The Impact of Working from Home during COVID-19 on Time Allocation across Competing Demands

Abstract

(1) Background: We apply the Total Leadership approach to better understand how employees allocate their time across the domains of work, family, community, and self at three points: pre-, during, and post-COVID-19 restrictions. (2) Methods: The study employed a mixed methods design with qualitative and quantitative survey data from 106 Australian employees who worked from home during the pandemic. (3) Findings: Three categories of participants emerged: work-centric, family-centric, and self-centric. The results showed a reduction in time allocated to work during restrictions, an anticipated further reduction post-restriction, and significant increases in the family and self domains. Qualitative analyses confirmed the shift away from work and a divergence between those who preferred the integration of domains verses those who preferred a segmentation approach. (4) Implications: The Total Leadership approach is relevant to this shift in values and priorities away from the work domain, since it encourages employees and employers to take a holistic perspective on their lives. This rethinking could help to reduce burnout and employee turnover—which are particularly salient due to the ‘great resignation’—and could contribute to the sustainability of workforces, as organisations strive to retain and recruit employees who increasingly value work–life balance and wellbeing. (5) Originality: The application of the Total Leadership approach provides a novel theoretical foundation to investigate how employees allocate time across different domains of their post-COVID-19 lives.

1. Introduction

The great remote working experiment, which many organizations and employees across the globe faced in response to the rapid spread of the COVID-19 virus, is an example of an HR practice once considered impossible by many that proved to be possible [1,2]. Working from home (WFH) was suddenly not only possible, but unavoidable during times of lockdowns, restrictions, and social distancing [3,4]. Human resource professionals, leaders, and employees were faced with the challenges of a rapid shift to remote work arrangements, but also with significant learning and growth opportunities. For employees, the shift to WFH illuminated other challenges around managing time and erected or dismantled barriers between various domains of life. When considering the future of work and sustainable workforces, many researchers argue that a degree of flexible and WFH arrangements is necessary to retain the best talent and ensure adequate staffing, as employees increasingly prioritize work–life balance and wellbeing.

One prominent theory of time allocation across life domains, Total Leadership [5], involves experimenting with changes that potentially enhance life satisfaction in four key domains: work, home, community, and self. Friedman proposed designing personal experiments to identify goals that benefit each domain. The sudden emergence of the COVID-19 pandemic in early 2020 resulted in many people having just such an opportunity to experiment with time allocation across these domains.

The shift to WFH was particularly relevant in countries that imposed harsh and long periods of restrictions, such as Australia, South Korea, the Philippines, and Argentina [2,6]. In the pandemic, Australians, for example, experienced strict national- and state-level border restrictions and other restrictive measures. Starting in March 2020, restrictions progressively implemented by the Australian government limited citizens’ movements and gatherings, and temporarily closed schools and non-essential businesses. As a result, all non-essential employees who could do so commenced WFH. Even though some mandates were eased when case numbers lessened, at the time of data collection for the present study (January–May 2021), non-essential employees in Australia predominantly worked from home [7], and in the state of Victoria, long-term lockdowns remained in place [8]. Australia was hardly unique in terms of restrictions, and while we do not claim that the experiences of this nation are universal, much of what is presented may be applicable to other countries.

The current study seeks to understand people’s priorities and time allocation across the four life domains [5,9] that were impacted by COVID-19 conditions. By asking people to: (a) report their time allocation during the period of restrictions; (b) to recall the way they previously allocated their time before COVID-19; and (c) to forecast how they would like to allocate their time in the future, we can compare time allocation across different periods of time. In addition, we aimed to understand whether demographic groups diverged in time allocation patterns, and qualitatively why some individuals would seek or not seek long-term changes in time allocation. Specifically, we address the following questions:

1.

How did employees allocate their time across the four domains of work, family, community, and self at three points in time: (a) pre-restrictions due to COVID-19, (b) during the period of restrictions, and (c) after restrictions ended?

2.

How do changes in time allocation across the three time periods relate to demographic characteristics, such as gender, age, and parental status?

3.

What are the implications of allocation changes across the three periods, and the stated reasons for those changes, for HR practices moving forward?

1.1. Competing Demands of Work and Family (Life)

Identity theory [10] posits that individuals carry multiple role identities, and need to attend to different responsibilities pertaining to these roles as, for example, employees, parents, friends, or volunteers. While people may identify with and view some roles as more important than others, the inability to fulfill even less important roles for a long period can generate inter-role conflict [11,12]. Work–family conflict specifically arises when the demands of work interfere or become incompatible with the demands of family or personal life [12,13]. Work–family conflict can operate in both directions, such that work can impede on family life and vice versa [14].

Following decades of focus on the negative outcomes of work–life conflict [15], researchers turned their attention to the idea of work–family balance and positive interdependencies between work and family roles (e.g., [11,16]). Building on research addressing positive interdependencies and positive spill-over, scholars [17,18] have introduced the concept of work–family enrichment, which refers to cases where experiences in one role improve the quality of the other role.

