Customer-Related Social Stressors and Burnout

Christian Dormann and Dieter ZapfJohann Wolfgang Goethe-University

Although almost all literature on burnout implicitly assumes that burnout is primarily caused bystressful employee–customer interactions, only a few studies have addressed this empirically. Aprincipal-components analysis of a newly developed instrument assessing various forms ofcustomer-related social stressors (CSS) in 3 different service jobs (N � 591) revealed 4 themesof CSS: disproportionate customer expectations, customer verbal aggression, disliked customers,and ambiguous customer expectations. These 4 CSS predict burnout beyond a variety of controlvariables. Contrary to other predictors of burnout analyzed in previous studies, the amount ofvariance explained in exhaustion (14%) by the 4 CSS scales is not higher than for personalaccomplishment (14%) and is considerably lower than for depersonalization (23%).

Service jobs in Western countries have become themajor employment sector (e.g., Paoli, 1997; Zeithaml& Bitner, 2000). A unique feature of service jobs isthat employees interact with customers. Many em-ployees apply for a service job because of their socialmotives and values (e.g., Judge & Bretz, 1992; Rav-lin & Meglino, 1987). In terms of conservation-of-resources (COR) theory (Hobfoll, 1989), the oppor-tunity to serve customers represents a resource forservice employees. However, interacting with cus-tomers is not always a pleasure. Rather, it may alsobe related to dissatisfaction and may cause psycho-logical strain. Surprisingly, a look at the literature onstress at work reveals that interactions with custom-ers are frequently not investigated as sources of stress(Dormann & Zapf, 1999; Frone, 2000; Grandey,Dickter, & Sin, 2002; Grandey, Tam, & Brauburger,2002; Spector & Jex, 1998). There is, however, theconcept of emotional labor or emotion work, whichhas recently been related to burnout and which de-scribes stressful aspects of service encounters. In thepresent study, we argue that this concept is important,but not sufficient to explain all stressful aspects in-herent in service provider–customer interactions. Onthe basis of COR theory (Hobfoll, 1989) and various

social psychological theories, we suggest other po-tentially stressful aspects that may occur in em-ployee–customer interactions. On the basis of thesetheoretical considerations, we describe the develop-ment of a new instrument, thecustomer-related so-cial stressors (CSS) scales, and we report first resultssupporting the construct validity of this newly devel-oped instrument.

Social Causes of Burnout

If one is interested in stress elicited in employee–customer interactions, the concept of burnout has tobe considered. Burnout was first investigated in thehelping professions (Leiter & Maslach, 1988;Maslach, 1982; Schaufeli & Enzmann, 1998;Schaufeli, Maslach, & Marek, 1993) but has beenextended to other service professions as well as tojobs not related to service (Schaufeli, Leiter,Maslach, & Jackson, 1996). It is argued that thepersonal relationships with patients, clients, or chil-dren are very demanding and require a high amountof empathy and emotional involvement. This is usu-ally combined with a high aspiration level to buildpersonal relationships and to avoid treating otherpeople like objects. Burnout is considered an indica-tion that employees are no longer able to adequatelymanage their interaction with clients.

Most authors acknowledge that burnout occurs injobs dealing with a variety of customers and clients.It is usually argued that burnout results from chronicexposure to specific conditions among workers “whodo ‘people-work’ of some kind” (Maslach & Jackson,1981, p. 99). “Despite similar noxious effects as otherstress reactions, the unique feature of burnout is thatits stress results from thesocial interactions between

Christian Dormann and Dieter Zapf, Department of Psy-chology, Johann Wolfgang Goethe-University, Frankfurt,Germany.

We are indebted to Karen Scholz, Janine Banat, andNikolai Egold, who collected the data. We also thankMyriam Bechtoldt, Claudia Gross, and Christina Werner fora critical reading of an earlier version of this article.

Correspondence concerning this article should be ad-dressed to Christian Dormann, Johann Wolfgang Goethe-University, Department of Psychology, Mertonstrasse 17,D-60054 Frankfurt/M, Germany. E-mail: Dormann@psych.uni-frankfurt.de

Journal of Occupational Health Psychology2004, Vol. 9, No. 1, 61–82

Copyright 2004 by the Educational Publishing Foundation1076-8998/04/$12.00 DOI: 10.1037/1076-8998.9.1.61

61

helpers and their recipients” (Maslach, 1982, p. 3).Indeed, burnout is thought “to represent aunique[italics added] response to frequent and intense cli-ent–patient interactions” (Lee & Ashforth, 1996, p.123). In line with these notions, most studies onburnout have focused on human service providers.For example, approximately 80% of the studies con-sidered in the meta-analysis of burnout by Lee andAshforth sampled human service providers, and mostof the remaining studies sampled supervisors andmanagers of such service providers.

It seems as if researchers have taken for grantedthat the specific nature of people-work is dealt withimplicitly if people-workers are investigated. But,surprisingly, only few studies analyzed whether it is,indeed, the customer who causes burnout. Some stud-ies investigated whether the structure of interactionswith customers (e.g., the number or length of inter-actions) or the content of the interaction (e.g., theseverity of clients’ problems to be solved) is relatedto burnout. The effects emerging in these studieswere often smaller compared with other stressors,such as time pressure (see Schaufeli & Enzmann,1998). Schaufeli and Enzmann concluded that burn-out isnot particularly related to stressful social inter-actions at work.

A central aim of this article is to revise this con-clusion. Because the number of studies dealing withCSS is still limited, we start by reviewing the litera-ture on stressful social interactions at work at abroader level, including interactions with colleaguesand supervisors. We try to identify several streams oftheoretical reasoning used in previous research, andwe analyze whether these can be adapted to the issueof CSS.

Existing Evidence of the Stressfulness ofSocial Interactions at Work

According to psychological theories of stress (e.g.,Lazarus & Folkman, 1984), speaking ofsocial stres-sors means speaking of a class of characteristics,situations, episodes, or behaviors that are related topsychological or physical strain and that are some-how social in nature. This is in contrast to stressorsrooted in the environment or in organizational andtask structures.

Social interactions at work may have positive andnegative effects. The opportunity to collaborate withcustomers, to solve their problems, and to fulfill theirdesires provides service employees with several re-sources. This may not be limited to people with

strong social motives. Cooperation and co-produc-tion (Schneider & Bowen, 1995; Zeithaml & Bitner,2000) with customers may foster feelings of socialcompanionship and relatedness. Solving other peo-ple’s problems may lead to a sense of competence,accomplishment, and growth. Grateful customersmay cause feelings of self-esteem. Thus, several as-pects of service work represent resources, which arevaluable for the employees according to the CORtheory (Hobfoll, 1989). The same argument appliesfor nonservice jobs that involve social contacts withsupervisors and colleagues.

However, employees may perceive a loss in theseresources when certain events occur. Such eventsmay be triggered by particular kinds of behaviors inemployees’ social work environment. Stress theories(e.g., Hobfoll, 2001; Lazarus, 1999) converge on theassumption that stress occurs if something importantis threatened. In COR theory (Hobfoll, 1989), threatis equated with a loss of resources. For instance, ifthe frequency of positive external evaluations (i.e., bysupervisors, colleagues, customers) decreases andnegative evaluations increase, that is, if positive re-inforcement through the social environment is lost,stress reactions should occur. Key resources dis-cussed by Hobfoll (2001) are self-efficacy, optimism,self-esteem, degree of goal pursuit, and social sup-port. Service work offers several opportunities toachieve these resources. For example, self-efficacymay be enhanced by solving a challenging problemfor a client, optimism may develop through accumu-lating knowledge that challenging problems can besolved, self-esteem may be enhanced if customersacknowledge an employee’s contribution to a chal-lenging problem-solving process, goal pursuit mayincrease through repeated experiences of its positiveoutcomes, and perceptions of social support are morelikely to evolve if there is good reason to collaboratewith supervisors or colleagues, such as a challengingproblem of a client. However, for example, if cus-tomer expectations disproportionately rise and canrarely be satisfied, employees’ self-efficacy may bereduced, their optimism may diminish, customers’anger may replace former gratitude thereby loweringemployees’ self-esteem, employees’ goal pursuitmay give way to rumination, and support may with-draw because it is constantly overtaxed. Thus, interms of COR theory, CSS are those kinds of cus-tomer expectations, service experiences, and behav-iors that cause a net loss in employees’ resources.

COR theory is not very specific in the processesand mechanisms leading to the loss of resources.Therefore, to develop an instrument on CSS, our

62 DORMANN AND ZAPF

main strategy was to review concepts and instru-ments used to describe potentially stressful interac-tions at work with supervisors and colleagues and, ifpossible, apply them to employee–customer interac-tions. Basically, we identified three groups of relatedconcepts: (a) social conflicts; (b) injustice, unfairtreatment, and nonreciprocal behavior; and (c) anti-social behavior at work.

Social Conflicts at Work

There are studies that use conflict theory as a basisfor social stressors at work (e.g., Appelberg, Ro-manov, Honkasalo, & Koskenvuo, 1991; Frese &Zapf, 1987; Spector, 1987). For example, Schwartzand Stone (1993) carried out a diary study and foundthat conflicts and problems with supervisors, col-leagues, and clients or customers counted for 15% ofthe most stressful situations of the day. Studies usingconflict-based measures found substantial relationswith a variety of strain measures (e.g., Appelberg etal., 1991; Beehr, Drexler, & Faulkner, 1997; de Dreu,van Dierendonck, & de Best-Waldhober, 2003;Frone, 2000; Spector, 1987; Spector, Dwyer, & Jex,1988; Zapf & Frese, 1991). Dormann and Zapf(1999, 2002) were able to demonstrate causal effectsof social stressors on strains in longitudinal analyses.In their studies, the social conflicts investigated in-cluded, for example, a supervisor’s assignment ofunpleasant tasks and being held responsible for themistakes of others.

Because many service employees spend consider-ably more time with customers or clients than withtheir supervisors or colleagues, we propose that underthese circumstances, conflicts with customers are atleast as important as conflicts with supervisors orcolleagues (see also Grandey et al., 2002). Whereasthere is a continuous relationship with a limited num-ber of supervisors and colleagues, this is not so forcustomers. Employees may have to deal with a largenumber of clients or customers every day, for exam-ple, in the case of call center work (Dorman &Zijlstra, in press; Holman, 2003; Isic, Dormann, &Zapf, 1999). Therefore, overall, interactions withcustomers may be much more frequent comparedwith interactions with supervisors or colleagues.

Unjust, Unfair, and Nonreciprocal Behavior

Some recent studies analyzed unfair or unjust be-havior as a source of stress (Donovan, Drasgow, &Munson, 1998; Tepper, 2000). Equity theory (Ad-ams, 1965), for example, addresses the fact that in-

puts and outputs in social interactions should bebalanced. Reciprocity theories (e.g., Buunk &Schaufeli, 1999) come to similar conclusions.Schaufeli and his colleagues (e.g., Bakker, Schaufeli,Sixma, Bosveld, & van Dierendonck, 2000;Schaufeli et al., 1996) repeatedly demonstrated that alack of organizational reciprocity contributed toburnout. Nonreciprocal situations are usually experi-enced as unfair. Donovan et al. (1998) developed ascale of unfair treatment in organizations and showedthat unfair treatment was related to dissatisfaction. InTepper’s (2000) study, unfair supervisor behaviorwas related to anxiety, depression, and emotionalexhaustion.

Similar effects can be expected with regard tocustomer-related reciprocity. The studies by Bakkeret al. (2000) and Schaufeli et al. (1996) showed thathigh demands of patients lead to a perceived lack ofpatient-related reciprocity (e.g., little appreciation forthe effort and time invested), which was related toburnout. On the basis of these theoretical conceptsand the existing evidence, we assume that if custom-ers try to get an advantage, if they express expecta-tions that exceed what the service providers think isstill acceptable and that are difficult to reject becauseof the obligation to be customer-oriented, a stressfulsituation is created.

