EXPERTS USE COMPENSATORY STRATEGIES …...extensive set of cues in a compensatory way to make their...

STUDIA PSYCHOLOGICA, 55, 2013, 4 251

EXPERTS USE COMPENSATORY STRATEGIES MOREOFTEN THAN NOVICES IN HIRING DECISIONS

Róbert HANÁK, Miroslav SIROTA, Marie JUANCHICH

Institute of Experimental Psychology, Slovak Academy of SciencesDúbravská cesta 9, 841 04 Bratislava, Slovak Republic

E-mail: [email protected]

Abstract: Previous research focusing on decision making has reported that most novices use anextensive set of cues in a compensatory way to make their decisions (i.e., compensatory strate-gies), whereas most experts use a limited set of relevant cues in a non-compensatory way (i.e.,non-compensatory strategies). We tested the generalizability of these conclusions in a personnelselection context with students as novices and recruiters as experts. In a realistic setting, weinvestigated the effect of expertise on a subjective and an objective measure of decision makingstrategies. Results showed that, in contrast with previous research, both novices and expertsmostly used compensatory strategies and that experts used them more often than novices.Further, consistently with previous research, experts allocated more importance than novices tocues predicting future job performance. We discussed theoretical and practical implications of ourfindings.

Key words: decision-making, personnel selection, compensatory, non-compensatory, expertise

Despite its obvious practical and theoreti-cal importance, too little attention has beenpaid to descriptive models of decision-mak-ing in selection and recruitment. The aim ofthis paper is to shed light on decision-mak-ing strategies of novices and experts in per-sonnel selection.

Decision-Making Strategies

When making decisions one can use a rep-ertoire of strategies. In this article, the termdecision strategy refers to a “sequence ofmental and effector (actions on environment)operations used to transform an initial stateof knowledge into a final goal state of knowl-edge” (Payne, Bettman, Johnson, 1993).These strategies refer to different proceduresand potentially reach different outcomes

(e.g., Dieckman, Rieskamp, 2007; Garcia-Retamero, Rieskamp, 2008). The first andcommon stage of a decision-making strat-egy is to assess the importance of the differ-ent attributes or cues of the available op-tions. For example, job experience and edu-cational level of a candidate are cues in mak-ing a personnel selection decision-making.To assess the importance of each cue, onecan rank the cues by importance or allocatea specific weight to each of them. Then, thedecision maker does or does not make trade-offs among the cues for the different options(Payne, Bettman, Johnson, 1993). It is at thatlast stage that major differences arise betweendecision-making strategies. Compensatorystrategies involve trade-offs among all theavailable cues weighted according to theirvalues. On the contrary, non-compensatory

DOI: 10.21909/sp.2013.04.640

252 STUDIA PSYCHOLOGICA, 55, 2013, 4

strategies do not involve trade-offs amongcues and their relative weights (Payne et al.,1993).

The Weighted Additive Strategy (WADD)is a typical compensatory decision strategy.In a nutshell, the WADD strategy is a sys-tematic procedure focusing on one alterna-tive at one time (e.g., one candidate after theother). After allocating a different importanceand value to each cue, the subjective valueof each cue is multiplied by its importanceweight. Finally the results of each multipli-cation are summed (e.g., Garcia-Retamero,Rieskamp, 2008; Bergert , Nosofsky, 2007).As a result, the WADD is very robust andreliable but time consuming and informationdemanding, which is not suitable under timeand cognitive constraints (e.g., Rieskamp,Otto, 2006; Bergert, Nosofsky, 2007; Broder,Gaissmaier, 2007). A strategy enabling thedecision-maker to cope with time pressureand limited information access is the Takethe Best strategy.

The Take the Best strategy (TTB) is a typi-cal non-compensatory strategy. Using theTTB strategies includes different stages. Afterallocating a different importance and valueto each cue, the decision maker comparesthe value of the most important cue amongdifferent options. If one option has a greatervalue than the others, this alternative will bechosen. If the values of the most importantcue are the same among the different alter-natives, the next cue is examined accordingto the same procedure until one of the cueshas a greater value for one of the alterna-tives. If all cues have the same value the de-cision maker will choose randomly amongthem (Gigerenzer, Todd, 2001; Hogarth,Karelaia, 2006; Rieskamp, Otto, 2006).

