JAGDIP SINGH and GARY K. RHOADS*

Though marketers have begun to use the role ambiguity construct in understand-

ing the boundary role phenomenon, several researchers have noted that extant mea-

sures of role ambiguity are deficient because they do not represent the breadth (or

multidimensionality) of the underlying construct. Building on previous work, the au-

thors develop a mu/f/dimensional, mi/Maceted, 45-item role ombiguity construct

(MULTIRAM) by delineating ot a dimensional level the various role ambiguities per-

ceived salient by marketing-oriented boundary spanners such as salespeople and

customer service personnel. Using data from multiple samples, they provide evidence

for reliability, stability, and convergent and discriminant validity for the seven facets

of the MULTIRAM construct. Their analysis further reveals that Rizzo, House, and

Lirtzman's global measure of role ambiguity underidentifies the role ambiguities faced

by boundary spanners. Finally, the authors examine selected correlates and con-

sequences of the MULTIRAM facets. The findings indicate that the MULTIRAM facets

have nomological validity and depict differential relationships with the various cor-

relates and consequences examined. Several implications for managers and re-

searchers are discussed, and directions for future research are provided.

Boundary Role Ambiguity in Marketing-OrientedPositions: A Multidimensional, MultifacetedOperationalization

Marketers are interested in applying role theory to un-derstand a wide range of psychological (e.g., job satis-faction) and behavioral (e.g., performance) dimensionsof a boundary spanner's job (Behrman, Bigoness, andPerreault 1981; Ford, Walker, and Churchill 1975). Inparticular, researchers have found that role variables suchas ambiguity, conflict, and inaccuracy offer a promising

•Jagdip Singh is Associate Professor of Marketing, WeatherheadSchool of Management, Case Western Reserve University. Gary K.Rhoads is Assistant Professor of Marketing, College of Business, IdahoState University.

The research was made possible by a grant from the MarketingScience Institute. The authors thank Sales and Marketing ExecutivesInternational and participating MSI companies for their assistance inconducting the various surveys. Roy D. Howell's helpful commentson the manuscript are also appreciated. A longer version, with moredetails on data collection procedures, sample characteristics, analyt-ical methods used, and results obtained, is available from the authors.

avenue for studying myriad boundary-spanning roles ofmarketing personnel who operate at the periphery of theorganization, including salespersons, customer servicerepresentatives, and industrial buyers. Despite this in-terest, several critiques of the research have surfaced re-cently (e.g.. King and King 1990). Specifically, the cri-tiques have questioned the nearly sole reliance on a limitedset of measures (e.g., the scales of Rizzo, House, andLirtzman 1970) of equivocal construct validity. For in-stance. King and King noted that, despite their wide-spread use, the Rizzo, House, and Lirtzman (RHL) mea-sures have shortcomings because the scale items (1) lackclarity and precision, (2) ignore the multidimensionalityof the underlying construct, (3) fail to represent the breadthof the role concepts, and (4) have poor discriminability.Interestingly, though marketers have been in the fore-front in developing alternative measures of role conflictand ambiguity (cf. the pioneering work of Ford, Walker,and Churchill 1975), they still are preoccupied with eitherusing global measures or aggregating the multidimen-sional scale to represent an overall measure.

328

Journal of Marketing ResearchVol. XXVin (August 1991), 328-38

BOUNDARY ROLE AMBIGUITY 329

We address some of the preceding concerns for therole ambiguity construct. We study a single variable indepth rather than a wide range of role constructs becausethat approach is likely to yield a more thorough under-standing of the focal concept. Several reasons dictatedour choice of role ambiguity. First, role ambiguity is animportant concept in role theory as well as in path-goaltheory of leadership. To the extent that marketers areinterested in path-goal theory, our study serves multipleconstituencies. Second, of all role concepts, role ambi-guity has received perhaps the most criticism. For in-stance. King and King (1990, p. 57) observe that con-ceptualization and operationalization "issues for roleambiguity [are] of greater concern." Third, in compar-ison with role conflict, role ambiguity is more amenableto managerial "intervention"—that is, implementingprograms that diminish boundary role ambiguity is rel-atively less difficult. Fourth, studies involving role am-biguity have yielded inconsistent results. Because suchinconsistencies may stem from "deficiencies in mea-surement" (King and King 1990), a focused study of therole ambiguity construct may provide clues to such con-tradictory findings.

The specific purpose of our study is to address someof the noted shortcomings of the current measures of roleambiguity by developing a ww/rifaceted, multidim&n-sional role ambiguity or MULTIRAM construct. We seekto delineate at a dimensional level the various compo-nents of role ambiguity perceived salient by boundaryspanners in marketing-oriented positions. Hence, we donot attempt to develop a unidimensional role ambiguityconstruct. Rather, we aim to capture the breadth of thefocal construct by examining its distinct and diverse di-mensions. In doing so, we build on previous work by(1) further refining and enhancing the conceptual domainof role ambiguity, (2) developing the MULTIRAM scaleto measure role ambiguity, and (3) providing evidenceofthe scale's psychometric properties. A notable featureof our study is that the MULTIRAM construct is devel-oped and validated by using data from multiple boundaryspanners (e.g., customer service representatives andsalespeople) in different organizational contexts (e.g.,medium- and large-sized firms). This variability, we be-lieve, is useful in determining MULTIRAM's general-izability. We begin with a brief review of the literature.

BOUNDARY SPANNERS AND ROLE AMBIGUITY

Role theory provides a rich conceptual framework forexplaining the importance of role ambiguity as an inter-vening variable between various job conditions and joboutcomes (Kahn et al. 1964). Kahn and his coauthorsdefined the term "role ambiguity" in a broad sense bynoting that (p. 73):

Role ambiguity is a direct function of the dis-crepancy between the information available to thejierson and that which is required for adequate per-formance of his role. Subjectively it is the differ-ence between his actual state of knowledge and that

which provides adequate satisfaction of his personalneeds and values.

