Introduction

Flexible work schedules (hereafter ‘flexible schedules’) entitle employees to have control over the timing of their work (e.g., flexible starting and ending times) and are regarded as important options of flexible working arrangements. The last several years, especially during the Covid-19, have witnessed a rapid growth of flexible working arrangements (Wang et al. 2022), and there have been extensive discussions about whether flexible working should become the default option in the work-family initiatives to address increasing work-family conflicts and promote employees’ balance between work and non-work time (CIPD 2021). However, to what extent flexible schedules facilitate the balance between work and non-work time is subject to ongoing debates. On the one hand, many studies argue that flexible schedules facilitate the balance between work and non-work time and well-being by enhancing workers’ control over temporal boundaries and resolving work-family conflicts (Chung & van der Lippe 2018; Li & Wang 2022). On the other hand, another stream of research argues that employees with flexible schedules may actually work longer and have less free time, which is termed as the ‘flexibility paradox’ (Chung 2022; Glavin & Schieman 2012; Mazmanian et al. 2013).

The existing studies are limited to a number of aspects, which may contribute to their inconsistent predictions and findings. First, although a few studies on flexible workplaces have used time diary data to explore the associations between working from home and time use patterns (Craig & Brown 2017; Powell & Craig 2015), no research has examined the time use patterns of employees using flexible schedules. Current research on the outcomes of flexible schedules relies on stylised survey questions to measure respondents’ time use, which may lead to measurement biases (Kan 2008). Specifically, stylised estimates refer to direct questioning in surveys that are used to ask how much time the respondents have spent, for example, in the previous week or on a particular activity (Kan 2008). These estimates are cheaper and easier to collect respondents’ information about their time use than time diary estimates, while over-reliance on respondents’ long-term memory can generate memory bias. Second, most existing research tends to conceptualise the use of flexible schedules as a simple dichotomised variable, ignoring the considerable variation that exists in terms of how and the degree to which flexible schedules can be used to promote work-family outcomes. Failing to consider the variation between different degrees of schedule flexibility prevents us from gaining a nuanced understanding of flexible schedules and time use patterns (Kossek et al. 2004; Zerubavel 1979). Third, given that time use is highly gendered and class-differentiated (Fagan et al. 2012), the current research has not yet systematically investigated the gender and class differences in the relationships between schedule flexibility and time use, which could conceal important nuances regarding the social consequences of flexible schedules.

To address these limitations and extend the debates over the ‘flexibility paradox’, this study aims to use rich time-use data in the UK to achieve the following two objectives. First, drawing on the previous literature, this study examines the degree of schedule flexibility as a crucial dimension of the flexible schedule by distinguishing between limited flexible schedules with core hours and unlimited flexible schedules without core hours. In limited flexible schedules, employees are required to work within a fixed core period (e.g., from 10 am to 3 pm, Mondays to Fridays) and can only decide their work schedule outside of this period (Baltes et al. 1999; Thompson et al. 2015), whereas unlimited flexible schedules do not have any restrictions and allow employees to have full schedule control. While the traditional Job Demand Control (JDC) model assumes that higher schedule control leads to better work-family outcomes (Gasser 2017; Grönlund 2007; Karasek 1979), the temporal regularity thesis in the sociology of time emphasises the importance of maintaining a stable time rhythm in social activities and a relatively clear boundary between work and non-work time for preventing over-access of work commitments and overtime (Hassard 2017; Zerubavel 1979). Given the inconsistent theoretical predictions and findings, the first objective of the study is to investigate how limited and unlimited flexible schedules influence employees’ amount of time spent on paid work, unpaid work, personal care, and free time.

