eff_COVID_neg_d "How much less efficient are you while working from home than at
the office - if less efficient"
Note: This variable gets deleted when processing the raw data as it is only used to clean
the wfh_eff_COVID_quant variable for the updated results code.
§ wfh_eff_COVID_pos_d "How much more efficient are you while working from home than
at the office - if more efficient"
§ wfh_eff_noCOVID_qual "How does your efficiency working from home compare to
your efficiency working on business premises? - categorical"
§ wfh_eff_noCOVID_neg_d "How much less efficient are you while working from home than
at the office - if less efficient & got the question that doesn't mention COVID"
§ wfh_eff_noCOVID_pos_d "How much more efficient are you while working from home
than at the office - if more efficient & got the question that doesn't mention COVID'"
§ wfh_eff_COVID_question "Equals 1 if the respondent received the efficiency question that
mentions COVID, 0 if they got the question that doesn't mention COVID"
§ lesseff_reasons_noroom "Why are you less efficient when working from home? - I don't have
a quiet room to work in"
§ lesseff_reasons_kidsinterr "Why are you less efficient when working from home? - I am
frequently interrupted by my kids"
§ lesseff_reasons_adultsinterr "Why are you less efficient when working from home? - I am
frequently interrupted by my partner or other adults I live with"
§ lesseff_reasons_internet "Why are you less efficient when working from home? - I don't
have an adequate internet connection"
§ lesseff_reasons_equipment "Why are you less efficient when working from home? - I need
specialized equipment to do my job"
§ lesseff_reasons_homecomputer "Why are you less efficient when working from home? - My
home computer is not good enough"
§ lesseff_reasons_tasks "Why are you less efficient when working from home? - My job
involves many tasks that cannot be done remotely"
124
§ lesseff_reasons_other "Why are you less efficient when working from home? - Other"
§ moreeff_reasons_quieter "Apart from saving time by not commuting, why are you more
efficient when working from home? - My home is quieter and has fewer interruptions "
§ moreeff_reasons_shortmeet "Apart from saving time by not commuting, why are you more
efficient when working from home? - I have fewer or shorter meetings when working from
home"
§ moreeff_reasons_choreseff "Apart from saving time by not commuting, why are you more
efficient when working from home? - Mealtimes, chores, and/or childcare are more efficient
when I work from home"
§ moreeff_reasons_internet "Apart from saving time by not commuting, why are you more
efficient when working from home? - My internet connection is better at home"
§ moreeff_reasons_equip "Apart from saving time by not commuting, why are you more
efficient when working from home? - I have better equipment at home than at work"
§ moreeff_reasons_lessstress "Apart from saving time by not commuting, why are you more
efficient when working from home? - I feel less stressed at home"
§ moreeff_reasons_other "Apart from saving time by not commuting, why are you more
efficient when working from home? - Other"
§ commutetime_towork "How long do you usually spend commuting to work (in minutes)?"
§ commutetime_fromwork "How long do you usually spend commuting from work (in
minutes)?"
§ coworker_interactions "How much do you enjoy your personal interactions with coworkers
at your employer's worksite?"
§ client_interactions "How much do you enjoy your personal interactions with customers,
clients, or patients at your employer's worksite?"
§ disability_qual "Do you have a health problem or a disability which prevents work or which
limits the kind or amount of work you do?"
§ workteam_tasks_percent "To perform your job, what percentage of your tasks require
collaboration as part of a team?"
§ workteam_npeople "How many people belong to your main work team? (Top-coded at 50)"
§ videocalls_preCOVID_percent "Before the pandemic, what percentage of your normal
working day did you spend in video calls?"
§ videocalls_current_percent "Currently, what percentage of your normal working day do you
spend in video calls?"
§ workteam_current_nmeetings "Currently, how many times does your main work team meet in
a typical week? Include in-person, telephonic, and video meetings. (Top-coded at 30)"
125
§ workteam_preCOVID_nmeetings "Before the pandemic, how many times did your main work
team meet in a typical week? Include in-person, telephonic, and video meetings. (Top- coded
at 30)"
§ boss_wfh_samedays "Will your manager work from home on the same days as you after the
pandemic is over?"
§ boss_wfh_unravel "If your manager starts coming into your employer's place of business on
some of your work-from-home days, what will you do?"
§ coworkers_wfh_samedays "Will most of your coworkers work from home on the same days
as you after the pandemic is over?"
§ coworkers_wfh_unravel "If your coworkers start coming into your employer's place of
business on some of your work-from-home days, what will you do?"
§ commutemode "Before COVID how did you typically commute to work? - categorical"
§ commutemode_s "Before COVID how did you typically commute to work? - categorical and
simplified"
§ wbp_return_anxious "On a scale of 0 to 10, how anxious are you about returning to work on
business premises?"
§ quit_qual "Have you quit or voluntarily left a job in the past 6 months? - categorical"
§ quit_date "Month (within the past 6) when you most recently quit a job - date format"
§ wfh_less_stress "How much do you agree: While working from home I am less stressed
because I don't feel like I am constantly under supervision."
§ groomtime_commute "How much time do you spend on grooming and getting ready for
work when you commute to your employer's or client's worksite?"
§ groomtime_wfh "How much time do you spend on grooming and getting ready for work
when you work from home?"
§ drivealone_preCOVID_pct "Driving alone: percent of commuting trips in 2019"
§ carpool_preCOVID_pct "Carpool: percent of commuting trips in 2019"
§ publictr_preCOVID_pct "Public transit: percent of commuting trips in 2019"
§ bicycle_preCOVID_pct "Bicycle: percent of commuting trips in 2019"
§ walk_preCOVID_pct "Walking: percent of commuting trips in 2019"
§ taxi_preCOVID_pct "Taxi/ride hailing: percent of commuting trips in 2019"
§ nocommute_preCOVID_pct "Did not commute pre-COVID (0 o 100)"
§ drivealone_current_pct "Driving alone: percent of commuting trips currently"
§ carpool_current_pct "Carpool: percent of commuting trips currently"
§ publictr_current_pct "Public transit: percent of commuting trips currently"
126
§ bicycle_current_pct "Bicycle: percent of commuting trips currently"
§ walk_current_pct "Walking: percent of commuting trips currently"
§ taxi_current_pct "Taxi/ride hailing: percent of commuting trips currently"
§ nocommute_current_pct "Do not commute currently (0 o 100)"
§ leavetime_preCOVID "In 2019 (before COVID), when you traveled to your employer's
worksite, approximately what time did you leave for work (e.g. 8:30am)? - categorical"
§ leavetime_current "Currently, when you traveled to your employer's worksite,
approximately what time did you leave for work (e.g. 8:30am)? - categorical"
§ leavetime_preCOVID_quant "In 2019 (before COVID), when you traveled to your
employer's worksite, approximately what time did you leave for work (e.g. 8:30am)? -
quantitative"
§ leavetime_current_quant "Currently, when you traveled to your employer's worksite,
approximately what time did you leave for work (e.g. 8:30am)? - quantitative"
§ worktime_curr_home_pct "What percentage of your total working time do you currently
spend at your home?"
§ worktime_curr_ebp_pct "What percentage of your total working time do you currently
spend at your employer's worksite"
§ worktime_curr_client_pct "What percentage of your total working time do you currently
spend at a client or customer's worksite?"
§ worktime_curr_faf_pct "What percentage of your total working time do you currently spend
at a friend or family member's home"
§ worktime_curr_cowork_pct "What percentage of your total working time do you currently
spend at a co-working space?"
§ worktime_curr_public_pct "What percentage of your total working time do you currently
spend at a public space (cafe library, etc.)?"
§ worktime_des_home_pct "After the pandemic ends what percentage of your total working
time would you like to spend at your home?"
§ worktime_des_ebp_pct "After the pandemic ends what percentage of your total working
time would you like to spend at your employer's worksite"
§ worktime_des_client_pct "After the pandemic ends what percentage of your total working
time would you like to spend at a client or customer's worksite?"
§ worktime_des_faf_pct "After the pandemic ends what percentage of your total working time
would you like to spend at a friend or family member's home"
§ worktime_des_cowork_pct "After the pandemic ends what percentage of your total working
time would you like to spend at a co-working space?"
§ worktime_des_public_pct "After the pandemic ends what percentage of your total working
time would you like to spend at a public space (cafe library, etc.)?"
127
§ worktime_des_nowork "I don't plan to work in 2022'"
§ worktime_plan_home_pct "After the pandemic ends what percentage of your total working
time do you and your employer plan for you to spend at your home?"
§ worktime_plan_ebp_pct "After the pandemic ends what percentage of your total working
time do you and your employer plan for you to spend at your employer's worksite"
§ worktime_plan_client_pct "After the pandemic ends what percentage of your total working
time do you and your employer plan for you to spend at a client or customer's worksite?"
§ worktime_plan_faf_pct "After the pandemic ends what percentage of your total working
time do you and your employer plan for you to spend at a friend or family member's home"
§ worktime_plan_cowork_pct "After the pandemic ends what percentage of your total
working time do you and your employer plan for you to spend at a co-working space?"
§ worktime_plan_public_pct "After the pandemic ends what percentage of your total working
time do you and your employer plan for you to spend at a public space (cafe library, etc.)?"
§ worktime_plan_nowork "I don't plan to work in 2022'"
§ worksite_option "Do you currently have the option to work at more than one employer
worksite?"
§ worktime_remoteable_pct "What percentage of your total working time do you usually
spend on tasks that can be done remotely?"
§ worktime_nonremotable_why "Why can't you work remotely 100% of the time?"
§ choice_dow_prefer "If your employer requires you to work on premises 3 days a week, which
would you prefer?"
§ wbp_dow_preferM "Would choose Monday as 1 of 3 on-premises days"
§ wbp_dow_preferT "Would choose Tuesday as 1 of 3 on-premises days"
§ wbp_dow_preferW "Would choose Wednesday as 1 of 3 on-premises days"
§ wbp_dow_preferR "Would choose Thursday as 1 of 3 on-premises days"
§ wbp_dow_preferF "Would choose Friday as 1 of 3 on-premises days"
§ wfanywhere_qual "In 2022 and later, will your employer allow you to work from anywhere
for one month each year?"
§ cities_attn "In how many big cities with more than 500.000 inhabitants have you lived?
Please insert the number *33* ."
§ who_decides_wfhdays "For employees who work from home, who decides their work-fromhome schedule?"
§ worktime_nonremotable_f2fcl "Can't work remotely: need face-to-face interactions with
clients/customers"
128
§ worktime_nonremotable_f2fco "Can't work remotely: need face-to-face interactions with
colleagues"
§ worktime_nonremotable_equip "Can't work remotely: need to interact with physical
equipment on premises"
§ worktime_nonremotable_other "Can't work remotely: other"
§ workstatus_monday "Monday of last week, did you work a full day (6+ hours), and if so
where?"
§ workstatus_tuesday "Tuesday of last week, did you work a full day (6+ hours), and if so
where?"
§ workstatus_wednesday "Wednesday of last week, did you work a full day (6+ hours), and if
so where?"
§ workstatus_thursday "Thursday of last week, did you work a full day (6+ hours), and if so
where?"
§ workstatus_friday "Friday of last week, did you work a full day (6+ hours), and if so where?"
§ workstatus_saturday "Saturday of last week, did you work a full day (6+ hours), and if so
where?"
§ workstatus_sunday "Sunday of last week, did you work a full day (6+ hours), and if so
where?"
§ wfhcovid_fracmat "Share of paid working days WFH this week (%), i.e. during COVID -
from
`matrix' days-of-week question"
§ grass_color_attnfull "What color is grass? Make sure that you select purple as an answer so
we know you are paying attention."
§ who_sets_wfhsched "Who sets your work-from-home schedule?"
§ factors_wfhsched_cow "Coordinating with coworkers is a factor to consider when setting
your WFH schedule"
§ factors_wfhsched_spouse "Coordinating with spouse is a factor to consider when setting
your WFH schedule"
§ factors_wfhsched_client "Coordinating with customers/clients is a factor to consider when
setting your WFH schedule"
§ factors_wfhsched_traffic "Commuting when there's less traffic/congestion is a factor to
consider when setting your WFH schedule"
§ common_varying_sched "What type of work-from-home schedule does your manager or
employer set?"
§ wfh_handle_chores "How often do you work from home to handle matters that require your
presence (e.g., to be there for a plumber, a repair person, or deliveries)?"
§ showerbathe_wbp "Do you shower/bathe each morning when you travel to work?"
129
§ brushteeth_wbp "Do you brush your teeth each morning when you travel to work?"
§ deodorant_wbp "Do you use deodorant each morning when you travel to work?"
§ makeup_wbp "Do you put on makeup each morning when you travel to work?"
§ shave_wbp "Do you shave each morning when you travel to work?"
§ freshclothes_wbp "Do you wear fresh clothes each morning when you travel to work?"
§ alarm_wbp "Do you set an alarm each morning when you travel to work?"
§ showerbathe_wfh "Do you shower/bathe each morning when you work from home?"
§ brushteeth_wfh "Do you brush your teeth each morning when you work from home?"
§ deodorant_wfh "Do you use deodorant each morning when you work from home?"
§ makeup_wfh "Do you put on makeup each morning when you work from home?"
§ shave_wfh "Do you shave each morning when you work from home?"
§ freshclothes_wfh "Do you wear fresh clothes each morning when you work from home?"
§ alarm_wfh "Do you set an alarm each morning when you work from home?"
§ commute_mode_faf "Commuting mode to the friends and family home"
§ commute_mode_cowork "Commuting mode to the co-working space"
§ commute_mode_public "Commuting mode to the public space"
§ commutetime_to_faf "Commuting time to the friends and family home (mins)"
§ commutetime_to_cowork "Commuting time to the co-working space (mins)"
§ commutetime_to_public "Commuting time to the public space (mins)"
§ commutetime_from_faf "Commuting time from the friends and family home (mins)"
§ commutetime_from_cowork "Commuting time from the co-working space (mins)"
§ commutetime_from_public "Commuting time from the public space (mins)"
§ party_affiliation "Do you usually think of yourself as a Republican, Democrat, Independent,
or what?"
