Effects of Leave Utilization on Employee’s Autonomy Satisfaction: The Moderating Role of Leave Quality
Department of Human Resource Management, University of Groningen Faculty of Economics and Business
Abstract
The present research investigated the effects of leave utilization on autonomy satisfaction, and whether leave quality acted as a moderator in this relationship. Potential predictors (i.e., person-level characteristics, job characteristics and social context composed of perceived fairness and conflict over leave) were examined to predict leave utilization. A field experiment was
conducted among 579 Dutch employees over the course of five months. The experimental group received unlimited leave, while the control group kept their regular leave policy (i.e., a legal amount of leave days per year based on the contractual work hours). Employees completed monthly online questionnaires and a selected group (N = 20) participated in qualitative
interviews. Monthly survey data was collected from January (T1) till May (T5). The quantitative data was analyzed using hierarchical regression analyses. Contrary to our hypotheses, the results indicate that leave utilization did not predict autonomy satisfaction and leave quality did not act as a moderator in this relationship. Leave was utilized in longer stretches and in shorter
durations, with an average of four leave days. Employees with children utilized more leave days and employees with a higher educational background utilized leave in longer stretches. Future research should further examine potential predictors when implementing unlimited leave
policies. The theoretical and practical implications highlight the importance of the hindrances for effective policy utilization. These impediments should be considered when implementing
unlimited leave policies within organizations.
Keywords: leave utilization, autonomy satisfaction, leave quality, perceived fairness, conflict over leave
Effects of Leave Utilization on Employee’s Autonomy Satisfaction: The Moderating Role of Leave Quality
Gradually, more companies are experimenting and implementing various forms of unlimited leave policies (ULPs). Particularly high-tech companies, such as Netflix and Sony Electronics have implemented ULPs successfully (Netflix, n.d.; Glassdoor, 2020). Managers and employees talk favorably about these policies, however there are potential barriers that disrupt the utilization and effectiveness of ULPs. The underutilization and ineffectiveness of ULPs contradicts the intended objective of these policies, which is to benefit employees' health and well-being. Examining both the outcomes and predictors of leave utilization is valuable for employees and organizations to ensure effective utilization. The innovativeness of our research lies in understanding the impediments of the utilization process of leave uptake. Specifically, the novelty stems from gaining insight into employee’s characteristics and their social context in determining how leave is utilized. In addition, this paper adds insight into the effects of employee’s leave utilization on their psychological needs’ satisfaction.
The present research examined leave utilization between employees experiencing the right to unlimited leave, compared to employees under a regular leave policy. Under the
unlimited leave policy, employees have an unlimited amount of paid leave days. In contrast, the regular leave policy entails that employees receive a legal amount of paid leave days per year. In the Netherlands, this is translated into four times the number of hours worked per week
(Ministerie van Sociale Zaken en Werkgelegenheid, 2019). Although unlimited leave is central to this research, for the scope of this paper, the focus lies on how employees utilize their leave.
explore whether employees’ disengagement and recovery from work strengthens the relationship between leave utilization and autonomy satisfaction. Research examining the effects of vacation utilization, work-life policies (WLPs) and flexible work arrangements (FWA) policies is
explored to evaluate potential predictors for the utilization of leave. The potential predictors examined in relationship with leave utilization include person-level characteristics, job
characteristics and employee’s social context (i.e., perceived fairness and conflict over leave). This proposes three research questions that will be addressed in this paper: 1) What is the effect of leave utilization on autonomy satisfaction? 2) Is this relationship moderated by leave quality? and 3) What factors predict employees leave utilization?
Using a field experiment with five measurement points over the course of five months, the study aimed to identify how employees from a Dutch bank utilized their (unlimited) leave. Employees were tracked through monthly questionnaires. In the following, the potential effects of unlimited leave and vacation utilization are outlined. Afterwards, recent findings of unlimited leave will be examined. Next, utilization will be defined followed by proposed factors involved in the utilization of unlimited leave. Throughout the paper, research on FWA policies and WLPs is examined to understand possible factors hindering leave utilization.
The Effects of Unlimited Leave
vacation and leisure time. It is a new area of flexibility that gives employees a high degree of autonomy to manage their own time in days and hours without any restrictions. Unlimited leave contrasts with the norm of static and rigid working hours, days and limited leisure time.
Important in this policy is that the employer signals trust, as the employee receives full control over their paid leave. Although employees are given a high degree of autonomy, the boundary condition and expectation is that their performance does not deteriorate (Allen & Russell, 1999).
Little research has been conducted about unlimited leave policies. Companies that have implemented this policy have usually reported beneficial organizational outcomes. For instance, Expand Research - a UK based consultancy agency - found that employee turnover had
decreased by 10%, average sick leave reduced by 50% and sales grew by 52% (Recruiter, 2017). Moreover, Glassdoor (2017) found that in the US, unlimited leave policies were the second most important determinant for retention and recruitment, in comparison to health insurance and retirement plans. Additionally, Kronos found that engagement numbers increased from 84% to 87%, a year after the policy was implemented. Moreover, employees’ voluntary turnover dropped from 6.4% to 5.6% (Ain, 2017).
Although there are beneficial outcomes, ULPs may have various restrictions to the implementation. Employees can perceive a high degree of ambiguity, which can intensify employees' pressure to work (White, Hill, McGovern, Mills & Smeaton, 2003). This ambiguity may lead to negative employee responses and minimize the policy utilization, which may trigger higher stress and strain. Additionally, the team's perspective is important to consider when examining who is eligible for the policy and the potential consequences. Moreover,
boundary conditions need to be considered to advance current literature on the driving factors that stimulate employees to utilize ULPs (Glassdoor, 2020).