Second, it is expected that the degree of schedule flexibility shapes time use patterns depending on gender and class due to widely argued gender and class differences in time use patterns and cultural norms. Regarding gender differences, while the time availability theory suggests that flexible schedules could reduce gender inequalities in paid and unpaid work time by promoting men’s participation in housework and women’s employment (Kan & Laurie 2018), the gender structure theory and ‘doing gender’ theory indicates that due to persistent traditional gender norms flexible schedules may intensify the gender inequality in time use by increasing men’s paid work hours and women’s unpaid work hours (Risman 2004; West & Zimmerman 1987). Regarding class differences, many studies indicate that workers from lower occupational classes are more likely to use their flextime to seek more paid work and thus have less personal care and free time, due to their relatively disadvantaged position in the labour market (Dumont et al. 2012). However, another strand of research suggests that workers from higher occupational classes will also work longer and have less free time when using flexible schedules to reciprocate the benefits (flexible schedules) from the employers (Chung & van der Horst 2020; Lott & Chung 2016). Furthermore, studies find that people’s occupational positions can influence their gendered behaviours, which leads to a potential intersection of gender and class. Given the potential intersection of gender and class in time use and flexible schedules, the second objective is to determine whether and to what extent the influence of flexible schedules (limited or unlimited) differs across different occupational classes and genders.

By achieving both objectives, this study makes three important contributions to the literature. First, we empirically extend the previous research by analysing the 24-hour time use patterns of employees using flexible schedules. Second, we provide novel insights into the debate of the flexibility paradox by examining the role of the degree of schedule flexibility. Third, we bridge the divergent theoretical perspectives of flexible working, gender and social class into one analytic framework, highlighting the heterogeneous effects of flexible schedules on time use patterns across socio-demographic groups.

Flexible schedules and the ‘flexibility paradox’

Governments and organisations have promoted flexible working schedules to enhance work-family initiatives for decades around the world. Specifically, the aims of work-family initiatives include ensuring sufficient free time, clear boundaries between work and life, good mental health status, as well as preventing work-family conflicts. However, whether flexible schedules ensure more free time or instead lead to longer work hours is subject to extensive debate. On the one hand, many studies indicate that schedule flexibility might benefit employees’ well-being by facilitating the balance between work and non-work time (Li & Wang 2022). This is because schedule flexibility enables employees to juggle competing demands in work and life (Wang et al. 2022). For example, with flexible schedules, employees can travel off-peak to work and save time for their private life. In addition, parents who use flexible schedules can get off work to take care of their children during the standard working period and then make up the working hours during their free time (Chung & van der Lippe 2018). On the other hand, some scholars have found that employees using flexible schedules spend more time on paid and unpaid work, known as the ‘flexibility paradox’ (Chung 2022; Mazmanian et al. 2013). For example, Chung and her colleagues find that employees using flexible schedules not only have longer paid work hours (Chung & van der Horst 2020), but also spend more time on routine housework and childcare (Powell & Craig 2015), especially for women with young children. Also, if employees spend more time on paid and unpaid work when working flexibly, their free time will be reduced accordingly. However, the current studies on the effects of flexible schedules on time use patterns are based on over-simplified stylised survey questions, overlooking the nuanced ways in which different types of flexible schedules shape workers’ time use across gender and occupational groups.

Degree of schedule flexibility and time use

Previous research tends to conceptualise the use of flexible schedules as a simple dichotomised variable, ignoring the considerable variation that exists in terms of how and the degree to which flexible schedules shape employees’ time use. The degree of schedule flexibility is such a crucial yet understudied dimension of flexible schedules (Chung 2022; Kossek et al. 2004). This study distinguishes between flexible schedules with core hours (which provide employees limited flexibility in work schedules) and flexible schedules without core hours (which allow employees to have unlimited autonomy in work schedules). Although the distinction between different degrees of schedule flexibility is regarded as theoretically important, there is no relevant empirical research. Existing theories have conflicting predictions about whether a higher degree of schedule flexibility leads to the time use patterns encouraged by work-family initiatives.

