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An examination of the role of emotional intelligence in work and family conflict *.

Employers need to recognize the constant challenge many employees face in balancing work and family. Recruiting and retaining top workers is essential to the success of the organization; thus, it behooves employers to understand the variables associated with the effective management of the work-family conflict.

One cannot pick up a newspaper or periodical or even turn on the news without being confronted with the issue of balancing work and family. For most, it is a constant struggle to attempt to balance the commitments of work and family life. Some researchers have suggested that work-family balance is an illusive goal and one that is unattainable (Caproni, 1997). The concern is that the more one is committed to work, the more one enjoys the associated benefits, both financial and non-financial, which encourage them to devote even more time and energy to work. Since neither one's time nor energy is limitless, by definition, then, such workers will find themselves far from the balance they originally sought with one of the roles invariably ending up on the losing end.

As a result of an increasingly larger share of the workforce occupying many non-work roles in addition to that of paid worker, organizations need to understand the impact of multiple roles on workers' productivity. Attitudes, behaviors and emotions associated with one role may spill over to the other (Edwards and Rothbard, 2000). In fact, many employers fear that engagement in the family role is accomplished only to the detriment to the work role.

The work-family literature frames this balance in seemingly diametrically opposed views, namely the depletion and enrichment arguments (Marks, 1977). The former is more deeply rooted in the literature and views these roles as conflicting (Friedman and Greenhaus, 2000). One's energy and time are limited, and, as such, the demand in each role depletes resources at the expense of the other. Yet those scholars that view the work-family research through the lens of the enrichment hypothesis suggest that it is the occupancy of multiple roles and the quality of those roles that yield beneficial effects on one's well-being (Barnett and Hyde, 2001). The benefits to individuals provide a net gain over the costs, leading to a positive emotional response and better well-being,

In an effort to explain the competing views in the literature--the depletion or enrichment hypotheses--we propose that the question needs to be examined at the individual level. Specifically, we posit that Emotional Intelligence, a dispositional variable, interacts with work-family conflict to predict one's well-being. Consistent with research conducted by Noor (2003) that resulted in support for the effect of locus of control on the relationship between work-family conflict and well-being, this study expands the link to examine the effect of a broader dispositional measure. Noor (2003) sampled 310 married women with children who were employed full-time in Malaysia. She found that "women with high control beliefs generally were more vulnerable to work-family conflict" and that work-family conflict was positively related to symptoms of psychological distress--women's sense of general well-being" (2003: 658).

This study builds on past models of work and family stress that use individual differences as moderators of the effects of work and family experiences on well-being (e.g., Frone et al., 1997a; Greenhaus and Parasuraman, 1986; Higgins et al., 1992; Parasuraman et al., 1996). In addition, the present study answers the call of Greenhaus and Beutell for more research "to determine the impact of specific personal characteristics on role attitude/behaviors that affect the arousal of work-family conflict" (1985: 83), as well as Carlson's (1999) call for additional study of personality variables such as the "Big Five" to provide further insight into the underpinnings of work-family conflict. We posit that it is not necessarily a general all-encompassing trait that distinguishes the "handlers" from the "non-handlers," but rather it is an individual trait which can cross gender, race, ethnicity, and age.

The ultimate question is can you have it all? As Friedman and Greenhaus (2000) state in their book, Work and Family--Allies or Enemies ?, it is possible to have both a fulfilling career and a satisfying family life, but it requires balanced involvement in both of these spheres of our life. In other words, Freidman and Greenhaus suggest that it is the successful management of conflicting demands and one's level of satisfaction with their decisions that lead to balance. It is on the interrole conflict between the work role and the other life roles that much of the literature is based. Work-family literature is based on the boundaries between the two domains as being permeable such that work can influence family and family can influence work.

Work-family conflict has been found to be a predictor of employee's well-being (Vallone and Donaldson, 2001) and several studies have shown that it is a mediator between work and family roles and individual well-being (Aryee et al., 1999; Frone et al., 1997a). Also, it has been empirically shown to lead to psychological depression (Googins, 1991), physical ailments (Frone et al., 1997a), lower life satisfaction (Aryee, 1992), lower quality of family life (Higgins et al., 1992) and lower energy levels (Googins, 1991). Additionally, it is negatively related to employee job satisfaction (Boles et al., 2001).