The Effects of Vacation
Examining the effects of vacation can give further understanding about the possible positive and negative effects of unlimited leave. Vacation is defined as time off the job, lasting several days or weeks (Lounsbury & Hoopes, 1986). Legislation in the European Union supports the notion of taking vacation and requires employers to offer at least four weeks of paid holiday (European Union, n.d.).
Longer periods of off-job time may give different effects on health and well-being than regular days off. Previous research has indicated that recovering from work demands during regular evening hours and weekends is not sufficient (Fritz & Sonnentag, 2005; van Hooff, Geurts, Kompier & Taris, 2007). De Bloom et al. (2010) found that employees experienced more positive moods, higher satisfaction and lower tension during vacation compared to regular working weeks.
Vacation such as intended with ULPs, have been shown to have positive effects on well-being such as lower levels of job stress and burnout (Etzion, 2003), improved physical and mental health (Fritz & Sonnentag, 2006), and improved life-satisfaction (Dolnicar,
Yanamandram & Cliff, 2012). It is therefore critical that individuals are able to recover from work demands by taking enough vacation to protect their health and well-being. In turn, this should be promoted by organizations and utilized by their employees.
Unlimited Leave Utilization
Across a variety of industries, only 68% of US employees had utilized their required vacation days (Society for Human Resource Management, 2017). A recent survey found that those that received paid time off only took 51% of their legal vacation time and 61% of employees still admitted doing work while being off (Glassdoor, 2014). This emphasizes the importance and relevance in examining the utilization of ULPs.
Previous research has not explicitly distinguished between availability and actual
utilization, in relation to flextime (Allen, Johnson, Kiburz & Shockley, 2013; Kelly et al., 2008). Availability in terms of flextime, refers to employee’s control over their working hours. This gives employees the freedom to deviate from the static nine-to-five working days by adjusting their start and end times according to their needs (Kattenbach, Demerouti, & Nachreiner, 2010; Spieler, Scheibe, Stamov-Roßnagel & Kappas, 2017). Generally, it is assumed that employees will use the flexibility that is provided to them by the organization. However, this is tailored per individual as their individual preferences, family responsibilities and coordination with
colleagues may prevent utilization (Spieler et al., 2017).
successful utilization consists of long and frequent stretches of leave, while shorter and less frequent leave is considered to be less effective to recover from job demands. Therefore, the longer the leave duration and the longer the stretches, the more benefits are expected for an individual’s health and well-being.
Concerning recovery time and utilization, research on vacation duration and frequency is still unclear. Previous research did not find differences in stress and burnout between individuals that took shorter versus longer vacations (more than ten days) (Etzion, 2003). Additionally, Lounsbury and Hoopes (1986) found that the duration of vacation did not contribute to
individuals post-vacation measurements (i.e., job involvement, job satisfaction, life satisfaction, turnover intention and organizational commitment). Moreover, no differences were found in happiness levels for individuals that took shorter vacations of approximately seven days (Kemp, Burt & Furneaux, 2008). Furthermore, having a single short-term vacation of four days was found to have positive and immediate effects on recovery. This effect was sustained up to thirty days post vacation (Blank et al., 2018). This concludes that the effects on recovery were found to be positive for both shorter and longer leave. However, it can be argued that below a certain number of leave days recovery is insufficient.
Organizational policies provide employees with structure (Kirby & Krone, 2002). However, employee’s interpretation and interaction processes can impede the utilization and effectiveness of specific policies targeted to improve their health and well-being. A policy’s organizational, interpersonal and public discourse impact both the structure and implementation. The combination of personal characteristics and environmental factors may contradict or
unlimited leave (Kirby & Krone, 2002). Taking a rational choice perspective, employees behave rationally and weigh the costs and benefits of alternatives of taking leave given the information they have (den Dulk & de Ruijter, 2008). Especially, the costs of taking leave can disrupt the utilization process as employee’s might feel guilty about taking leave when considering their team members. The feeling of guilt arises because their tasks and responsibilities during their leave are shifted towards their team. Therefore, employees' workload might enhance the costs of taking leave and hinder the utilization process. The perceived costs felt by employees act as a potential explanation why their leave is underutilized (Budd & Mumford, 2006).
Unlimited leave can be seen as a form of FWA. FWA refers to employer provided benefits that allow employees to control where, when and how long employees spend on their work-tasks (Hill et al., 2008). Interconnected with FWA are work-life policies or family-friendly policies that specifically target employee’s imbalance in their work and private domain to
minimize role conflicts. These policies fall into five broad categories to improve work-life balance: flextime work schedules, flexplace or telecommuting, job-sharing, part-time flexplace and sabbaticals or career breaks (Downes & Koekemoer, 2011). Similar to ULPs, the objective is to improve employee’s work-life balance and their well-being. These policies are designed to enhance employee’s needs by balancing the demands between work and personal life. The examination of the effects and utilization of these policies will be further discussed in the sections below.
Effects of Leave Utilization on Autonomy Satisfaction
employees “...need to experience a sense of volition and psychological freedom...” (Gillet, Morin, Choisay & Fouquereau, 2019, p.113). Specifically, autonomy satisfaction is the extent to which employees feel that their need to be autonomous is fulfilled through the choices, decisions and freedom experienced (van Hooff & Geurts, 2015). This in turn acts as an energetic personal resource that can promote employee’s well-being (Deci & Ryan, 2000).
Resources that are replenished during work hours are built upon during vacation, where psychological needs are fulfilled (Kujanpää et al., 2020). Self-determination theory (Deci & Ryan, 2000) states three basic innate psychological needs (i.e., autonomy, relatedness and competence) that enhance individuals well-being and growth. For the scope of this paper, the focus lies on the need for autonomy. Additionally, the structuration theory (Giddens, 1984) argues that an individual's autonomy is influenced by structure, which is maintained and adapted through the exercise of agency such as in ULPs.