Other research takes a more integrative approach, suggesting that flexibility at work allows opportunities to effectively engage in non-work domains of life, such as having time for oneself, for friends, and for family, with fulfillment in non-work domains contributing to career success and wellbeing [19,20,21]. During the forced experience of WFH during the pandemic, many employees started to observe ways in which different life domains and identities intersected and interfered with each other, both positively and negatively [4].

These circumstances suggested the value of work–life integration, and particularly the Total Leadership approach [5,9], as an appropriate framework to explore how employees can apply a whole-life approach to manage competing responsibilities across the four different domains. This approach moves beyond the simple dichotomy of work and family by highlighting the significance of integrating other non-work domains. An integration approach may be of particular relevance during and after the pandemic when many employees questioned the role of work in their lives, as evidenced by the ‘great resignation’ where many employees abandoned jobs that did not deliver a sense of fulfilment [22,23].

1.2. Overview of Total Leadership: The Work–Life Integration Approach

The concept of work–life integration encourages employees to think about ways to blend work and non-work areas of life in order to harmonize different domains of life [9]. Consider the following example proposed by Friedman [9]. Kerry’s family members and work colleagues noticed that she was working too hard and spreading herself too thin by caring for others. Friends advised her to try being as generous to herself as she was to others, and Kerry responded by focusing more on the self domain and began training for a triathlon with friends and workout partners. Through this experiment with integrating domains, Kerry was able to look after her health and spend time with friends which, in turn, helped her to be more focused on her work.

This is an example of how an employee can achieve a four-way win under the Total Leadership approach. The four-way-win logic argues that creatively combining and integrating domains and stakeholders from various domains can offer opportunities for mutual benefits across all domains [9,10]. Total Leadership is a synthesis of two separate fields of study, the study of leadership, and the study of how to find harmony among different domains of life, which encourages and empowers employees to experiment with new ideas for how to enhance performance in work and non-work areas of life [24]. It starts with looking at individuals’ deeply held core values about work, family, community, and self, and understanding who and what matters the most [25], then experimenting with strategies that mutually benefit performance in the four domains, rather than increasing the happiness in one domain at the sake of another.

One of the biggest challenges employees faced in the pandemic context was a blurring of the boundaries between work and other life domains [2,4]. This blurring can potentially lead to decreased wellbeing, poor productivity, turnover, and relationship issues. Keeney et al. [11], in their attempt to understand the need for broadening the conceptualization and measurement of ‘work–family’ to ‘work–life’, argued that the latter more fully captures the construct space that is relevant to a contemporary workforce with diverse life circumstances. Because family is not the only domain that can interfere with work, failure to consider other aspects of life (e.g., community/physical, and the emotional health of individuals) can have a detrimental impact on employee morale, retention, career success, and general wellbeing [19,26]. Furthermore, Friedman and Lobel [25] found that when senior executives help employees focus on what matters most, not only at work but also in other domains, employees flourish, and organizations achieve superior performance. Employers who support their employees to align values across work and non-work activities engender more committed employees and report higher wellbeing and optimal functioning [11,13,24,26]. Findings of an experimental study of 379 executive MBA students who completed the Total Leadership program revealed that students who completed the program significantly increased satisfaction and performance in all domains of life [24]. The participants further described that an understanding of ‘four-way wins’ helped them to become more purposeful with time allocation and encouraged them to experiment with alternative ways of work to achieve work- and non-work-related goals without compromising quality. The authors argue for management development specialists not just to incorporate different work–life initiatives in theory, but also to help employees experiment with these initiatives by providing structure, guidance, and support. For instance, study participants suggested that they would benefit from work–life policies, but only after receiving support from coaches and peers and through self-reflection, rather than merely reading about such policies in a document or on a company website. For another example, Maddox-Daines [27] found that organizations that treated staff as a resource rather than as people during COVID-19 remote working periods saw increases in employee self-imposed surveillance and negative impacts on wellbeing and physical health.

Even though research suggests that satisfaction in non-work domains of life can spill over to the work domain [11], research has less often considered how employees allocate their time across the four domains of life. The current COVID-19 WFH context offers an opportunity to help fill this research gap.

2. Data and Methods

2.1. Research Design

To address the three research questions, we employed a mixed methods research (MMR) design, which has the advantage of uncovering insights which are not available to separate qualitative or quantitative studies [28]. A cross-sectional survey allowed for an integrative (convergent) mixed methods approach [29] to explore the allocations of time and respondent sense of fulfilment with different domains (quantitative) and what the respondents learned from the period of WFH (qualitative).

