Reasons to Reduce: A Vignette-Experiment Examining Men and Women’s Considerations to Scale Back Following Childbirth

Reasons to Reduce: A Vignette-Experiment Examining Men and Women’s Considerations to Scale Back... Abstract The reduction of working hours can help avoid work–family conflict, yet many people who would like to scale back do not actually do so. This vignette-experiment examines which considerations are most important in men and women’s decision-making whether to scale back following childbirth. About 2,464 vignettes were conducted in the Netherlands, Sweden, and the United Kingdom. Results indicate that men find the income of their partner and career consequences most important, while women focus mainly on partner income and collegial support. Swedes, however, differ from their Dutch and British counterparts, and express more counter-gender-normative behavior. Introduction Many young parents struggle to meet the competing demands of work and family. On the one hand, their employer expects commitment from employees, but at the same time they are also expected to be involved parents (Bianchi and Milkie 2010; Blair-Loy 2003). One way to combine these responsibilities is by reducing one’s working hours following the birth of a child (Becker and Moen 1999). Reducing one’s hours—as well as using other work–family policies—enables parents to remain in the labor market while freeing time to care for their child. Research suggests that employees who reduce their work hours experience less work–family conflict (Higgins, Duxbury, and Johnson 2000; van Rijswijk et al. 2004). Experiencing less work–family conflict is associated with higher physical and mental wellbeing (Allen and Armstrong 2006; Leineweber et al. 2013); higher organizational productivity, lower absence, and lower turnover (Carlson et al. 2011; Kossek and Ozeki 1999); and lower societal healthcare costs and higher fertility rates (Castles 2003; Higgins, Duxbury, and Johnson 2004). Thus, reducing one’s hours can be beneficial for both employees, organizations, and the state. However, it is known that a significant number of people who have the right to and would like to reduce their hours do not actually do so (McDonald, Brown, and Bradley 2005; Stier and Lewin-Epstein 2003). Why these people refrain from doing so remains unclear. Understanding what underlies this “provision–utilization gap” (McDonald, Brown, and Bradley 2005; Pasamar 2015) is important for organizations and countries wishing to promote the option to reduce one’s hours; which is often done to help people reduce their work–family conflict (Kossek and Ollier-Malaterre 2012), and to promote gender equality (Haas and Hwang 2016; Kossek and Ollier-Malaterre 2012; Müller, Neumann, and Wrohlich 2016). In this paper, we use a vignette-experiment (also known as a factorial survey design) in order to disentangle people’s reasons for using—or abstaining from using—the option to reduce their working hours, and investigate which considerations are most important in men and women’s decision-making whether to scale back? Both economists and sociologists have been interested in explaining people’s reduction of working hours. They have shown that reducing one’s working hours can be costly in a number of ways, and that people often refrain from reducing their hours in order to avoid these costs—or reduce their hours when these costs are absent. Economic studies look mainly at the role of financial-economic factors on labor market decisions (such as the costs of formal childcare; when formal childcare is very expensive reducing work hours becomes more attractive) or at a comparative advantage between partners (Akgunduz and Plantenga 2015; Becker 1965; Heckman 1974). Sociological theories on the utilization of work–family policies, on the other hand, often include other types of costs, such as how utilization might be costly for one’s career (McDonald, Bradley, and Brown 2008; Perlow 1995), can have personal costs (Campbell, Charlesworth, and Malone 2012), or social costs (Kirby and Krone 2002; McDonald, Brown, and Bradley 2005). Although it is thus known that a number of economic and social considerations can be of importance to people who are deciding whether to reduce their working hours, little is known about which considerations people pay most attention to when making their decision; scaling back might be attractive in one way but costly in another. In order to gain more insight in what underlies the provision–utilization gap, research is needed that pays attention to the relative importance of these considerations. In this paper, we therefore not only include economic and social considerations but also make an important contribution to the existing literature by examining the relative importance of these considerations through the use of a vignette-experiment. In a vignette-experiment, respondents are presented with a number of short descriptions of hypothetical situations which explicitly contain factors that are—based on the literature—thought to be the most important aspects in the decision-making process of people. In our experiment, these factors are the economic and social considerations introduced above. These factors are systematically varied over the vignettes (e.g., in one vignette it is stated that the costs of childcare are high, and in the other that they are low), and after each vignette respondents are asked for their desired action: if they would be in this hypothetical situation, would they scale back or not? As each respondent is shown multiple vignettes in which the factors are systemically varied, it is possible to analyze the isolated effect of the individual factors, as well as their relative importance (Aguinis and Bradley 2014; Alexander and Becker 1978; Rossi and Nock 1982). Note that vignette-experiments thus measure hypothetical behavior rather than actual behavior, though research suggests that people’s responses to vignette-experiments match their actual behavior remarkably well (Hainmueller, Hangartner, and Yamamoto 2015). By employing a vignette, we provide an important additional perspective to existing research. Previous research mainly relied on questionnaires to investigate people’s working hours or utilization of work–family policies. This type of research is particularly well-suited for the collection of large amounts of data on easily quantifiable issues, such as weekly working hours or the utilization of policies. Questionnaires are, however, less appropriate for the investigation of complex decision-making situations, while this is precisely the strength of vignettes. Therefore, research based on questionnaires and research based on vignette-experiments complement each other. There are three main reasons why vignette-experiments are well suited for testing complex decision-making situations. First, people are often not aware which factors enter into their own decision-making process, making it difficult (if not impossible) for them to provide an accurate answer when asked directly about their motivations in a questionnaire (Alexander and Becker 1978). By using a vignette-experiment, we ensure that respondents do not need to be conscious of the considerations underlying their decision-making; instead the quasi-experimental setting enables the researchers to disentangle the considerations presented. Second, complex decision-making situations can be sensitive topics, and thus there is a risk that people may express biased, socially desirable answers. In our case, this might, for example, mean that women who do not want to scale back to care for their child will still say that they will do so, because they feel that this is expected of them. However, while the risk of social desirability is not absent from vignette-experiments, it is maintained to be smaller than in questionnaires because the theoretically relevant factors are “hidden” in the vignettes (Alexander and Becker 1978; Wallander 2009). This ensures that respondents are not fully attentive to the factors, and thus not as likely to consciously bias their reports with socially desirable answers as they would have been had they been asked directly about their judgment. Last, research based on questionnaires is often cross-sectional, and thus cannot shed light on the causal direction. In the context of people’s decision-making to scale back it is, for example, unclear whether people do not get promoted because they work part-time, or start working part-time because they do not get promoted. Vignette-experiments are well suited for investigating causal relations as variations in working hours and other variables of theoretical interest can be exogenously determined and systematically varied (Aguinis and Bradley 2014; Wallander 2009). According to Kelly et al. (2008), the absence of studies allowing for causal inferences is one of the main lacuna in work–family research, which led them to call for more (quasi-)experimental research. In the context of work–family policies, vignette-experiments have already been employed to examine managers’ decision-making, either regarding the provision of work–family policies (Been et al. 2017) or regarding their acceptance of utilization requests (den Dulk and de Ruijter 2008; Klein, Berman, and Dickson 2000). Most work–family research focuses exclusively on the decision-making of women (Haas and Hwang 2016), which is unfortunate as work–family policies are increasingly offered to and used by men, and promoting male utilization is employed as a tool for increasing gender equality (Haas and Hwang 2016; Kossek and Ollier-Malaterre 2012; Müller, Neumann, and Wrohlich 2016). However, as gender expectations for men and women continue to differ, and male utilization of work–family policies continues to lack behind that of women (even in countries with a high level of gender equality, such as Sweden; Haas and Hwang 2009, 2016), it is to be expected that men and women pay attention to different considerations when making their decision whether or not to reduce their hours. Therefore, we will separately investigate the relative importance of considerations for men and for women. Similarly, a lot of research focuses on the individual without considering how the cultural context might impact individual decision-making (Ollier-Malaterre et al. 2013). We aim to provide insight into how the decision to scale back is made differently in different contexts, by focusing on the Netherlands, Sweden, and the United Kingdom, three countries with varying working-cultures and levels of gender equality. The Netherlands is characterized by the fact that it has many policies that facilitate a more traditional division of labor between parents, with the man being the main breadwinner. Sweden, on the other hand, has many formal policies designed to support dual-earner families and gender equality. Lastly, the United Kingdom can be seen as a market-oriented country, where the government neither supports gender equality nor traditional gender roles, but leaves it up to market forces to shape gender relations (Korpi 2000; Korpi, Ferrarini, and Englund 2013). In each of the selected countries, part-time work is relatively common, and most employees are entitled to scale back if they would want to do so (Roeters and Craig 2014), which ensures it would be relatively easy for respondents to identify with the hypothetical situations presented. Data were collected as part of the European Sustainable Workforce Survey (van der Lippe et al. 2016). Theoretical Background Individual Considerations Financial costs According to the micro-economic theory of labor supply, people decide rationally how much time (if any) they want to spend on the labor market, depending on the potential financial gains from working (Killingsworth 1983; Mincer 1962). Many parents of young children who wish to work have to arrange for their children to be cared for by others during these hours, and formal childcare can be expensive. It should be noted that this does not equally apply to all parents, though, as some work alternate shifts, rely on free informal childcare by friends or relatives, or live in countries where childcare is heavily subsidized. The net-gains of working for parents are thus not only affected by their salary but also by the costs of childcare (Cloïn 2010; Heckman 1974). If one has a high earning potential, an extra hour of work becomes more profitable, and the opportunity costs of not working are higher. This makes it logical to want to participate more in the labor market. It follows that when the costs for childcare are low, an hour of work is more profitable, and people want to work more hours. Conversely, when the costs are high, parents are more likely to want to scale back. Empirical studies have also shown this by modeling the increase in (female) labor participation as a result of a decrease in (net) childcare costs (Akgunduz and Plantenga 2015). Therefore, we expect that employees are more likely to reduce their working hours if the financial benefits of working are lower due to high costs of childcare (H1). Career costs Many people do not only work to earn money but also aspire to have a successful career (Eurofound 2012; van der Horst 2014). Reducing one’s working hours can be costly because it harms one’s promotion prospects (McDonald, Bradley, and Brown 2008). In many organizations in Europe and United States, a notion of an ideal worker persists which is based on the traditional male breadwinner: a highly committed, full-time worker, with limited care-giving responsibilities (Acker 1990; Haas and Hwang 2016; Reid 2015). In these organizations, the amount of hours one puts into one’s job are often seen as indicative of one’s commitment to the organization and, relatedly, to one’s ambition to advance in the organization. Consequently, employees who scale back can be perceived as not fully committed and thus less ambitious, which affects their chances of being promoted (McDonald, Bradley, and Brown 2008; Perlow 1995). Empirical studies have also found that perceived negative career consequences limit the uptake of work–family policies (Darcy et al. 2012; McDonald, Bradley, and Brown 2008; Smith and Gardner 2007). Therefore, we expect employees to be more likely to reduce their working hours if they do not perceive this to have negative career consequences (H2). Personal costs People also engage in paid work because they find their job intrinsically rewarding: work can be interesting, challenging, meaningful, or simply enjoyable (Eurofound 2012; Wilson 2006). When one changes one’s working hours the enjoyability of a job might decrease for two reasons. First, people who work fewer hours tend to be assigned less challenging, lower status tasks—even when holding the same position as their full-time counterparts—because their superiors tend to assign them projects without tight deadlines, or without high-profile clients (Campbell, Charlesworth, and Malone 2012; McDonald, Bradley, and Brown 2009). Second, the enjoyability of the job might also decrease because only more enjoyable tasks can be cut in order to allow for a decrease in working hours, as other—less enjoyable—tasks will always continue to be required. For example, after a reduction in hours someone might still be required to attend meetings and do administration, which will cost the same amount of time as before, and thus these tasks will from then on take up a larger proportion of the job than before. We are not aware of any empirical studies examining the effect of anticipated changes in job enjoyment on the utilization of work–family policies. However, studies do show that people value their job enjoyment (Graves et al. 2012; Sturges 2013; Wilson 2006), which would suggest that they are reluctant to give this up. Therefore, we hypothesize that employees are more likely to reduce their working hours if they do not think that this will affect the enjoyability of their job (H3). Social costs Most people spend a lot of time with their colleagues, and wish to maintain a positive—or at least not negative—relationship with them (Eurofound 2012). The extent to which co-workers support their colleagues who want to use work–family policies varies. Some employees are very supportive toward their colleagues’ (anticipated) use of work–family programs, either because they believe this to be important, or because they experience similar choices or work–life struggles themselves. This can consequently encourage employees to apply to use such policies (Kirby and Krone 2002). Conversely, however, employees can also be resentful toward their co-workers who use work–family policies as they themselves feel excluded from enjoying these “privileges,” for example because they do not have children, or have