Positive effects have been found when providing employees with more autonomy over their work arrangements. Flexible and autonomous working schedules, help synchronize
employees' life domains (Felstead, Jewson, Phizacklea & Walters, 2002). Autonomous working schedules seem to have a positive effect on work-life balance, improved mental health, and reduced work-life conflicts (Russell, O’Connell, & McGinnity, 2009; Gregory & Milner, 2009). Moreover, flextime has found to increase the perceived control in both work and home domains (Hsu, Chen, & Shaffer, 2019). This in turn, might lead to higher levels of autonomy satisfaction. Although research is limited in examining employees' need fulfillments after policy
Depending on the frequency and duration of leave employees might experience varying levels of autonomy satisfaction. Greater levels of satisfaction in autonomy have been shown to improve self-esteem and psychological health (Ilardi, Leone, Kasser & Ryan, 1993). It is expected that employees who utilize leave will experience higher autonomy satisfaction in comparison to employees not utilizing their leave. Additionally, more autonomy satisfaction is expected when employees utilize leave more and in longer spans to ensure better recovery from their work demands to satisfy their needs.
Overall, autonomy satisfaction has been found to be beneficial for individuals well-being. Therefore, when policies are implemented that supposedly provide a high degree of autonomy it is interesting to examine whether individuals indeed feel greater autonomy satisfaction
depending on their utilization of leave.
Hypothesis 1: Employees will experience more autonomy satisfaction when reporting more leave utilization (i.e., more frequent and longer leave) (see Figure 1).
The Moderating Role of Leave Quality
Depending on how employees utilize their leave, they will perceive various levels of autonomy satisfaction over time. How employees perceive their leave quality can induce a strengthened or weakened effect on their perception of autonomy satisfaction. Therefore, leave quality will be examined as a potential moderator to affect employee’s well-being and health during times of leave.
mental disengagement and no longer being psychologically occupied with work-related matters (Wendsche & Lohmann-Haislah, 2016). Specifically, psychological detachment emphasizes that individuals should mentally distance themselves from their work demands (Sonnentag & Bayer, 2005). An employee’s detachment from work during non-work hours enhances employee’s recovery (Wendsche & Lohmann-Haislah, 2016). Individuals are able to benefit more from leisure time when they are able to mentally switch off, which leads to a better mood and less fatigue (e.g., Sonnentag & Bayer, 2005).
It is important that individuals recover during their leisure time for one’s own well-being and health. The importance of fully disconnecting from work is a challenge when employees take leave (Glassdoor, 2014). Glassdoor’s Employment Confidence Survey examined US employees vacation time. A quarter of employees (24%) reported that co-workers contacted them or were contacted by their boss (20%), while others (17%) report difficulty in detaching from work (Glassdoor, 2014). Employee’s that experience feelings of being “always on” experience higher stress levels and work-life conflicts (Allen et al., 2013; Butts, Becker & Boswell, 2015; Perlow & Porter, 2009).
expected that mental disengagement and recovery is greater in employees that utilize ULPs in longer and frequent spans of leave.
Hypothesis 2: Leave quality (i.e., not working, psychological detachment and low need for recovery) will positively influence the relationship between leave utilization and autonomy satisfaction (see Figure 1).
Effects of Person-Level and Job Characteristics on Leave Utilization
Employees may consider whether taking leave is beneficial depending on their person-level characteristics and their job characteristics. Whether an employee has children, is highly educated, and whether they are male, or female can influence their need for leisure time.
Additionally, job characteristics (i.e., contractual hours, contract type, organizational tenure, job tenure and initiated interdependence) can influence whether employees are able to take leave, are comfortable taking leave and to what degree they can utilize leave.
Previous research has found that employees do often not use all of their vacation days due to the demographic and job characteristics (Fakih, 2018; Hilbrecht & Smale, 2016). Specifically, research found that employees who are older (Fakih, 2018; Hilbrecht & Smale, 2016), male (Maume, 2006), not married or living with a spouse (Altonji & Usui, 2007; Fakih, 2018; Hilbrecht & Smale, 2016), without children (Hilbrecht & Smale, 2016), and have lower socioeconomic status (i.e., higher income and/or educational background) (Hilbrecht & Smale, 2016) usually utilize fewer vacation days.
relationship between needs and flexible work arrangements use. WLP utilization found that men, mothers with a career focus, and employees without a spouse underutilized WLPs (Bailyn, Fletcher & Kolb, 1997).
Furthermore, employees who work longer hours had underutilized vacation, while employees with a longer job tenure utilized more vacation (Maume, 2006). Research on FWA has found employees tenure, supervisory responsibilities and perceptions of the workgroup composition to predict utilization (Lambert, Marler & Gueutal, 2008). These person-level characteristics and job-related factors will be examined in an explorative fashion to understand their effects on leave utilization.
Exploratory Hypothesis 3: Person-level characteristics (i.e., age, gender, family status, children, educational level) affect the utilization of leave (see Figure 1).
Exploratory Hypotheses 4: Job characteristics (i.e., contractual hours, contract type, organizational tenure, job tenure and initiated interdependence) affect the utilization of leave (see Figure 1).
Effects of the Social Context on Leave Utilization
Perceiving fairness refers to the beliefs that employees hold about how they are treated in relation to others (Wilkinson, Tomlinson & Gardiner, 2018). Organizational justice is the
foundation for fairness, in which there is distributive justice, interactional justice and procedural justice. Specifically, distributive justice focuses on how individuals evaluate the allocation of resources as fair (Wilkinson, Tomlinson & Gardiner, 2018). When a particular set of individuals utilize unlimited leave more enthusiastically than others, it may lead to inequity and negative perceptions of team members. Employees may feel that they are being treated differently when taking less or more leave than their team members, which affects their perception of fairness.
