J Bus Psychol DOI 10.1007/s10869-015-9415-8
ORIGINAL PAPER
An Examination of the Relationship Between the Work–School Interface, Job Satisfaction, and Job Performance Rebecca Wyland1 • Scott W. Lester1 • Kyle Ehrhardt2 • Rhetta Standifer1
Springer Science+Business Media New York 2015
Abstract Purpose This study provides a comprehensive examination of how the work–school interface relates to work outcomes such as task performance and job satisfaction. Additionally, this study builds upon past research by examining a range of work- and school-related resources and demands that collectively influence the work–school interface. Design/Methodology/Approach Data were obtained from 170 working undergraduate students at multiple time points over the course of a semester, as well as from participants’ supervisors at the organizations in which the students work. Findings The strongest antecedent of job satisfaction, interpersonal facilitation, and job performance was work– school facilitation. Demands in one role create pressures in the other. Contrary to expectations, job demands positively related to work–school facilitation, while school demands positively related to school–work facilitation. Implications For practitioners, this study highlights the need to better understand the interplay between school and
work roles for employees at a time when continuing education is emphasized. Employers benefit from the performance gains and positive attitudinal shifts that stem from experiences of facilitation between roles. From a theoretical perspective, this study reveals a unique pattern of results that adds to our understanding of the dynamics involved in the integrated work–school routines of working students. Originality/Value This is one of the first studies to investigate the relationships between four bi-directional forms of the work–school interface and subsequent multisource assessments of organizational outcomes. As such, it offers an examination of how conflict and facilitation from both the work and school domains relate to work outcomes. Keywords Work–school conflict School–work conflict Work–school facilitation School–work facilitation Job satisfaction Task performance
Introduction & Rebecca Wyland
[email protected] Scott W. Lester
[email protected] Kyle Ehrhardt
[email protected] Rhetta Standifer
[email protected] 1
Management and Marketing Department, University of Wisconsin-Eau Claire, 1005 Garfield Ave, Eau Claire, WI 54702-4004, USA
2
University of Colorado - Denver, The Business School, 1475 Lawrence St., Denver, CO 80202, USA
For most of us, the need to manage multiple life roles is the norm rather than the exception. We may simultaneously be an employee and spouse/partner in a committed relationship, for example, or perhaps hold a parent role in addition to our work-related roles. Researchers have shown that such involvement in multiple life roles can carry both negative and positive implications. We may experience inter-role conflict, for instance, when we encounter incompatible pressures stemming from two or more life domains (Greenhaus and Beutell 1985). However, participation in multiple life roles can also be beneficial, with experiences in one life domain advancing or improving our functioning in another (Crouter 1984; Sieber 1974). This
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positive perspective on the interdependency of multiple life roles is commonly described as facilitation (Butler 2007; Creed et al. 2015), which Greenhaus and Powell (2006, p. 73) define in general terms as ‘‘the extent to which experiences in one role improves the quality of life’’ in another. Together, these dual processes of inter-role conflict and facilitation have predominantly been studied within the work–family literature, with meta-analytic evidence that both may occur across these specific life domains (Shockley and Singla 2011). More recently, scholars have begun to apply these concepts to investigate a newer topic: the interplay of the work and school domains (e.g., Butler 2007; Creed et al. 2015; McNall and Michel 2011). These early investigations have contributed greatly to our knowledge of the working student. For example, researchers provided increased insight into the dispositional tendencies of working students who experience conflict and/or facilitation between roles (e.g., Hecht and McCarthy 2010; McNall and Michel 2011). In addition, research illustrates that experiences of work–school conflict (WSC) and facilitation may have implications for school-related performance (Butler 2007; Markel and Frone 1998), as well as individuals’ well-being (Creed et al. 2015; Park and Sprung 2015). Still, our understanding of the work–school interface remains limited on the whole, particularly with respect to how conflict and facilitation experienced between these roles may influence work-related outcomes. With this in mind, our objective in this study is twofold. First, we provide a comprehensive examination of how the work–school interface relates to key work outcomes, including employees’ job satisfaction and different facets of job performance. Specifically, we investigate how these work-related outcomes are shaped by a student’s experience among four key constructs: WSC, which occurs when the work role interferes with demands and responsibilities from the school role (Markel and Frone 1998), along with school–work conflict (SWC), which occurs when the school role interferes with demands and responsibilities from the work role. We also look at the influences of work– school facilitation (WSF), which occurs when the work role improves the quality of the school role, and school– work facilitation (SWF), which occurs when the school role improves the quality of the work role (Butler 2007; Greenhaus and Powell 2006). By doing so, our study offers an inclusive, bi-directional examination of how experiences of conflict and facilitation stemming from the work and school domains relate to key work outcomes. As a second objective, we endeavor to build on current research by examining a broad range of work- and school-related resources and demands that may contribute in shaping the work–school interface. To accomplish this, we integrate key demands/resources identified in existing research with
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additional resource constructs unique to the work and school domains in our model. In terms of contribution, our study holds important practical implications for organizations with employees’ currently pursuing degree programs. As higher education costs continually increase (U.S. Department of Education 2011), many students seek to fund such costs through paid employment. Indeed, research indicates that more than 75 % of older undergraduates work while enrolled in higher education institutions (Horn et al. 2002). This highlights a need to better understand the interplay between school and work roles, especially for organizations that contribute in some capacity toward employees’ schooling, given the potential impact on these organizations in terms of cost and performance. Even if not contributing financially, organizations may still be affected. Employee performance may decline due to attitudinal shifts or conflict experienced between the school and work roles; on the other hand, an employee’s attitude and/or performance may improve due to successful role facilitation. Our study also offers several advancements in scholars’ theoretical understanding of the work–school interface. Most notably, the current research is among the first to offer a bi-directional examination of how conflict and facilitation stemming from the work and school domains may simultaneously contribute in shaping work-related outcomes. This bi-directional approach follows scholars’ recognition that experiences of conflict and facilitation in one life domain may not only have cross-domain effects, but may also hold within-domain implications (Shockley and Singla 2011). In the current study, for example, this perspective acknowledges that work outcomes may not only be influenced by SWC and facilitation (the cross-domain effects), but also by WSC and facilitation (the withindomain effects). Most studies of the work–school interface capture only one direction for these effects. We further contribute to extant literature through our broad assessment of work-related outcomes and the inclusion of both work- and school-related antecedents. We consider relationships between each dimension of the work–school interface, employees’ job satisfaction, as well as multiple dimensions of employee job performance rated by their supervisor such as task performance and evaluations of interpersonal facilitation. This provides insight into the dimensions of the work–school interface which may be dominant in shaping these key work outcomes, and our evaluation of both work- and school-related demands and resources provides insight into key antecedents which influence individuals’ WSC, WSF, SWF, and SWC. In the following section, we first offer a general theoretical framework for the current study and present the study hypotheses. We then present our methodology and test our proposed model using a sample of 170 employed
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students. Finally, we close with a discussion of contributions to research and practice.
