Supervisor and coworker support: a source ...

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Supervisor and coworker support: a source congruence approach to buffering role conflict and physical stressors a

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Margarita Mayo , Juan I. Sanchez , Juan C. Pastor & Alfredo Rodriguez

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IE Business School, Madrid, Spain

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Florida International University, Miami, FL, USA

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Facultad de Psicología, Universidad Complutense de Madrid, Madrid, Spain Published online: 18 Apr 2012.

To cite this article: Margarita Mayo , Juan I. Sanchez , Juan C. Pastor & Alfredo Rodriguez (2012): Supervisor and coworker support: a source congruence approach to buffering role conflict and physical stressors, The International Journal of Human Resource Management, 23:18, 3872-3889 To link to this article: http://dx.doi.org/10.1080/09585192.2012.676930

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The International Journal of Human Resource Management, Vol. 23, No. 18, October 2012, 3872–3889

Supervisor and coworker support: a source congruence approach to buffering role conflict and physical stressors† Margarita Mayoa*, Juan I. Sanchezb, Juan C. Pastora and Alfredo Rodriguezc

Downloaded by [Erasmus University] at 05:10 27 May 2013

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IE Business School, Madrid, Spain; bFlorida International University, Miami, FL, USA; c Facultad de Psicologı´a, Universidad Complutense de Madrid, Madrid, Spain The buffering effects of supervisor support on the stressor – strain relationship have proven elusive in prior research (Beehr, Farmer, Glazer, Gudanowski and Nair (2003), ‘The Enigma of Social Support and Occupational Stress: Source Congruence and Gender Role Effects,’ Journal of Occupational and Health Psychology, 8, 220– 231). We built on emerging work on source congruence and conservation of resource theory to test a series of hypotheses intended to clarify these mixed findings. Using a sample of 768 employees from 45 organizations in North America, results from moderated regression analyses, showed that the effects of supervisor support on the stressor– strain relationship depended on source congruence. In accordance with our predictions, although we found buffering effects for the physical stressors – strain relationship, we found a reverse buffering effect for the role conflict – strain relationship. These differential buffering effects did not emerge when considering coworker support. We discuss the implications of our results for shedding light on the mixed evidence regarding buffering work stressors reported in prior research. Keywords: coworker support; physical stressors; role conflict; source congruence; stress; supervisor support

Introduction Social support has been heralded as a resource that helps employees cope with work stressors, which are the stimuli that induce the stress process and ultimately provoke employee strains (Sosik and Godshalk 2000; Searle, Bright and Bochner 2001; van Dierendonck, Haynes, Borrill and Stride 2004). Theoretical models involving both main and interaction effects have been advanced to explain the role that supervisor support plays in the work stressor – strain relationship (Carlson and Perrewe´ 1999; Cooper, Dewe and O’Driscoll 2001). According to the main effects model, supervisor support directly reduces the level of tension, dissatisfaction and other forms of strain, regardless of the level of stressors. On the other hand, the moderating or buffering hypothesis postulates an interaction effect whereby supervisor support attenuates the impact of stressors on strains. In other words, there should be a strong stressor – strain relationship when supervisor support is low and a weak relationship when supervisor support is high. Unlike the main effects model, which has held up in individual studies (e.g. Blau 1981; Beehr 1985; Ganster, Fusilier and Mayer 1986; Fried and Tiegs 1993) as well as in a meta-analysis of the work stress literature (Viswesvaran, Sanchez and Fisher 1999),

*Corresponding author. Email: [email protected] †

An earlier version of this paper was published in the Best Paper Proceedings of the Academy of Management Conference in 2007.

ISSN 0958-5192 print/ISSN 1466-4399 online q 2012 Taylor & Francis http://dx.doi.org/10.1080/09585192.2012.676930 http://www.tandfonline.com