To illustrate these strategies, consider thefollowing hiring context in which the options

for the decision maker are the different can-didates and the cues their respective char-acteristics:

A recruiter is looking for a manager for amedium size factory. In the job profile, heselected three criteria according the rel-evance: education level, cognitive abilitiesand motivation. Two applicants pass a se-ries of tests.

- Candidate A does not meet the educationcriteria but has very good performance oncognitive abilities and motivation test.

- Candidate B meets all the criteria but haslower performance on cognitive ability testsand motivation than candidate A.

If weights of cues are not equal and val-ues of cues are not dichotomous, a recruiterusing a compensatory strategy would hirethe applicant A, even if the education leveldoes not satisfy one of the criteria. The deci-sion is the result of a compensation of thecue “education level” by the value of theother cues relevant for the position. A re-cruiter using a non compensatory strategywould not hire applicant A since he does notmeet the first of the criteria judged to be nec-essary for the position but applicant B whomeets the first relevant criteria. Better per-formance of candidate A in cognitive abili-ties test and motivation cannot compensatefor the lack of most relevant cue (stoppingrule).

Because of its extensive processing ofavailable information, the WADD strategyis accepted as a normative decision strategy(Frisch, Clemen, 1994). Indeed, in an idealdecision-making environment the systematiccharacter of the WADD compensatory strat-egy is more likely to result in accurate deci-sions. However, this does not hold undertime pressure or cognitive limitation (Payneet al., 1988). Using the WADD strategy in a


very limited time or with low attention ca-pacities could result in an interruption of theprocess before it leads to a result or to baddecisions based on computational errors(Payne, Bettman, 2002). On the other hand,the non systematic character of the TTB non-compensatory strategy does not guaranteethat the best decision has been made butrather a satisfying decision, implying a lim-ited cognitive effort and time cost (Gigerenzer,Goldstein, 1996). Overall, it cannot be con-cluded that the WADD or the TTB is thebest strategy; their effectiveness dependson both the environment (e.g., informationavailable) and the relationship between thedecision maker’s cognitive resources and thetask’s complexity, according to the notion ofbounded rationality (Simon, 1982). AsGigerenzer and Todd (2001) suggested, indi-viduals have a toolbox of decision-makingstrategies in which they choose the onedeemed to be the most suitable in a specificsituation1. As a result, a great amount of re-search has focused on the conditions of theuse of one or another strategy, testing theadaptive nature of decision-making strate-gies.

The Effect of Expertise inDecision-Making Strategy Choice

Different factors determine the use of dif-ferent strategies such as time constraint,amount of information available, and the typeand structure of the task at hand (e.g.,Shanteau, 1992a; Bergert, Nosofsky, 2007).The degree of expertise of the decision makeris also deemed to determine the choice of

decision-making strategy. Experts and nov-ices use different decision strategies toachieve the best outcome (Shanteau, 1992a;Garcia-Retamero, Dhami, 2009). Indeed, thedifficulty in identifying the most importantcue would prevent novices selecting theTTB strategy. Furthermore, novices are heldto rely on explicit, controlled and slower pro-cesses, whereas, experts rely on implicit andfast processes and use less but more relevantpieces of information (Shanteau et al., 1991;Garcia-Retamero, Dhami, 2009). Expertsmay employ non-compensatory strategies,whereas novices may rely on more cog-nitively complex strategies. In a study fo-cusing on burglars’ decision-making strate-gies, Garcia-Retamero and Dhami (2009)found that expert burglars used the TTB strat-egy more than novices. When assessinghouse safety, expert burglars used the TTBdecision strategy in 85% of the cases whereasnovices (students) in only 2.5%. Similarly,Shanteau (1992b) concluded that experts useTTB more often than lay individuals in audittasks. Decision-making strategies are highlycontext dependent since the choice of strat-egy is determined by contextual factors andthe relevance of the cues is a function of thegoal of the decision-maker. The potential togeneralise findings in one context to anotheris very poor (Shanteau, 1992a).