Depletion

The depletion argument stems from research on role drain, namely what Marks refers to as the "drain theory" of energy (1977) as well as role conflict (Merton, 1957; Greenhaus and Beutell, 1985). The depletion argument of interrole conflict, according to Kahn, Wolfe, Quinn, Snoek and Rosenthal, is defined as the "simultaneous occurrence of two (or more) sets of pressures such that compliance with one would make more difficult compliance with another" (1964: 19). Goode suggests that the "individual's total role obligations are over-demanding." He further states that "role strain--difficulty in meeting given role demands --is therefore normal" (1960: 485). He likens the need for an individual to allocate his energy and skills to reduce role strain to "some bearable proportions" to the way the individual handles limited economic resources. One needs to make decisions as to where to allocate money and where not, the same as one needs to do with their energy. Similar to the equimarginal principle in economics which posits that one should maximize utility in allocating limited dollars among goods and services, an individual needs to maximize the results of his/her efforts and energy invested in one domain over the other. Opposing pressures arise from engaging in multiple roles and these pressures can be incompatible by requiring different roles to compete for a person's limited time resources as well as the strains associated with one or more roles (Kopelman et al., 1983). The assumption underlining the depletion argument is that multiple demands of paid worker and family role are detrimental to the individual and that role participation invokes stress, resulting in emotional strain (Rothbard, 2001).

Enrichment

The enrichment view, as postulated by Marks (1977), suggests that as an individual increases the number of roles he or she occupies, there is a net gain or benefit from them (enrichment) rather than a loss or depletion. Many studies have empirically supported the enhancement hypothesis by depicting a positive relationship between the involvement in multiple roles and various measures of psychological well-being (Barnett et al., 1992; Baruch and Barnett, 1986). The enrichment argument assumes that the benefits of multiple roles outweigh the costs, leading to gratification rather than strain (Rothbard, 2001).

HYPOTHESES

This study is primarily concerned with identifying a possible explanation for the disagreement regarding the beneficial effects of multiple roles on well-being. Similar to prior research, this study analyzed the roles of spouse, parent and worker (Sieber, 1974). These non-work roles were identified and studied because we want to focus on work-family conflict. Sociologists have focused on the resulting outcome of role strain or overload from one possessing both a paid worker role and a family role (Geerken and Gove, 1983).

Well-being

Researchers have developed models to predict how work and family influence stress and well-being (e.g., Frone et al., 1997b; Greenhaus and Parasuraman, 1986; Higgins et al., 1992; Kopelman et al., 1983; Parasuraman et al., 1996). Edwards and Rothbard (1999) studied how the cognitive appraisal process (up to that point, "notably absent from the models") influenced stress. Using the person-environment fit theory, Edwards and Rothbard "examined how the comparison of work and family experiences to the person's values relates to stress and well-being" (1999: 85). They wanted to explore possible explanations for why different people in the same situation experience different levels of stress.

Some models of work and family stress use individual differences as moderators of the effects of work and family experiences on well-being (e.g., Greenhaus and Parasuraman, 1986; Higgins et al., 1992; Parasuraman et al., 1996). Friedman and Greenhaus (2000) argue that time is not the major enemy of work-family conflict, rather it is the level of psychological interference of work into the family domain and of family concerns into the workplace. Recent research has associated personality variables and work-family conflict.

Personality traits and the interaction on work-family conflict have been studied, including aggressiveness (Lightdale and Prentice, 1994) and negative affectivity (Carlson, 1999; Bruck and Allen, 2003). In addition, there have been several studies that found a positive relationship between Type A behavior and workfamily conflict (Burke et al., 1979). Neuroticism was also found to have a positive relationship to work-family conflict (Bruck and Allen, 2003). Further research has shown that conscientiousness helps reduce the negative impact that work role ambiguity has on one's well-being (Bruck and Allen, 2003). Moreover, agreeableness was found to have a negative effect on work-family conflict: the more agreeable the individual, the greater reported work-family conflict (Bruck and Allen, 2003). Emotional Intelligence (EI) was also shown to predict persistence under frustrating circumstances (Schutte et al., 2000) and has been found to moderate the effect of work-family conflict on career commitment (Carmeli, 2003). In a study of senior managers, Carmeli found a significant interaction of work-family conflict and Emotional Intelligence in predicting career commitment. Stated differently, the higher a senior manager is on Emotional Intelligence, the weaker the negative effect of work-family conflict on career commitment (2003).