Recendy, King and King (1990) elaborated on this con-ceptual definition by observing that four forms of am-biguity are likely to be critical in understanding the un-certainty in a role—ambiguity about (1) one's scope ofresponsibilities, (2) the role behaviors necessary to fulfillone's responsibilities, (3) role senders' expectations forvarious role behaviors, and (4) the consequences of one'sactions on the attainment of one's goals and the wellbe-ing of oneself, the role set, and the organization.

Kahn and his coauthors noted that some individualsare more likely to experience role ambiguity when they(1) cross boundaries, (2) produce innovative solutions tononroutine problems, and (3) experience diverse role ex-pectations and demands from inside and outside the or-ganization. These individuals, called "boundary span-ners," are persons who operate at the periphery of anorganization (e.g., salespeople, industrial buyers, cus-tomer service representatives). Furthermore, the authorsnoted that role ambiguity leads to stress because con-cerns about how to proceed with critical tasks lead tofrustration, which in turn results in tension. In addition,role ambiguity is thought to impede the ability to im-prove performance and obtain rewards, thus reducing jobsatisfaction.

Though theoretical bases for role ambiguity have beenwell explicated, few researchers have attempted to mea-sure the breadth of role ambiguity as defined by Kahnand his coauthors and elaborated by King and King (1990).According to Jackson and Schuler (1985), 85% of allrole research studies use the 6-to-12-item scale of Rizzo,House, and Lirtzman (RHL). This instrument capturesunidimensional ambiguity perceptions about the overallor global ambiguity associated with one's role. Despiteits widespread use, researchers are uncertain whetherRHL's measure can possibly capture the breadth of roleambiguity reflected in the complex domain of boundary-spanning roles. Unfortunately, few alternative multidi-mensional measures of role ambiguity have been devel-oped and examined for reliability and validity. A notedexception is found in marketing. Specifically, Ford,Walker, and Churchill (1975) and Chonko, Howell, andBellenger (1986) have explored the various facets of roleambiguity—company, sales manager, customer, andfamily. T'heir efforts have provided insight into the am-biguities experienced by industrial salespeople, but littleis known about the psychometric properties of the in-struments. Thus, whether boundary spanners can dis-criminate empirically among what researchers see asconceptually distinct facets of role ambiguity is un-known. Likewise, in the face of inconsistent findings,researchers surmise that current role ambiguity measuresmay be unfit for use in boundary-spanning contexts (Kingand King 1990). To address these gaps, we sought torefine and enhance the role ambiguity construct by a three-step approach, summarized in Figure 1. We discuss eachstep in turn.

330 JOURNAL OF MARKETING RESEARCH, AUGUST 1991

Figure 1

METHOD OF ANALYSIS USED FOR DEVELOPING THE

ROLE AMBIGUITY (MULTIRAM) CONSTRUCT

Step I: Domain Specilication

•Refine and Enhance the Construct Domain:Identify its Distinct Facets and Dimensions

•Generate Items for Each Facet and Dimension•Pretest Items with Focus Groups

Collect SME Data

Step H: Scale Refinement

I lr̂ l ()iili.T \IMI\MS

•Exploratory Factor Analysis•Isolate Dimensions for each Facet•Compute Reliabilities

Second Order Analysis•Restricted Factor Analysis•Isolate Distinct Facets•Examine Reliabilities, Variance Extracted, etc.•Examine Convergent and Discriminant Validity

ICollect IS Data

Step III: Scale Validation

•Confirmatory First Order Analysis•Confirmatory Second Order Analysis•Convergent and Discriminant Validity•Nomological Validity

STEP IDOMAIN SPECIFICATION: INITIALDEVELOPMENT AND PRETESTING

Tbe cooperation of an office equipment supplier wassougbt for tbis phase of the study. In all, six focus groupsconsisting of six to eight persons eacb (two witb sales-

people and four with customer service representatives)were conducted during regular business hours. Eacb groupwas informed that tbe aim was to understand (1) the var-ious ambiguities they perceived to be salient in perform-ing tbeir role and (2) how such ambiguities affect tbeirjob conditions and perfomiance. In addition, face-to-facediscussions were conducted individually witb somesalespeople and managerial personnel. Tbe focus groupdiscussions were tape-recorded; bowever, all partici-pants were promised confidentiality.

Tbe analysis of focus group/individual discussions in-dicated tbat enbancement of the conceptual domain ofrole ambiguity was warranted. In particular, our analysisconfirmed previous fmdings tbat boundary spanners' roleambiguity about tbeir (1) company and top management(e.g., policies and procedures), (2) boss (e.g., perfor-mance evaluation, support), (3) customers (e.g., ser-vice), and (4) family (e.g., time spent on job) is salientand likely to be critical in tbeir performance. Furtber-more, tbis analysis revealed additional facets of role am-biguity—specifically, about (5) managers in otber (tbantbeir own) departments, (6) coworkers, and (7) etbicalconduct on tbe job (e.g., in interacting with customers).These additional facets are consistent witb researcb find-ings suggesting tbat boundary spanners interact witb otherdepartments and, in some situations, with tbeir cowork-ers in performing effectively on tbe job. Likewise, etb-ical issues are known to be critical in boundary role po-sitions and are likely to be problematic because no "certainand sure" guidelines are available (in most companies)for sucb situations (Bellizzi and Hite 1989).

In addition, the focus group revealed tbat at least someof tbe role ambiguity facets are likely to be complex inand of tbemselves. For instance, several different com-ments were categorized under company policies and topmanagement ambiguity, ranging from promotional cri-teria to bandling of nonroutine activities on the job.Likewise, tbe boss facet included multifold remarksranging from tbe support provided to meeting demands.This complexity has two major implications. First, itsuggests that, at least for some facets, a large set of itemsis needed to capture the richness inherent in eacbfacet. Second, it suggests tbat, to circumscribe tbeMULTIRAM construct properly, it is important to in-clude an intermediate conceptual level (which we referto as "facets") between the global definition of role am-biguity and its various dimensions. For instance, ambi-guity associated with the company is viewed properly asa facet of tbe global role ambiguity construct; bowever,tbis facet itself may be composed of several dimensions.Therefore, we use tbe following operational definition.