Theoretical Foundation and Hypotheses Conservation of resources (COR) Theory (Hobfoll 1989) provides the underpinnings for our proposed theoretical model. The foundation of COR Theory is that people are motivated to keep and acquire resources, which Hobfoll (2002, p. 307) defines as ‘‘entities that either are centrally valued in their own right or act as a means to obtain centrally valued ends.’’ More specifically, COR Theory articulates multiple theoretical tenets that have implications for the current study. First, a key premise of COR Theory is that a loss in resources motivates individuals to maintain current resources and/or invest other resources to recover from the loss (Hobfoll 1989, 1998, 2001). This principle recognizes that resource loss can be a particularly salient experience for individuals, as well as that resource investment on the part of individuals who has the capacity to counterbalance experiences of resource loss. Another COR Theory premise is that a gain in resources can serve as a catalyst for individuals to acquire additional resources, a prospect referred to as a resource ‘‘gain spiral’’ (Hakanen et al. 2008). By the same token, COR theory recognizes that experiences of resource loss may also increase the likelihood of future resources losses, a concept described as a resource ‘‘loss spiral’’ (Halbesleben et al. 2014). Collectively, this tenet of COR Theory stipulates that initial resource gains or losses often beget future resource gains or losses as well (c.f., Hobfoll 1989, 2001, 2002 for detailed discussions of gain and loss spirals). Here we incorporate these key principles of COR Theory, as well as draw upon previous work–family and work– school research, to suggest that demands and resources originating in the work role may influence WSC and WSF, which in turn contribute in shaping employees’ job satisfaction, task performance, and interpersonal facilitation. We further suggest that demands and resources originating in the school role may influence SWC and SWF, which in turn may also contribute in shaping these same work outcomes. Figure 1 offers a summary of our model.
received significant support within the work–family literature (Byron 2005). As such, we apply similar logic when examining antecedents of the work–school interface in the current study. First, we anticipate that job demands will positively relate to individuals’ reports of WSC. As job demands reflect ‘‘those physical, psychological, social, or organizational aspects of…(a) job that require sustained physical and/or psychological (cognitive and emotional) effort or skills’’ (Bakker and Demerouti 2007, p. 312), it follows that high levels of job demands may be associated with increased pressure for employees to devote more time and energy toward their work-related responsibilities. In order to meet such job demands, therefore, working students may feel obligated to miss classes, ignore school-related deadlines, or engage in fewer extracurricular activities, thereby increasing the conflict between the work and school roles (i.e., WSC). Existing research supports this notion. Butler (2007), for example, argued that job demands may drain available time resources working students could otherwise devote to school-related tasks and assignments. In addition, work–school researchers have demonstrated a positive relationship between job demands and WSC (Butler 2007; Markel and Frone 1998). The relationship between job demands and WSF, on the other hand, has not received the same degree of empirical attention within the work–school arena. Still, COR Theory provides theoretical support for a relationship between job demands and both WSC and WSF. As noted above, COR theory suggests that a loss in key resources often begets other resource losses, thereby resulting in a resource loss spiral (Hobfoll 2002). In this sense, along with leaving individuals more vulnerable to experiences of WSC, resources consumed in dealing with high levels of job demands may also limit individuals’ ability to experience the potential facilitative effects between work and school roles. As a result, a negative relationship between job demands and WSF is expected. We thus offer the following hypothesis for job demands: Hypothesis 1 Job demands will be (a) positively related to WSC and (b) negatively related to WSF. School Demands, SWC, and SWF
Job Demands, WSC, and WSF A dominant model in the work–family literature (Frone et al. 1992) suggests that relationships between antecedents, the work–family interface, and outcomes are specific to certain domains. In particular, Frone et al. (1992) predicted that work domain antecedents tend to influence work–family conflict, while family antecedents generally predict family–work conflict. This premise has
Similar arguments to those presented for job demands may also be applied for understanding the relationships between school demands, SWC, and SWF. Again, applying Frone’s et al. (1992) inter-role conflict model, demands originating in the school domain should promote SWC. Like wise, in a similar sense that job demands may be associated with increased pressure to devote time and energy toward workrelated responsibilities, high levels of school demands
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Job Demands
Job Resources: Job Control Work Interpersonal Support a
H1(a,b)
H3(a,b) -H4(a,b)
Work school Conflict
Work school Facilitation Self-rated: Job Satisfaction H8(a,b,c) -H11(a,b,c)
School Demands
School Resources: School Control School Interpersonal Support b School Relevance
H2(a,b)
H5(a,b) -H7
Supervisor -rated: Task Performance Interpersonal Facilitation
School work Conflict Time 3: Outcomes
School work Facilitation Time 2: Conflict and Facilitation
Time 1: Demands/Resources
Fig. 1 Proposed research model with hypotheses. aCross-domain interpersonal interest/support received at work. bCross-domain interpersonal interest/support received at school
require working students to devote significant energies toward their school-related responsibilities. In other words, when working students perceive excessive school demands, they may use time and effort which should be devoted to the work domain in order to meet these school demands, thereby increasing levels of SWC. School demands could also impede on working students’ ability to focus on the learning process in school. Working students, for instance, might be focused only on completing tasks at the expense of learning and reflection, which could decrease levels of facilitation experienced between the school and work roles. COR Theory perspectives on loss spirals also provide support for a relationship between school demands and SWC, as well as between school demands and SWF, following similar arguments to those presented above. We thus hypothesize: Hypothesis 2 School demands will be (a) positively related to SWC and (b) negatively related to SWF. Job Resources, WSF, and WSC Aligned with COR Theory perspectives, resource expansion theories (e.g., Greenhaus and Powell 2006; Grzywacz
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2002; Marks 1977; Sieber 1974) stipulate that experiences and resources acquired in one domain can be used to benefit another. Drawing on this premise and previous work–family literature (e.g., Butler et al. 2005; Grzywacz and Butler 2005; Grzywacz and Marks 2000; Vodydanoff 2004), Butler (2007) predicted for the work–school arena that job control would have a positive relationship with WSF. His argument held that working students who have the ability to decide how to complete their work (thus having high levels of job control) will increase their psychological resources and experience more facilitation between the work and school roles. Along with increasing WSF, job control is also expected to reduce WSC. Butler (2007), for example, found support for a relationship between job control and WSC, drawing again on work–family scholarship (Ashforth et al. 2000; Greenhaus and Powell 2006) and theorizing that greater control would allow working students to decide how and what work tasks to complete. Work–family studies have also generally supported a relationship between job control and lower levels of conflict between work and family roles (e.g., Butler et al. 2005). Beyond job control, we expect that WSF will increase when individuals from the work domain (e.g., coworkers
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and supervisors) take an interest in working students’ school program. We use the term ‘‘cross-domain interpersonal interest/support’’ to capture this idea, and suggest that this construct constitutes an important interpersonal resource. More specifically, it reflects an interpersonal resource that is received from individuals present in one domain, but the content of which pertains to a separate domain—for example, interpersonal support received from key work constituents such as a supervisor, but the content of which is relevant to one’s school. Such interest from others may encourage working students to reflect on how their newly acquired knowledge learned in school may be applicable to the workplace, thus improving facilitation between the work and school domains. COR Theory supports this perspective, recognizing that resources such as cross-domain interpersonal interest/support received in the work domain could be used to acquire additional resources in other domains (Hobfoll 1989), thus promoting WSF. We also expect that cross-domain interpersonal interest/support received at work may reduce WSC. Although Butler (2007) did not hypothesize this specific relationship, he offered that ‘‘students in jobs allowing for greater control may be able to organize work to discuss school with other employees, select routine tasks that allow thinking about school, or postpone tasks to accomplish some schoolwork’’ (Butler, 2007, p. 503). These perspectives provide support for our contention that working students will experience less WSC when coworkers and supervisors take an interest in their school program. More specifically, this interpersonal interest/support is expected to improve working students’ mood and allow them to reflect on and discuss their school interests. During these discussions, working students may be reminded of information from the school domain that could help reduce inter-role conflict. COR Theory again offers support for these arguments. When faced with demanding situations, individuals may draw on key resources such as interpersonal support to mitigate the potential threat or loss of resources stemming from such demands (Hobfoll 1989), thereby reducing WSC. Collectively, therefore, this theory and research yields the following hypotheses: Hypothesis 3 Job control will be (a) positively related to WSF and (b) negatively related to WSC. Hypothesis 4 Cross-domain interpersonal interest/support received at work will be (a) positively related to WSF and (b) negatively related to WSC. School Resources, SWF, and SWC Similar arguments to those presented in the preceding section for job resources hold for school resources as well. For example, when working students have more decision-