§ party_affiliation_s "Do you usually think of yourself as a Republican, Democrat,
Independent, or what? (simplified variable)"
§ leanDem "100 x 1(Democrat or Independent, close to Democrat)"
§ leanRep "100 x 1(Republican or Independent, close to Republican)"
§ leanInd "100 x 1(Independent, neither party)"
§ Dem_self "100 x 1(Democrat)"
§ Rep_self "100 x 1(Republican)"
§ Ind_self "100 x 1(Independent)"
130
§ numwfh_days_postCOVID_boss_s_u_l "Employer planned share of paid working days WFH
after COVID (%) - this version does not reclassify workers w/o clear indications from their
employers based on current working status"
§ infection_labsearch_avoid "In my job search, I avoid jobs with high infection risk"
§ infection_labsearch_highpay "In my job search, I require higher pay for jobs with high
infection risk"
§ infection_labsearch_benefits "In my job search, I require higher benefits for jobs with high
infection risk"
§ infection_labsearch_wfhpref "In my job search, I prefer jobs allowing me to work from
home"
§ infection_labsearch_no "Worries about infection don't affect my job search'"
§ labsearch_qual "Which of the following best describes your job search (with respect to
WFH)?"
§ infection_lfp "Are worries about catching COVID or other infectious diseases a factor in your
decision not to seek work at this time?"
§ wfh_lfp "Would you start seeking work if you were guaranteed to find a job allowing you to
work from home?"
§ coworkers_samedays_pref "Would you like your co-workers to come into work on the same
days as you?"
§ wfh_coordinate_eff "Which of the following would make your job more efficient?"
§ wfh_coordinate_pref "Which of the following would you prefer?"
§ wbp_smallmeet_pref "When you are working on your employer's premises, how would you
like to hold small meetings with your coworkers?"
§ wfh_top3benefits_commute "Top 3 benefits of WFH include: No commute"
§ wfh_top3benefits_groom "Top 3 benefits of WFH include: Less time getting ready"
§ wfh_top3benefits_flex "Top 3 benefits of WFH include: Flexibility on when I work"
§ wfh_top3benefits_meetings "Top 3 benefits of WFH include: Fewer meetings"
§ wfh_top3benefits_quiet "Top 3 benefits of WFH include: Individual quiet time"
§ wfh_top3benefits_family "Top 3 benefits of WFH include: More time with family/friends"
§ wfh_top3benefits_other "Top 3 benefits of WFH include: Other"
§ wfh_top3benefits_num "Number of benefits of WFH chosen"
§ wbp_top3benefits_collab "Top 3 benefits of WBP include: Face-toface collaboration"
§ wbp_top3benefits_social "Top 3 benefits of WBP include: Socializing"
§ wbp_top3benefits_facetime "Top 3 benefits of WBP include: Face time with manager"
131
§ wbp_top3benefits_equip "Top 3 benefits of WBP include: Better equipment"
§ wbp_top3benefits_quiet "Top 3 benefits of WBP include: Quiet"
§ wbp_top3benefits_bound "Top 3 benefits of WBP include: Work/personal time boundaries"
§ wbp_top3benefits_other "Top 3 benefits of WBP include: Other"
§ wbp_top3benefits_num "Number of benefits of WBP chosen"
§ wfhcovid_cpsq "100 x (At any time in the last 4 weeks, did you telework or work at home for
pay because of the coronavirus pandemic?) - numeric"
§ wfhcovid_fracmat_all "Share of paid working days WFH this week (%), i.e. during COVID -
from `matrix' days-of-week question. This version for ALL respondents (not just those
currently working)"
§ whfcovid_cpsq_posend "Equals 1 if CPS question about telework appears at the end of the
survey. 0 otherwise."
§ freq_nonwork_car "How frequently do you use a car for non-work trips? - qualitative"
§ freq_nonwork_taxi "How frequently do you use a taxi/rideshare for non-work trips? -
qualitative"
§ freq_nonwork_transit "How frequently do you use public transit for non-work trips? -
qualitative"
§ freq_nonwork_bike "How frequently do you use a bicycle for non-work trips? - qualitative"
§ freq_nonwork_walk "How frequently do you walk for non-work trips? - qualitative"
§ worktime_nonremoteable_pct "What percentage of your total working time do you usually
spend on tasks that cannot be done remotely?"
§ workstatus_current_d "Currently (this week) what is your work status - detailed version prior
to November 2020"
§ income_year "Year corresponding to the main labor earnings question used to construct
weights for the respondent."
§ infectionfear_car "On a scale of 0 to 4, how concerned are you about getting infected with a
serious illness (e.g. COVID-19) each time you travel by car?"
§ infectionfear_taxi "On a scale of 0 to 4, how concerned are you about getting infected with a
serious illness (e.g. COVID-19) each time you travel by taxi/rideshare?"
§ infectionfear_bus "On a scale of 0 to 4, how concerned are you about getting infected with a
serious illness (e.g. COVID-19) each time you travel by bus?"
§ infectionfear_subway "On a scale of 0 to 4, how concerned are you about getting infected
with a serious illness (e.g. COVID-19) each time you travel by subway?"
§ infectionfear_train "On a scale of 0 to 4, how concerned are you about getting infected with a
serious illness (e.g. COVID-19) each time you travel by commuter train?"
132
§ infectionfear_bikewalk "On a scale of 0 to 4, how concerned are you about getting infected
with a serious illness (e.g. COVID-19) each time you travel by bicycle or walking?"
§ forcedchoice_prefer "If your employer said you need to come to work in person two days a
week, which would you prefer?"
§ device_used "What device are you using to answer this survey?"
§ wfh_interviewing "Has working from home made it easier or harder to interview for
prospective new jobs?"
§ work_facility "What type of facility best describes where you work (or worked in your most
recent job)?"
§ mask_indoorsatwork "In the past week, how often did you wear a face mask indoors at
work?"
§ mask_outdoorsleisure "In the past week, how often did you wear a face mask outdoors for
leisure?"
§ mask_whendriving "In the past week, how often did you wear a face mask when driving your
own car?"
§ mask_home "In the past week, how often did you wear a face mask in your own house?"
§ mask_indoorsleisure "In the past week, how often did you wear a face mask indoors for
leisure?"
§ work_computer_pct "When working, what percentage of the time are you using a laptop or
desktop computer?"
§ occupation_clean "Occupation (self-reported and reassigning 'Other' occupations based on
description)"
§ sum3plus4 "What is 3 + 4?"
Note: We first asked this question in the March 2022 survey but did not allow respondents to
complete it if they did not answer correctly. From April 2022 we do allow respondents to
continue if they get it wrong and intend to use it as part of our battery of attention check
questions.
§ boss_plan_implement "Are you already following your employer's plan for post-COVID
working arrangements?"
§ interview_time_remote "How many hours does it take to interview for a prospective job via
an online interview?"
§ interview_time_inperson "How many hours does it take to interview for a prospective job
via an in-person interview?"
§ employer_days_meet "Last week, did you come into work as many days as your employer
wanted you to come in?"
§ wbp_days_comein "Days came into work last week"
133
§ wbp_days_empwant "Days employer wanted you to come into work"
§ fewerdays_punishment "How has your employer responded to employees who work on
business premises fewer days than requested?"
Note: This variable applies to the May 2022 version of the underlying survey question,
which allowed respondents to pick a single answer. The June 2022 and later versions of the
question allow for multiple answers, resulting in the separate variables names
“fewerdays_...” below.
§ handshake_current "Currently, when you are introduced to somebody at work, what do you
do?"
§ fewerdays_nothing "Nothing - if come into work less than employer requests"
§ fewerdays_verbal "Verbal reprimand - if come into work less than employer requests"
§ fewerdays_perfrev "Negative performance review - if come into work less than employer
requests"
§ fewerdays_lesspay "Pay cut or bonus - if come into work less than employer requests"
§ fewerdays_threat "Threat to terminate - if come into work less than employer requests"
§ fewerdays_terminate "Termination - if come into work less than employer requests"
§ fewerdays_other "Other - if come into work less than employer requests"
§ fewerdays_dontknow "Don't know - if come into work less than employer requests"
§ fewerdays_user "User input for other - if come into work less than employer requests"
§ failcomplete_nothing "Nothing - if consistently fail to complete work on time"
§ failcomplete_verbal "Verbal reprimand - if consistently fail to complete work on time"
§ failcomplete_perfrev "Negative performance review - if consistently fail to complete work
on time"
§ failcomplete_lesspay "Pay cut or bonus - if consistently fail to complete work on time"
§ failcomplete_threat "Threat to terminate - if consistently fail to complete work on time"
§ failcomplete_terminate "Termination - if consistently fail to complete work on time"
§ failcomplete_other "Other - if consistently fail to complete work on time"
§ failcomplete_dontknow "Don't know - if consistently fail to complete work on time"
§ failcomplete_user "User input for other - if consistently fail to complete work on time"
§ infection_labsearch_avoid_nofi "Indicator equal to 1 if 'No' option shown first for
infection_labsearch_avoid question"
§ infection_labsearch_highpay_nofi "Indicator equal to 1 if 'No' option shown first for
infection_labsearch_highpay question"
134
§ infection_labsearch_benef_nofi "Indicator equal to 1 if 'No' option shown first for
infection_labsearch_benefits question"
§ infection_labsearch_wfhpref_nofi "Indicator equal to 1 if 'No' option shown first for
infection_labsearch_wfhpref question"
§ infection_labsearch_no_nofi "Indicator equal to 1 if 'No' option shown first for
infection_labsearch_no question"
§ labsearch_qual_nofi "Indicator equal to 1 if 'No' option shown first for labsearch_qual
question"
§ infection_lfp_nofi "Indicator equal to 1 if 'No' option shown first for infection_lfp question"
§ wfh_lfp_nofi "Indicator equal to 1 if 'No' option shown first for wfh_lfp_nofi question"
§ npeople_engage_work_cat "During a typical workday, how many coworkers, customers, and
clients do you engage in person or by video?"
§ meetings_workday_pct "What percentage of your typical workday do you spend meeting or
talking to people?"
§ meetings_cow_pct "What percentage of your typical workday do you spend in meetingsthat
include coworkers?"
§ nilf_mainreason_HPS_clean "What is your main reason for not working for pay or profit?"
§ big5_vividimagination "Big 5: I have a vivid imagination"
§ big5_sympathize "Big 5: I sympathize with others' feelings"
§ big5_makeamess "Big 5: I make a mess of things"
§ big5_lifeoftheparty "Big 5: I am the life of the party"
§ big5_moodswings "Big 5: I have frequent mood swings"
§ big5_donttalk "Big 5: I don't talk a lot"
§ big5_notabstract "Big 5: I am not interested in abstract ideas"
§ big5_forgetputback "Big 5: I often forget to put things back in their proper place"
§ big5_seldomblue "Big 5: I seldom feel blue"
§ big5_notinterestedothers "Big 5: I am not really interested in others"
§ big5_feelothersemotions "Big 5: I feel others' emotions"
§ big5_getupseteasily "Big 5: I get upset easily"
§ big5_getchoresdone "Big 5: I get chores done right away"
§ big5_notgoodimagination "Big 5: I do not have a good imagination"
§ big5_keepinbackground "Big 5: I keep in the background"
§ big5_diffabstract "Big 5: I have difficulty understanding abstract ideas"
135
§ big5_relaxed "Big 5: I am relaxed most of the time"
§ big5_nototherproblems "Big 5: I am not interested in other people's problems"
§ big5_talktodiffpeople "Big 5: I talk to a lot of different people at parties"
§ big5_likeorder "Big 5: I like order"
§ job_att_rank_advance "Job attributes rank: chances for advancement (1 = Most important)"
§ job_att_rank_important "Job attributes rank: important and feeling of accomplishment (1 =
Most important)"
§ job_att_rank_nofire "Job attributes rank: No danger of being fired (1 = Most important)"
§ job_att_rank_income "Job attributes rank: High income (1 = Most important)"
§ job_att_rank_hours "Job attributes rank: Short working hours, lots of free time (1 = Most
important)"
§ life_rank_family "Life priorities: Family (1 = Most important)"
§ life_rank_friends "Life priorities: Friends (1 = Most important)"
§ life_rank_work "Life priorities: Work (1 = Most important)"
§ life_rank_politics "Life priorities: Politics (1 = Most important)"
§ life_rank_leisure "Life priorities: Leisure time (1 = Most important)"
§ life_rank_religion "Life priorities: Religion/spirituality (1 = Most important)"
§ work_firm_succeed "I am willing to work harder to help the firm I work for succeed."
§ wfh_top3benefits_gaslunch "Top 3 benefits of WFH include: Saving on gas and lunch costs"
§ wbp_top3benefits_mentoring "Top 3 benefits of WBP include: Better professional
development, learning, mentoring"
§ CSA_job_curr "Combined Statistical Area (City) of current job's business premises"
§ CSA_live_curr "Combined Statistical Area (City) of current residence"
§ wfh_eff_noCOVID_randi "Binary indicator for whether we randomized response options in
the efficiency question"
§ work_industry_tech "Is your current (or most recent) job in the tech sector?"
§ habitsrev_postCOVID "Same as habits_postCOVID but with reverse order of response
options"
§ jobsearch_changes_order "Order of response options: infection_labsearch_* questions"
§ jobsearch_wfh_order "Order of response options: labsearch_qual question"
§ notlooking_reasons_order "Order of response options: infection_lfp"
§ start_looking_order "Order of response options: wfh_lfp"
§ wfh_eff_noCOVID_order "Order of options shown in wfh_eff_noCOVID_qual"
136
§ female_fertility_qual "Have you given birth to any children in 2015 or later?"
§ male_fertility_qual "Are you the biological father of any children born in 2015 or later?"
§ female_fertility_quant "How many children have you given birth to in 2015 or later?"
§ male_fertility_quant "How many children born in 2015 or later are you the biological father
of?"
§ child`i'_birthyear_f "Birth year of biological child `i' - missing if fewer than `i' children.
Only asked from 11/22 onwards."
o Note: The above describes variables for � = 1, 2, 3, 4, 5, 6.