a stay-at-home spouse (Kirby and Krone 2002). Colleagues might also be unsupportive as they have to (or fear they might have to) take on additional workload, or perform a greater share of unpleasant tasks, such as working on holidays. Their negative attitude can discourage employees from applying to reduce their working hours (Boren and Johnson 2013; Kirby and Krone 2002; McDonald, Bradley, and Brown 2009). Empirical studies have shown that employees with supportive colleagues (Waters and Bardoel 2006), or with colleagues who used work–family policies themselves (Bygren and Duvander 2016; Dahl, Løken, and Mogstad 2012) are more likely to use these policies. This leads us to H4: employees are more likely to reduce their working hours if they experience collegial support for this. Household Considerations So far, we considered the decision to scale back as an individual decision, but work–family decisions of partners are often coordinated. Couples can opt for one, both, or neither partner to reduce their hours (Becker and Moen 1999). According to Becker’s New Home Economics theory (1965), specialization yields the highest household utility because both partners can capitalize on and develop their comparative advantages. The partner with the highest earnings has a comparative advantage in paid work, and thus it would be rational that he or she specializes in employment and does not scale back, whereas the partner with the lowest hourly wage will specialize in unpaid work, including childcare, and may have a smaller, part-time job on the side. Empirical evidence suggest that couples with young children indeed often specialize, and that the relative earnings of the partners influences who scales back—although gender also plays a role here (Becker and Moen 1999; Kanji 2013; Kühhirt 2012). For now, we still leave gender out of the equation, and hypothesize that employees are less likely to reduce their working hours if they earn more than their partner (H5), and that they are more likely to reduce their working hours if they earn less than their partner (H6). Gender Gender differences in the likelihood to reduce It is known that women scale back more often than men (Becker and Moen 1999; van Gils, Kraaykamp, and van der Lippe 2009). Partially, this might be explained by the process discussed earlier: women tend to earn less than their male partners (due to differential wages and a tendency for homogamy), and therefore it is more often rational for the female partner to scale back and the male partner to specialize in paid work. Simultaneously, a gender perspective suggests that another reason why women scale back more often than men is that societal expectations on the role of men and women differ, and that people tend to conform to these expectations as it is costly to violate social norms of appropriate behavior (Akerlof and Kranton 2000; West and Zimmerman 1987). Although the traditional breadwinner–homemaker model is no longer dominant in Europe, it still “profoundly impacts how gender organizes societies,” by continuing to persist as an ideal, where the work role still firstly lies with the husband, and the responsibility for the home and children with the wife (Kanji and Samuel 2017). Because scaling back is in line with gender expectations for women but not for men, we expect that women will more often choose to reduce their working hours and take up childcare responsibilities than men, even in similar circumstances (as is the case in our vignette experiment). Therefore, we expect that women are more likely to reduce their working hours than men (H7). Gender differences in the relative importance of considerations Taking this reasoning one step further, we will not only test how gender expectations influence men and women’s overall willingness to scale back but also explore whether gender expectations influence which consequences associated with scaling back men and women perceive as most important. In other words, men and women might differ in which considerations they focus on most when considering whether to scale back. Building upon the reasoning set out above it can be argued that in industrialized societies career orientation is central to the male identity (Gilmore 1990). Because men have learned that it is important for them to have a successful career, in line with “doing gender”, avoiding career costs would be important in their decision-making (West and Zimmerman 1987), and thus they would be reluctant to scale back when they think that this will have negative career consequences (van der Horst 2014). Furthermore, because men tend to be more career oriented, they might be more reluctant to specialize in unpaid work, even when their partner earns more than they do (Gilmore 1990; Greenstein 2000). Women, on the other hand, continue to shoulder the main responsibility for the home, and more often have a “job” rather than a “career” (Becker and Moen 1999). This means that in general work tends to be less central to their identity than it is for men. Therefore, it is likely that women display their feminine identity through greater importance to non-career considerations: financial costs (both the costs of childcare and the relative income of their partner), personal costs (whether it will continue to be enjoyable for them to work), and social costs (the attitudes of colleagues). Previous studies have indeed found that non-career aspirations are valued more by women, and career aspirations more by men (Konrad et al. 2000; van der Horst 2014). The Country Context Our research is conducted in the Netherlands, Sweden, and the United Kingdom. We selected these countries because in each of them part-time work is relatively common and many employees have the right to request changing their working hours, which makes it realistic for respondents to envision themselves in a situation where they might reduce their working hours. These three countries are similar in many respects, such as levels of fertility, marriage, and cohabitation (OECD 2017b); however, they are also very different in their working-cultures and levels of gender equality, and consequently different levels of part-time work (see table 1 for an overview of the male, female, and total prevalence of part-time work in these countries). As it can be expected that these different country contexts affect individual employees’ decision-making regarding working hours, we will take an explorative approach to see whether reasons to reduce differ in these countries. Table 1 People working part-time as a percentage of the employed, in the Netherlands, Sweden, and the United Kingdom (age 15–64 years), 2016   Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8    Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8  Source:Eurostat (2017). Note: Dutch respondents are considered to be working part-time if their usual working hours are <35. Respondents from Sweden and the United Kingdom are seen as part-time employees when they self-identified as doing so. Table 1 People working part-time as a percentage of the employed, in the Netherlands, Sweden, and the United Kingdom (age 15–64 years), 2016   Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8    Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8  Source:Eurostat (2017). Note: Dutch respondents are considered to be working part-time if their usual working hours are <35. Respondents from Sweden and the United Kingdom are seen as part-time employees when they self-identified as doing so. According to Korpi’s (2000; Korpi, Ferrarini, and Englund 2013) typology of gendered policy models in modern welfare states, the three countries belong to different clusters, and carry out different policies regarding gender equality and female labor participation, with Sweden belonging to earner-carer group, the Netherlands to the traditional-family group, and the United Kingdom to market-oriented group. Sweden has many formal policies designed to support equality between the sexes, and actively supports dual-earner families, for example through high-quality, heavily subsidized public childcare. This has contributed to a high level of female labor participation, which is to a large extent full-time or long part-time. In Sweden, all parents with children under the age of eight have the right to reduce their work hours to 75 percent of full-time. However, although gender equality is high on the agenda in Sweden, part-time work is much more prevalent among women than men, and this gender distinction is even more apparent among parents with young children. In couples with two children where the youngest child is between three and five years old, 43 percent of women and 8 percent of men work part-time (Evertsson et al. 2009; Swedish Labour Force Survey 2016). The Netherlands, on the other hand, belongs to the “traditional-family” countries, meaning that its policies to a larger extent facilitate the traditional male breadwinning family rather than gender equality (Korpi 2000; Korpi, Ferrarini, and Englund 2013). Paternity leave, for example, is very limited, and there is no heavily subsidized public childcare. In the Netherlands, a “one-and-a-half earners model” has become dominant (Visser 2002), and it is almost natural for women to work part-time. The gap between male and female working hours is largest among men and women with live-in children and a partner: in 2015 women in this category worked an average of twenty-four to twenty-six hours a week, while their male counterparts worked approximately forty hours a week (Portegijs and van den Brakel 2016). Part-time work in the Netherlands is well regulated and protected, due to “what is probably the most comprehensive state effort to increase high quality part-time work” (Gornick and Meyers 2003, 165), which includes the right of most Dutch employees—not only parents—to request a decrease (or increase) in their working hours (although there are a few exceptions) (den Dulk 2016). Although it is especially common for Dutch women to work part-time, part-time work among Dutch men is compared to other EU member states also relatively high, though much lower than among women (Eurostat 2017). The United Kingdom, on the other hand, belongs to the group of market-oriented countries, meaning that the government neither actively supports gender equality, nor supports traditional gender roles, but instead leaves it up to market forces to shape gender relations (Korpi 2000; Korpi, Ferrarini, and Englund 2013). This orientation on the free market means, for example, that the level of protection for (intended) part-time employees is much lower than in the Netherlands and Sweden, and the quality of part-time jobs is generally lower than that of full-time jobs. This should be understood as an institutional impediment to scaling back: switching to working part-time means for many people in the United Kingdom that they have to sacrifice job quality, and thus scaling back will not be an attractive option for many ambitious employees. Another important factor is that childcare in the United Kingdom is very expensive, which means that “for too many families it simply does not pay to work” (Rutter 2015). In addition, in the United Kingdom, part-time work is mainly a women’s issue, and mothers in particular often work part-time: 58 percent of mothers with a child of preschool age do so (Cory and Stirling 2016). In the United Kingdom, all employees who have been with their employer for over twenty-six weeks can request a reduction of working hours, however, there are more “opt out” possibilities for employers in the United Kingdom than in Sweden or the Netherlands, including, for example, the burden of additional costs, inability to recruit additional staff, or a detrimental impact on the quality of service (EurWORK 2014). While part-time work in the United Kingdom is relatively prevalent, comparable with Sweden, it should be noted that involuntary part-time work is more common in the United Kingdom than in the other two countries (OECD 2017a). Method Sample To test our hypotheses, we use data from the European Sustainable Workforce Survey (van der Lippe et al. 2016) that were collected in 2015/2016. In addition to the vignette-experiment, this dataset includes multilevel organization data based on questionnaires filled out by employees, their managers, and the HR-managers. Linking the vignettes to an organizational survey was done so we could link the data obtained through the vignettes to respondent- and organization-level data obtained from the questionnaire. Organizations were sampled based on their representation of three different sizes (1–99 employees; 100–249; 250 or bigger) and six different sectors (manufacturing, health care, higher education, transportation, financial services, and telecommunication), using a combination of stratified random sampling (through national business lists) and personal connections. Thus, in all three countries employees belonged to the same six sectors. Initially, participation of the organizations was solicited, and after they agreed to participate employees were contacted at work and requested to fill out the survey, either online or on paper. After employees completed the questionnaire they were asked if they wanted to participate in the vignette study (“an interesting thought-experiment”), which followed immediately after. Only respondents who were younger than forty were invited to participate in the vignette, as we wanted it to be a realistic option for respondents that they might be expecting a child. One of the main advantages of vignette-experiments is that they permit general conclusions about causal mechanisms using nonrandom samples, as long as certain criteria for internal and external validity are met (Auspurg and Hinz 2015). Internal validity is ensured by administering the vignettes at random and having each vignette rated by numerous respondents. External validity is less straightforward, but relies on the theoretical question whether the causal mechanism holds for all people, or only for a selective subgroup. For testing causal mechanisms that are considered universal a homogeneous convenience sample is deemed sufficient to generalize to the entire population (which is why student samples are often used in (vignette-)experiments). However, if one assumes that such a causal mechanism functions differently for separate sub-groups, one cannot automatically generalize results from a non-representative subsample to the entire population. As we assumed that the mechanism we were trying to test would only apply to a certain sub-group—namely employed individuals of childbearing age—we only administered the experiment to respondents belonging to this group. This is also the reason why we used separate samples of men and women; we worked from the assumption (based in theory) that the mechanism would function differently for men and women. The response rate was 61.4 percent for the questionnaire, and 57.2 percent for the vignettes, leading to a total of 743 respondents. From the initial sample of 743, we excluded subjects who had not completed all the vignettes, as this would prevent us from analyzing the within-subject variation resulting from the vignette-factors (n = 102, 14 percent). We also excluded respondents who were over forty but filled in the paper vignettes anyway (n = 22, 3 percent), or who had missing values on any of the independent or control variables, which was only the case for their working hours (n = 3, <1 percent). The final sample consisted of 616 respondents, and as each respondent filled in four vignettes we had a total of 2,464 vignettes. As the vignette, not the respondent, is the unit of analysis, N = 2,464 (Atzmüller and Steiner 2010; Wallander 2009). Considering the simplicity of our vignette-experiment, with a relatively small number of variables of interest, this is a rather large sample (Ganong and Coleman 2006). The Vignette Before respondents were presented with the actual vignettes, they were shown a short introduction. It was explained to them that they would be shown four “hypothetical scenarios” relating to a situation in which they and a partner were “expecting a(nother) child” (whether the respondent had children was added as a control variable). Respondents were asked to imagine the following to happen to them in their current job, and to express if and how much they would like to reduce their working hours in that situation. It was also specified that the situations referred to “you and your partner,” and asked respondents without a partner to answer the questions according to how they would respond if they were to have a partner. In relation to the hypotheses set out above, our vignette included the independent variables childcare costs, career