Antisocial Behavior at Work

A third approach refers to a range of studies onantisocial behavior at work that have studied similarphenomena, under a variety of labels (Keashly &Jagatic, 2003), such as workplace aggression (R. A.Baron & Neuman, 1996, 1998), emotional abuse(Keashly, 1998), social incivility (Andersson & Pear-son, 1999), workplace bullying (Einarsen, Hoel,Zapf, & Cooper, 2003), or mobbing (Zapf, Knorz, &Kulla, 1996). Antisocial behaviors can be classifiedinto various forms: (a) psychological and physical,(b) direct and indirect forms of harmful behaviors,and (c) intended and not intended or ambiguousbehaviors (see R. A. Baron & Neumann, 1996, 1998).We discuss these concepts in terms of how they canbe applied to employee–customer interactions.

Psychological and physical behaviors. Somestudies report physical violence of customers or cli-ents (e.g., R. A. Baron & Neuman, 1996; Budd,Arvey, & Lawless, 1996). However, this form ofviolence is usually specific for certain organizationsand occupations and is relatively rare (Budd et al.,1996; Leather, Beale, Lawrence, Brady, & Cox,1999). Therefore, we did not consider physical vio-

63CUSTOMER-RELATED SOCIAL STRESSORS

lence from customers as a potential CSS applicable toall service sectors in the present study, although weacknowledge the importance of physical aggressionin some service sectors. However, psychologicalforms of aggression have to be considered.

Direct and indirect behaviors. Theories onworkplace aggression (e.g., R. A. Baron & Neuman,1996) usually differentiate between direct (physicalviolence, threat of violence, verbal aggression) andindirect psychological aggression. Indirect formssuch as spreading rumors, social exclusion, or delib-erately withholding information, which have beeninvestigated in studies on aggression, seemed to usless meaningful in employee–customer interactionsbecause of the limited contact. However, verbal ag-gression as a form of direct psychological aggression,such as yelling at the service provider or makingsarcastic or offensive remarks, can be applied to theemployee–customer interaction, and it should beconsidered as a potential CSS (see also Grandey etal., 2002).

A quantitative study on the relation between cus-tomer behavior and employee responses was carriedout by Grandey et al. (2002) concurrently with ourresearch. In particular, they investigated customerverbal abuse among call center employees. Theymeasured the frequency of abusive customer callsand how stressful these calls were (i.e., primary ap-praisal in terms of intensity) by using one item re-spectively. The appraised stressfulness of abusivecalls correlated with negative affect at work and jobsatisfaction. The frequency of abusive calls had noeffect. This study, however, suffered from the weak-ness that only one-item measures were applied thatwere strictly tailored for use in call centers.

Intended and nonintended, ambiguous behaviors.Definitions of aggression usually imply the intent toharm another person. As such, aggression theoriescan be directly related to the concept of primaryappraisal as threat, harm, or loss (e.g., Lazarus &Folkman, 1984). There are, however, some forms ofantisocial behavior, such as workplace bullying (Ein-arsen et al., 2003) or incivility, which do not presup-pose conscious intentions for negative social behav-iors but which use similar measurement instruments.In the case of workplace bullying, these behaviors areconsidered stressful because they are part of an en-during process of conflict escalation (Zapf & Gross,2001). Concepts of workplace incivility (Cortina,Magley, Hunter Williams, & Day Langhout, 2001;Duffy, Ganster, & Pagon, 2002; Glomb, 2002) havebeen linked to the concept of daily hassles (e.g.,Kanner, Coyne, Schaefer, & Lazarus, 1981),

which—if accumulating over time—lead to psycho-logical strain. It can be assumed that these behaviorsare stressful because they threaten one’s self-esteem.Thus, the literature on threatened self-esteem may beconsidered here (Baumeister, Smart, & Boden,1996). Self-esteem, which is an important resourceaccording to Hobfoll (1989), is threatened if positiveself-evaluations are questioned by negative externalevaluations. Self-esteem may be at risk if customersquestion one’s authority, autonomy, power, influ-ence, and personal freedom. This may include, forinstance, customers who question the employee’sknowledge or competence, telling him or her in detailhow to accomplish the job, or who emphasize statusdifferences.

In sum, we applied four concepts to the serviceinteraction that describe aspects of social behavior(conflicts, aggressive, uncivil, and unfair behavior)that are threatening basic resources according toCOR theory and that are, therefore, assumed to bestressful for the service provider.

Further Evidence for the Stressfulness of CSS

In the previous sections, we identified four streamsof theoretical reasoning on the stressfulness of socialevents (social conflicts, unfair behavior, intended di-rect verbal aggression, and uncivil behavior with noor ambiguous intent to harm but that negatively af-fects self-esteem) and allocated existing evidence onCSS according to these theories. There is furtherevidence on CSS that does not unambiguously fit intothese categories. The main reason is that some studiesused ambiguous measurements. For instance, an itemaddressing the incidence of “problem customers”leaves it unclear if the problem refers to conflicts,aggression, incivility, or injustice. Nevertheless,these studies are valuable because they demonstratethat some kinds of CSS are stressful, and we brieflyreview them here.

Bitner, Booms, and Mohr (1994) found that 22%of negative events reported occurred when dealingwith “problem customers.” Koeske and Koeske(1989) found that strain was related to “difficult”client interactions. In a diary study of working stu-dents, Grandey et al. (2002) found that of the anger-provoking events encountered, 43% referred to “mis-treatment” by customers. In a study on call centers byIsic and Zapf (2002), 43% of the call center agentsreported that they had to deal with “angry” customerson a daily basis. Schonfeld (1992) analyzed “epi-sodic,” student-related stressors and found them to berelated to the development of depressive symptoms

64 DORMANN AND ZAPF

in a longitudinal study. Finally, Lim and Yuen(1998), in referring to Dhaliwal (1993), noted thatmuch of nurses’ dissatisfaction arises from unreason-able demands by patients and their relatives. Nursesreported that they were not treated with respect andthat patients urged nurses to comply with their wisheswithout taking work-related constraints into account.Lim and Yuen (1998, p. 275) used items such as “Theexpectations of patients and their relatives on nursingservices are unrealistically high,” “Patients/relativesdo not treat nurses with respect,” and “Patients/rela-tives are generally not appreciative of what nurses dofor them.” A composite scale correlated fairly highwith job satisfaction (–.45) and moderately with or-ganizational commitment (–.35) and job-induced ten-sion (.31). This study is interesting because the itemsused to assess patient-related stressors avoidedphrases addressing primary appraisal processes. Theitems referred to behavior of patients toward the jobincumbents in general, instead of the appraisal ofhow patients treat the respondent. This strategy ap-proximates an “objective” job analysis. Nevertheless,the correlations obtained were quite high. A similarapproach was followed in the present study.

Although the previously reviewed literature sug-gests that CSS might be more important thanSchaufeli and Enzmann (1998) concluded in theirreview on burnout, the existing empirical evidence isvery limited. There is, however, research on emo-tional labor or emotion work and burnout. This re-search recently has investigated aspects of emotionregulation during social interactions at work and isdescribed next.

Emotional Labor as a Source of Burnout

In recent years, research on emotional labor oremotion work and its effect on burnout has attractedincreased attention (e.g., Abraham, 1998; Brother-idge & Grandey, 2001; Dormann, Zapf, & Isic, 2002;Grandey, 2000; Morris & Feldman, 1996; Schaubro-eck & Jones, 2000; Zapf, Vogt, Seifert, Mertini, &Isic, 1999). Building on the work of Goffman (1959),Hochschild (1983) argued that people in social inter-actions tend to play roles and attempt to create certainimpressions, including the display of normativelyappropriate emotional behavior. Morris and Feldman(1996, p. 987) defined emotional labor as the “effort,planning, and control needed to express organization-ally desired emotions duringinterpersonal transac-tions [italics added].” That is, organizations developso-called display rules to show certain emotions to-ward customers, which may be an explicit or implicit

part of the organizational culture. The service pro-viders are expected to behave according to theserules. Emotion work has been investigated across awide variety of service occupations, including flightattendants, cashiers, bank clerks, and call center em-ployees. In these studies, emotional labor conceptu-ally represents the independent variable and burnoutrepresents the dependent variable in human servicework.

The key component of emotional labor with regardto negative health outcomes in general and burnout inparticular is emotional dissonance (e.g., Grandey,2000; Hochschild, 1983; Morris & Feldman, 1996;Zapf, 2002). Emotional dissonance describes the dis-crepancy between genuinely felt emotions and thoseemotions that an employee is required to display in aservice setting. In his review of 12 studies, Zapffound an average correlation of .32 between emo-tional dissonance and emotional exhaustion. Theconcept of emotional dissonance addresses withoutdoubt an important aspect of service work.

However, we believe that concepts such as emo-tional dissonance and other aspects of emotional la-bor are not fully sufficient to explain all the stressfulaspects occurring in service encounters. Basically,the frequency and intensity of emotional dissonancedepend on three antecedent variables (Zapf, 2002):(a) the existence of display rules prescribing a certainemotional expression (mostly the expression of pos-itive emotions), (b) the frequency (and duration) ofinteractions with customers in which the display ruleshave to be applied, and (c) the absolute and relativefrequency of negative social interactions.

Various reasons have been suggested for emo-tional dissonance causing psychological strain.Hochschild (1983) suggested that the pure frequencyand length of required emotional expression will, atsome point, overtax the individual’s abilities to showthese emotions. The individual will respond withincreased effort, which will lead to increased physi-ological activation. In the long run, this will causepsychological strain. Grandey (2003) suggested thatthe requirement to both downregulate existing nega-tive emotions and upregulate organizationally desiredpositive emotions represents a threat to employees’emotional autonomy. The COR theory predicts thatthis will cause psychological strain (Hobfoll, 1989).In addition, the regulation of emotion requires self-control strength, which is a limited resource (Mu-raven & Baumeister, 2000). Thus, the negative con-sequence of emotion work also comes along throughthe overtaxation (loss) of this particular resource.

There are, however, various reasons why emo-

65CUSTOMER-RELATED SOCIAL STRESSORS

tional dissonance does not cover all stressful aspectsof employee–customer interactions. First, if a cus-tomer behaves aggressively, a service provider maybe allowed to express negative emotions (e.g., flightattendants). Therefore, no or little emotional disso-nance should occur in this situation. Nevertheless, heor she may appraise the situation as threatening his orher self-esteem, thus threatening resources accordingto COR theory (Hobfoll, 1989). Second, the existingconcepts and measures of emotional dissonance as-sess how often emotional dissonance occurs (e.g.,Brotheridge & Lee, 1998; Zapf et al., 1999), but theyare not able to discriminate between variousqualita-tive levels of negative social interaction. We suggestthat emotional dissonance is a very sensitive measurefor negative aspects of a social situation; that is, itmay occur even in the case of subtle events. Forexample, one customer may behave arrogantly inmimics and gestures without saying much, and an-other customer may verbally attack the service pro-vider. We posit that emotional dissonance measuresare not able to adequately address these differences.

However, we suggest that emotional dissonancecovers aspects that are not addressed by conflict oraggression theory based measures. An example is thecase of a nurse who, after 14 hours work, is fatiguedand not able to express positive emotions anymore,but who neither has a conflict nor is negativelytreated by the patient in terms of aggressive, uncivil,or unfair behavior.

Research Questions

Because we were not aware of an instrument thatcovers the described kinds of potentially stressfulcustomer-related events, we developed an instrumentthat focused on CSS at work. This article has threeaims. The first goal is to demonstrate the validity ofa newly developed measure of CSS in terms of fac-torial structure and criterion relationships. In thisstudy we pursue an exploratory strategy because it isdifficult to predict how many aspects of CSS will bedistinguished empirically. This is so because the the-oretical concepts previously described do not refer toindependent phenomena and show substantial empir-ical correlations (e.g., Cortina et al., 2001:r � –.59between incivility and fair treatment; Tepper, 2000:r � –.53 between abusive supervision and interac-tional justice). Thus, we cannot predict the exactnumber of factors. Ideally, we would expect a four-factor solution, because of the four theoreticalsources of item generation (social conflicts, intendeddirect [verbal] aggression, unfair behavior, and un-

civil behavior). However, our first hypothesis is thatmore than one factor would emerge (Hypothesis 1).Our second hypothesis is that the different CSSscales are not redundant in the prediction of burnout(Hypothesis 2).