When resentment is felt by the individual taking leave, they might feel discouraged to take leave. Particularly, this resentment is present when coworkers feel they are having to do extra work while a colleague is on leave. Therefore, to ensure their colleagues have a fair workload (compared to themselves), individuals may weigh whether taking leave is beneficial and fair to their team (Peper et al., 2014).
To our knowledge, little research has examined the effects of conflicts arising due to leave and its impact on leave utilization. Conflicts over leave can arise when multiple team members want to take leave at the same time and the distribution of leave between team
members is disagreed upon. Contradictory to conflict, research has emphasized the importance of support in successful FWA implementation. Previous research has found supervisor support to be important in decreasing work-to-leisure conflicts (Wong & Lin, 2007). Moreover, supervisor support increases perceptions of successful FWA implementation (Lee, MacDermid, Williams, Buck & Leiba-O’Sullivan, 2002). Furthermore, coworker support is important in fostering the utilization of FWA, as it provides employees with assurance and understanding about their needs (Clark, 2002). Thus, when employees experience more conflict with their supervisor and
colleges it is expected to lower their leave utilization. Overall, employees' social context determines whether taking leave is perceived to be fair and whether conflicts over leave influence whether employees utilize their leave and to what extent.
Hypothesis 5: Employees scoring higher on perceived fairness will utilize leave more than employees scoring lower on perceived fairness (see Figure 1).
Hypothesis 6: Employees scoring higher on conflicts over leave, will utilize leave less than employees scoring lower on conflicts over leave (see Figure 1).
Figure 1
Method Design and Procedure
The data is derived from a controlled trial in a Dutch bank. Half of the participants were assigned to the experimental group which received unlimited leave for the duration of one year. The other half constituted of the control group for which leave policies remained the same throughout the year. The regular leave policy entails that employees who work an average of 36 hours per week receive 194,4 vacation hours per year (i.e., 144 hours are statutory holidays and 50.4 hours are non-statutory hours) (CAO Bank1). The bank used an internal recruitment
procedure (i.e., team leaders were contacted and asked to take part in the research, in which 54% agreed to allow their employees to take part). Therefore, true randomization was not possible due to organizational constraints. Quantitative data was collected via online questionnaires, and monthly assessments over the course of one year. The present research concerns a shorter period of examination, having data points monthly for five consecutive months (January till May 2020). Variables considering leave were measured after the baseline measurement in January and therefore range from February till May. The monthly online questionnaires were conducted via the Unipark/Questback platform. Additionally, face-to-face qualitative interviews were
conducted with a subgroup (N = 20) of participants from the experimental group in January, April and August of 2020. However, for the scope of this paper the focus will be on quantitative data.
Participants
The sample consisted of an experimental group (N = 290) and a control group (N = 289). The experimental group consisted of participants working under the unlimited leave policy,
while the control group included employees under a regular leave policy. Small differences were found between the two groups. Firstly, there was a difference in organizational tenure for the experimental group (M = 140.80, SD = 118.97) and the control group (M = 179.72, SD = 141.38); t(336.45) = -2.89 p =.00, equal variances not assumed. Secondly, a difference was found in age between the experimental (M = 41.59, SD = 9.90) and control group (M = 45.11, SD = 10.87); t(388) = -3.34 p =.00, equal variances assumed. Furthermore, more males were
included in the control group (69.2% among the experimental group and 77.5% among the control group). The remaining percentages were females (30.8% among the experimental group and 22.5% among the control group).
When combining the experimental and control group, employees (72.9% males, 27.1% females) had a mean age of 43.16 years (SD = 10.48). The general response rate fluctuated per variable (N = 334 - 491). Of the total sample, 83.9% lived with a spouse/partner and or had a child/children and 16.1% lived by themselves. The majority of respondents was highly educated (48.1%) and had received an academic education or a PhD or higher (24.9%), followed by medium educated (16.2%) and the minority were lower educated (1.3% had completed only a middle vocational education and 9.5% a high school diploma). Regarding their tenure, the average number of months employees worked in the organization was 158 months, and an
and ‘agree’ (24%), the remaining percentages did not think other jobs dependent directly on their job ranging from neutral position to disagreeing with the statement (41.7%).
Measurements
Leave utilization. Participants were asked about their leave duration (e.g., “How many
days leave did you take off from work?”). Leave duration per person was calculated by summing the average time points of days taking off from work for the period from February till May. Leave frequency was assessed by asking respondents to select their leave based on the following question: “How have you distributed your leave across the last four weeks?”. The scale for leave frequency was recoded into three categories after correcting the original fourth category ‘other’. Leave frequency was ordered ranging from shorter stretches of leave to longer stretches: “All days of leave in one long stretch”, “"Several shorter stretches of leave across the month or a longer stretch and several shorter stretches of leave" and “A few hours of leave here and there”. The average was calculated by averaging each time point (T2-T5) using the recoded leave frequency.
Autonomy satisfaction. Need satisfaction items were used from the Basic Psychological
Leave quality. Participants were assessed on their leave quality by evaluating three items
from a self-developed scale. Participants responded to a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Participants were asked to evaluate three statements associated with the three characteristics: working during leave (“Did you engage in work-related activities such as reading and answering emails during your leave?”), not thinking about work during off-time (i.e., psychological detachment) (“Did you disengage from work-related thoughts during your leave?”) and low need for recovery (“I felt recovered after my leave”) (Geurts & Sonnentag, 2006; Wendsche & Lohmann-Haislah, 2016). Item one was recoded and reversed to ensure that all items were positive on the scale. Afterwards, the items were combined and averaged per time point ranging from February till May. An overall leave quality average was computed where all average time points were combined (α =.61).
