Beyond Self-Efficacy: Interactive Effects Of Role Conflict And Perceived Collective Efficacy.
Concordant with the definition of self-efficacy, collective efficacy refers to members' perceptions of their group's competency (Bandura, 1986) or aggregated ability to successfully complete a designated task (Guzzo et al., 1993). Belief structures are present in most work groups (Louis and Sutton, 1991), and these opinions regarding a group's collective efficacy may have important effects on an individual's experiences and reactions at work. Although collective efficacy has been the subject of very little research (Bandura, 1997), findings suggest that it varies among groups (Campion et al., 1993), and that it is positively correlated with job satisfaction, commitment (Riggs and Knight, 1994), and task performance (Parker, 1994; Prussia and Kinicki, 1996). Jex and Gudanowski (1992) also reported several significant relationships between collective efficacy and perceived problems at work (i.e., job stressors) and psychological strains.
Taken together, these studies suggest that beliefs about the collective efficacy of one's work group may significantly influence a variety of work outcomes. However, additional work is needed to uncover the effects of perceived collective efficacy after considering the effects of self-efficacy. For example, the literature has not examined what, if any, effects arise from an individual's beliefs regarding his or her work group's efficacy after considering the effects of self-efficacy. We propose that one possible consequence of perceived collective efficacy may be its relationship to job stressors that the individual encounters.
Many employees encounter role conflict in their jobs. This stressor arises when a job incumbent is confronted by incompatible or incongruous expectations that are difficult or impossible to simultaneously satisfy (Kahn et al., 1964). Greater role conflict is consistently associated with greater job stress and burnout (e.g., Lee and Ashforth, 1993). The lean structures of today's organizations make it likely that role conflict will continue to be a frequent source of stress for many employees.
The purpose of the current study is two-fold. First, we examine the direct effects of perceived collective efficacy, after statistically controlling for self-efficacy beliefs, on three outcomes important to both the organization and individual: job satisfaction, job exhaustion, and intent to turnover. Next, we extend previous studies by examining the interaction of perceptions of collective efficacy and role conflict on the three outcome variables. Given that many jobs are performed within a group setting and team based approaches are growing (for reviews, see Bettenhausen, 1991; Guzzo and Dickson, 1996; Weingart, 1997), empirical investigations of this nature appear warranted.
In the following sections, we first briefly discuss the importance of the outcome variables examined in this study. We then discuss the relevance of perceived collective efficacy in a nursing environment and the expected hypotheses that we tested. Finally, we present our findings, discuss the potential implications for managers, and offer directions for future research.
Job satisfaction is an emotional and cognitive state resulting from evaluating one's task, activity, job, or other related experiences (Locke, 1976). Research has long shown that job dissatisfaction is associated with more employee stress and an increase in heart disease and poor mental health (Cooper and Payne, 1988). Further, there is strong support for job satisfaction's negative relationship to employee withdrawal behaviors such as absenteeism and turnover (Mobley et al, 1979; Mowday, 1981). Understanding when and why individuals voluntarily leave organizations is an issue that has intrigued both practitioners and academicians (Mowday et al, 1982). Despite over 100 years of research in this area (Bluedorn, 1982; Steers and Mowday, 1981), investigations examining this elusive relationship continue to surface. Practitioner interest in the topic stems primarily from the need to control costs, because the financial resources needed to recruit, select, and train new employees remain sizable (Cascio, 1994; Dalt on et al, 1981; Williams and Livingstone, 1994). Researchers, on the other hand, continue to develop and refine models to understand the theoretical antecedents and consequences of employee separation (Griffeth and Hom, 1995; Lum et al., 1998), including a more involved awareness of the causes of turnover (McEvoy and Cascio, 1987).
Our final outcome, emotional exhaustion, is believed to be at the core of burnout (Maslach, 1982), and is characterized by a lack of energy and a feeling that one's emotional resources are used up (Cordes and Doughtery, 1993). Researchers have linked burnout to a variety of mental and physical health problems (Burke and Deszca, 1986; Maslach and Pines, 1977), including decreased self-esteem, increased levels of irritability, depression, and anxiety, as well as the deterioration of family and social relationships (Jackson and Schuler, 1983). Burnout also has been linked to several negative organizational outcomes including lower organizational commitment among nurses (Leiter and Maslach, 1988) and impaired performance (Wright and Bonett, 1997). Clearly, emotional exhaustion is financially costly to organizations.