Our third hypothesis is related to the relationshipsbetween CSS and emotional labor. Based on ourprevious arguments, we supposed that both sets ofconcepts partly overlap but also independently con-tribute to burnout. We propose that emotional disso-nance will partly mediate the effect of CSS on burn-out. This is so because CSS qualify a socialinteraction as negative. In the majority of all cases,service providers have to show positive emotions.Therefore, positive emotions have to be shown in anegative social situation, which will lead to emo-tional dissonance. However, because employees aresometimes allowed to show adequate negative emo-tions or show them although they are expected not todo so (emotional deviation; Rafaeli & Sutton, 1990),and because we assume that emotional dissonancemeasures do not adequately reflect the various qual-ities of negative social interactions (from subtle un-intended forms of behaviors to escalated conflicts andoutbursts of verbal aggression), we hypothesize thatthere will also remain direct effects of CSS on burn-out although the effect sizes may be reduced.

Given the difficulty to confirm mediating effects incross-sectional research, we decided to compare thefollowing models. The first model treated CSS andemotional dissonance as independent although corre-lated predictors of burnout. In the second model,emotional dissonance mediated the effect of CSS onburnout. In the third model, CSS represented themediating variables of emotional dissonance on burn-out. This model is theoretically less plausible, al-though one could argue that perceiving emotionaldissonance would reduce CSS because the serviceproviders should behave more positively toward cus-tomers by strategies of deep acting (strategies towork on one’s inner feelings so that they match theexpressed feelings; see Grandey, 2000; Hochschild,1983; Zapf, 2002). The third model allows us toanalyze whether there is a unique contribution ofemotional dissonance in the prediction of burnoutthat could not be explained by CSS. We propose thatthere will be such a unique contribution becauseemotional dissonance can occur in otherwise positiveor neutral social interactions due to the fact that thefrequency and duration of interactions with custom-ers overtax the service providers’ ability to show thedesired emotions. In sum, we hypothesize that CSS(Hypothesis 3a) and emotional dissonance (Hypoth-

66 DORMANN AND ZAPF

esis 3b) independently contribute to burnout but thatemotional dissonance partly mediates the relationbetween CSS and burnout (Hypothesis 3c).

Finally, we analyze whether CSS provide addedvalue in the examination of burnout. The respectivehypothesis was that CSS would still have additionalexplanatory power after other sources of burnoutwere controlled for in hierarchical regression analy-sis. This means that the possibility has to be rejectedthat variance in burnout, as explained by the CSSscales, can also be explained by variables that havealready been established in the prediction of burnout.Third-variable explanations also need to be ruled out.For example, it might be possible that third variables,such as gender, are common causes of CSS andburnout and should thus be controlled for. Moreover,selection or socialization effects may also lead tospurious relations among the CSS scales and burnout(see Semmer & Schallberger, 1996). These effectscan partly be controlled for by means of dummy-coded variables representing the samples studied inthis article. Finally, work-related variables might leadto spurious relationships between the CSS scales andburnout. To control for confounding effects of work-related variables, we also control for these in hierar-chical regression analysis. In sum, we propose thatCSS would explain burnout even if all these potentialconfounding and or mediating variables were con-trolled for (Hypothesis 4).

Method

Sample

The participants were sampled from three different occu-pations. Our aim was not to be as representative as possiblebecause this would have required a random sample of aconsiderable number of service occupations. However, wewanted toexclude examples of CSS that are unlikely toapply to all service occupations. For example, we excludedpotential CSS such as conflicts between different customerswaiting in line, customers writing annoying letters, or be-haviors of people with mental disabilities. For this reason,we did not include human service jobs such as nurses orpsychotherapists. In addition, the employees should have atleast a moderate amount of contact to each customer, so thatcertain stressful events have a certain likelihood to occur.

The present sample (N � 591) was composed of threedifferent occupations (flight attendants, travel agency em-ployees, and sales clerks in shoe stores). The data weregathered by independent research groups; the survey of theflight attendants (n � 312) was carried out by Karen Scholz(2001) as part of her PhD dissertation. Student teams gath-ered the other samples as part of a university seminarsupervised by Christian Dormann.

The flight attendants represent a convenience sample.The questionnaires were first distributed in packages to

several flight attendants personally known to Karen Scholz,and then they were distributed further. Two student researchteams gathered data in travel agencies using slightly differ-ent questionnaires with a few nonoverlapping items. Theshoe stores (n � 88) and travel agencies (Sample 1:n �132; Sample 2:n � 59) were randomly selected in thetowns of Frankfurt and Darmstadt in Germany. Once thestore managers agreed to participate, they were providedwith the appropriate number of questionnaires. The ques-tionnaires were collected in the stores and picked up byresearch team members. With the exception of the flightattendants, each participant was allowed to complete thequestionnaire during work hours.

We do not have determinate information on the rejectionrates; however, about 55% of the distributed questionnaireswere returned. On average, the participants were 32.13years old (SD � 9.52). Seventy-eight percent were female.

Because there were slightly different research focuses inthe different research teams, not all variables analyzed in thepresent article were gathered in all samples. With only oneexception (see below), however, there are virtually no miss-ing data for the central variables of the present article (i.e.,CSS and burnout).

Measures

CSS. Most items of the CSS measures were developedafter a couple of semistructured interviews held with em-ployees in shoe stores, travel agencies, and flight attendants.Further items were derived from customer-related state-ments of flight attendants, which were found in the work ofHochschild (1983) and Nerdinger (1994), for example. Wethereby tried to make sure that the items addressed conflicts,aggressive, unfair, and uncivil behavior. Six further itemswere derived from a scale, which measures social stressorsfrom supervisors and colleagues, developed by Frese andZapf (1987). This scale was useful because it also consistedof items referring to conflicts, aggressive, and unfair behav-ior. For instance, the item “My supervisor pushes all thetime” was changed to “Our customers always push us.” Theterms “me” and “my” were replaced by “us” and “our,”respectively, to obtain measures that reflect what all em-ployees in similar positions experience and not only what aparticular person experiences. This was to minimize theamount of subjective bias (Frese & Zapf, 1988). All answerswere made on a 5-point scale ranging from 1� not at alltrue to 5 � absolutely true. The results of the principal-components analysis and the descriptive indices of the fourextracted scales can be found in the Results section, alongwith the verbatim wording of each item.

Emotional dissonance was measured using the FrankfurtEmotion Work Scales developed by Zapf et al. (1999). Thisscale consists of five items referring to the display of emo-tions not actually felt, as well as to the suppression of feltemotions (e.g., “‘A’ can openly display his/her feelingstowards clients—‘B’ has to display feelings toward clientswhich do not reflect his/her true feelings. What is your joblike?”). Responses were made on a 5-point scale rangingfrom 1 � very seldom/never to 5 � very often with theexception of the item that used the “A versus B”-formatshown above. In these instances, the responses ranged from1 � exactly like “A” to 5 � exactly like “B.” Cronbach’salpha of this scale was .81.

67CUSTOMER-RELATED SOCIAL STRESSORS

Job stressors and resources. Most job stressors wereassessed using the German instrument for stress-orientedjob analysis ISTA [Instrument zur StressbezogenenTatigkeitsanalyse] (Semmer, Zapf, & Dunckel, 1995, 1999;Zapf, Bechtoldt, & Dormann, in press), which is a validatedand well-established German measure. Five scales weretaken from the ISTA instrument.Control at work wasmeasured by five items (e.g., “Considering your work ingeneral, how much room do you have for your own deci-sions?”) The items required a response on a 5-point scalethat ranged from 1� very few to 5 � very much. Cron-bach’s alpha for control at work was .79.Timing controlwas measured with five items (e.g., “Do you decide on yourown as to how long you work on a particular task?”). Theresponse format varied to some extent, but most itemsexhibited the same response scale as the items for control atwork. Cronbach’s alpha for timing control was .75.Con-centration demands were measured with five items (e.g.,“Do you have to remember information for short periods oftime that is hard to keep in mind?”), which required aresponse on a 5-point scale that ranged from 1� veryseldom/never to 5 � very often. Cronbach’s alpha for con-centration demands was .74.Time pressure was measuredwith five items (e.g., “How often are you under time pres-sure?”), which required a response on a 5-point scale thatranged from 1� very seldom/never to 5 � very often.Cronbach’s alpha for time pressure was .82.Organizationalproblems were measured with five items (e.g., “‘A’ hasdocuments and information that are always correct andup-to-date—‘B’ has documents and information that areoften incomplete and out of date. What is your job like?”).All items used the “A versus B” format with responsesranging from 1� exactly like “A” to 5 � exactly like “B.”Cronbach’s alpha for organizational problems was .73.

In addition to scales taken from the ISTA instrument, wemeasuredsocial stressors in interactions with supervisorsand colleagues using the scale developed by Frese and Zapf(1987). The validity of this scale has been established inseveral previous studies (e.g., Dormann & Zapf, 1999,2002; Frese & Zapf, 1987). The scale comprises 8 items(e.g., “My supervisor always assigns the pleasant tasks tocertain people”), which required a response on a 5-pointscale that ranged from 1� does not apply at all to 5 �applies completely. When factor analyzed, the items exhib-ited a clear one-factor solution, with the first factor explain-ing 34.90% of the variance. It was important to control forthis scale because 6 out of the 8 items were adapted tomeasure CSS (together with an additional 22 items), possi-bly leading to a partial conceptual overlap. Cronbach’salpha for social stressors was .80.

Social support by supervisors andsocial support by col-leagues were measured using Frese’s (1989) German adap-tation of the social support scales developed by House andCaplan (Caplan, Cobb, French, Harrison, & Pinneau, 1975;House, n.d.). Only four out of the five original items wereused. The questions (“How much can each of these peoplebe relied upon when things get tough at work?” “Howwilling to listen to your work-related problems is each of thefollowing people?” “How helpful is each of the followingpeople to you to get your job done?” and “How willing tolisten to your personal problems is each of the followingpeople?”) had to be rated on a 4-point scale ranging from1 � not at all to 4 � completely with respect to supervisors

and colleagues, respectively. Cronbach’s alphas were .89for supervisor support and .88 for colleague support.

Burnout. Burnout was measured using the German ver-sion (Bussing & Perrar, 1992) of the Maslach BurnoutInventory (MBI; Maslach, Jackson, & Leiter, 1996). TheMBI comprises three scales: emotional exhaustion, deper-sonalization, and personal accomplishment. All responseswere made on the frequency scale ranging from 1� neverto 7 � every day. Emotional exhaustion was measured withnine items and yielded a Cronbach’s alpha of .85. Deper-sonalization was measured using five items (� � .77), andpersonal accomplishment was measured with eight items(� � .78).

Treatment of Missing Values

Among the scales used to measure traditional work stres-sors and resources, the questionnaire given to the flightattendants did not include the scales for organizationalproblems, social stressors by supervisors and colleagues,social support by supervisors, and social support by col-leagues. In addition, a small subset of items to measure CSSwas not applied in 29.55% of the questionnaires distributedto travel agency employees (Sample 2). These items orscales were not included in each questionnaire because ofconsiderations of length. This represents a planned missingdata design (Graham, Hofer, & MacKinnon, 1996). Themissing data in such circumstances are said to be missingcompletely at random (MCAR; see Little & Rubin, 1989).Overall, there were 8.45% missing data in the present study.Of these, 7.55% were MCAR because they were excludedin the respective sample. The remaining 0.90% missingvalues were due to unknown reasons, some of them perhapsnonrandom. If data are MCAR, the expectation maximiza-tion (EM) approach to missing data is highly recommended(Little & Rubin, 1989). It leads to less biased and moreefficient parameter estimates when compared with othermissing data strategies. The EM approach was applied usingthe NORM computer program (see Schafer, 1997). In plainwords, the EM algorithm produces iteratively refined esti-mates of variances and covariances, which were used as thebasis for subsequent analyses. NORM was applied twice,once for the items used to measure CSS to factor analyzethem, and once for all scales (including those based on thefactor analysis) to conduct regression analyses of the burn-out symptoms. Through the application of NORM, themaximum sample size (N � 591) equals the effective sam-ple size for each analysis.