§ children_des_wfhself "Factor in the decision to have children: OWN ability to WFH"
§ children_des_housing "Factor in the decision to have children: housing costs"
§ children_des_healthcare "Factor in the decision to have children: access to health
insurance/care"
§ children_des_wfhpartner "Factor in the decision to have children: PARTNER's ability to WFH"
§ children_des_careerself "Factor in the decision to have children: OWN career prospects"
§ children_des_careerpart "Factor in the decision to have children: PARTNER's career
prospects"
§ children_des_tax "Factor in the decision to have children: tax benefits/credits"
§ children_des_childcare "Factor in the decision to have children: childcare costs"
§ manage_employees_qual "Do you directly manage or supervise other employees in your
organization?"
§ manage_employees_quant "How many employees do you directly manage or supervise?"
§ mycamera_on_2to4person "During 2 to 4 person work meetings on video-conferencing
platforms, how often do you have your camera on?"
§ mycamera_on_5to10person "During 5 to 10 person work meetings on video-conferencing
platforms, how often do you have your camera on?"
§ mycamera_on_10to30person "During 10 to 30 person work meetings on video-conferencing
platforms, how often do you have your camera on?"
137
§ mycamera_on_30plusperson "During >30 person work meetings on video-conferencing
platforms, how often do you have your camera on?"
§ othcamera_on_2to4person "During 2 to 4 person work meetings on video-conferencing
platforms, how often do others have their camera on?"
§ othcamera_on_5to10person "During 5 to 10 person work meetings on video-conferencing
platforms, how often do others have their camera on?"
§ othcamera_on_10to30person "During 10 to 30 person work meetings on video-conferencing
platforms, how often do others have their camera on?"
§ othcamera_on_30plusperson "During >30 person work meetings on video-conferencing
platforms, how often do others have their camera on?"
§ mycamera_eff_2to4person "During 2 to 4 person work meetings on video-conferencing
platforms, how does having your camera on (showing your face) impact your engagement?"
§ mycamera_eff_5to10person "During 5 to 10 person work meetings on video-conferencing
platforms, how does having your camera on (showing your face) impact your engagement?"
§ mycamera_eff_10to30erson "During 10 to 30 person work meetings on video-conferencing
platforms, how does having your camera on (showing your face) impact your engagement?"
§ mycamera_eff_30plusperson "During >30 person work meetings on video-conferencing
platforms, how does having your camera on (showing your face) impact your engagement?"
§ othcamera_eff_2to4person "During 2 to 4 person work meetings on video-conferencing
platforms, how does having their camera on (showing their face) impact others' engagement?"
§ othcamera_eff_5to10person "During 5 to 10 person work meetings on video-conferencing
platforms, how does having their camera on (showing their face) impact others' engagement?"
§ othcamera_eff_10to30person "During 10 to 30 person work meetings on video- conferencing
platforms, how does having their camera on (showing their face) impact others' engagement?"
138
§ othcamera_eff_30plusperson "During >30 person work meetings on video-conferencing
platforms, how does having their camera on (showing their face) impact others' engagement?"
§ camera_column_order "Order of responses shown for camera questions - low_to_high or
high_to_low"
§ random_day_of_week "Day of week reference for interaction question"
§ work_random_dow "Last random_day_of_week did you: WFH, come into work, or not
work?"
§ mins_getting_mentored "Interaction: getting mentored (mins)"
§ mins_mentoring_others "Interaction: mentoring others (mins)"
§ mins_disc_ownperform "Interaction: discussing your performance w/ supervisor (mins)"
§ mins_disc_othperform "Interaction: discussing performance of managees (mins)"
§ mins_training "Interaction: training (mins)"
§ mins_profdev "Interaction: professional development and learning (mins)"
§ limit_vigorous "Does your health currently limit you in doing vigorous activities?"
§ limit_moderate "Does your health currently limit you in doing moderate activities?"
§ limit_lifting "Does your health currently limit you in lifting/carrying groceries?"
§ limit_severalflights "Does your health currently limit you in climbing several flights of stairs?"
§ limit_oneflight "Does your health currently limit you in climbing one flight of stairs?"
§ limit_kneeling "Does your health currently limit you in bending, kneeling, or stopping?"
§ limit_mileplus "Does your health currently limit you in walking more than one mile?"
§ limit_severalblocks "Does your health currently limit you in walking several blocks?"
§ limit_oneblock "Does your health currently limit you in walking one block?"
§ limit_bathdress "Does your health currently limit you in bathing or dressing yourself?"
§ subj_wellbeing "Subjective wellbeing ladder - best life at 10 worst at 0, on which step do you
currently stand?"
§ children_household_yesno "Are there children under 18 living in your household?"
§ covid_test_positive "Have you had a positive diagnosis for COVID-19?"
139
§ covid_believe_positive "Despite not testing positive, do you believe you have had COVID19?"
§ covid_long_qual "Did you have any symptoms lasting 3 months or longer that you did not
have prior to having COVID?"
§ covid_long_close_qual "Have any close friends or family members experienced COVID
symptoms lasting 3 months or longer?"
§ covid_vuln_care_qual "Do you live with or care for someone who would be more vulnerable
than the general population to COVID or other infectious diseases?"
§ ever_meet_coworkers "Do you ever meet with your coworkers in person?"
§ long_meet_coworkers "When you do meet your coworkers, for how long do you meet?"
§ workday_exercise "Last [random day of the week] EXERCISED during the workday"
§ workday_readleisure "Last [random day of the week] READ FOR LEISURE during
the workday"
§ workday_gaming "Last [random day of the week] PLAYED A PHONE/COMPUTER
GAME during the workday"
§ workday_chores "Last [random day of the week] DID CHORES during the workday"
§ workday_childcare "Last [random day of the week] DID CHILDCARE during the workday"
§ workday_errands "Last [random day of the week] DID PERSONAL ERRANDS during
the workday"
§ workday_other "Last [random day of the week] DID OTHER during the workday"
§ workday_none "Last [random day of the week] DID NONE OF THE ABOVE during
the workday"
§ workcomm_email "Uses EMAIL to communicate for work purposes"
§ workcomm_slack "Uses SLACK to communicate for work purposes"
§ workcomm_textpersonal "Uses MESSAGING ON PERSONAL PHONE to communicate
for work purposes"
§ workcomm_zoom "Uses ZOOM to communicate for work purposes"
§ workcomm_teams "Uses MICROSOFT TEAMS to communicate for work purposes"
§ workcomm_officephone "Uses OFFICE PHONE CALLS to communicate for work purposes"
140
§ workcomm_personalphone "Uses HOME/PERSONAL PHONE CALLS to communicate for
work purposes"
§ workcomm_none "Uses NONE OF THE ABOVE to communicate for work purposes"
§ workcomm_freq_email "How often do you use EMAIL to communicate for work purposes?"
§ workcomm_freq_slack "How often do you use SLACK to communicate for work purposes?"
§ workcomm_freq_textpersonal "How often do you use MESSAGING ON PERSONAL
PHONE to communicate for work purposes?"
§ workcomm_freq_zoom "How often do you use ZOOM to communicate for work purposes?"
§ workcomm_freq_teams "How often do you use MICROSOFT TEAMS to communicate
for work purposes?"
§ workcomm_freq_officephone "How often do you use OFFICE PHONE CALLS to
communicate for work purposes?"
§ workcomm_freq_personalphone "How often do you use PERSONAL PHONE CALLS
to communicate for work purposes?"
§ overlook_email "How often do you overlook work-related EMAIL communications?"
§ overlook_slack "How often do you overlook work-related SLACK communications?"
§ overlook_textpersonal "How often do you overlook work-related TEXT MESSAGES ON
YOUR PERSONAL PHONE?"
§ overlook_zoom "How often do you overlook work-related ZOOM communications?"
§ overlook_teams "How often do you overlook work-related MICROSOFT
TEAMS communications?"
§ overlook_officephone "How often do you overlook work-related CALLS ON YOUR
OFFICE PHONE"
§ overlook_personalphone "How often do you overlook work-related CALLS ON
YOUR PERSONAL PHONE?"
§ afterhours_email "How often do you respond to work-related EMAIL communications after
hours or on weekends?"
§ afterhours_slack "How often do you respond to work-related SLACK communications after
hours or on weekends?"
141
§ afterhours_textpersonal "How often do you respond to work-related TEXT MESSAGES ON
YOUR PERSONAL PHONE after hours or on weekends?"
§ afterhours_zoom "How often do you respond to work-related ZOOM communications after
hours or on weekends?"
§ afterhours_teams "How often do you respond to work-related MICROSOFT TEAMS
communications after hours or on weekends?"
§ afterhours_officephone "How often do you respond to work-related CALLS ON YOUR
OFFICE PHONE after hours or on weekends?"
§ afterhours_personalphone "How often do you respond to work-related CALLS ON
YOUR PERSONAL PHONE after hours or on weekends?"
§ workday_alcohol "Last [random day of the week] DRANK ALCOHOL during the workday"
§ work_random_dow_d "Last random_day_of_week which of these did you do? -
DETAILED VERSION"
§ workday_split_indiv "Individual Work % Split of Last Random Day of Week"
§ workday_split_meet2to4 "2 to 4 Person Meetings % Split of Last Random Day of Week"
§ workday_split_meet5plus "5 or More Person Meetings % Split of Last Random Day of Week"
§ workday_split_lunch "Lunmch % Split of Last Random Day of Week"
§ workday_split_downtime "Downtime % Split of Last Random Day of Week"
§ sick_lastweek_qual "Were you feeling sick, ill, or injured on any days last week?"
§ sick_lastweek_quant "On how many workdays did you feel sick, ill or injured last week?"
§ sick_lastweek_workanyway "Sick/Ill/Injured Days Last Week You WORKED ANYWAY"
§ sick_lastweek_wfh "Sick/Ill/Injured Days Last Week You WORKED FROM HOME"
§ sick_lastweek_notwork "Sick/Ill/Injured Days Last Week You DIDN'T WORK"
§ usual_days_perweek "Usual number of days worked per week (categorical)"
§ ioneyearahead "Saw version of worker desires/employer plans saying `one year ahead'"
§ iextratime_new "Saw version of extratime question saying `while you WFH'"
§ onewaytrip_fullremote "How long would it take to travel (one-way) from your home to your
employer's location?"
142
§ compress_feel_hoursconst "How would you feel about compressing your workweek into 4
days, while continuing to work the same number of hours over the week?"
§ compress_feel_workconst "How would you feel about compressing your workweek into 4
days, while doing the same amount of work over the week?"
§ compress_feel_hoursconst_qual "How much of a pay raise/cut do you value compressing your
workweek into 4 days, while continuing to work the same number of hours over the week?"
§ compress_feel_workconst_qual "How much of a pay raise/cut do you value compressing your
workweek into 4 days, while doing the same amount of work over the week?"
§ compress_feel_hoursconst_quant "How much of a pay raise/cut do you value compressing
your workweek into 4 days, while continuing to work the same number of hours over the
week?"
§ compress_feel_workconst_quant "How much of a pay raise/cut do you value compressing
your workweek into 4 days, while doing the same amount of work over the week?"
§ prefer_4d10h_5d8h "Which do you prefer: working 4-days per week for 10 hours or 5 day per
week for 8 hours?"
§ manager_4day_shift "In the past 12 months, has your manager spoken to you about shifting to
a 4-day workweek?"
§ wfh_able_intcount_cont "How much would your efficiency working from home increase if
you had perfect high-speed internet?"
§ work_alldays_mat "Total number of days working 6+hours last week - from matrix question
w/o restricting by work status"
§ work_wfhdays_mat "Total number of days working from home last week - from matrix
question w/o restricting by work status"
§ work_wbpdays_mat "Total number of days working on employer/client premises last week
- from matrix question w/o restricting by work status"
§ birth_year "What year were you born?"
§ employer_emp_cat "Counting all of its locations, how many employees work for your primary
employer?"
143
§ live_adults_partner "Binary indicator for whether living with a spouse/domestic partner"
§ employer_censusbirth_cat_d "When did your your employer hire its first employee (at any
location)? - Breakdown pre-2006"
§ employer_mylocbirth_cat_d "When did your employer start operations at the location you
are assigned to? - Breakdown pre-2006"
§ fullremote_payvary "As a fully remote employee, does your pay depend on where you live?"
§ sick_lastweek_type "Last week, when you felt sick/ill/injured were you: sick/ill contagious,
sick/ill NOT contagious, or injured?"
§ two_video_calls "Have you ever been on two video calls at the same time?"
§ talktext_during_calls "How often do you talk to or text your family or friends while on a work
call on Zoom/Teams/Webex or similar?"
§ multitask_during_calls_num "When you are on work calls on Zoom/Teams/Webex what
share of the time are you multi-tasking? - numerical"
§ multitask_during_calls_cat "When you are on work calls on Zoom/Teams/Webex whatshare
of the time are you multi-tasking? - categorical"
§ multitask_during_calls_catq "When you are on work calls on Zoom/Teams/Webex what
share of the time are you multi-tasking? - quantitative from cat"
§ howlong_resi_current "How long have you lived in your current residence?"
§ manager_4day_ntimes "How many times in the past 12 months has your manager spoken to
you about shifting to a 4-day workweek?"
§ manager_4day_recent "When did your manager speak to you most recently about shifting to
a 4-day workweek?"
§ manager_4day_message "What was your manager's message when they most recently
spoke to you about shifting to a 4-day workweek?"
§ commknow_ftjobs "Do any of your employers know you have another full-time job?"
§ num_ftjobs "How many full-time jobs do you currently have? - qualitative"
§ cps_telework23_yesno "At any time LAST WEEK did you telework or work at home for
pay?"
§ cps_telework20_yesno "Did you telework or work at home for pay in February 2020 before
the COVID-19 pandemic started?"
144
§ cpsalt_telework23_yesno "Did you spend any time LAST WEEK working at home for your
job?"
§ cpsalt_telework20_yesno "Did you spend any time working at home for your job in February
2020 before the COVID-19 pandemic started?"
§ cps_telework23_hours "Last week, you worked N hours. How many of these hours did you
telework or work at home for pay?"