2.2. Data Collection

After receiving approval from the Human Research Ethics Committee from the affiliated university in November 2020, the survey was administered from January to May 2021. During this time, remote work was mandatory for the majority of Australian employees (except those classed as authorized workers who were permitted to attend work, e.g., police officers or baristas in cafes offering take-away), and the sample was limited to respondents who engaged in WFH during the period of survey administration. All surveys were completed online and obtained via the survey panel provider, Prolific. Prolific (https://prolific.co/, accessed on 20 July 2022) is an online survey platform. Prior research studies published in highly ranked academic journals [30] have collected data using Prolific and similar platforms due to: (a) high recruitment standards for participants and reasonable costs; (b) the explicit informing of prospective participants that they are being recruited for participation in research; and (c) the fact that researchers can select participants from demographic variables suitable to their research (see [31] for a review). For instance, in our recruitment, we used the following pre-screening items to determine eligibility. Only those (a) 18 and over, (b) who listed their country of residence as Australia, and (c) who indicated that they were working from home during COVID-19 were invited to participate. We also included an attention-check question as a way to remove participants who responded without carefully reading the survey questionnaire [32].

One hundred and six respondents completed the survey. The sample size for any experimental design is a trade-off as participants and researchers have limited resources. Our sample size was sufficient for a within-participant design. We did not want to expose more people than necessary to the possible costs associated with participating in an online survey. As a condition of recruitment, the data provider only included participants who responded to all time allocation items and passed the attention-check question. Although some demographic information was missing (see

Table 1. Participant demographics and descriptions for fulfillment, benefits and challenges of WFH.

Time Domains	Mean	Std. Dev.	N
Demographics
Women	0.538	0.501	106
Age in years	37.4	10.4	99
Married/partnered	0.679	0.469	106
Number children	0.798	1.03	99
Post-grad. education	0.465	0.501	99
English as first language	0.828	0.379	99
Asian	0.236	0.427	106
Management	0.226	0.420	106
Work hours	36.5	9.95	92
Fulfillment with
Work	2.5	1.10	106
Family	2.93	0.964	106
Community	1.90	0.925	106
Self	2.45	1.20	106
Benefits
More time for myself	2.25	1.25	106
More time to be with family	2.23	1.48	106
Time spend on work is more productive	1.45	1.34	106
Save time and money	2.21	1.34	106
I can choose when to work	1.90	1.51	106
Challenges
Distracted by children/other family	2.39	1.42	106
Feel like I am working all day	2.69	1.17	106
Miss work colleagues, feel isolated	2.12	1.34	106
Less self-motivated to work	1.83	1.24	106
No choice when to work (online 9–5)	0.972	1.28	106

below), all participants were included in the analyses where possible.

2.3. Measures

Key quantitative items for RQ1 addressed the three time periods. Consistent with Friedman [9] (pp. 55–62), we asked participants to indicate their time allocation for each domain for each time period (pre-, during, and post-restrictions), allocating a percentage (from 0 to 100) which reflected the time they devoted to each domain, such that the total of all domains equalled 100. A sample question asked was “Thinking about how you actually focus time and attention to each domain of your life under COVID-19 restrictions, allocate 100 points across the following four domains”. They were provided with a constant sum question with four domains and space to indicate the percentage of time allocated to each domain. To understand who was affected (RQ2), demographic variables measured gender, age, marital or partner status, number of dependent children, educational attainment, language(s) spoken, Asian heritage, management responsibilities, and usual work hours. Note that Asian and Caucasian heritage were the most common responses to a US-based race question (accounting for 82% of responses), which did not include an option for Aboriginal and Torres Strait Islander people. Management responsibilities were coded if the respondent reported a job title including the word “management” or variants thereof, “CEO”, or “director”; however, “Account manager” was not coded as a management position. Usual work hours were drawn from a generic question at the end of the survey. Both management and work hours are reported under demographics for simplicity only.

Several items may shed light on the why and implications question (RQ3) regarding shifts into the future time period. First, respondents were asked to “indicate their sense of fulfilment with each domain when working from home under restrictions compared to pre-COVID time”, on a 5-point Likert scale (from 0 = extremely dissatisfied to 5 = extremely satisfied). Second, two items asked about benefits and challenges of WFH, “under COVID-19 restrictions, which domain(s) was/were positively [negatively] impacted,” with respondents asked to rank these variables from 1 to 5 (reverse scored from 0 to 4, such that 4 was the most impacted domain). Third, an open-ended question asked, “What is the most important lesson that you learnt during the COVID-19 restrictions in terms of the four domains of daily activities (work, family, community, self)?” Although there were some missing data (see Table 1), all respondents answered the open-ended question.

Except for time allocation and the qualitative responses, descriptive statistics are provided in Table 1. Most demographic variables are coded as dummies, such that the mean represents the proportion of, e.g., women, those married/partnered, with post-graduate education, English as a first language, Asian heritage, and management responsibilities. The remaining demographic variables are numeric, as in age, number of children, and usual work hours. Note that only 92 respondents answered all relevant questions, but all usable responses were included in the analysis.