Regression analyses were based on the corrected vari-ance–covariance matrix and were carried out using LISREL8 and maximum likelihood estimation (Jo¨reskog & So¨rbom,1993). To test the significance of increments inR, we usedF tests. BecauseF tests of increments inR2 are not auto-matically provided by LISREL, we computed them manu-ally using the formula:Fchange� (N – �p – 1) * �R2 / (�p* (1 – R2)), with df1 � �p and df 2 � N – p – 1 (N �sample size,�p � number of additional predictors added inthe current regression step,�R2 � increment inR2 betweenthe current and the preceding regression step,R2 � R2

obtained in the current regression step, andp � number ofpredictors in the current regression step).

68 DORMANN AND ZAPF

Results

First, the items used to measure CSS were factoranalyzed. Visual inspection of the scree plot of apreliminary principal-components analysis using thevarimax rotation revealed that there was a bend afterthe first factor and after the fourth factor. In addition,the eigenvalues of the fifth and sixth factor were onlymarginally above 1.0. Therefore, the extraction waslimited to four factors. The varimax-rotated solutionis shown in Table 1. The four factors accounted for49.67% of the total variance.1 It should be noted thatfactor loadings lower than .40 in absolute value arenot shown for reasons of clarity.

Although confirmatory factor analysis (CFA)should not be used toconfirm an exploratory factorsolution of the same data, CFA can be used to showthat a four-factor solution is statistically superior to aone-factor solution. A comparison showed that thefour-factor solution fitted much better than the one-

factor model (�df � 6, ��2 � 421.61,p � .01). Fitindices addressing whether a model provides a par-simonious fit to the data also revealed that the four-factor solution is better: Its parsimonious normed fitindex was .71 (compared with .64 for the one-factormodel), and its parsimonious goodness of fit indexwas .71 compared with .68. The absolute fit was farfrom being perfect, however; this was due to a largenumber of error autocorrelations that one is usuallyunable to specify a priori.

The first factor contained customers’ attitudes andbehaviors challenging what is considered reasonableand acceptable from the service provider’s point ofview (disproportionate customer expectations). Wedecided to exclude items from subsequently com-puted scales that had loadings below .50 or cross-

1 The intercorrelations of the items are available fromChristian Dormann.

Table 1Factor Loadings of the Items Used to Measure Customer-Related Social Stressors

Item 1 2 3 4

SC17 Some customers always demand special treatment .73SC15a Some customers think they are more important than others .68 .40SC19 Our customers do not recognize when we are very busy .67SC21 Some customers ask us to do things they could do by themselves .67SC16a Some customers are “know it alls” .66 .46SC18 Customers vent their bad mood out on us .61SC31 Our customers do not understand that we have to comply with certain rules .57SC20 Complaining without reason is common among our customers .56SC33 Our customers’ demands are often exorbitant .55SC30 Our customers are pressed for time .55SC10a If an error occurs, the customers always blame us—never themselves .43SC27 Customers often shout at us .73SC24 Customers personally attack us verbally .67SC26 Customers are always complaining about us .60SC28a Our customers have no manners .46 .59SC03 Customers get angry at us even over minor matters .54SC01 Some customers argue all the time .52SC04a The customers always criticize us—they never see what is well done .48SC23a Customers lack trust in our work .48SC05 One has to work with hostile customers .72SC07 One has to work together with customers who have no sense of humor .64SC02 Some customers are unpleasant people .61SC06 Our work rhythm is steadily interrupted by certain customers .51SC08a Our customers always push us .45SC22 Customers’ wishes are often contradictory .70SC13 It is not clear what customers request from us .68SC12 It is difficult to make arrangements with customers .62SC14 Customers’ instructions can complicate our work .61

Variance explained 31.94 6.53 6.00 5.12a These items were excluded from subsequently computed scales.

69CUSTOMER-RELATED SOCIAL STRESSORS

loadings above .40 in absolute value to increase dis-criminant validity. The two items SC15 and SC16,which reflect arrogant customer behavior, were ex-cluded from the scale because they had strong cross-loadings on the third factor. The items SC10 andSC28 were excluded from the scale because theirloadings were below the criterion of .50. The scalebased on the remaining eight items had a very goodinternal consistency (Cronbach’s� � .86).

Factor 2 was characterized by loadings of itemsreflecting verbal aggression by customers as well ascustomer quarrels and criticisms (customer verbalaggression). One item was excluded from the subse-quently computed scale because of a salient cross-loading on Factor 1 (SC28) and one item was ex-cluded because of its loading, which was below .50(SC23). The scale based on the remaining five itemsdisplayed good internal consistency (Cronbach’s� �.72).

Four items had factor loadings of .50 or higher onFactor 3. These items reflect aversions employeeshave to customers (disliked customers). The fifth item(SC8) was excluded from the scale because its load-ing was below .50. The four-item scale had a satis-factory internal consistency (Cronbach’s� � .67).

Finally, Factor 4 was characterized by items con-sisting of customer expectations that are ambiguous

and unclear (ambiguous customer expectations). Allfour items were retained, and the scale had a satis-factory internal consistency (Cronbach’s� � .68). Insummary, based on the items of the present study,CSS seem to be comprised of four main factors:disproportionate customer expectations, customerverbal aggression, disliked customers, and ambigu-ous customer expectations.

The correlations between these four scales, to-gether with the other study variables, are shown inTable 2. The correlations among the four CSS scaleswere between moderate and high, ranging from .34(disliked customers with ambiguous customer expec-tations) to .58 (disproportionate customer expecta-tions with customer verbal aggression). The correla-tional pattern supports Hypothesis 1 in that fournonredundant CSS scales were identified in thisstudy.

The correlations between the CSS scales and burn-out provide first evidence for the validity of the CSSscales. The correlations between emotional exhaus-tion and the four new scales were between .27 and.30, and only time pressure (.31) and organizationalproblems (.21) reached correlations of similarstrength. A more differentiated picture emerged forthe correlations of the four CSS scales and deperson-alization, which ranged from .20 (ambiguous cus-

Table 2Descriptive Statistics of Study Variables

Variable M SD No. 1 2 3 4 5 6

1. Dummy travel agency (S1) 0.22 0.42 1 —2. Dummy flight attendant 0.53 0.50 1 �.57 —3. Dummy shoe store 0.15 0.36 1 �.22 �.44 —4. Age 32.14 9.52 1 .05 �.18 .10 —5. Gender 1.22 0.43 1 .01 �.11 �.12 .21 —6. Control 3.48 0.81 5 .12 �.26 .03 .18 .11 —7. Timing control 3.70 0.89 5 �.30 .40 �.35 .08 .10 .388. Concentration necessities 3.10 0.76 5 .20 .01�.36 .08 .15 �.059. Time pressure 3.56 0.84 5 �.07 .36 �.44 �.08 .06 .01

10. Organizational problems 2.19 0.62 5 .01 .00�.12 �.08 .09 �.0611. Social stressors 1.90 0.53 8 �.33 .37 �.06 �.16 �.05 �.1612. Supervisor support 3.14 0.70 4 .07 .00�.03 �.01 �.01 .1013. Colleague support 3.22 0.63 4 .08 .00�.06 �.09 �.10 .1114. Emotional dissonance 3.54 0.93 5 �.22 .59 �.40 �.16 �.12 �.1715. Disproportionate customer expectations 3.02 0.70 8�.16 .37 �.23 �.21 �.08 �.2116. Aggressive customers 1.95 0.54 5 �.06 .29 �.20 �.17 �.08 �.2317. Disliked customers 2.88 0.73 4 .04 .07�.10 �.20 �.06 �.2418. Ambiguous customers expectations 2.14 0.55 4 .08 .00�.18 �.10 .02 �.0619. Emotional exhaustion 2.14 0.83 9 .21�.16 �.14 .00 .05 .0520. Depersonalization 2.10 0.97 5 �.13 .20 �.09 �.13 .01 �.1821. Personal accomplishment 4.70 0.93 8 �.01 �.03 .05 .18 .06 .12

Note. Correlations greater than�.10� are significant atp � .01, correlations greater than�.07� are significant atp � .05,and correlations greater than�.06� are significant atp � .10.

70 DORMANN AND ZAPF

tomer expectations) up to above .40 (disliked cus-tomers and customer verbal aggression). No othercoefficient except emotional dissonance reached thatlevel. There was also evidence for the validity of theCSS scales with regard to personal accomplishment.In particular, the correlations between customer ver-bal aggression (–.33) and ambiguous customer ex-pectations (–.27) were among the strongest associa-tions found across all variables investigated.

In the following, a series of analyses were con-ducted to further establish the validity of the four newCSS scales. First, the differential validity of the fourscales was analyzed. In multiple regression analysesof the three burnout scales, all four CSS scales wereexamined for relevance with regard to the develop-ment of burnout symptoms or whether they wereredundant because of their intercorrelations. The re-sults of the three regression analyses are summarizedin Table 3. The results suggest that all four CSSscales were simultaneously able to predict burnout.Seven out of the 12 tested coefficients were signifi-cant (i.e.,p � .01, two-sided). With the exception ofthe (nonsignificant) positive effect of disliked cus-tomers on personal accomplishment, all other effectswere in the expected direction. In general, the effectsof customer verbal aggression were the strongestacross all three burnout symptoms. Ambiguous cus-

tomer expectations were positively related to emo-tional exhaustion and to personal accomplishment.Disliked customers played a significant role only foremotional exhaustion, and disproportionate customerexpectations played a significant role only for deper-sonalization. Thus, Hypothesis 2 was partiallysupported.

Analyzing Hypotheses 3a–c, we carried out twohierarchical multiple regressions with burnout as de-pendent variables and CSS and emotional dissonanceas predictors. In the first analysis, emotional disso-nance was entered before the CSS scales to investi-gate whether the direct effects of CSS on burnoutwere reduced through the mediating effect of emo-tional dissonance. The results are shown in Table 4.In all instances, emotional dissonance significantlypredicted burnout when entered into the equationfirst, which corresponds to the first step of testing formediation according to R. M. Baron and Kenny(1986; i.e., the amount of explained variance differedsignificantly from zero). However, only for deperson-alization, emotional dissonance remained a signifi-cant predictor after CSS was entered into the equa-tion, which corresponds to the third step according toBaron and Kenny (i.e., the regression coefficienttaken from the final step of the equation remainedsignificant). The coefficients obtained for the CSS

7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

—.11 —.28 .46 —.02 .20 .17 —.03 .08 .28 .28 —.05 �.02 �.08 �.28 �.35 —.05 �.03 �.03 �.28 �.29 .52 —.33 .25 .49 .14 .36 �.12 �.05 —.10 .23 .45 .19 .42 �.13 .01 .51 —.00 .24 .35 .24 .40 �.15 �.07 .44 .58 —

�.08 .31 .29 .19 .28 .02 .08 .34 .49 .46 —�.04 .27 .19 .25 .22 �.08 �.06 .16 .48 .40 .34 —

.01 .30 .31 .21 .16 �.23 �.16 .18 .30 .30 .28 .27 —

.10 .19 .32 .14 .29 �.23 �.08 .39 .41 .44 .30 .20 .54 —

.03 .04 .01 �.27 �.19 .25 .16 �.10 �.17 �.33 �.10 �.27 �.29 �.30 —

71CUSTOMER-RELATED SOCIAL STRESSORS

scales were only slightly different compared withthose shown in Table 3 (in which emotional disso-nance was not included; this corresponds to the sec-ond step of the procedure suggested by Baron andKenny). The (standardized) effects of disproportion-ate customer expectations and customer verbal ag-gression on depersonalization decreased from .22 to.15, and from .30 to .26, respectively, which suggestsa partial mediation process (R. M. Baron & Kenny,1986). Nevertheless, the changes were small. Thus,emotional dissonance seems to qualify as a partial

and weak mediator between CSS and depersonaliza-tion. It does not represent a mediator between CSSand exhaustion, and CSS and accomplishment.