§ cpsalt_telework23_hours "Last week, you worked N hours. How many of these hours did you
work at home (or at a friends place, coffee shop, or the like)?"
§ cps_telework20_moreless "LAST WEEK, did you do more, less, or the same amount of
telework or work at home for pay as in February 2020 (before the COVID-19 pandemic)?"
§ cpsalt_telework20_moreless "LAST WEEK did you do more, less or the same amount of
work at home for your job as in February 2020 (before the COVID-19 pandemic)?"
§ cps_remote_hours_pct "Percent of hours worked last week that you teleworked or worked at
home for pay"
§ cpsalt_remote_hours_pct "Percent of hours worked last week that you worked at home (or a
friend's place, coffee shop, or other location)"
§ ilowquality "Indicator for low quality data."
§ education_ss "Education - categorical with only 4 values"
§ pets_no "Do you live with any pets? - No"
§ pets_dogs "Do you live with any pets? - Yes, dog(s)"
§ pets_cats "Do you live with any pets? - Yes, cat(s)"
§ pets_fish "Do you live with any pets? - Yes, fish"
§ pets_rabbits "Do you live with any pets? - Yes, rabbit(s)"
§ pets_rodents "Do you live with any pets? - Yes, hamster(s)/rats(s)/guinea pig(s)"
§ pets_reptiles "Do you live with any pets? - Yes, lizard(s), turtle(s), or snake(s)"
§ pets_birds "Do you live with any pets? - Yes, owl(s), falcon(s), or other bird(s)"
§ pets_other "Do you live with any pets? - Yes, other"
§ workday_hours_videocall "Hours in video or phone calls last random_day_of_week"
§ workday_hours_f2fmeeting "Hours in face-to-face meetings last random_day_of_week"
145
§ workday_hours_textemail "Hours in text or email conversationslast random_day_of_week"
§ workday_hours_indivwork "Hours doing individual work last random_day_of_week"
§ workday_hours_downtime "Hours of downtime last random_day_of_week"
§ workday_pct_videocall "Percent of workday in video or phone calls last
random_day_of_week"
§ workday_pct_f2fmeeting "Percent of workday in video call or phone last
random_day_of_week"
§ workday_pct_textemail "Percent of workday in text or email conversations last
random_day_of_week"
§ workday_pct_indivwork "Percent of workday doing individual work last
random_day_of_week"
§ workday_pct_downtime "Percent of workday on downtime last random_day_of_week"
§ wfh_ideal_physical_health "If you worked 5 days/week, how many WFH days/week would
be best for your physical health?"
§ wfh_ideal_mental_health "If you worked 5 days/week, how many WFH days/week would be
best for your mental health?"
§ age_2digit "How old are you?"
§ mostrecent_workday_dow "What day of the week was your most recent workday before
today?"
§ mostrecent_workday_nmeet "How many work-related meetings did you have on your most
recent workday?"
§ selected_meeting_time "Randomly selected time for meeting used in:
selected_meeting_npeople selected_meeting_duration selected_meeting_modes - string"
§ iselected_meeting_time "Randomly selected time for meeting used in:
selected_meeting_npeople selected_meeting_duration selected_meeting_modes - categorical"
§ selected_meeting_npeople "How many people (including yourself) participated in
[randomly_selected_meeting]?"
§ selected_meeting_duration "How long did the meeting last?"
146
§ selected_meeting_modes "How did meeting participants engage with one another in that
meeting?"
§ solve_problems_qual "In your current job, where do you solve problems faster?"
§ solve_problems_qual_d "In your current job, where do you solve problems faster? -
detailed"
§ solve_problems_quant "How much faster (%) do you solve problems when WFH (negative if
faster on employer premises)?"
§ learn_things_qual "In your current job, where do you learn new things faster?"
§ learn_things_qual_d "In your current job, where do you learn new things faster? - detailed"
§ learn_things_quant "How much faster (%) do you learn things when WFH (negative if faster
on employer premises)?"
§ help_job_higher "When you need help doing your job, percent of the time you go to a higherup"
§ help_job_peer "When you need help doing your job, percent of the time you go to a peer"
§ help_job_selfother "When you need help doing your job, percent of the time you go
elsewhere/solve on your own"
§ hours_mentored "Hours in the past month: getting mentored or discussing performance
with supervisor"
§ hours_training "Hours in the past month: training sessions led by colleagues or higher-ups"
§ hours_seminars "Hours in the past month: work-related courses or seminars taught by
persons outside place of work"
§ hours_ownlearning "Hours in the past month: work-related learning on your own"
§ seminars_college_qual "Were any of the work-related courses/seminars taught at a college
or university?"
§ useful_mentoring "How often do you use what you learned getting mentored?"
§ useful_training "How often do you use what you learned in training?"
§ useful_seminars "How often do you use what you learned in courses/seminars?"
§ useful_ownlearning "How often do you use what you learned own your own?"
§ rank_mentoring "Mentoring: rank by usefulness in another job"
147
§ rank_training "Training: rank by usefulness in another job"
§ rank_seminars "Courses/Seminars: rank by usefulness in another job"
§ rank_ownlearn "Own Learning: rank of activities by usefulness in another job"
§ moreless_mentoring_2019 "Mentoring: hours in 2019 compared to now"
§ moreless_training_2019 "Training: hours in 2019 compared to now"
§ moreless_seminars_2019 "Courses/seminars: hours in 2019 compared to now"
§ moreless_ownlearn_2019 "Own learning: hours in 2019 compared to now"
§ mostrecent_workday_wfhwbp "On your most recent workday did you: WFH the full day or
work on employer/client premises?"
§ selected_meeting_who_peers "Indicator for whether PEERS attended
selected_meeting_time"
§ selected_meeting_who_sup "Indicator for whether PEOPLE WHO SUPERVISE YOU
attended selected_meeting_time"
§ selected_meeting_who_managees "Indicator for whether PEOPLE YOU MANAGE
attended selected_meeting_time"
§ selected_meeting_who_clients "Indicator for whether OUTSIDE
CUSTOMERS/CLIENTS attended selected_meeting_time"
§ selected_meeting_who_other "Indicator for whether OTHERS attended
selected_meeting_time"
§ selected_meeting_who_other_user "Description of OTHERS who attended
selected_meeting_time"
§ selected_meeting_schedadv "Was the meeting (selected_meeting_time) scheduled in
advance?"
§ selected_meeting_clearagenda "Did the meeting (selected_meeting_time) have a clear
agenda or purpose?"
§ selected_meeting_part_qual "Did you actively participate in the meeting or just listen?"
§ selected_meeting_part_quant "What percent of the meeting were you actively
participating?"
§ selected_meeting_val_self "How valuable was the meeting for you personally?"
148
§ selected_meeting_val_others "How valuable do you think the meeting was for other
participants?"
§ selected_meeting_val_selfq "How valuable was the meeting for you personally? -
quantitative"
§ selected_meeting_val_othersq "How valuable do you think the meeting was for other
participants? - quantitative"
§ partner_workstatus_current_d "What is your spouse/domestic partner's current working
status?"
§ office_freq "How often do you work in an office space?"
§ office_top3_quality "Top 3 factors about office work: QUALITY OF SPACE"
§ office_top3_travelease "Top 3 factors about office work: EASE OF TRAVEL TO OFFICE"
§ office_top3_equipment "Top 3 factors about office work: EQUIPMENT IN THE SPACE"
§ office_top3_location "Top 3 factors about office work: LOCATION, NEARBY
SHOPPING, RESTAURANTS, ENTERTAINMENT"
§ office_top3_refreshments "Top 3 factors about office work: LUNCH,
DRINKS, REFRESHMENTS AT OFFICE"
§ office_top3_othamenities "Top 3 factors about office work: AMENITIES LIKE TABLE
TENNIS, GYM, ETC."
§ office_inperson_meet_quant "When you work at your employer's site, how much of your
workday is typically filled with in-person meetings and events? - numerical"
§ office_inperson_meet_qual "When you work at your employer's site, how much of your
workday is typically filled with in-person meetings and events?"
§ office_meet_1other "Percent of in-person meetings involing 1 OTHER PERSON"
§ office_meet_2to4others "Percent of in-person meetings involing 2 to 4 OTHERS"
§ office_meet_5to10others "Percent of in-person meetings involing 5 to 10 OTHERS"
§ office_meet_10plusothers "Percent of in-person meetings involing 10+ OTHERS"
§ office_meet_quant "Estimated meeting size by respondent when at the worksite"
§ rto_policies_qual "How many distinct Return to Office Policies has your employer announced
since fall 2020? - categorical"
149
§ rto_policies_quant "How many distinct Return to Office Policies has your employer
announced since fall 2020? - numerical"
§ rto_compliance_pct "Roughly what percentage of your co-workers comply with your
employer's current Return to Office Policy?"
§ rto_conseq_nothing "What happens to employees who don't comply with RTO Policy:
NOTHING"
§ rto_conseq_verbal "What happens to employees who don't comply with RTO Policy:
VERBAL REPRIMAND"
§ rto_conseq_perfrev "What happens to employees who don't comply with RTO Policy:
NEGATIVE PERFORMANCE REVIEW"
§ rto_conseq_paybonus "What happens to employees who don't comply with RTO Policy:
REDUCTION IN PAY/BONUS"
§ rto_conseq_threat "What happens to employees who don't comply with RTO Policy:
THREAT TO TERMINATE"
§ rto_conseq_terminate "What happens to employees who don't comply with RTO Policy:
TERMINATION"
§ rto_conseq_other "What happens to employees who don't comply with RTO Policy: OTHER"
§ rto_conseq_dontknow "What happens to employees who don't comply with RTO Policy:
DON'T KNOW"
§ rto_conseq_otheruser "What happens to employees who don't comply with RTO Policy:
USER INPUT"
§ offsite_events_qual "Does your employer hold occasional offsite events that bring
employees together for a mix of work and social activities?"
§ offsite_events_freq "In 2023, how often did you participate in offsite work/social events
sponsored by your employer?"
§ offsite_events_quant "In 2023, how often did you participate in offsite work/social events
sponsored by your employer? - numerical"
§ offsite_events_freqfull "In 2023, how often did you participate in offsite work/social events
sponsored by your employer? - imputing never"
150
§ offsite_events_quantfull "In 2023, how often did you participate in offsite work/social events
sponsored by your employer? - numerical imputing zeros"
§ offsite_events_size "How many employees typically participated in the offsite employersponsored event(s) that you attended in 2023?"
§ offsite_events_duration "How long did these offsite employer-sponsored events typically
last in 2023?"
§ offsite_events_duration_quant "Number of days offsite employer-sponsored events
typically lasted in 2023?"
§ offsite_events_travel "How many hours did it typically take you to reach these offsite
employer-sponsored events in 2023?"
§ dress_code_current "Currently, what is the dress code at your workplace?"
§ dress_code_2019 "What was the dress code at your workplace in 2019?"
§ same_job_2019 "Are you currently working for the same employer in the same type of job
as in 2019?"
§ blazersuit_days_current "How many days per week do you wear a BLAZER or SUIT
for work?"
§ dressshoes_days_current "How many days per week do you wear DRESS SHOES for work?"
§ blazersuit_days_2019 "In 2019, how many days per week did you wear a BLAZER or SUIT
for work?"
§ dressshoes_days_2019 "In 2019, how many days per week did you wear DRESS SHOES for
work?"
§ selected_meeting_sameroom "Were there any other meeting participants in the same room as
you during the meeting?"
§ inc2019_cat "How much did you earn by working in 2019, on a before-tax basis?"
§ icovid_wfhcovid_ever "Equals 1 if they saw the version of `wfhcovid_ever' that mentions
COVID. Equals 0 if they saw the version referring to 2020."
§ considered_wfhjob "Have you applied or considered applying to a job that would allow you
to work from home 1 or more days per week?"
151
2. Value labels of categorical variables. See below for the value labels of categorical variables.
Our replication code in the file WFH_results_Master_May21.do also labels the values of each of
the included categorical variables below.
§ Age
agebin 1 "Under 20"
agebin 2 "20 - 29"
agebin 3 "30 - 39"
agebin 4 "40 - 49"
agebin 5 "50 - 64"
agebin 6 "65+"
§ Education (there are two similar variables)
education 1 "Less than high-school graduation"
education 2 "High-school graduation"
education 3 "1 to 3-years of college"
education 4 "4 years of college degree"
education 5 "Masters or Professional Degree"
education 6 "PhD"
education 1 "Less than high-school degree"
education 2 "High-school degree"
education 3 "1 to 3-years of college"
education 4 "4-year college degree"
education 5 "Graduate degree"
§ Efficiency WFH during COVID relative to
expectations wfh_expect 1 "Hugely better, 20%+ "
wfh_expect 2 "Substantially better -- 10 to 20% "
152
wfh_expect 3 "Better -- up to 10% "
wfh_expect 4 "About the same "
wfh_expect 5 "Worse - up to 10% "
wfh_expect 6 "Substantially worse - 10 to 20% "
wfh_expect 7 "Hugely worse, 20%+ "
§ Current working status
workstatus_current 1 "Working on my business premises"
workstatus_current 2 "Working from home"
workstatus_current 3 "Not working"
§ Income categories (coarse and fine)
iincomebin 1 "$20k to $50k"
iincomebin 2 "$50k to $100k"
iincomebin 3 "$100k to $150k"
iincomebin 4 "$150k+"
income_cat 0 "<5k",
income_cat 1 "5k - 10k"
income_cat 2 "10k - 20k"
income_cat 3 "20k - 30k"
income_cat 4 "30k - 40k"
income_cat 5 "40k - 50k"
income_cat 6 "50k - 60k"
income_cat 7 "60k - 70k"
income_cat 8 "70k - 80k"
income_cat 9 "80k - 100k"
income_cat 10 "100k - 125k"
income_cat 11 "125k - 150k"
income_cat 12 "150k - 200k"
income_cat 13 "200k - 250k"
income_cat 14 "250k +"
income_cat 15 "Prefer not to answer"
Note: The income_cat labels also apply to the variable containing 2019 income that we
collected in 2022 and later, `inc2019_cat’.