Perceived role ambiguity is a /wM/ndimensional,ww/rifaceted evaluation about the lack of salient in-formation needed to perform a role effectively. Spe-cifically, this evaluation may include ambiguity aboutrole definition, expectations, responsibilities, tasks,and behaviors in one or more facets of the task en-vironment. These facets, in tum, reflect one or moremembers of the boundary spanner's role set (e.g..

BOUNDARY ROLE AMBIGUITY 331

customer, boss) and/or activities required to per-form a role (e.g., ethical conduct). Finally, each facetmay itself be viewed as a multidimensional evalu-ation of the ambiguity about that facet.

Following King and King, in tbis definition we view roleambiguity as the salient uncertainties faced by boundaryspanners in performing tbeir role and embrace the entiredomain of role ambiguity as defined by its various forms.In addition, we build on previous research of Ford,Walker, and Cburcbill (1975) and Cbonko, Howell, andBellenger (1986) by refming (i.e., by considering tbeglobal, facet, and dimensional levels) and enhancing (i.e.,by considering additional facets) previous definitions ofrole ambiguity. Operationally, we used the qualitativedata from focus groups to generate items for tbeMULTIRAM constnict. In all, 55 items were developed.We refmed tbe items by administering them to two groupsof personnel (one group composed of salespeople andtbe other of customer service representatives) and ob-taining feedback. On the basis of tbis feedback, we de-leted five redundant items and fiirtber refined some items.Tbe items retained for further analysis were (1) com-pany/top management, 14 items, (2) boss, 9 items, (3)customers, 8 items, (4) family, 4 items, (5) otber man-agers, 4 items, (6) coworkers, 5 items, and (7) ethicalconduct, 6 items. These items served as input to step IIanalysis.

STEP IISCALE REFINEMENT: SALES AND MARKETING

EXECUTIVES (SME) STUDY

Sample

The sample was selected from U.S.-based membersof the Association of Sales and Marketing Executives(SMEs). SMEs occupy sales and marketing positions inrelatively small to medium-sized firms. In all, 2000members in four states (Minnesota, Nortb Carolina, Obio,and Texas) were selected at random. About 150 selectedmembers (7.5%) bad eitber moved or were no longerwitb tbe company. Hence, tbe effective sample was 1850.Eacb selected member was sent a prenotification card,two questionnaire packets, and a reminder card. In all,518 responses were obtained for a response rate of 28%;472 were usable (usable response rate = 25.5%).

Analysis Strategy

In a meta-analysis, Cburcbill and Peter (1984, p. 370)suggest tbat tbe conventional scale development processis likely to favor selection of "items [wbich] are so sim-ilar [to eacb otber] tbat tbey underidentify constructs."Consequently, we used a scale refinement process (seeFigure 1) tbat placed empbasis on retaining tbe "ricb-ness" or breadtb of the focal constnict through use offirst-order and second-order analysis. In tbe first-orderanalysis, we separately analyzed eacb of the sevenMULTIRAM facets by means of exploratory factor anal-

ysis (EFA), which belped ascertain tbe dimensionalityand factor structure for eacb of tbe seven facets. Onceacceptable dimensions were obtained, second-orderanalysis was perfonned. It involved examining wbetbertbe seven facets obtained in step I provided an acceptablemodel for tbe intercorrelations among the dimensionsderived from first-order analysis. Recall tbat tbe second-order factors are at an intermediate conceptual level be-tween tbe global constnict and its many distinct dimen-sions. Hence, the second-order factors are useful forfurther analysis because tbey retain some of the breadtbof the underlying construct under a relatively parsimon-ious structure. Restricted factor analysis (RFA) viaLISREL 7 (Joreskog and Sorbom 1988) was used to ex-ecute the second-order analysis. As RFA allows system-atic constraints on the relationships between the dimen-sions and intermediate facets, it is possible to specifytbat a particular dimension is a unique "measure" of aspecific facet (i.e., cross-loadings are zero). Tbe use ofLISREL 7 bas anotber important advantage—it providesa systematic basis for evaluating the "goodness" of thevarious models investigated. Such evaluations were basedon and implemented in accord with the work of Bagozziand Yi (1988).

First-Order Results

The Appendix lists the items selected for each dimen-sion and eacb facet on the basis of first-order analysisand summarizes tbe results by providing tbe dominantloading for eacb item and Cronbacb's a for each di-mension. In addition, the composite reliabilities andvariance extracted for eacb facet are provided. The ini-tial EFA for the 14 company items indicated that twoitems were inconsistent witii the remaining items and threeadditional items cross-loaded on two or more factors.The EFA was rerun after deletion of those items. Tbescree plot for tbe nine company items indicated a clearbreak after tbe tbird value, suggesting tbe presence oftbree distinct factors tbat explain more than 74% of tbetotal variance. Upon oblique rotation, a clear factorstructure was obtained. Specifically, all items bad adominant loading (i.e., s ±.30) on a single factor andcross-loadings were mostly significant with their differ-ences from the dominant loading > . 10 in absolute value.The three dimensions were labeled "flexibility," "work,"and "promotion." Tbe flexibility dimension (two items)taps a boundary spanner's ambiguity about the amountof flexibility be or sbe bas in performing various roleactivities. The ambiguity about tbe quantity and tbepriority of tbe various tasks tbat must be performed iscaptured by tbe work dimension (four items). The pro-motion dimension (tbree items) reflects a boundary span-ner's ambiguity about tbe requirements for promotion.In addition, the flexibility, work, and promotion dimen-sions bave acceptable levels of reliability, witb Cron-bacb's a estimated as .70, .84, and .75, respectively.Finally, the intercorrelations among the three dimensionsare between .58 and .49, suggesting tbat the dimensionsare probably distinct.