Second, we reversed the order by which the vari-ables were entered into the equation, that is, the CSSscales were entered first and emotional dissonancesecond. This was to test for the possibility that emo-tional dissonance represents an indicator for an em-ployee’s attempt to create a positive affective toneduring interactions with customers, which might leadto fewer CSS. The results are shown in Table 5. It

Table 3Multiple Regressions (Maximum Likelihood) of the Three Burnout Symptoms on the FourCustomer-Related Social Stressors Scales (N � 591)

Measure

Emotional exhaustion Depersonalization Personal accomplishment

B SE B � B SE B � B SE B �

Disproportionate customer expectations .11 .06 .09 .31 .07 .22** .10 .07 .07Customer verbal aggression .22 .08 .14** .52 .08 .30**�.57 .09 �.33**Disliked customers .14 .05 .12** .10 .06 .08 .10 .06 .08Ambiguous customer expectations .20 .07 .13**�.09 .07 �.05 �.34 .08 �.20**

R2 � .14 R2 � .23 R2 � .14F � 23.63** F � 44.55** F � 23.79**

Note. For all threeF tests,dfs � 4, 586.** p � .01 (two-tailed).

Table 4Hierarchical Multiple Regressions (Maximum Likelihood) of the Three Burnout Symptoms on EmotionalDissonance and the Four Customer-Related Social Stressors Scales Added (N � 591)

Step and measure

Emotional exhaustion Depersonalization Personal accomplishment

B SE B � B SE B � B SE B �

Step 1Emotional dissonance .01 .04 .01 .19 .05 .18** .02 .05 .02

R2 � .03 R2 � .15 R2 � .01F � 19.71** F � 102.88** F � 5.85*

Step 2Disproportionate customer

expectations .10 .07 .09 .21 .07 .15** .09 .07 .07Customer verbal aggression .22 .08 .14** .46 .08 .26**�.57 .09 �.33**Disliked customers .13 .05 .12** .08 .06 .06 .10 .06 .07Ambiguous customer expectations .20 .07 .13**�.04 .07 �.02 �.34 .08 �.20**

�R2 � .11 �R2 � .11 �R2 � .13�F � 18.14** �F � 21.10** �F � 22.16**

R2 � .14 R2 � .26 R2 � .14

Note. All coefficients are taken from the final step. For Step 1,dfs � 1, 589 for all threeF tests; Step 2,dfs � 4, 585for all threeF tests.* p � .05. **p � .01 (two-tailed).

72 DORMANN AND ZAPF

turned out that emotional dissonance was not signif-icant anymore for emotional exhaustion and personalaccomplishment, but it significantly contributed tothe prediction of depersonalization after CSS werecontrolled. Nevertheless, the increment in explainedvariance (2%) was much lower than the explainedvariance without CSS being controlled (15%; seeTable 4). Thus, CSS could represent a mediator be-tween emotional dissonance and depersonalization.Taken together, emotional dissonance explained vari-ance above and beyond CSS in the prediction ofdepersonalization, but it does not have a unique con-tribution to exhaustion and reduced accomplishment.

The correlations reported in Table 2 support thenotion that burnout depended primarily on socialinteractions with customers. In addition, the CSSscales were not redundant (see Table 3), and theyexhibited differential validity with regard to emo-tional dissonance (Table 4 and Table 5). However,the “added value” of the newly developed CSS scalesshould be also shown with regard to other probablecauses of burnout.

Therefore, a final series of three hierarchical re-gression analyses for emotional exhaustion, deper-sonalization, and personal accomplishment were car-ried out to test Hypothesis 4, which predicts thatother job stressors and resources are not able toexplain the effects of CSS on burnout. The predictor

variables were entered into the equation in six blocksto obtain the degree of variance accounted for by theblocks of variables: Step 1, age and gender; Step 2,three dummies representing the travel agencies, theflight attendants, and the shoe stores; Step 3, task-related stressors and resources; Step 4, supervisor-and colleague-related stressors and resources; Step 5,emotional dissonance; and Step 6, the four CSSscales. We used a dummy for travel agencies becausethe data for Sample 1 were gathered (July–December1999) after the data for Sample 2 (May – July 1999),leading to possible seasonal fluctuations in workingconditions.

The results are shown in Table 6. For emotionalexhaustion the results indicate that two out of thefour CSS scales, disliked customers and ambigu-ous customer expectations, were no longer signif-icant. However, the effect of disproportionate cus-tomer expectations was now significant where ithad previously played a marginal role. For deper-sonalization, disproportionate expectations andverbal aggression remained significant (see Table3). In all instances, the magnitude (i.e., beta coef-ficients) of the four CSS scales was reduced. Forpersonal accomplishment, the pattern of significantresults did not change compared with those shownin Table 3; however, the effect sizes decreasedslightly.

Table 5Hierarchical Multiple Regressions (Maximum Likelihood) of the Three Burnout Symptoms on the FourCustomer-Related Social Stressors Scales and Emotional Dissonance Added (N � 591)

Step and measure

Emotional exhaustion DepersonalizationPersonal

accomplishment

B SE B � B SE B � B SE B �

Step 1Disproportionate customerexpectationsCustomer verbal aggression (The coefficients are identical to

those in Table 4.)Disliked customersAmbiguous customer expectations

R2 � .14 R2 � .23 R2 � .14F � 23.63** F � 44.55** F � 23.79**

Step 2Emotional dissonance (The coefficients are identical to those in Table 4.)

�R2 � .00 �R2 � .02 �R2 � .00�F � .07 �F � 17.94** �F � .07

R2 � .14 R2 � .26 R2 � .14

Note. All coefficients are taken from the final step. For Step 1,dfs � 4, 586 for all threeF tests; Step 2,dfs � 1, 585for all threeF tests.** p � .01 (two-tailed).

73CUSTOMER-RELATED SOCIAL STRESSORS

Table 6Hierarchical Regression (Maximum Likelihood) of Emotional Exhaustion, Depersonalization, and Personal Accomplishment (N � 591)

Step and measure

Emotional exhaustion Depersonalization Personal accomplishment

B SE B � B SE B � B SE B �

Step 1Age .00 .00 .01 �.01 .00 �.06 .01 .00 .12**Gender (1� female; 2� male) �.02 .07 �.01 .16 .08 .07 .06 .09 .03

�R2 � .00; �F � .91 �R2 � .02; �F � 5.50** �R2 � .03; �F � 9.61**Step 2

Travel agency (Sample 1) dummy .04 .12 .02 �.06 .14 �.03 �.04 .14 �.02Flight attendant dummy �.73 .12 �.44** �.24 .14 �.13 .18 .14 .10Shoe store dummy �.27 .14 �.12* .33 .16 .12* .14 .16 .06

�R2 � .08; �F � 16.23** �R2 � .03; �F � 6.87** �R2 � .00; �F � .44Step 3

Control .05 .05 .05 �.16 .05 �.14** .09 .05 .08Timing control .04 .05 .05 .14 .05 .13** �.10 .05 �.09Concentration demands .05 .05 .05 .03 .06 .02 .17 .06 .14**Time pressure .17 .05 .16** .15 .05 .13** .10 .05 .09Work-organization problems �.00 .07 �.00 �.06 .06 �.03 �.22 .06 �.15**

�R2 � .14; �F � 20.37** �R2 � .12; �F � 17.49** �R2 � .08; �F � 10.69**Step 4

Social stressors supervisors/colleagues .04 .07 .03 .03 .08 .01 �.02 .08 �.01Supervisor support �.14 .05 �.12** �.22 .06 �.16** .21 .06 .16**Colleague support �.13 .06 �.09* .06 .07 .04 .03 .07 .02

�R2 � .05; �F � 13.23** �R2 � .05; �F � 11.35** �R2 � .04; �F � 9.68**Step 5

Emotional dissonance .09 .05 .10 .19 .05 .18** .00 .05 .00�R2 � .02; �F � 15.66** �R2 � .04; �F � 30.09** �R2 � .00; �F � 1.10

Step 6Disproportionate customer expectations .18 .06 .15** .14 .07 .10* .08 .07 .06Customer verbal aggression .22 .07 .14** .44 .08 .25** �.52 .08 �.30**Disliked customers .07 .05 .06 .05 .06 .03 .07 .06 .05Ambiguous customer expectations .03 .06 .02 �.02 .07 �.01 �.30 .08 �.18**

�R2 � .05; �F � 11.42** �R2 � .06; �F � 13.06** �R2 � .09; �F � 17.70**Overall R2 � .34 Overall R2 � .32 Overall R2 � .25

Note. All coefficients taken from the final equation. For Step 1,dfs � 2, 588 for all threeF tests; Step 2,dfs � 3, 585 for all threeF tests; Step 3,dfs � 5, 580 for all threeF tests; Step 4,dfs � 3, 577 for all threeF tests; Step 5,dfs � 1, 576 for all threeF tests; Step 6,dfs � 4, 572 for all threeF tests.* p � .05. ** p � .01 (two-tailed).

74D

OR

MA

NN

AN

DZ

AP

F

To test whether the observed changes in the re-gression coefficients were significant,2 we used LIS-REL 8 (Joreskog & So¨rbom, 1993). The results fromthis series of analyses indicated that there were threesignificant changes. For emotional exhaustion, thechanges in the regression coefficients of disliked cus-tomers (�df � 1, ��2 � 5.58, p � .02) and ofambiguous customer expectations (�df � 1, ��2 �5.63,p � .02) decreased significantly. For deperson-alization, there was a single significant decrease inthe regression coefficient of disproportionate cus-tomer expectations (�df � 1, ��2 � 6.58,p � .02).For personal accomplishment, there was no signifi-cant change in the regression coefficients. Thus, al-though there were some reductions in effect sizes,several effects of CSS on burnout remained signifi-cant, thus supporting Hypothesis 4.

To shed some light on the processes by which thefour CSS and other variables lead to burnout, weinvestigated whether any of the control variablesalone could account for the change in the regressioncoefficients previously observed.3 We did not findany significant effect. The strongest reduction in theeffect of ambiguous customer expectations on emo-tional exhaustion was due to the dummy variablecoding the flight attendants,�2(1, N � 591) � 1.51,p � .22 (all other�2 � 1.05,p � .29). Similarly, thestrongest reduction in the effect of disliked customerson emotional exhaustion was due to the same dummyvariable,�2(1, N � 591) � 2.63,p � .11 (all other�2 � .53, p � .46). The strongest reduction in theeffect of disproportionate customer expectations ondepersonalization was due to emotional dissonance,�2(1, N � 591)� 2.17,p � .14 (all other�2 � 1.12,p � .28). In summary, although three of the effects ofthe CSS scales decreased significantly after the wholeset of control variables was included, no single con-trol variable contributed significantly to this result. Inother words, there is no evidence that any of thevariables investigated may serve as a substitute forCSS. This represents further support for Hypothesis 4.

Discussion

In this article we analyzed employee–customerinteractions from a stress perspective. Because a gen-eral theory that may explain why such interactionsmay be stressful does not exist, we reviewed theliterature on social stress within organizations. Weidentified situations and behaviors describing poten-tially stressful aspects of social interactions, whichmight also apply for interactions of service providersand customers. We used the COR theory as a frame-

work, which suggests various resources such as self-esteem, self-efficacy, or goal pursuit, which may bethreatened in customer interactions. Moreover, wereferred to theories on social conflicts, workplaceaggression, incivility, and concepts referring to reci-procity, fairness, and justice, which were assumed todescribe aspects of social behavior that threaten basicresources according to COR theory (Hobfoll, 2001).The present study revealed four constructs and theirmeasures, which can be used to assess stressors inemployee–customer interactions. The CSS scales in-clude disproportionate customer expectations, cus-tomer verbal aggression, disliked customers, and am-biguous customer expectations.

The first factor describes situations in which cus-tomers tax or challenge the service they want toreceive from the service provider. The items addressservice expectations that might be legitimate but thatseem to be disproportionate from the service provid-er’s point of view. These expectations seem unjusti-fied and sometimes unfair by the service providers.This factor corresponds to theories on fairness (Don-ovan et al., 1998), justice (Greenberg, 1990), andreciprocal behavior (Schaufeli et al., 1996). One mayalso draw parallels to the effort–reward imbalancemodel of Siegrist (2000). Certainly, there is no clearreference point. A customer’s behavior may conflictwith other customers who have to wait for an undulylong time; it may be disproportionate compared withwhat the organization receives from the customer inexchange, or they may be requesting things theycould do themselves. The situation is considered asone-sided and is lacking reciprocity. The question of

2 Such a test requires fixing the one particular regressioncoefficient in the extended model (including all variables) tothe corresponding value obtained from the model includingonly the four CSS scales. A significant chi-square differencetest (Bentler & Bonett, 1980) with one degree of freedomindicates a change in the value of the coefficient underconsideration. Therefore, for each burnout variable, a modelincluding all predictors was tested in which the coefficientunder consideration—from disproportionate customer ex-pectations to emotional exhaustion—was fixed at the samevalue obtained from the simple model, in which only theCSS scales were used as predictors.