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evidence of the moderating effects of supervisor support has been, in the words of Beehr et al. (2003, p. 220), ‘rather tenuous, inconsistent and unclear’. That is, although several studies have supported this ‘buffering effect’ suggesting that supervisor support reduces the impact of stressors on strain (e.g. Beehr, King and King 1990; Dorman and Zapf 1999; Sargent and Terry 2000; Beehr et al. 2003), others have either failed to detect it (e.g. Blau 1981; Ganster et al. 1986; Fried and Tiegs 1993; Beehr, Jex, Stacy and Murray 2000) or found rather weak support (Dorman and Zapf 1999). Furthermore, still other studies have reported an intriguing ‘reverse buffering’ effect, which suggested that support may at times exacerbate, rather than weaken, the impact of stressors on strains (e.g. Kobasa and Puccetti 1983; Kaufmann and Beehr 1986; Glaser, Tatum, Nebeker, Sorenson and Aiello 1999; Kickul and Posig 2001; Deelstra et al. 2003). Our study attempts to reconcile these apparent contradictory results by investigating how the congruence between the sources of stressors and of social support makes a difference in determining the ameliorating effect of social support on the relationship between stressors and strain. The notion of source congruence, first advanced by Blau (1981) and later Kaufmann and Beehr (1986), refers to the congruence between sources of the stressor and of social support. In particular, we examine two sources of stressors – role conflict and physical stressors – and two sources of support – supervisor and coworker. From a both theoretical and practical standpoint, it seems important to understand why support from the supervisor, a frequently offered prescription in the practitioners press, does not alleviate employee strain in every situation. Researchers have called for theoretically guided efforts to disentangle the seemingly inconsistent findings concerning the buffering effects of supervisor support (Beehr et al. 2003). Although Cohen and Wills (1985) contended that, to be effective, the kind of support should have a good fit with the focal stressor, the extant research does not seem to provide a convincing, unambiguous set of criteria capable of explaining when and how stressors and support fit each other. Indeed, Viswesvaran, Sanchez and Fisher’s metaanalysis (1999) concluded that the type of support thought to fit the specific type of stressor did not yield larger moderator effects than types of support that did not seemingly fit the stressor. Beehr et al. (2003) also noted that researchers have had a great deal of difficulty predicting whether or not a specific type of support will buffer a given stressor. Along these same lines, de Jonge and Dormann (2006) concluded that ‘inconsistencies in demonstrating interaction effects between stressors and resources represent one of the major threats to prominent models on organizational stress’ (p. 1369). The study described herein relies on emerging work on source congruence and conservation of resource (COR) theory to predict the extent to which the buffering effect of supervisor support depends on the congruence between the resource (e.g. supervisor support) and the source of the specific stressor. In particular, we examined a work stressor that is likely to be congruent with or emanate from primarily the supervisor (e.g. role conflict), together with a stressor (e.g. physical stressors), which tends to be incongruent with the supervisor because it typically falls beyond the supervisor’s control. Then, we compared the results of supervisor support with those of coworker support to provide a more robust test of the source congruence hypothesis. An additional strength of our study is that, in contrast to prior studies of buffering effects, it employed a relatively large sample size that afforded us sufficient statistical power to detect even small stressor by support interactions. Theoretical background Social support generally refers to the individual belief that help would be available from other people in difficult situations (Cobb 1976). Support may come from different sources.


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There are work-related and non-work related sources of support, such as supervisors, coworkers and family (Halbesleben 2006). Here, we focus on work-related sources of support because they are more closely related to the stressors of interest – work conflict and poor physical conditions. Family and non-work related sources might be most relevant when considering buffering stressors such as work– family conflict. Traditionally, it was thought that social support, independently of the source, was a strong remedy against job stressors. However, Blau (1981) was the first to suggest that sources of support may need to be independent of sources of stressors because support coming from the same source that is provoking the stressor might be awkward and unproductive. Similarly, Kaufmann and Beehr (1986) also called for further examination of the congruence between the source of the stressor and the source of support as an explanation for the contradictory buffering effects of social support. Beehr et al. (2003) further explicated the theoretical rationale behind this source congruence hypothesis by arguing that, when both support and stressors originate in the same source (e.g. the supervisor), two conflicting or dissonant cognitions may arise about this source, hence augmenting rather than buffering the impact of stressors on strains. However, Beehr et al. (2003) did not find consistent support for the source congruence hypothesis, which had anticipated that such congruence would be more harmful than helpful, which led them to call for additional research on alternative forms of support –stressor congruence. In line with this call for further research, recent revisions of the COR theory (Hobfoll 2001; Hobfoll and Kay 2007) focusing on employee appraisals of resources may help us sort out the boundary conditions under which supervisor support has a buffering effect from those under which it has a reverse buffering effect. The basic tenet of COR theory (Hobfoll 1989, 1998; Hobfoll and Shirom 2000) is that strain is most likely to occur when (a) there is a perceived threat to one’s resources, (b) there is an actual resource loss or (c) the anticipated return on investment of one’s resources does not materialize. This theory proposes that people seek to acquire and maintain resources and stress arises because there is a threat of a loss of resources, an actual loss in resources or lack of an expected gain in resources. The term ‘resources’ refers to objects, conditions, personal characteristics and energies that are valued by the individual (Hobfoll 1989). Thus, stressors threaten valuable employee resources such as status, position, self-esteem and energy. Hobfoll (1998) designated social support as one of the most important resources for dealing with stressors, since it can both widen one’s pool of available resources and can replace or reinforce other resources that have been lacking. That is, supervisor support may promote a positive sense of self and a sense of security that in turn facilitates the preservation of these and other valued resources, thereby preventing strain despite the threat represented by work stressors (Hobfoll 1989). COR theory also incorporates the notion of resource appraisal (Hobfoll 2001; Hobfoll and Kay 2007), suggesting that employees assess the extent to which the resource (e.g. source of support) matches the stressor. Thus, for supervisor support to have a buffering effect on the stressor – strain relationship, it needs to be perceived by the subordinate as fitting the specific type of stressor. In particular, job-related strain involves both mental and physical health over a relative long period of time (6 or 12 months). Following previous studies on strain (e.g. Spreitzer, Kizilos and Nason 1997; Sprigg, Jackson and Parker 2000), we consider two aspects of job-related strain, namely job-related tension or anxiety and medical physical symptoms. To test this argument regarding fit, we focused on two stressors that have been traditionally associated with employee strain, namely role conflict and physical working conditions. On the one hand, role conflict, which has received a great deal of attention for over four decades (e.g. Katz and Kahn 1966; Rizzo, House and Lirtzman 1970; Perrewe et al. 2004), occurs when individuals experience two or more sets of incompatible role