332 JOURNAL OF AAARKETING RESEARCH, AUGUST 1991

The EFA for the nine boss items indicated tbe pres-ence of two distinct factors, which were labeled "sup-port" and "demands" dimensions. Tbe support dimen-sion (four items) appears to measure ambiguity about tbesupport one is likely to receive from tbe boss. In con-trast, the demands dimension (five items) captures theambiguity about tbe boss's expectations for various roletasks. The intercorrelation between the two dimensionsis .76, indicating that tbe two dimensions are closely re-lated but not redundant. Cronbaeh's a for each dimen-sion is .86.

The EFA results for the eight customer items showeda clear break after the third eigenvalue, suggesting tbepresence of three factors that explain more than 75% oftbe total variance. The tbree factors were labeled "in-teraction," "objection," and "presentation." Tbe inter-action dimension (tbree items) appears to measureboundary spanners' ambiguity about bow to interact withvarious customers, whereas the objection dimension (tbreeitems) taps their ambiguity about bow to address cus-tomers' objections. Finally, the presentation dimension(two items) seems to capture boundary spanners' am-biguity about the product benefits and/or companystrengths tbat tbey should present to the customers. Theintercorrelations among the tbree dimensions range from.69 to .57, supporting the view that these dimensions arelikely to be nonredundant. Furthermore, Cronbacb's afor tbe interaction, objection, and presentation dimen-sions is .78, .81, and .81, respectively.

Next, we examined tbe EFA results for tbe six etbicalitems. For tbese items, tbe "break-in-eigenvalues" cri-terion indicated tbe presence of two factors. Tbe firstfactor appears to represent an external dimension—thatis, boundary spanners' ambiguity about ethical situationsthat arise in tbeir role transactions witb partners outsidethe company. In contrast, the intemal dimension appearsto capture tbe corresponding ambiguity in relation to rolepartners inside the company. The intercorrelation be-tween tbe two dimensions is only .44, indicating thatthese dimensions are largely distinct. Both dimensionshave acceptable reliability, witb Cronbacb's a of .90(external) and .83 (intemal).

For tbe remaining tbree facets (i.e., otber managers,coworkers, and family), the EFA for each facet indicatedtbe presence of a single dominant factor. This single fac-tor explained more tban 67% of the total variance foreach of tbe tbree facets. Without exception, the itemloadings were high and significant on the single factorextracted. Consistent witb tbis finding, Cronbacb's a fortbese facets is significant and large, ranging from .87 to.88. The implication is that, at least on tbe basis of theoperational items used here, tbe otber managers, co-workers, and family facets cannot be reduced furtber intodimensions and bence are probably unidimensional.

Second-Order ResultsRecall tbat this analysis involves restricted factor anal-

ysis (RFA) of the dimensions obtained in tbe first-order

analysis. Consistent witb tbis approacb, a restricted modelwas posited sucb tbat the items belonging to individualdimensions of tbe company, boss, customer, and ethicalfacets were summed and used as indicators of tbeir re-spective facets. This approacb of using first-order di-mensions (e.g., flexibility, work, etc.) as "indicators"of a second-order factor (e.g., company) rather than asimultaneous estimation of first- and second-order fac-tors appears justified because of the sample size require-ments and tbe sbeer size of tbe problem (i.e., 45 X 45matrix). Moreover, because at least two indicators areneeded to model measurement error for tbe individualfacets, tbe items for tbe remaining tbree facets (i.e., othermanagers, coworkers, and family) were split systemat-ically into two groups of equal size wherever possible.Tbe second-order model is restricted in tbe sense thatindicators are posited to be measures of one and onlyone facet of role ambiguity.

The RFA produced tbe following statistics: x̂ = 186.6,d.f = 83, GFI = .99, AGFI = .99, and RMR = .029.Additionally, the normed fit index (NFI) was .99. Con-sistent with Bagozzi and Yi's criteria, these statisticssuggest tbat tbe bypothesized second-order model witbseven facets is a reasonably good representation of tbeSME data. Nevertheless, residuals were examined toevaluate the "goodness" of tbe hypothesized model. Ofthe 120 observed intercorrelations (all of wbicb are sig-nificant atp = .01), 99% of the fitted residuals are lesstban . 10 (in absolute value), and more tban 95% of tbemare smaller tban .05 in absolute value. Tbis finding sug-gests that the seven facets are able to reproduce most ofthe observed intercorrelations among tbe role ambiguitydimensions. Hence, it appears that tbe a priori bypotb-esized seven facets are central aspects of tbe MUL-TIRAM constnict and tbe measures of tbe individual fac-ets are relatively "clean" and reliable.

Additional evidence in support of tbe preceding resultsis forthcoming from the data. First, all loadings are sig-nificant atp = .05 (i.e., T-value > 2.0). Second, notein tbe Appendix tbat eacb facet bas a composite reli-ability of .70 or higher, witb the exception of the ethicaldimension for which the reliability is borderline. Tbird,tbe intercorrelations among tbe facets reveal tbat noneof tbem is redundant. In general, the facet intercorrela-tions range from .85 to .32, witb an average of .58.Fourtb, tbe variance extracted by each facet (Appendix)exceeds .50, indicating tbat eacb facet has acceptablevalidity (Bagozzi and Yi 1988).