Emotional Intelligence

Emotional Intelligence is a profile of self-awareness, of managing one's emotions, of motivation, of empathy and social competence. Goleman's (1995) work thrusted the concept into the spotlight, although the term Emotional Intelligence was first used by Salovey and Mayer (1990). They defined Emotional Intelligence as "the ability to monitor one's own feelings and emotions, to discriminate among them, and to use this information to guide one's thinking and actions" (1990: 189).

Mayer and Salovey (1997) later identified four components of Emotional Intelligence: perception, assimilation, understanding and management. The first component is described as an ability to be self-aware of emotions and to be able to express one's emotional needs. Assimilation refers to one's ability to distinguish among different emotions they may be feeling and to prioritize those that are influencing their thought processes (Mayer and Salovey, 1997). The third component is the ability to understand complex emotions such as simultaneous feelings of loyalty and betrayal (Mayer and Salovey, 1997). The ability to distinguish the emotions that emerge from perceptions is important in overcoming negative responses to emotions. It is also in this component that Mayer and Salovey include the ability to understand other's emotional expressions and behaviors. Lastly, the management component is the ability to connect or disconnect from an emotion, depending on its usefulness in any given situation (Mayer and Salovey, 1997). This component varies from the personality domain because the regulation of emotions can vary to suit specific personality traits (Mayer and Salovey, 1997). Caruso et al. (2002) examined the relation of an ability measure of Emotional Intelligence to personality. This examination found that Emotional Intelligence was a "measure as reliable and independent of traditional defined personality traits, supporting the discriminant validity of the Emotional Intelligence construct" (2002: 306). Similarly, Saklofske et al. (2003) state that Emotional Intelligence self-reports measures account for variance not accounted for by personality. The contribution of Emotional Intelligence to one's attitude toward change was found to be significant, indicating the added value of using an Emotional Intelligence measure above and beyond the effect of personality (Vakola et al., 2004).

Many scholars have theorized that high Emotional Intelligence contributes to success in various aspects of life including work and relationships (e.g., Goleman, 1995; Salovey and Mayer, 1990). Because Emotional Intelligence theoretically includes the ability to understand and regulate others' as well as one's own emotions, it may be related to both characteristics that build relationships and the quality of those relationships (Schutte et al., 2001).

Furthermore, scholars have theorized that high Emotional Intelligence would lead to greater feelings of emotional well-being (Goleman, 1995; Saarni, 1999; Salovey and Mayer, 1990; Salovey et al., 1995; Schutte et al., 2002). Some empirical evidence that Emotional Intelligence is associated with emotional well-being comes from research indicating that higher Emotional Intelligence is associated with less depression, greater optimism (Schutte et al., 1998) and greater self-esteem (Schutte et al., 2002). Moreover, research found that individuals with higher Emotional Intelligence were better able to maintain a positive mood and self-esteem when faced with a negative state induction (Schutte et al., 2002). Thus, both theory and prior research advance a connection between Emotional Intelligence and well-being.

Hypothesis 1: Emotional Intelligence is positively related to well-being.

Work-family conflict has been identified as a source of stress that influences well-being (Greenhaus and Parasuraman, 1986). For example, it has been shown to be positively related to depression and decreased satisfaction with life and an intensified depressive affect (Marshall and Lang, 1990). Even perceived unfairness between work and family demands leads to psychological distress and depression in both men and women (Voydanoffand Donnelly, 1999). Thus, if one perceives the work-family demands as unfairly monopolizing their time and attention, one experiences more conflict between the two domains. This conflict leads to reduced feelings of well-being.

Hypothesis 2: Work-family conflict is negatively related to well-being.