In contrast to these findings, Highhouse(2008) disputed the effect of expertise ondecision-making strategies by emphasisingthe negative effect of expertise on personnelselection practice. In the personnel selectioncontext, Highhouse found that three expertpractitioners out of four believed that theycould assess the suitability of a candidatemore accurately with an informal discussionthan with specific selection tests (i.e., usednon-predictive cues). This could be because

1 Ballová Mikušková (2013) explains how peopleare able to switch from intuitive to deliberativemode according to a specific situation.


experts believe that their expertise enablesthem to rely more on their own intuition ratherthan to rely on formal procedures such asselection tests (see also Čavojová, 2013). Inthis study, we explore how novices and ex-perts weigh cues and select strategies whenmaking personnel selection decisions. Ex-perts are assumed to use a smaller set of mostrelevant information (Weiss, Shanteau, 2003),but what are the relevant cues in a hiringdecision?

Weighting the Cues in aPersonnel Selection Situation

When making a decision in recruitment,the first step is assessing the importance ofthe different characteristics of the applicants(e.g., job experience, job related knowledge).During this process, the decision-maker al-locates specific weights to the different cuesthat will be used according to the preferreddecision strategy. Assessing the importanceof the characteristics of a candidate amountsto assessing to what extent these character-istics predict performance at the organisa-tional level. This is a real challenge in prac-tice and therefore, an important issue for re-searchers. Choosing the right candidate rep-resents a high stake for any organisation, asgood selection decisions result in higher lev-els of annual profit for an organisation(Terpstra, Rozell, 1993).

A very wide variety of characteristics areconsidered to assess whether a candidate issuitable for a position. However, some of thesecharacteristics are not relevant to selectingan individual, as they are not predictive offuture performance. Schmidt and Hunter(1998) have made an overview of the predic-tive validity of applicants’ characteristicsshowing that cues commonly used in the past

were in fact not predictive of job performance.For example, graphology, age and interestshad no predictive validity on overall job per-formance but we used them in our research formeasuring the participants’ awareness of thecues predictive validity. The belief of practi-tioners in the relative efficiency of selectionprocedures or tools partly explains their will-ingness to integrate such tests in their prac-tice (Terpstra, Rozell, 1997). For example, themain reason why some American HR manag-ers did not use cognitive ability tests in thenineties is that the tests were perceived asnon-useful (Terpstra, Rozell, 1997). Althoughorganisational psychology research broughtclear evidence of the value of different cues,findings failed to be fully implemented in prac-tice. Different papers describe how researchand practice fail to meet and work in synergyfor mutual benefit (e.g., Anderson et al., 2004;Nowicki, Rosse, 2002). One of the guidelinesto bridge the gap between research and prac-tice would be to focus more specifically on adescriptive model of behaviour rather thannormative or prescriptive models (Andersonet al., 2004). Consistent with this recommen-dation, this research focuses at a descriptivelevel on how experts and novices allocate im-portance to a set of characteristics of job ap-plicants traditionally used in selection proce-dure.

GOAL AND HYPOTHESES

In the current research, we investigateddecision-making strategies as a function ofexpertise in hiring decisions. Our goal is two-fold: 1) comparing the decision strategiesused by experts and novices in a personnelselection situation; 2) comparing differencesin weighing of cues between experts andnovices in personnel selection. Following


findings of previous studies, we expect thatexperts will mostly adopt the TTB strategywhereas novices will mostly adopt theWADD strategy. We are aware that expertsin recruitment make mistakes and they arenot reaching optimal level of performance,however, we expect that experts will allocategreater weight to cues predicting future per-formance (i.e., cognitive abilities) than nov-ices and less weight to cues not predictingfuture performance (i.e., graphology).