Measuring Collective Efficacy Beliefs
Collective efficacy has been operationalized in a variety of ways. For example, collective efficacy has been measured as an aggregate of individual members' self-efficacy or as an agreed-upon amount derived from group discussions (Bandura, 1997; Gibson, 1999; Hodges and Carron, 1992). Alternatively, researchers (e.g., Jex and Gudanowski, 1992) have defined collective efficacy as individual member's assessments of their group's ability to perform job-related behaviors.
Because this study focuses on individual perceptions and individual outcomes that result from perceptions of one's work groups' competency, and because it is important to match the measure to the level of analysis, we utilized individuals' ratings of their groups' efficacy. Consistent with Jex and Gudanowski (1992) and others (e.g., Earley, 1993; Parker, 1994), we use collective efficacy" to refer to an individual's assessments of his or her group's competency and likelihood for success. We provide this definition without making assumptions regarding the degree of agreement among members about the assessment. Perceptions of the group may impact decisions to remain a member of the group as well as affective reactions to a job regardless of whether the individual's perceptions are accurate or agreed upon by others.
Collective Efficacy in Nursing Environments
Perceptions of collective efficacy may significantly influence individual and organizational outcomes because they become part of the group member's normative belief structure. As a consequence, they influence members' expectations about the way things are and will be done (Zacarro et al., 1995). Given the task requirements of the job, the nursing profession is inherently dependent on the coordination of group activities (Egan and Kadushin, 1995; Parson, 1997). Moreover, there continue to be calls to break away from traditional forms of patient care to an interdisciplinary approach (Clouten and Webber, 1994; Poulin et al., 1994). Therefore, nursing groups appear to be especially suitable for examining perceptions of collective efficacy and its relationship with job stressors encountered on the job. The delivery of high quality health services often depends on collaborative relationships (Antai-Otong, 1997) among individuals with vastly different skills. Hence, we hypothesized:
H1: Controlling for self-efficacy, nurses who perceive greater collective efficacy within their department report greater job satisfaction, less exhaustion, and fewer intentions to turnover.
The Interaction of Role Conflict and Collective Efficacy
As noted above, research has shown that employees encounter role conflicts in virtually all occupations and work settings. With respect to the current study, past research has demonstrated the adverse effects of role conflict in nursing environments (Barber and Iwai, 1996; Jamal, 1990), including lower job satisfaction and increased turnover. Perceptions of collective efficacy may largely determine members' expectations about the manner in which tasks should be and/or are completed. Zaccaro et al. (1995) proposed that increased job dissatisfaction and intent to turnover are more likely to take place when a work group perceives itself to possess low ability, one factor in determining the successful completion of team objectives. Alternatively, individuals who perceive their group members to be highly competent may react less negatively when role conflict arises because they anticipate that others within their department can successfully contribute towards the completion of tasks. Regardless of how strongly a n urse believes in her (his) own abilities (i.e., high self-efficacy), he (she) cannot simultaneously complete paperwork, schedule medical tests, and respond to a patient's call button. Having confidence in the abilities of others within a department to successfully complete nursing tasks may determine how the members of a department delegate tasks when time pressures are abundant. Believing that the members of one's department can aid in the completion of tasks is likely to alleviate feelings of stress and frustration (Jex and Gudanowski, 1992). We expect that individuals who perceive greater collective efficacy in their department will report greater job satisfaction, lower exhaustion and fewer intentions to turnover when faced with increased levels of role conflict than individuals who perceive lower collective efficacy. Hence, we hypothesized:
H2: Perceived collective efficacy will moderate the relationship between role conflict and job satisfaction, exhaustion, and intent to turnover. Specifically, perceptions of greater collective efficacy will reduce the negative relationship between role conflict and job satisfaction and reduce the positive relationship between role conflict and emotional exhaustion and intent to turnover.