consequences, enjoyment, collegial support, and partner income, which each had two or three manipulations that varied systematically between the vignettes. Childcare costs reflected the costs of childcare in relation to one’s income (0 = much lower, 1 = about the same). Career consequences told people whether working fewer hours would affect their promotion prospects (0 = less likely to be promoted, 1 = chances will not be affected). The variable enjoyment told people whether working fewer hours would affect the enjoyability of their job (0 = you will have to give up some tasks you really enjoy, 1 = you will continue to do the same type of tasks, and your work will remain as enjoyable as it is now). Furthermore, collegial support indicated whether colleagues would disapprove (= 0), or approve (= 1) when they would reduce their working hours. Lastly, partner income told people how much their partner earned in relation to themselves (1 = less, 2 = about the same, 3 = more), which was recoded into two dummies. After each vignette respondents were asked: “In this situation, would you reduce your contract to work fewer hours per week?” (0 = no, 1 = yes), this was used as our dependent variable. Figure 1 shows an example of a vignette. Figure 1 View largeDownload slide Example of a vignette. Figure 1 View largeDownload slide Example of a vignette. Respondent Characteristics In addition to the manipulated vignette-factors, we included a number of respondent-level characteristics. In line with our different expectations based on gender and country, we included the sex of the respondent (0 = female, 1 = male), and the country of residence (1 = the Netherlands, 2 = Sweden, 3 = United Kingdom). Moreover, we included a number of control variables, namely age (16–39 years), whether the respondent lived with a partner (0 = no, 1 = yes), and whether the respondent had minor children (0 = no, 1 = yes). We also included the respondent’s current working hours (5–70), as we assumed that respondents who already worked fewer hours would be less likely to want to reduce even more. Analytic Strategy Unlike regular regression models, in a vignette experiment the vignette is seen as the level of analysis, not the respondent. As four vignettes are shown to each respondent the vignettes are nested within the respondents, which makes a multilevel analysis appropriate (Atzmüller and Steiner 2010). We first ran an empty model in order to calculate the intraclass correlation coefficient to determine how much variance is explained by each level (the vignette and the respondent level). Subsequently, we applied a multilevel logistic regression model to test our hypotheses. Analyses were conducted for all respondents together, as well as separately for men and women, and for men and women per country, in order to see whether the different subgroups focus on different considerations. Results are presented as average marginal effects rather than the estimated coefficients, because these are easier to interpret, especially for logistic regression (Jann 2013; Mood 2010). The average marginal effects express how the probability of the dependent variable being 1 (i.e., people want to reduce) changes as the independent variables change from 0 to 1 for binary variables, or for a one unit increase for continuous variables, holding the other variables constant. In other words, if, for example, collegial support has an average marginal effect of 0.1, this means that when people were shown the vignette that indicated that their colleagues would approve of them scaling back, they were 10 percentage points more likely to want to reduce their hours than if they saw vignettes which stated that their colleagues would disapprove, keeping everything else constant. In addition, the average marginal effects will also be presented in a plot to visualize the relative sizes of the effects, and thereby aid the interpretation of the relative importance of the factors. Results Descriptive Statistics Descriptive statistics are presented in table 2. Our sample contained about the same number of men and women, and over half (56 percent) of the respondents were Dutch, while 22 percent were Swedish and 22 percent British. The average age of our respondents was thirty-one, 70 percent lived with a partner and 40 percent had minor children. Moreover, on average people worked 39 hours per week, though Dutch women in particular have a much lower average (34 hours) than the other groups (39–41). When responding to the vignettes, respondents indicated 59 percent of the time that they would want to reduce their working hours in the situation presented in the vignette. Women did so more often than men: 64 percent of the time as opposed to 53 percent. Table 2 Descriptive statistics (SD)   Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67    Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67  Table 2 Descriptive statistics (SD)   Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67    Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67  Hypotheses Testing Table 3 shows the average marginal effects predicting the desired reduction of working hours for all respondents and by gender. Based on the empty model (not shown here), we calculated the intraclass correlation coefficient, which is 0.21 for the vignette level and 0.79 for the respondent level. Thus, the factors specified on the vignette account for 21 percent of people’s decision-making, while differences between people account for the remaining 79 percent of the variance. Looking at the total sample, we found support for all hypotheses: employees were more likely to want to reduce their working hours if the costs of childcare are high compared to their wage (H1), they do not expect this to have negative career consequences (H2), they do not think that this will affect the enjoyability of their job (H3), they experience collegial support for this (H4), and when they earn less than their partner (H6). Employees were less likely to reduce their hours when they earn more than their partner (H5). Moreover, women were more likely to reduce their hours than men (H7). The predictive probability of wanting to reduce is 54 percent for men and 80 percent for women (the predictive probabilities of all factors can be found in table A1). Table 3 Average marginal effects predicting the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Table 3 Average marginal effects predicting the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Relative Importance for Men and Women To see which considerations are most important in men and women’s decision-making, we turn to the size of the average marginal effects. Figure 2 shows a plot of the average marginal effects presented in table 3 to visualize the differences in effect-sizes. For men, we found a significant effect of all factors except childcare costs. The most important factors in the decision-making of men are the relative income of their partner and career consequences. When men earn less than their partner they are 21 percentage points less likely to want to reduce their working hours than when they earn about the same, and when they earn more compared to the same their likelihood increases with 21 percentage points. Similarly, expecting no career consequences makes men 17 percentage points more likely to want to reduce than when they do expect career consequences. Turning to women, we find no significant effect of career consequences and enjoyment. In addition, for women, their partner’s income is the most important factor: the likelihood that a woman will reduce her hours reduces by 22 percentage points when her partner earns less compared to when he earns the same. However, when her partner earns more than she does, the likelihood that she will reduce her hours is only 6 percentage points higher than when he earns the same (discussed below). The second most important factor in women’s decision-making is collegial support. When women experience collegial support their probability of reducing becomes 14 percentage points larger. Lastly, when the costs of childcare are close to one’s hourly wage, women become 9 percentage points more likely to reduce than when the costs of childcare are lower. Figure 2 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, for all respondents and by gender. Figure 2 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, for all respondents and by gender. It stands out that when their partner earns more, women only become 6 percentage points more likely to reduce their hours, while for men this increases by 21 percentage points. When we look at the absolute predictive probabilities (table A1) we see that this is because women are already more likely to want to reduce their hours than men. When a woman earns the same as her partner her probability of wanting to reduce is 77 percent, while for men in this situation this is 60 percent. When a woman earns less than her partner her likelihood of reducing increases by “only” 6 percentage points compared to 83 percent, but this is still higher than it is for men, who increase by 21 percentage points to a predictive probability of 81 percent. Country Differences In addition, we conducted further analyses to explore the differences between men and women in the different countries, the results of which can be found in table 4 and plotted in figure 3. We see that for almost all groups the income of the partner was the most important factor, but we see some important differences between the groups. For Dutch and British men, the probability of reducing increases strongly when their partner earns more (in both cases by 20 percentage points), and decreases strongly when their partner earns less (NL: 20; UK: 30 percentage points). However, while Swedish men become 16 percentage points more likely to reduce when their partner earns more, no significant decline is found when their partner earns less. Turning to women, we see that partner income has no significant effect for Swedes. For both Dutch and British women, the likelihood of reducing decreases when their partner earns less (NL: 17 percentage points; UK: 29 percentage points), but while Dutch women become more likely to reduce their hours when their partner earns more (10 percentage points), for British women no significant difference is found. Again we turned to the predictive probabilities (table A2) to shed more light on the aspects that stand out. We see that in the situation where the partner earns the same, Dutch and British men are much less likely to reduce their hours (NL: 60 percent; UK: 47 percent) than their female counterparts (NL: 71 percent; UK: 82 percent), and while men’s likelihood to reduce is much more affected by the income of their partner and thus varies more, the absolute likelihood of reducing remains higher for women (men NL: 79 percent; UK: 67 percent; women NL: 81 percent; UK: 79 percent). Swedish men, on the other hand, are compared to other men much more likely to reduce when their partner earns the same (75 percent), and no significant decline is found when their partner earns less. Swedish women have an 80 percent likelihood of reducing when their partner earns the same, but for them no significant change is found resulting from partner income. Table 4 Average marginal effects predicting the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Table 4 Average marginal effects predicting the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Figure 3 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, by gender and country. Figure 3 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, by gender and country. Moreover, for men in all three countries the probability of wanting to reduce increases strongly when they expect no career consequences (NL: 18; SW: 13; UK: 13 percentage points), and Swedish men are also much more likely to reduce their hours when they do not expect a change in enjoyment (16 percentage points). Apart from partner income, collegial support was the most important factor for women in all three countries (NL: 9; SW: 22; UK: 16 percentage points). Similar to their male counterparts, Swedish women also attach great importance to whether they expect a change in enjoyment and to not expecting career consequences; in both cases they are 13 percentage points more likely to want to reduce. British women, and to a lesser extent also Dutch women, also pay attention to whether the costs of childcare were close to their hourly wage, in which case they were 16 and 6 percentage points, respectively, more likely to reduce. Unexpectedly, we found for British women also a negative effect of career consequences, meaning that when they expect that reducing their hours will have no career consequences, they are 1 percentage point less likely to scale back. Sensitivity Analyses A number of sensitivity analyses were performed. As it might be difficult for respondents without a partner to report about how they would behave if they were to have a partner, we ran the analyses excluding single people. Similarly, we ran the analyses including only people who did not have children, as it can be argued that people who are parents have already made the decision whether they want to scale back or not, and thus are unlikely to scale back even more. On the other hand, it might be difficult for people without children to really anticipate what having children will be like, and therefore, we also ran the analyses including only people with children. Furthermore, we included the controls sector (manufacturing, health care, higher education, transportation, financial services, and telecommunication), type of job (ISCO), and job status (ISEI) in turn to see whether the mechanism would function differently for respondents in different sectors or with different jobs. Moreover, to see whether the results were mainly driven by one country, we repeated the analyses excluding each of the countries in turn. Lastly, we included a variable representing the order in which respondents had seen the vignettes, as respondents might tire and focus only on one or two considerations rather than the whole vignette, leaving earlier choices to differ from later choices. Results were in all cases very similar, which suggests that our findings are robust. Discussion In this paper, we have examined how people make the decision whether or not to reduce their working hours following the birth of a child. Reducing one’s hours can enable employees to be engaged in childcare, while continuing their involvement in employment. However, little is known about why people who want to and have the right to reduce their hours refrain from doing so. With our study, we aim to shed further light on this in four ways. First, we have combined two prominent approaches toward studying work hour reductions by combining economic theories regarding determinants of working hours with sociological theories on the utilization of work–family policies. Second, by using a vignette-experiment, we were able to not only examine whether people find these costs important but to also investigate the relative importance of these considerations. Third, contrary to most previous research, we have included both men and women, rather than only women, and thereby contribute to the understudied understanding of male utilization. Fourth, by focusing on the Netherlands, Sweden, and the United Kingdom, we aim to allow insight into how the decision to scale back is made differently in different cultural contexts. Our findings suggest that both economic and social considerations play a role in people’s decision-making to scale back—although there are gender and country differences in which considerations are most important. Financial considerations, specifically the comparative advantage between partners, is an important consideration for both men and women—though in different manners. Additionally, how utilization might be costly for one’s career factors strongly into the decision-making of men, and social costs (the support of colleagues) into the decision-making of women. With regards to the different countries, we see that Swedish women in particular, and to a lesser extent also Swedish men, stand out as they express more counter-gender-normative behavior. In addition, women are generally much more likely to indicate that they want to reduce their hours than men. One of our most striking findings is that for both genders the relative income of their partner is the most important consideration, but when we look closer the picture is more complex. Men are overall more likely to indicate to want to reduce their hours as their partner’s income relative to their own increases. Women, on the other hand, are very likely to want to reduce their hours