METHOD

Participants

In this study 46 participants volunteeredto participate without financial incentive.Two similarly sized groups were formed. Theexpert group consisted of people who regu-larly recruit candidates for job posts. To beclassified as an expert all of the followingcriteria had to be met: at least two years ofexperience in the field; experience of hiringat least 50 people with responsibility for thewhole selection process and final decision.The sample of recruiters consisted of 21 re-cruiters with an average of 6.1 years of expe-rience (SD = 4.1 years), and an average of172 positions recruited (SD = 215.3 posi-tions). The average age of the recruitersample was 32.3 years old (SD = 10.6 years)and most of them were women (n = 16). Thenovice group consisted of 25 undergradu-ate management students at the Universityof Economics in Bratislava, Slovakia. Nonehad any experience with personnel selectionas a recruiter nor had they received any rel-evant training, such as human resourcesmanagement classes. All participants in thenovice sample were aged 20 years old andmost were male (n = 14).

Materials and Procedure

The hiring task was designed to enablethe authors to identify whether the decisionwas made using a WADD strategy or a TTBstrategy based on a final choice of one outof the two candidates in each of four trials.We, therefore, refer to this procedure as be-ing outcome-based. The hiring task proce-dure involved two stages, each composedof several steps. In the first stage, partici-pants were first informed of their personnelselection objective: You would like to hire asales person to sell luxury cars and you arelooking for the best salesperson available.Then they were provided with a table exhib-iting nine job-hiring cues. These were se-lected and categorised based on Hunter’sand Schmidt’s (1998) review of the literatureon cues used in selection procedures andtheir predictive validity (i.e., to what extentthey predict future performance in the posi-tion). Three cues were not predictive of fu-ture performance: graphology, hobbies andeducation (r < .11) and six cues were predic-tive of future performance: collaborator’sassessment, job experience, references, cog-nitive tests, assessment centre and specificjob knowledge (r > .18). Participants wereasked to rate the subjective importance ofeach cue in accordance with the specific jobpost. They received 100 points, which theyallocated among the 9 characteristics. Thenumber of nine characteristics was inspiredby Garcia-Retamero and Dhami (2009) re-search who used 8 characteristics in a simi-lar task.

The second stage of the procedure in-volved four decision choices between twocandidates. For both candidates, 9 charac-teristics (i.e., cues) were presented simulta-


neously. The value of each cue was in a bi-nary mode either positive or negative. Forexample, a positive value of the cue Educa-tion, was described as follows, “The appli-cant is a university graduate with verygood results, having studied interna-tional trade“; whereas a negative value forthe same cue was described as follows“The applicant successfully finished HighSchool with very good results, having stud-ied trade as a specialty”.

To ensure that the choice of one of thetwo candidates was the result of either theWADD or the TTB strategy, the composi-tion of the choices in each trial was designedas a function of the individual ranking andweights of cues provided by the participantin the first stage. This procedure was thesame as that used in Lee and Cummins (2004).All trials were presented on a computerscreen (Microsoft Excel was used) and alldata were collected in individual sessions orby email.

Finally, after completing the four decisiontrials, participants were asked to completea short self-report questionnaire on deci-sion-making strategies. Participants were in-formed that two different strategies couldbe used in personnel selection (WADD andTTB) and these were briefly described. Par-ticipants then reported which of the twostrategies they used in the hiring decisiontask, and which they would use in hiringdecision without limitation (e.g., time, cost).Furthermore, participants responded tothree further items investigating how theythink HR managers usually make hiring de-cisions, how managers without HR trainingmake hiring decisions and finally, how stu-dents in management would make hiringdecisions. Judgments were collected on a5-point Likert scale ranging from 1: WADD

to 5: TTB (1, 2, 3 indicated WADD and 4, 5indicated TTB).

RESULTS

Decision-Making Strategies of Expertsand Novices

On average over the four trials, participantsused the WADD strategy (82.1%, CI [75.9%,87.0%]) more often than the TTB strategy(17.9%, CI [13.0%, 24.1%]). We expected ex-perts to mostly use the TTB strategy but, onthe contrary, results showed that expertsused the WADD strategy (M = 91.7%, SD =14.4%) more than the TTB (M = 8.3%, SD =14.4%). In agreement with our prediction,novices used the WADD strategy (M =74.0%, SD = 31.9%) more than the TTB (M =26.0%, SD = 31.9%). Most importantly, whenwe compared differences between novicesand experts in strategy selection, contraryto our prediction, experts used the TTB strat-egy less than novices, t(34,7) = -2.49, p =.018, CI [-32.1%, -3.2%], d = 0.70.