§ Census division (broad region) of residence
censusdiv 1 "New England"
153
censusdiv 2 "Mid-Atlantic"
censusdiv 3 "East North Central"
censusdiv 4 "West North Central"
censusdiv 5 "South Atlantic"
censusdiv 6 "East South Central"
censusdiv "West South Central"
censusdiv 8 "Mountain"
censusdiv 9 "Pacific"
§ Industry of current job
work_industry 1
"Agriculture",
work_industry 2 "Arts & Entertainment"
work_industry 3 "Finance & Insurance"
work_industry 4 "Construction"
work_industry 5 "Education"
work_industry 6 "Health Care & Social Assistance"
work_industry 7 "Hospitality & Food Services"
work_industry 8 "Information"
work_industry 9 "Manufacturing"
work_industry 10 "Mining"
work_industry 11 "Professional & Business Services"
work_industry 12 "Real Estate"
work_industry 13 "Retail Trade"
work_industry 14 "Transportation and Warehousing"
work_industry 15 "Utilities"
work_industry 16 "Wholesale Trade"
work_industry 17 "Government"
work_industry 18 "Other"
§ Sex. Note: gender_d includes the "Other/prefer not to say option" while gender
focuses on male/female (sex only)
gender 1 "Female"
gender 2 "Male"
gender 3 "Other/prefer not to say"
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§ Desired post-COVID working from home days (there are two similar variables)
wfh_days_postCOVID_s 1 "Never"
wfh_days_postCOVID_s 2 "Rarely (e.g.
monthly)" wfh_days_postCOVID_s 3 "1 day per
week"
wfh_days_postCOVID_s 4 "2 days per week"
wfh_days_postCOVID_s 5 "3 days per week"
wfh_days_postCOVID _s 6 "4 days per week"
wfh_days_postCOVID _s 7 "5 days per week"
wfh_days_postCOVID_ss 1 "Rarely or
never" wfh_days_postCOVID_ss 2 "1 day
per week"
wfh_days_postCOVID_ss 3 "2 days per week"
wfh_days_postCOVID_ss 4 "3 days per week"
wfh_days_postCOVID_ss 5 "4 days per week"
wfh_days_postCOVID _ss 6 "5 days per week"
Note: In December 2021 we began a transition to question text that says "After the
pandemic ends," instead of "After COVID, in 2022 and later". The transition to the new
wording will be complete in January 2022.
§ Employer planned post-COVID working from home
days. wfh_days_postCOVID_boss 1 "Never"
wfh_days_postCOVID_boss 2 "Rarely"
wfh_days_postCOVID_boss 3 "1 day per week"
wfh_days_postCOVID_boss 4 "2 days per week"
wfh_days_postCOVID_boss 5 "3 days per week"
wfh_days_postCOVID_boss 6 "4 days per week"
wfh_days_postCOVID_boss 7 "5 day per week"
wfh_days_postCOVID_boss 8 "No clear plans from employer"
wfh_days_postCOVID_boss 9 "No employer"
wfh_days_postCOVID_boss_ss 1 "Rarely or never"
wfh_days_postCOVID_boss_ss 2 "1 day per week"
wfh_days_postCOVID_boss_ss 3 "2 days per week"
wfh_days_postCOVID_boss_ss 4 "3 days per week"
wfh_days_postCOVID_boss_ss 5 "4 days per week"
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wfh_days_postCOVID_boss_ss 6 "5 day per week"
wfh_days_postCOVID_boss_ss 7 "No clear plans from employer"
wfh_days_postCOVID_boss_ss 8 "No employer"
wfh_days_postCOVID_boss_pre_ss 1 "Rarely or never"
wfh_days_postCOVID_boss_pre _ss 2 "1 day per week"
wfh_days_postCOVID_boss_pre _ss 3 "2 days per week"
wfh_days_postCOVID_boss_pre _ss 4 "3 days per week"
wfh_days_postCOVID_boss_pre _ss 5 "4 days per week"
wfh_days_postCOVID_boss_pre _ss 6 "5 day per week"
wfh_days_postCOVID_boss_pre _ss 7 "No clear plans from employer"
wfh_days_postCOVID_boss_pre _ss 8 "No employer"
Note: In December 2021 we began a transition to question text that says "After the
pandemic ends," instead of "After COVID, in 2022 and later". The transition to the new
wording will be complete in January 2022.
§ Ability to work from home. Note: wfh_able is based on a question asked prior to August
2020. wfh_able_qual is based on a question asked from November 2020
wfh_able 1 "Completely, 100%+ efficient"
wfh_able 2 "Mostly, 80% to 90% efficient"
wfh_able 3 "Partly, 50% to 70% efficient"
wfh_able 4 "Barely, less than 50% efficient"
wfh_able 5 "No, I cannot do my job at home"
wfh_able_qual 1 "No"
wfh_able_qual 2 "Yes"
§ Stigma associated with working from home
wfh_Dperception 1 "Improved among almost all"
wfh_Dperception 2 "Improved among most"
wfh_Dperception 3 "Improved among some"
wfh_Dperception 4 "No change"
wfh_Dperception 5 "Worsened among some"
wfh_Dperception 6 "Worsened among most"
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wfh_Dperception 7 "Worsened among almost all"
§ Value of working from home. Note: wfh_feel_legacy is based on a question asked prior to
August 2020. wfh_feel is based on a question asked from August 2020. wfh_feel_detailed uses
a more granular set of responses that we used from September 2020. The numerical variable
wfh_feel_quant uses data from both questions.
wfh_feel 1 "Incredibly positive, >25% raise"
wfh_feel 2 "Strongly positive, 15-25% raise"
wfh_feel 3 "Positive, <15% raise "
wfh_feel 4 "Neutral"
wfh_feel 5 "Negative, <15% paycut"
wfh_feel 6 "Strongly negative, 15-25% paycut"
wfh_feel 7 "Incredibly negative, >25% paycut"
wfh_feel_detailed 1 "More than 35% raise"
wfh_feel_detailed 2 "25 to 35% raise"
wfh_feel_detailed 3 "15 to 25% raise"
wfh_feel_detailed 4 "10 to 15% raise"
wfh_feel_detailed 5 "5 to 10% raise"
wfh_feel_detailed 6 "Less than 5% raise"
wfh_feel_detailed 7 "Neutral"
wfh_feel_detailed 8 "Less than 5% pay cut"
wfh_feel_detailed 9 "5 to 10% pay cut"
wfh_feel_detailed 10 "10 to 15% pay cut"
wfh_feel_detailed 11 "15 to 25% pay cut"
wfh_feel_detailed 12 "25 to 35% pay cut"
wfh_feel_detailed 13 "More than 35% pay cut"
wfh_feel_legacy 1 "Incredibly positive, >20% raise"
wfh_feel_legacy 2 "Strongly Positive, 10-20%+ raise"
wfh_feel_legacy 3 "Moderately Positive, <10% raise "
wfh_feel_legacy 4 "Neutral"
wfh_feel_legacy 5 "Moderately Negative, <10% paycut"
wfh_feel_legacy 6 "Strongly Negative, 10-20% paycut"
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wfh_feel_legacy 7 "Incredibly Negative, >20% paycut"
§ Efficiency while working from home. Note: wfh_eff_COVID_legacy is based on a question
asked prior to August 2020. wfh_eff_COVID is based on a question asked from August 2020.
The numerical variable wfh_eff_COVID_quant uses data from both questions
wfh_eff 1 "Much more, >35% "
wfh_eff 2 "Substantially more, 15-25% "
wfh_eff 3 "More, <15% "
wfh_eff 4 "About the same"
wfh_eff 5 "Less, <15%"
wfh_eff 6 "Substantially less, 15-25%"
wfh_eff 7 "Much less, >35%"
wfh_eff_COVID_legacy 1 "Better"
wfh_eff_COVID_legacy 2 "About the same"
wfh_eff_COVID_legacy 3 "Slightly lower -- 5 to
15%"
wfh_eff_COVID_legacy 4 "Somewhat lower -- 20 to 40%"
wfh_eff_COVID_legacy 5 "Much lower -- >40%"
§ Goods vs.services industries
goodservices 1 "Goods"
goodservices 2 "Services"
§ Red vs blue states (based on Cook Political Report's Partisan Voting Index using the
2012/2016 elections)
redblue 1 "Red (Republican-leaning)"
redblue 2 "Blue (Democratic-leaning)"
§ Return to pre-COVID activities. The labels below also apply to the variable
`habitsrev_postCOVID’ that presents the response options in reverse order but are coded
the same as the original variable.
habits_postCOVID 1 "Completely"
habits_postCOVID 2 "Substantially"
habits_postCOVID 3 "Partially"
habits_postCOVID 4 "None"
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§ Living with other adults?
live_adults 1 "No"
live_adults 2 "Yes, partner/adult children"
live_adults 3 "Yes, roommates/other"
§ Living with children?
live_children 1
"No"
live_children 2 "Yes, youngest in pre-/primary"
live_children 3 "Yes, youngest in ES "
live_children 4 "Yes, youngest is in MS"
live_children 5 "Yes, youngest is in HS"
§ Occupation
occupation 1 "Armed Forces",
occupation 2 "Construction and Extraction"
occupation 3 "Farming, Fishing and Forestry"
occupation 4 "Installation, Maintenance and Repair"
occupation 5 "Management, Business and Financial"
occupation 6 "Office and Administrative Support"
occupation 7 "Production"
occupation 8 "Professional and related"
occupation 9 "Sales and related" occupation
10 "Service"
occupation 11 "Transportation and material moving"
occupation 12 "Other"
Note: The occupation variable likely has significant measurement error as is. Starting with
the May 5, 2022 data release we include a variable called “occupation_clean” that we
believe is higher quality. We recommend users of our data to either use “occupation_clean”
or clean the legacy “occupation” variable substantially before using it in any analysis.
Some potential reasons of concern with the legacy “occupation” variable:
First, respondents from the general population are not likely to be familiar with
occupational classifications and so may struggle classifying themselves. A significant
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proportion choose “Other” when one of the other categories does not immediately seem
right. Users of this variable may want to go through each of the user-provided descriptions
in the variable “occupation_other” (see variable description above) and reclassify them.
This process is what we’ve done to obtain the new variable “occupation_clean.”
Second, due to a survey setup error, the September 2020 to March 2021 waves
mistakenly did not include “Installation, Maintenance and Repair” as a possible response,
so there are no responses in that category in those waves. Many of these will likely show
up in “Other” and will need to be reclassified.
§ Race/ethnicity
race_ethnicity 1 "Black or African American"
race_ethnicity 2 "Hispanic (of any race)"
race_ethnicity 3 "Asian"
race_ethnicity 4 "Native American or Alaska Native"
race_ethnicity 5 "Native Hawaiian or Pacific Islander"
race_ethnicity 6 "White (non-Hispanic)"
race_ethnicity 7 "Other"
Note: We do not reweight our raw data based on race and ethnicity, so our provided survey
weights may not be particularly well-suited to analyze disparities across racial and ethnic
groups. There is also no guarantee that individuals who participate in our survey and report
belonging to a minority group are representative of that minority, even after reweighting to
match the CPS along sex-age-education-earnings categories.
§ Race/ethnicity (simplified)
race_ethnicity_s 1 "Black or African American"
race_ethnicity_s 2 "Hispanic (of any race)"
race_ethnicity_s 3 "Other"
race_ethnicity_s 4 "White (non-Hispanic)"
Note: We do not reweight our raw data based on race and ethnicity, so our provided survey
weights may not be particularly well-suited to analyze disparities across racial and ethnic
groups. There is also no guarantee that individuals who participate in our survey and report
belonging to a minority group are representative of that minority, even after reweighting to
match the CPS along sex-age-education-earnings categories.
§ Is time saved by not commuting part of your extra efficiency when working from home?
wfh_extraeff_comm_qual 1 “Yes”
wfh_extraeff_comm_qual 2 “No”
§ Assuming it doesn’t matter for your pay, which working arrangements would you prefer after
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COVID is under control?
wfh_feel_new_qual 1 "Prefer 5 days/wk on employer premises"
wfh_feel_new_qual 2 "Prefer 2 days/wk WFH"
wfh_feel_new_qual 3 "About the same"
§ Does or will your employer require you to be vaccinated to work on business premises?
vaccine_req_boss 1 “Yes”
vaccine_req_boss 2 “No”
vaccine_req_boss 3 “Employer has not announced a policy”
§ Should employers require vaccination before letting workers return to th eemployer’s
worksite?
vaccine_req_should_gen 1 “Yes, for all”
vaccine_req_should_gen 2 “Yes, except w/ medical exemptions”
vaccine_req_should_gen 3 “Yes, when the job involves proximity to others”
vaccine_req_should_gen 4 “No, but they should encourage workers”
vaccine_req_should_gen 5 “No, workers should decide on their own”
§ Should your employer require vaccination before letting you and your co-workers return to
the worksite?
vaccine_req_should_myboss 1 “Yes, for all”
vaccine_req_should_myboss 2 “Yes, except w/ medical exemptions”
vaccine_req_should_myboss 3 “Yes, when the job involves proximity to others”
vaccine_req_should_myboss 4 “No, but they should encourage workers”
vaccine_req_should_myboss 5 “No, workers should decide on their own”
§ If you were to work from home one more day per week than your co-workers, how might
this affect your chance of a promotion in the next 3 years?
prom_eff_1day_qual 1 "It would reduce my chance of a promotion"
prom_eff_1day_qual 2 "No effect"
prom_eff_1day_qual 3 "It would increase my chance of a promotion"
§ If you were to work from home 5+ days a week and your co-workers work on the business
premises 5+ days a week, how might this affect your chance of a promotion in the next 3
years?
prom_eff_5day_qual 1 "It would reduce my chance of a promotion"
prom_eff_5day_qual 2 "No effect"
prom_eff_5day_qual 3 "It would increase my chance of a promotion"
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§ Do you need to be physically present on business premises to perform your job (current or
most recent)?
wfh_able_qual_May 1 "Yes, for all of my job"
wfh_able_qual_May 2 "Yes, for part of my job"
wfh_able_qual_May 3 "No"
§ For unemployed respondents:
You stated that you are currently (un)employed (looking for work or awaiting recall to
your old job).