making abilities in their school role (thus greater school control), they may accordingly be afforded the opportunity to choose classes and activities that are more relevant to their own interests and experiences. Working students may use this control to make decisions that will benefit other aspects of their life, including their work role, thereby promoting levels of SWF. Moreover, just as job resources are expected to reduce WSC, school resources may also be expected to reduce SWC. Drawing on COR Theory, the presence of key resources such as school control should allow individuals to manage school-related responsibilities in such a way that their completion does not encroach on individuals’ work role (c.f., Hobfoll 2002). Working students with greater school control may also select classes and activities that can help them reduce the demanding situations they are experiencing, thereby reducing the threat of SWC. Classmates and professors may also be able to provide cross-domain interpersonal interest/support similar to that offered in the work domain by coworkers and supervisors. When classmates and professors take an interest in their work roles, working students may perceive increased support which can improve SWF. Similarly, when classmates and professors show an interest in a student’s job, he/she can discuss workplace experiences and seek advice for ways to improve upon demanding situations, thereby decreasing SWC. Finally, we expect that experiences of SWF may be greater when assignments, topics, and theoretical perspectives individuals learn within the school domain are perceived as relevant to their workplace. We term this idea ‘‘school relevance,’’ and COR Theory offers support for a link between school relevance and SWF. Specifically, drawing on COR Theory perspectives on resource gain spirals (Hobfoll 1989, 2002), work-relevant course topics and theories covered in school would be expected to increase individuals’ intellectual capital, as well as allow for immediate opportunities for individuals’ to apply their knowledge in the workplace, thereby precipitating increased chances to acquire new resources at work and promote SWF. Although the relationship between school relevance and SWF has not been studied directly within the work–school arena, indirect support for this relationship can be inferred from Butler (2007), who demonstrated a relationship between job–school congruence and WSF. Related to school relevance, job–school congruence focuses on the overall congruence between the skills and knowledge individuals’ use in their job and school roles. Collectively, this theory and research yields the following hypotheses: Hypothesis 5 School control will be (a) positively related to SWF and (b) negatively related to SWC.
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Hypothesis 6 Cross-domain interpersonal interest/support received at school will be (a) positively related to SWF and (b) negatively related to SWC. Hypothesis 7 to SWF.
School relevance will be positively related
WSC, SWC, Job Satisfaction, and Job Performance Inter-role conflict theorists suggest that incompatible roles will negatively impact one another because demands in one role will deplete resources available in the other (Greenhaus and Beutell 1985; Kahn et al. 1964). Such conflict can hold negative consequences for a variety of outcomes, including reduced job satisfaction and less willingness to engage in performance-related workplace behaviors. To this end, reviews in the work–family literature have established a negative relationship between work–family conflict and job satisfaction (Allen et al. 2000; Kossek and Ozeki 1998; Shockley and Singla 2011). Work–family scholars have also demonstrated a link between inter-role conflict and performance (Carlson et al. 2008). In comparison to the work–family literature, work– school research is more limited in considering the relationship between WSC and work-related outcomes. However, in one of the few empirical tests to date, McNall and Michel (2011) hypothesized a significant negative relationship between WSC and both job satisfaction and job performance. Although the authors noted a significant negative correlation between WSC and job satisfaction, they did not support the hypothesized relationship between WSC and either outcome. Nevertheless, their study was limited by its cross-sectional design, the exclusion of bidirectional forms of conflict and facilitation, and the use of a self-report measure of job performance, leading the authors to call for future research that addresses these limitations. In the current study, we heed McNall and Michel’s (2011) recommendations by capturing supervisorreported measures of performance, as well as by evaluating employee job satisfaction at a separate measurement point than WSC. We additionally extend current research by examining the relationship between WSC and two dimensions of job performance—task performance and interpersonal facilitation. How WSC may relate to both of these performance dimensions is important as each has a distinct focus and may carry different consequences for organizations. For example, task performance specifically concerns employees’ jobs and their general abilities for carrying out assigned tasks. In contrast, interpersonal facilitation focuses on the quality of individuals’ interpersonal behaviors (Van Scotter and Motowidlo 1996).To this end, low levels of interpersonal facilitation has been described as having
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potentially lingering organizational consequences given the potential damage to employee relationships and morale (Wyland et al. 2013). Drawing on inter-role conflict perspectives and research described above, we posit for the current study that WSC will negatively relate to job satisfaction, as well as both facets of job performance (i.e., task performance and interpersonal facilitation). For example, due to simultaneous work and school deadlines, an employee may let a school project deadline slip in order to finish a project at work (i.e., WSC). Yet, the quality of the work project may also suffer because the employee may develop anxiety over missing this school deadline. If the quality of the work project suffers, it may also impact relationships with coworkers on the project. As the situation continues to unfold, interpersonal facilitation may be hindered because the employee has less time to devote toward relationship development. Further, a supervisor may perceive that the quality of work is decreasing because the employee is having a hard time balancing both school and work. It is likely that a supervisor who sees these types of behaviors would ultimately perceive lower levels of task performance and interpersonal facilitation in rating the employee. Preliminary empirical support has also been reported for a negative relationship between SWC and job performance (Wyland et al. 2013). We expect to see similar negative implications for SWC here. As SWC increases, working students may have less concern for their work role, which may ultimately lead to lower levels of job satisfaction and job performance. For example, when working students spend time at work worrying about school project deadlines and demands, they may have a difficult time focusing on their work tasks, thus having implications for their task performance at work. This concern for the school role may further lead working students to take time off of work in order to meet school demands, thereby decreasing opportunities for interpersonal facilitation. Taken together, therefore, we offer the following: Hypothesis 8 WSC will be negatively related to (a) job satisfaction, (b) task performance, and (c) interpersonal facilitation. Hypothesis 9 SWC will be negatively related to (a) job satisfaction, (b) task performance, and (c) interpersonal facilitation. WSF, SWF, Job Satisfaction, and Job Performance Employees experiencing facilitation between their work and school roles are likely having experiences in their work roles that help to improve their school role. For example, working students may be able to reflect on work experiences during class, helping them to both understand and
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retain information because they are able to draw on personal experiences. Through this process of WSF, employed students may become more satisfied with their job because they are able to acquire work experiences which are helpful in other domains. This facilitation may also motivate the working student to perform better at their job. It also may motivate them to generate more work experience samples, thus making them more interested in their job tasks and more willing to build interpersonal relationships by helping coworkers. It is reasonable to assume this also holds for working students who are experiencing facilitation from their school role to their work role. For example, working students may be able to directly apply their newly acquired knowledge and skills from their school role to their work role. This process of SWF may help the working student understand their job better, ultimately improving job satisfaction. Working students may also be able to acquire skills in school (e.g., technical skills and interpersonal skills) that can facilitate making their job more efficient and effective, thereby increasing task performance and interpersonal facilitation. Theoretical support for these contentions is again provided by COR Theory. As noted, one premise of COR Theory postulates that employees are able to reinvest resources and use them as a catalyst to gain more resources (Hobfoll 1989). In the above scenarios, the facilitation process allows employees to acquire resources, which could help motivate working students to work harder so that even more resources (e.g., a bonus) might be acquired from higher levels of performance. Altogether, this theorizing leads to the following hypotheses: Hypothesis 10 WSF will be positively related to (a) job satisfaction, (b) task performance, and (c) interpersonal facilitation. Hypothesis 11 SWF will be positively related to (a) job satisfaction, (b) task performance, and (c) interpersonal facilitation.