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demands so that fulfilling one impedes the fulfilment of the other(s). Research has shown that role conflict is closely related to the supervisor (O’Driscoll and Beehr 1994) and it is associated with a number of dysfunctional outcomes, such as job dissatisfaction and psychological strains (e.g. Jackson and Schuler 1985). On the other hand, poor working conditions (Sutton and Rafaeli 1987; McCoy and Evans 2005), such as extreme temperatures, inappropriate lighting, noise, crowding, and lack of space and privacy, according to ergonomics research, are the result of occupational and organizational design, which are typically beyond the control of the supervisor (Humphrey, Nahrgang and Morgeson 2007; Dierdorff and Ellington 2008; Fritz and Sonnentag 2009). We have focused on these two specific resources because they are viewed to have their origin at differing sources, hence allowing us to test the source congruence hypothesis. In particular, we expect role conflict to be originated from the supervisor, whereas physical stressor would be originated from the organization. Thus, role conflict is source-congruent with supervisor support, but physical stressors are not. Hypotheses Because one of the supervisor’s main responsibilities is to shape the employee’s role expectations, employees are therefore likely to perceive their supervisor as the main source of conflicting role demands (O’Driscoll and Beehr 1994). This line of thinking is consistent with the fact that ‘the boss’ dominates anecdotal reports of complaints about conflicting work assignments (e.g. Kellerman 2004). Thus, because role conflict and supervisor support are likely to emanate from the same source (i.e. the supervisor), supervisor support seems particularly prone to magnify the negative impact of this stressor (e.g. Rizzo, House and Lirtman 1970; Perrewe et al. 2004). According to Kaufmann and Beehr (1986), when a supervisor who is also the source of stress approaches employees to offer his/her support, ‘even this “friendly” approach may be experienced as stressful’ (p. 524). Under such circumstances, supervisor support may be perceived as inconsistent and insincere (Kickul and Posig 2001), and it may even provoke self-perceptions of incompetence in the subordinate (Blaine, Crocker and Major 1995). Thus, we propose the following source congruence hypothesis between supervisor support and role conflict. Hypothesis 1:

Supervisor support will have a reverse buffering effect on the relationship between role conflict and strain so that role conflict will be more strongly associated with strains (i.e. job tension and medical symptoms) when supervisor support is high than when it is low.

In contrast, when stressors are typically attributed to the nature of the job, as it is the case for poor physical working conditions (Sutton and Rafaeli 1987; McCoy and Evans 2005; Dierdorff and Ellington 2008), employees attribute less responsibility to supervisors for the hardships of the physical environment. That is, even though managers may influence employees’ individual working conditions through differential task assignments, they are unlikely to control the fundamental physical conditions that define the job. Also, supervisors know about these conditions and, therefore, may provide tips and support to cope with this type of physical stressor (Beehr et al. 2003). Thus, we propose a source incongruence hypothesis between supervisor support and physical stressors. Hypothesis 2:

Supervisor support will have a buffering effect on the relationship between physical stressors and strain so that physical stressors will be less strongly associated with strains (job tension and medical symptoms) when supervisor support is high than when it is low.


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To provide a more comprehensive test of our theory, we compared the impact of supervisor support with that of coworker support. Our reasoning for including coworker support was twofold. First, support from coworkers is an important source of social support for employees and therefore it is often included in this literature (Viswesvaran et al. 1999). Second, although coworkers are certainly important role senders and can influence the speed and coordination of work tasks, they do not typically have the authority to shape employee work assignments in the manner that supervisors do. Therefore, because employees are unlikely to attribute stressors such as role conflict or working conditions to coworkers, one should not expect a reverse buffering effect for coworkers’ support. Instead, supportive coworkers may indeed buffer the effects of role conflict on strain because they help employees vent their frustrations, provide fresh ideas that help employees cope with conflicting role demands and coach employees to develop new coping mechanisms. In line with these arguments, Beehr et al. (2003) found that coworker support moderated the relationship between workload and psychological strain. Thus, we expect a buffering effect. Hypothesis 3:

Coworker support will have a buffering effect on the relationship between role conflict and strain so that role conflict will be less strongly associated with strain (i.e. job tension and medical symptoms) when coworker support is high than when it is low.