In testing our hypotheses, we took a conservative approach in that we controlled for variables previously found to explain variance in our outcome variables. We included age and gender as control variables based on findings of previous studies showing their impact on job satisfaction and intentions to leave (e.g., Eichar et al., 1991; Lambert, 1991; Scott and McClellan, 1990). Moreover, research has shown both age (Stanton et al., 1998) and gender to be associated with exhaustion (Greenglass et al., 1998), hence they are included as control variables. Finally, because we wanted to examine the effects of collective efficacy beyond that explained by self-efficacy, we controlled for perceptions of self-efficacy.
Sample and Procedure
A questionnaire, along with a cover letter explaining the purpose of the study and a postage paid pre-addressed envelope, were distributed to 380 nurses of a metropolitan hospital located in the Southeast United States. One hundred eighty-eight surveys were returned by mail directly to the authors for a response rate of nearly 50 percent (49.4%). Analysis of demographic data indicated approximately 90% of the respondents were female, ranging in age from 24 to 64. Based on the personnel database, the Director of Nursing Research confirmed that the sample's demographics were very similar to that of the entire nursing staff employed at the hospital.
Collective Efficacy. We adapted a ten-item measure used by Riggs and Knight (1994) to assess collective efficacy. Respondents were asked to think about their department and rate the group's abilities to perform their jobs using a six-point scale with endpoints of strongly disagree (1) and strongly agree (6). Items include "This department is not very effective" (reversed scored) and "The department I work with has above average ability." Higher scores indicate heightened levels of perceived collective efficacy.
Role Conflict. A three-item scale developed by Rizzo et al. (1970) was used to measure role conflict. An example item is "I receive incompatible requests." The seven-point scale has endpoints of strongly disagree (1) and strongly agree (7), such that higher scores reflect greater perceived role conflict.
Self-efficacy. Beliefs about one's own efficacy was measured using an 11-item scale developed by Riggs (Riggs and Knight, 1994). An example item is "I have confidence in my ability to do my job." A six-point format with response anchors ranging from strongly disagree (1) to strongly agree (6) was used.
Job satisfaction. Job satisfaction was measured with the Michigan Organizational Assessment Questionnaire (Cammann et al., 1979). An example item is "All in all, I am satisfied with my job." The three-item scale used a seven-point format with end-points of strongly disagree (1) and strongly agree (7). Higher scores reflect greater job satisfaction.
Exhaustion. Emotional exhaustion reflects the core of job burnout (Leiter, 1990) and was measured using nine items from the Maslach Burnout Inventory (Maslach and Jackson, 1986, 1981). Respondents used a scale from never (0) to every day (6) to respond to each item. An example item is, "I feel emotionally drained from my work." Higher scores reflect greater levels of exhaustion.
Intent to turnover. Turnover intentions were measured using a seven-item scale (Mobley et al., 1978; Mowday et al., 1984) with endpoints of strongly disagree (1) and strongly agree (7). An example item is "I intend to quit my job." Higher scores reflect stronger intentions to turnover.
Means, standard deviations, reliability estimates, and intercorrelations among the study variables are reported in Table 1. All reliability estimates were greater than .70, indicating an adequate level of agreement. As shown, self-efficacy was positively correlated with perceived group efficacy (p<.01), job satisfaction (p<.01) and exhaustion (p<.05), but was not significantly correlated with either role conflict or intent to turnover. Perceived collective efficacy was negatively correlated with role conflict (p<.01) and intent to turnover (p<.01), and positively correlated with job satisfaction (p<.01).