Person-level and job characteristics. As potential predictors, person-level characteristics
Social context. Social context was composed of two variables (i.e., perceived fairness
and conflict over leave). One item was used to measure perceived fairness using a self-developed scale. Respondents were asked to evaluate the following statement “My team distributes leave fairly across the team members.” They evaluated the item on a 5-point scale ranging from 1 ((strongly disagree) to 5 (strongly agree). The item was averaged across five measurement points to compute an overall average of perceived fairness. Respondents answered three
statements to determine their conflict over leave. Conflict over leave was measured using a self-developed scale. Participants were asked to evaluate statements about their leave across their team and manager using a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). This was measured using three items: “My team quarrels about leave (e.g., who can take leave and when)”, “My manager struggles to distribute leave fairly across the team” and “Distributing leave leads to discussion between my manager and my team”. Five time points were averaged to compute an overall conflict over leave variable for the analysis (α = .88).
Statistical Analysis
time. Additionally, pie-charts were created for leave frequency to depict potential changes across T2 (February) till T5 (May). Next, repeated measures ANOVAs were conducted to calculate the main effects of time, and group (experimental and control group), and the group x time
interactions for leave duration, autonomy satisfaction, perceived fairness and conflict over leave. T-tests were conducted for leave frequency and leave quality to examine differences between the experimental and control group on the four measurement occasions. No systematic changes were detected; therefore, we tested the hypotheses using the combined sample and used a combined average using all time points. Direct correlations using the average values of the variables were applied to examine if there was a relationship between leave utilization (i.e., leave frequency and leave duration) and autonomy satisfaction. Additionally, correlations between the predictors and leave utilization were examined.
After the preliminary analyses, hierarchical regression analysis was conducted to test if leave utilization affected autonomy satisfaction and if leave quality moderated this relationship. In the relationship between leave utilization the interaction terms (leave quality x leave
frequency; leave quality x leave duration) were inserted into the model to test leave quality as a potential moderator. Next, two regression analyses were conducted for leave duration and leave frequency as dependent variables. Person-level characteristics, job-characteristics and social context (i.e., perceived fairness and conflict over leave) were entered separately as independent variables to determine whether these between-person variables could predict leave utilization.
Results Preliminary Analysis
Differences across time between the experimental and control group. Before testing the
hypotheses, differences between the two groups are displayed in Appendix A. Leave duration and perceived fairness show a similar pattern, with a decrease from February till March,
followed by an increase in April and May. This trend is observed between the two groups, with slightly higher leave duration and lower perceived fairness reported by the experimental group. Autonomy satisfaction between the two groups show a similar pattern with a decrease from March to April, following an increase in May. Conflict over leave showed a different pattern between the two groups, in which the experimental group reported more conflict over leave compared to the control group. A stable trend is observed between the two groups for leave frequency and leave quality. The time trends displayed in Appendix A for the two groups should be interpreted with caution as the scales were not adjusted in the line graphs in order to visually detect changes. Therefore, although differences are reported between the two groups these differences are minor.
Differences across time for the combined sample. In the next step, the means reported in
the line graphs across time were examined using the combined sample (see Appendix A). A stable time trend for all variables except for leave duration was observed. Leave duration across time showed a steep decrease in leave days reported in March, followed by an increase from April onwards. No extreme patterns were observed for leave frequency from February till May (i.e., T2-T5). A similar trend could be seen where participants reported more leave in one long stretch in comparison to a few days here and there. This trend fluctuated only mildly during the months where participants tended to use more shorter stretches and or longer stretches.
Trend analyses. The analyses proceeded by examining the output of the repeated
interactions using the averaged variables for each time point. As missing data reduced the sample size due to listwise deletion, repeated measures analyses could not be conducted for leave
frequency and leave quality. Listwise deletion only included the data of employees that took leave, which reduced the sample size drastically. Therefore, for these variables the analysis was proceeded using T-tests.
Repeated measures ANOVAs showed that for leave duration, autonomy satisfaction, perceived fairness and conflict over leave the time effects were significant (Table 1). Within-subject contrasts further demonstrated that there were cubic time trends for leave duration, perceived fairness and conflict over leave. As an exception, autonomy satisfaction demonstrated an order 4 time trend, suggesting that these variables did not increase linearly over time, instead increased and leveled off. This entails that employees over time experienced fluctuations in the number of days taken off, autonomy satisfaction, perceived level of fairness and conflict over leave. Furthermore, the group effects and the group x time interaction terms for all variables were not significant. Therefore, it was suitable to combine the two groups in the analyses.
Although time effects were found to be significant to increase power in the analyses the five time points were averaged.
for each of the four consecutive measurements including the average leave quality variable (t(335)= -.05, p =.96, equal variances assumed). To sum up, it was suitable to combine the two groups and average the measurement occasions per variable.
Table 1
Repeated Measures ANOVA’s for the Effects Across Time (T1-T5), Between Groups (experimental and control group) and Group x Time Interactions for Each Variable
Variables F-value Partial Eta Squared
Group Effect Time Effect Group x Time effect Group Effect Time Effect Group x Time effect Leave Duration 2.28 13.98* .22 .01 .19 .00 Autonomy Satisfaction .43 12.17* .55 .00 .23 .01 Perceived Fairness 1.41 9.12* 1.16 .01 .20 .03
Conflict over Leave 1.6 4.44* 1.68 .01 .11 .04
Note. Measurement occasions for the differences across times were conducted using the average variables for each time period. The baseline measure (T1) was excluded for leave duration, where four measurement occasions were assessed. *p < 0.05.