The ability to perceive, understand and manage emotions is an integral part of Emotional Intelligence; thus, it seems that people with high Emotional Intelligence should experience lower worker family conflict. Carmeli (2003) studied the relationship between Emotional Intelligence and work attitudes and the behavior of senior managers. Among other findings, his results supported a finding that Emotional Intelligence moderated the negative influence of work-family conflict on career commitment. He suggests that this result "indicates that senior managers who have high Emotional Intelligence may better and more carefully handle the inherent work-family conflict than those with low Emotional Intelligence" (2003: 805).

A person with high EI is one that can recognize, and then effectively deal with their own emotions while at the same time recognize and empathize with others' feelings. Inherent in the work-family conflict is a tremendous amount of emotional upheaval. Inevitably one domain will encroach on the other and it results in more than just a time issue or energy constraints; it also invokes one's emotions. The ability to be aware of your emotions, express them and effectively manage them is a key determinant in whether the conflict between the two domains negatively impacts one's well-being.

This study suggests that Emotional Intelligence will have an impact on the relationship between work-family conflict and well-being. Consistent with Jordan et al. who argued that "Emotional Intelligence moderates the links between perceptions of job insecurity and affective reaction, as well as the links between affective reactions and behavior" (2002: 365), we posit that Emotional Intelligence interacts with work-family conflict to predict well-being.

Hypothesis 3: There is an interaction effect between Emotional Intelligence and work-family conflict on well-being.

METHODS

Participants

A total of 205 people participated in this study. For the study, 60.0% were female. Most (81.0%) were married and the most common racial/ ethnic group was Caucasian (77.1%), followed by African-American (15.1%). The age of the respondents ranged between 19 and 70, with a mean of 47.48 years, and a standard deviation of 11.14 years. For number of children, 34.6% reported having no children, with the most any respondent had was five children (M = 1.27, SD = 1.19). For education, 50.2% had a high school diploma, and the remainder had a college degree or more education. Years with the organization ranged from 1 to 34 (M = 10.78, SD = 7.32). Hours of work reported ranged from 4 to 82 (M = 38.25, SD = 8.16). For satisfaction and importance of work, the means and standard deviations, are 5.04 (1.36) and 5.87 (1.19), respectively.

The data collected for use in this study were part of a "Quality of Work-Family Study" at a university in the northeast of the U.S. This sample was drawn from a large university representing a large variety of jobs including unionized trade workers to executive managers. The survey sample was obtained from the population of employees at a suburban doctoral-granting university with a budget of over $242 million with approximately 8,000 full-time and part-time employees.

Measures

Gender was coded "0" for Male and "1" for Female. Marital status was coded as "1" for married and "0" for all other categories (i.e., single, widowed or divorced). Information on race, age, number of children and number of children living at home, average number of hours worked/week, number of hours caring for elderly parent were also collected from the respondent.

Control Variables. Consistent with prior research, martial status was considered a control variable (Bruck and Allen, 2003; Carlson, 1999; Cooke and Rousseau, 1984). In addition, work satisfaction (Netermeyer et al., 1996) and importance of work (Rothbard, 2001) were controlled for since these have been found to have a significant influence on work-family conflict, Emotional Intelligence and/ or well-being--a finding that is replicated in this study (Table 1).

Dependent Variable. The General Well-Being scale (GWB), developed in 1970 for the National Center for Health Statistics, was used to measure the dependent variable of well-being. The GWB is a structured instrument for assessing self-representations of subjective well-being. Scale scores run from 14 (lowest well-being) to 110 (highest well-being) for the first 18 items as described by Fazio (1977). This measure has been validated and shown to have good psychometric properties (Fazio, 1977). Mean scores for the first 18 items of the schedule were 75 for men and 71 for women (SD = 15 and 18, respectively). An example of an item from this scale is "Have you been under or felt you were under any strain, stress, or pressure during the past month?" The internal reliability, as measured by Cronbach's alpha, for this study was .89, an acceptable level based on Nunnally's (1978) criteria of .70.