On the one hand, a longstanding theoretical tradition, such as the Job-Demand Control (JDC) model (Karasek 1979), assumes a linear relationship between schedule flexibility and the balance between work and non-work time, suggesting that high degrees of schedule flexibility can promote employees’ well-being, quality of life and job performance by alleviating work pressure, reducing workloads and ensuring more free time for recreational labour (Grönlund 2007; Wheatley 2017). For example, a three-nation investigation across Russia, Canada and Israel finds that employees who can decide when to start and end their work without certain limits (i.e., unlimited flexible schedules) have better mental health status (i.e., less job stress and mental strain) than those who have less schedule flexibility (Barney & Elias 2010). In addition, Gasser (2017) found that a higher degree of schedule flexibility (e.g., flexible schedules without core hours) is associated with fathers’ less paid work hours, especially for those without leadership positions in the workplace. Taken together, the JDC model and recent empirical findings indicate that a higher degree of schedule flexibility may lead to time use patterns that facilitate the balance between work and non-work time.

On the other hand, another strand of research challenges the assumption of the JDC model, indicating that unlimited schedule control may bring unpredictable schedules that go against the balance between work and non-work time. Specifically, the concept of temporary regularity has been proposed by several scholars and indicates that ‘rational schedule flexibility’ should maintain a relatively stable social rhythm and a certain degree of rigidity in the boundary between work and non-work time (Hassard 2017; Sargent et al. 2020; Zerubavel 1979), which can prevent employees from overwork and role conflicts. Therefore, employees’ schedule flexibility should be limited to a certain extent to avoid blurring the boundaries between work and non-work time. In addition, the work-family border theory (Clark 2000) also indicates the importance of maintaining a relatively rigid boundary between work and family time. Specifically, when the boundary between work and family domains is blurred or eliminated, people are more likely to experience role conflicts because work and family are two distinct domains characterised by different rules, thinking and behavioural patterns (Clark 2000; Michel et al. 2011). Thus, when the boundary between work and family domains is less clear, employees often find it difficult to negotiate with employers or families about where and when household or workplace responsibilities should be carried out (Chung & van der Horst 2020; Lott & Chung 2016). Furthermore, flexible work-family borders can also increase the amount of cognitive load (e.g., the spillover of negative emotions) that people have across the borders (Kim et al. 2019).

Overall, previous research has conflicting predictions about whether a higher degree of schedule flexibility leads to time use patterns facilitating the balance between work and non-work time. Surprisingly, there is so far no empirical research to distinguish different degrees of flexible schedules and test their impacts on time use. Therefore, the study’s first objective is to examine how unlimited and limited flexible schedules shape employees’ 24-hour time use patterns in paid work, unpaid work, personal care and free time.

Gender and occupational differences

This study further explores how the degree of schedule flexibility shapes time use patterns depending on gender and class due to widely argued gender and class differences in time use patterns and cultural norms (Fagan et al. 2012). Despite these widely acknowledged gender and occupational differences, the existing theories have inconsistent predictions and there is so far no empirical research to investigate the gender and class differences in the relationships between schedule flexibility and time use, which could conceal important nuances regarding the social consequences of flexible schedules.

Gender

Most previous research on gender differences in time use focuses on the traditional gender division of time use, where men focus on paid employment and women spend longer time on domestic household responsibilities but have less free time (Sullivan & Gershuny 2018). A growing body of research argues that such traditional gender division of time use is formed largely in response to the institutional constraints in the workplace, such as long and inflexible working hours (Syrda 2022; Wang et al. 2022; Wang & Lu 2022; Wang and Gong 2023). According to time availability theory, an individual’s allocation of time to household labour depends on and follows the allocation of time to paid work (Kan & Laurie 2018). Thus, time availability theory would predict that the use of flexible schedules increases women’s time spent on labour participation and men’s time spent on domestic housework (Chung 2018; Golden 2008), thereby reducing gender disparities in time use in both domains. For example, mothers with heavy childcare demands can actively engage in the labour market when using unlimited flexible schedules since they are not required to commit to specific work time periods. In contrast, the gender structure theory (Risman 2004) and the doing gender theory (West & Zimmerman 1987) indicate that the use of flexible schedules will not reduce but intensifies the gender inequalities in time use. This is because gender as a structure continually shapes individuals’ internal identities and external expectations, thereby spirally enhancing gender norms (Risman 2004), while the entrenched gender norms can gradually drive men and women to do gender to conform to their own and cultural expectations. For example, research shows that men are more likely to use flexible schedules for work-related purposes and end up with long working hours, whereas women tend to use flexible schedules or flexplace for family-related purposes and end up with heavier housework burdens and less recreational labour (Chung 2022; Lott & Chung 2016; Powell & Craig 2015). This echoes the ‘flexibility paradox’ as a result of using flexible schedules. Taken together, previous studies make conflicting predictions about whether flexible schedules expand or narrow the gender gaps in time use.