2.4. Data Analysis

For the quantitative analyses, statistical significance was generated from either χ² tests or paired t-tests. The latter is for contrasts across continuous measures (e.g., age, fulfillment scales), with the prior used for categorical variables for time domains (described below). The qualitative analysis generated themes which translated to dichotomous variables for χ² test comparisons across time allocation categories. To address RQ1, average time devoted to each domain was compared across the three time periods. Respondents were partitioned into groups according to either pre-, during-, or post-restriction time allocation. As cluster analysis has been shown to be unreliable due to numerous algorithms and multiple starting and stopping rules [33,34], we instead applied two rules for categorization into groups: (1) work-centric applied to anyone devoting at least half their time to work; (2) family-, self-, or community-centric were assigned to the remainder depending upon the maximum time devoted to any of the three (note there were no ties).

Analyses for RQ2 involved comparing demographic variables of groups across three time periods. Quantitative analyses for RQ3 involved replicating those analyses using the fulfillment and benefits/challenges of WFH variables.

The qualitative analysis for RQ3 relied on data from the open-ended survey question regarding lessons learned. Answers tended to be brief, with 73 or 107 responses limited to 1 to 15 words. To analyse the results, two researchers independently read all responses to develop initial codes using an inductive method, with no pre-given codes [35], utilizing Gioia et al.’s [36] suggestion that it is useful to maintain ‘semi-ignorance’ (p. 21) of the literature for inductive analyses. That exercise resulted in sets of 22 and 43 prospective codes, with two respondents claiming “none”. To adjudicate, the lead researcher combined the two lists, resulting in 25 codes. To translate these codes to themes, the research team simplified the analysis by collapsing four codes for overwork into a single theme. For example, the following was coded as “reframe” by one researcher, and as “financial pressure to work” by the other: “very easy to get stressed and worry about being able to bring in enough income both short-term and long-term. Difficult to turn off from work and just relax.” Both were ultimately coded as “overwork.” A more subtle example involved the following: “Working without being in the physical presence of others on a permanent basis does not suit me”. One researcher initially coded this response as “value interactions”, and the other as “place to work is important”, each of which are reasonable; nonetheless, the quotation was placed under the “segmentation” category, which involved a clear delineation of work and home, here across space and social settings.

Further discussion within the team simplified the results to 16 themes in total. Five respondents had two codes and, for the qualitative analysis only, their responses were treated as separate responses, (i.e., as 111 total responses). The 16 themes were initially analysed by frequencies to identify any story that emerged. Next, the 16 themes were translated into dummy variables and tested for linkages to the pre-restriction groups and post-restriction groups.

3. Results

Respondents were partitioned into groups according to their pre-, during-, and post-restriction time allocations. The application of the two rules for partitioning participants resulted in three distinct categories: (1) work-centric, (2) family-centric and (3) self-centric, noting that no respondent reported spending most non-work time on community. After presenting comparative time allocation on each domain across the three time frames (see

Table 2. Time allocation: percentages devoted to work, family, community, and self.

Time Domains	Pre-Restrictions	Restrictions	Post-Restrictions
Work	46.4	43.7 *	37.6 ***
Family	25.9	28.3 **	29.1
Community	8.0	5.3 ***	9.9 ***
Self	19.7	22.7 ***	23.4

Note. N = 106, 2-tailed t-test for comparisons between pre- and during-restriction periods (2nd column), and between during- and post-restriction periods (3rd column), * p < 0.10, ** p < 0.05, *** p < 0.01.

), further analyses compared two groups at a time.

3.1. Quantitative Results

Considering RQ1, the average percentage of time devoted to each domain over time is detailed in Table 2. From pre-restrictions to the restriction period, there were significant reductions in time devoted to work and community, with significant increases in time on family and self. From the restrictions period to the post-restriction period, respondents predicted further and significant decreases in time devoted to work and a significant expansion of time devoted to community, with the shifts from pre-restrictions to restrictions in terms of family and self basically projected to continue.

Table 3. Time allocation categories: pre- to during-restriction shifts.

		During Restrictions		Row Totals
Pre-restrictions	Work	Family	Self
Work	37	9	12	58
Family	7	24	2	33
Self	2	2	11	15
Column totals	46	35	25	106

Note. χ² statistic 55.6 (p < 0.000, 4 d.f.).

and

Table 4. Time allocation categories: pre- to post-restriction shifts.

		Post-Restrictions		Row Totals
Pre-restrictions	Work	Family	Self
Work	25	13	20	58
Family	3	28	2	33
Self	0	5	10	15
Column totals	28	46	32	106

Note. χ² statistic 46.5 (p < 0.000, 4 d.f.).

compare the domain groups after applying the two classification rules to, first, pre- and during restrictions (Table 3) and, second, to pre- and post-restrictions (Table 4). In Table 3, the pre-restriction groups are found in the first column, with sums the across rows for the during restriction categories to yield row totals; similarly, the during-restriction categories are identified by the first row, with sums over the columns to yield column totals at the bottom. Table 4 is the same, except the during-restriction categories are replaced by post-restriction categories. In both tables, the χ² statistic for differences between the two distributions are significant (p < 0.001). These results again suggest employees will continue to reduce working time and expand time devoted to family and self.

