Industrial and Organizational Psychology, 3 (2010), 171–177.Copyright © 2010 Society for Industrial and Organizational Psychology. 1754-9426/10

COMMENTARIES

Oops. . . . We Did It Again:Industrial–Organizational’s Focuson Emotional Intelligence Insteadof on Its Relationships toWork Outcomes

SETH KAPLAN AND JOSE CORTINAGeorge Mason University

GREGORY A. RUARKU.S. Army Research Institute

One of the central endeavors of schol-arly and applied industrial–organizational(I–O) psychology is the attempt to iden-tify and enhance the personal charac-teristics that predict consequential work-place outcomes (e.g., job attitudes andjob performance). Although traditionallyfocused on more traditional abilities andskills (e.g., cognitive and psychomotorones), this enterprise increasingly has begunto focus on various socioemotional vari-ables, such as personality traits (Barrick,Mount, & Judge, 2001), affective variables(Kaplan, Bradley, Luchman, & Haynes,

Correspondence concerning this article should beaddressed to Seth Kaplan.E-mail: skaplan1@gmu.edu

Address: Department of Psychology, GeorgeMason University, 4400 University Avenue, MSN-3F5,Fairfax, VA 22030

Seth Kaplan and Jose Cortina, Department of Psy-chology, George Mason University; Gregory A. Ruark,U.S. Army Research Institute, Fort LeavenworthResearch Unit.

This material is based upon work supported byU.S. Army Research Institute under Contract No.W91WAW-08-P-0430. The statements and opinionsexpressed in this presentation do not necessarily reflectthe position or the policy of the U.S. Army and noofficial endorsement should be inferred.

2009), and myriad interpersonal skills(Dudley & Cortina, 2008).

In our view, emotional intelligence (EI)is the latest in this list of alternative predic-tors. Like its predecessors, EI has ardentsupporters and vehement detractors. AsCherniss reviews, both camps have plentyof ammunition to cite in defending theirrespective views about the nature, measure-ment, and predictive value of EI (Cherniss,2010). Also like many of its predecessors,EI, or more specifically I–O’s investigationinto EI, has been somewhat misguided.Instead of first systematically delineatingthe nature and dimensionality of the cri-terion space and working backwards toidentify relevant socioemotional predictors,the field once again has ‘‘started withthe predictor and then gone in search ofsomething to predict.’’ In this sense, thestudy of EI is another example of a some-what flawed approach that management-related research often continues to fol-low, despite admonitions to do otherwise(Austin & Villanova, 1992; Burke, Sarpy,Tesluk, & Smith-Crowe, 2002; Campbell,1990; Dalal & Hulin, 2008).

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172 S. Kaplan, J. Cortina, and G.A. Ruark

What Exactly Are We Tryingto Do Here?

In our view, the ultimate goal of mostorganizational research is to try to under-stand, predict, explain, and change organi-zational phenomena and outcomes (e.g.,worker well-being, individual or teamperformance, retention, etc.). In workingtoward this goal, the typical strategy, at leastin theory, entails identifying and describ-ing the phenomenon of interest and thenseeking to identify variables or processesthat help explain or account for it (Camp-bell, 1990; Hunt, 1996). Thus, the focus isforemost on the outcome.

Cherniss points out that this criterion-driven approach also characterized theintroduction and initial study of EI in stat-ing that, ‘‘Interest in the topic [of EI] ini-tially was fueled by anecdotal evidencesuggesting that mental ability by itself isnot enough for success in life.’’ As toooften seems to happen though, psychol-ogy, including I–O to some degree, hasbecome more interested in the predic-tor (EI) and ‘‘what it’s good for’’ thanin the question of ultimate scientific andapplied (organizational) interest, which inthis case is, ‘‘which socioemotional charac-teristics help to explain emotionally relevantworkplace outcomes and phenomena?’’(Austin & Villanova, 1992; Messick, 1995).

This focus on EI and its predictive value,without adequate regard for the outcomesit may or may not predict, has resultedin a jumble of variables now subsumedunder the EI label. Our task now is thatof trying to disentangle that jumble for, asCherniss notes, ‘‘of all the criticisms thathave been raised, the most fundamentalinvolves the lack of agreement concerningwhat EI is. This issue needs to be addressedfirst because all of the other issues, such ashow significant EI is for work-related per-formance, depend on how one defines EI.’’