The surprising role of expertise in selec-tion of decision-making strategies may haveoccurred due to possible confounding vari-ables such as gender (novices were mostlymales and experts mostly females) or age(novices were younger than experts). Wecontrolled the possible confounding vari-ables statistically by using a linear regres-sion modelling approach. According to thisapproach, evidence of confounding occurswhen a slope of the main variable of inter-est decreases by entering confounding vari-ables into a multiple linear regression. Asimple linear regression of expertise on strat-egies yielded a significant slope of exper-tise, (b = -0.71, β = -.33; t = -2.34, p = .024),which has even increased – not decreased


(b = -0.99, β = -.47) – by entering the addi-tional two variables, gender and age, into amultiple regression analysis. Indeed, the ad-justed association between expertise andstrategy selection was marginally statisti-cally significant, t = -1.81, p = .077, whereas

gender and age failed to predict significantlystrategy selection (respectively, β = .21; t =1.35, p = .184; β = -.08; t = -0.34, p = .739).Therefore, gender or age, cannot accountfor the found association between exper-tise and strategy use despite their unbal-

Note: Error bars represent 95% confidence intervals.Judgments were given on a 5-point Likert scale ranging from 1: only WADD to 5: only

TTB.

Figure 1. Differences in self-reported use of decision strategies between experts andnovices


anced distributions across the two exper-tise groups.

Results from the self-assessment of theusual strategy use are consistent with theresults of the strategies traced in the hiringtask. Overall, participants reported that in thehiring task they used the WADD strategymore (M = 2.13, SD = 1.00). Furthermore, dif-ferences in self-report of strategies variedaccording to degree of expertise. Experts re-ported significantly different strategies(WADD) than novices (TTB) and the resultsin strategy traced in the hiring task were dif-ferent as well.

As Figure 1 shows, experts reported thatthey used the TTB strategy less so thannovices did (respectively, M = 1.95, SD =0.97, M = 2.28, SD = 1.02); t(39) = 2.34, p =.024, CI [0.08, 1.05], d = 0.33. Participants re-ported that without any constraints theywould similarly use the WADD strategy(M = 2.66, SD = 0.96). The correlation be-tween decision-making strategies in hiringdecisions and self reported strategies for hir-ing decisions were statistically significantand of medium size (r = .43, p = .003). Thismeans, that once the strategies were ex-plained, participants were aware of the typeof decision strategy they used.

Concerning what participants thoughtabout the strategy used by others, we foundthat participants judged that an ideal HRmanager and HR students would use theWADD strategy (respectively, M = 2.66,SD = 0.06; M = 2.85, SD = 1.05). On the con-trary, HR managers in general and managerswithout HR training were expected to usethe TTB strategy (respectively, M = 3.10, SD= 0.94; M = 3.38, SD = 0.99).

Overall, findings pointed to the prevailinguse of the WADD strategy in hiring deci-sions by both experts and novices. However,

this preference was greater for expert recruit-ers. These conclusions were supported byboth strategies traced in actual decision-making and by self-report of strategy use ineveryday practice.

Importance Given to Cues DescribingApplicants According to Expertise

With regards to the diagnosticity of cues,we focused on the weight given to the dif-ferent cues available for the participants tojudge “whom to hire”.

In order to compare differences in cueweight estimations among experts and nov-ices, a mixed ANOVA was conducted withcue weight as the dependent variable, de-gree of expertise as between-subject and cueas within-subject factor. As the weights ofevery participant should sum to 100%, themain effect of the group was not exploredand focus was on the interaction of exper-tise degree with cue. Results showed a sig-nificant within-subjects effect of cue andgroup x cue interaction, F(5,10) = 37.83, p <.001, η2 = .46; F(5,10) = 4.71, p < .001, η2 = .10.This result shows that experts and novicesdid not allocate the same importance to thedifferent cues.