Turning to RQ2,

Table 5. Demographic characteristics by pre-restriction categories.

Variables	Work-Centric	Family-Centric	Self-Centric
Women	0.569	0.606	0.267 **
Age in years	38.6	37.0	33.6
Married/partnered	0.655	0.879 **	0.333 **
Number children	0.574	1.45 ***	0.214
Post-grad education	0.426	0.581	0.357
English as 1st language	0.852	0.806	0.786
Asian	0.155	0.333 **	0.333
Management	0.224	0.273	0.133
Work hours	39.0	33.2 **	33.8
N	58	33	15

Note. Significance from χ² statistics for dichotomous and t-statistic for continuous variables, in comparison to work-centric group. ** p < 0.05, *** p < 0.01.

reports breakdowns of the demographic variables for the pre-restriction groups. Half of all respondents (58) were initially work-centric, with most of the remainder family-centric (33). Limiting discussion to significant differences, the results suggest that family-centric respondents tended to be married/partnered, had relatively large numbers of children, were more often Asian, and tended to work fewer hours, each relative to the work-centric respondents. The self-centric respondents tended to be male (i.e., less often women) and single or divorced (i.e., less often married/partnered).

The same characteristics were considered in terms of the different groups for pre- and post-restriction time allocation, as shown in

Table 6. Demographic characteristics: pre- to post-restriction categories.

Variables	Work–Work-Centric	Family– Family-Centric	Self–Self-Centric	Work–Self-Centric	Work– Family-Centric
Women	0.560	0.607	0.300 *	0.700	0.385 +
Age in years	39.7	37.3	31.4 **	35.6	40.8
Married/partnered	0.680 *	0.893	0.200 ***	0.400 ***	1.00 +++
Number children	0.304 ***	1.46	0 ***	0.444 ***	1.23 +
Post-grad education	0.391	0.577	0.222 *	0.389	0.538
English as 1st language	0.870	0.885	0.778	0.889	0.769
Asian	0.120 *	0.321	0.400	0.100 *	0.308
Management	0.374	0.441	0.316	0.444	0.480
Work hours	40.5 **	32.4	30.8	38.1 *	37.7
N	23	26	10	20	13

Note. Significance from χ² statistics for dichotomous and t-statistic for continuous variables. For comparisons of family- to family-centric group: * p < 0.10, ** p < 0.05, *** p < 0.01. For comparisons of work- to self-centric and work- to family-centric groups: + p < 0.10, +++ p < 0.01.

. Those who began and remained either work-centric or self-centric, and those who switched from work- to self-centric were significantly less often partnered and had fewer children, relative to the family- to family-centric group. Furthermore, the Asian group tended to be family- to family-centric, relative to the work- to work-centric group; conversely, the work- to work-centric group reported significantly longer work hours than the family- to family-centric group, and the self- to self-centric group was predominantly male with low levels of education, again relative to the family- to family-centric group. The work- to self-centric group members were less often married/partnered, had fewer children, were less often Asian, and reported longer hours relative to the family- to family-centric group. Comparing the work- to self-centric and work- to family-centric groups (significance denoted by ‘+’), the latter were more often male, partnered, and had more children.

Turning to the fulfillment and benefits/challenges of WFH variables and pre-restriction time allocation in

Table 7. Fulfillment, benefits and challenges of WFH by pre-restriction categories.

Variables	Work-Centric	Family-Centric	Self-Centric
Fulfillment with
Work	2.50	2.52	2.47
Family	2.78	3.24 **	2.93
Community	1.79	2.09	1.87
Self	2.40	2.30	3.00 *
Benefits
More time for myself	2.24	2.30	2.07
More time to be with family	1.98	1.70	1.53
Time spend on work is more productive	1.95	2.42	1.87
Save time and money	2.05	2.15	2.07
I can choose when to work	1.81	1.42	2.47
Challenges
Distracted by children/other family	1.72	1.91	1.93
Feel like I am working all day	2.16	2.24	1.73
Miss work colleagues, feel isolated	2.16	2.21	2.13
Less self-motivated to work	2.74	2.18 *	2.33
No choice when to work (online 9–5)	1.22	1.45	1.87
N	58	33	15

Note. Significance from t-statistics (all continuous variables) in comparisons to work-centric group. * p < 0.10, ** p < 0.05.

, significant differences were found with family-centric respondents tending to report higher levels of family fulfillment, and less often reporting the challenge of being less self-motivated to work, both relative to work-centric respondents. Self-centric individuals reported higher levels of fulfillment with community relative to work-centric individuals.

The results for the same variables across the pre- and post-restriction periods can be found in

Table 8. Fulfillment, benefits and challenges of WFH by pre- and post-restriction categories.