To provide a starting point in address-ing this issue, Cherniss suggests that weagree upon adopting Mayer and col-leagues’ definition of EI as ‘‘the ability toperceive and express emotion, assimilate

emotion in thought, understand and rea-son with emotion, and regulate emotionin the self and others (Mayer, Salovey, &Caruso, 2000, p. 396).’’ Cherniss also sug-gests making a distinction between EI, asdefined by Mayer and colleagues, and otheremotional and social competencies (ESCs).These suggestions, namely, that we agreeon a definition and make this distinctionbetween EI and these ESCs, seem like use-ful starting points in beginning to unravelthis cluttered mess of variables, and wecommend Cherniss for making them. How-ever, we also emphasize that they are onlythis—starting points. Labeling this jumble,or any part of it, as ‘‘EI’’ is fine. In doing so,though, we must remain cognizant that ourultimate objective is, or should be in ourview, predicting and explaining the out-come not just settling on what EI ‘‘is’’ or ‘‘isnot.’’

From our perspective, starting with thecriterion, instead of with EI, will be themost effective way to achieve this disentan-glement. Continuing to focus on EI, with-out thoroughly considering the outcomesfor which different various socioemotionalpredictors are more or less consequential,is not the most fruitful way to advanceI–O knowledge and practice (Austin &Villanova, 1992).

As support for this point, consider thecase of I–O’s approach to assessment cen-ters (ACs). Initially, we as a field approachedACs as one might approach sausage: ‘‘Don’tknow what’s in it, but it tastes good, so I’lleat it.’’ Because we did not understand whatACs actually measured, however, develop-ment was stymied. Eventually, we beganto break ACs down into their componentparts in order to better understand thewhole. We found, not surprisingly, thatsome components (e.g., in-basket tasks)predicted some outcomes (e.g., clerical per-formance) whereas other components (e.g.,leaderless group discussion) predicted oth-ers (e.g., leadership). Only when we beganto consider the specific outcomes to whichspecific AC components might relate didwe develop an understanding of the com-ponents themselves (Howard, 1997).

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A More Useful Approach

In our view, a useful approach to studyingEI, and emotional abilities and competencein general, is by following a criterion-drivenstrategy (e.g., Burke et al., 2002; Hunt,1996). Below, we outline what this strategywould look like in practice, and we high-light the benefits that this strategy wouldprovide in studying emotion-relevant work-place processes and phenomena. Much ofthis discussion derives from conclusionsthat the authors have drawn while work-ing on a project that entails developing andvalidating a model of army leader emotionmanagement (LEM). This model ultimatelywill inform the development of army LEMtraining. Thus, we cite our personal obser-vations and ‘‘lessons learned’’ in laying outand arguing for this criterion-focused strat-egy below.

Step 1: Selecting the Phenomenaor Outcome of Interest

A first step in this criterion-driven approachwould entail carefully identifying thoseworkplace phenomena and outcomes inwhich emotions and emotionally relevantprocessing are most relevant and conse-quential. Although this idea of beginningwith the outcome seems almost axiomatic,research on EI oftentimes has not fol-lowed it. Instead of starting with the ques-tion of, ‘‘which socioemotional variablesmight help in explaining this particularoutcome?,’’ researchers instead often ask,‘‘what can EI predict?’’ Indeed, EI hasbeen correlated with a wide range ofdiverse criteria (e.g., physical and psycho-logical well-being, interpersonal relation-ships, academic and vocational achieve-ment, among many others [see Mayer,Roberts, & Barsade, 2008]), often with littletheoretical rationale offered for why or howthese relationships should exist.

Not surprisingly, this purely empiricalmethod has resulted in a long, confusing,and inconsistent catalogue of results, asCherniss acknowledges. Continuing thispractice will only serve to hinder, instead

of facilitate, our understanding of EIand related socioemotional variables. Bystarting with Mayer et al.’s (2000) model orany other model of EI, we shift attentionaway from the phenomena of ultimateinterest and implicitly assume that thisparticular predictor (or set of predictors)should be most relevant for these variousphenomena.

In reality, as these inconsistent resultssuggest, different socioemotional predictorsare more or less relevant for, and differen-tially related to, various outcomes. To illus-trate this point, consider findings regardingthe personality traits of Extraversion andNeuroticism in relation to job attitudesversus task performance. Although Extraver-sion is consistently related to more posi-tive job attitudes (Judge, Heller, & Mount,2002), it is generally not strongly linkedto task performance (Salgado, 2003). Con-versely, although Neuroticism is reliablylinked to lower workplace well-being (Judgeet al., 2002), it is only modestly related totask performance (Salgado, 2003) and issometimes even predictive of higher perfor-mance (Smillie, Yeo, Furnham, & Jackson,2006). We imagine that this pattern ofresults is the norm for socioemotional vari-ables not the exception, Thus, to say thatEI (or any set of socioemotional predictors)‘‘matters’’ or ‘‘is beneficial’’ is misleading,if not nonsensical, unless we know ‘‘forwhat’’ it matters and ‘‘why’’ it matters forthat particular outcome.