In addition, support from coworkers should also help neutralize the negative consequences of physical stressors. Even though coworkers might influence working conditions, they are hardly responsible for the general physical conditions at work, such as the size of work stations, amount of storage space, visual privacy, air quality and temperature. Coworkers can certainly be a source of noise and distraction (Oldham and Rotchford 1983), but even if that is the case, work settings in which people encounter frequent contact with others facilitate communication and interpersonal bonds (Oldham and Brass 1979), which help reduce strain. For instance, there is ample evidence that frequent communication with peers is related to higher levels of job satisfaction (Brass, Galaskiewicz, Greve and Tsai 2004; Balkundi and Harrison 2006). Furthermore, a supportive group of coworkers should help alleviate physical stressors because coworkers share a common understanding of the same physical environment. Thus, we expect the following buffering effect. Hypothesis 4:

Coworker support will have a buffering effect on the relationship between physical stressors and strain so that physical stressors will be less strongly associated with strain (i.e. job tension and medical symptoms) when coworker support is high than when it is low.

Method Participants The data for this study were collected from 45 service and manufacturing organizations of various sizes in the northeastern USA and Canada. In total, 768 completed surveys were returned out of the 1291 distributed to employees at all job levels, yielding a response rate of 59%. About half of participants were male (55.6%). Thirty percent were between 20 and 30 years of age, and 27% were between 30 and 40. Twenty-seven percent had an average tenure with their organization of between 2 and 5 years, and 41% had their current supervisors for the last 2– 5 years.


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Data collection procedure After initial contacts (via students enrolled in an MBA program at a large university in the northeastern USA), requests to participate in a large-scale study were sent to supervisors at 45 companies. These supervisors were asked to request their subordinates to participate in the study and distribute the questionnaires. Completed surveys were returned in a sealed envelope to the researchers. Employees received an explanation of the objectives of the study and instructions for filling out the survey at a meeting of their work group held during working hours. The work groups were defined as those employees reporting to the same supervisor. Following this introduction, participants were asked to participate in the study voluntarily by completing the survey, and they were also assured of the anonymity of their responses. The purpose and procedure of the study were stated as follows: We are interested in learning more about the job situations of people working in various industries located within the Western New York and Southern Ontario Region. This survey focuses on three areas: (1) the potentially stressful aspects of your job, (2) your own sense of health and well-being, and (3) your supervisor’s style of interacting with you. To make things easier and less time consuming, you will be asked to respond to a series of standard questions and statements concerning each of these three areas. In all cases, you need only write in the number which comes closest to providing the most accurate picture of you, your job and its context. Rest assured that your responses will remain completely confidential and anonymous. Your completed survey will be turned over to researchers at the University for analyses. No one will ever be able to connect your name with your responses.

We used a survey design because we were interested in targeting attitudinal outcomes across a large sample of organizations in order to increase the generalizability of our results. In addition, a survey design allowed us to collect data via well-tested scales in the literature that provide reliable and valid measures of the theoretical constructs. Measures Social support. We assessed social support via the social support scale developed by Caplan, Cobb, French, Van Harrison and Pinneau (1975). Items asked participants to evaluate the extent to which their supervisor and coworkers provided social support. The four items are: (1) How much does each of these people go out of their way to do things to make your life easier for you? (2) How easy is it to talk with each of the following people? (3) How much can each of these people be relied on when things get tough at work? And (4) How much is each of the following people willing to listen to your personal problems? For each question, participants evaluated the extent to which their supervisor and their coworkers provided support, using a 5-point Likert scale ranging from ‘not at all’ (1) to ‘almost always’ (5). Each set of four items was summed into a global index of support for each of the two sources. Cronbach’s a reliabilities were 0.87 and 0.82 for supervisor and coworker support, respectively. Role conflict. We assessed role conflict through the stress diagnostic survey developed by Ivancevich and Matteson (1980). The five items included in this scale are as follows: (1) I work on unnecessary tasks or projects, (2) I get caught in the middle between my supervisor and my subordinates, (3) The formal chain of command is not adhered to, (4) I do things on the job that are accepted by one person and not by others and (5) I receive conflicting requests from two or more people. Respondents indicated the frequency of this stressor using a 5-point scale ranging from ‘never’ (1) to ‘frequently if not always’ (5). The scale’s Cronbach’s a was 0.73.