Independent Variables

Work-Family Conflict. In this study, Work-Family Conflict (WFC) was measured using an eight-item scale. The first four items in the scale measure work-interfering with family (WIF), as developed by Kopelman, Greenhaus and Connolly (1983). The last four items were developed by Burley (1989) to assess family-interfering with work (FlW). This study analyzed both directions of work-family conflict (work interfering with family (WIF) and family interfering with work (FIW) as a combined measured of overall conflict. The internal reliability for this study, as measured by Cronbach's alpha, was .89. In addition, the work-family conflict variable means and standard deviations were comparable to those found in previous work-family conflict studies.

An example of an item from the WIF scale is "On the job I have so much work to do it takes away from my personal interests." An example from the FIW scale is "I'm often too tired at work because of the things I have to do at home." These eight items have been used in other work-family conflict research (Adams et al., 1996; Judge et al., 1994).

Emotional Intelligence. The Schutte Emotional Intelligence Scale (EIS), a self-report measure, was used in this study to measure Emotional Intelligence. This scale is based on the model of Salovey and Mayer (1990), which has been labeled as the standard for "scholarly discourse" (Jordan et al., 2003). As Schutte et al. (1998) stated in the defining article of the EIS, it is a reliable, valid measure of Emotional Intelligence as conceptualized by Salovey and Mayer (1990). The EIS represents the following categories which are consistent with the Mayer and Salovey (1997) conceptualization of Emotional Intelligence: appraisal and expression of emotion in oneself and others, regulation of emotion in self and others, and utilization of emotions solving problems.

The EIS is a scale of a trait measure of Emotional Intelligence that was developed through factor analysis which showed good reliability with two different samples. Two-week test-retest reliability indicated that the scores were fairly stable over time. The EIS reported internal consistency was between .87 and .90 (Schutte et al., 1998). It consists of 33 items which assess to which extent individuals perceive, understand, regulate and harness emotions adaptively. On a five-point Likert scale (1 = strongly disagree, 5 = strongly agree) respondents rate their agreement with such items as "I am aware of my emotions as I experience them," and "I help other people feel better when they are down." The sum of all items constitutes the total score, which can range from 33-165 (higher scores indicate greater Emotional Intelligence). The internal reliability for this study, as measured by Cronbach's alpha, was .90.

Analysis

To test hypotheses 1, 2 and 3, a two-way ANOVA was used with the independent variables being Emotional Intelligence (low and high) and WFC (low and high), and the dependent variable was well-being. The independent variables were dichotomized using median splits to conduct the 2 x 2 analysis of variance on well-being. The dichotomization of the variables is consistent with prior research (Nikolaou and Tsaousis, 2002; Hammer et al., 2004). Since job satisfaction and job importance were found to be significantly correlated with the dependent variable, factorial analysis of covariance (ANCOVA) was carried out, with job satisfaction and job importance as covariates, along with marital status since prior research suggested its impact on well-being (Bruck and Allen, 2003; Carlson, 1999; Cooke and Rousseau, 1984). As covariates in the ANCOVA, any variability attributed to these variables was partialled out of the dependent variable, well-being.

RESULTS

The correlations between the three primary scales (Emotional Intelligence, work-family conflict, and well-being) and the selected variables including the control variables as well as the reliability estimates are presented in Table 1. Emotional Intelligence (M = 123.7, SD = 13.5) was correlated with well-being (r = .36), importance of work (r = .17) and negatively correlated with work-family conflict (r = -.27). Work-family conflict (M = 19.53, SD = 5.8) was also negatively correlated with well-being (r = -.35), age (r = -.15), satisfaction with work (r = -.23), and importance of work (r = -.19). Work-family conflict was significantly yet slightly correlated with number of hours the respondent worked (r = .16). In addition, well-being was positively correlated with work satisfaction (r = .33), and importance of work (r = .24).

Table 2 displays the analysis of covariance for well-being, based on Emotional Intelligence and work-family conflict. The covariates included marital status, work satisfaction, and importance of work. The overall model was significant (p < .001), accounting for 30.7% of the variance in well-being. Both main effects (Emotional Intelligence and work-family conflict) were significant (p < .001), with Emotional Intelligence accounting for 10.8% of the variance in well-being and work-family conflict accounting for 7.4% of the variance. In addition, the interaction of Emotional Intelligence and work-family conflict was also significant (p < .05).