Step 2: Defining and Delineatingthe Criterion

After selecting the outcome of interest,a second step in this criterion-drivenapproach would entail explicitly defin-ing and mapping out the dimensional-ity of that criterion (Austin & Villanova,1992; Campbell, 1990). Within the per-formance domain, for instance, one mightdistinguish not only between differenttypes of performance (e.g., task vs.contextual performance) but also amongthe dimensions within those types (e.g.,

174 S. Kaplan, J. Cortina, and G.A. Ruark

sportsmanship, courtesy, etc. as dimen-sions of organizational citizenship behav-iors; Organ, 1988). Here too, differentsocioemotional predictors likely impact thevarious dimensions to differing magnitudesand, quite possibly, through different mech-anisms as well.

Our impression is that researchers,including some in I–O, generally havefailed to follow this second step as well.As Cherniss appropriately notes, studiesexamining EI’s predictive value generallyhave neglected (a) the distinctions amongthe particular components of EI, (b) thedistinctions among the specific types ordimensions of the outcome domain, and(c) the moderating role of contextual fac-tors. Instead, researchers typically employa summary or overall measure of EI anda summary or overall measure of perfor-mance (e.g., Wong & Law, 2002; see thestudies cited in the Cherniss review). Doingso implies that EI and all of its compo-nents, whichever model one advocates, areequally relevant for and similarly related tothe various dimensions that comprise the(performance) domain. These are untestedassumptions that, at a minimum, requireempirical verification (see Barsade & Gib-son, 2007 for a similar recognition).

To illustrate how these first two steps canplay out in practice, we use our projecton army LEM as an example. In this project,instead of starting with any particular modelof EI or catalog of ESCs, we concentratedfirst on the nature of LEM. We defined thisconcept as, ‘‘the processes and behaviorsinvolved in assisting employees in regulat-ing their emotional experiences so as tofacilitate the attainment of organizationalobjectives’’ and delineated eight conceptu-ally distinct sets of leader behaviors (i.e.,dimensions) that comprise or capture thecriterion space (see Table 1). We gener-ated these eight dimensions or factors byreviewing literature on the most frequentand consequential sources of workplaceemotions (e.g., Basch & Fisher, 2000) andon leaders as causes of such emotion (e.g.,Dasborough, 2006).

Table 1. Proposed Dimensions (i.e., Set ofBehaviors) Comprising the Criteria of LeaderEmotion Management Performance in theAuthors’ Project on Army Leader EmotionManagement

1. Interacts and communicates in an interper-sonally sensitive and respectful manner

2. Demonstrates consideration and supportfor employees

3. Uses emotional displays to influenceemployees’ behavior

4. Structures work tasks with consideration foremployees’ emotions

5. Provides frequent emotional ‘‘uplifts’’6. Behaves in a fair and ethical manner7. Manages interactions and relationships

among coworkers8. Maintains open and frequent communica-

tion

Step 3: Identifying Theoretically RelevantSocioemotional Predictors

The next step in our project, and in thiscriterion-driven approach in general, isidentifying the predictor variables that mostlikely will help explain or account forthe specific dimensions of the criteria ofinterest. Selecting particular candidate pre-dictors is a theoretical exercise that forcesthe researcher to select those variables forwhich a sound theoretical rationale existslinking them to specific aspects of the out-come space (Campbell, 1990). This thirdstep is the stage where the benefits ofthis criterion-centered approach are per-haps most evident and where the dangersof relying on any single predefined set ofsocioemotional predictors (like a particularmodel of EI) seem most detrimental.

First, by forcing the researcher to captureand delineate the entire criterion domain,this criterion-centered strategy necessitatesconsideration of a broader range of socioe-motional predictors than one otherwisemight undertake. Focusing exclusively onMayer et al.’s (2000) conceptualization,for instance, would limit the number andbreadth of potentially important predic-tors. Indeed, we would echo Cherniss’

EI and work outcomes 175

suggestion not to assign EI, as defined byMayer et al. (2000), any special priority orweight over other socioemotional predic-tors. No empirical evidence of which weare aware documents that the four branchesthat emerged from Mayer et al.’s definitionare more powerful predictors than are thenumerous other ESCs that Cherniss reviews.