3 We used LISREL 8 to test 42 models (14 controlvariables times 2 CSS scales for emotional exhaustion plus14 control variables times 1 CSS scale for depersonaliza-tion). Each model included the four CSS scales plus onecontrol variable. The coefficient for the CSS scale underconsideration was fixed at the value obtained from themodel without the control variable. A significant chi-squarevalue indicates that adding the effect of the control vari-able led to a significant change in the coefficient underconsideration.

75CUSTOMER-RELATED SOCIAL STRESSORS

reciprocity is closely related to the issue of fairnessand justice. If the interaction is perceived as beingunfair, the employees may feel that customers havetaken advantage of them and typical stress emotions,such as anger, are likely to occur. Semmer (2000)pointed out that legitimacy of demands could becrucial in the assessment of stressors at work. Acertain behavior required in the job may not have anynegative effects if this behavior is seen as a centraland legitimate aspect of the job. However, the samerequired behavior can be considered as stressful if itis seen as illegitimate. According to Semmer, legiti-macy is related to the self-concept. Thus dispropor-tionate customer expectations threaten this basicresource.

The second factor refers to being exposed to verbalaggression of customers and refers to theories onworkplace aggression (R. A. Baron & Neuman,1996) and other kinds of antisocial behavior. Severalstudies (e.g., Zapf, Knorz, & Kulla, 1996) haveshown that verbal aggression of colleagues and su-pervisors represent social stressors. Consistent withthese findings, the present study shows that in servicejobs, customer verbal aggression is a serious stressoras well. This is of no surprise because in manyservice jobs interactions with customers are muchmore frequent than interactions with supervisors andcolleagues. It can be expected that customer verbalaggression has similar effects. Aggression is definedby the intention to harm another person. Specifically,verbal aggression harms another person’s self-es-teem, thus threatening basic resources according toCOR theory.

The third factor comprises items referring to inter-actions with hostile, humorless, and unpleasant cus-tomers and interruptions by customers. This factor isless easy to interpret. These customers may showbehavior that is not directly perceived as aggressivebecause an obvious intention to harm is lacking. Normay the behavior be characterized as obviously un-fair. Rather, the underlying behaviors may comeclose to behaviors described as uncivil (Andersson &Pearson, 1999; Cortina et al., 2001). That is, hostile,humorless, and unpleasant customers who do notrespect the service provider’s work rhythm may usesubtle forms of uncivil behavior, which negativelyaffect the service provider’s self-esteem. Thus, evenif there is no intention to harm, basic resources suchas self-esteem can be threatened.

The fourth factor refers to ambiguous and unclearcustomer expectations. In a sense, this factor is sim-ilar to the concept of role ambiguity (Katz & Kahn,1978) and the concept of uncertainty of goal attain-

ment (Frese & Zapf, 1994; Semmer et al., 1995).Unfortunately, these concepts were not included inthis study. Therefore, it remains to be seen whetherthis CSS factor is redundant with these variables.However, we suppose that role ambiguity and uncer-tainty refer more to the cognitive aspects (difficultiesin goal and plan development and information pro-cessing), whereas the scale ambiguous customer ex-pectations is more related to the social and emotionalimplications of this ambiguity. It should be noted,however, that the cognitive and socioemotional as-pects are related and cannot be completely separated(Schaufeli & Enzmann, 1998; Zapf, Seifert,Schmutte, Mertini, & Holz, 2001). Conflicts, aggres-sive acts, and the like may impair cooperative behav-iors and the information flow. This may create orga-nizational problems, uncertainty, or time pressure.That is, we expect a correlation between ambiguouscustomer expectations and these variables; however,further research is needed to investigate whetherthese variables are completely redundant.

The correlations between the four CSS scales werebetween .34 and .58, suggesting that, in general,employee–customer interactions are either more pos-itive or more negative. Although the strengths of theassociations may be partly due to common methodvariance, the sizes of these correlations correspond tothose of similar concepts that are related to socialinteraction within the organization (Cortina et al.,2001; Tepper, 2000). As in these studies, our resultsshow that the CSS scales are correlated but not mu-tually redundant.

Moreover, the data show that emotional disso-nance, the key variable of emotional labor referringto discrepancies between felt and expressed emo-tions, and the CSS scales are also not mutually re-dundant. The CSS scales address aspects of the in-teraction with customers that explain variancebeyond the effects of emotional dissonance.

A question is, why are the effects of emotionaldissonance that go above and beyond CSS limited todepersonalization? It has been argued (e.g., Grandey,2003) that emotional dissonance especially occurs ifemployees engage in surface rather than in deepacting. Surface acting, for example, does not involvetaking the perspective of the customer, and it does notinvolve a real understanding of the customer’s wor-ries and concerns. Depersonalization represents thesymptom that describes the case when this way ofacting has changed from being an occasional strategyand has become a habit.

Finally, we were able to demonstrate that CSS andemotional dissonance remain determinants of burn-

76 DORMANN AND ZAPF

out when other relevant stressors and resources atwork are controlled for. It should be noted that ourstrategy to use hierarchical regression and enter theCSS scales in the last block is a conservative strategythat maximizes the likelihood to reject our hypothe-sis. The CSS scales provide additional explanatoryvalue above and beyond a great variety of previouslyinvestigated predictors such as task-related stressorsand resources, social stressors and support from su-pervisors and colleagues, and further controls. Inparticular, we feel that the additional variance ex-plained in exhaustion (5%), depersonalization (6%),and personal accomplishment (9%) is remarkable.

A variety of other stressors have been examined aspotential causes of burnout in previous research.Leiter and Maslach (1988) suggested that emotionalexhaustion represents a kind of strain that is directlyaffected by these causes. That is, emotional exhaus-tion mediates the effects of all stressors on deperson-alization, which represents a form of defensive cop-ing, and on personal accomplishment, whichrepresents a form of self-evaluation. Their model isconsistent with the results of a large proportion ofprevious research, which has shown that stressors, ingeneral, account for the most variance in emotionalexhaustion followed by depersonalization and per-sonal accomplishment. This burnout model was mod-ified by Leiter (1993) based on the COR theory ofHobfoll (1989; Hobfoll & Freedy, 1993). Leiter(1993) suggested that stressors cause exhaustion,whereas resources should help to overcome defensivecoping in terms of depersonalization and reducedpersonal accomplishment. It is not the center of ourarticle to discuss the various models of burnout.However, we want to point out that our results at leastpartially challenge the older mediation model ofLeiter and Maslach (1988), because the degree ofvariance explained in the three burnout symptoms bythe four CSS scales is highest for depersonalization(23%) and is identical for emotional exhaustion andpersonal accomplishment (both 14%; see Table 3).This result is incompatible with a pure mediationmechanism. Rather, the present findings suggest thatemotional exhaustion might be a necessary conditionfor depersonalization and reduced personal accom-plishment to occur, but it is not singularly sufficient.

Another reason why we were able to explain ahigher amount of variance in depersonalization com-pared with exhaustion might be that most previousstudies analyzed employees in human service jobs. Inhuman service jobs the primary task is to “modify”the customers physically or psychologically. Em-ployees in human service jobs such as nurses, teach-

ers, and so on may be more likely to reject deperson-alization as a coping strategy than the samplesanalyzed in the present article. We suppose that em-ployees in shoe stores and travel agencies as well asflight attendants did not choose their jobs becausethey wanted toserve people but because of otherreasons. For instance, people may apply for a job asa flight attendant or in a travel agency because theyare attracted by the possibility to travel a lot. In asimilar vein, shoe store clerks may not necessarily bepeople whose desire is to serve other people. Incontrast, to take care of other people is a frequentmotive for people working in human service jobs,and depersonalization is extremely incompatible withthis motive. This is less likely to be the case for theparticipants of the present study. Therefore, they maymore quickly adopt depersonalization strategies as ameans of coping with their customers’ behavior.

A yet unresolved question it related to optimalcoping strategies when facing demanding customers.We concur with Dollard, Dormann, Boyd, Winefield,and Winefield (2003) that services require a psycho-logical balance between emotional under- and over-involvement on the side of the service provider. Forexample, Winefield (2003) argued that underinvolve-ment might be a precursor of providers’ depersonal-ization. Overinvolvement, on the other hand, mayfacilitate exhaustion. A balance is not easilyachieved, and ways to do so are sometimes part ofprofessional training. A particular state of balance issometimes calleddetached concern, which describesa seemingly paradoxical state of being completely“there for” the customer but simultaneously beingemotionally detached from the customer’s emotionalstate (e.g., Potter, 1983). Detached concern is one ofthe most efficient moderators to reduce the impact ofstressors on professional burnout (e.g., Savicki &Cooley, 1982). We believe that this applies wellwhen one has to deal with customer-related stressors.In particular, using a laboratory experiment,Stemmler (1997) showed that verbal harassmentleads to less physical arousal when participants areencouraged to interpret it in a detached manner.However, Dollard et al. (2003) noted that to avoid thedevelopment of depersonalization as a habituationresponse to too frequent emotional detachment (seealso Grandey, 2000), and to maintain positive regardtoward one’s clients, employees should be able todifferentiate between themselves and their role asrepresentatives of their occupation or organization.Dollard et al. referred to such a coping strategy asrole separation.

There are some limitations of the present research.

77CUSTOMER-RELATED SOCIAL STRESSORS

First, it is a cross-sectional study in which the ques-tion of reversed causation or omitted third variablescannot be fully solved (see Zapf, Dormann, & Frese,1996). For instance, Kop, Euwema, and Schaufeli(1999) argued that depersonalization might lead toaggressive and violent employee behavior. This may,in turn, frustrate customers, make them angry andaggressive, and tempt them to (verbally) attack theemployee (e.g., Berkowitz, 1989), so that the direc-tion of the causal relation between aggressive cus-tomers and depersonalization may be reversed com-pared with our interpretation. In addition, it alsoseems plausible that depersonalization and customerverbal aggression are reciprocally related. Both pos-sibilities may have led to an overestimation of thecausal effect of customer verbal aggression on deper-sonalization. On the other hand, we believe that thirdvariables, which may have spuriously created thepattern of observed relations, are less of a problem inthis study. We controlled for a variety of potentialthird variables in hierarchical regression analyses.None of them were per se able to reduce the effectsof the CSS scales. Another reason to believe thatthird variables are not much of a problem is the factthat disliked customers seem to be least relevant forthe development of burnout, on average (see Table3). The items used to measure disliked customersseem to be much more dependent on subjective ap-praisals compared with the remaining three CSSscales. For example, the item “One has to work withcustomers who have no sense of humor” may dependon an employee’s own sense of humor. However, ifthe relationships between disliked customers andburnout were only a matter of confounding due tobiased self-reports, one would have certainly ex-pected that this relation would be particularly strong.This was not the case.

Another limitation of the present study is that wemay not have covered the full range of possible CSS.For example, what have been left out are conflictsamong customers, which affect the service providerand in which the service providers are sometimesexpected to intervene and handle the conflict. How-ever, our aim was to develop scales that can beapplied to almost every service job. Because there isan increasing amount of service jobs in which em-ployees do not interact with their customers in aface-to-face fashion, we did not include items tomeasure conflicts among customers. During voice-to-voice interaction, employees usually cannot observeovert conflicts among customers. A prominent exam-ple is call center jobs (e.g., Dormann et al., 2002), buttelephone-based interactions are also part of many

other service jobs. We also did not include aspects ofphysical violence. Physical violence also does notoccur in voice-to-voice interactions, but the mainreason for excluding them is their low prevalence(R. A. Baron & Neumann, 1996).