Method Data Collection and Sample This study was part of a large work–school balance project that took place at a mid-size Midwestern university. Employed students in upper-level business classes were invited to participate, with the incentive that all participants would receive a small amount of extra credit (1 % of their course grade) for completing three paper-and-pencil surveys over the course of a semester. Surveys were given during class time and were distributed approximately four
weeks apart. This time lag allowed for all data collection to occur within a single semester, as well as provided a sufficient amount of time for the examination of the spillover of individuals’ experiences of demands and resources across multiple life roles. Previous work–family scholars (e.g., Matthews et al. 2010, 2014) used the same four week time lag. Participants were also informed that they would receive a small amount of additional extra credit (additional 1 % of their course grade) for providing a supervisor’s email address and obtaining their consent to provide work-related performance data for the student. Collectively, therefore, this study combined self-report data collected at three time points with matched work performance data collected from individuals’ supervisors. Time 1 measures were captured from participants during the 3rd week of the semester, while Time 2 measures were collected during the week 6 or 7 of the semester (slight variation between specific classes). Job satisfaction, the only participant-rated Time 3 measure, was captured during the 11th week of the semester. Supervisors were then contacted to provide performance data. In an effort to be sensitive to workload demands and variance in availability, supervisors were allowed to submit data anytime between the week 11 and 14 of the semester. In total, 435 students were approached to participate in this study. Of these, 119 did not participate, either because they were not currently employed (61 individuals), or by choice (58 individuals). Three-hundred sixteen working students thus completed the initial survey. However, due to attrition, only 170 individuals completed all three self-report surveys and had a supervisor provide work-related performance data. As such, the overall study response rate was 45 %, which is based on the number of eligible participants (i.e., 435 overall students—61 unemployed students = 374 eligible participants). We furthermore verified that study participants did not change jobs during the course of the semester. In terms of sample characteristics, slightly more than half (51 %) of the sample was male. Ages of participants ranged from 19 to 29 with an average age of approximately 21 years. Most (90 %) of the working students indicated that they were single, and on average, participants were enrolled in five courses during the semester in which the study was administered. Measures Time 1 measures comprised work- and school-related demands and resources—specifically: job demands and school demands, job control and school control, cross-domain interpersonal interest/support received at both work and school, as well as school relevance. All control variables were also measured at Time 1. Time 2 measures
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featured those constructs which collectively captured bidirectional effects (i.e., work–school and school–work) for conflict and facilitation—more specifically, WSC, SWC, WSF, and SWF. Finally, Time 3 self-report and supervisorreported measures focused on study outcomes, including job satisfaction, task performance, and interpersonal facilitation. More detail for each measure is provided below. Job Demands and School Demands We measured job demands (a = .82) using the 6-item scale that Butler (2007) offered. The items originated from Karasek’s (1979) Job Demands Scale. Similarly, to measure school demands (a = .77), we modified this 6-item scale to reflect individuals’ experiences at school as opposed to work. For example, a sample job demands scale item was ‘‘To what extent does your job require a great deal of work to be done,’’ and the corresponding school demands scale item was ‘‘To what extent does your school require a great deal of work to be done.’’ Response options ranged from 1 = Never/Very rarely to 5 = Always/Very often. Job Control and School Control Job control (a = .60) was measured using the 3-item scale that Butler (2007) offered. The items originated from Karasek’s (1979) Decision Authority Scale. Again, we modified this 3-item measure to capture school control (a = .74). For instance, a sample job control scale item was ‘‘To what extent do you have freedom to decide how to organize your work,’’ and the corresponding school control scale item was ‘‘To what extent do you have freedom to decide how to organize your schoolwork activities.’’ Response options ranged from 1 = Never/Very rarely to 5 = Always/Very often. Cross-Domain Interpersonal Interest/Support As described above, cross-domain interpersonal interest/support constitutes an interpersonal resource received from key constituents in one domain that pertains to a separate domain (e.g., interpersonal support received from a professor, but the content of which is relevant to one’s work). Aligned with this definition, we first measured cross-domain interpersonal interest/support received at work (a = .70) using two items developed for this study which directly assess the degree to which participants’ supervisors and coworkers take an interest in their school work. One item pertained to supervisors’ interest (‘‘Your supervisor takes an interest in your school work’’), while the second item pertained to coworkers’ interest (‘‘Your coworkers take an interest in your school work’’).