Inspection of the means and standard errors in Table 3 found the group with high Emotional Intelligence coupled with low work-family conflict to have the highest mean for well-being (M = 81.13). In addition, respondents with low Emotional Intelligence and high work-family conflict had the lowest level of well-being (M = 63.36). Figure I provides a graph of the interaction of Emotional Intelligence and work-family conflict. Based on the results indicated in Tables 2 and 3 and Figure I, hypotheses 1, 2 and 3 could not be rejected. (1)

[FIGURE I OMITTED]

DISCUSSION

As shown, the hypotheses advanced in this study on the influence of work-family conflict and Emotional Intelligence on well-being could not be rejected. The results showed that the variables of Emotional Intelligence and work-family conflict (hypotheses 1 and 2) had significant influence on the dependent variable of well-being. Similarly, results from testing Hypothesis 3 showed a significant interaction effect between Emotional Intelligence and work-family conflict on well-being.

The results presented in this study suggest that Emotional Intelligence acts as a protector variable in the impact of work-family conflict on one's well-being. Higher Emotional Intelligence positively influenced well-being. Specifically, those individuals in this sample who had high Emotional Intelligence with low work-family conflict reported the highest well-being while those with low Emotional Intelligence and high work-family conflict reported the lowest well-being. Additionally, the results of this study showed that low Emotional Intelligence and low work-family conflict yielded similar well-being scores as those with high Emotional Intelligence and high work-family conflict. Thus, in situations where one experiences a significant amount of work-family conflict, the possession of high Emotional Intelligence will protect their well-being. This study showed that for these people, their well-being scores were very similar to those who experience low work-family conflict. Consequently, it seems that possession of high Emotional Intelligence is more important when facing work-family conflict.

This finding is consistent with past research that has theorized that high Emotional Intelligence leads to greater feelings of well-being (Goleman, 1995; Saarni, 1999; Salovey and Mayer, 1990; Salovey et al., 1995; Schutte et al., 2002). The ability to be aware of one's emotions and capable of managing them successfully will enhance one's well-being when facing work-family conflict. To help illustrate this effect, one may think of Emotional Intelligence as something one can develop to help protect them against the stress of meeting demands in both domains. It is something in one's "bag-of-tricks," if you will, that can be utilized to maintain a healthy well-being.

This study makes several contributions to the field. It contributes to the work-family literature by focusing the lens in which work-family conflict is viewed. Specifically, this study suggests that the dichotomous hypotheses of depletion and enrichment may each have value but they are driven by an intensely individualistic phenomenon.

Implications

Work-family conflict is an issue that cannot be ignored. The profile of the labor supply (workers have increased family responsibilities, i.e., greater number of dual-income households and elder-care responsibilities) coupled with societal pressure places this issue squarely on any human resource professional's radar. Lost time due to family demands and employee stress costs employers billions of dollars each year. In fact, despite employers having strong work-family or work-life initiatives, many employees still face difficult and oftentimes debilitating stress from the conflict that arises from trying to balance both domains. As found in this study, in Hypothesis 2, the resulting work-family conflict experienced by employees has a negative effect on their well-being.

The tested hypotheses in this study begin to shed light on possible avenues for employee training to better equip them with much needed tools to handle work-family conflict. Demographic trends highlight that if employees cannot find ways to effectively deal with the work-family conflict, they choose to remove themselves from the work domain. The finding in this study (Hypothesis 1c), that emotionally intelligent individuals have higher well-being when facing work-family conflict than those with lower Emotional Intelligence, can be useful to employers when trying to retain workers. Successful employers recognize the strategic advantage that human resources can provide and must find ways to help retain highly skilled employees. Retention, therefore, needs to be a significant goal of employers and they must determine ways to help these employees deal with the oftentimes conflicting demands of the family and work domain.

Organizations can target resources to help individuals improve their Emotional Intelligence in order to better handle the conflicting demands. One's resiliency can be measured through their Emotional Intelligence. Emotionally intelligent individuals can, through self-regulation, adapt to the social situation and remain functional (Eisenberg and Fabes, 1992). Human resource professionals need to implement learning opportunities as well as nurture an environment that recognizes the value of self-exploration. It is a concept often met with skepticism and ridicule. Therefore, it is important that the organization's culture supports and encourages employees to put effort into self-awareness training and exercises.