Although we have shown that CSS are superior inpredicting burnout, one might argue that the task-related stressor scales we applied do not represent anappropriate standard against which the effects of theCSS scales should be evaluated. Prior research hasfound much stronger effects for task-related stressorsthan we did. For example, Lee and Ashforth’s (1996)meta-analysis showed that time pressure shares onaverage 25% variance with emotional exhaustion,whereas we found only about 9% (12% if correctedfor attenuation). However, as Schaufeli and Enzmann(1998) noted, the high degree of shared variancefound in previous studies must be qualified because,for example, time pressure has often been operation-alized in terms of experienced strain. This wasavoided in the present study for the task-related stres-sors and resources as well as for the CSS scales (seeSemmer, Zapf, & Greif, 1996). Although we applieda self-report methodology, the items used to measureCSS (and emotional labor) were phrased in a way tominimize the amount of subjective bias. For instance,one item was “Customers vent their bad mood out onus” rather than “. . . on me” to reduce appraisal pro-cesses. Our estimated relationships are likely to beconservative compared with other measures used inburnout research.

Because our aim was to develop a measure thatapplies to a great variety of occupations, the CSSscales should be tested further across different ser-vice industries. Moreover, the validity of the fourCSS scales and the constructs they represent need tobe established in different languages and cultures.For example, in Germany it is common sense that theservice culture in organizations is less developedcompared with other countries such as the UnitedStates. It might therefore be possible that some of theconstructs investigated do not represent so much astressor for U.S. employees as for German ones. Thesocializing impact of an apparent service culture maylead to different appraisal processes and coping strat-egies (Lazarus & Folkman, 1984). Customers whoalways expect special treatment may be quite com-mon in the United States, and U.S. employees mayconsider this less stressful. The scales should, there-fore, be tested in various national settings.

The samples investigated in this study do not rep-resent human services. Nonhuman service jobs havenot been investigated so often with regard to burnout,

78 DORMANN AND ZAPF

but they employ much more people than humanservices. Therefore, future studies should continueaccumulating knowledge outside the health and edu-cation sectors. Burnout can emerge in almost anyservice occupation (e.g., Leiter & Schaufeli, 1996),but its causes and its symptoms vary considerably inimportance. Customer-related social stressors shouldbe considered as potential antecedents of burnout inthese jobs.

References

Abraham, R. (1998). Emotional dissonance in organiza-tions: Antecedents, consequences and moderators.Ge-netic, Social, and General Psychology Monographs, 124,229–246.

Adams, J. S. (1965). Inequity in social exchange. In L.Berkowitz (Ed.),Advances in experimental social psy-chology (Vol. 2, pp. 267–299). New York: AcademicPress.

Andersson, L. M., & Pearson, C. M. (1999). Tit for tat? Thespiraling effect of incivility in the workplace.Academy ofManagement Review, 24, 452–471.

Appelberg, K., Romanov, K., Honkasalo, M. -L., & Kos-kenvuo, M. (1991). Interpersonal conflicts at work andpsychosocial characteristics of employees.Social Sci-ence Medicine, 32, 1051–1056.

Bakker, A. B., Schaufeli, W. B., Sixma, H. J., Bosveld, W.,& van Dierendonck, D. (2000). Patient demands, lack ofreciprocity, and burnout: A five-year longitudinal studyamong general practitioners.Journal of OrganizationalBehavior, 21, 425–441.

Baron, R. A., & Neuman, J. H. (1996). Workplace violenceand workplace aggression: Evidence on their relativefrequency and potential causes.Aggressive Behavior, 22,161–173.

Baron, R. A., & Neuman, J. H. (1998). Workplace aggres-sion—the iceberg beneath the tip of workplace violence:Evidence on its forms, frequency and targets.PublicAdministration Quarterly, 21, 446–464.

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological re-search: Conceptual, strategic, and statistical consider-ations.Journal of Personality and Social Psychology, 51,1173–1182.

Baumeister, R. F., Smart, L., & Boden, J. M. (1996). Rela-tion of threatened egotism to violence and aggression:The dark side of high self-esteem.Psychological Review,103, 5–33.

Beehr, T. A., Drexler, J. A., & Faulkner, S. (1997). Workingin small family businesses: Empirical comparisons tonon-family businesses.Journal of Organizational Behav-ior, 18, 297–312.

Bentler, P. M., & Bonett, D. G. (1980). Significance testsand goodness of fit in the analysis of covariance struc-tures.Psychological Bulletin, 88, 588–606.

Berkowitz, L. (1989). Frustration-aggression hypothesis:Examination and reformulation.Psychological Bulletin,106, 59–73.

Bitner, M. J., Booms, B. H., & Mohr, L. A. (1994). Criticalservice encounters: The employee’s viewpoint.Journalof Marketing, 58(4), 95–106.

Brotheridge, C. M., & Grandey, A. A. (2001). Emotionallabor and burnout: Comparing two perspectives of “peo-ple work.” Journal of Vocational Behavior, 60, 17–39.

Brotheridge, C. M., & Lee, R. T. (1998, August).On thedimensionality of emotional labor: Development and val-idation of an emotional labor scale. Paper presented atthe First Conference on Emotions in Organizational Life,San Diego, CA.

Budd, J. W., Arvey, R. D., & Lawless, P. (1996). Correlatesand consequences of workplace violence.Journal of Oc-cupational Health Psychology, 1, 197–210.

Bussing, A., & Perrar, K. -M. (1992). Die Messung vonBurnout. Untersuchung einer deutschen Fassung desMaslach Burnout Inventory (MBI-D) [The measurementof burnout. Studies on a German version of the MaslachBurnout Inventory].Diagnostica, 38, 328–353.

Buunk, B. P., & Schaufeli, W. B. (1999). Reciprocity ininterpersonal relationships: An evolutionary perspectiveon its importance for health and well-being. In M. Hew-stone & W. Stroebe (Eds.),European review of socialpsychology (pp. 259–340). Chichester, UK: Wiley.

Caplan, R. D., Cobb, S., French, J. R. P., Harrison, R. van,& Pinneau, S. R. (1975).Job demands and workerhealth. Washington, DC: National Institute for Occupa-tional Safety and Health.

Cortina, L. M., Magley, V. J., Hunter Williams, J., & DayLanghout, R. (2001). Incivility in the workplace: Inci-dence and impact.Journal of Occupational Health Psy-chology, 6, 64–80.

de Dreu, C. K. W., van Dierendonck, D., & de Best-Waldhober, M. (2003). Conflict at work and individualbeing. In M. J. Schabracq, J. A. M. Winnubst, & C. L.Cooper (Eds.),Handbook of work and health psychology(pp. 495–516). Chichester, UK: Wiley.

Dollard, M. F., Dormann, C., Boyd, C. M., Winefield, A. H.,& Winefield, H. R. (2003). Unique aspects of stress inhuman service work.Australian Psychologist, 38,84–91.

Donovan, M. A., Drasgow, F., & Munson, L. J. (1998). ThePerceptions of Fair Interpersonal Treatment scale: De-velopment and validation of a measure of interpersonaltreatment in the workplace.Journal of Applied Psychol-ogy, 83, 683–692.

Dormann, C., & Zijlstra, F. (Eds.). (in press).Call centrework: Smile by wire [A special issue of the EuropeanJournal of Work and Organizational Psychology]. Howe,England: Psychology Press.

Dormann, C., & Zapf, D. (1999). Social support, socialstressors, and depression: Testing for main and moder-ating effects with structural equations in a 3-wave lon-gitudinal study. Journal of Applied Psychology, 84,874–884.

Dormann, C., & Zapf, D. (2002). Social stressors at work,irritation, and depression: Accounting for unmeasuredthird variables in a multi-wave study.Journal of Occu-pational and Organizational Psychology, 75, 33–58.

Dormann, C., Zapf, D., & Isic, A. (2002). EmotionaleArbeitsanforderungen und ihre Konsequenzen bei CallCenter-Arbeitspla¨tzen [Emotional job requirements andtheir consequences in call center jobs].Zeitschrift furArbeits- und Organisationspsychologie, 46, 201–215.

Duffy, M. K., Ganster, D. C., & Pagon, M. (2002). Socialundermining in the workplace.Academy of ManagementJournal, 45, 331–352.

79CUSTOMER-RELATED SOCIAL STRESSORS

Einarsen, S., Hoel, H., Zapf, D., & Cooper, C. L. (2003).The concept of bullying at work: The European tradition.In S. Einarsen, H. Hoel, D. Zapf, & C. L. Cooper (Eds.),Bullying and emotional abuse in the workplace: Interna-tional perspectives in research and practice (pp. 3–30).London: Taylor & Francis.

Frese, M. (1989). Gu¨tekriterien der Operationalisierung vonsozialer Unterstu¨tzung am Arbeitsplatz [Psychometriccriteria of the operationalization of social support atwork]. Zeitschrift fur Arbeitswissenschaft, 43, 112–122.

Frese, M., & Zapf, D. (1987). Eine Skala zur Erfassung vonSozialen Stressoren am Arbeitsplatz [A scale measuringsocial stressors at work].Zeitschrift fur Arbeitswissen-schaft, 41, 134–141.

Frese, M., & Zapf, D. (1988). Methodological issues in thestudy of work stress: Objective vs. subjective measure-ment and the question of longitudinal studies. In C. L.Cooper & R. Payne (Eds.),Causes, coping, and conse-quences of stress at work (pp. 375–411). Chichester, UK:Wiley.

Frese, M., & Zapf, D. (1994). Action as the core of workpsychology: A German approach. In H. C. Triandis,M. D. Dunnette, & L. M. Hough (Eds.),Handbook ofindustrial and organizational psychology (Vol. 4, pp.271–340). Palo Alto, CA: Consulting PsychologistsPress.

Frone, M. R. (2000). Interpersonal conflict at work andpsychological outcomes: Testing a model among youngworkers.Journal of Occupational Health Psychology, 5,246–255.

Glomb, T. M. (2002). Workplace anger and aggression:Informing conceptual models with data from specificencounters.Journal of Occupational Health Psychology,7, 20–36.

Goffman, E. (1959).The presentation of self in everydaylife. New York: Doubleday Anchor.

Graham, J. W., Hofer, S. M., & MacKinnon, D. P. (1996).Maximizing the usefulness of data obtained with plannedmissing value patterns: An application of maximum like-lihood procedures.Multivariate Behavioral Research,31, 197–218.

Grandey, A. A. (2000). Emotion regulation in the work-place: A new way to conceptualize emotional labor.Journal of Occupational Health Psychology, 5, 95–110.

Grandey, A. A. (2003). When “the show must go on”:Surface acting and deep acting as determinants of emo-tional exhaustion and peer-rated service delivery.Acad-emy of Management Journal, 44, 86–98.

Grandey, A. A., Dickter, D. N., & Sin, H. -P. (2002,February).Customer verbal abuse of service representa-tives: Consequences and coping. Paper presented at theannual meeting of the Society of Industrial and Organi-zational Psychology, Toronto, Ontario, Canada.

Grandey, A. A., Tam, A. P., & Brauburger, A. L. (2002).Affective states and traits in the workplace: Diary andsurvey data from young workers.Motivation and Emo-tion, 26, 31–55.

Greenberg, J. (1990). Organizational justice: Yesterday, to-day, and tomorrow. Journal of Management, 16,399–432.

Hobfoll, S. E. (1989). Conservation of resources: A newattempt at conceptualizing stress.American Psychologist,44, 513–524.

Hobfoll, S. E. (2001). The influence of culture, community,

and the nested-self in the stress process: Advancing con-servation of resources theory.Applied Psychology: AnInternational Review, 50, 337–421.

Hobfoll, S. E., & Freedy, J. (1993). Conservation of re-sources: A general stress theory applied to burnout. InW. B. Schaufeli, C. Maslach, & T. Marek (Eds.),Pro-fessional burnout: Recent developments in theory andresearch (pp. 115–129). Washington, DC: Taylor &Francis.

Hochschild, A. R. (1983).The managed heart. Berkeley:University of California Press.

Holman, D. J. (2003). Call centres. In D. J. Holman, T. D.Wall, C. W. Clegg, P. Sparrow, & A. Howard (Eds.),Thenew workplace: A guide to the human impact of modernworking practices. Chichester, UK: Wiley.

House, J. S. (n.d.).The questionnaire. University ofMichigan.