Occupational class

Previous studies also suggest that the impacts of flexible schedules on time use can be occupational class differentiated (Chung & Booker 2022; Chung & van der Horst 2020). However, we still know little about whether and how the benefits of flexible schedules vary across occupational lines due to the lack of empirical evidence. On the one hand, employees in the lower occupational classes have less bargaining power (Dumont et al. 2012; Lu et al. 2023; Shi & Wang 2022), less job security, and face higher risks of underemployment (Inanc 2018). Studies also find that lower occupational groups are more likely to experience less free time and sleep time (Chatzitheochari & Arber 2012). Thus, lower occupational groups may use flexible schedules to seek more paid work opportunities, thereby sacrificing their free time. On the other hand, the ‘gift exchange theory’ indicates that employees in higher positions might reciprocate the gifts (e.g., flexible schedules) from the employer and then increase their commitment and work harder (Chung & van der Horst 2020). A stream of time use studies also finds that people of higher socioeconomic status are more likely to suffer less free time and more fragmented schedules, which can increase their subjective time pressure (Cornwell et al. 2019). It is also worth noting that the potential intersection of gender and occupational class among the impacts of flexible schedules might exist since studies have evidenced that people’s occupational positions can influence their gendered behaviours (Kan & Laurie 2018). Thus, the investigation of the intersection between gender and occupational class is also needed.

Overall, previous research on gender and occupational differences in time use tends to focus on specific domains (e.g., paid work and unpaid work) and has divergent theoretical predictions. However, it is less clear how the associations between different types of flexible schedules and time use vary across intersecting axes of these demographic and socioeconomic characteristics. Therefore, the study’s second objective is to examine whether and how unlimited and limited flexible schedules shape employees’ use patterns in paid work, unpaid work, personal care and free time vary across gender and occupational classes.

Research methods

Data and sample

The study uses data from the UK Time Use Survey (UKTUS) 2014/2015, the latest nationally representative time-use survey in the UK. This survey initially sampled around 11,000 eligible households drawn from the Postcode Address File (PAF) system by using a multi-stage stratified probability sampling design (Gershuny & Sullivan 2017). The sampling areas cover England, Wales, Scotland, and the Land Property Services Agency (LPSA) in Northern Ireland. The UKTUS has 10,280 eligible respondents, with 81.1% completing one diary or more (16,550 diary days). During the survey, the respondents recorded what they were doing, how they were doing it, and their feelings towards their activities across 144 10-minute episodes over the course of two days, one weekday and one day from the weekend. After completing their time diaries, the respondents were interviewed about their socioeconomic conditions and life circumstances. This study focuses on the subset of diaries recorded by adults who reported working in paid employment. In addition, since the study only investigates the time use of employees on typical workdays, it excluded the diaries for weekends and non-work days. After excluding diaries with missing data in key measurements, our final analytic sample includes 1933 employees who fully recorded their activities during each episode. More details about the sample can be seen in Table 1.

Table 1 Weighted sample descriptive statistics.
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Measurements

Dependent variables

Following previous time-use analyses, this study classifies respondents’ 24-h time use into four main activities: paid work, unpaid work, personal care and free time (Chatzitheochari & Arber, 2012; Craig & Brown, 2017; Zuzanek, 1998). Therefore, the dependent variables for this study are the amount of time respondents spent doing paid work, unpaid work, doing personal care, along with how much free time they had. Although the respondents might have been multitasking during each episode, this study only counts their primary activities. Paid work encompasses the activities related to respondents’ main and secondary jobs, including working, work-related travelling and other unspecified working-related activities. Unpaid work includes activities related to caring for others (i.e., household care and childcare) and routine and non-routine housework. Personal care is the amount of time respondents spend on activities that meet personal needs (i.e., sleeping, grooming and dressing) (Chatzitheochari & Arber, 2012; Zuzanek, 1998). Free time is the amount of time spent on activities other than paid work, unpaid work and personal care activities (Chatzitheochari & Arber, 2012; Craig & Brown, 2017). The time participants spent on these activities was measured in minutes.