both when their partner earns more and when their partner earns the same. This indicates that the reduction of working hours for childcare purposes continues to be a gendered decision. The default, at least from a female perspective, is that they will be the one to reduce their hours, and women only deviate from this when this is very financially appealing. This is in line with our expectations; because the breadwinner–homemaker model continues to impact gender norms we expected women to be more likely to take up childcare responsibilities than men (Kanji and Samuel 2017). Turning to which considerations are most important for the different sexes, our finding that men focus strongly on whether reducing their hours will have career consequences aligns with the notion that career orientation is central to the male identity (Gilmore 1990). As men have learned that having a successful career is important, they wish to avoid behavior that could harm their career, and are thus reluctant to scale back when they think that this could hamper their promotion prospects (West and Zimmerman 1987). On the other hand, our finding that the relative income of the partner is the strongest predictor of men’s reduction of working hours—even stronger than the possibility of career consequences—is a surprising one. Based on the literature, we expected men to wish to continue to work many hours even when their partner earns more because it is important to them to be the main provider (Gilmore 1990; Greenstein 2000), yet we find the opposite. Our results suggest that financial considerations might be more important to men than gender normativity. This could imply that the reason why men work part-time less often than women (Eurostat 2017) is not (solely) that men behave gender-normatively and wish to be the main provider, but that this is also due to the wage gap for women, which leaves men to more often have a comparative advantage in paid work (Becker 1965; Eurostat 2015). Additionally, this could also stem from maternal gatekeeping, i.e., the notion that mothers can inhibit fathers’ involvement in childcare (Allen and Hawkins 1999). Although men express a willingness to reduce their hours if they earn the same as their partner, we see that women are even more willing to do so, and as work–family decisions of partners tend to be coordinated this might result in men scaling back less often, even though they would have been willing to do so. Moreover, we found that women focus mainly on non-career considerations in their decision-making to scale back, primarily social costs and financial costs, which aligns with previous research (Konrad et al. 2000; van der Horst 2014). As discussed earlier, we found that women’s likelihood of reducing was strongly affected by their income relative to their partner’s. This is in line with our expectations; women are more likely to reduce when this is financially sensible. Whether there will be social costs (i.e., if their colleagues disapprove) is their second most important consideration. This suggests that women are, to a greater extent than men, influenced by their social environment, and find it important to receive the support of others for their actions. Contrary to what we expected we found no significant effect of personal costs (i.e., the enjoyability of the job) on women’s desire to reduce their working hours, while we did find this to play a role for men. We expected that the notion that women tend to have a “job” rather than a “career” (Becker and Moen 1999) would make that women find it important that their job is something they enjoy—otherwise they might as well drop out of employment completely. However, it might be that it is precisely because they have a job instead of a career that they find the enjoyability of the work less important: the time spent on work does not have to be terribly enjoyable or intellectually satisfying as it is not central to their identity, but rather something that is done “on the side,” next to other aspects of one’s life. This would also explain why we did find enjoyability to play a role for men. Turning to country differences, we see that Swedish women in particular, and to a lesser extent Swedish men, stand out by expressing more counter-gender-normative behavior. Unlike for Dutch and British women, the income of the partner and the costs of childcare are not important to the decision-making of Swedish women. Simultaneously, they—like men from all countries—find it important that scaling back has no career consequences. Swedish men largely focus on the same considerations as their Dutch and British counterparts, but are overall more willing to reduce their hours than other men. It is not surprising that Swedes in particular stand out in this way. Sweden is a country that actively supports equality between the sexes and favors dual-earner families, and work–family policies in Sweden are focussed on increasing the working hours of women (Evertsson et al. 2009; Korpi, Ferrarini, and Englund 2013). It is also noteworthy that how “realistic” considerations are in a country context also seems to influence how important employees deem these considerations. Formal childcare is well regulated and heavily subsidized in Sweden, and neither Swedish men nor women seem to factor the costs thereof into account in their decision-making. In the Netherlands and especially the United Kingdom, however, childcare is expensive, and women in these countries do factor the costs of childcare into their decision-making to scale back. This fits with economic literature on female labor market participation, which shows that female labor market participation increases as a result of a decrease in (net) childcare costs (Akgunduz and Plantenga 2015). Lastly, a surprising finding is the negative effect of career consequences that was found for British women: when they expect scaling back to have no career consequences, they are less likely to indicate to want to scale back, contrary to the expected positive effect. While it should be interpreted with caution considering it is marginally significant and the size of the effect is small, a possible explanation is that these women are so grateful to their organization for not punishing a reduction of working hours with career consequences, that they want to reciprocate to the organization and end up working more hours (Grover and Crooker 1995). Limitations In our study, we have employed a vignette-experiment, as this method is particularly well-suited for exploring the relative importance of factors in complex decision-making situations (Alexander and Becker 1978; Wallander 2009). However, vignette-experiments also have some limitations. An often heard limitation is that it requires variables and levels to be pre-specified, which comes with the risk that important variables are omitted (Aguinis and Bradley 2014). However, the factors presented on a vignette are not random, but based on the literature, and while no new factors can be detected using a vignette-experiment, its strength lies elsewhere: in being able to analyze the isolated effect of these pre-specified factors, as well as exploring causality. For this reason, employing a vignette-experiment is only appropriate for topics where previous studies have provided a good indication which factors are important (Aguinis and Bradley 2014; Ganong and Coleman 2006). Even so, as our experiment is a simplification of reality we have intentionally—and very possibly unintentionally—excluded factors that people in real-life do take into account in similar decision-making situations, most notably informal childcare arrangements (which tend to be very common, especially in the United Kingdom; Verhoef et al. 2015). However, whereas this precludes us from drawing conclusions on the role these excluded factors play in people’s decision-making about reducing, thanks to our experimental design this does not affect our findings regarding the relative importance of the included considerations vis-à-vis each other. Another often heard limitation is that vignette-experiments have lower external validity due to their hypothetical nature (Aguinis and Bradley 2014; Wallander 2009). One way in which we have attempted to improve this is through our sample selection: we sampled employees of childbearing age, which corresponds with the population to whom we generalize our results, in order to ensure that it is easier for respondents to identify with the situation presented, and this thus secures more reliable answers (Aguinis and Bradley 2014). That being said, it should be kept in mind that with our vignette-experiment we measure people’s intended behavior rather than their actual behavior, which may not always coincide. This may, for example, lead to more socially desirable responses, or people holding unrealistically positive expectations of their own behavior. However, the risk of social desirability bias is often maintained to be smaller in vignette-experiments than in questionnaires, because the theoretically relevant factors are “hidden” in short stories (Alexander and Becker 1978; Wallander 2009). In addition, research suggests that people’s responses to vignette-experiments match their actual behavior remarkably well (Hainmueller, Hangartner, and Yamamoto 2015). Additionally, while vignette experiments have the advantage of permitting general conclusions about causal mechanisms using nonrandom samples, this hinges on the assumption that the causal mechanism is universal to the group to which it is to be generalized (Auspurg and Hinz 2015). For certain types of behavior, such as altruism and rational behavior, this is considered universal for humans, and thus homogeneous convenience samples are deemed sufficient (which is why student samples are often used in (vignette-)experiments). As we assumed that the mechanism we were trying to test would only apply to a certain sub-group—namely employed individuals of childbearing age—we only administered the experiment to this group. This is also the reason why we used separate samples of men and women; we worked from the assumption (based in theory) that the mechanism would function differently for men and women. However, the question remains whether the causal mechanism underlying decisions regarding employees’ working-hours following childbirth is universal over job type, or whether this is specific to certain types of jobs. Theoretically, we assumed this to be the same for different types of jobs, and controlling for job characteristics did not lead to different results. However, we cannot exclude the option that it does function differently for different types of jobs and sectors than were included in our study, and therefore it would be good for future research to conduct a vignette-experiment on a nationally representative sample of employees. Conclusion All in all, our study indicates that men and women have different reasons to reduce. Women are overall more likely to want to reduce their hours, but become less willing to do so if they have a partner who earns less than they do, or if their colleagues are unsupportive. Men, on the other hand, base their decision largely on their income relative to their partner’s (if their partner earns more, they are more likely to reduce, and if their partner earns less, they are less likely to reduce) and on whether they expect to suffer career consequences. Furthermore, we found that Swedish women, and to a lesser extent Swedish men, differ from their Dutch and British counterparts, as they expressed more inclination to exhibit counter-gender-normative behavior. Finally, we maintain that our findings suggest that the mere availability of the option to reduce one’s working hours following the birth of a child is not enough for people to actually do so. Before people can reduce their working hours they need to believe that they will not suffer collegial disapproval or career consequences. When the organizational culture is supportive of work–family needs, employees who want or need to use work–family policies do not need to refrain from this for fear of organizational consequences. Leonie van Breeschoten is currently doing her PhD at the Department of Sociology/ICS at Utrecht University, the Netherlands. She does research into questions regarding the combination of work and family life in European countries. Anne Roeters is a senior researcher at the Netherlands Institute for Social Research. She received her doctorate in Sociology from Utrecht University, the Netherlands. Her research interests include time use, the work/family interface, cross-national research, and gender differences. Tanja van der Lippe is Professor of Sociology at Utrecht University, and head of the Department of Sociology and Research Director, ICS Utrecht. Her research interests are in the area of work–family linkages in Dutch and other societies, for which she received a number of large scale grants from Dutch and European Science Foundations. She is an elected member of the European Academy of Sociology (2010), the Royal Netherlands Academy of Arts and Sciences (2014), and the Royal Holland Society of Sciences and Humanities (2013). She has published extensively on work and care of men and women in European countries. Appendix Table A1 Predictive probabilities of the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)  Table A1 Predictive probabilities of the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)  Table A2 Predictive probabilities of the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)  Table A2 Predictive probabilities of the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)  Funding This work was supported by the European Research Council (340045). 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Reasons to Reduce: A Vignette-Experiment Examining Men and Women’s Considerations to Scale Back Following Childbirth

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Abstract

Abstract The reduction of working hours can help avoid work–family conflict, yet many people who would like to scale back do not actually do so. This vignette-experiment examines which considerations are most important in men and women’s decision-making whether to scale back following childbirth. About 2,464 vignettes were conducted in the Netherlands, Sweden, and the United Kingdom. Results indicate that men find the income of their partner and career consequences most important, while women focus mainly on partner income and collegial support. Swedes, however, differ from their Dutch and British counterparts, and express more counter-gender-normative behavior. Introduction Many young parents struggle to meet the competing demands of work and family. On the one hand, their employer expects commitment from employees, but at the same time they are also expected to be involved parents (Bianchi and Milkie 2010; Blair-Loy 2003). One way to combine these responsibilities is by reducing one’s working hours following the birth of a child (Becker and Moen 1999). Reducing one’s hours—as well as using other work–family policies—enables parents to remain in the labor market while freeing time to care for their child. Research suggests that employees who reduce their work hours experience less work–family conflict (Higgins, Duxbury, and Johnson 2000; van Rijswijk et al. 2004). Experiencing less work–family conflict is associated with higher physical and mental wellbeing (Allen and Armstrong 2006; Leineweber et al. 2013); higher organizational productivity, lower absence, and lower turnover (Carlson et al. 2011; Kossek and Ozeki 1999); and lower societal healthcare costs and higher fertility rates (Castles 2003; Higgins, Duxbury, and Johnson 2004). Thus, reducing one’s hours can be beneficial for both employees, organizations, and the state. However, it is known that a significant number of people who have the right to and would like to reduce their hours do not actually do so (McDonald, Brown, and Bradley 2005; Stier and Lewin-Epstein 2003). Why these people refrain from doing so remains unclear. Understanding what underlies this “provision–utilization gap” (McDonald, Brown, and Bradley 2005; Pasamar 2015) is important for organizations and countries wishing to promote the option to reduce one’s hours; which is often done to help people reduce their work–family conflict (Kossek and Ollier-Malaterre 2012), and to promote gender equality (Haas and Hwang 2016; Kossek and Ollier-Malaterre 2012; Müller, Neumann, and Wrohlich 2016). In this paper, we use a vignette-experiment (also known as a factorial survey design) in order to disentangle people’s reasons for using—or abstaining from using—the option to reduce their working hours, and investigate which considerations are most important in men