Descriptive Statistics
their autonomy satisfaction. The correlation between leave quality and autonomy satisfaction is positive and weak. This suggests that when individuals experience high leave quality (i.e., not working, psychological detachment and low need for recovery) they experience higher autonomy satisfaction. Moreover, leave quality positively and weakly correlated with age and
organizational tenure, meaning that employees that are older with a longer tenure are more efficient at detaching from their work and able to recover during leisure time. Lastly, three negative and weak correlations were found between leave quality and family status, contractual hours and conflict over leave. This suggests that having a spouse and a child/children, working more hours per week and experiencing conflict over leave contribute to poorer leave quality.
Furthermore, correlations were examined between the potential predictors (person-level characteristics, job characteristics and the social context) and utilization of leave. Leave duration was positively and weakly correlated with having children, which means that employees with children took more days off in comparison to employees without children. Moreover, leave frequency correlated positively and weakly with employees' educational background. Higher educated people seem to take leave in one long stretch. Perceived fairness had a positive and weak correlation with autonomy satisfaction, suggesting that employees that perceived more fairness in distribution leave experienced more autonomy satisfaction. A negative and weak correlation was found for employees who have children on their autonomy satisfaction. Employees with children were experiencing less autonomy satisfaction. Additionally,
Table 2
Means, Standard Deviations and Zero-Order Correlations Between Study Variables (N = 334 - 491)
10. Initiated Interdependence -.03 -.19** .02 -.01 .08 .13* .03 -.08 -.10 11. Perceived Fairness -.06 .02 .05 .05 -.07 .01 -.01 -.01 .01 -.04 12. Conflict over Leave -.13* .11* -.01 .05 -.08 -.11* .06 -.13* -.04 -.07 -.30** (.88) α 13. Leave Duration .07 -.01 .10 .13* .01 .08 -.01 -.00 .06 .06 .03 -.10 14. Leave Frequency .08 -.06 .00 -.07 .12* -.00 .01 .05 -.01 -.03 -.05 .04 -.00 15. Autonomy Satisfaction -.01 -.09 -.08 -.11* -.01 .07 -.02 -.06 -.10 .05 .21** -.18** -.03 .02 (.77) α 16. Leave Quality .16** -.04 -.14* -1.06 -.07 -.17** .06 .17** .12* -.08 .03 -.13* .09 .09 .11* (.61)α aAverage Cronbach's α values displayed in parentheses on the diagonal.
Note. * p< .05 (two-tailed); ** p< .01 (two-tailed). SD; standard deviation.
Test of Hypotheses
In the following the results per hypothesis are discussed.
H1 and H2: Leave utilization predicting autonomy satisfaction and leave quality moderating the relationship between leave utilization on autonomy satisfaction. Hierarchical
regression analysis was conducted to test the relationship between leave utilization (leave frequency and leave duration) on autonomy satisfaction (Table 3). Model 1 indicates that leave frequency and leave duration did not predict autonomy satisfaction. Thus, employees' utilization of leave did not predict their autonomy satisfaction. In the next step, leave quality was examined as a potential moderator in the relationship between leave utilization on autonomy satisfaction. Model 2 indicates that the interaction terms (leave quality x leave frequency; leave quality x leave duration) did not predict autonomy satisfaction. Leave quality did not moderate the relationship between leave utilization and autonomy satisfaction.
H3: Person-level characteristics predicting leave utilization. Multiple regression
analysis was conducted for person-level characteristics predicting leave frequency and leave duration separately (Table 4). The analyses indicated that person-level characteristics did not predict leave frequency. Only education was found to be a marginally significant predictor of leave frequency (p = .06), suggesting that those that are highly educated took longer stretches of leave. Moreover, person-level characteristics did not predict leave duration. Only having children was a marginally significant predictor, with parents taking more leave days than people without children (p = .07).
H4: Job characteristics predicting leave utilization. Multiple regression analysis was
4). The analyses indicated that job characteristics did not predict leave frequency or leave duration.
H5 and H6: Social context predicting leave utilization. Multiple regression analysis was
conducted for perceived fairness and conflict over leave predicting leave frequency and leave duration separately (Table 4). It was found that perceived fairness and conflict over leave did not predict leave frequency or leave duration.
Table 3
Hierarchical Multiple Regression Analysis for Leave Utilization Predicting Autonomy Satisfaction with the Interaction Terms for Leave Quality
Model 1 Model 2
Variables B SEB β B SEB β
Leave Frequencya .01 .05 .01 .18 .19 .20
Leave Duration -.00 .01 -.01 -.03 .03 -.26
Leave Quality .06 .03 .11 .12 .11 .21
Leave Frequency x Leave Quality -.04 .04 -.26
Leave Duration x Leave Quality .01 .01 .27
R2 .01 .01
F for change in R2 1.38 .94
Note. *P < 0.05; **P <0.01.
a1 = A few hours of leave here and there, 2 = A longer stretch and several shorter sketches of leave; Several
shorter stretches of leave across the month, 3 = All days of leave in one long stretch.
B Values refer to unstandardized B-coefficients.
SEB Values refer to the standard error of unstandardized B-coefficients.