Independent variables

The key independent variable is respondents’ use of flexible schedules, which is a categorical variable including three categories: ‘no flexible schedules’, ‘limited flexible schedules (with core hours)’ and ‘unlimited flexible schedules (without core hours)’. ‘Core hours’ refers to a fixed continuous period that workers should be working status. For instance, in limited flexible schedules, employees are required to work within a fixed core period (e.g., from 10 am to 3 pm, Mondays to Fridays) and can only decide their work schedule outside of this period (Thompson et al. 2015). By contrast, unlimited flexible schedules do not have any restrictions and allow employees to have complete schedule control.

Moderator and confounders

Occupational class is measured using the three-category model of the occupational class presented in one version of the National Statistics Socioeconomic Classification (NS-SEC), which was developed from a widely used and reliable measurement of social class, known as the Goldthorpe Schema (Erikson & Goldthorpe 2010). This study uses a version of the NS-SEC, which presents a three-category model of occupational class: professional and managerial (high class), intermediate (middle class), and routine and manual (low class). We also included a range of control variables, which were shown in previous studies to be related to time use patterns (Chatzitheochari & Arber 2012; Powell & Craig 2015). These include age, gender, logged household monthly income, the presence of children under 16, and general health status.

Analytic approach

This study first uses descriptive statistics to explore respondents’ time use patterns by different types of flexible schedules. Following the majority of previous studies on time use (Kan 2008; Powell & Craig 2015), this study then uses Ordinary Least Squares (OLS) regressions to examine the effects of different types of flexible schedules and the potential moderating effects of occupational class and gender. Three-way interaction terms are also added to the models to examine the intersection between occupational class and gender. All the models have passed the tests for multicollinearity (the VIF scores of all the variables in the models are smaller than 5). All analyses are weighted to take into account the complex survey design.

Results

Descriptive statistics

Table 1 presents the results of the weighted descriptive analyses. Overall, we find that 69% of the respondents did not use any flexible schedule, and there are 23% and 8% of the respondents who used limited and unlimited flexible schedules respectively. Regarding time use patterns, we find that those using flexible schedules, regardless of type, tend to spend less time on paid work and personal care, spend more time on unpaid work, and tend to have more free time. In addition, respondents with different statuses of flexible schedules also have different demographic and socioeconomic characteristics. For example, male respondents who have older age are more likely to use unlimited flexible schedules. In addition, respondents with a higher occupational class are more likely to use limited flexible schedules. Finally, respondents using both types of flexible schedules tend to have higher household incomes than those who did not use any flexible schedules. Given these demographic and socioeconomic differences, it is crucial to take into account these factors in the multivariate regression analyses.

Effects of different flexible schedules on daily time use patterns

Table 2 displays the results of a series of multivariate linear regressions predicting the effects of different flexible schedules on the amount of time respondents spent on various activities over a weekday. Model 1 in Table 2 indicates that those who used limited flexible schedules spent significantly less time in paid work than those who did not use any flexible schedule (coefficient = −17.32, SE = 8.58, p < 0.05). By contrast, although the effect of unlimited flexible schedules on paid work time in Model 1 is negative, it has a large standard error and is not statistically significant (coefficient = −28.99, SE = 15.21). Next, Model 2 in Table 2 indicates that while using limited flexible schedules is not associated with significantly longer time spent on unpaid work (coefficient = 2.95, SE = 4.36), those who used unlimited flexible schedules spent significantly more time on unpaid work (coefficient = 16.70, SE = 7.03, p < 0.05). In addition, Model 3 in Table 2 indicates that both limited and unlimited flexible schedules had no significant impact on the amount of time respondents spent on personal care activities. Finally, Model 4 in Table 2 indicates that employees who used limited flexible schedules had more free time than those who did not use flexible schedules (coefficient = 16.53, SE = 8.37, p < 0.05). By contrast, using unlimited flexible schedules had no significant impact on employees’ free time (coefficient = 16.79, SE = 13.54). Regarding the effects of control variables, analyses in Supplementary Table A1 in the appendix show that women have shorter paid work time, longer unpaid work and personal care time than men. Parents of children under 16 tend to have longer unpaid work, less paid work, and less free time than non-parents. Respondents with an older age tend to spend longer time on unpaid work and free time activities. Those with higher incomes have longer paid work time and shorter unpaid work time. Finally, those with poor health status have shorter paid work time and longer free time.