and women’s decision-making whether to scale back? Both economists and sociologists have been interested in explaining people’s reduction of working hours. They have shown that reducing one’s working hours can be costly in a number of ways, and that people often refrain from reducing their hours in order to avoid these costs—or reduce their hours when these costs are absent. Economic studies look mainly at the role of financial-economic factors on labor market decisions (such as the costs of formal childcare; when formal childcare is very expensive reducing work hours becomes more attractive) or at a comparative advantage between partners (Akgunduz and Plantenga 2015; Becker 1965; Heckman 1974). Sociological theories on the utilization of work–family policies, on the other hand, often include other types of costs, such as how utilization might be costly for one’s career (McDonald, Bradley, and Brown 2008; Perlow 1995), can have personal costs (Campbell, Charlesworth, and Malone 2012), or social costs (Kirby and Krone 2002; McDonald, Brown, and Bradley 2005). Although it is thus known that a number of economic and social considerations can be of importance to people who are deciding whether to reduce their working hours, little is known about which considerations people pay most attention to when making their decision; scaling back might be attractive in one way but costly in another. In order to gain more insight in what underlies the provision–utilization gap, research is needed that pays attention to the relative importance of these considerations. In this paper, we therefore not only include economic and social considerations but also make an important contribution to the existing literature by examining the relative importance of these considerations through the use of a vignette-experiment. In a vignette-experiment, respondents are presented with a number of short descriptions of hypothetical situations which explicitly contain factors that are—based on the literature—thought to be the most important aspects in the decision-making process of people. In our experiment, these factors are the economic and social considerations introduced above. These factors are systematically varied over the vignettes (e.g., in one vignette it is stated that the costs of childcare are high, and in the other that they are low), and after each vignette respondents are asked for their desired action: if they would be in this hypothetical situation, would they scale back or not? As each respondent is shown multiple vignettes in which the factors are systemically varied, it is possible to analyze the isolated effect of the individual factors, as well as their relative importance (Aguinis and Bradley 2014; Alexander and Becker 1978; Rossi and Nock 1982). Note that vignette-experiments thus measure hypothetical behavior rather than actual behavior, though research suggests that people’s responses to vignette-experiments match their actual behavior remarkably well (Hainmueller, Hangartner, and Yamamoto 2015). By employing a vignette, we provide an important additional perspective to existing research. Previous research mainly relied on questionnaires to investigate people’s working hours or utilization of work–family policies. This type of research is particularly well-suited for the collection of large amounts of data on easily quantifiable issues, such as weekly working hours or the utilization of policies. Questionnaires are, however, less appropriate for the investigation of complex decision-making situations, while this is precisely the strength of vignettes. Therefore, research based on questionnaires and research based on vignette-experiments complement each other. There are three main reasons why vignette-experiments are well suited for testing complex decision-making situations. First, people are often not aware which factors enter into their own decision-making process, making it difficult (if not impossible) for them to provide an accurate answer when asked directly about their motivations in a questionnaire (Alexander and Becker 1978). By using a vignette-experiment, we ensure that respondents do not need to be conscious of the considerations underlying their decision-making; instead the quasi-experimental setting enables the researchers to disentangle the considerations presented. Second, complex decision-making situations can be sensitive topics, and thus there is a risk that people may express biased, socially desirable answers. In our case, this might, for example, mean that women who do not want to scale back to care for their child will still say that they will do so, because they feel that this is expected of them. However, while the risk of social desirability is not absent from vignette-experiments, it is maintained to be smaller than in questionnaires because the theoretically relevant factors are “hidden” in the vignettes (Alexander and Becker 1978; Wallander 2009). This ensures that respondents are not fully attentive to the factors, and thus not as likely to consciously bias their reports with socially desirable answers as they would have been had they been asked directly about their judgment. Last, research based on questionnaires is often cross-sectional, and thus cannot shed light on the causal direction. In the context of people’s decision-making to scale back it is, for example, unclear whether people do not get promoted because they work part-time, or start working part-time because they do not get promoted. Vignette-experiments are well suited for investigating causal relations as variations in working hours and other variables of theoretical interest can be exogenously determined and systematically varied (Aguinis and Bradley 2014; Wallander 2009). According to Kelly et al. (2008), the absence of studies allowing for causal inferences is one of the main lacuna in work–family research, which led them to call for more (quasi-)experimental research. In the context of work–family policies, vignette-experiments have already been employed to examine managers’ decision-making, either regarding the provision of work–family policies (Been et al. 2017) or regarding their acceptance of utilization requests (den Dulk and de Ruijter 2008; Klein, Berman, and Dickson 2000). Most work–family research focuses exclusively on the decision-making of women (Haas and Hwang 2016), which is unfortunate as work–family policies are increasingly offered to and used by men, and promoting male utilization is employed as a tool for increasing gender equality (Haas and Hwang 2016; Kossek and Ollier-Malaterre 2012; Müller, Neumann, and Wrohlich 2016). However, as gender expectations for men and women continue to differ, and male utilization of work–family policies continues to lack behind that of women (even in countries with a high level of gender equality, such as Sweden; Haas and Hwang 2009, 2016), it is to be expected that men and women pay attention to different considerations when making their decision whether or not to reduce their hours. Therefore, we will separately investigate the relative importance of considerations for men and for women. Similarly, a lot of research focuses on the individual without considering how the cultural context might impact individual decision-making (Ollier-Malaterre et al. 2013). We aim to provide insight into how the decision to scale back is made differently in different contexts, by focusing on the Netherlands, Sweden, and the United Kingdom, three countries with varying working-cultures and levels of gender equality. The Netherlands is characterized by the fact that it has many policies that facilitate a more traditional division of labor between parents, with the man being the main breadwinner. Sweden, on the other hand, has many formal policies designed to support dual-earner families and gender equality. Lastly, the United Kingdom can be seen as a market-oriented country, where the government neither supports gender equality nor traditional gender roles, but leaves it up to market forces to shape gender relations (Korpi 2000; Korpi, Ferrarini, and Englund 2013). In each of the selected countries, part-time work is relatively common, and most employees are entitled to scale back if they would want to do so (Roeters and Craig 2014), which ensures it would be relatively easy for respondents to identify with the hypothetical situations presented. Data were collected as part of the European Sustainable Workforce Survey (van der Lippe et al. 2016). Theoretical Background Individual Considerations Financial costs According to the micro-economic theory of labor supply, people decide rationally how much time (if any) they want to spend on the labor market, depending on the potential financial gains from working (Killingsworth 1983; Mincer 1962). Many parents of young children who wish to work have to arrange for their children to be cared for by others during these hours, and formal childcare can be expensive. It should be noted that this does not equally apply to all parents, though, as some work alternate shifts, rely on free informal childcare by friends or relatives, or live in countries where childcare is heavily subsidized. The net-gains of working for parents are thus not only affected by their salary but also by the costs of childcare (Cloïn 2010; Heckman 1974). If one has a high earning potential, an extra hour of work becomes more profitable, and the opportunity costs of not working are higher. This makes it logical to want to participate more in the labor market. It follows that when the costs for childcare are low, an hour of work is more profitable, and people want to work more hours. Conversely, when the costs are high, parents are more likely to want to scale back. Empirical studies have also shown this by modeling the increase in (female) labor participation as a result of a decrease in (net) childcare costs (Akgunduz and Plantenga 2015). Therefore, we expect that employees are more likely to reduce their working hours if the financial benefits of working are lower due to high costs of childcare (H1). Career costs Many people do not only work to earn money but also aspire to have a successful career (Eurofound 2012; van der Horst 2014). Reducing one’s working hours can be costly because it harms one’s promotion prospects (McDonald, Bradley, and Brown 2008). In many organizations in Europe and United States, a notion of an ideal worker persists which is based on the traditional male breadwinner: a highly committed, full-time worker, with limited care-giving responsibilities (Acker 1990; Haas and Hwang 2016; Reid 2015). In these organizations, the amount of hours one puts into one’s job are often seen as indicative of one’s commitment to the organization and, relatedly, to one’s ambition to advance in the organization. Consequently, employees who scale back can be perceived as not fully committed and thus less ambitious, which affects their chances of being promoted (McDonald, Bradley, and Brown 2008; Perlow 1995). Empirical studies have also found that perceived negative career consequences limit the uptake of work–family policies (Darcy et al. 2012; McDonald, Bradley, and Brown 2008; Smith and Gardner 2007). Therefore, we expect employees to be more likely to reduce their working hours if they do not perceive this to have negative career consequences (H2). Personal costs People also engage in paid work because they find their job intrinsically rewarding: work can be interesting, challenging, meaningful, or simply enjoyable (Eurofound 2012; Wilson 2006). When one changes one’s working hours the enjoyability of a job might decrease for two reasons. First, people who work fewer hours tend to be assigned less challenging, lower status tasks—even when holding the same position as their full-time counterparts—because their superiors tend to assign them projects without tight deadlines, or without high-profile clients (Campbell, Charlesworth, and Malone 2012; McDonald, Bradley, and Brown 2009). Second, the enjoyability of the job might also decrease because only more enjoyable tasks can be cut in order to allow for a decrease in working hours, as other—less enjoyable—tasks will always continue to be required. For example, after a reduction in hours someone might still be required to attend meetings and do administration, which will cost the same amount of time as before, and thus these tasks will from then on take up a larger proportion of the job than before. We are not aware of any empirical studies examining the effect of anticipated changes in job enjoyment on the utilization of work–family policies. However, studies do show that people value their job enjoyment (Graves et al. 2012; Sturges 2013; Wilson 2006), which would suggest that they are reluctant to give this up. Therefore, we hypothesize that employees are more likely to reduce their working hours if they do not think that this will affect the enjoyability of their job (H3). Social costs Most people spend a lot of time with their colleagues, and wish to maintain a positive—or at least not negative—relationship with them (Eurofound 2012). The extent to which co-workers support their colleagues who want to use work–family policies varies. Some employees are very supportive toward their colleagues’ (anticipated) use of work–family programs, either because they believe this to be important, or because they experience similar choices or work–life struggles themselves. This can consequently encourage employees to apply to use such policies (Kirby and Krone 2002). Conversely, however, employees can also be resentful toward their co-workers who use work–family policies as they themselves feel excluded from enjoying these “privileges,” for example because they do not have children, or have a stay-at-home spouse (Kirby and Krone 2002). Colleagues might also be unsupportive as they have to (or fear they might have to) take on additional workload, or perform a greater share of unpleasant tasks, such as working on holidays. Their negative attitude can discourage employees from applying to reduce their working hours (Boren and Johnson 2013; Kirby and Krone 2002; McDonald, Bradley, and Brown 2009). Empirical studies have shown that employees with supportive colleagues (Waters and Bardoel 2006), or with colleagues who used work–family policies themselves (Bygren and Duvander 2016; Dahl, Løken, and Mogstad 2012) are more likely to use these policies. This leads us to H4: employees are more likely to reduce their working hours if they experience collegial support for this. Household Considerations So far, we considered the decision to scale back as an individual decision, but work–family decisions of partners are often coordinated. Couples can opt for one, both, or neither partner to reduce their hours (Becker and Moen 1999). According to Becker’s New Home Economics theory (1965), specialization yields the highest household utility because both partners can capitalize on and develop their comparative advantages. The partner with the highest earnings has a comparative advantage in paid work, and thus it would be rational that he or she specializes in employment and does not scale back, whereas the partner with the lowest hourly wage will specialize in unpaid work, including childcare, and may have a smaller, part-time job on the side. Empirical evidence suggest that couples with young children indeed often specialize, and that the relative earnings of the partners influences who scales back—although gender also plays a role here (Becker and Moen 1999; Kanji 2013; Kühhirt 2012). For now, we still leave gender out of the equation, and hypothesize that employees are less likely to reduce their working hours if they earn more than their partner (H5), and that they are more likely to reduce their working hours if they earn less than their partner (H6). Gender Gender differences in the likelihood to reduce It is known that women scale back more often than men (Becker and Moen 1999; van Gils, Kraaykamp, and van der Lippe 2009). Partially, this might be explained by the process discussed earlier: women tend to earn less than their male partners (due to differential wages and a tendency for homogamy), and therefore it is more often rational for the female partner to scale back and the male partner to specialize in paid work. Simultaneously, a gender perspective suggests that another reason why women scale back more often than men is that societal expectations on the role of men and women differ, and that people tend to conform to these expectations as it is costly to violate social norms of appropriate behavior (Akerlof and Kranton 2000; West and Zimmerman 1987). Although the traditional breadwinner–homemaker model is no longer dominant in Europe, it still “profoundly impacts how gender organizes