Finally, tbe convergent and discriminant validity ofthe individual facets is supported when the facets arecorrelated witb Rizzo, House, and Lirtzman's (1970)measure of role ambiguity and role conflict (see first tworows in Table 1). Tbe table sbows tbat for SME data,tbe correlations of role ambiguity facets witb RHL's roleambiguity measure are consistently bigber than their cor-responding correlations witb role conflict. For instance,tbe company facet correlates .69 witb RHL's role am-biguity, but only .50 witb role conflict. Tbis finding is

BOUNDARY ROLE AMBIGUITY 333

Table 1CONVERGENT, DISCRIMINANT, AND NOMOLOGICAL VALIDITY OF THE MULTIRAM FACETS: RESULTS FROM

CORRELATIONAL ANALYSIS OF RHL's ROLE VARIABLES AND SELECTED CORRELATES AND CONSEQUENCES OF

ROLE AMBIGUITY

~ ~ MULTIRAM facets

Company Boss Customer EthicalOther

managersCowork-

ers Family

Convergent and discriminant validity: Rizzo, House, and Lirtzman's (1970) role variablesFirst-order correlations from SME data

Role ambiguity' .69*** .69*** .45*** .35***Role conflict' .50*** 49*** .31*** .23***

First-order correlations from IS dataRole ambiguity' .61*** .63*** .34*** 22***Role conflict" .43*** .31*** .32*** .15*

Nomological validity: correlates^Experience" -.17*** - .08*Education" .08* .03Sex" .13** .09Locus of control" .22*** .22***

Nomological validity: consequences*"Job satisfaction" -.60*** -.64***Job performance" -.34*** -.25***Job tension" .51*** .50***Turnover intentions" .52*** .50***

-.14**.06.06.15**

-.42***-.43***

.34***

.25***

- .05- .05

.10*

.11*

.30***

.27***

.29***

.31***

.41***

.36***

.46***

.14*

.12**

.01

.07

.27***

- . 41***-.28***

.37***

.27***

.42***

.26***

.42***

.30***

.08*

.00

.10*

.25***

.39***

.27***.31***.22***

.22***

.10*

.18**

.10

.10*

.04

.02

.13**

.23***

.21***

.19***

.10*"All values for this variable are Pearson product moment correlations."All values are from SME data only. Because of space limitations, results from IS data are not reported.'AH values for this variable are point biserial correlations.*p < .05.**p < .01.***p < .001.

indicative of the discriminant validity of the role ambi-guity facets. In addition, the role ambiguity facets havelarge, positive, and significant correlations with RHL'srole ambiguity measure. This fmding is indicative of theconvergent validity of the ambiguity facets. However,the results indicate that RHL's measure of role ambi-guity is likely to underidentify the role ambiguities facedby boundary role personnel because it appears to bealigned more closely with the company and boss facets.With the other five facets, RHL's measure shares lessthan 21% of the individual variance (range: customer20.2% to family 4.8%).

STEP inSCALE VAUDATION: INDUSTRIAL SAMPLE (IS)

STUDYBecause the facets uncovered in the preceding analysis

may have capitalized on chance (as the RFA is based onfirst-order exploratory analysis), a followup study withan industrial sample was conducted in step III to obtainconfirmatory evidence.

Sample

The sample was drawn from two divisions of a U.S.-based Fortune 500 industrial manufacturer. The bound-

ary spanners sampled were (1) marketing and salespersonnel who were mainly responsible for meetingdivision's sales objectives and (2) customer service staffwho were responsible for providing technical, installa-tion, and other necessary services. From the two divi-sions, 520 personnel were selected for participation. Us-able responses from 216 individuals were obtained for ausable response rate of 41.5%. In contrast to the SMEsample, however, the industrial sample representsboundary spanners in a large, diversified, multinational,industrial corporation. This difference in job contexts islikely to afford a more rigorous and insightful analysisof the MULTIRAM construct.

Analysis Strategy

To examine MULTIRAM's validity, we conductedthree confirmatory analyses. Initially, first-order analy-sis was perfonned via confirmatory factor analysis (CFA)by hypothesizing a priori the dimensions expected sep-arately for each facet. These hypotheses were based onSME data results; for instance, for the company facet,three dimensions were posited with a loading pattem inaccord with that in the Appendix. In addition, the pattemwas constrained so that each item loaded on one and onlyone dimension, with cross-loadings set to zero. Next, the

334 JOURNAL OF MARKETING RESEARCH, AUGUST 1991

second-order factors obtained from SME data were sub-jected to validation analysis, which involved performingCFA by positing a priori seven distinct facets with cross-loadings constrained to zero. Both analysis were exe-cuted by using LISREL 7. Finally, the reliability, vari-ance extracted, and discriminant and convergent validityfor each of the facets obtained from IS data were ex-amined. This analysis was analogous to that used for SMEdata.

First-Order Validation

The CFA results for each of the facets reveal that thefit of the data to the a priori hypothesized dimensionsranges from reasonably good (i.e., boss facet x^ = 75.4,d.f. = 26, GFI = .93, AGFI = .88, RMR = .04, NFI= .94) to very good (i.e., family facet x^ = 95, d.f. =2, GFI = .99, AGFI = .99, RMR = .01, NFI = .99).Such a conclusion appears justified because (1) the GFIand the NFI exceed .90 for all models, indicating thatmost of the intercorrelations are "explained," (2) theAGFI, though known to be a more conservative indi-cator (cf. Bagozzi and Yi 1988, p. 79), approaches orexceeds .90—the cutoff value suggested for "good"models—and (3) the RMR is .05 or less for all models,indicating that residuals are mostly small and insignifi-cant. In addition, all loadings are large and significant(at/7 ^ .01), and the various parameter estimates (e.g.,error variances, latent correlations) are within their log-ical bounds. Hence, the hypothesized dimensions basedon SME data (see Appendix) appear to be valid andmeaningful underlying latent variables that faithfully re-produce the intercorrelations among the MULTIRAMitems. These dimensions were then subjected to second-order validation.