Suppose you got a new job offer.
For a given pay, would you be more or less likely to take the job if it allowed you to
work from home [ 1 / 2 to 3 / 4 to 5] day[s] a week?
For employed respondents:
You stated that you are currently employed.
Suppose you got an offer for a new job with the same pay as your current job.
Would you be more or less likely to take the new job if it let you work from home [ 1 / 2
to 3 / 4 to 5/ day[s] a week?
offer 1 "More likely to consider"
offer 2 "No effect"
offer 3 "Less likely to consider"
§ How does the efficiency of video calls for [ one-on-one and small / medium sized / large ]
group meetings (up to 4 people) compare to the efficiency of in-person meetings?
videocall 1 "Hugely better - 50+% more eff."
videocall 2 "Substantially better - 20-50% more eff."
videocall 3 "Better - up to 20+ more eff."
videocall 4 "About the same"
videocall 5 "Worse - up to 20% less eff."
videocall 6 "Substantially worse - 20-50% less
eff." videocall 7 "Hugely worse - 50+% less eff"
videocall 8 "Not applicable - no work video calls"
§ How would you respond if your employer announced that all employees must return to
worksite 5+ days a week starting on August 1, 2021?
wbp_react_qual 1 "Comply and return"
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wbp_react_qual 2 "Return & start looking for a WFH job"
wbp_react_qual 3 "Quit, regardless of getting another job"
§ How much would your efficiency working from home increase if you had perfect high-speed
internet?"
wfh_able_intcount 1 "None, my internet is fast enough"
wfh_able_intcount 2 "A little, about 5% increase", add
wfh_able_intcount 3 "Somewhat, about 10% increase", add
wfh_able_intcount 4 "Substantially, about 20% increase", add
wfh_able_intcount 5 "Massively, 30% or more", add
label values wfh_able_intcount wfh_able_intcount
§ What plans does your employer have for working arrangements of full-time employees after
COVID, in 2022 or later?
employer_arr_qual 1 "Fully on-site"
employer_arr_qual 2 "Hybrid: 1 to 4 days WFH"
employer_arr_qual 3 "Fully remote"
employer_arr_qual 4 "No clear plans from employer"
employer_arr_qual 5 "Other"
§ Who decides which days and how many days employees work remotely?
who_decides_wfhdays 1 "Each employee"
who_decides_wfhdays 2 "Each team"
who_decides_wfhdays 3 "Company-wide common schedule"
who_decides_wfhdays 4 "Company-wide varying schedule"
who_decides_wfhdays 5 "No clear plans from employer"
who_decides_wfhdays 6 "Other"
§ When does your employer anticipate that most of their full-time employees will return to
working one or more days per week on business premises?
employer_return_when 1 "Already back"
employer_return_when 2 "July 2021"
employer_return_when 3 "August 2021"
employer_return_when 4 "September 2021"
employer_return_when 5 "2021Q4"
employer_return_when 6 "2022Q1"
employer_return_when 7 "2022Q2 or later"
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§ After COVID, in 2022 and later, how many days a week will that typical employee work on
business premises?
wfh_days_postCOVID_boss_ty labels are similar to wfh_days_postCOVID_boss
wfh_days_postCOVID_boss_ty_ss labels are similar to wfh_days_postCOVID_boss_ss
Note: neither wfh_days_postCOVID_boss_ty_ss or wfh_days_postCOVID_boss_ty_ss
take a value of 9 (corresponding to “No employer”) because non-employed respondents
did not see the underlying question.
§ Which of the following would you prefer? a) Being able to choose which days you work from
home (if any) b) Your employer sets a policy...
choice_prefer 1 "I choose which days to WFH (if any)"
choice_prefer 2 "My employer sets a policy on WFH days"
§ When you return to work in person, and you are introduced to somebody will you...? AND
Before COVID (in 2019), when you were introduced to somebody at work what did you do?
AND Currently, when you are introduced to somebody at work, what do you do?
handshake 1 "Shake hands"
handshake 2 "Fist bump"
handshake 3 "Elbow bump"
handshake 4 "Not touch (verbally greet)"
handshake 5 "Other"
§ How much do you enjoy your personal interactions with coworkers at your employer's
worksite? AND How much do you enjoy your personal interactions with customers, clients,
or patients at your employer's worksite?
interactions 0 "0 - not at all"
interactions 1 "1"
interactions 2 "2"
interactions 3 "3"
interactions 4 "4"
interactions 5 "5"
interactions 6 "6"
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interactions 7 "7"
interactions 8 "8"
interactions 9 "9"
interactions 10 "10 - very much"
interactions 11 "N/A"
§ How does your efficiency working from home during the COVID-19 pandemic compare to
your efficiency working on business premises before the pandemic? – categorical AND How
does your efficiency working from home compare to your efficiency working on business
premises? – categorical
wfh_eff_COVID_qual 1 “Better”
wfh_eff_COVID_qual 2 “About the same”
wfh_eff_COVID_qual 3 “Worse”
§ In the last six months, has your employer announced new plans about working from home
after the pandemic ends, in 2022 or later? – categorical
wfh_postCOVID_boss_ann 1 "No"
wfh_postCOVID_boss_ann 2 "Yes"
§ Currently (this week) what is your work status? - categorical version of the question asked
since November 2020.
workstatus_current_new 1 "Working for pay" workstatus_current_new
2 "Employed and paid, but not working" workstatus_current_new 3
"Unemployed, searching" workstatus_current_new 4 "Unemployed,
awaiting recall" workstatus_current_new 5 "Out of the labor force"
§ Counting all locations where your primary employer operates, what is the total number of
persons who work for your employer?
employer_sizecat 1 “1 to 9 staff”
employer_sizecat 2 "10 to 49 staff"
employer_sizecat 3 "50 to 99 staff"
employer_sizecat 4 "100 to 499 staff"
employer_sizecat 5 "500+ staff"
§ Excluding yourself but including employees and independent contractors, how many staff
members are part of your business?
ownbusiness_sizecat 1 "0 staff"
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ownbusiness_sizecat 2 "1 to 9 staff"
ownbusiness_sizecat 3 "10 to 49 staff"
ownbusiness_sizecat 4 "50 to 99 staff"
ownbusiness_sizecat 5 "100+ staff"
§ Which of the following best describes your current employment situation?
self_employed 1 "Wage/salary employee - primarily"
self_employed 2 "Wage/salary employee - side jobs"
self_employed 3 "Self employed - own business"
self_employed 4 "Independent contractor/ gig worker"
§ Do you have a health problem or a disability which prevents work or which limits the kind
or amount of work you do?
disability_qual 1 "Yes"
disability_qual 2 "No"
disability_qual 3 "Prefer not to answer"
§ Will your manager work from home on the same days as you after the pandemic is over?
boss_wfh_samedays 1 "Yes"
boss_wfh_samedays 2 "No"
boss_wfh_samedays 3 "No manager"
§ Will most of your coworkers work from home on the same days as you after the pandemic is
over?
coworkers_wfh_samedays 1 "Yes"
coworkers_wfh_samedays 2 "No"
§ If your manager starts coming into your employer's place of business on some of your workfrom-home days, what will you do?
boss_wfh_unravel 1 "Keep WFH those days"
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boss_wfh_unravel 2 "Work on premises some of those days"
boss_wfh_unravel 3 "Work on premises whenever my manager does"
§ If your coworkers start coming into your employer's place of business on some of your workfrom-home days, what will you do?
coworkers_wfh_unravel 1 "Keep WFH those days"
coworkers_wfh_unravel 2 "Work on premises some of those days"
coworkers_wfh_unravel 3 "Work on premises whenever my coworkers do"
§ Before COVID how did you typically commute to work?
(detailed) commutemode 1 "Car"
commutemode 2 "Subway"
commutemode 3 "Train"
commutemode 4 "Bus"
commutemode 5 "Walk"
commutemode 6 "Bicyle"
commutemode 7 "Taxi/Ride-share"
§ Before COVID how did you typically commute to work? (simplified
version) commutemode_s 1 "Car"
commutemode_s 2 "Subway/Train/Bus/Taxi/Rideshare"
commutemode_s 3 "Walk/Bicycle"
§ On a scale of 0 to 10, how anxious are you about returning to work on business premises?
wbp_return_anxious 0 "0 - not at all"
wbp_return_anxious 1 "1"
wbp_return_anxious 2 "2"
wbp_return_anxious 3 "3"
wbp_return_anxious 4 "4"
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wbp_return_anxious 5 "5"
wbp_return_anxious 6 "6"
wbp_return_anxious 7 "7"
wbp_return_anxious 8 "8"
wbp_return_anxious 9 "9"
wbp_return_anxious 10 "10 - very much"
wbp_return_anxious 11 "N/A"
§ Have you quit or voluntarily left a job in the past 6 months?
quit_qual 1 "Yes"
quit qual 2 "No"
§ On a scale of 0 to 10, how much do you agree with the following statement? "While working
from home I am less stressed because I don't feel like I am constantly under supervision."
wfh_less_stress 1 "1"
wfh_less_stress 2 "2"
wfh_less_stress 3 "3"
wfh_less_stress 4 "4"
wfh_less_stress 5 "5"
wfh_less_stress 6 "6"
wfh_less_stress 7 "7"
wfh_less_stress 8 "8"
wfh_less_stress 9 "9"
wfh_less_stress 10 "10 - very much"
wfh_less_stress 11 "N/A"
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§ In 2019 (before COVID), when you traveled to your employer's worksite, approximately what
time did you leave for work (e.g. 8:30am)? AND Currently, when you traveled to your
employer's worksite, approximately what time did you leave for work (e.g. 8:30am)?
leavetime 1 "Before 6:00am"
leavetime 2 "6:00am"
leavetime 3 "6:30am"
leavetime 4 "7:00am"
leavetime 5 "7:30am"
leavetime 6 "8:00am"
leavetime 7 "8:30am"
leavetime 8 "9:00am"
leavetime 9 "9:30am"
leavetime 10 "10:00am"
leavetime 11 "10:30am"
leavetime 12 "After 10:30am"
§ Do you currently have the option to work at more than one employer worksite?
worksite_option 1 "Yes"
worksite_option 2 "No"
§ Why can't you work remotely 100% of the time? nonremotable_why
1 "In-person meetings w/ clients/customers" nonremotable_why 2
"Collaborate in-person w/ colleagues" nonremotable_why 3
"Interact physically w/ equipment" nonremotable_why 4 "Other"
Note: In December 2021 we moved to allowing for multiple answers in the underlying
survey question so starting with that month there are individual binary variables for each
option.
§ If your employer requires you to work on premises 3 days a week, which would you prefer?
choice_dow_prefer 1 "Each person chooses which 3 days"
choice_dow_prefer 2 "Employer sets the same 3 days for all"
§ In 2022 and later, will your employer allow you to work from anywhere (e.g. from Hawaii
without the expectation of coming into work) for one month each year?
wfanywhere 1 "Yes"
wfanywhere 2 "No"
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§ For each day last week, did you work a full day (6 or more hours), and if so where (i.e. from
home, on employer or client premises)?
workstatus_days 1 "Did not work"
workstatus_days 2 "Worked from home"
workstatus_days 3 "Worked on employer or client premises"
Note: These labels apply to the following variables: workstatus_monday,
workstatus_tuesday, workstatus_wednesday, workstatus_thursday, workstatus_friday,
workstatus_saturday, workstatus_Sunday
§ What color is grass? The fresh, uncut grass, not leaves or hay. Make sure that you select
purple as an answer so we know you are paying attention.
grass_color_attnfull 1 "Magenta"
grass_color_attnfull 2 "Green"
grass_color_attnfull 3 "Purple"
grass_color_attnfull 4 "Blue"
grass_color_attnfull 5 "Black"
grass_color_attnfull 6 "White"
grass_color_attnfull 7 "Brown"Who sets your work-from-home schedule?
who_sets_wfhsched 1 "Self" who_sets_wfhsched 2 "Manager or employer"
who_sets_wfhsched 3 "No employer policy"
§ What type of work-from-home schedule does your manager or employer set?
common_varying_sched 1 "Common schedule"
common_varying_sched 2 "Varying schedule"
§ How often do you work from home to handle matters that require your presence (e.g., to be
there for a plumber, a repair person, or deliveries)?
wfh_handle_chores 1 "Once per week or more"
wfh_handle_chores 2 "Once or twice a month"
wfh_handle_chores 3 "Rarely or never"
§ Which of the following would you do each morning when you travel to work? Shower/bathe,
Brush teeth, Use deodorant, Put on makeup, Shave, Wear fresh clothes, Set an alarm to wake
up
groom_tasks 0 "No"
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groom_tasks 100 "Yes"
Note: The labels above apply to variables formed by one of the following stems
showerbathe, brushteeth deodorant makeup shave freshclothes alarm
and one of the following suffixes
_wfh, _wbp
§ What is your primary transportation mode for commuting to the friend or family member's
home/public space (cafe, library etc.)/co-working space where you usually work?
commuting_modes_new 1 "Drive alone"
commuting_modes_new 2 "Carpool"
commuting_modes_new 3 "Public transit"
commuting_modes_new 4 "Bicycle"
commuting_modes_new 5 "Walk"
commuting_modes_new 6 "Taxi/Ridehailing"
commuting_modes_new 7 "NA"
Note: The labels above apply to any of the following variables: commute_mode_ faf,
commute_mode_ cowork, commute_mode_ public
§ Generally speaking, do you usually think of yourself as a Republican, Democrat,
Independent, or what?
party_affiliation 1 "Strong Democrat"
party_affiliation 2 "Not very strong Democrat"
party_affiliation 3 "Independent close to Democrat"
party_affiliation 4 "Independent (Neither party)"
party_affiliation 5 "Independent, close to Republican"
party_affiliation 6 "Not very strong Republican"
party_affiliation 7 "Strong Republican"
party_affiliation 8 "Other party"
party_affiliation 9 "Don't know or rather not say'"
party_affiliation_s 1 "Democrat"
party_affiliation_s 2 "Independent/Other"
party_affiliation_s 3 "Republican"
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§ Which of the following best describes your job search (with respect to WFH)?
labsearch_qual 1 "Only considering WFH jobs"
labsearch_qual 2 "Prefer jobs allowing WFH"
labsearch_qual 3 "No preference about WFH"
§ Are worries about catching COVID or other infectious diseases a factor in your decision not
to seek work at this time?"
infection_lfp 1 "Yes, the main reason"
infection_lfp 2 "Yes a secondary reason"
infection_lfp 3 "No"
§ Would you start seeking work if you were guaranteed to find a job allowing you to work from
home?
wfh_lfp 1 "Yes, definitely"
wfh_lfp 2 "Yes, possibly"
wfh_lfp 3 "No"
§ Would you like your co-workers to come into work on the same days as you?
coworkers_samedays_pref 1 "Yes"
coworkers_samedays_pref 2 "No"
§ Which of the following would make your job more efficient? AND Which of the following
would you prefer?