In our own project, we certainly foundthe need to go beyond Mayer and col-leagues’ model, as several of the LEMdimensions theoretically require knowl-edges, skills, abilities, and other factors(KSAOs) that are beyond this or, for thatmatter, any one predefined set or pack-age of socioemotional predictors. As anillustration, consider the LEM dimensionof structuring work tasks with considera-tion for employees’ emotions. A long line ofresearch documents the role of task charac-teristics on employees’ attitudinal and affec-tive reactions (see Humphrey, Nahrgang, &Morgeson, 2007). Certainly, EI could playa part in leaders’ proficiency in structuringemployees’ tasks to create or maintain cer-tain task-related emotions. However, thatpart is not necessarily a large one andmay even be rather trivial. The effectiveleader also must have various other KSAOsto be effective in this objective, such as, forinstance, (a) possessing specific contextualknowledge regarding the likely emotionaleffects that the particular work task likelywill generate and (b) being conscientiousenough to monitor employees’ emotionalreactions and to integrate those observa-tions into subsequent decisions regardingeach employee.

As far as we can tell, neither EI northe various catalogs of ESCs that Chernisssummarizes adequately capture these twoother predictors. This lack of coverage isproblematic because as we would imaginethat these two particular KSAOs, amongmany others, are as consequential, ifnot more consequential, than those inthe models that Cherniss reviews. Thus,focusing on EI or these other defined setsof ESCs potentially would have resulted inmissing most of the important antecedentsto this LEM dimension. Such is true

for other LEM dimensions as well. Forinstance, we suspect that characteristicssuch as empathy, perspective taking, andintegrity are far better predictors of leaderfairness than are those appearing in themodels reviewed by Cherniss (Brown &Trevino, 2006).

To summarize this point, focusing onany one definition or conceptualizationof EI, to the exclusion of other impor-tant socioemotional variables, will resultin I–O’s failure to appropriately capturethe entire universe of relevant predictors,thereby resulting in suboptimal predictionof organizational outcomes. Conversely,‘‘starting with the criterion’’ and workingbackwards to identify predictor variableswill help ensure that all important socioe-motional variables are surveyed. In turn,explanatory power and predictive validityfor the outcomes of interest will increaseas well.

In addition to the practical gains inprediction, this strategy of selecting pre-dictors based on their proposed relation-ships with specific performance dimensionsis also most productive from a scien-tific and knowledge-generation perspective.By theoretically and statistically examin-ing linkages between specific predictorsand specific (dimensions of) criteria, onelearns both about the individual variablesin each domain and about the constructspace constituting those two domains (Bin-ning & Barrett, 1989). Seen in this light, thebest way to learn about EI is to start withsomething other than EI.

Finally, this focus on the criteria canserve as a reminder that improving the givenoutcome (e.g., LEM performance) also canentail developing relevant knowledge andskills, not only using personnel strategies(e.g., selection) based largely on stableindividual differences. That is, modelingthe entirety and complexity of the outcomespace often may lead to the recognitionthat the behaviors to be changed orenhanced are largely a function of learnableknowledge and skills, not only of stableabilities.

176 S. Kaplan, J. Cortina, and G.A. Ruark

More generally, we question Mayeret al.’s (2000) labeling of EI as a set ofabilities. Abilities represent relatively stablecharacteristics that are largely heritable.A more appropriate characterization, inour view, is labeling these socioemotionalvariables as sets of knowledge and skillsthat can change and can be developedover time. Indeed the notion that onecan improve in the capacity to perceiveor manage emotions, for instance, is afundamental premise of interventions andprograms such as those designed to increaseparenting skills or to train psychotherapists(e.g., Barone et al., 2005; Long, Angera,Carter, Nakamoto, & Kalso, 1999). To claimthat these efforts are futile seems a gloomy,and largely unsupported, notion.

Conclusion

We question the dominant approach thatapplied psychologists, including some I–Oresearchers, have followed in investigatingEI. Instead of trying to determine ‘‘howwell EI predicts,’’ a more useful strategyfor organizational researchers will be tostart with the criterion of interest and thenwork backward to identify those partic-ular socioemotional constructs that pre-dict specific dimensions of that criterion.In following this strategy, we encourageresearchers to adopt Cherniss’s recommen-dations for defining EI and distinguishingit from other emotional-relevant variables.However, in making this endorsement, wealso would remind researchers that thereis nothing ‘‘sacred’’ or especially valu-able about Mayer et al.’s (2000) definitionand that the phenomena of interest, notany one particular conceptualization of EI,should drive the choice of predictors. Thiscriterion-driven strategy ultimately will bemost effective in disentangling the jumbleof socioemotional variables and in helpingto explain, understand, predict, and changeorganizational phenomena.

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