Second-Order Validation

The CFA analysis for the a priori model of sevenMULTIRAM facets yields a x^ of 158.71 (d.f = 83, p< .001), indicating that there are statistical differencesbetween the reproduced and the observed intercorrela-tions. Because problems with the chi square statistic arewell known (Bagozzi and Yi 1988), other indicators forthe goodness of fit are given greater prominence. Whenother indicators are examined, the hypothesized structureappears to be a reasonably good fit to the IS data. Inparticular, the GFI exceeds .90 and the AGFI is .89.Consistent with this fmding, the RMR is only .046, im-plying that the residual intercorrelations are generallysmall. In addition, all hypothesized loadings are signif-icant atp = .01 and the solution does not yield any evi-dence for specification errors (e.g., negative variances),suggesting that the a priori posited structure (i.e., basedon SME data) results in a well-specified and reasonableempirical model. Further evidence in support of this modelwas obtained by examining the reliability, variance ex-tracted, and convergent and discriminant validity of theindividual MULTIRAM facets.

Reliability and Validity Analysis

The results of reliability and validity analysis revealthat the seven MULTIRAM facets are relatively distinct,have acceptable reliability, and individually extract sig-nificant variance (>.5O). Specifically, the intercorrela-tions range from .24 to .89, with an average of .50. Thesefindings suggest that none of the facets is redundant. Inaddition, the composite reliability for each facet exceeds.70, indicating that the first-order dimensions reliablymeasure the hypothesized facets. The only exception isthe ethical facet, for which the reliability is .66. Like-wise, the variance extracted for each facet meets the "50%or more" criterion (cf. Bagozzi and Yi 1988), implyingthat the MULTIRAM facets are meaningful and valid.

Table 1 (see third and fourth rows) provides additionalevidence for the discriminant and convergent validity ofthe MULTIRAM facets. First, note that each of the sevenfacets has a higher correlation with RHL's measure ofrole ambiguity than it has with role conflict. This findingis indicative of the discriminant validity of the facets.Second, for each facet, the correlation with RHL's roleambiguity is positive and statistically significant (at p =.01). This finding is suggestive of the convergent valid-ity of the MULTIRAM facets. Consistent with SME data,RHL's measure of role ambiguity is aligned more closelywith company and boss facets of role ambiguity than withthe other five facets. In this sense, RHL's role ambiguitymeasure is likely to underidentify the role ambiguitiesfaced by boundary role personnel.

Summary and Discussion

In sum, the evidence reported here appears sufficientto indicate that the 45-item MULTIRAM scale measuresseven facets and 13 dimensions of role ambiguity thatare theoretically meaningful, empirically distinct, stableacross subpopulations, and adequate to tap the breadthof role ambiguity in boundary spanners, hence warrant-ing additional research attention. Though our results ap-pear promising, additional construct validation researchto refine the measurement properties of MULTIRAMitems may be needed. First, the reliability and stabilityof the MULTIRAM facets and dimensions should be ex-amined in other subpopulations of boundary spanners andin cross-cultural situations. Second, there is a need tounderstand the discriminability of individual items andthe extent to which the breadth of the role ambiguityconstruct is measured (also referred to as "bandwidth")by applying latent trait theory methods to the MUL-TIRAM scale.

In comparison with the role ambiguity scale of Rizzo,House, and Lirtzman, the 45-item MULTIRAM scaleinvolves significant additional costs in practical use be-cause of (1) more items and hence more time/cost foradministration, response, and data coding, (2) morecomplexity of underlying structure and hence more time/cost for data analysis and interpretation, and (3) highopportunity costs for a fixed length of questionnaire.

BOUNDARY ROLE AMBIGUITY 335

However, our results suggest that the payoffs from thisincreased complexity include a deeper and more com-plete measurement of the role ambiguities faced byboundary spanners. Consequently, use of the MUL-TIRAM scale is likely to result in better descriptive un-derstanding of the ambiguities inherent in a boundaryperson's role (e.g., useful for diagnostic analysis). Whatis less clear at this stage is whether this increased de-scriptive understanding translates into greater substan-tive understanding by providing greater insights into theconsequences and correlates of role ambiguity in bound-ary spanners. Such payoffs in substantive understandingappear critical in shifting the cost/benefit equation in fa-vor of the more complex MULTiRAM scale. Though adetailed analysis ofthe MULTIRAM's potential for sub-stantive payoffs is beyond the scope of our study (how-ever, see authors' footnote), we provide some insightinto MULTIRAM's ability to enhance substantive un-derstanding via nomological validity analysis.

NOMOLOGICAL VALIDITY ANALYSIS

We investigated four correlates (i.e., experience, ed-ucation, sex, and locus of control) and four conse-quences (i.e., satisfaction, perfonnance, job tension, andturnover intentions) of role ambiguity to assess MUL-TIRAM's nomological validity. Previous meta-analyseshave revealed that the selected variables are related sig-nificantly to role ambiguity (Jackson and Schuler 1985).We discuss the hypothesized relationships and the resultsobtained from correlational analysis but, to conservespace, we report only results from SME data.

Experience

With increasing professional experience, ambiguityabout what various role members expect and how tasksmust be performed is likely to decline. Presumably, ex-perience helps a role incumbent to become more effi-cient in obtaining information as well as to accumulatea greater quantity of information from the job environ-ment. We assessed experience as the total number of yearsof professional experience.

Education

Overall, a positive but weak relationship between ed-ucation level and role ambiguity has been reported. Aplausible explanation is that role incumbents with higherlevels of education generally occupy higher positions inthe organization hierarchy and, at higher organizationallevels, role ambiguity is likely to be high. We assessededucation by using a 5-category scale: (1) high school,(2) 1 to 3 years of college, (3) college degree, (4) grad-uate school, and (5) master's or higher degree.

Sex

Female salespersons have been found to perceive sig-nificantly higher role ambiguity than their male col-leagues. A plausible reason for this finding is that female

salespeople may be less willing to ask for help and toask questions because of the fear of being perceived asincompetent. Such fear might interfere in their ability toobtain additional information that helps clarify their roles.

Locus of Control

Researchers have found that because "internals" tendto be better informed about their role and task environ-ment than "externals," they should experience less roleambiguity. We used a 12-item measure based on Rot-ter's (1966) work to examine this relationship.