societies,” by continuing to persist as an ideal, where the work role still firstly lies with the husband, and the responsibility for the home and children with the wife (Kanji and Samuel 2017). Because scaling back is in line with gender expectations for women but not for men, we expect that women will more often choose to reduce their working hours and take up childcare responsibilities than men, even in similar circumstances (as is the case in our vignette experiment). Therefore, we expect that women are more likely to reduce their working hours than men (H7). Gender differences in the relative importance of considerations Taking this reasoning one step further, we will not only test how gender expectations influence men and women’s overall willingness to scale back but also explore whether gender expectations influence which consequences associated with scaling back men and women perceive as most important. In other words, men and women might differ in which considerations they focus on most when considering whether to scale back. Building upon the reasoning set out above it can be argued that in industrialized societies career orientation is central to the male identity (Gilmore 1990). Because men have learned that it is important for them to have a successful career, in line with “doing gender”, avoiding career costs would be important in their decision-making (West and Zimmerman 1987), and thus they would be reluctant to scale back when they think that this will have negative career consequences (van der Horst 2014). Furthermore, because men tend to be more career oriented, they might be more reluctant to specialize in unpaid work, even when their partner earns more than they do (Gilmore 1990; Greenstein 2000). Women, on the other hand, continue to shoulder the main responsibility for the home, and more often have a “job” rather than a “career” (Becker and Moen 1999). This means that in general work tends to be less central to their identity than it is for men. Therefore, it is likely that women display their feminine identity through greater importance to non-career considerations: financial costs (both the costs of childcare and the relative income of their partner), personal costs (whether it will continue to be enjoyable for them to work), and social costs (the attitudes of colleagues). Previous studies have indeed found that non-career aspirations are valued more by women, and career aspirations more by men (Konrad et al. 2000; van der Horst 2014). The Country Context Our research is conducted in the Netherlands, Sweden, and the United Kingdom. We selected these countries because in each of them part-time work is relatively common and many employees have the right to request changing their working hours, which makes it realistic for respondents to envision themselves in a situation where they might reduce their working hours. These three countries are similar in many respects, such as levels of fertility, marriage, and cohabitation (OECD 2017b); however, they are also very different in their working-cultures and levels of gender equality, and consequently different levels of part-time work (see table 1 for an overview of the male, female, and total prevalence of part-time work in these countries). As it can be expected that these different country contexts affect individual employees’ decision-making regarding working hours, we will take an explorative approach to see whether reasons to reduce differ in these countries. Table 1 People working part-time as a percentage of the employed, in the Netherlands, Sweden, and the United Kingdom (age 15–64 years), 2016   Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8    Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8  Source:Eurostat (2017). Note: Dutch respondents are considered to be working part-time if their usual working hours are <35. Respondents from Sweden and the United Kingdom are seen as part-time employees when they self-identified as doing so. Table 1 People working part-time as a percentage of the employed, in the Netherlands, Sweden, and the United Kingdom (age 15–64 years), 2016   Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8    Total (%)  Men (%)  Women (%)  The Netherlands  49.7  26.2  76.4  Sweden  23.9  13.0  35.6  United Kingdom  25.2  11.3  40.8  Source:Eurostat (2017). Note: Dutch respondents are considered to be working part-time if their usual working hours are <35. Respondents from Sweden and the United Kingdom are seen as part-time employees when they self-identified as doing so. According to Korpi’s (2000; Korpi, Ferrarini, and Englund 2013) typology of gendered policy models in modern welfare states, the three countries belong to different clusters, and carry out different policies regarding gender equality and female labor participation, with Sweden belonging to earner-carer group, the Netherlands to the traditional-family group, and the United Kingdom to market-oriented group. Sweden has many formal policies designed to support equality between the sexes, and actively supports dual-earner families, for example through high-quality, heavily subsidized public childcare. This has contributed to a high level of female labor participation, which is to a large extent full-time or long part-time. In Sweden, all parents with children under the age of eight have the right to reduce their work hours to 75 percent of full-time. However, although gender equality is high on the agenda in Sweden, part-time work is much more prevalent among women than men, and this gender distinction is even more apparent among parents with young children. In couples with two children where the youngest child is between three and five years old, 43 percent of women and 8 percent of men work part-time (Evertsson et al. 2009; Swedish Labour Force Survey 2016). The Netherlands, on the other hand, belongs to the “traditional-family” countries, meaning that its policies to a larger extent facilitate the traditional male breadwinning family rather than gender equality (Korpi 2000; Korpi, Ferrarini, and Englund 2013). Paternity leave, for example, is very limited, and there is no heavily subsidized public childcare. In the Netherlands, a “one-and-a-half earners model” has become dominant (Visser 2002), and it is almost natural for women to work part-time. The gap between male and female working hours is largest among men and women with live-in children and a partner: in 2015 women in this category worked an average of twenty-four to twenty-six hours a week, while their male counterparts worked approximately forty hours a week (Portegijs and van den Brakel 2016). Part-time work in the Netherlands is well regulated and protected, due to “what is probably the most comprehensive state effort to increase high quality part-time work” (Gornick and Meyers 2003, 165), which includes the right of most Dutch employees—not only parents—to request a decrease (or increase) in their working hours (although there are a few exceptions) (den Dulk 2016). Although it is especially common for Dutch women to work part-time, part-time work among Dutch men is compared to other EU member states also relatively high, though much lower than among women (Eurostat 2017). The United Kingdom, on the other hand, belongs to the group of market-oriented countries, meaning that the government neither actively supports gender equality, nor supports traditional gender roles, but instead leaves it up to market forces to shape gender relations (Korpi 2000; Korpi, Ferrarini, and Englund 2013). This orientation on the free market means, for example, that the level of protection for (intended) part-time employees is much lower than in the Netherlands and Sweden, and the quality of part-time jobs is generally lower than that of full-time jobs. This should be understood as an institutional impediment to scaling back: switching to working part-time means for many people in the United Kingdom that they have to sacrifice job quality, and thus scaling back will not be an attractive option for many ambitious employees. Another important factor is that childcare in the United Kingdom is very expensive, which means that “for too many families it simply does not pay to work” (Rutter 2015). In addition, in the United Kingdom, part-time work is mainly a women’s issue, and mothers in particular often work part-time: 58 percent of mothers with a child of preschool age do so (Cory and Stirling 2016). In the United Kingdom, all employees who have been with their employer for over twenty-six weeks can request a reduction of working hours, however, there are more “opt out” possibilities for employers in the United Kingdom than in Sweden or the Netherlands, including, for example, the burden of additional costs, inability to recruit additional staff, or a detrimental impact on the quality of service (EurWORK 2014). While part-time work in the United Kingdom is relatively prevalent, comparable with Sweden, it should be noted that involuntary part-time work is more common in the United Kingdom than in the other two countries (OECD 2017a). Method Sample To test our hypotheses, we use data from the European Sustainable Workforce Survey (van der Lippe et al. 2016) that were collected in 2015/2016. In addition to the vignette-experiment, this dataset includes multilevel organization data based on questionnaires filled out by employees, their managers, and the HR-managers. Linking the vignettes to an organizational survey was done so we could link the data obtained through the vignettes to respondent- and organization-level data obtained from the questionnaire. Organizations were sampled based on their representation of three different sizes (1–99 employees; 100–249; 250 or bigger) and six different sectors (manufacturing, health care, higher education, transportation, financial services, and telecommunication), using a combination of stratified random sampling (through national business lists) and personal connections. Thus, in all three countries employees belonged to the same six sectors. Initially, participation of the organizations was solicited, and after they agreed to participate employees were contacted at work and requested to fill out the survey, either online or on paper. After employees completed the questionnaire they were asked if they wanted to participate in the vignette study (“an interesting thought-experiment”), which followed immediately after. Only respondents who were younger than forty were invited to participate in the vignette, as we wanted it to be a realistic option for respondents that they might be expecting a child. One of the main advantages of vignette-experiments is that they permit general conclusions about causal mechanisms using nonrandom samples, as long as certain criteria for internal and external validity are met (Auspurg and Hinz 2015). Internal validity is ensured by administering the vignettes at random and having each vignette rated by numerous respondents. External validity is less straightforward, but relies on the theoretical question whether the causal mechanism holds for all people, or only for a selective subgroup. For testing causal mechanisms that are considered universal a homogeneous convenience sample is deemed sufficient to generalize to the entire population (which is why student samples are often used in (vignette-)experiments). However, if one assumes that such a causal mechanism functions differently for separate sub-groups, one cannot automatically generalize results from a non-representative subsample to the entire population. As we assumed that the mechanism we were trying to test would only apply to a certain sub-group—namely employed individuals of childbearing age—we only administered the experiment to respondents belonging to this group. This is also the reason why we used separate samples of men and women; we worked from the assumption (based in theory) that the mechanism would function differently for men and women. The response rate was 61.4 percent for the questionnaire, and 57.2 percent for the vignettes, leading to a total of 743 respondents. From the initial sample of 743, we excluded subjects who had not completed all the vignettes, as this would prevent us from analyzing the within-subject variation resulting from the vignette-factors (n = 102, 14 percent). We also excluded respondents who were over forty but filled in the paper vignettes anyway (n = 22, 3 percent), or who had missing values on any of the independent or control variables, which was only the case for their working hours (n = 3, <1 percent). The final sample consisted of 616 respondents, and as each respondent filled in four vignettes we had a total of 2,464 vignettes. As the vignette, not the respondent, is the unit of analysis, N = 2,464 (Atzmüller and Steiner 2010; Wallander 2009). Considering the simplicity of our vignette-experiment, with a relatively small number of variables of interest, this is a rather large sample (Ganong and Coleman 2006). The Vignette Before respondents were presented with the actual vignettes, they were shown a short introduction. It was explained to them that they would be shown four “hypothetical scenarios” relating to a situation in which they and a partner were “expecting a(nother) child” (whether the respondent had children was added as a control variable). Respondents were asked to imagine the following to happen to them in their current job, and to express if and how much they would like to reduce their working hours in that situation. It was also specified that the situations referred to “you and your partner,” and asked respondents without a partner to answer the questions according to how they would respond if they were to have a partner. In relation to the hypotheses set out above, our vignette included the independent variables childcare costs, career consequences, enjoyment, collegial support, and partner income, which each had two or three manipulations that varied systematically between the vignettes. Childcare costs reflected the costs of childcare in relation to one’s income (0 = much lower, 1 = about the same). Career consequences told people whether working fewer hours would affect their promotion prospects (0 = less likely to be promoted, 1 = chances will not be affected). The variable enjoyment told people whether working fewer hours would affect the enjoyability of their job (0 = you will have to give up some tasks you really enjoy, 1 = you will continue to do the same type of tasks, and your work will remain as enjoyable as it is now). Furthermore, collegial support indicated whether colleagues would disapprove (= 0), or approve (= 1) when they would reduce their working hours. Lastly, partner income told people how much their partner earned in relation to themselves (1 = less, 2 = about the same, 3 = more), which was recoded into two dummies. After each vignette respondents were asked: “In this situation, would you reduce your contract to work fewer hours per week?” (0 = no, 1 = yes), this was used as our dependent variable. Figure 1 shows an example of a vignette. Figure 1 View largeDownload slide Example of a vignette. Figure 1 View largeDownload slide Example of a vignette. Respondent Characteristics In addition to the manipulated vignette-factors, we included a number of respondent-level characteristics. In line with our different expectations based on gender and country, we included the sex of the respondent (0 = female, 1 = male), and the country of residence (1 = the Netherlands, 2 = Sweden, 3 = United Kingdom). Moreover, we included a number of control variables, namely age (16–39 years), whether the respondent lived with a partner (0 = no, 1 = yes), and whether the respondent had minor children (0 = no, 1 = yes). We also included the respondent’s current working hours (5–70), as we assumed that respondents who already worked fewer hours would be less likely to want to reduce even more. Analytic Strategy Unlike regular regression models, in a vignette experiment the vignette is seen as the level of analysis, not the respondent. As four vignettes are shown to each respondent the vignettes are nested within the respondents, which makes a multilevel analysis appropriate (Atzmüller and Steiner 2010). We first ran an empty model in order to calculate the intraclass correlation coefficient to determine how much variance is explained by each level (the vignette and the respondent level). Subsequently, we applied a multilevel logistic regression model to test our hypotheses. Analyses were conducted for all respondents together, as well as separately for men and women, and for men and women per country, in order to see whether the different subgroups focus on different considerations. Results are presented as average marginal effects rather than the estimated