Table 2 Ordinary Least Squares (OLS) regressions predicting the effects of different flexible schedules on the time quantity of each main activity on one weekday.
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Occupational class and gender differences

Furthermore, this study investigates the potential moderation effects of occupational class and gender. As shown in panel A of Table 3, Model 1 and Model 4 report significant interactions between limited flexible schedules and high occupational class. This indicates that compared with workers from the low occupational class, the use of limited flexible schedules is more likely to reduce the working time (coefficient = −52.79, SE = 23.04, p < 0.05) and increase the free time (coefficient = 64.39, SE = 23.03, p < 0.01) for workers from the high occupational class. By contrast, as shown in Model 2 to Model 3, no evidence suggests the significant moderation effects of occupational class on the impacts of both limited and unlimited flexible schedules on employees’ time spent on unpaid work and personal care. Surprisingly, as shown in panel B of Table 3, gender has no significant moderating effects on the impacts of both limited and unlimited flexible schedules on employees’ time use, regardless of activity types.

Table 3 Ordinary Least Squares (OLS) regressions predicting the interaction effects between flexible schedules and occupational class (panel A); effects between flexible schedules and gender (panel B).
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Next, the study further investigates the moderation effects between gender, occupational class and limited flexible schedules on time use. Specifically, Table 4 presents the interaction effects between occupational class and limited flexible schedules on paid work and free time for men and women. Model 1 and Model 2 in Table 4 indicate that occupational class significantly moderates the effects of limited flexible schedules (rather than unlimited flexible schedules) on male employees’ paid work (high class: coefficient = −95.76, SE = 27.91, p < 0.001; middle class: coefficient = −109.43, SE = 40.16, p < 0.01) and free time (high class: coefficient = 112.96, SE = 30.52, p < 0.001; middle class: coefficient = 85.81, SE = 37.87, p < 0.05). Specifically, these patterns suggest that compared with male employees in the low occupational class, those in the middle or high occupational class who use limited flexible schedules are more likely to work shorter hours and have longer free time. In contrast, as shown in Model 3 and Model 4, the moderation effects of occupational class on the impacts of limited flexible schedules are not significant among female employees. Further analyses in Supplementary Table A2 show that the interaction effects between occupational class between limited flexible schedules are generally not significant on unpaid work and personal care for both men and women. One exception is that compared with men in the low occupational class, using unlimited flexible schedules is associated with less unpaid work for men in the middle occupational class.

Table 4 Ordinary Least Squares (OLS) regressions predicting the interaction effects between occupational class and flexible schedules with gendered samples (paid work and free time).
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Given the gender-differentiated patterns in the interaction effects between occupation and limited flexible schedules, further analyses in Supplementary Table A3 in the Appendix shows that the three-way interactions between limited flexible schedules, gender and occupational class are significant for free time (coefficient = −90.71, SE = 43.42, p < 0.05) and paid work (high class: coefficient = 73.02, SE = 42.44, p < 0.1; middle class: coefficient = 98.61, SE = 53.33, p < 0.1). By contrast, for time use in other domains (e.g., unpaid work and personal care), most effects of flexible schedules do not significantly vary across gender and occupations (see Supplementary Table A2 in Appendix). No evidence suggests significant three-way interactions between flexible schedules, gender and occupational class among the impacts of any type of flexible schedules on unpaid work and personal care (see Supplementary Table A3 in Appendix).