Job Satisfaction

Previous studies show significant negative relationshipbetween job satisfaction and role ambiguity, with cor-relations of the order of - . 4 6 . We used a 26-itemmultidimensional scale for job satisfaction (pay, poli-cies, recognition, boss, coworkers, customers, and fam-ily; composite reliability = .93) to assess this relation-ship.

Job Performance

High role ambiguity is hypothesized to result in lowerperfonnance because, when boundary spanners lackknowledge about the most effective role behaviors, theirefforts are likely to be "inefficient, misdirected, or in-sufficient" (Jackson and Schuler 1985, p. 43). Empiricalsupport for this hypothesis is weak, with correlations ofthe order of - .24. We used a self-rating, 6-item measureof job performance (a = .76) to examine this relation-ship.

Job Tension

Role ambiguity is hypothesized to be related posi-tively to job tension because lack of salient informationneeded to perform a role results in frustration, and frus-tration leads to tension. We used a 7-item measure (typ-ical items were "I feel a lot of anxiety" and "I havefeelings of low self esteem") wherein boundary spannerswere asked how often (5-point scale) they had experi-enced the stated symptoms (a = .81).

Turnover Intentions

Turnover intentions are hypothesized to be relatedpositively to role ambiguity because boundary spannersare likely to find ambiguous roles less rewarding anddysfunctional, and hence are prone to seek alternative,less ambiguous, situations. Empirical results yield cor-relations of the order of .30. We used a 3-item measureof turnover intentions (typical item was "I often thinkabout quitting") (a = .93).

RESULTS

Table 1 shows the correlations between the MUL-TIRAM facets and the correlates and consequences. Interms of the correlates, note that all of the significantcorrelations are in the hypothesized direction. Specifi-

336 JOURNAL OF AAARKETING RESEARCH, AUGUST 1991

cally, (1) role ambiguity decreases with increasingprofessional experience, (2) female boundary spannersperceive higher role ambiguity than their male counter-parts, and (3) "externals" experience greater role am-biguity than "internals" in boundary-spanning roles. Forthe cases of education, the correlations are mostly weakand insignificant. However, the only significant corre-lation for education (with the company facet) is in thehypothesized direction as well; more educated boundaryspanners perceive greater company role ambiguity. Inaddition, Table 1 reveals that the MULTIRAM facetshave relatively stronger correlations with the locus ofcontrol correlate. Finally, the different MULTIRAM facetsappear to vary significantly in their relationships withdifferent correlates. For instance, the other managers andcoworker facets correlate strongly with locus of control,whereas the company and customer facets appear to beinfluenced more by professional experience. This evi-dence for differential relationships is important becauseit suggests that the seven MULTIRAM facets are distinctand measure inherently different ambiguities facing aboundary spanner.

The results from correlational analysis of conse-quences further support the nomological validity of theMULTIRAM facets. First, it is noteworthy that, withoutexception, all correlations between MULTIRAM facetsand examined consequences are significant and in thehypothesized direction. Higher role ambiguity uniformlyresulted in significantly and substantially (1) lower jobsatisfaction, (2) decreased job performance, (3) in-creased job tension, and (4) greater chances of turnover.Second, consistent with Jackson and Schuler's findingsfor role ambiguity, the MULTIRAM facets have rela-tively stronger relationships with the job satisfactionmeasure. Third, consistent with the findings obtained forcorrelates, the results for the consequences yield addi-tional evidence of differential relationships for the MUL-TIRAM facets. Note, for instance, that whereas job sat-isfaction is affected relatively strongly by company andboss role ambiguity (i.e., in comparison with other fac-ets), job performance is influenced more strongly bycustomer ambiguity.

Summary and Discussion

The motivation for the study of the correlates and con-sequences is to ascertain the nomological validity of theMULTIRAM scale. Hence, the preceding results shouldbe viewed neither as a hypothesis for, nor a test of, a"model" of role ambiguity with its antecedents and con-sequences. Rather, on the basis of previous research, wejudiciously selected a limited set of correlates and con-sequences for the sole purpose of assessing MULTI-RAM's nomological validity. The results of our studysupport nomological validity of the MULTIRAM facetsand indicate that the use of the MULTIRAM facets islikely to enhance our descriptive understanding of theambiguities faced by boundary spanners in marketing-oriented positions. Moreover, delineating role ambiguity

to its facet level can possibly contribute to substantiveadvancements in the area because of the MULTIRAMfacets' differential potency. We now outline several im-plications for researchers and practitioners, and offer someguidelines for use of the MULTIRAM scale.

IMPUCATIONS

Our study addresses some recent concerns about theconceptualization and operationalization of role ambi-guity. Specifically, we enhance previous work in the areaby identifying additional facets of role ambiguity. In par-ticular, we find theoretical and empirical support for threefacets (i.e., other managers, coworkers, and ethical con-duct) in addition to the four reported by Ford and hisassociates (i.e., company, boss, customer, and family).Furthermore, we offer a refinement of previous defini-tions by considering the global, facet (i.e., second-order), and dimensional (i.e., first-order) levels of eval-uation. Our empirical results suggest that boundaryspanners invoke conceptually meaningful and empiri-cally distinct evaluations at each level of the MUL-TIRAM construct.

Additionally, our results have meaningful implicationsfor practitioners and researchers. In terms of practice,managers of boundary spanners (e.g., sales managers)are likely to find the MULTIRAM instrument a usefultool for diagnosing the role ambiguities faced by theirsubordinates. Diagnostic information is accessible at thedimensional as well as the facet level such that managerscan more precisely pinpoint areas of concern and imple-ment remedial actions. For example, if a salesforce isnot performing well because of task ambiguity, use ofthe MULTIRAM scale might help the manager to as-certain that the customer facet (for example) yields highrole ambiguity and, within the customer facet, the pre-sentation dimension (for example) is perceived by thesalesforce as exceptionally uncertain. Armed with thisdiagnostic information, the manager can implement pro-grams (e.g., training) that help reduce customer presen-tation ambiguity. Furthermore, managers can use theMULTIRAM scale to determine whether different sales-people (e.g., at different career stages) face different roleambiguities that impede their performance. This differ-ential information then can be used by managers to tailortheir intervention strategies (e.g., training) to individualboundary spanners. In addition, managers can deploy theMULTIRAM scale as a control mechanism. Specifi-cally, for each MULTIRAM dimension and/or facet,managers can develop norms and tolerable limits basedon their particular organizational environment and goals.Then, the MULTIRAM scale can be administered at reg-ular intervals to track perceived role ambiguities. Spe-cific managerial actions can be mandated when role am-biguity exceeds preset tolerance limits.