Isic, A., Dormann, C., & Zapf, D. (1999). Belastungen undRessourcen an Call Center-Arbeitspla¨tzen [Stressors andresources at call center jobs].Zeitschrift fur Arbeitswis-senschaft, 53, 202–208.

Isic, A., & Zapf, D. (2002).Aufgaben- und kundenbezogeneArbeitsbedingungen in Call Centern und ihre Wirkungauf die Gesundheit [Task and customer-related job con-ditions in call centres and their effect on well-being].Hamburg, Germany: Verwaltungs-Berufsgenossenschaft.

Joreskog, K. G., & So¨rbom, D. (1993).LISREL 8. Chicago:Scientific Software, Inc.

Judge, T. A., & Bretz, R. D. (1992). Effects of work valueson job choice decisions.Journal of Applied Psychology,77, 261–271.

Kanner, A. D., Coyne, J. C., Schaefer, C., & Lazarus, R. S.(1981). Comparison of two modes of stress measure-ment: Daily hassles and uplifts versus major life events.Journal of Behavioral Medicine, 4, 1–39.

Katz, D., & Kahn, R. L. (1978).The social psychology oforganizations. New York: Wiley.

Keashly, L. (1998). Emotional abuse in the workplace.Journal of Emotional Abuse, 1, 85–117.

Keashly, L., & Jagatic, K. (2003). By any other name:American perspectives on workplace bullying. In S. Ein-arsen, H. Hoel, D. Zapf, & C. L. Cooper (Eds.),Bullyingand emotional abuse in the workplace: Internationalperspectives in research and practice (pp. 31–61). Lon-don: Taylor & Francis.

Koeske, G. F., & Koeske, R. D. (1989). Construct validityof the Maslach Burnout Inventory: A critical review andreconceptualization.Journal of Applied Behavioral Sci-ence, 25, 131–144.

Kop, N., Euwema, M., & Schaufeli, W. (1999). Burnout,job stress and violent behaviour among Dutch police.Work & Stress, 13, 326–340.

Lazarus, R. S. (1999).Stress and emotion: A new synthesis.New York: Springer.

Lazarus, R. S., & Folkman, S. (1984).Stress, appraisal, andcoping. New York: Springer.

Leather, P., Beale, D., Lawrence, C., Brady, C., & Cox, T.(1999). Violence at work. Introduction and overview. InP. Leather, C. Brady, C. Lawrence, D. Beale, & T. Cox(Eds.),Work-related violence. Assessment and interven-tion (pp. 3–18). London: Routledge.

Lee, R. T., & Ashforth, B. E. (1996). A meta-analyticexamination of the correlates of the three dimensions of

80 DORMANN AND ZAPF

job burnout. Journal of Applied Psychology, 81,123–133.

Leiter, M. P. (1993). Burnout as a developmental process:Consideration of models. In W. Schaufeli, C. Maslach, &T. Marek (Eds.),Professional burnout: Recent develop-ments in theory and research (pp. 237–250). Washing-ton, DC: Taylor & Francis.

Leiter, M. P., & Maslach, C. (1988). The impact of inter-personal environment on burnout and organizationalcommitment. Journal of Organizational Behavior, 9,297–308.

Leiter, M. P., & Schaufeli, W. B. (1996). Consistency of theburnout construct across occupations.Anxiety, Stress,and Coping, 9, 229–243.

Lim, V. K. G., & Yuen, E. C. (1998). Doctors, patients, andperceived job image: An empirical study of stress andnurses in Singapore.Journal of Behavioral Medicine, 21,269–282.

Little, R. J. A., & Rubin, D. B. (1989). The analysis ofsocial science data with missing values.SociologicalMethods and Research, 18, 292–326.

Maslach, C. (1982).Burnout: The costs of caring. Engle-wood Cliffs, NJ: Prentice Hall.

Maslach, C., & Jackson, S. E. (1981). The measurement ofexperienced burnout.Journal of Occupational Behavior,2, 99–113.

Maslach, C., Jackson, S. E., & Leiter, M. P. (1996).Maslach Burnout Inventory manual (3rd ed.). Palo Alto,CA: Consulting Psychologists Press.

Morris, J. A., & Feldman, D. C. (1996). The dimensions,antecedents, and consequences of emotional labor.Acad-emy of Management Journal, 21, 986–1010.

Muraven, M., & Baumeister, R. F. (2000). Self-regulationand depletion of limited resources: Does self-controlresemble a muscle?Psychological Bulletin, 126,247–259.

Nerdinger, F. W. (1994).Zur Psychologie der Dienstleis-tung [On the psychology of services]. Stuttgart, Ger-many: Scha¨ffer-Poeschel.

Paoli, P. (1997).Second European Survey on Working Con-ditions 1996. Dublin, Ireland: European Foundation forthe Improvement of Living and Working Conditions.

Potter, B. A. (1983). Job burnout and the helping profes-sional.Clinical Gerontologist, 2, 63–65.

Rafaeli, A., & Sutton, R. I. (1990). Busy stores and demand-ing customers: How do they affect the display of positiveemotions? Academy of Management Journal, 33,623–637.

Ravlin, E. C., & Meglino, B. M. (1987). Effects of values onperception and decision making: A study of alternativework values measures.Journal of Applied Psychology,72, 666–673.

Savicki, V., & Cooley, E. J. (1982). Implications of burnoutresearch and theory for counselor educators.Personnel &Guidance Journal, 60, 415–419.

Schafer, J. L. (1997).Analysis of incomplete multivariatedata. London: Chapman & Hall.

Schaubroeck, J., & Jones, J. R. (2000). Antecedents ofworkplace emotional labor dimensions and moderators oftheir effects on physical symptoms.Journal of Organi-zational Behavior, 21, 163–183.

Schaufeli, W. B., & Enzmann, D. (1998).The burnoutcompanion to study and practice: A critical analysis.London: Taylor & Francis.

Schaufeli, W. B., Leiter, M. P., Maslach, C., & Jackson,S. E. (1996). Maslach Burnout Inventory—General Sur-vey. In C. Maslach, S. E. Jackson, & M. P. Leiter (Eds.),Maslach Burnout Inventory manual (3rd ed., pp. 19–26).Palo Alto, CA: Consulting Psychologists Press.

Schaufeli, W. B., Maslach, C., & Marek, T. (Eds.). (1993).Professional burnout: Recent developments in theory andresearch. Washington, DC: Taylor & Francis.

Schneider, B., & Bowen, A. E. (1985). Employee andcustomer perceptions of the service in banks: Replicationand extension.Journal of Applied Psychology, 70,423–433.

Scholz, K. (2001).Dienstleistungsklima und seine person-alen Folgen: Organisationale Voraussetzungen fur gutenService [Service climate and its consequences for per-sonnel: Organizational requirements for good service].Wiesbaden, Germany: Gabler.

Schonfeld, I. S. (1992). A longitudinal study of occupa-tional stressors and depressive symptoms in first-yearfemale teachers.Teaching and Teacher Education, 8,151–158.

Schwartz, J. E., & Stone, A. A. (1993). Coping with dailywork problems. Contributions of problem content, ap-praisals, and person factors.Work & Stress, 7, 47–62.

Semmer, N. K. (2000). Control at work: Issues of specific-ity, generality, and legitimacy. In W. J. Perrig & A. Grob(Eds.), Control of human behavior, mental processes,and consciousness—Essays in honour of the 60th birth-day of August Flammer (pp. 555–574). Mahwah, NJ:Erlbaum.

Semmer, N., & Schallberger, U. (1996). Selection, social-isation, and mutual adaptation: Resolving discrepanciesbetween people and work.Applied Psychology: An In-ternational Review, 45, 263–288.

Semmer, N. K., Zapf, D., & Dunckel, H. (1995). Assessingstress at work: A framework and an instrument. In O.Svane & C. Johansen (Eds.),Work and health: Scientificbasis of progress in the working environment (pp. 105–113). Luxembourg: Office for Official Publications of theEuropean Communities.

Semmer, N. K., Zapf, D., & Dunckel, H. (1999). Instrumentzur Stressbezogenen Ta¨tigkeitsanalyse ISTA [Instrumentfor stress-related job analysis]. In H. Dunckel (Ed.),Handbuch psychologischer Arbeitsanalyseverfahren[Handbook of psychological job analysis instruments](pp. 179–204). Zu¨rich, Switzerland: vdf Hochschulverlag.

Semmer, N. K., Zapf, D., & Greif, S. (1996). “Shared jobstrain”: A new approach for assessing the validity of jobstress measurements.Journal of Occupational and Or-ganizational Psychology, 69, 293–311.

Siegrist, J. (2000). Adverse health effects of effort-rewardimbalance at work: Theory, empirical support, and im-plications for prevention. In C. L. Cooper (Ed.),Theoriesof organizational stress (pp. 190–204). Oxford, UK:Oxford University Press.

Spector, P. E. (1987). Interactive effects of perceived con-trol and job stressors on affective reactions and healthoutcomes for clerical workers.Work & Stress, 1,155–162.

Spector, P. E., Dwyer, D. J., & Jex, S. M. (1988). Relationof job stressors to affective, health, and performanceoutcomes: A comparison of multiple data sources.Jour-nal of Applied Psychology, 73, 11–19.

Spector, P. E., & Jex, S. M. (1998). Development of four

81CUSTOMER-RELATED SOCIAL STRESSORS

self-report measures of job stressors and strain: Interper-sonal Conflict at Work Scale, Organizational ConstraintsScale, Quantitative Workload Inventory, and PhysicalSymptoms Inventory.Journal of Occupational HealthPsychology, 3, 356–367.

Stemmler, G. (1997). Selective activation of traits: Bound-ary conditions for the activation of anger.Personalityand Individual Differences, 22, 213–233

Tepper, B. J. (2000). Consequences of abusive supervision.Academy of Management Journal, 43, 178–190.

Winefield, H. R. (2003). Work stress and its effects ingeneral practitioners. In M. F. Dollard, A. H. Winefield,& H. R. Winefield (Eds.),Occupational stress in theservice professions (pp. 187–207). London: Taylor &Francis.

Zapf, D. (2002). Emotion work and psychological well-being. A review of the literature and some conceptualconsiderations.Human Resource Management Review,12, 237–268.

Zapf, D., Bechtoldt, M., & Dormann, C. (in press). Instru-ment zur Stre�bezogenen Arbeitsanalyse (ISTA), Frage-bogen Version 6. 0 [Instrument for stress-related jobanalysis (ISTA) questionnaire version 6.0].Zeitschrift furArbeits- und Organisationspsychologie.

Zapf, D., Dormann, C., & Frese, M. (1996). Longitudinalstudies in organizational stress research: A review of theliterature with reference to methodological issues.Jour-nal of Occupational Health Psychology, 1, 145–169.

Zapf, D., & Frese, M. (1991). Soziale Stressoren am Ar-

beitsplatz und psychische Gesundheit [Social stressors atwork and psychological health]. In S. Greif, E. Bamberg,& N. Semmer (Eds.),Psychischer Stre� am Arbeitsplatz[Psychological stress at work] (pp. 168–184). Go¨ttingen,Germany: Hogrefe.

Zapf, D., & Gross, C. (2001). Conflict escalation and copingwith workplace bullying: A replication and extension.European Journal of Work and Organizational Psychol-ogy, 10, 497–522.

Zapf, D., Knorz, C., & Kulla, M. (1996). On the rela-tionship between mobbing factors, and job content,social work environment and health outcomes.Euro-pean Journal of Work and Organizational Psychology,5, 215–237.

Zapf, D., Seifert, C., Schmutte, B., Mertini, H., & Holz, M.(2001). Emotion work and job stressors and their effectson burnout.Psychology and Health, 16, 527–545.

Zapf, D., Vogt, C., Seifert, C., Mertini, H., & Isic, A.(1999). Emotion work as a source of stress: The conceptand development of an instrument.European Journal ofWork and Organizational Psychology, 8, 371–400.

Zeithaml, V. A., & Bitner, M. J. (2000).Service marketing:Integrating customer focus across the firm. Boston:McGraw-Hill.

Received April 8, 2002Revision received September 15, 2003

Accepted September 16, 2003y

82 DORMANN AND ZAPF