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Response options ranged from 1 = Strongly disagree to 5 = Strongly agree. In a similar vein, we measured cross-domain interpersonal interest/support received at school (a = .77) using six items which reflect the degree to which participants’ professors and classmates take an interest in individuals’ work life or work activities. These items were derived from Caplan et al. (1975) more general measure of social support. Specifically, three items pertained to professors’ level of interest/support (e.g., ‘‘How much does your professor go out of his/her way to do things to make your work life easier’’), while the other three items pertained to classmates’ level of interest/support (e.g., ‘‘How much do your classmates go out of their way to do things to make your work life easier’’). Response options ranged from 1 = Not at all to 5 = Very much. School Relevance We captured school relevance based on individuals’ evaluation of the statement ‘‘Your professor(s) assign work and theories that you can apply to your job.’’ Response options ranged from 1 = Strongly disagree to 5 = Strongly agree. Work–School Conflict (WSC) WSC (a = .84) was measured using a modified version of a 4-item scale that was originally developed by Grzywacz and Marks (2000). Scale items used in the current study were modified to reflect the degree to which work negatively impacts school. A sample item was ‘‘Job worries or problems distract you when you are at school.’’ Response options ranged from 1 = Never to 5 = All the time. Work–School Facilitation (WSF) WSF (a = .77) was measured with a 5-item scale that Butler (2007) developed. Butler (2007) modified an existing work–family facilitation measure offered by Grzywacz and Marks (2000). The items reflect the degree to which work positively influences school. A sample item was ‘‘Having a good day at work makes you a better student.’’ Response options ranged from 1 = Never to 5 = All the time. School–Work Conflict (SWC) We measured SWC (a = .80) with the same 4-item scale that was used to measure WSC. Here, however, Grzywacz and Marks (2000) scale was modified to reflect the degree to which school negatively impacts work. A sample item was ‘‘School worries and problems distract you when you
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are at work.’’ Response options ranged from 1 = Never to 5 = All the time.
influence on variables.
all
within-domain
latent
endogenous
School–Work Facilitation (SWF)
Results We measured SWF (a = .77) with the same 5-item scale that was used for WSF. Here, however, Butler’s (2007) measure was modified to reflect the degree to which school positively influences work. A sample item was ‘‘Having a good day at school makes you a better worker.’’ Response options ranged from 1 = Never to 5 = All the time.
Descriptive Statistics Table 1 presents descriptive statistics and bivariate correlations for all study variables. Measurement Model
Job Satisfaction Job satisfaction (a = .93) was assessed using 3 items from Hackman and Oldham’s (1975) job diagnostic survey. Previous scholars used this 3-item measure to assess the degree to which participants were satisfied with their job (Shaffer et al. 2000).Response options ranged from 1 = Strongly disagree to 5 = Strongly agree. A sample item was ‘‘Generally speaking, I’m very satisfied with this job.’’ Task Performance Supervisor-rated task performance (a = .90) was measured using a7-item measure that asked supervisors to select the number on a five-point scale that corresponded to the employee’s task performance (Williams & Anderson, 1991). Response options ranged from 1 = Strongly disagree to 5 = Strongly agree. Interpersonal Facilitation Finally, supervisor-rated interpersonal facilitation (a = .91) was measured using a 7-item scale originally developed by Motowidlo and Van Scotter (1994). Supervisors were asked to evaluate how likely the employee was to display desired interpersonal-related behaviors, for example, ‘‘praise coworkers when they are successful.’’ Response options ranged from 1 = Very unlikely to 5 = Very likely. Control Variables We controlled for three additional variables—two workrelated constructs: individuals’ average number of hours worked per week (1 = 1–10 h to 5 = 41 or more hours) and individuals’ tenure in their current position (0 = less than 1 year, 1 = 1 year or more); along with one schoolrelated construct: the number of classes in which participants’ were currently enrolled (1 = 1–6 = 6 or more). Each control variable was treated as having an exogenous
Prior to testing the study hypotheses, we first performed a confirmatory factor analysis (CFA) that included each of the thirteen latent study constructs to ensure the appropriateness of our measurement model. To conduct this CFA, we used an item parceling strategy given both the size of the model and the study’s sample size. Item parceling is a procedure in which composite indicators are created to capture a set of measured items for one or more latent variables. It is a procedure recommended for large models as item parceling reduces the number of parameters to be estimated, thereby allowing for more stable fit estimates, less biased parameter estimates, and more favorable sample size to parameter ratios (Alhija and Wisenbaker 2006; Bagozzi and Edwards 1998; Bandalos 2002; Yuan et al. 1997). Item parceling is, moreover, a suggested practice for study contexts in which some latent variables have a large number of measured items (Bandalos and Finney 2001; Little et al. 2002), as was the case here. Following scholars’ recommendations (e.g., Holt 2004; Nasser and Takahashi 2003), parcels were created for latent constructs with four or more measured indicators via random assignment of individual items. Model fit was evaluated by a collective evaluation of the CFI, RMSEA, and SRMR fit indices, following standards outlined by Kline (2005). CFA results of the specified thirteen-factor measurement model yielded good fit overall: v2299 = 375.81, p \ .01; CFI = .97, RMSEA = .04, SRMR = .05. In addition, all items/parcels loaded significantly on their identified latent factor with a mean standardized factor loading of .79, thereby supporting convergent validity. To further confirm the appropriateness of the measurement model, we next compared the fit of the expected thirteen-factor model to a variety of alternative models in which one or more of the factor covariances were constrained to one. Alternative models included the following: 1. All combinations of fixing the covariances between corresponding job and school constructs to one; 2. All combinations of fixing the covariances between respective groups of job and school resources to one; 3. All combinations of fixing the covariance between WSC, SWC, WSF, and/or SWF to one; and finally, 4. All
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123 3.18 3.37 3.66
4. Job demands (T1)
5. School demands (T1)
6. Job control (T1)
3.12 3.77 4.41 4.12
14. School–work facilitation (T2)
15. Job satisfaction (T3)
16. Task performance (supervisor-rated)
17. Interpersonal facilitation (supervisor-rated)
0.71
0.54
0.96
0.73
0.85
0.80
0.97
1.07
0.79
0.85
0.97
0.78
0.65
0.76
0.77
0.97 0.49
SD
.06
.04
.04
-.03
.09
.06
.27
.18
-.20
-.03
-.05
-.04
.21
.26
-.17
– .07
1
.00
.14
.10
-.05
-.06
-.05
-.01
.09
-.11
-.08
-.01
.17
-.08
-.07
-.06
–
2
.01
.01
-.07
.03
.11
-.02
.01
.01
-.01
-.01
.05
-.01
.02
-.12
–
3
.88 .66
-.01
.06
-.01
.09
.35
.22
.50
.08
.00
-.07
.07
-.07
4
.84
.04
.02
-.13
.07
.39
.07
.43
-.06
-.08
-.05
-.05
-.16
5
.20
.07
.28
.25
.60
.10
.23
.23
.03
-.16
.30
-.14
6
.77
.14
.30
.35
.16
-.06
.44
-.13
.28
.18
-.03
7
.71 .06
.09
.00
-.05
-.02
.12
-.21
.03
-.13
8
.17
.76
.04
.07
-.06
.28
-.08
.20
-.04
9
–
.03
.15
.24
.34
.07
.43
.11
10
-.08
.02
-.05
.21
.61
.23
.88
11
.19
.27
.37
.54
.22
.75
12
-.12
-.10
-.05
.29
.77
13
.07
.12
.09
.81
14
.18
.26
.90
15
.28
.89
16
.88
17
b
a
Cross-domain interpersonal interest/support received at school
Cross-domain interpersonal interest/support received at work
N = 170. Correlations greater than .14 in absolute value are significant at p \ .05. Correlations greater than .19 in absolute value are significant at p \ .01. Boldfaced, italicized entries on the diagonal are the square root of the average variance explained. To demonstrate discriminant validity, values must be greater than correlations with latent constructs in the same row and column (Andrews et al. 2009)