Confirming the Uniqueness of Job Satisfaction, Exhaustion, and Turnover Intent
Given the high intercorrelations between our three dependent measures (r's ranging from (.49 to -.63), we conducted confirmatory factor analyses using LISREL 8 (Joreskog & Sorbom, 1993) to assess the discriminant validity of our dependent variables (i.e., job satisfaction, exhaustion, and intent to turnover). The 18 items from the three scales were examined in three models: a null model, a one-factor model, and a three-factor model. The null model was most restrictive in that each item loaded on a separate variable, thus featuring 18 orthogonal factors. In the second model, all 18 items loaded on one factor. In the three-factor model, each item loaded on its respective factor. If the three constructs are truly distinct, the three-factor model should provide the best fit. Results indicate that neither the null model (df = 135, [chi square] = 1314.64, GFI = .55, AGFI = .43, CFI = .00, IFI = .00) nor the one-factor model (df = 135, [chi square] = 298.82, GFI = .84, AGFI = .80, CFI = .59, IFI .60) provided eviden ce of adequate fit. Conversely, the three-factor model (df = 132, [chi square] = 184.79, GFI = .90, AGFI = .87, CFI = .72, IFI = .73) represented a significant improvement over the next best fitting solution (df = 3, [DELTA] [chi square] = 114.03, p<.01). These results support the uniqueness of each of the three dependent measures.
Test of Hypotheses
To test Hypothesis 1, we used hierarchical regression analysis (Cohen and Cohen, 1975). For each outcome (job satisfaction, exhaustion, and intent to turnover), gender, age, self-efficacy, and role conflict were entered in the first step. In step 2, perceived collective efficacy was entered. We used hierarchical moderated regression to test Hypothesis 2 by entering the interaction term (role conflict x perceived collective efficacy) in step 3.
Table 2 displays the results of the regression analyses. The overall models for job satisfaction (F = 15.19, p<.01), exhaustion (F = 15.77, p<.01), and intent to turnover (F=15.38, p<.01) were significant and explained 35-36% of the variance in each outcome. Age and gender failed to significantly predict any of the work outcomes. As expected, self-efficacy positively predicted job satisfaction (p<.05) and negatively predicted exhaustion (p<.01). Direct effects were also found for role conflict on job satisfaction (p<.01), exhaustion (p<.01.), and intent to turnover (p<.0l). Consistent with previous studies, perceived collective efficacy directly and positively predicted job satisfaction (p<.01) and negatively predicted intent to turnover (p<.01), explaining an additional 3-4% of the variance in these outcomes. However, collective efficacy did not explain additional variance in exhaustion beyond self-efficacy scores. Given these results, partial support for Hypothesis 1 was found.
After controlling for the direct effects, the role conflict-collective efficacy interaction significantly explained an additional amount of variance in job satisfaction ([DELTA][R.sup.2] = .04, p < .01), exhaustion ([DELTA][R.sup.2] .02, p < .05) and intent to turnover ([DELTA][R.sup.2] = .03, p < .01), providing support for Hypothesis 2. These effects are within the typical range (i.e., [DELTA][R.sup.2] = .01 to .03) reported for moderator effects in non-experimental studies (Champoux and Peters, 1987).
In order to identify the form of interaction, we plotted slopes (Stone and Hollenbeck, 1989) for individuals reporting high collective efficacy (i.e., at least one standard deviation above the mean; subgroup N 39), moderate collective efficacy (i.e., between one standard deviation below the mean and one standard deviation above the mean; subgroup N = 111), and low collective efficacy (i.e., at least one standard deviation below the mean; subgroup N = 30). Figures I, II, and III display the interactions for job satisfaction, exhaustion, and intent to turnover, respectively. Consistent with our hypotheses, perceived collective efficacy buffered the dysfunctional effects of role conflict on all three outcomes. Subgroup analyses substantiate these findings. For example, the relationship between role conflict and turnover intent was much stronger for low collective efficacy individuals (r = .68) when compared to high collective efficacy respondents (r = .33). Comparable associations were demonstrated for both job satisfaction (r = -.52 and -.34, respectively) and exhaustion (r = .63 and .46, respectively).
In extending the work of Jex and Gudanowski (1992), the results from this field study confirm our contention that perceptions of collective efficacy significantly influence some individual outcomes beyond that of self-efficacy. Furthermore, our findings indicated that collective efficacy moderated the relationship between role conflict and several outcomes. Specifically, our findings suggest that the negative effects of role conflict can be partially lessened when individuals perceive their groups to be highly efficacious. With today's leaner staffing strategies and the increased use of teams comprised of members from a variety of disciplines and varying priorities, it seems unlikely that team members will be able to avoid encountering role conflicts at work. Therefore, our findings appear to be particularly relevant. Our results are also consistent with Bandura's (1982) proposition that collective efficacy is integral to group success because it influences members' willingness to stay members of a group when efforts fail to produce expected results.