Variables	Work–Work-Centric	Family– Family-Centric	Self–Self-Centric	Work– Self-Centric	Work– Family-Centric
Fulfillment with
Work	2.60	2.71	2.20	2.35	2.54
Family	2.84 *	3.32	2.70 *	2.55 **	3.00
Community	1.84 *	2.25	1.70	1.95	1.46 **
Self	2.48	2.29	2.80	2.35	2.31
Benefits
More time for myself	2.24	2.39	1.9	2.3	2.15
More time to be with family	1.56	1.64	1.1	2.2	2.46 **
Time spend on work is more productive	1.88	2.39	2.3	1.9	2.15
Save time and money	2.44	2.07	2.5	1.75	1.77
I can choose when to work	1.96	1.5	2.2	1.85	1.46
Challenges
Distracted by children/other family	1.56	2.07	1.7	1.9	1.77
Feel like I am working all day	2.12	2.29	1.6	2.2	2.15
Miss work colleagues, feel isolated	2.12	2.11	2.1	2.05	2.38
Less self-motivated to work	2.76	2.14	2.5	2.65	2.85
No choice when to work (online 9–5)	1.44	1.39	2.1	1.2	0.85
N	23	26	10	20	13

Note. Significance from χ² statistics for dichotomous and t-statistic for continuous variables. For comparisons to family- to family-centric group: * p < 0.10, ** p < 0.05.

. Relative to the family- to family-centric group, the work- to work-centric group reported lower levels of fulfillment in terms of family and community, as did the self- to self-centric and work- to self-centric groups in terms of family fulfillment, and the work- to family-centric group in terms of community fulfillment. In terms of benefits/challenges of WFH, the work- to family-centric group more often reported additional time with family as a WFH benefit.

3.2. Qualitative Results

To provide some nuanced understanding for the RQ3, in this section, we present qualitative findings for the study. The 10 most common themes which emerged are described in

Table 9. Qualitative themes for lessons learned.

Themes	Respondents	Examples
Telework works	17	“Working more ‘solidly’ at home can be more tiring, but the amount of work I achieve is substantially more.”
Importance of self	15	“I need to look after my own mental health better.”
Importance of family	14	“Family is super important.”
Segmentation	14	“Just to keep a schedule so that not too much time is spent in one area and missed in other areas.”
Balance	10	“Balance is necessary.”
Overwork	7	“That work was dominating too much of my time…”
Be flexible to reframe	6	“You must find your own balance as traditional boundaries are blurred.”
Importance of community	6	“That my community is actually an interesting place, and if I want to make it better, I need to take a more active part.”
Value connections	5	“Although I enjoy my personal (self) time, I need social/family connection more than I thought.”
Work to self	5	“Life is not all about work. It’s [also] about time for reflection.”
Various other	9

. The table first names the themes, from most to least common, with the number of respondents invoking the theme provided in the second column, and relevant example quotations in the third column. Note that the ‘Other’ category captures themes mentioned at most by four respondents. Most of the themes are self-descriptive, given the question concerned “the most important lesson that you learnt… in terms of the four domains…” However, it is worth noting that we interpreted the ‘segmentation’ strategy as strengthening boundaries, particularly between home and work, and that ‘overwork’ involved a variety of people who felt their job demanded too much time, that financial constraints led to overwork, or that they tended to work all the time as a matter of course.

Recalling the significant decrease in time allocated to work, both during and particularly post-restriction, it is not surprising that the themes that emerged were generally negative regarding the work domain. Admittedly, as the quotes below suggest, the most common theme, telework works, is positive regarding work. However, that theme captures 17 of the total 111 responses (15.3%). For instance, participants shared that “I can work from almost anywhere and quality of work is not affected” (telework works) and “I can be at least as productive at home as I am in the office, with an added benefit of having more energy” (telework works).

On the other hand, as expressed in the quotes below, overwork was clearly negative regarding work (9.0%), as was moving time from work to self (4.5%). However, what also emerges in the qualitative responses is the implicit importance of family (12.6%) and community (5.4%) which, in combination with overwork and moving time from work to self, represented 26.2% of responses. For example, emphasizing the importance of overall quality of life, one participant shared that, “Analyzing my work life and whether it gave me overall quality of life with the hours I worked. I learnt it did not and I am totally reassessing my career path now” (reframe work to other) and “I would like to do more community work” (importance of community).

An additional 9.0% of responses mention the theme of balance, and while some responses are generic (e.g., “balancing everything”), others are clearly negative regarding time spent on the work domain. For instance, “work does not really mean anything,” or “take time out of the rat race.”