3.17
2.95
11. work–school conflict (T2) 3.31
2.95
10. School relevance (T1)
12. work–school facilitation (T2)
2.49
9. School interpersonal support (T1)b
13. School–work conflict (T2)
3.51
8. School control (T1)
3.10
5.22
3. Number of classes (T1)
7. Work interpersonal support (T1)
2.40 0.60
1. Work hours per week (T1) 2. Position tenure (T1)
a
M
Variable
Table 1 Means, standard deviations, and bivariate correlations of study variables
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combinations of fixing all constructs measured at a specific time point to one. For each comparison, the original thirteenfactor model demonstrated superior fit: v2diff(1–15) = 25.46–363.37, p \ .01 for each test. As a supplemental test of discriminant validity, we also calculated the square root of the average variance explained (AVE) for each latent construct (Fornell and Larcker 1981). These values are displayed on the diagonal in Table 1. According to Andrews et al. (2009, p. 1431), to demonstrate discriminant validity, the square root of the AVE should ‘‘exceed the corresponding latent variable correlations in the same row and column of the correlation matrix.’’ As shown, this condition was satisfied for each of the thirteen latent study variables. SEM Analysis and Hypothesis Tests We used structural equation modeling (SEM) with maximum likelihood estimation to test the study hypotheses. Consistent with the CFA described above, we also employed an item parceling strategy for the SEM analysis given both the size of the model and the study’s sample size. Following convention, all covariances between exogenous variables were freely estimated in the SEM analysis and no residual covariances (between measured items or disturbance terms) were permitted. Two-tailed significance tests were used to evaluate all hypotheses. SEM results for the proposed study model demonstrated reasonable fit on the whole: v2417 = 629.93, p \ .01; CFI = .91, RMSEA = .05, SRMR = .07. Figure 2 provides a summary of the significant structural model paths, along with standardized coefficients for these relationships. Relationships Between Demands, Resources, and the Work–School Interface Supporting Hypothesis 1(a) and 2(a), job demands and school demands were each positively related to reports of conflict originating within-domain. More specifically, job demands were positively related to WSC (c = .61, p \ .01), while school demands were positively related to SWC (c = .53, p \ .01). Hypotheses 1(b) and 2(b), however, were not supported. While both Hypotheses 1(b) and 2(b) stipulated that demands would be negatively related to reports of facilitation originating within-domain, the opposite result, in fact, emerged. That is, job demands were positively related to WSF (c = .31, p \ .01) and school demands were positively related to SWF (c = .18, p \ .05). These interesting yet unanticipated findings are revisited later. We also found mixed support for the relationship between job resources, WSF, and WSC. First, supporting Hypothesis 3(a), job control was positively related to WSF (c = .40, p \ .01). Likewise, cross-domain interpersonal
interest/support received at work was positively related to WSF (c = .44, p \ .01), supporting Hypothesis 4(a). Of these two job resources, however, only cross-domain interpersonal interest/support received at work was found to be negatively related to WSC (c = -.19, p \ .05). While this finding supports Hypothesis 4(b), no support was found for Hypothesis 3(b), which stipulated that job control would be negatively related to WSC. Mixed support again emerged for the relationship between school resources, SWF, and SWC. Hypothesis 5(a), which proposed that school control would be positively related to SWF, was not supported. However, school control was negatively related to SWC (c = -.19, p \ .05), supporting Hypothesis 5(b). In contrast, both cross-domain interpersonal interest/support received at school (c = .33, p \ .01) and school relevance (c = .32, p \ .01) were positively related to SWF, offering support for Hypothesis 6(a) and Hypothesis 7, respectively. Finally, Hypothesis 6(b), which suggested that cross-domain interpersonal interest/support received at school would be negatively related to SWC, was not supported. Relationships Between the Work–School Interface, Job Satisfaction, and Performance Outcomes Recall that Hypotheses 8-11 considered the relationships between WSC, SWC, WSF, SWF, self-reported job satisfaction, and two supervisor-rated performance outcomes: task performance and interpersonal facilitation. Across these hypotheses, only Hypotheses 9 and 10 received some measure of support. Specifically, although Hypotheses 9(a) and 9(c) were not supported as there was no relationship between SWC and either job satisfaction or interpersonal facilitation, Hypothesis 9(b), which called for a negative relationship between SWC and task performance, was supported (b = -.24, p \ .05). Hypotheses 10(a), 10(b), and 10(c), on the other hand, were each supported as positive path coefficients characterized the relationships between WSF and job satisfaction (b = .60, p \ .01), WSF and task performance (b = .45, p \ .01), and WSF and interpersonal facilitation (b = .27, p \ .01). Hypothesis 10 was thus fully supported.1
1
We conducted two robustness tests for the model results reported. First, aligned with recommendations concerning the use of control variables (Spector and Brannick 2011), we retested our hypotheses in a separate model which excluded the three control variables (work hours per week, position tenure, and number of classes). Second, we re-analyzed the model using all available data with full information maximum likelihood as the estimation method. For both of these alternative models, model fit indices were largely equivalent, standardized path coefficients underwent only minor changes in magnitude, and there were no differences in the significance of individual model paths.
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Job Demands
Work school Conflict Job Demands: γ = .61 ** Work Interpersonal Support: γ = -.19 *
Job Resources: Job Control Work Interpersonal Support a
Work school Facilitation Job Demands: γ = .31 ** Job Control: γ =.40 ** Work Interpersonal Support: γ = .44 **
School Demands
School wo rk Conflict School Demands: γ = .53 ** School Control: γ = -.19 *
Work-school Facilitation Job Satisfaction: β = .60 ** Self-rated: Job Satisfaction Supervisor-rated: Task Perfo rmance Interpersonal Facilitation
Work-school Facilitation Task Performance: β = .45 ** Interpersonal Facilitation: β = .27 ** School-work Conflict Task Performance: β = -.24 *
School Resources: School Control School Interpersonal Support b School Relevance
School wo rk Facilitation School Demands: γ = .18 * School Interpersonal Support: γ = .33 ** School Relevance: γ = .32 **
Fig. 2 Summary of structural equation model results. Standardized path coefficients are reported for significant model paths. Nonsignificant model paths, item parcel loadings, item parcel errors, exogenous covariances, disturbance terms, and control variable paths
are omitted for brevity. aCross-domain interpersonal interest/support received at work. bCross-domain interpersonal interest/support received at school. Note N = 170. v2 (417) = 629.93, p \ .01; CFI = .91, RMSEA = .05, SRMR = .07. *p \ .05. **p \ .01
Post hoc Relative Weights Analyses
any other predictor, each of which failed to explain significant levels of variance. Second, with respect to task performance, WSF again emerged as the most influential predictor, accounting for about 54 % of the overall variance explained, which was about three times the amount accounted for by any other predictor. Still, both SWC (17 %) and position tenure (16 %) were also shown to explain non-trivial levels of variance. Finally, variance explained in interpersonal facilitation was again primarily attributable to WSF, which accounted for 50 % of the overall variance explained and was the only non-trivial predictor. Analyses were conducted using RWA-Web (Tonidandel and LeBreton 2015), with significance tests based on bootstrapping with 10,000 replications in order to construct confidence intervals (Tonidandel et al. 2009).
