Unravelling motives and time use of additional leave in a flexible benefits plan: a mixed-methods case study in Belgium

The paper situates working-time reduction (WTR) as a key lever for a well-being economy that prioritizes human and ecological well-being over material growth. WTR may benefit well-being (via improved work-life balance and time allocation) and the environment (via income and time-use effects). Flexible benefits plans (cafeteria systems) allow employees to select benefits (including additional leave) in a tax-efficient way, making additional leave a marginal, individually chosen WTR form with limited direct salary impact. Despite rising popularity, little is known about why employees choose additional leave in such plans and how they intend to use this time. The study addresses: RQ1 What motives play a role in choosing additional leave? RQ2 How do employees who choose additional leave plan to use the additional non-working time? RQ2a What activities do they plan in general? RQ2b Can employees be clustered into distinct groups based on planned time use? The study explores potential socio-environmental implications, acknowledging that planned time use may not perfectly translate into actual behaviour.

The review covers two strands: flexible benefits and broader WTR literature. Motives in WTR are grouped as push (negative aspects of work such as intensity, lack of control), pull (desire for more leisure or specific activities like family time, hobbies, unpaid work), and barriers (intrinsic enjoyment of work, external constraints including norms, finances, or occupational demands). Environmental motives are seldom primary except among voluntary simplifiers. Flexible benefits literature indicates motives for additional leave include desire for leisure, education, care; non-choice reasons include financial constraints and occupational pressures. Time-use literature shows that reduced working hours typically increase time on domestic work, childcare, and personal care (sleep/rest), with moderate increases in personal/social leisure, education, and volunteering; transport effects are mixed but short trips/holidays may increase. Some studies note shifts toward home-cooked meals and healthier eating with shorter working hours. Subgroup differences often relate to family composition; parents show distinct patterns in time allocation. These insights inform expectations for motives (RQ1) and time use (RQ2).

Design: Mixed-methods case study in a Belgian media company offering a flexible benefits plan (since 2017) across five categories; additional leave capped at 10 days (including carryover). Employees are informed about net value advantages (~15% vs cash). Quantitative data: Administrative records (Jan 2022) for Belgian employees (N=1040) with sex, age, seniority, and 2022 plan choices; online survey (Mar 2022) via Qualtrics capturing socio-demographics, worktime characteristics, number of additional leave days chosen, planned time use for 18 activities (5-point Likert; list derived from Belgian TUS with additions for travel and food), motives and evaluations (work intensity; experienced sufficiency of time for 10 activities; ideal worker norm; sufficiency/difficulty of standard leave; work-life balance), personal traits (materialism), and environment-related characteristics (importance of protecting the environment, environmental actions, travel behaviour). Invitations sent to all Belgian employees; response rate 32% (337), final matched and cleaned sample N=241 (53.1% female; mean age 44.0; 33.6% part-time). In the sample, 44.8% (N=108) chose ≥1 additional leave day (most popular: 10 days 24.5%, 5 days 9.5%). Qualitative data: Semi-structured online interviews (Jul–Aug 2022) with 13 employees selected from survey respondents who consented and chose ≥5 additional leave days (convenience sampling). Interviews in Dutch (16–36 min), recorded, transcribed; topics: motives (RQ1), planned time use (RQ2), openness to part-time work. Analyses: Quantitative descriptives; cluster analysis based on motives (N=241) using seven variables: work intensity; three PCA-derived experienced time-use factors (personal and social leisure; non-care work and personal development; care work); ideal worker norm; sufficiency of standard leave; difficulty taking up standard leave. Hierarchical clustering (Ward’s linkage, squared Euclidean), selecting a 3-cluster solution via graphical/numerical criteria; robustness via multinomial logistic regression and LPA/LCA (two-class feasible). Planned time-use analysis restricted to choosers (N=108): descriptives and PCA (five factors: personal development & social contribution; rest & media; family & domestic responsibilities; entertainment & social engagement; second job), followed by hierarchical clustering yielding a 2-cluster solution; robustness via logistic regression and LPA/LCA (two-class feasible; 97.2% concordance). Qualitative template analysis (NVivo) with an a priori coding template refined iteratively; themes centred on drivers, barriers, and flexibility.