Comparing the 10 most common themes to individuals who were in the work–family- or self-centric categories pre-restrictions, the importance of family was significantly related to family-centric relative to work-centric (χ² = 6.79, p < 0.009), and the importance of community and the category of self-centric relative to work-centric (χ² = 7.39, p < 0.007). Performing that same analysis for the five groups for pre- and post-restriction time and the themes, we found a significant relationship between the theme of telework works and work- to work-centric compared to family- to family-centric (χ² = 8.19, p < 0.004), and for that same theme a significantly higher association for work- to family-centric relative to family- to family-centric (χ² = 3.78, p < 0.052), and for work- to family-centric relative to work- to self-centric (χ² = 4.92, p < 0.027). Additionally, the importance of the theme self appeared significantly more often in the work- to self-centric group compared to the family- to family-centric group (χ² = 4.48, p < 0.034). The theme importance of family was significantly lower in the work- to self-centric group (χ² = 5.68, p < 0.017), and was significantly higher in the work- to family-centric group relative to the work- to self-centric group (χ² = 3.18, p < 0.074). The theme of value connections was found more frequently in both the self- to self-centric group (χ² = 2.80, p < 0.095) and the work- to self-centric group (χ² = 2.97, p < 0.085), both relative to the family- to family-centric group.

4. Discussion

The current study used the Total Leadership [9] framing of life domains to understand how WFH, as a result of the COVID-19 pandemic, changed the allocation of time from pre-restrictions to during the restrictions and beyond for a sample of 106 Australian employees who engaged in WFH during the pandemic. In terms of RQ1, from the pre- to during-restriction periods, net movement occurred away from work-centric to family-centric and self-centric (Table 3). Differences from pre- to projected post-restriction time allocation were even more dramatic, with a decline of more than 50% from 58 to only 28 work-centric respondents, with expansions from 33 to 46 family-centric respondents, and from 15 to 32 self-centric respondents (Table 4). These findings suggest that for more than half of the respondents (63 of 106, see Table 4), COVID-19 circumstances led to a rethinking and reprioritizing of values for these time domains, with the largest movement being away from work-centric. These findings suggest that the pandemic and related restrictions accelerated changes in the ways in which people live, work, and relax [4]. Furthermore, the emergence of the ‘great resignation’ post-lockdown [22,23] should be interpreted beyond individuals simply quitting or changing jobs to explicitly include efforts to reduce work hours.

Regarding demographic distinctions (RQ2), pre-restriction patterns (Table 5) were unsurprising, such as family-centric respondents tending to be married/partnered, and with dependent children. However, comparing pre-restriction to projected post-restriction patterns (Table 6) reveals an unexpected gender finding. Men more often began and remained self-centric but were also more likely to switch away from work- towards a family-centric time allocation. The latter finding suggests some individuals are challenging traditional gender roles. Relatedly, only one group came close to the high levels of being partnered with dependent children compared to the family- to family-centric group, and that was the work- to family-centric group.

Therefore, the Total Leadership framing of this study revealed an important commonality and simultaneously an important divergence. The commonality lies in movement away from being work-centric, but with a critical divergence related to gender, and especially marital/partner status and children in terms of where the time is reallocated to, which reinforces the importance of work–life integration approaches addressing competing demands on employees. As an implication, future research could further explore the impact of shifts in time allocation by comparing actual shifts to perceptions of quality of life. That is, do people actually prefer and enjoy their new time allocations and is this reflected in a greater perceived quality of life? This impact is not necessarily a ‘given’, as we are not always good at forecasting what will make us happy [37].

Considering RQ3, or the ‘why’ of these shifts, the quantitative results revealed relatively trivial but intuitive findings, e.g., family-centric individuals reporting higher levels of family fulfillment (Table 7). One surprising result was that those who switched from work- to family-centric, and the family- to family-centric group reported high levels of community fulfillment (see Table 8).

The qualitative analysis was designed to further address RQ3. Again, most results were intuitive, such as the work- to work-centric group more often reporting the theme of telework works. However, the group that switched from work- towards family-centric also tended to report telework works, suggesting the importance of appropriate design and technology for successful WFH. Perhaps most intriguing are the findings that, for pre-restriction time allocation, those who were classified as self-centric more often reported the theme of importance of community, while for the pre- and post-restriction groups, the theme of valuing connections was reported most often by those who ended up in the self-centric group, either from an initial classification as self-centric or from being work-centric. These findings suggest that the self-centric group does not necessarily represent people who spend time alone but might, instead, capture individuals engaging in self-development activities with others (e.g., sports, education), or perhaps reflects respondents spending time with friends but classifying that time as devoted to self, rather than community.

5. Implications for WFH Practices and Theory

The application of the Total leadership approach provided a strong foundation to understand how employees allocated time across different domains of their life, moving beyond previous dichotomous approaches comparing only work with family or ‘life’ more broadly. The results imply that organizational leaders and HRM practitioners should find ways to accommodate post-pandemic employee preferences regarding how they prefer to allocate their time across different domains. Based on the current study’s findings of a significant decrease in time allocated to work, various types of flexible work arrangements could be considered and trialled for effectiveness and impact [38]. One example lies in the four-day week option, which is gaining popularity in some European countries [39]. Our findings also reveal diverging goals in shifts away from work, as some participants increase time allocated to self while others put that time into family. Therefore, it is unlikely that any single flexible work arrangement will resolve the issues involved. For example, in the four-day week example, self-centric employees may value longer weekends, but family-centric parents might find that work schedule inconsistent with childcare needs. Furthermore, caregiving needs for aging parents and for young children may require diverse working time arrangements, as would different ways that time is devoted to self (e.g., sports as opposed to education).