To better understand the interaction effects between limited flexible schedules, gender and occupations on paid work and free time, we plotted the marginal effects in Fig. 1 (paid work) and Fig. 2 (free time). For paid work time, the left-side panel of Fig. 1 shows that male employees in the middle and high occupational classes who use limited flexible schedules tend to spend significantly less time on paid work than those who do not use flexible schedules. On the contrary, among male employees in the low occupational classes, those who use limited flexible schedules tend to spend more time on paid work than those without flexible schedules. However, the right-side panel of Fig. 1 shows that female employees’ paid working time generally does not vary with flexible schedules across different occupational classes. Nevertheless, women working in high occupational classes tend to have much longer working time than those from lower classes, suggesting that occupational class rather than flexible schedules play a more important role in shaping employed women’s working time.

Fig. 1
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The gender differences in the moderation effects of occupational class (paid work).

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Fig. 2
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The gender differences in the moderation effects of occupational class (free time).

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For free time, the left-side panel of Fig. 2 shows that male employees from the high and middle occupational classes who use limited flexible schedules report significantly more free time when compared to those who do not use flexible schedules. However, this trend is reversed for male employees in the low occupational classes. As for females, as shown on the right side of Fig. 2, we find that female employees’ free time varies very little with flexible schedules across different occupational classes. Again, women working in higher occupational classes tend to have much less free time than those from lower classes, suggesting that it is the occupational class rather than flexible schedules that primarily shapes employed women’s working time.

Discussion and conclusions

In recent years, the rise of flexible work schedules has stimulated extensive debates over whether flexible schedules facilitate the balance between work and non-work time or instead lead to longer working hours (known as the ‘flexibility paradox’). Using nationally representative time use data in the UK (2014–2015), this study contributes to the debates by exploring how different types of flexible schedules shape employees’ time spent on paid work, unpaid work, personal care and free time activities across different gender and occupational groups. Overall, this study has yielded the following important findings.

Firstly, this study finds that employees who use limited flexible schedules tend to spend significantly less time on paid work and have more free time, while employees who use unlimited flexible schedules tend to spend significantly more time doing unpaid work. These patterns contradict the arguments from the traditional JDC model (Karasek 1979), which predicts that a higher degree of schedule flexibility prevents employees’ time scarcity and ‘flexibility paradox’ issues. Instead, we find that using unlimited flexible schedules does not significantly reduce paid work time and increase free time due to large standard errors. This suggests that employees using unlimited flexible schedules are likely to be a heterogeneous social group and are more likely to experience the ‘flexibility paradox’ in the domain of unpaid work. Thus, our results are generally consistent with the temporary regularity thesis in the sociology of time (Hassard 2017; Zerubavel 1979) and work-life borders theory (Clark 2000). This suggests that placing a limit on the degree of schedule flexibility may help employees achieve better work-life balance in terms of reducing paid work time and increasing free time, highlighting the importance of maintaining a stable time rhythm in social activities and a relatively clear temporal boundary between work and non-work domains.

Secondly, we find that the time use consequences of flexible schedules vary alongside intersecting axes of gender and occupations. Regarding gender differences, we find that the use of flexible schedules, regardless of type, does not change the traditional gender labour division in paid work and unpaid work, where men have more paid work and women have more unpaid work (Kan & Laurie 2018; Risman 2004). These gendered patterns are generally consistent with the doing gender theory (rather than time availability theory), which argues that the persistent traditional gender norm shapes the way in which men and women use flexible schedules (West & Zimmerman 1987). While men are more likely to use the time saved from flexible schedules for work-related purposes, women tend to use flexible schedules for family-related purposes (Chung 2022; Lott and Chung 2016). Thus, the strong traditional gender norm generally maintains the gender inequalities in time use.