coefficients, because these are easier to interpret, especially for logistic regression (Jann 2013; Mood 2010). The average marginal effects express how the probability of the dependent variable being 1 (i.e., people want to reduce) changes as the independent variables change from 0 to 1 for binary variables, or for a one unit increase for continuous variables, holding the other variables constant. In other words, if, for example, collegial support has an average marginal effect of 0.1, this means that when people were shown the vignette that indicated that their colleagues would approve of them scaling back, they were 10 percentage points more likely to want to reduce their hours than if they saw vignettes which stated that their colleagues would disapprove, keeping everything else constant. In addition, the average marginal effects will also be presented in a plot to visualize the relative sizes of the effects, and thereby aid the interpretation of the relative importance of the factors. Results Descriptive Statistics Descriptive statistics are presented in table 2. Our sample contained about the same number of men and women, and over half (56 percent) of the respondents were Dutch, while 22 percent were Swedish and 22 percent British. The average age of our respondents was thirty-one, 70 percent lived with a partner and 40 percent had minor children. Moreover, on average people worked 39 hours per week, though Dutch women in particular have a much lower average (34 hours) than the other groups (39–41). When responding to the vignettes, respondents indicated 59 percent of the time that they would want to reduce their working hours in the situation presented in the vignette. Women did so more often than men: 64 percent of the time as opposed to 53 percent. Table 2 Descriptive statistics (SD)   Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67    Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67  Table 2 Descriptive statistics (SD)   Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67    Total  Men   Women     (N = 616)  Total (n = 303)  NL (n = 167)  SW (n = 69)  UK (n = 67)  Total (n = 313)  NL (n = 177)  SW (n = 65)  UK (n = 71)  Respondent characteristics   Male  0.49                   Age  31 (5)  31 (5)  31(5)  33(5)  29(5)  31(5)  31(5)  32(5)  29(5)   Partner  0.70  0.72  0.68  0.86  0.67  0.68  0.71  0.71  0.58   Child (ren)  0.40  0.39  0.35  0.55  0.33  0.42  0.46  0.51  0.24   Working hours  39 (9)  41 (8)  41 (9)  41 (7)  40 (9)  37 (8)  34 (9)  40 (5)  39 (7)   Country (NL)  0.56  0.55        0.57          Sweden  0.22  0.23        0.21          UK  0.22  0.22        0.23        Dependent variable                     Would reduce hours  0.59  0.53  0.53  0.62  0.46  0.64  0.64  0.62  0.67  Hypotheses Testing Table 3 shows the average marginal effects predicting the desired reduction of working hours for all respondents and by gender. Based on the empty model (not shown here), we calculated the intraclass correlation coefficient, which is 0.21 for the vignette level and 0.79 for the respondent level. Thus, the factors specified on the vignette account for 21 percent of people’s decision-making, while differences between people account for the remaining 79 percent of the variance. Looking at the total sample, we found support for all hypotheses: employees were more likely to want to reduce their working hours if the costs of childcare are high compared to their wage (H1), they do not expect this to have negative career consequences (H2), they do not think that this will affect the enjoyability of their job (H3), they experience collegial support for this (H4), and when they earn less than their partner (H6). Employees were less likely to reduce their hours when they earn more than their partner (H5). Moreover, women were more likely to reduce their hours than men (H7). The predictive probability of wanting to reduce is 54 percent for men and 80 percent for women (the predictive probabilities of all factors can be found in table A1). Table 3 Average marginal effects predicting the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Table 3 Average marginal effects predicting the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.074*** (0.020)  0.049 (0.033)  0.091*** (0.024)   No career consequences (vs. likely consequences)  0.088*** (0.020)  0.165*** (0.034)  0.025 (0.023)   No change in enjoyment (vs. loss of enjoyable tasks)  0.052* (0.022)  0.100** (0.037)  0.019 (0.025)   High collegial support (vs. no support)  0.112*** (0.022)  0.083* (0.037)  0.137*** (0.027)   Partner earns (ref. same)          Less  −0.225*** (0.031)  −0.206*** (0.051)  −0.218*** (0.038)    More  0.122*** (0.025)  0.211*** (0.045)  0.059* (0.029)  Respondent characteristics   Male  −0.259*** (0.045)       Age  0.007 (0.005)  0.007 (0.009)  0.008 (0.006)   Partner  0.087 (0.054)  −0.127 (0.095)  0.166** (0.057)   Child(ren)  −0.302*** (0.060)  −0.077 (0.099)  −0.386*** (0.077)   Current working hours  0.015*** (0.003)  0.012** (0.004)  0.016*** (0.003)   Country (ref. NL)         Sweden  0.044 (0.056)  0.236** (0.089)  −0.128 (0.073)   UK  −0.110 (0.060)  −0.157 (0.108)  −0.117 (0.068)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Relative Importance for Men and Women To see which considerations are most important in men and women’s decision-making, we turn to the size of the average marginal effects. Figure 2 shows a plot of the average marginal effects presented in table 3 to visualize the differences in effect-sizes. For men, we found a significant effect of all factors except childcare costs. The most important factors in the decision-making of men are the relative income of their partner and career consequences. When men earn less than their partner they are 21 percentage points less likely to want to reduce their working hours than when they earn about the same, and when they earn more compared to the same their likelihood increases with 21 percentage points. Similarly, expecting no career consequences makes men 17 percentage points more likely to want to reduce than when they do expect career consequences. Turning to women, we find no significant effect of career consequences and enjoyment. In addition, for women, their partner’s income is the most important factor: the likelihood that a woman will reduce her hours reduces by 22 percentage points when her partner earns less compared to when he earns the same. However, when her partner earns more than she does, the likelihood that she will reduce her hours is only 6 percentage points higher than when he earns the same (discussed below). The second most important factor in women’s decision-making is collegial support. When women experience collegial support their probability of reducing becomes 14 percentage points larger. Lastly, when the costs of childcare are close to one’s hourly wage, women become 9 percentage points more likely to reduce than when the costs of childcare are lower. Figure 2 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, for all respondents and by gender. Figure 2 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, for all respondents and by gender. It stands out that when their partner earns more, women only become 6 percentage points more likely to reduce their hours, while for men this increases by 21 percentage points. When we look at the absolute predictive probabilities (table A1) we see that this is because women are already more likely to want to reduce their hours than men. When a woman earns the same as her partner her probability of wanting to reduce is 77 percent, while for men in this situation this is 60 percent. When a woman earns less than her partner her likelihood of reducing increases by “only” 6 percentage points compared to 83 percent, but this is still higher than it is for men, who increase by 21 percentage points to a predictive probability of 81 percent. Country Differences In addition, we conducted further analyses to explore the differences between men and women in the different countries, the results of which can be found in table 4 and plotted in figure 3. We see that for almost all groups the income of the partner was the most important factor, but we see some important differences between the groups. For Dutch and British men, the probability of reducing increases strongly when their partner earns more (in both cases by 20 percentage points), and decreases strongly when their partner earns less (NL: 20; UK: 30 percentage points). However, while Swedish men become 16 percentage points more likely to reduce when their partner earns more, no significant decline is found when their partner earns less. Turning to women, we see that partner income has no significant effect for Swedes. For both Dutch and British women, the likelihood of reducing decreases when their partner earns less (NL: 17 percentage points; UK: 29 percentage points), but while Dutch women become more likely to reduce their hours when their partner earns more (10 percentage points), for British women no significant difference is found. Again we turned to the predictive probabilities (table A2) to shed more light on the aspects that stand out. We see that in the situation where the partner earns the same, Dutch and British men are much less likely to reduce their hours (NL: 60 percent; UK: 47 percent) than their female counterparts (NL: 71 percent; UK: 82 percent), and while men’s likelihood to reduce is much more affected by the income of their partner and thus varies more, the absolute likelihood of reducing remains higher for women (men NL: 79 percent; UK: 67 percent; women NL: 81 percent; UK: 79 percent). Swedish men, on the other hand, are compared to other men much more likely to reduce when their partner earns the same (75 percent), and no significant decline is found when their partner earns less. Swedish women have an 80 percent likelihood of reducing when their partner earns the same, but for them no significant change is found resulting from partner income. Table 4 Average marginal effects predicting the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Table 4 Average marginal effects predicting the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics   Childcare costs close to hourly wage (vs. lower)  0.059 (0.049)  0.055 (0.052)  0.027 (0.054)  0.064* (0.027)  0.075 (0.054)  0.156** (0.051)   No career consequences (vs. likely consequences)  0.182*** (0.051)  0.134* (0.057)  0.128* (0.054)  0.051 (0.027)  0.128* (0.057)  −0.099* (0.050)   No change in enjoyment (vs. loss of enjoyable tasks)  0.117* (0.056)  0.163* (0.066)  −0.020 (0.058)  −0.003 (0.030)  0.134* (0.061)  0.021 (0.051)   High collegial support (vs. no support)  0.128* (0.055)  −0.030 (0.056)  0.081 (0.062)  0.088** (0.031)  0.220** (0.072)  0.156** (0.060)   Partner earns (ref. same)                Less  −0.200** (0.076)  −0.071 (0.084)  −0.304*** (0.086)  −0.172*** (0.041)  −0.112 (0.078)  −0.285*** (0.081)    More  0.194** (0.067)  0.163* (0.071)  0.205* (0.099)  0.101** (0.037)  −0.006 (0.065)  −0.029 (0.059)  Respondent characteristics   Age  0.012 (0.013)  0.006 (0.015)  −0.006 (0.015)  −0.002 (0.007)  0.037* (0.016)  0.014 (0.009)   Partner  −0.026 (0.145)  −0.172 (0.112)  −0.199 (0.181)  0.235*** (0.060)  −0.131 (0.125)  0.113 (0.096)   Child(ren)  −0.090 (0.152)  0.135 (0.159)  −0.384* (0.177)  −0.350*** (0.093)  −0.256 (0.155)  −0.474*** (0.135)   Current working hours  0.009 (0.006)  0.020* (0.009)  0.010 (0.007)  0.020*** (0.003)  0.018 (0.015)  −0.004 (0.007)  Note. Average marginal effects (dy/dx) were calculated as the discrete change from the base level. * p < 0.05 ** p < 0.01 *** p < 0.001. Figure 3 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, by gender and country. Figure 3 View largeDownload slide Plotted average marginal effects predicting the desired reduction of working hours, by gender and country. Moreover, for men in all three countries the probability of wanting to reduce increases strongly when they expect no career consequences (NL: 18; SW: 13; UK: 13 percentage points), and Swedish men are also much more likely to reduce their hours when they do not expect a change in enjoyment (16 percentage points). Apart from partner income, collegial support was the most important factor for women in all three countries (NL: 9; SW: 22; UK: 16 percentage points). Similar to their male counterparts, Swedish women also attach great importance to whether they expect a change in enjoyment and to not expecting career consequences; in both cases they are 13 percentage points more likely to want to reduce. British women, and to a lesser extent also Dutch women, also pay attention to whether the costs of childcare were close to their hourly wage, in which case they were 16 and 6 percentage points, respectively, more likely to reduce. Unexpectedly, we found for British women also a negative effect of career consequences, meaning that when they expect that reducing their hours will have no career consequences, they are 1 percentage point less likely to scale back. Sensitivity Analyses A number of sensitivity analyses were performed. As it might be difficult for respondents without a partner to report about how they would behave if they were to have a partner, we ran the analyses excluding single people. Similarly, we ran the analyses including only people who did not have children, as it can be argued that people who are parents have already made the decision whether they want to scale back or not, and thus are unlikely to scale back even more. On the other hand, it might be difficult for people without children to really anticipate what having children will be like, and therefore, we also ran the analyses including only people with children. Furthermore, we included the controls sector (manufacturing, health care, higher education, transportation, financial services, and telecommunication), type of job (ISCO), and job status (ISEI) in turn to see whether the mechanism would function differently for respondents in different sectors or with different jobs. Moreover, to see whether the results were mainly driven by one country, we repeated the analyses excluding each of the countries in turn. Lastly, we included a variable representing the order in which respondents had seen the vignettes, as respondents might tire and focus only on one or two considerations rather than the whole vignette, leaving earlier choices to differ from later choices. Results were in all cases very similar, which suggests that our findings are robust. Discussion In this paper, we have examined how people make the decision whether or not to reduce their working hours following the birth of a child. Reducing one’s hours can enable employees to be engaged in childcare, while continuing their involvement in employment. However, little is known about why people who want to and have the right to reduce their hours refrain from doing so. With our study, we aim to shed further light on this in four ways. First, we have combined two prominent approaches toward studying work hour reductions by combining economic theories regarding determinants of working hours with sociological theories on the utilization of work–family policies. Second, by using a vignette-experiment, we were able to not only examine whether people find these costs important but to also investigate the relative importance of these considerations. Third, contrary to most previous research, we have included both men and women, rather than only women, and thereby contribute to the understudied understanding of male utilization. Fourth, by focusing on the Netherlands, Sweden, and the United Kingdom, we aim to allow insight into how the decision to scale back is made differently in different cultural contexts. Our findings suggest that both economic and social considerations play a role in people’s decision-making to scale back—although there are gender and country differences in which considerations are most important. Financial considerations, specifically the comparative advantage between partners, is an important consideration for both men and women—though in different manners. Additionally, how utilization might be costly for one’s career factors strongly into the decision-making of men, and social costs (the support of colleagues) into the decision-making of women. With regards to the different countries, we see that Swedish women in particular, and to a lesser extent also Swedish men, stand out as they express more counter-gender-normative behavior. In addition, women are generally much more likely to indicate that they want to reduce their hours than men. One of our most striking findings is that for both genders the relative income of their partner is the most important consideration, but when we look closer the picture is