Instead, we believe the Total Leadership, or work–life integration, approach is ideal for dealing with values shifting away from the work domain, since it encourages employees to take a holistic perspective on the role of work in their lives [19,22,24]. Therefore, HR and line managers should encourage and support employees to align their deeply held values and what they want to achieve in different domains of life [4,26,38]. In addition, having open and honest conversations with employees about what they want to achieve in life in general to integrate personal goals into performance development plans may provide an avenue to fulfil their competing demands.

To increase the chances of success in work–life integration, managers and supervisors should be role models, providing examples of how they integrate different domains of their life and encouraging employees to share their own initiatives [9,21]. However, work–life integration is not appropriate for everyone or required for Total Leadership. Some employees (and some respondents here) prefer work–life segmentation or firming up barriers between work and other time domains [38]. Therefore, employees and managers should have a clear awareness of what works best for individuals (and organizations) and support them through organizational policies and practices to achieve those ends, efforts which could start during the recruiting process [4,13,38].

Another implication for HR practitioners concerns the dividing lines found in the current study (depending on gender and especially whether respondents reported having a partner and/or children) among those who wish to become less work-centric. To increase equity, WFH arrangements need to account for these diverse circumstances, perhaps with satellite offices or hybrid arrangements, with some employees engaging mainly in WFH and others mainly in a physical workplace. Again, a Total Leadership approach can help respond to these issues by innovatively integrating different domains of employees’ lives. Building a business case and altering organizational culture to willingly accommodate employees’ non-work demands may result in favourable outcomes for employees and employers [40]. This approach might also promote gender equity by allowing the (predominantly) men who wish to switch to being more family-centric to do so, a switch which challenges traditional gender roles [41].

In summary, organizations should consider purposefully reframing flexible work arrangements to improve all employees’ quality of life, rather than viewing it as a family- or gender-related entitlement. This approach could make flexible work accessible to all and decrease flexibility stigma [42,43]. It is also important to recognize that not all employees want to work flexibly and may even resent those who do, perceiving that they will be responsible to pick up the slack for employees who appear less present. Leaders will need to engage in open discussions with those who harbor these resentments and ensure exploitation is not occurring (or perceived to be occurring) and determine ways to equitably distribute tasks and workloads.

6. Limitations and Directions for Future Research

Given the sample was limited to respondents who engaged in WFH during the restrictions, the experiences of frontline employees who continued work at a physical workplace are not represented. Another limitation is that the design was cross-sectional instead of longitudinal, so pre-restriction reports may be subject to recall bias [44], and post-restriction preferences may not be realized in practice [32]. We also acknowledge that the study was limited to Australian respondents. Experiences and outcomes elsewhere may differ.

In terms of future research, we recommend a study of how digital transformation can lead to more effective WFH experiences for employees with diverse lives and for employers who manage a heterogeneous workforce. We also believe further research is needed to explore practical and innovative ways that employees can integrate different domains of life that go beyond the notion of ‘work–family’ by integrating other life domains such as community and self. By extending this line of research, it may also be worth further exploring benefits and unique challenges that employees with different demographic characteristics may encounter when integrating the four domains of life. Furthermore, given some employees expect to reduce the time allocated to work, future research should explore how employees can frame flexible work arrangement requests to yield win–win outcomes for their managers. Focusing on organizational research, researchers could explore how organizations can support employees to achieve four-way wins by successfully integrating the domains of work, family, community, and self.

Finally, one of the more intriguing findings involves self-centric individuals valuing connections and reporting the theme of importance of community. In response, future research could tease out time devoted to self which is social as opposed asocial. More generally, work–life integration may blur lines between the four domains, as with the example of a women training for a triathlon (self) with friends (community); further research might address and unpack this form of blurring.

7. Conclusions

The rapid shift to remote working in response to COVID-19 restrictions showed many employees, leaders, and HR professionals to be resilient, adaptive, and able to deliver and perform while working from home. Findings from the current study highlight an important trend: many employees desire greater flexibility in how they allocate their time, and specifically desire more time away from work in favour of the domains of family, self, and perhaps community. How organizations create greater flexibility to fulfil these emerging preferences of employees while ensuring productivity in these circumstances is a key area for researchers and HR professionals to consider. To ensure the sustainability of their workforce, leaders need to consider the flexible and work–life preferences of their employees as they compete in the war for talent and as they address the increasing awareness and focus on employee wellbeing.