As noted earlier, a key objective of the current study was to offer a comprehensive assessment of the work–school interface by simultaneously examining relationships among bi-directional spillover effects and work outcomes. Given this, we supplemented our primary findings by conducting relative weights analyses among the four constructs capturing the work–school interface (WSC, WSF, SWC, and SWF) for job satisfaction, task performance, and interpersonal facilitation. Relative weights analysis is a statistical method which partitions the contribution to explained variance between predictors in a regression equation in order to better understand the unique influence of each predictor (Johnson 2000; Tonidandel and LeBreton 2011). This objective is aligned with our theoretical question as to which of the bi-directional work–school conflict and facilitation constructs serve as key drivers of work-related outcomes. Results first indicated that variance explained in job satisfaction was attributable primarily to WSF, which accounted for more than 80 % of the overall variance explained. This value was about eleven times greater than
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Discussion This study contributes to the work–school literature by using multi-source data to examine relationships between resources, demands, the work–school interface, and important organizational outcomes. Study results revealed
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an interesting combination of findings—some of which supported hypothesized relationships. However, a few of the significant paths in our SEM analyses indicated relationships that were in the opposite direction of what was anticipated. Collectively, these results increase our understanding of the dynamics that occur within the work– school interface and suggest a number of avenues for future research. Discussion of Study Findings Demands, Resources, and the Work–School Interface Our results offer support to the notion that demands in one role (work or school) may create pressures in another role, which positively relates to inter-role conflict (WSC and SWC). Interestingly, and contrary to expectations, our findings also demonstrated that job demands positively related to WSF, while school demands positively related to SWF. Previous scholars have noted the potential benefits of dual-role participation in terms of resource sharing across roles (Butler 2007; Greenhaus and Powell 2006). However, it is surprising to see these significant positive relationships between job/school demands and the bi-directional forms of inter-role facilitation (WSF and SWF). In addition, although Butler (2007) did not hypothesize a direct relationship between job demands and WSF, it is important to note that he too reported a positive bivariate relationship between these constructs, adding credence that our findings here were not simply a random occurrence. One possible explanation for these findings may lie in the generational qualities of the sample. Similar to Butler (2007), our study investigated the work–school interface for undergraduate students. Participants were predominately members of Generation Y (also known as Millennials), who are often described as multi-taskers and technology driven (c.f., Sessa et al. 2007). It is conceivable that increased demands in one arena signal to millennial employees that multi-tasking will be required, leading to a heightened focus on the myriad of tasks at hand and improving inter-role facilitation. A second plausible explanation for the relationships between job/school demands and the bi-directional forms of inter-role facilitation pertains to the perceived nature of specific demands. Scholars suggest that demands may be appraised in different ways, with some demands perceived as hindrances and some perceived as challenges. This distinction has further been shown to have implications for the relationship between demands and outcomes, with hindrance demands more likely to promote negative outcomes and challenge demands more likely to lead to positive outcomes (Cavanaugh et al. 2000; LePine et al. 2005). Unfortunately, the measure of demands used in the current
study did not allow for a distinction between challenge and hindrance demands to be made. It is possible, though, that the positive relationships between demands and facilitation were due to students’ perceptions of the demands they faced primarily as challenges. If so, these challenge demands may have provided an opportunity for working students to build resources such as increased knowledge, skills, and abilities which could be transferred across roles, thus promoting facilitation. Increased insight into the relationship between job/ school demands and facilitation may also be gleaned from considering the influence of various moderator variables. More specifically, examining potential moderators could offer a more fine-grained lens on the conditions under which the relationship may be positive or negative. One such possibility is the degree of overlap between one’s career aspirations or plan of study and his/her current job. In this case, greater alignment between the work and school roles may suggest that demands experienced in one role have a greater potential long-term benefit, and thus may be more likely to promote facilitation. It is also conceivable that certain trait characteristics may lead some individuals to focus on the potential positive consequences of facing demanding situations in their school or work roles (e.g., opportunity to learn, build new skills), thereby making these individuals more likely to experience facilitation as a result. It is important to note that each of the above explanations reflects post hoc reasoning, and as such, must be recognized as speculative. However, each offers a potentially useful and interesting direction for further examining the positive relationships between job demands, school demands, and inter-role facilitation found here, as well as in previous research (e.g., Butler 2007). Clearly, future research is needed to better understand these effects. Turning to job and school resources, our results for the relationships between control (job control or school control) and the work–school interface revealed two unique patterns of findings. When job control was examined as an antecedent, there was a significant positive relationship with WSF, but no significant relationship with WSC. Conversely, when school control was the antecedent of interest, there was a significant negative relationship with SWC, but no relationship with SWF emerged. One possible explanation for this pattern of findings is that participants viewed school control as relating more to the ‘‘when’’ of school commitments, particularly as it related to course scheduling, whereas they viewed job control as relating more to the ‘‘how’’ of getting their work completed. For example, if working students have the ability to schedule their classes around required work hours, it is not surprising they would experience significantly less SWC even if the nature of their school responsibilities
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and activities did not relate as directly to their work (i.e., SWF). When participants have more autonomy at work, we would expect that they could organize their work in a way that facilitates their school obligations, hence the significant relationship between job control and WSF. However, this autonomy regarding how to fulfill their work responsibilities may not influence deadlines for school obligations, hence the non-significant path between job control and WSC. Beyond our findings for control, three of the four proposed relationships between cross-domain interpersonal interest/support and the work–school interface were also shown to be significant. Specifically, interest/support from supervisors and coworkers had both a negative relationship with WSC and positive relationship with WSF, while interest/support from professors and classmates had a positive association with SWF. In addition, although the relationship between interest/support from professors and classmates and SWC failed to reach significance, this relationship was in the expected direction. At a general level, these findings speak to the utility of interpersonal resources for individuals balancing multiple life roles—a perspective largely supported in previous research within the work–family domain (e.g., Kossek et al. 2011). However, at a more specific level, findings from the current study also point to the value in examining perceptions of interpersonal interest/support that is explicitly cross-domain in its orientation. This focus is aligned with theorists’ suggestions that experiences of interpersonal support may be most effective when the nature of the support is closely aligned with aspecific type of stressor (Cutrona and Russell 1990). Applied here, for example, it is possible that individuals attempting to balance their school and work roles may see a benefit from interpersonal support when individuals within each specific domain recognize the challenges that are inherent in dividing one’s attention between their school and work responsibilities. A supervisor taking an interest in a student employee’s school responsibilities, for instance, sends a clear signal that he/she is aware of and values the student employee’s other life roles. As a result, greater WSF may be perceived, along with lower potential threats of WSC—both findings supported in the current study. Work–life researchers may consider drawing on our findings as a basis for exploring the efficacy of crossdomain experiences of support in other work/non-work contexts as well. Our results also support a positive relationship between school relevance and SWF. This finding speaks to the importance of applying theories and content learned in school to the workplace. Future researchers may draw from this finding as a foundation for exploring the applicability of specific theories or specific programs of study.