Table 4
Multiple Regression Analyses for Person-Level Characteristics, Job Characteristics and Social Context (i.e., Perceived Fairness and Conflict over Leave) Predicting Leave Utilization (N = 334 - 491)
Leave Utilization
Leave Frequencya Leave Duration
Variables B SEB β B SEB β
F .26 .94 Social Context Perceived Fairness -.04 .06 -.04 .08 .36 0.1 Conflict over Leave .03 .06 .03 -.53 .39 -.07 R2 .00 .01 F .46 1.13 Note. P* < .10, **P < 0.05; ***P <0.01.
a1 = A few hours of leave here and there, 2 = A longer stretch and several shorter sketches of leave; Several shorter
stretches of leave across the month, 3 = All days of leave in one long stretch.
b1= male, 2 = female.
c1= I live by myself, 2 = I live with my spouse/partner and/or a child/children. d1 = no children, 2 = children.
eCoded from 1 (primary education) to 7 (PhD or higher).
f1 = I have a permanent work contract, 2 = I have a temporary work contract.
β Values refer to the standardized β-coefficients from six different regression analyses entered separately with each dependent variable.
Discussion
Research on vacation has mainly focused on the relationship between leisure and well-being (de Bloom et al., 2009; de Bloom et al., 2010; Gump & Matthews, 2000; Strandberg et al., 2018). There is limited research on how employees utilize their leave. Specifically, it is unknown how employees utilize their leave when provided with an unlimited leave policy in comparison to employees with a regular leave policy. The present study investigated whether leave
perceived fairness and conflict over leave) determined how and under what conditions employees utilized leave.
Leave utilization
The results provide insight into how employees with different leave policies utilize their leave in terms of leave frequency and leave duration. Between the experimental and control group it was observed that the control group took slightly longer stretches of leave in comparison to the experimental group. However, the experimental group under the unlimited leave policy took slightly more leave days. Moreover, the range for leave duration was thirty days. This suggests that although the average duration was four days, some employees actually utilized their leave much more than others. These excessive amounts of leave days should be examined further to understand the reasons and motives for taking longer leave.
Although these differences were small this supports the aim of ULPs, as it stimulated employees with an unlimited amount of leave to take more leave days to recover from their work demands. As expected, when given an unlimited amount of leave days employees would be inclined to use more leave days. However, as previous research indicates this is affected by the perceived costs (Budd & Mumford, 2006) and the ambiguity of the unlimited nature that may intensify the pressure to work (White et al., 2003). Providing employees with a policy that is structured and clear might stimulate longer leave duration and frequency.
utilization. These results enhance our knowledge on how employees prefer to take leave, that is in longer stretches with a limited number of days off.
Leave utilization and autonomy satisfaction
The results did not support the hypothesis that leave utilization, which consists of leave frequency and leave duration, enhanced employees autonomy satisfaction. The average amount of leave days reported were approximately four days. The results suggest that the limited number of days taken off might explain why no differences were found in their autonomy satisfaction. Although previous research on leave duration is mixed, de Bloom et al. (2010) showed a similar finding that no differences were found in health and well-being after vacation for the duration of approximately nine days. This might explain that the shorter the duration, the less long-lasting the effects are when employees return back to work. Therefore, it is still unclear whether leave duration is a factor in determining whether employees feel satisfied with their level of autonomy. The post-vacation effects and the relationship with leave duration should be examined in future research.
child/children gave higher levels of stress and uncertainty. Thus, this might have affected how employees were able to satisfy their need for autonomy. These external factors might have influenced how employees utilized their leave and in turn also influenced how they felt about their leave.
Leave quality in the relationship between leave utilization and autonomy satisfaction
While, family status, contractual work hours and conflict over leave hindered employees leave quality. Having children, working longer hours and experiencing conflict over leave might impede leisure time. This suggests that potential factors could hinder or stimulate whether employees are able to successfully recover from their work demands.
Predictors of leave utilization
The hypothesis that person-level characteristics predict leave utilization was not supported. A possible explanation for the finding was that the sample included more males in comparison to females. In previous research gender is an important determinant for the
utilization of policy effectiveness (Gregory, Hofäcker & König 2013; Lott, 2014; Maume, 2006). Specifically, men report more problems with boundary management and underutilized flexible work arrangements more than women (Bailyn, Fletcher & Kolb, 1997). However, at a
correlational level education was related to leave frequency. Furthermore, having children was related to leave duration. Therefore, employees with a higher educational background tend to take longer stretches of leave and employees that have children tend to take more leave days. External factors might explain why employees take more leave when they have children. These results are according to our expectations and support previous research that found that
individuals without children (Hilbrecht & Smale, 2016), and have lower socioeconomic status (i.e., higher income and/or educational background) (Hilbrecht & Smale, 2016) utilize fewer vacation days.
whether employees' job characteristics were not influential in determining employees leave utilization. First, the organizational culture might have contributed to the utilization of leave. The average job tenure was approximately thirteen years, this suggests that employees have ingrained patterns associated with the socialization process. Their job tenure has shaped their thoughts on what is accepted and in turn how they evaluate norms based on their traditional leave policy. As stated in previous research, this might have contributed to how they perceived their control and pressure when they took more leave (Stavrou & Ierodiakonou, 2011). Furthermore, employees experiencing more job insecurity experience frustration when taking leave as they lose their control over their work and life domains (Cheng & Chan, 2008; Vander Elst, Van den Broeck, De Witte, & Cuyper, 2012). Thus, this might have influenced how they utilized their leave. Future research should examine organizational tenure and job insecurity further to determine whether these factors influence the utilization process.
Thirdly, the results did not support the hypothesis that perceived fairness predicted better leave utilization. The results indicated that perceived fairness was related to autonomy
consequences (Kirby & Krone, 2002; ter Hoeven et al., 2017), task interdependence (Parker & Allen, 2001) and managerial attitudes (den Dulk & de Ruijter, 2008).