We agree with Jex and Gudanowski (1992) who propose that individual and group efficacy may have a distinct set of underpinnings and possess different predictive validities. In a general sense, our results substantiate this view. For example, the correlation between individual and collective efficacy was relatively modest (r = .22, p<.01), reflecting little evidence of construct redundancy. Moreover, correlations between these variables and other constructs examined in this study were not wholly consistent (i.e., role conflict, job satisfaction, and turnover intent), thus providing additional support for independence.
Finally, our results indicate that when role conflict is low, those perceiving their group to be efficacious reported lower job satisfaction and higher exhaustion and intent to turnover scores. Although not a main objective of this study, these findings appear to be counterintuitive since past research has usually substantiated positive relationships between collective efficacy and work outcomes. However, past studies often present scores across the entire range of collective efficacy. With regard to explaining our unexpected findings, research has suggested that efficacious groups are persistent, dedicated, and often intrigued by challenging work. They also see performance as a way to separate themselves from others in the organization (Zaccaro et al., 1995). When there are few obstacles in the immediate work environment, as is the case when role conflict is low, efficacious group members may be unable to perceive opportunities for growth or the possibility of distancing themselves from other groups. Hence, an environment possessing low role conflict may not provide desired opportunities for an efficacious group to display their skills. Given that we did not measure variables necessary to substantiate these claims, they remain speculative pending future research.
Implications for Practice
Organizations are increasingly using work groups or teams to involve and empower employees (Ford and Fottler, 1995). In doing so, it seems prudent for managers to give consideration to the interdependent nature of some jobs and the resulting implications of perceived collective efficacy. Stevens and Campion (1994; 1999) recently offered evidence for the practical value of considering individual skills and abilities in the staffing of work teams. Careful consideration should be given to the specific technical and interpersonal skills needed within a group and the steps required to ensure the appropriate selection, training, and retention of group members. Diligence in forming and managing teams may improve the overall performance of a group and the perceived efficacy among its members as they receive performance feedback. Such an expectation is consistent with Prussia and Kinicki's (1996) laboratory findings regarding the impact of feedback on perceptions of efficacy.
We recognize that some jobs may be more conducive to the moderating effects of collective efficacy. Members of groups are characterized by their interdependence (Campion et al., 1993; Shea and Guzzo, 1987), and groups clearly differ as to the degree of task interdependence among its members.
Some groups require greater coordination and synchronization of actions (e.g., nurses) while others allow each group member to work more independently (Shaw, 1981). Environments, such as nursing, that require greater synchronization of individual actions may be more conducive to demonstrating the direct and buffering effects of collective efficacy. To more fully understand the interactions demonstrated in this initial field study, additional research is needed that measures the degree of interdependence among group members and its effects on the susceptibility of an individual's outcomes to differences in perceived collective efficacy.
Limitations of the Current Research
Results of the current investigation need to be viewed in light of this study's limitations. First, the analyses were conducted with one sample employed by one organization. Thus, this study represents a very conservative test of the effects found here. Despite the fact that this task environment appears to be amenable to investigations of this nature, generalization will require an assessment of a wider array of settings. Moreover, the sample size was marginal given the goals of the study. For example, to gain the best representation of the current study's findings, we were required to partition our data into high- and low-collective efficacy groups. An obvious consequence of doing so is the modest number of respondents occupying low (N=30) and high (N=39) collective efficacy subgroups. Clearly, we would have preferred to have more nurses in each cell.
Directions for Future Research
Research building on the results reported here may proceed in a number of directions. At a minimum, researchers may find it useful to address the limitations noted above in settings that contain the full range of group-related performance requirements. Similarly, we employed dependent variables in the current study based on their previously substantiated association with role conflict and other stressors. Given that most research assessing the predictive ability of collective efficacy has used performance as the dependent outcome (Bandura, 1986; Prussia and Kinicki, 1996), employing collective efficacy in this manner seems logical. Finally, the next stage of research development would benefit from looking at the relationships that include collective efficacy longitudinally. It may be that groups that have been functioning for a short time respond differently to contextual factors (e.g., role conflict) when compared to those that have been in existence for a significant longer timeframe. Groups that have devel oped over a period of time may head in one of two directions. Specifically, groups and collective efficacy may evolve in either a positive or negative way. Having a better understanding of the personalities and underlying motivations of actors within the group may provide researchers and practitioners the opportunity to predict when group membership is good and when it is not.