Emotional Intelligence can be developed and improved. Organizations can begin to allocate resources to helping employees learn to be resilient and to develop increased Emotional Intelligence. By helping employees effectively deal with the inherent emotions of handling the family and work domains, employers will benefit as well. As Cappelli noted, "when employees believe that their employer is supportive of their well-being, they are more committed" (2003:11). Similarly, Thompson et al. suggested that the "organization's ability to communicate respect for employees' non-work lives affects the level of perceived work-family conflict" (2004: 558). Moreover, organizations that assist employees in improving their Emotional Intelligence should benefit by reducing the oftentimes dysfunctional behavior that results when employees become overwhelmed by stress. Employees struggling to meet the demands in both domains are searching for avenues that provide help and relief to this constant dance between work and family. Organizations that can effectively offer training in the abilities underlying the construct of Emotional Intelligence will ultimately enjoy more committed employees.

Limitations and Future Research

There are several limitations of this study that should be understood in interpreting the results. To begin, the cross-sectional nature of the study prevents the examination of causal relationships. Future studies with an experimental design are needed to draw conclusions about causality. Although causation cannot be substantiated with cross-sectional data, the theoretical underpinnings strongly support the directions suggested in the study.

All measures were derived from the self-report of the respondents, potentially contributing to inflated inter-item correlations due to common method variance (Podsakoff et al., 2003). Common method variance is variance that is attributable to the measurement method rather than to the constructs measured. However, the use of self-report scales seems logical since the study was interested in capturing stable, internal states of the respondents that could not be manipulated. Furthermore, Crampton and Wagner (1994) challenge the validity of the general condemnation of self-reports, citing that there is research that has failed to show evidence of any meaningful inflation. Rothbard and Edwards (2003) justify the use of self-report measures when they are consistent with the focal constructs of the study, since the most accurate source of information regarding an individual's own perceptions of workfamily conflict and well-being is the person him/herself. Thus, this limitation is warranted by the focus on psychological stress which arises from the person's perception of the situation and self (Edwards and Rothbard, 1999). Moreover, the pattern of results observed suggest that common method bias is an unlikely explanation for the results.

All data were collected at one point in time and from one organization. A more precise study should involve multiple methods (e.g., interviews with family and co-workers, diaries of employees and their family) of data collection. Also, multiple sources of data should be used (family members, co-workers, supervisors). Further, all of the respondents worked for a northeast university. Nearly half of them had a college degree or higher. It is important to note that the sample did not include any members of the faculty since that is a position unique to a university setting. The sample, however, did include a broad range of non-faculty job types. Yet it cannot be overlooked that a university culture is quite unique. For example, a core value for most institutions of higher learning is the longevity of service by its employees. As a result, employees tend to have less anxiety over job security. Additionally, a common benefit associated with employment at a university or college is a generous time-off allotment, thus allowing for greater workfamily flexibility. Consequently, the depletion argument may be underrepresented.

This study helps support the introduction of an individual-specific variable into the continuous analysis of work-family conflict. Future research, however, should address the limitations of this study to confirm the findings. Specifically, future research should test more diverse samples, encompassing many industries, geographic locations, and classification of employees. In addition, the study would be greatly enhanced if one could obtain confirmatory data. A longitudinal study is needed so that the process can be studied over time, capturing the data during various occurrences of stressful situations.

Additionally, it would be helpful to substitute an ability measure of Emotional Intelligence, such as the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), to substantiate the finding using the self-report measure. Also, it would be useful to look at the model separately for work interfering with family and family interfering with work. While this study did use a work-family conflict measure that differentiates between work interfering with family and family interfering with work, the study analyzed them together, because the purpose of this study was to look at all sources of work-family conflict. Future research, however, may look at each separately.

Furthermore, this study primarily consisted of working spouses and parents. However, an emerging trend that will undoubtedly affect the workfamily conflict is the role of elder-care provider. According to the National Council for the Aging, approximately 40% of the workforce will be caring for an elderly parent by 2020. Arguably the role of elder-care provider stirs even greater emotional response as many find it difficult to handle the emotional burdens of caring for an ailing parent. This role needs to be included in the debate of work-family conflict as it is one many people will find themselves occupying.