more complex. Men are overall more likely to indicate to want to reduce their hours as their partner’s income relative to their own increases. Women, on the other hand, are very likely to want to reduce their hours both when their partner earns more and when their partner earns the same. This indicates that the reduction of working hours for childcare purposes continues to be a gendered decision. The default, at least from a female perspective, is that they will be the one to reduce their hours, and women only deviate from this when this is very financially appealing. This is in line with our expectations; because the breadwinner–homemaker model continues to impact gender norms we expected women to be more likely to take up childcare responsibilities than men (Kanji and Samuel 2017). Turning to which considerations are most important for the different sexes, our finding that men focus strongly on whether reducing their hours will have career consequences aligns with the notion that career orientation is central to the male identity (Gilmore 1990). As men have learned that having a successful career is important, they wish to avoid behavior that could harm their career, and are thus reluctant to scale back when they think that this could hamper their promotion prospects (West and Zimmerman 1987). On the other hand, our finding that the relative income of the partner is the strongest predictor of men’s reduction of working hours—even stronger than the possibility of career consequences—is a surprising one. Based on the literature, we expected men to wish to continue to work many hours even when their partner earns more because it is important to them to be the main provider (Gilmore 1990; Greenstein 2000), yet we find the opposite. Our results suggest that financial considerations might be more important to men than gender normativity. This could imply that the reason why men work part-time less often than women (Eurostat 2017) is not (solely) that men behave gender-normatively and wish to be the main provider, but that this is also due to the wage gap for women, which leaves men to more often have a comparative advantage in paid work (Becker 1965; Eurostat 2015). Additionally, this could also stem from maternal gatekeeping, i.e., the notion that mothers can inhibit fathers’ involvement in childcare (Allen and Hawkins 1999). Although men express a willingness to reduce their hours if they earn the same as their partner, we see that women are even more willing to do so, and as work–family decisions of partners tend to be coordinated this might result in men scaling back less often, even though they would have been willing to do so. Moreover, we found that women focus mainly on non-career considerations in their decision-making to scale back, primarily social costs and financial costs, which aligns with previous research (Konrad et al. 2000; van der Horst 2014). As discussed earlier, we found that women’s likelihood of reducing was strongly affected by their income relative to their partner’s. This is in line with our expectations; women are more likely to reduce when this is financially sensible. Whether there will be social costs (i.e., if their colleagues disapprove) is their second most important consideration. This suggests that women are, to a greater extent than men, influenced by their social environment, and find it important to receive the support of others for their actions. Contrary to what we expected we found no significant effect of personal costs (i.e., the enjoyability of the job) on women’s desire to reduce their working hours, while we did find this to play a role for men. We expected that the notion that women tend to have a “job” rather than a “career” (Becker and Moen 1999) would make that women find it important that their job is something they enjoy—otherwise they might as well drop out of employment completely. However, it might be that it is precisely because they have a job instead of a career that they find the enjoyability of the work less important: the time spent on work does not have to be terribly enjoyable or intellectually satisfying as it is not central to their identity, but rather something that is done “on the side,” next to other aspects of one’s life. This would also explain why we did find enjoyability to play a role for men. Turning to country differences, we see that Swedish women in particular, and to a lesser extent Swedish men, stand out by expressing more counter-gender-normative behavior. Unlike for Dutch and British women, the income of the partner and the costs of childcare are not important to the decision-making of Swedish women. Simultaneously, they—like men from all countries—find it important that scaling back has no career consequences. Swedish men largely focus on the same considerations as their Dutch and British counterparts, but are overall more willing to reduce their hours than other men. It is not surprising that Swedes in particular stand out in this way. Sweden is a country that actively supports equality between the sexes and favors dual-earner families, and work–family policies in Sweden are focussed on increasing the working hours of women (Evertsson et al. 2009; Korpi, Ferrarini, and Englund 2013). It is also noteworthy that how “realistic” considerations are in a country context also seems to influence how important employees deem these considerations. Formal childcare is well regulated and heavily subsidized in Sweden, and neither Swedish men nor women seem to factor the costs thereof into account in their decision-making. In the Netherlands and especially the United Kingdom, however, childcare is expensive, and women in these countries do factor the costs of childcare into their decision-making to scale back. This fits with economic literature on female labor market participation, which shows that female labor market participation increases as a result of a decrease in (net) childcare costs (Akgunduz and Plantenga 2015). Lastly, a surprising finding is the negative effect of career consequences that was found for British women: when they expect scaling back to have no career consequences, they are less likely to indicate to want to scale back, contrary to the expected positive effect. While it should be interpreted with caution considering it is marginally significant and the size of the effect is small, a possible explanation is that these women are so grateful to their organization for not punishing a reduction of working hours with career consequences, that they want to reciprocate to the organization and end up working more hours (Grover and Crooker 1995). Limitations In our study, we have employed a vignette-experiment, as this method is particularly well-suited for exploring the relative importance of factors in complex decision-making situations (Alexander and Becker 1978; Wallander 2009). However, vignette-experiments also have some limitations. An often heard limitation is that it requires variables and levels to be pre-specified, which comes with the risk that important variables are omitted (Aguinis and Bradley 2014). However, the factors presented on a vignette are not random, but based on the literature, and while no new factors can be detected using a vignette-experiment, its strength lies elsewhere: in being able to analyze the isolated effect of these pre-specified factors, as well as exploring causality. For this reason, employing a vignette-experiment is only appropriate for topics where previous studies have provided a good indication which factors are important (Aguinis and Bradley 2014; Ganong and Coleman 2006). Even so, as our experiment is a simplification of reality we have intentionally—and very possibly unintentionally—excluded factors that people in real-life do take into account in similar decision-making situations, most notably informal childcare arrangements (which tend to be very common, especially in the United Kingdom; Verhoef et al. 2015). However, whereas this precludes us from drawing conclusions on the role these excluded factors play in people’s decision-making about reducing, thanks to our experimental design this does not affect our findings regarding the relative importance of the included considerations vis-à-vis each other. Another often heard limitation is that vignette-experiments have lower external validity due to their hypothetical nature (Aguinis and Bradley 2014; Wallander 2009). One way in which we have attempted to improve this is through our sample selection: we sampled employees of childbearing age, which corresponds with the population to whom we generalize our results, in order to ensure that it is easier for respondents to identify with the situation presented, and this thus secures more reliable answers (Aguinis and Bradley 2014). That being said, it should be kept in mind that with our vignette-experiment we measure people’s intended behavior rather than their actual behavior, which may not always coincide. This may, for example, lead to more socially desirable responses, or people holding unrealistically positive expectations of their own behavior. However, the risk of social desirability bias is often maintained to be smaller in vignette-experiments than in questionnaires, because the theoretically relevant factors are “hidden” in short stories (Alexander and Becker 1978; Wallander 2009). In addition, research suggests that people’s responses to vignette-experiments match their actual behavior remarkably well (Hainmueller, Hangartner, and Yamamoto 2015). Additionally, while vignette experiments have the advantage of permitting general conclusions about causal mechanisms using nonrandom samples, this hinges on the assumption that the causal mechanism is universal to the group to which it is to be generalized (Auspurg and Hinz 2015). For certain types of behavior, such as altruism and rational behavior, this is considered universal for humans, and thus homogeneous convenience samples are deemed sufficient (which is why student samples are often used in (vignette-)experiments). As we assumed that the mechanism we were trying to test would only apply to a certain sub-group—namely employed individuals of childbearing age—we only administered the experiment to this group. This is also the reason why we used separate samples of men and women; we worked from the assumption (based in theory) that the mechanism would function differently for men and women. However, the question remains whether the causal mechanism underlying decisions regarding employees’ working-hours following childbirth is universal over job type, or whether this is specific to certain types of jobs. Theoretically, we assumed this to be the same for different types of jobs, and controlling for job characteristics did not lead to different results. However, we cannot exclude the option that it does function differently for different types of jobs and sectors than were included in our study, and therefore it would be good for future research to conduct a vignette-experiment on a nationally representative sample of employees. Conclusion All in all, our study indicates that men and women have different reasons to reduce. Women are overall more likely to want to reduce their hours, but become less willing to do so if they have a partner who earns less than they do, or if their colleagues are unsupportive. Men, on the other hand, base their decision largely on their income relative to their partner’s (if their partner earns more, they are more likely to reduce, and if their partner earns less, they are less likely to reduce) and on whether they expect to suffer career consequences. Furthermore, we found that Swedish women, and to a lesser extent Swedish men, differ from their Dutch and British counterparts, as they expressed more inclination to exhibit counter-gender-normative behavior. Finally, we maintain that our findings suggest that the mere availability of the option to reduce one’s working hours following the birth of a child is not enough for people to actually do so. Before people can reduce their working hours they need to believe that they will not suffer collegial disapproval or career consequences. When the organizational culture is supportive of work–family needs, employees who want or need to use work–family policies do not need to refrain from this for fear of organizational consequences. Leonie van Breeschoten is currently doing her PhD at the Department of Sociology/ICS at Utrecht University, the Netherlands. She does research into questions regarding the combination of work and family life in European countries. Anne Roeters is a senior researcher at the Netherlands Institute for Social Research. She received her doctorate in Sociology from Utrecht University, the Netherlands. Her research interests include time use, the work/family interface, cross-national research, and gender differences. Tanja van der Lippe is Professor of Sociology at Utrecht University, and head of the Department of Sociology and Research Director, ICS Utrecht. Her research interests are in the area of work–family linkages in Dutch and other societies, for which she received a number of large scale grants from Dutch and European Science Foundations. She is an elected member of the European Academy of Sociology (2010), the Royal Netherlands Academy of Arts and Sciences (2014), and the Royal Holland Society of Sciences and Humanities (2013). She has published extensively on work and care of men and women in European countries. Appendix Table A1 Predictive probabilities of the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)  Table A1 Predictive probabilities of the desired reduction of working hours, for all respondents and by gender (SE)   Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)    Total (N: 2,464)  Men (n: 1,212)  Women (n: 1,252)  Gender         Men  0.538 (0.037)       Women  0.797 (0.27)      Vignette characteristics         Childcare costs          Close to hourly wage  0.636 (0.027)  0.569 (0.045)  0.674 (0.031)    Much lower than hourly wage  0.710 (0.025)  0.619 (0.043)  0.765 (0.029)   Career consequences          No career consequences  0.629 (0.027)  0.512 (0.046)  0.707 (0.030)    Likely consequences  0.717 (0.025)  0.676 (0.042)  0.732 (0.029)   Enjoyment          No change in enjoyment  0.648 (0.027)  0.544 (0.046)  0.710 (0.030)    Likely to lose enjoyable tasks  0.700 (0.026)  0.644 (0.044)  0.730 (0.030)   Collegial support          High collegial support  0.614 (0.028)  0.550 (0.046)  0.648 (0.033)    No collegial support  0.727 (0.025)  0.633 (0.043)  0.785 (0.028)   Partner earns          Less  0.481 (0.033)  0.389 (0.054)  0.549 (0.039)    About the same  0.706 (0.030)  0.595 (0.053)  0.767 (0.033)    More  0.828 (0.025)  0.806 (0.041)  0.826 (0.030)  Table A2 Predictive probabilities of the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)  Table A2 Predictive probabilities of the desired reduction of working hours, by gender and country (SE)   Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)    Men   Women     NL (n = 668)  SW (n = 276)  UK (n = 268)  NL (n = 708)  SW (n = 260)  UK (n = 284)  Vignette characteristics               Childcare costs                Close to hourly wage  0.563 (0.066)  0.748 (0.082)  0.417 (0.074)  0.655 (0.036)  0.727 (0.082)  0.650 (0.059)    Much lower than hourly wage  0.622 (0.064)  0.804 (0.072)  0.444 (0.075)  0.720 (0.035)  0.802 (0.072)  0.805 (0.048)   Career consequences                No career consequences  0.502 (0.069)  0.709 (0.090)  0.370 (0.074)  0.663 (0.035)  0.700 (0.087)  0.780 (0.050)    Likely consequences  0.683 (0.062)  0.843 (0.064)  0.498 (0.073)  0.713 (0.035)  0.828 (0.068)  0.681 (0.056)   Enjoyment                No change in enjoyment  0.531 (0.069)  0.699 (0.093)  0.438 (0.075)  0.690 (0.036)  0.701 (0.086)  0.719 (0.053)    Likely to lose enjoyable tasks  0.648 (0.064)  0.861 (0.062)  0.419 (0.075)  0.687 (0.036)  0.835 (0.067)  0.739 (0.052)   Collegial support                High collegial support  0.526 (0.068)  0.792 (0.076)  0.386 (0.076)  0.644 (0.037)  0.641 (0.097)  0.645 (0.063)    No collegial support  0.654 (0.063)  0.763 (0.079)  0.467 (0.074)  0.733 (0.036)  0.861 (0.060)  0.801 (0.049)   Partner earns                Less  0.395 (0.079)  0.679 (0.102)  0.165 (0.092)  0.534 (0.038)  0.692 (0.095)  0.531 (0.083)    About the same  0.596 (0.077)  0.750 (0.094)  0.469 (0.094)  0.706 (0.041)  0.804 (0.075)  0.817 (0.052)    More  0.789 (0.061)  0.913 (0.045)  0.674 (0.080)  0.807 (0.039)  0.798 (0.080)  0.787 (0.061)  Funding This work was supported by the European Research Council (340045). 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Social PoliticsOxford University Press

Published: Feb 2, 2018

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