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Table 1 Means, Standard Deviations, Reliability Estimates and Intercorrelations Among Study Variables Variable M SD 1 2 3 1. Age 40.14 8.29 - 2. Gender 1.95 0.52 -.08 - 3. Role Conflict 3.22 1.18 -.08 .10 (.87) 4. Collective Efficacy 4.92 0.68 .07 -.05 -.38 (**) 5. Individual Efficacy 4.92 0.59 .12 .02 -.13 6. Job Satisfaction 5.63 1.14 -.01 -.06 -.49 (**) 7. Turnover Intent 2.39 1.43 -.13 -.02 .50 (**) 8. Exhaustion 2.33 1.15 -.18 (*) .07 .53 (**) Variable 4 5 6 7 1. Age 2. Gender 3. Role Conflict 4. Collective Efficacy (.85) 5. Individual Efficacy .22 (**) (.84) 6. Job Satisfaction .39 (**) .19 (**) (.78) 7. Turnover Intent -.39 (**) -.09 -.63 (**) (.91) 8. Exhaustion -.30 (**) -.26 (**) -.63 (**) .49 (**) Variable 8 1. Age 2. Gender 3. Role Conflict 4. Collective Efficacy 5. Individual Efficacy 6. Job Satisfaction 7. Turnover Intent 8. Exhaustion (.89) N range from 175-188 (*) p<.05 (**) p<.01 (one-tailed test) Notes: Gender variable (1 = male; 2 = female) Reliability estimates shown along diagonal Table 2 Hierarchical Regression Predicting Job Satisfaction, Job Burnout, and Intent to Turnover Job Satisfaction Variables [beta] [R.sup.2] [DELTA][R.sup.2] Step 1: Age -.01 Gender .01 Individual Efficacy .26 (*) Role Conflict (A) -.48 (**) .28 .28 Step 2: Collective Efficacy (B) .34 (**) .31 .03 (**) Step 3: A x B .22 (**) .35 .04 (**) Job Exhaustion Step 1: Age -.02 Gender .01 Individual Efficacy -.37 (**) Role Conflict (A) .49 (**) .34 .34 Step 2: Collective Efficacy (B) -.11 .34 .00 Step 3: A x B -.14 (*) .36 .02 (*) Intent to Turnover Step 1: Age -.02 Gender -.22 Self-efficacy .04 Role Conflict (A) .62 (**) .28 .28 Step 2: Collective Efficacy (B) -.46 (**) .32 .04 (**) Step 3: A x B -.28 (**) .35 .03 (**) Variables F (Step) df Step 1: Age Gender Individual Efficacy Role Conflict (A) 17.27 (**) 4,175 Step 2: Collective Efficacy (B) 16.12 (**) 5,174 Step 3: A x B 15.19 (**) 6,173 Job Exhaustion Step 1: Age Gender Individual Efficacy Role Conflict (A) 22.37 (**) 4,175 Step 2: Collective Efficacy (B) 18.07 (**) 5,174 Step 3: A x B 15.77 (**) 6,173 Intent to Turnover Step 1: Age Gender Self-efficacy Role Conflict (A) 17.04 (**) 4,175 Step 2: Collective Efficacy (B) 16.28 (**) 5,175 Step 3: A x B 15.38 (**) 6,173 N = 180 (*) p < .05. (**) p < .01 (one-tailed test).
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|Author:||Zellars, Kelly L.; Hochwarter, Wayne A.; Perrewe, Pamela L.; Miles, Angela K.; Kiewitz, Christian|
|Publication:||Journal of Managerial Issues|
|Article Type:||Statistical Data Included|
|Date:||Dec 22, 2001|
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