Regarding occupational differences, we find that using limited flexible schedules polarises the time use patterns in paid work and free time between higher and lower occupations for men. Specifically, while men in higher occupations benefit most from limited flexible schedules (i.e., less paid work and more free time), those from lower occupations are most likely to be exploited by these flexible schedules (i.e., more paid work and less free time). Compared with those working in managerial and professional occupations, employees in the lower occupational classes have less bargaining power (Dumont et al. 2012), less job security, and face higher risks of underemployment (Inanc 2018), and thus are more likely to work long hours and have less free time (Chatzitheochari & Arber 2012). However, these patterns only exist among male employees using limited flexible schedules rather than unlimited flexible schedules, again highlighting the importance of distinguishing between different types of flexible schedules and their different implications across gender and occupational groups.

In addition, this study has some limitations, which could be potential directions for future studies. Firstly, the study only explores employees’ time use patterns on weekdays, which are relatively stable and predictable. Future could profitably examine the time use patterns of employees’ flexible schedules at weekends or holidays, which could provide a more comprehensive understanding of the impact of flexible schedules on employees’ time use and other outcomes such as health and wellbeing (Wang & Li 2019; Gong et al. 2021a; Gong et al. 2021b). Secondly, there are many other dimensions of flexible schedules (i.e., formality, schedule irregularity and place mobility), which have not been measured appropriately and considered in the analysis of the impacts of flexible schedules (Kossek et al. 2004). Future studies can further examine such a series of dimensions of flexible schedules as predictors or moderators of the relationships between flexible schedules and time use. Thirdly, due to data limitations, this study focuses on the effects of flexible schedules on individual-level time use patterns. However, a growing body of research highlights the linked lives between different family members within households (e.g., couples). Thus, future research could examine the cross-over effects of flexible schedules on time use patterns across different family members (Kim et al. 2019), which could further advance our understanding of the social consequences of flexible schedules. Finally, this study elucidates the relationship between flexible work schedules and the balance of work/non-work time, providing key insights into patterns of energy consumption by employees (such as commuting and electricity use). However, since the study’s focus is not on energy consumption, the discussion about how socioeconomic factors influence energy consumption is rather absent. Following the latest relevant studies on time use and energy consumption (Lőrincz et al. 2022, Lőrincz et al. 2021), future studies can further explore how flexible work schedules link to the formulation of more effective energy policies. It is also worth noting that, during the Covid-19 pandemic, remote work became prevalent, potentially influencing workers’ time use patterns and energy consumption. However, the time-use survey conducted during the Covid-19 pandemic in the UK does not include workers’ flexible working arrangements. Future studies could expand our findings by considering the combination of remote working and flexible schedules in the analyses and by using data collected during the Covid-19 pandemic in other countries.

These weaknesses should not, however, overshadow the study’s main contributions to our understanding of the consequences of flexible working on time use disparities across socio-demographic groups. Overall, we found that flexible schedules are primarily beneficial to men in higher occupational groups in terms of paid work and free time when placing a limit on schedule flexibility. Therefore, the use of limited flexible schedules, rather than promoting a gender convergence in the division of paid and unpaid work, further reinforces the lower occupational classes workers’ disadvantaged position in the labour market and their risks of free time scarcity. Despite the UK government keep promoting flexible working policies during the last decades, this study identifies the social inequalities emerging during the implementation of flexible working policies, a consequence of the policy process neglecting the diverse challenges and disadvantages confronted by various societal groups. Furthermore, the policy’s implementation presents stark variations across different industries and organisations, being significantly constrained by sector norms and organisational culture. Policymakers should target these inequities specifically by encouraging sectors with lower-income jobs to offer more social support and skills development opportunities, and promoting shared parental leave to reduce gender disparities (Wang & Lu 2022; Wang & Morav 2021). Additionally, ongoing evaluation and policy adjustment are essential to prevent the exacerbation of inequality during policy implementation.

Taken together, these findings shed valuable light on the unintended consequences of flexible schedules on employees’ time use patterns, highlighting the importance of considering variation between different degrees of schedule flexibility and its intersection with gender and class. Policymakers should consider such nuanced effects of flexible schedules on time use across social classes and gender and revisit the variation between different degrees of schedule flexibility when promoting flexible schedules.