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The Work–School Interface and Work-Related Outcomes An important contribution of this study was its investigation of the relationships between all four bi-directional forms of work/school conflict and facilitation and work outcomes. To this end, our results indicated that the most influential predictor of job satisfaction, interpersonal facilitation, and job performance was WSF. WSF was significantly and positively related with all three outcome measures. In addition, the proposed relationships for SWC were partially supported, as SWC demonstrated a negative relationship with task performance. Results, on the other hand, did not show WSC or SWF to be significant predictors of any work-related outcomes. Collectively, these findings reflect an interesting pattern of results. Still, it is important to keep the nature of our sample in mind when interpreting these findings. Our undergraduate sample was predominately comprised of ‘‘traditional’’ students. By traditional, we mean students between the ages of 19–22 (as evidenced by an average age of 21), which is not surprising given that students enter the College of Business at this specific university during their junior year. It is likely that a significant percentage of the sample is not employed in a position that they would consider a career job. As such, it is conceivable that many participants may place a higher level of importance on their school role. Taking this into account helps highlight the potential value of WSF. For example, when the work role facilitates the school role, working students ultimately express more satisfaction on the job as they may view their ‘‘secondary’’ role has contributed to their ‘‘primary’’ life role. They likewise may be more willing to help coworkers and supervisors and be evaluated as a higher performer by their supervisor. This role importance lens must be considered as speculative given that it is based on post hoc reasoning. However, it does appear to offer a reasonable explanation for the consistent, meaningful influence of WSF on work outcomes found in this study. What’s more, a role importance lens can also be viewed as providing a useful means for understanding the null relationships between SWF and work-related outcomes. For example, it is conceivable that while students’ learning at school has the potential to inform their work role in a positive way, the connection may not be particularly strong if their current job is viewed as a ‘‘secondary’’ role. In this scenario, job satisfaction is likely not to be significantly influenced, and supervisors would not be expected to significantly raise performance evaluations. Our speculations about role importance may also provide insight into understanding the mixed findings for the relationship between SWC and work outcomes. Consider first that SWC demonstrated a significant negative
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relationship with supervisors’ reports of employee task performance. This relationship was as hypothesized, and recognizes that if school commitments are taking away from students’ ability to perform their work role responsibilities, supervisors would be likely to notice and rate job performance lower. Interestingly, however, no such relationship was discovered for job satisfaction, which suggests that while supervisors’ reports of employee performance may be influenced by conflict originating in the school role, such conflict had little influence on how individuals’ personally felt about their job. It is possible that conflict stemming from individuals’ primary domain (i.e., school) may have little relationship with their overall attitudes toward a secondary domain (i.e., work). Conflict arising from school-related responsibilities is likely to influence supervisor impressions of employee task performance, however, regardless of the value employees assign to the work domain. By the same token, we would also be less likely to see WSC influence supervisor ratings of job performance because performance decrements stemming from work’s interference with the school role would be more likely to be noticed by those evaluating students’ performance at school (e.g., their professors). Again, it should be kept in mind that a role importance perspective offers only one lens for unpacking the relationships between WSC, SWC, WSF, SWF, and work-related outcomes found here. Still, it does stand as a theoretically interesting perspective for future research on the effects of bi-directional conflict and facilitation between different life domains, and we encourage others to incorporate such possibilities in designing future research. Study Implications Our results highlight the critical role that WSF plays in creating a ‘‘win–win’’ situation for both the working student and the organization. Indeed, when the work role is improving the quality of the school role, both employees and employers have reason to be pleased with the situation. Student workers are more satisfied on the job, they are more willing to help out fellow employees, and their immediate supervisor evaluates their performance at a higher level. Our findings furthermore inform the proactive steps employers may take to increase the likelihood that employees who are balancing work and school roles will perform at higher levels. Job control and interpersonal support at work were both positively related to WSF. This suggests offering working students autonomy in their jobs to the extent possible. In addition, it is important for employers to create a work environment where both supervisors and coworkers show interest in their colleagues’ school endeavors and attempt to create
opportunities for work–school synergies while they are at work. Our findings further showed that job demands positively related to WSF. In other words, employees that are going to school are looking for ways to prove (and improve) themselves. A willingness to provide these employees with challenges and responsibilities is likely to be well received as long as employers stay within reasonable limits. These challenges may trigger an increased focus and motivation that prompts employees to multi-task in ways that benefits both roles. Limitations Our sample came from a single university, which has implications for generalizability. For example, it is possible that there are certain characteristics among institutional members that do not generalize to other universities. In addition, unique attributes of local employers may also not generalize to other areas. Second, the sample size for the current study was modest. Larger samples would reduce possible concerns associated with statistical power. It should be noted, however, that numerous findings emerged in spite of the small sample size. This suggests that significant relationships are likely to exist as our analyses provide a conservative test of the proposed model. Third, although we collected our data at multiple time points, we did not conduct a longitudinal study. Future research would benefit from longitudinal designs. Directions for Future Research Many students simultaneously work and study. As such, learning how to successfully balance the roles of student and employee is likely to remain a challenge. This study provides strong evidence of the critical role that WSF plays in the job performance of working students. Future research should therefore explore additional antecedents (e.g., financial need, school standing, major, service learning participation, and study abroad participation) of WSF as well as other bi-directional forms of conflict and facilitation. Additional research of all four bi-directional forms of the work–school interface is also vital. The present investigation focused on the perceptions and behaviors of traditional undergraduate students. Further exploration of graduate students and ‘‘non-traditional’’ undergraduates would also offer important insight. While the significant role of WSF is likely to remain, it would be interesting to see if a sample of older students, especially if they are already in their career field of choice, would place a greater emphasis on SWF. Future research could also draw on role importance perspectives identified in our discussion of study findings above, especially when examining samples
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that may attach different weights to the work and school roles, for example MBA students. This study revealed only one significant relationship (out of a possible six) between conflict experienced in the work– school interface and the organizational outcomes of interest (i.e., SWC was negatively related to task performance). More research is thus needed to better comprehend the role that WSC and SWC play on work-related outcomes, particularly when assessed simultaneously with experiences of facilitation. Further, future research could expand on the outcome variables that we examined. One variable that may be of particular interest to organizations that are currently investing in their employees’ education is retention. In conclusion, this study contributed to the work–school literature by presenting and testing a model that included all four bi-directional forms of the work–school interface. The findings revealed a unique pattern of results that both added to our understanding of the dynamics of this interface, as well as prompted ideas for future inquiry. We hope these findings will serve as building blocks for further investigation into ways that students, employers, and educational institutions can more effectively manage the connection between the work and school roles.
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