- Coworkers coordinate to come in
- Each coworker decides when to come in
- No difference
Applies to wfh_coordinate_eff AND wfh_coordinate_pref
1 "Coworkers coordinate to come in"
2 "Each coworker decides when to come in"
3 "No difference"
§ When you are working on your employer's premises, how would you like to hold small
meetings with your coworkers?
wbp_smallmeet_pref 1 "In person"
wbp_smallmeet_pref 2 "Video call"
wbp_smallmeet_pref 3 "No preference"
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§ How frequently do you use the following modes of transportation for non-work trips (e.g.
shopping, socializing, recreation)?
freq_nonwork_transport 1 "5+ times per week"
freq_nonwork_transport 2 "2 to 4 times per week"
freq_nonwork_transport 3 "Once per week"
freq_nonwork_transport 4 "Rarely or never"
Note: These labels apply to all of: freq_nonwork_car, freq_nonwork_taxi,
freq_nonwork_transit, freq_nonwork_bike, freq_nonwork_walk
§ Current working status - detailed question from prior to November 2020
workstatus_current_d 1 "Working on my business premises"
workstatus_current_d 2 "Working from home", add
workstatus_current_d 3 "Employed & paid, but not working", add
workstatus_current_d 4 "Unemployed", add
workstatus_current_d 5 "Not working or looking for work", add
§ If your employer said you need to come to work in person two days a week, which would
you prefer?
forcedchoice 1 "Come in T/Th with all coworkers"
forcedchoice 2 "Choose which days - no coordination"
§ Has working from home made it easier or harder to interview for prospective new jobs?
interviewing 1 "Easier"
interviewing 2 "Harder"
interviewing 3 "No difference"
interviewing 4 "I haven't been seeking a new job"
§ What type of facility best describes where you work (or worked in your most recent job)?
work_facility 1 "Office"
work_facility 2 "Factory/warehouse"
work_facility 3 "Retail/entertainment"
work_facility 4 "Food/accommodation"
work_facility 5 "Construction/agriculture/mining"
work_facility 6 "School/university"
work_facility 7 "Hospital/healthcare"
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§ In the past week, how often did you wear a face mask in the following situations?
masking 1 "Never/Rarely"
masking 2 "Ocassionally"
masking 3 "Mostly"
masking 4 "Always"
masking 5 "Not relevant for me"
Note: These labels apply to the following variables: mask_indoorsatwork,
mask_outdoorsleisure, mask_whendriving, mask_home, mask_indoorsleisure
§ Are you already following your employer's plan for post-COVID working
arrangements? boss_plan_implement 1 "Yes"
boss_plan_implement 2 "No, some/all is not yet implemented"
§ Last week, did you come into work as many days as your employer wanted you to come in?
employer_days_meet 1 "Yes"
employer_days_meet 2 "No"
§ How has your employer responded to employees who work on business premises fewer days
than requested?
fewerdays_punishment 1 "Nothing" fewerdays_punishment
2 "Verbal reprimand" fewerdays_punishment 3 "Negative
performance review" fewerdays_punishment 4 "Reduction
in pay/bonus" fewerdays_punishment 5 "Threat to
terminate" fewerdays_punishment 6 "Termination"
fewerdays_punishment 7 "Other"
fewerdays_punishment 8 "Don't know"
§ During a typical workday, how many coworkers, customers, and clients do you engage in
person or by video?
npeople_engage_work_cat 1 "None"
npeople_engage_work_cat 2 "1 to 10"
npeople_engage_work_cat 3 "11 to 50"
npeople_engage_work_cat 4 "51 to 100"
npeople_engage_work_cat 5 "101 to 500"
npeople_engage_work_cat 6 "500 or more"
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§ What is your main reason for not working for pay or profit?
nilf_mainreason_HPS_clean 1 "Don't want to be employed"
nilf_mainreason_HPS_clean 2 "Sick/caring for someone w/
COVID"
nilf_mainreason_HPS_clean 3 "Caring for children"
nilf_mainreason_HPS_clean 4 "Caring for elderly person"
nilf_mainreason_HPS_clean 5 "Concern about catching/spreading
COVID" nilf_mainreason_HPS_clean 6 "Sick/disabled but not w/
COVID" nilf_mainreason_HPS_clean 7 "Retired"
nilf_mainreason_HPS_clean 8 "Laid off/furloughed due to COVID pandemic"
nilf_mainreason_HPS_clean 9 "Employer out of business b/c of COVID pandemic"
nilf_mainreason_HPS_clean 10 "No transportation to work"
nilf_mainreason_HPS_clean 11 "Other reason"
§ The following labels apply to the big-5 questions:
big5 1 "Very inaccurate"
big5 2 "Moderately inaccurate"
big5 3 "Neither accurate nor inaccurate"
big5 4 "moderately accurate"
big5 5 "Very accurate"
§ I am willing to work harder than I have to in order to help the firm or organization I work for
succeed.
work_firm_succeed 1 "Strongly agree"
work_firm_succeed 2 "Agree"
work_firm_succeed 3 "Neither agree nor disagree"
work_firm_succeed 4 "Disagree"
work_firm_succeed 5 "Strongly disagree"
§ The randomized order of response options shown to a given respondents is given by a
numeric code corresponding to the options as listed for the main variable. For example, a
response order of “123” means the respondent in question saw the response options in the
order in which they appear in the labels. For example, for the variable `infection_lfp’ a
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response order of “123” means the respondent saw “Yes, the main reason” as the top option,
“Yes, a secondary reason” as the second option, and “No” as the bottom option. A response order
of “321” would have meant the reverse order. This pattern applies to the following ordering
variables starting with the October 5, 2022 data release:
`jobsearch_changes_order', `jobsearch_wfh_order', `notlooking_reasons_order',
`start_looking_order', `wfh_eff_noCOVID_order'.
§ Have you given birth to any children in 2015 or later? AND Are you the biological father
of any children born in 2015 or later?
female_fertility_qual AND male_fertility_qual 1 “Yes”
female_fertility_qual AND male_fertility_qual 2 “No”
§ Which of the following have factored into your decision whether to have children?
Note: The labels below apply to all variables called “children_des_*”.
children_des_* 1 "Lowered"
children_des_* 2 "Not a factor"
children_des_* 3 "Increased"
§ Do you directly manage or supervise other employees in your organization?
manage_employees 1 "Yes"
manage_employees 2 "No" manage_employees
3 "Yes, but only rarely"
§ During X person work meetings on video-conferencing platforms, how often do you/others
have your/their camera on?
Note: The labels below apply to all variables called “mycamera_on_*” or
“othcamera_on_*” corresponding to own and others’ camera status and a range of
meeting sizes.
camera_freq 1 "Always (>90% of time)"
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camera_freq 2 "Mostly (70 - 90% of time)"
camera_freq 3 "Sometimes (40 - 60% of time)"
camera_freq 4 "Occasionaly (10 - 30% of time)"
camera_freq 5 "Never" camera_freq
6 "Does not apply"
§ During X person work meetings on video-conferencing platforms, how does having
your/others' camera on (showing your face) impact your/their engagement?
Note: The labels below apply to all variables called “mycamera_eff_*” or
“othcamera_eff_*” corresponding to own and others’ camera status and the effect on
engagement.
camera_eff 1 "Very positively (up >50%)"
camera_eff 2 "Positively (up 10 - 40%)"
camera_eff 3 "No impact"
camera_eff 4 "Negatively (down 10 - 40%)"
camera_eff 5 "Very negatively (down >50%)"
camera_eff 6 "Does not apply"
§ Last random_day_of_week which of the following did you do?
Note: `random_day_of_week’, the variable containing the random day of the week that
the respondent was asked about, is itself a string variable that can be encoded to make it
into a categorical variable.
work_random_dow 1 "Worked from home"
work_random_dow 2 "Worked on premises"
work_random_dow 3 "Did not work"
§ The following items are about activities you might do during a typical day. Does your health
currently limit you in these activities?
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Note: The value labels below apply to all of the variables encoding responses to the
limitation question, namely:
limit 1 "Limited a lot"
limit 2 "Not limited at
all" limit 3 "Limited a
little"
§ Are there children under 18 living in your
household? children_household_yesno 1 "No"
children_household_yesno 2 "Yes, 1 child"
children_household_yesno 3 "Yes, 2 children"
children_household_yesno 4 "Yes, 3 children"
children_household_yesno 5 "Yes, 4 or more children"
§ Have you had a positive diagnosis for COVID19? covid_test_positive 1 "Yes, I tested
positive" covid_test_positive 2 "No"
covid_test_positive 3 "Prefer not to say"
§ Despite not testing positive, do you believe you have had COVID19? covid_believe_positive 1 "Yes"
covid_believe_positive 2 "No"
covid_believe_positive 3 "Unsure"
§ Despite not testing positive, do you believe you have had COVID-19? Have any close
friends or family members experienced COVID symptoms lasting 3 months or longer?
AND Do you live with or care for someone who would be more vulnerable than the
general population to COVID or other infectious diseases?
covid_close 1 "Yes"
covid_close 2 "No"
covid_close 3 "Don't know/Prefer not to say"
Note: These value labels apply to both of the following variables:
“covid_long_close_qual”, “covid_vuln_care_qual”
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§ Do you ever meet with your coworkers in person?
ever_meet_coworkers 1 "Never"
ever_meet_coworkers 2 "About once per year"
ever_meet_coworkers 3 "Once per quarter"
ever_meet_coworkers 4 "Once per month"
ever_meet_coworkers 5 "Twice or more per month"
ever_meet_coworkers 6 "I don't have any
coworkers"
§ When you do meet your coworkers, for how long do you
meet? long_meet_coworkers 1 "A few hours"
long_meet_coworkers 2 "One day"
long_meet_coworkers 3 "Multiple days"
long_meet_coworkers 4 "One workweek or more"
§ In your current job, how often do you use each of these work-related communications?
workcomm_freq 1 "Hourly"
workcomm_freq 2 "Daily"
workcomm_freq 3 "Weekly"
workcomm_freq 4 "Once or twice per month"
Note: These value labels apply to each of the variables whose name starts with
“workcomm_freq_”
§ In your current job, how often do you overlook work-related communications on each
of the following?
overlook 1 "Often, 1+ times per week"
overlook 2 "Sometimes, 1 or 2 times per month"
overlook 3 "Rarely or never"
Note: These value labels apply to each of the variables whose name starts with “overlook_”
§ In your current job, do you respond to work-related communications after hours or on
weekends on any of the following?
afterhours 1 "Daily"
afterhours 2 "Weekly"
afterhours 3 "Monthly"
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afterhours 4 "Once or twice per year"
afterhours 5 "Never"
Note: These value labels apply to each of the variables whose name starts with
“afterhours_”
§ Last random day of week which of the following did you do? [Detailed version
where respondents can give the location of work away from premises]
work_random_dow_d 1 "Worked from home"
work_random_dow_d 2 "Worked on premises"
work_random_dow_d 3 "Worked at a co-working space"
work_random_dow_d 4 "Worked at a public space (e.g. cafe)"
work_random_dow_d 5 "Worked at a friend/family member's home"
work_random_dow_d 6 "Did not work"
§ Were you feeling sick, ill, or injured on any days last week?
sick_lastweek_qual 1 "Yes"
sick_lastweek_qual 2 "No"
§ Usual days Worked Per Week –
categorical usual_days_perweek 1 "1
day per week"
usual_days_perweek 2 "2 day per week"
usual_days_perweek 3 "3 day per week"
usual_days_perweek 4 "4 day per week"
usual_days_perweek 5 "5+ day per week"
§ How would you feel about compressing your workweek into 4 days, while [continuing
to work the same number of hours] OR [doing the same amount of work] over the
week?