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Physical stressors. We measured physical stressors using Sutton and Rafaeli’s (1987) 18-item scale, which assesses the degree to which employees perceive their working conditions (such as temperature, quality of light and space) as adequate. Answers ranged from ‘very inadequate’ (1) to ‘very adequate’ (5). Cronbach’s a was 0.87. Strain. Two forms of strain were assessed, namely job tension and medical symptoms. Job tension was measured using the seven-item scale included in House and Rizzo’s (1972) anxiety –stress questionnaire. This scale measures individuals’ feelings of irritation and tension (e.g. ‘My job tends to directly affect my health’, ‘I work under a great deal of tension’). The Cronbach’s a for the scale in this study was 0.85. To assess the degree to which employees experienced medical symptoms, we provided participants with the list of physical ailments in the Quick and Quick’s (1984) stress survey, which includes headaches, nervousness, poor appetite, constipation, restlessness, cold sweats, heart beating hard and hands trembling. Participants reported the frequency with which they had experienced these medical symptoms in the past 12 months using a 5-point scale ranging from ‘never’ (1) to ‘frequently if not always’ (5). The Cronbach’s a for the scale in this study was 0.80. Control variables. We controlled for employees’ age, gender, years of experience at the company, years worked with the supervisor and dispositional optimism. Age and years of experience at the company might provide employees with solid and stable social support networks, including the relationship with their supervisors. For example, age has been positively related to job and mental well-being (Siu, Spector, Cooper and Donald 2001). Gender is another variable that has been related to stress and social support. Men and women often choose different career paths (Stroth and O’Reilly 1999) that lead to different kinds of work stressors (Alvesson and Billing 1997) and develop different social support networks (Ibarra 1992, 1993; McPherson, Smith-Lovin and Cook 2001). Similarly, we expect the number of years working with the supervisor to have a positive effect on the quality of the relationship, as interpersonal problems between leaders and followers will result in attrition. Finally, we included dispositional optimism to control for the potential effect of negative affectivity (Watson, Pennebaker and Folger 1987). Dispositional optimism has been found to buffer the relationship between stressors and strain (Scheier and Carver 1985, 1992), and it has also shown a positive relationship with social support (Brissette, Scheier and Carver 2002). We measured dispositional optimism using the nine-item life orientation test (Scheier and Carver 1985). Each item is scored on a 5-point scale ranging from ‘not at all true’ (1) to ‘frequently if not always true’ (5), and the scale yielded a Cronbach’s a of 0.68. Measurement model To evaluate the extent to which our findings were influenced by common method variance, we followed the procedure recommended by Podsakoff, MacKenzie, Lee, and Podsakoff (2003) and employed by Ahuja, Chudoba, Kacmar, McKnight and George (2007) and by Carlson and Kacmar (2000). Following this approach, we estimated three models: (1) a null measurement model, (2) a multifactor trait measurement model with the proposed latent constructs and (3) a trait measurement model with an additional method factor. If a common method effect existed, model 3 would fit the data significantly better than model 2. Then we would need to determine the amount of variance in the model contributed by the single method factor. To do that, we computed the average variance extracted (AVE) for the latent constructs against the method factor. It has been argued that, to rule out the presence of pervasive method variance, the



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variance explained by the method factor should be less than 25% of the total variance (Williams, Cote and Buckley 1989). Three models were estimated through confirmatory factor analysis (CFA) using AMOS 7.0 (Arbuckle 2006). The results of the CFA were as follows: null model, x 2 ¼ 9125, df ¼ 1540, p , 0.001; Tucker – Lewis index, TLI ¼ 0.38, comparative fit index, CFI ¼ 0.40, root mean square error of approximation, RMSEA ¼ 0.10; multifactor trait model with eight factors, x 2 ¼ 3342, df ¼ 1488, p , 0.001; TLI ¼ 0.90, CFI ¼ 0.91, RMSEA ¼ 0.05; and multifactor trait model with a single method factor, x 2 ¼ 3123, df ¼ 1480, p , 0.001; TLI ¼ 0.92, CFI ¼ 0.93, RMSEA ¼ 0.04. The eight-factor model provided a good fit to the data, with RMSEA scores below 0.06, whereas TLI and CFI were above 0.90 (Bentler and Bonnet 1980). The loadings from model 3 were then used to compute the AVE for each latent construct, including the method factor. The results indicated that, although model 3 fitted the data better than model 2 (Dx 2 ¼ 219, df ¼ 8), the method factor accounted for only 16% of the total variance – less than the 25% cut-off recommended by Williams et al. (1989). Thus, we concluded that common method variance did not significantly contaminate the results. Data analyses To test the hypotheses, we used moderated hierarchical regression analyses computed in accordance with the procedure delineated by Aiken and West (1991). To test the ‘reverse buffering effect’, we first computed the interaction term or cross-product between supervisor support and role conflict. We expected that the sign of this interaction would be positive when predicting strain, such that the relationship between role conflict and strain would be stronger under high supervisor support. In contrast, to test the ‘buffering effect’, we computed three interaction or cross-product terms: supervisor support and physical stressors, coworker support and role conflict, and coworkers support and physical stressors. According to our hypotheses, we expected a negative sign of these interactions when predicting strain. The statistical significance of the interaction or moderation effect was assessed after controlling for all main effects. Control variables (demographic variables, optimism) were entered first in the models, followed by the main effects of physical stressors and role conflict. The two sources of social support were entered in the next step, and the interaction terms in the final step. Results Descriptive statistics Descriptive statistics, reliabilities and correlations for all variables are reported in Table 1. The bivariate correlations indicated that the relationships between sources of social support and strain were negative. Supervisor support had negative and statistically significant correlations with job tension (r ¼ 2 0.27, p , 0.01) and medical symptoms (r ¼ 2 0.27, p , 0.01). The same correlation pattern emerged for coworker support, although correlations with job tension (r ¼ 2 0.21, p , 0.01) and medical symptoms (r ¼ 2 0.21, p , 0.01) were smaller. Role conflict had positive and statistically significant correlations with job tension (r ¼ 0.46, p , 0.01) and medical symptoms (r ¼ 0.36, p , 0.01). Physical stressors had positive and statistically significant correlations with job tension (r ¼ 0.26, p , 0.01) and medical symptoms (r ¼ 0.24, p , 0.01). In addition, optimism had a negative correlation with job tension (r ¼ 2 0.25, p , 0.01) and medical symptoms (r ¼ 2 0.36, p , 0.01).