In terms of research, our results have major implica-tions. Specifically, in future theoretical work, it appearsmore useful to supplant global measures of role ambi-guity (e.g., the Rizzo, House, and Lirtzman measure)

BOUNDARY ROLE AMBIGUITY 337

with one or more facets of the MULTIRAM scale. Thereason is that the global measure, at best, underidentifiesthe role ambiguities faced by the boundary spanner and,at worst, is redundant with the MULTIRAM scale. Fur-thermore, researchers can exercise considerable flexibil-ity in using the MULTIRAM scale. For instance, whenthe purpose of research is to focus on role ambiguitiesintemal to the organization, researchers may find it pref-erable not to measure the customer and family facets.Likewise, if researchers want to use a global measure ofrole ambiguity for the purposes of testing a nomologicalset of relationships and/or theory building, they may findit advantageous to develop a composite measure by sum-ming over the seven facets of role ambiguity. Such a

composite may be a weighted average, giving more em-phasis to facets the researcher deems fit. This approach,we believe, is superior to recourse to a global measureof role ambiguity that yields a composite from a severelyrestrictive measurement of role ambiguities with an un-known weight structure. Thus, we concur with Ford andhis coworkers and King and King in prescribing that thereis little justification for the continued use of such globalmeasures. Our results for the selected correlates and con-sequences amplify the benefits of this prescription. Be-cause these benefits promise significant substantiveprogress, we encourage marketing researchers to use theMULTIRAM scale in their study of boundary-spanningroles.

APPENDIXTHE MULTIRAM SCALE." ITEMS, FACTOR LOADINGS, REUABILITY AND VARIANCE EXTRACTED FROM

SME STUDY

Loading Facef Dimension'' Item description1.02

.38

.82

.67

.97

.53

.92

.60

.98

.89

.78

.59

.41

.64

.55

.49

.83

.70

.87

.65

.48

.62

.82

.56

.541.03

.91

.86

.85

.88

.68

.53

.80

.75

.80

Company(p = .77; p., =

Boss(p = .87; p^ =

Customer(p = .81; p,̂ =

Ethical(p = .68; p^ =

Other managers(p = .83; p., =

.53)

.77)

.59)

.55)

.71)

Flexibility(a = .70)Work(a = .84)

Promotion(a = .75)

Support(a = .86)

Demands(a = .86)

Interaction(a = .78)

Objection(a = .81

Presentation(a = .81)

External(a = .90)Intemal(a = .83)

_

(a = .88)

.82

How much freedom of action I am expected to haveHow I am expected to handle nonroutine activities on the jobThe sheer amount of work I am expected to doWhich tasks I should give priorityHow much work I am expected to doHow I should handle my free time on the jobWhat I can do to get promotedHow vulnerable to job termination I amWhat is the critical factor in getting promoted

To what extent my boss is open to hearing my point of viewHow satisfied my boss is with meHow far my boss will go to back me upThe method my boss will use to evaluate my performanceHow my boss expects me to allocate my time among different aspects of

my jobHow to meet the demands of my bossHow I should respond to my boss's criticismWhat aspects of my job are most important to my bossThe level of professionalism my boss expects of me

How I am expected to interact with my customersHow much service I should provide my customersHow I should behave (with customers) while on the jobHow I am expected to handie my customers' objectionsHow I am expected to handle unusual problems and situationsHow I am expected to deal with customers' criticismWhich specific company strengths I should present to customersWhich specific product benefits I am expected to highlight for customers

If I am expected to lie a little to win customer confidenceIf I am expected to hide my company's foul-ups from my customersHow I should handle ethical issues in my jobHow top management expects me to handle ethical situations in my jobWhat I am expected to do if I find others are behaving unethicallyThe ethical conduct my boss expects of me

How managers in other departments expect me to interact with themWhat managers in other departments think about the job I performHow I should respond to questions/criticism of managers from other de-

partmentsHow much information I should provide managers from other departments

338 JOURNAL OF MARKETING RESEARCH, AUGUST 1991

APPENDIX—(Continued)

Loading Facet' Dimension Item description

.74

.83

.84

.77

.64

.83

.82

.81

.79

Coworkers(p = .85; p..

Family(p = .86; p«

= .74)

. = .75)

a = .87

(a = .88)

How my coworkers expect me to behave while on the jobHow much information my coworkers expect me to convey to my bossWhat my coworkers expect me to do for themThe extent to which my coworkers expect me to share job-related infor-

mation with themThe kind of attitude my coworkers expect me to have toward the company

About how much time my family feels I should spend on the jobTo what extent my family expects me to share my job-related problemsHow my family feels about my jobWhat my family thinks about the ambiguity (e.g., nonroutine job, no fixed

hours of work) in my job"All scale items were assessed by using a 5-point Likert scale with the category lables 1 = very certain, 2 = certain, 3 = neutral, 4 - uncertain.

ysis results were obtained by the maximum likelihood method with oblique rotation utilizing the FACTOR routine in SPSS'.Because of space limitations, only the dominant loading is shown. ^ ,. j

'The estimated composite reliability (p) and the variance extracted (pJ from restricted factor analysis of MULTIRAM facets (i.e., second-order analysis) is in parentheses.

"The estimated Cronbaeh's alpha reliability for each dimension is in parentheses.

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