Lastly, much of the work-family literature is not cross-cultural. A significant contribution to the field and the body of literature at large would be to analyze cross-cultural differences in the antecedents and moderators of work-family conflict and well-being.

Conclusion

The primary purpose of this study was to gain further insight into the effect that work-family conflict has on one's well-being, by introducing a dispositional variable, Emotional Intelligence, into the equation. The results provide an avenue to explore that attempts to shed some light on the opposing views in the work-family conflict literature, namely the depletion and the enrichment hypotheses. The results of this study support the finding that possession of Emotional Intelligence will act as a protector variable of one's well-being in the face of work-family conflict. In other words, Emotional Intelligence interacts with work-family conflict to predict one's well-being.

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Janet A. Lenaghan

Assistant Professor of Management

Hofstra University

Richard Buda

Associate Professor of Management

Hofstra University

Alan B. Eisner

Associate Professor and Graduate Program Chair of Management

Pace University

* The authors gratefully acknowledge the insightful comments of Dr. Charles C. Fischer, editor of JMI and two anonymous reviewers. We would also like to thank Alvin Hwang and Dan Baugher for their contributions to this research. This article is dedicated to the memory of our friend and coauthor, Dr. Richard Buda, who passed away on September 2, 2005.

(1) Outcomes comparable to those reported emerged when treating WFC and EI as continuous variables and using hierarchical regression. The interaction effect remained significant at the .05 level.
Table 1
Correlations between Primary Scales and Selected Variables

 Work-
 Emotional family Emotional
 Intelligence Conflict Well-being

Emotional Intelligence 1.00
Work-family Conflict -.27 ** 1.00
Well-being .36 ** -.35 ** 1.00
Gender (a) .13 -.12 -.06
Marital Status (b) .08 -.05 .13
Race/Ethnicity (c) .08 .03 -.06
Age .07 -.15 * .09
Number of Children -.03 .01 -.09
Education .09 .05 .07
Staff Size -.05 .06 -.01
Years in Organization .05 .02 .05
Hours of Work .02 .16 * .03
Satisfaction of Work .11 -.23 ** .33 **
Importance of Work .17 ** -.19 ** .24 **

(N = 205)

* p < .05; ** p < .01.

(a) Gender: 1 = Male; 2 = Female

(b) Marital Status: 0 = Other; 1 = Married

(c) Race/Ethnicity: 0 = Other; 1 = Caucasian

Note. Italicized numbers on the diagonal are the reliability
coefficients. All other numbers are correlations.

Table 2
ANCOVA Analysis of the Influence of Emotional Intelligence and
Work-family Conflict on Well-being

Source SS df MS

Full Model 16765.58 6 2794.26
Marital Status 651.85 1 651.85
Work Satisfaction 1719.17 1 1719.17
hnportance of Work 68.25 1 68.25
El 4564.45 1 4564.45
WFC 3014.51 1 3014.51
El X WFC Interaction 731.36 1 731.36
Error 37879.57 198 191.31
Total 54645.16 204

 Partial
 Eta
Source F p Squared

Full Model 14.61 .001 .307
Marital Status 3.41 .066 .017
Work Satisfaction 8.99 .003 .043
hnportance of Work 0.36 .551 .002
EI 23.86 .001 .108
WFC 15.76 .001 .074
EI X WFC Interaction 3.82 .052 .019
Error
Total

(N = 205)

(a) Covariates.

(b) Main effect adjusted means: High EI (M = 79.01) versus Low EI
(M = 69.33).

(c) Main effect adjusted means: High WFC (M = 70.13) versus Low WFC
(M = 78.22).

Table 3
Descriptive Statistics for Well-being Adjusted for Covariates (a)

Emotional Work-family
Intelligence Conflict N M SE

Low Low 39 75.30 2.23
 High 62 63.36 1.81
High Low 58 81.13 1.85
 High 46 76.89 2.04

(N = 205)

(a) Covariates: Marital Status, Work Satisfaction, and
Importance of Work.
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Date:Mar 22, 2007
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