2.24 1.44 2.93 1.88 3.58 2.71 2.13 3.42 3.56 2.21 1.80

1. Age 2. Gender (1 m; 2 f) 3. Years at the company 4. Years with supervisor 5. Optimism 6. Physical stressors 7. Role conflict 8. Supervisory support 9. Coworkers support 10. Job tension 11. Medical symptoms

1.09 0.50 1.40 0.92 0.66 0.66 0.72 1.02 0.86 0.80 0.59

SD – 0.01 0.61 0.32 20.14 20.11 20.06 0.09 0.09 0.07 20.14

1 – 2 0.12 0.10 2 0.07 0.08 2 0.06 2 0.01 0.04 0.03 0.17

2

– 0.32 0.09 2 0.07 0.04 2 0.00 0.03 0.18 2 0.04

3

– 0.02 2 0.04 2 0.02 0.08 0.10 0.09 2 0.08

4

(0.68) 2 0.18 2 0.20 0.22 0.20 2 0.25 2 0.36

5

(0.87) 0.33 20.29 20.27 0.26 0.24

6

(0.73) 20.36 20.25 0.46 0.36

7

(0.87) 0.46 2 0.27 2 0.27

8

(0.82) 20.21 20.21

9

(0.85) 0.52

10

(0.80)

11

Note. Coefficient a’s appear along the diagonal in parentheses. Correlations greater than 0.07 are significant at p , 0.05; correlations greater than 0.10 are significant at ,0.01. Age, 1 ¼ 20 or less, 2 ¼ 30s, 3 ¼ 40s, 4 ¼ 50s, 5 ¼ 60s or more; gender, 1 ¼ male, 2 ¼ female; years at the company and years worked with supervisor, 1 ¼ less than 2, 2 ¼ 2–5, 3 ¼ 6 –10, 4 ¼ 11–15, 5 ¼ more than 15.

M

Variables

Table 1. Descriptive statistics, reliability and correlations among study variables.


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Tests of hypotheses Table 2 shows that the interaction terms predicted incremental variance beyond main effects for the two dependent variables (job tension and medical symptoms). To minimize the threat of multicollinearity, we centered all independent variables before entering them into the regression equations (Aiken and West 1991). No evidence of multicollinearity was detected, according to Kleinbaum, Kupper and Mueller’s (1988) criteria for variance inflation factor (VIF) and tolerance criteria. Also, the Durbin – Watson statistics for all analyses indicated that errors were not correlated (Ryan 1997). Buffering effects of supervisor support. Hypothesis 1 predicted a reverse buffering effect of supervisor support on the relationship between role conflict and strain. The supervisor support £ role conflict interaction emerged as a positive and statistically significant predictor of job tension (b ¼ 0.12, p , 0.01) and medical symptoms (b ¼ 0.07, p , 0.05). To further examine whether the nature of this interaction conformed to the reverse buffering effects of supervisor support predicted by our hypotheses, we plotted the interactions using Aiken and West’s (1991) procedures. Figure 1(a), (b) shows that, as Hypothesis 1 predicted, the association of role conflict with both job tension and medical symptoms was stronger when supervisory support was high than when it was low. In contrast, Hypothesis 2 predicted a positive buffering effect for supervisor support when the stressor is the physical environment. As we expected, the unfavorable or reverse buffering effect of supervisor support was limited to the experience of role conflict and did not apply to the effects of physical stressors on strain. Indeed, there was a significant buffering effect of supervisor support on the relationship between physical stressors and medical symptoms (b ¼ 2 0.08, p , 0.05, Figure 1(c)). That is, the negative consequences of physical stressors on medical symptoms were weaker when supervisory support was high than when it was low. Although statistically non-significant, a similar trend was detected for job tension. Buffering effects of coworker support. Hypotheses 3 and 4 predicted that support from coworkers would buffer the negative effects of both role conflict and physical stressors. Table 2 shows that the coworker support £ role conflict interaction term had a negative and statistically significant relationship with job tension (b ¼ 2 0.10, p , 0.05) and medical symptoms (b ¼ 2 0.09, p , 0.05). Again, we further examined the direction of the moderating effects by plotting the interactions using Aiken and West’s (1991) procedures. As we expected, role conflict had significantly weaker associations with job tension (Figure 2(a)) and medical symptoms (Figure 2(b)) when employees reported high rather than low coworker support, thereby supporting Hypothesis 3. However, the coworker support £ physical stressors interaction did not reach statistical significance predicting either job tension or medical symptoms. These results failed to support Hypothesis 4. We repeated the regression analyses and examined the moderating effect of optimism on the relationship between role conflict and strain after controlling for social support. The results failed to yield statistically significant interactions between role conflict and optimism or between physical stressors and optimism, hence strengthening the argument that social support, and not optimism, accounted for the buffering effects between work stressors and strain. A post hoc test of stressor –support source congruence COR theory underscores the importance of source congruence between stressors and support (Hobfoll 2001). We have argued that role conflict is more likely to be attributed to