Motives (Cluster analysis, N=241): Three clusters emerged. - Cluster A: Work-life balancers (53.1%). Lowest work intensity; higher sufficiency for personal/social leisure and standard leave; low difficulty taking up leave. Moderate preference for additional leave (43.8% choose; mean 3.39 days). Highest work-life balance. - Cluster B: Time-strapped leave seekers (25.3%). Lower experienced sufficiency for personal/social leisure and standard leave; relatively higher work intensity; low difficulty taking up leave. Highest preference for additional leave (65.6% choose; mean 5.02 days). Overrepresented by women (63.9%), younger (mean 40.8), lower seniority (9.4 years), more parents (63.9%; youngest child mean 10.2). More trips within Europe by plane than Cluster C. - Cluster C: Leave-sufficient non-seekers (21.6%). High sufficiency of standard leave and high difficulty taking it up; significantly lower choice for additional leave (23.1%; mean 1.65 days). Overrepresented by men (67.3%), older (45.3), higher salary (2923 euros), moderate seniority (14.4 years). Descriptive planned time use among choosers (N=108): Top intended increases: core family time 80.6%, sleeping/resting 79.6%, hobbies 77.8%, social time with friends/family 64.8%, household chores 67.6%. Travel increases: domestic/inland trips 60.2%, within-Europe travel 53.7%. Least intended increases: takeaway meals 2.8%, volunteering 4.6%, second job 5.6%. Planned time-use clusters (N=108): - Cluster I: In-house caregivers (57.4%). Higher intended increases in childcare/parent care and domestic responsibilities; comparatively lower on travel/entertainment. Profile: more men (41.9%), older (43.4), higher seniority (13.3 years), higher salary (2718 euros), predominantly couples with children (72.6%). - Cluster II: Outdoor leisure spenders (42.6%). Higher intended increases in rest, hobbies, media, entertainment, social participation, all travel types, restaurants, and cooking at home. Profile: more women (76.1%), younger (38.1), lower seniority (9.5), lower salary (2522 euros); over half childless (54.3%). Qualitative insights: Motives are mixed. Pull: general desire for more leisure; specific aims (self-care/rest, social/family time, leisure/hobbies, travel including slower or longer trips, informal care, household tasks). Push: work intensity, long hours, on-call demands, workload peaks; sometimes prior overwork experiences. Plan context: additional leave is chosen because it is offered and financially advantageous; flexibility is highly valued as a buffer for last-minute needs (care, chores, rest, spontaneous activities), providing autonomy/peace of mind. Barriers: competing benefits or need for cash bonus; occupational demands impeding actual uptake; personal reasons (job enjoyment, sufficient standard leave, work ethics). Well-being and environment: Choosers report higher work intensity and lower work-life balance than non-choosers (t-tests: p=0.007 and p=0.004), but causality cannot be inferred. Intended activities (rest, family/social time, hobbies) are consistent with well-being benefits; caregiving/household work may partly offset benefits. Environmental impacts likely moderated: while travel intention is notable, most intended activities are low-impact; parental status constrains high-impact activities (e.g., travel), suggesting lower environmental rebound among caregivers.

The study answers RQ1 by identifying key motives: primary pull driver is desire for more personal and social leisure; a key barrier is difficulty taking up standard leave. Motive patterns relate to socio-demographics: time-strapped leave seekers are typically women with children and lower salaries; leave-sufficient non-seekers are often higher-paid men who struggle to use existing leave. Interviews enrich these findings by highlighting the role of plan design (financial advantage, availability) and the centrality of flexibility/autonomy. For RQ2, employees intend to use additional leave mainly for rest, family/social activities, hobbies, and household tasks, with significant but secondary intentions for travel. RQ2b reveals two groups: caregivers emphasizing in-house care/domestic duties and largely childless employees emphasizing outdoor leisure and travel. These patterns imply well-being benefits via autonomy and leisure engagement but potential partial offsets when time shifts to unpaid care/household work. Environmental impacts may be neutral to mildly positive overall due to prevalence of lower-impact activities and caregiving constraints, though travel-related rebounds exist for the outdoor leisure group. Findings should be interpreted cautiously due to cross-sectional design, plan already in place, and self-selection.

Choosing additional leave within a flexible benefits plan is driven by a blend of push, pull, personal, contextual, and plan-specific factors. Desire for more leisure is a principal driver; difficulty in taking up standard leave is a main barrier. Employees plan to allocate additional time to rest, family and social activities, hobbies, household tasks, and travel, with flexibility for ad-hoc use. Parental status differentiates time-use patterns: couples with children focus on caregiving, while others lean toward broader leisure and travel. Tentative implications are that additional leave can support a well-being economy by enhancing autonomy and leisure engagement and by substituting paid work with relatively low-impact activities, although benefits may be offset by shifts to unpaid care/household work or environmentally intensive travel. Future research should broaden contexts, use longitudinal and more granular time-use measures, and compare different WTR forms to clarify causal links among WTR, well-being, and environmental outcomes.

Single-company case in a specific sector primarily with white-collar workers limits generalizability; company-wide flexibility policies (hybrid work, flextime) limit exploration of flexibility as a push factor. Cross-sectional data and a cafeteria system already in place constrain causal inference and risk hypothetical bias (planned vs actual time use). Survey and interview samples exhibit self-selection (overrepresentation of leave choosers and strong preferences), and interviews targeted those with ≥5 additional leave days, further biasing findings. Measures are largely self-reported; travel data may be affected by COVID-19 restrictions. Time-use categories are broad (not diary-based), limiting precise environmental impact estimation.