The label below applies to `compress_feel_hoursconst’ and `compress_feel_workconst’:
compress_feel 1 "I would like to compress my workweek"
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compress_feel 2 "No preference"
compress_feel 3 "I would not like to compress my workweek"
The label below applies to `compress_feel_hoursconst_qual’ and
`compress_feel_workconst_qual’:
compress_feel_qual -5 ">15% pay cut"
compress_feel_qual -4 "11 to 15% pay cut"
compress_feel_qual -3 "6 to 10% pay cut"
compress_feel_qual -2 "3 to 5% pay cut"
compress_feel_qual -1 "1 to 2% pay cut"
compress_feel_qual 0 "Indifferent"
compress_feel_qual 1 "1 to 2% pay raise"
compress_feel_qual 2 "3 to 5% pay raise"
compress_feel_qual 3 "6 to 10% pay raise"
compress_feel_qual 4 "11 to 15% pay raise"
compress_feel_qual 5 ">15% pay raise"
§ Which do you prefer: working 4-days per week for 10 hours or 5 day per week for 8
hours? prefer_4d10h_5d8h 1 "Work 4 days/week for 10 hours/day"
prefer_4d10h_5d8h 2 "Work 5 days/week for 8 hours/day"
§ In the past 12 months, has your manager spoken to you about shifting to a 4-
day workweek?
manager_4day_shift 1 "Yes"
manager_4day_shift 2 "No"
§ Counting all of its locations, how many employees work for your primary
employer? employer_emp_cat 1 "Fewer than 10"
employer_emp_cat 2 "10 to 49"
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employer_emp_cat 3 "50 to 99"
employer_emp_cat 4 "100 to 499"
employer_emp_cat 5 "500 to 4999"
employer_emp_cat 6 "5000+"
§ As a fully remote employee, does your pay depend on where you
live? fullremote_payvary 1 "Yes, by location"
fullremote_payvary 2 "No, same pay across the US"
§ Last week, when you felt sick/ill/injured were you: sick/ill contagious, sick/ill
NOT contagious, or injured?
sick_lastweek_type 1 "Sick/ill: potentially
contagious" sick_lastweek_type 2 "Sick/ill: NOT
contagious"
sick_lastweek_type 3 "Injured"
§ Have you ever been on two video calls at the same
time? two_video_calls 1 "No"
two_video_calls 2 "Yes, once"
two_video_calls 3 "Yes, 2 to 5 times"
two_video_calls 4 "Yes, 6 or more times"
§ How often do you talk to or text your family or friends while on a work call
on Zoom/Teams/Webex or similar?
talktext_during_calls 1 "Never"
talktext_during_calls 2 "Rarely, for
emergencies" talktext_during_calls 3 "Once per
month" talktext_during_calls 4 "Once per
week" talktext_during_calls 5 "Daily"
§ When you are on work calls on Zoom/Teams/Webex what share of the time are you
multi- tasking? – categorical
multitask_during_calls_cat 1 "0 to 20%"
multitask_during_calls_cat 2 "20 to 40%"
multitask_during_calls_cat 3 "40 to 60%"
multitask_during_calls_cat 4 "60 to 80%"
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multitask_during_calls_cat 5 "80 to 100%"
§ How long have you lived in your current
residence? howlong_resi_current 1
"Under 2 months"
howlong_resi_current 2 "2 to 6 months"
howlong_resi_current 3 "7 to 12 months"
howlong_resi_current 4 "1 to 5 years"
howlong_resi_current 5 "Over 5 years"
§ How many times in the past 12 months has your manager spoken to you about shifting to
a 4-day workweek?
manager_4day_recent 1 "This month"
manager_4day_recent 2 "Last month"
manager_4day_recent 3 "2 to 6 months ago"
manager_4day_recent 4 "More than 6 months ago"
§ What was your manager's message when they most recently spoke to you about shifting to
a 4-day workweek?
manager_4day_message 1 "Ruled out"
manager_4day_message 2 "Under consideration"
manager_4day_message 3 "Likely, but not yet planned"
manager_4day_message 4 "Underway with plans in place"
§ How many full-time jobs do you currently have? –
qualitative num_ftjobs 1 "1 job"
num_ftjobs 2 "2 jobs"
num_ftjobs 3 "3 or more jobs"
§ Do any of your employers know you have another full-time
job? commknow_ftjobs 1 "Yes"
commknow_ftjobs 2 "No"
§ At any time LAST WEEK did you telework or work at home for pay? Did you telework
or work at home for pay in February 2020 before the COVID-19 pandemic started? Did
you spend any time LAST WEEK working at home for your job? Did you spend any time
working at home for your job in February 2020 before the COVID-19 pandemic started?
cps_telework 1 "Yes"
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cps_telework 2 "No"
Note: The label above applies for the following variables (corresponding to the four
questions reproduced above): cps_telework23_yesno cps_telework20_yesno
cpsalt_telework23_yesno cpsalt_telework20_yesno
§ LAST WEEK, did you do more, less, or the same amount of telework or work at home
for pay as in February 2020 (before the COVID-19 pandemic)? LAST WEEK did
you do more, less or the same amount of work at home for your job as in February 2020
(before the COVID-19 pandemic)?
cps_moreless_telework 1 "More"
cps_moreless_telework 2 "Less"
cps_moreless_telework 3 "About the same"
Note: The label above applies for the following variables (corresponding to the two
questions reproduced above): cps_telework20_moreless
cpsalt_telework20_moreless
§ If you worked 5 days/week, how many WFH days/week would be best for your
physical [mental] health?
wfh_ideal 1 "0 days (fully in person)"
wfh_ideal 2 "1 day"
wfh_ideal 3 "2 days"
wfh_ideal 4 "3 days"
wfh_ideal 5 "4 days"
wfh_ideal 6 "5 days (fully remote)"
Note: The above labels pertain to both of the following variables, corresponding
to separate questions about physical and mental health:
wfh_ideal_physical_health wfh_ideal_mental_health
§ What day of the week was your most recent workday before
today? mostrecent_workday_dow 1 "Monday"
mostrecent_workday_dow 2 "Tuesday"
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mostrecent_workday_dow 3 "Wednesday"
mostrecent_workday_dow 4 "Thursday"
mostrecent_workday_dow 5 "Friday"
mostrecent_workday_dow 6 "Saturday"
mostrecent_workday_dow 7 "Sunday"
§ Selected meeting time for follow-up questions
iselected_meeting 1 "First work-related meeting after lunch"
iselected_meeting 2 "First work-related meeting of the day"
iselected_meeting 3 "Last work-related meeting before lunch"
iselected_meeting 4 "Last work-related meeting of the day"
§ How many people (including yourself) participated in
[randomly_selected_meeting]? selected_meeting_modes 1 "All in
person"
selected_meeting_modes 2 "All via video conference"
selected_meeting_modes 3 "Mix of in-person and and remote"
§ In your current job, where do you solve problems faster? In your current job, where do
you learn new things faster? (SIMPLE VERSION)
faster 1 "Working from home"
faster 2 "About the same"
faster 3 "Working on your employer's premises"
Note: The above labels apply to the following variables:
solve_problems_qual learn_things_qual
§ In your current job, where do you solve problems faster? In your current job, where do
you learn new things faster? (DETAILED VERSION)
solve_problems_qual_d 1 "WFH - More than 30% faster"
solve_problems_qual_d 2 "WFH - 20 to 30% faster"
solve_problems_qual_d 3 "WFH - 10 to 20% faster"
solve_problems_qual_d 4 "WFH - 5 to 10% faster"
solve_problems_qual_d 5 "WFH - Under 5% faster"
solve_problems_qual_d 6 "About the Same"
solve_problems_qual_d 7 "Employer premises - Under 5%
faster" solve_problems_qual_d 8 "Employer premises - 5 to 10%
faster"
solve_problems_qual_d 9 "Employer premises - 10 to 20% faster"
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solve_problems_qual_d 10 "Employer premises - 20 to 30% faster"
solve_problems_qual_d 11 "Employer premises - More than 30% faster"
Note: The above labels apply to the following variables:
solve_problems_qual_d learn_things_qual_d
§ Were any of the work-related courses/seminars taught at a college or university?
seminars_college_qual 1 "Yes"
seminars_college_qual 2 "No"
§ How often do you use what you learned [in learning
activity]? useful 1 "Rarely/never"
useful 2 "Once a month"
useful 3 "Once a week"
useful 4 "Daily"
Note: The above labels apply to the following variables:
useful_mentoring useful_training useful_seminars useful_ownlearning
§ More or less hours by [learning activity] comparing 2019 to
now? moreless_activity 1 "More hours"
moreless_activity 2 "About the same"
moreless_activity 3 "Fewer hours"
Note: The above labels apply to the following variables:
moreless_mentoring_2019 moreless_training_2019 moreless_seminars_2019
moreless_ownlearn_2019
§ What is your spouse/domestic partner's current working status?
partner_workstatus_current_d 1 "Working primarily from home"
partner_workstatus_current_d 2 "Working primarily on business
premises" partner_workstatus_current_d 3 "Not working, full-time
student" partner_workstatus_current_d 4 "Not working, other"
§ On your most recent workday did you: WFH the full day or work on
employer/client premises?
186
mostrecent_workday_wfhwbp 1 "Work from home the full day"
mostrecent_workday_wfhwbp 2 "Work on employer or client premises"
§ Was the meeting (selected_meeting_time) scheduled in
advance? selected_meeting_schedadv 1 "No"
selected_meeting_schedadv 2 "Yes, within 1 to 2 days"
selected_meeting_schedadv 3 "Yes, within 1 week"
selected_meeting_schedadv 4 "Yes, more than 1 week before"
§ Did the meeting (selected_meeting_time) have a clear agenda or purpose?
selected_meeting_clearagenda 1 "Yes"
selected_meeting_clearagenda 2 "No"
§ Did you actively participate in the meeting or just listen?
selected_meeting_part_qual 1 "Yes, I led the meeting or gave a presentation"
selected_meeting_part_qual 2 "Yes, I participated in the discussion"
selected_meeting_part_qual 3 "No, I just listened"
§ How valuable was the meeting for you personally?
selected_meeting_val_self l 1 "Complete waste of my
time" selected_meeting_val_self 2 "1% to 19% useful"
selected_meeting_val_self 3 "20% to 49% useful"
selected_meeting_val_self 4 "50 to 79% useful"
selected_meeting_val_self 5 "80 to 100% useful"
§ How valuable do you think the meeting was for other participants?
selected_meeting_val_others 1 "Complete waste of
time" selected_meeting_val_others 2 "1% to 19%
useful"
selected_meeting_val_others 3 "20% to 49% useful"
187
selected_meeting_val_others 4 "50 to 79% useful"
selected_meeting_val_others 5 "80 to 100% useful"
§ How often do you work in an office space?
office_freq 1 "Never"
office_freq 2 "Occasionally - about once a month"
office_freq 3 "Regularly - about once a week"
office_freq 4 "Most days - at least 2 or 3
days/week" office_freq 5 "Every day"
§ When you work at your employer's site, how much of your workday is typically filled
with in-person meetings and events?
office_inperson_meet 1 "At least 90%"
office_inperson_meet 2 "Roughly 70 to 90%"
office_inperson_meet 3 "40 to 70%"
office_inperson_meet 4 "10 to 40%"
office_inperson_meet 5 "Less than 10%"
§ How many distinct Return to Office Policies has your employer announced since fall
2020? rto_policies 1 "None"
rto_policies 2 "One"
rto_policies 3 "Two"
rto_policies 4 "Three"
rto_policies 5 "Four"
rto_policies 6 "Five or more"
§ Does your employer hold occasional offsite events that bring employees together for a
mix of work and social activities?
offsite_events_qual 1 "Yes"
offsite_events_qual 2 "No"
offsite_events_qual 3 "I don't know"
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§ In 2023, how often did you participate in offsite work/social events sponsored by
your employer?
offsite_events_freq 1 "Never"
offsite_events_freq 2 "Once"
offsite_events_freq 3 "Twice"
offsite_events_freq 4 "3 times"
offsite_events_freq 5 "4 times"
offsite_events_freq 6 "5 or more times"
Notes: These value labels apply to both offsite_events_freq and
offsite_events_freqfull, the latter which imputes “Never” for people who say
their employer does not hold occasional offsite events in response to the
question coded into offsite_events_qual above.
§ How long did these offsite employer-sponsored events typically last in
2023? offsite_events_duration 1 "Less than a full day"
offsite_events_duration 2 "1 full day"
offsite_events_duration 3 "2 days"
offsite_events_duration 4 "3 days"
offsite_events_duration 5 "4 days or more"
§ Currently, what is the dress code at your workplace? What was the dress code at
your workplace in 2019?
dress_code 1 "Business formal"
dress_code 2 "Business/smart casual"
dress_code 3 "Relaxed"
dress_code 4 "Uniform"
dress_code 5 "Safety"
dress_code 6 "Anything goes"
§ Are you currently working for the same employer in the same type of job as in
2019? same_job_2019 1 "Yes"
same_job_2019 2 "No"
189
§ Were there any other meeting participants in the same room as you during the meeting?
selected_meeting_sameroom 1 "Yes"
selected_meeting_sameroom 2 "No"
§ Have you applied or considered applying to a job that would allow you to work from
home 1 or more days per week?
considered_wfhjob 1 "Yes"
considered_wfhjob 2 "No"
Abstract (if available)
Abstract
This study examines the incongruence of rank-and-file US workers and managing leaders within organizations when it comes to remote, hybrid, and in-person working arrangements and how changing working models affect employee performance and motivation. This study aims to aid organizations in increasing job satisfaction through improvements in organizational practices surrounding in-office versus remote-first worker-designated roles. These improvements will lower organizational operating costs by reducing turnover, employee burnout, and absenteeism. Ultimately all US workers will benefit through increased trust and the greater life quality that comes from reduced mental stress for both workers and executive management. This matters as 79% of workers who expressed a wish to permanently work from home (WFH) or in a hybrid model and employers will need to reconcile company wishes to return to the office against employees’ desires to not give up the time they regained and repurposed by not commuting to an office as a result of the global COVID-19 pandemic (Barrero et al., 2021).
Linked assets
University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Younger, Robert
(author)
Core Title
Labor versus management perspectives on remote, in-person, and hybrid work: an examination of incongruences, challenges, and strategies for optimal workplace collaboration, motivation, and performance
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Organizational Change and Leadership (On Line)
Degree Conferral Date
2024-12
Publication Date
12/09/2024
Defense Date
11/26/2024
Publisher
Los Angeles, California
(original),
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
changing work models,employee engagement,employee motivation,employee performance,employee productivity,hybrid work,in-person work,job satisfaction,Maslow's hierarchy of needs,motivation-hygiene theory,OAI-PMH Harvest,organizational culture,remote teams,remote work,two-factor theory,working arrangements
Format
theses
(aat)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Canny, Eric (
committee chair
), Maddox, Anthony (
committee member
), Seli, Helena (
committee member
)
Creator Email
robyounger@me.com,ryounger@usc.edu
Unique identifier
UC11399EHFT
Identifier
etd-YoungerRob-13680.pdf (filename)
Legacy Identifier
etd-YoungerRob-13680
Document Type
Dissertation
Format
theses (aat)
Rights
Younger, Robert
Internet Media Type
application/pdf
Type
texts
Source
20241210-usctheses-batch-1227
(batch),
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Repository Email
cisadmin@lib.usc.edu
Tags
changing work models
employee engagement
employee motivation
employee performance
employee productivity
hybrid work
in-person work
job satisfaction
Maslow's hierarchy of needs
motivation-hygiene theory
organizational culture
remote teams
remote work
two-factor theory
working arrangements