0.28**

0.03 0.02 0.16** 0.05 20.16** 0.39** 0.11**

1

0.29** 0.01*

20.07* 20.04

2 0.06* 2 0.06* 0.12** 20.02 20.10** 20.05 0.31** 0.02**

0.03 0.02 0.16** 0.05 20.15** 0.37** 0.09**

3

0.03 0.02 0.15** 0.05 2 0.15** 0.37** 0.10**

2

Job tension

0.28**

2 0.11** 0.20** 0.06 2 0.04 2 0.28** 0.26** 0.07*

1

0.29** 0.01**

20.05 20.06*

20.10** 0.20** 0.06 20.03 20.27** 0.24** 0.06*

2

Medical symptoms

0.07* 2 0.08* 2 0.09** 2 0.02 0.30** 0.01*

2 0.07* 2 0.04

2 0.10** 0.20** 0.07* 2 0.02 2 0.27** 0.24** 0.06*

3

Note. Age, 1 ¼ 20 or less, 2 ¼ 30s, 3 ¼ 40s, 4 ¼ 50s, 5 ¼ 60s or more; gender, 1 ¼ male, 2 ¼ female; years at the company and years worked with supervisor, 1 ¼ less than 2, 2 ¼ 2– 5, 3 ¼ 6–10, 4 ¼ 11–15, 5 ¼ more than 15. *p , 0.05; **p , 0.01.

1. Controls Age Gender Years at the company Years with supervisor Optimism Role conflict Physical stressors 2. Support Supervisor support Coworkers support 3. Interactions Supervisor support £ role conflict Supervisor support £ physical stressors Coworkers support £ role conflict Coworkers support £ physical stressors R2 DR 2

Steps and variables

Table 2. Results of hierarchical regression analyses on strain.


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The International Journal of Human Resource Management (a)

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0.8 0.6

Job Tension

0.4 0.2 0 –0.2 –0.4 –0.6

Low Supervisor Support High Supervisor Support

–0.8 Role Conflict 0.8

Medical Symptoms

0.6 0.4 0.2 0 –0.2 –0.4 –0.6


–0.8 Role Conflict (c)

0.8 0.6

Medical Symptoms


(b)

0.4 0.2 0 –0.2 –0.4 –0.6


–0.8 Physical Stressors

Figure 1. Reverse buffering effects of supervisory support for (a) role conflict predicting job tension, (b) role conflict predicting medical symptoms and (c) physical stressors predicting medical symptoms.

supervisors than to peers, customers and other organizational stakeholders. To test the assumption that employees are more likely to perceive supervisors as the source of their role conflict, but not as the source of physical stressors, we conducted a separate supplementary study using a different sample. Participants used a 5-point scale ranging from 1 (not at all) to 5 (almost always) to answer the following six questions: ‘To what extent do you find inadequate physical conditions at work emanating from your (1) supervisors, (2) coworkers and (3) organization?’ and ‘To what extent do you find role

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0.8 0.6

Job Tension

0.4 0.2 0 –0.2 –0.4

Low Coworker Support

–0.6

High Coworker Support

–0.8 Role Conflict 0.8 0.6 Medical Symptoms


(b)

0.4 0.2 0 –0.2 –0.4 Low Coworker Support

–0.6

High Coworker Support

–0.8 Role Conflict

Figure 2. Buffering effects of coworker support for role conflict predicting (a) job tension and (b) medical symptoms.

conflict at work emanating from your (1) supervisors, (2) coworkers and (3) organization?’ A sample of 131 employed individuals enrolled in an executive MBA program in Spain completed the questionnaire. The average age of sample members was 32, the average work experience was 9 years and 74% of this sample was male. As we expected, role conflict was primarily attributed to the supervisor, and not to the coworkers (Msupervisor ¼ 3.37 vs. Mcoworker ¼ 1.57, d ¼ 1.80; t(130) ¼ 24.14, p , 0.001) or to the organization (Msupervisor ¼ 3.37 vs. Morganization ¼ 2.24, d ¼ 1.13; t(130) ¼ 12.79, p , 0.001). Also as we expected, physical stressors were attributed primarily to the organization, and not to the supervisors (Morganization ¼ 2.55 vs. Msupervisor ¼ 1.36, d ¼ 1.19; t(130) ¼ 12.59, p , 0.001) or to the coworkers (Morganization ¼ 2.55 vs. Mcoworker ¼ 1.19, d ¼ 1.36; t(130) ¼ 12.17, p , 0.001). These results are consistent with our assumption that role conflict is source congruent primarily with supervisor rather than coworker support. Discussion Contributions to theory This study contributes to clarify the mixed evidence concerning the buffering and reverse buffering effects of supervisor support in regard to the impact of work stressors on employee strain. The results are largely consistent with our source congruence hypotheses, suggesting that supervisor support may be beneficial when it counteracts stressors that are