Lastly, conflict over leave did not affect how employees utilized their leave. At a correlational level, conflict over leave related negatively to autonomy satisfaction. Employees experiencing perceived fairness and limited conflict over leave was related to a higher level of autonomy satisfaction. Previous research supports this finding that the perceived costs felt by employees affect their utilization (Budd & Mumford, 2006). Moreover, conflict over leave was higher in the experimental group in comparison to the control group. Thus, those with unlimited leave experienced more conflict. A possible explanation could be the association between the ambiguity of a new policy and employees’ organizational tenure, which was higher in the control group. Previous research has found that organizational tenure contributed to lower family-work conflict and turnover intentions (Karatepe, 2009). Therefore, the more familiar employees are with the organization and team the less conflict they might encounter. Moreover, the least amount of conflict over leave is reported in February when school holidays start in the
Theoretical Implications
The results of this study contribute to the literature in the following ways. First, the results provide insight into how employees utilized their leave, and particularly unlimited leave. To our knowledge, there is limited research examining the utilization of leave. A self-composed definition is provided and expanded upon to understand what components frame utilization. This study goes beyond existing literature by examining the boundary conditions of unlimited leave utilization. It is valuable to explore how leave is utilized and how unlimited leave can enhance employee’s well-being.
Practical Implications
The present study provides practical implications for organizations to consider when implementing unlimited leave. Understanding why leave is underutilized should be further explored in order for organizations to successfully implement leave policies. By identifying the conditions under which employees utilize leave optimally (i.e., recovered from work demands), organizations can guide policies more effectively. Informing managers and team members to provide an organizational context where taking leave is supported and encouraged is important for effective policy use. Organizations should be aware that individuals utilize leave differently when they have children. Moreover, managers should guide team members to be open and communicate their needs to their team. When the team provides an open climate where
employees are able to take leave in a fair manner, without any conflicts, it can contribute to their well-being. Understanding why employees feel that their leave is unfair and under what
circumstances taking leave can result in conflicts is important for managers to consider. The social context in which employees are surrounded is important for organizations to take into account. Overall, giving employees a high degree of autonomy over their leave hours and days should be examined in specific organizational contexts. A context where employees are able to freely use their autonomy within a team-setting. Employees' perception of whether taking leave would be beneficial is determined not only by their own needs, but by that of their team or organization.
Limitations and Suggestions for Future Research
One important limitation that affected the reliability of the data concerns the
social events). Specifically, in the Netherlands, a ‘work from home guideline’ was proposed on the 2nd of March followed by the ‘intelligent lockdown’ on the 15th of March (Ministerie van Algemene Zaken, 2020). The pandemic may have contributed to the underutilization of leave and employee’s well-being. This can be further supported by the drop in leave duration starting from March onwards, and a decrease in autonomy satisfaction during April. Additionally, the differences between employees under a regular leave policy and those with unlimited leave were therefore limited. It can be questioned whether employees felt the need to take leave under the forced conditions to work from home and the restrictions imposed on our society. Employee’s working from home were provided with a degree of flexibility that was otherwise not given to such a large extent. Vacation is about recovering from work demands to improve well-being, however when employees are experiencing external stress and uncertainty during a global pandemic this can be harder to obtain. Future research should examine the nature of unlimited leave and how employees use their leave under normal circumstances where traveling and social events are not restricted.
within teams and how solutions were made to support taking leave. Future research should examine this concept further. Lastly, having previous data on employees' leave uptake before partaking in the study would be beneficial to understand and compare whether their leave was underutilized in comparison to previous years.
Secondly, the sample was limited to a highly educated group of employees of which the majority were males. This limits the generalizability and external validity of the data. Examining a heterogeneous group of employees that differ in age groups and work in sectors that are male and female-oriented would be more representative. Moreover, examining different sectors would entail investigating the role of different organizational cultures on utilizing leave. Future research should examine the role that age and gender plays in leave utilization in relationship to the organization’s culture.
Another limitation is that the data was based only on self-reports, which is prone to biases. Perceived fairness only included one item; therefore, future research should measure more dimensions of fairness. However, the scales were extracted from valid measures and the self-developed scales reported high reliability. We recommend future research to use self-reports in combination with interviews to understand the underlying reasons why leave was
underutilized. When implementing a policy that gives a high degree of autonomy and
uncertainty, good communication within the teams is crucial for effective policy utilization. The team dynamic and the perceptions from employees and their direct colleagues should be
examined.
Examining the optimal amount of leave days to ensure higher levels of leave quality and autonomy satisfaction would be valuable. As shown in this research, individuals prefer to take leave in a longer stretch or in short durations.
Although, there are limitations the study provides many strengths. It is among the first to examine unlimited leave and how employees utilize their leave policy. Additionally, the study gave insight into the importance of autonomy satisfaction and its influence on leave quality, perceived fairness and conflict over leave. The study examined different predictors and outcome variables to grasp the totality of why and how employees utilize their leave.
Conclusions
In this study, a new phenomenon in the literature, unlimited leave, was elaborated upon. Specifically, the present research explored how employees utilized their leave. The majority of employees utilized their leave in longer stretches and short durations, with an average of four leave days. Leave utilization was not found to predict autonomy satisfaction. Moreover, leave quality did not moderate this relationship. Lower levels of leave quality were reported when employees experienced conflict over leave, worked longer hours and had children. Potential predictors were examined (i.e., person-level characteristics, job characteristics and social context), in which employees with children utilized more leave and those with a higher educational background took longer stretches of leave. However, the results should be interpreted with caution as the data was collected during the outbreak of COVID-19. Future research should examine these concepts further, under normal circumstances and for a longer period of time to explore how and if employees utilize more leave when provided with unlimited leave. Implications highlight the importance of examining potential hindrances in the
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