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originated outside of the supervisor’s realm, such as physical stressors. In contrast, supervisor support may increase subordinates’ strains when stressors deemed to be originated in the supervisor, such as role conflict. Our finding concerning the simultaneous occurrence of opposite buffering effects of supervisor support is noteworthy, because such a finding has proven elusive in prior studies. In what was possibly the first study explicitly designed to identify the conditions under which reverse buffering occurs. Beehr et al. (2003) found no support for the hypothesis that a reverse buffering effect occurs when the source of supervisor support coincides with the source of the stressor. Beehr et al. (2003) speculated that the lack of empirical support might have been due, in part, to a small sample size. They also noted that there are multiple interpretations of the concept of source congruence, and called for additional research on alternative forms of fit between work stressors and social support. Based on the COR framework, we found support for the notion that role conflict and physical conditions are two stressors likely to have differential effects when interacting with supervisor support. Our results hint that although supervisor support alleviates medical symptoms originated by physical stressors, it magnifies the unfavorable effects of role conflict on both job tension and medical symptoms. An alternative causal explanation for the reverse buffering effect of social support has been that stressors lead to strain, which in turn leads employees (as proactive agents) to seek social support (Kaufmann and Beehr 1986). We addressed this issue by examining the effects of support from coworkers. If employees actively seek support when stressors are related to strain, then we should find reverse buffering effects for both supervisor and coworker support. However, we found that only supervisor support exacerbated the association between role conflict and strain. This finding supports the source congruence explanation. Lastly, our results indicated that supervisor support had stronger direct associations with strains than did coworker support: correlations between supervisor support and strains (job tension and medical symptoms were 2 0.27 and 2 0.27 vs. correlations of 2 0.21, 2 0.21, between coworker support and the same strains). The magnitude of these differences is similar to that reported in Viswesvaran et al.’s (1999) meta-analysis. When compared to the relatively modest effect sizes associated with both positive and negative buffering uncovered here and elsewhere (Viswesvaran et al. (1999) reported similar DR 2 ranging from 0.01 to 0.03), these correlations suggest that supervisor support is still a more powerful reducer of employee strain than coworker support is, despite the former’s potential for reverse buffering. Limitations and future research In spite of the large sample size and the high response rate, our design had some limitations. First, associations among self-reported variables might have been inflated by common method variance, but our CFAs suggested that such inflation was minimal in our case. In addition, nonlinear effects such as the interactions that captured the buffering effects are hardly attributable to method bias (Aiken and West 1991). Second, our crosssectional design precluded cause-and-effect determinations, and future longitudinal and experimental research may help clarify the causal direction of these findings. More nuanced relationships between stressors and support should be examined in future research. For instance, Harris and Kacmar (2006) found a U-shape curvilinear relationship between the quality of the relationship between leaders and followers so that employees in high-quality leader member exchange (LMX) relationships with their supervisors

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paradoxically experienced more stress than did their colleagues in moderate-quality LMX relationships. Finally, we examined solely self-reported measures of strain. Our reliance on self-reports undoubtedly facilitated gathering data from a large sample, thus increasing the statistical power needed to detect the kind of interaction or buffering effects that we sought. Even though there is a well-documented empirical association between psychological and physiological measures of strains (Fox, Dwyer and Ganster 1993; Sprigg, Stride, Wall, Holman and Smith 2007), a broader set of strain measures that also encompasses directly measurable physiological outcomes such as cortisol levels, muscular disorders and blood pressure should be included in future studies.


Implications and conclusions The most straightforward implication of our study is that managers should be aware of the sources of stressors impinging on their subordinates before they possibly overwhelm them with their support. For this reason, it is important that they develop observation and diagnostic skills to assess the origin of stressors affecting their subordinates, and then offer the kind of support that is most likely to match the stressor. When the source of employees’ stressors is largely unrelated to their supervisors (e.g. physical conditions), supervisors may be in the best position of truly alleviating the negative consequences of stressors. However, if the source of stressors is perceived to be linked to the supervisor, as it appears to be the case of role conflict, supervisor support may make matters worse. Employees should also remain aware of instances when ‘talking to the boss’ may not be the best approach to reduce tension (Harris and Kacmar 2006). Our results suggest that this scenario is likely when the source of stressors is also the supervisor, who may end up aggravating the stressor – strain relationship. In short, while supervisor support has undeniable beneficial effects to alleviate employee strain, it also has the potential for making matters worse when support comes from the same source as stressor at hand. We hope that our findings stimulate further research on the boundary conditions influencing the extent to which social support and other resources adequately match work stressors (Beehr et al. 2003; de Jonge and Dormann 2006). Acknowledgement This research was partially funded by a research grant from the Ministry of Science and Innovation of Spain # ECO2009-12952 to Margarita Mayo.

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