More specifically, we expected experts togive more weight to relevant cues (i.e., spe-cific job knowledge) than novices and nov-ices to give more weight to less relevantcues (i.e., graphology). Thus, the group of9 cues was split into two categories: pre-dictive and non-predictive of future jobperformance according to Schmidt andHunter ’s review (1998). As a result,collaborator’s assessment, job experience,references, cognitive tests, assessment cen-tre and specific job knowledge werecategorised as predictive cues (see left panel


of Figure 2); whereas graphology, hobbiesand education were categorised as non-pre-dictive (see right panel of Figure 2). Onaverage, experts allocated more importanceto predictive cues than novices (respec-tively, M = 13.90, SD = 1.39 vs., M = 12.21,SD = 1.18), t(44) = 4.46, p < .001, CI [1.85,

4.91], d = 1.31. Furthermore, novices allo-cated more importance to non-predictivecues than experts (respectively, M = 8.90,SD = 2.37; M = 5.52, SD = 2.78), t(44) = 4.46,p < .001, CI [2.46, 0.93], d = 1.31. Comparingsignificance and effect size, we could seethat in predictive and non-predictive cues

Note: Error bars represent 95% confidence intervals.Not relevant cues: years of education, graphology, hobbies

Figure 2. Experts and novices mean weights allocated to the six job relevant cues and tothe three not relevant cues right panel


the difference between groups in cueweight are almost the same. To furtheranalyse the weight allocated to each cue,we considered them individually. From theconfidence intervals (Figure 2) it is appar-ent that experts’ mean cue weights werestatistically significantly higher than thoseof novices for the predictive cue ‘assess-ment centres’ (d = 0.79), and smaller for thenon-predictive cue ‘years of education’(d = -1.00) and ‘graphology’ (d = -0.59).Other differences were not statistically sig-nificant, however, medium effect sizes wereidentified. Experts allocated more impor-tance to the predictive cues ‘job experience’(d = 0.56) and ‘specific job knowledge’ (d =0.48) than novices. Conversely, the weightallocated to the predictive cue ‘references’was smaller for experts than for novices(d = -0.47).

DISCUSSION

The present study was designed to de-termine the extent to which decision strate-gies and decision quality of novices andexperts differ in a hiring context. The find-ings show that experts used the compensa-tory Weighted ADDitive (WADD) strategymore often than the non compensatory TakeThe Best (TTB) strategy to determinewhom to hire. Novices did not use theWADD strategy more than experts; to thecontrary, they used the TTB strategy mostoften. These results of the strategy tracingprocedure were consistent with the self-re-ported strategy use. In addition, experts al-located greater weight than novices to cuespredicting future performance (i.e., cogni-tive abilities) and less weight to cues notpredicting future performance (i.e., graphol-ogy).

Both Novices and Experts UseCompensatory Strategies

We found that both novices and expertsuse compensatory strategies. This findingshowed, for the first time to our knowledge,the important role of expertise in choosing adecision strategy for personnel selection. Ourresults are inconsistent with previous find-ings showing that experts use TTB more thanthe WADD decision strategy (e.g., Shanteau,1992a; Bergert, Nosofsky, 2007; Broder,Gaissmaier, 2007). For example, Garcia-Retamero and Dhami (2009) showed that ex-pert robbers used the TTB strategy more thanWADD strategies when deciding whichhouse they should burgle. Contrary to pre-vious findings, experts did not use only rel-evant pieces of information compared withnovices; they used all the information andmade trade-offs among them even more of-ten than novices. This result also appears tocontrast with Highhouse’s findings (2008)that expert HR managers rely on intuitiveprocesses rather than analytical ones.

Why Did Experts Mostly Usea Compensatory Strategy?

Two main explanations why experts mostlyused a compensatory strategy can be sug-gested to account for the discrepancy be-tween previous findings and our results. Thefirst explanation focuses on the task and thematerials used in the present study and thesecond on the specificity of the personnelselection issue.

First of all, a tendency for preferring theWADD strategy by professional recruitersand also by novices could be explained bythe design of the hiring task. Indeed, task


characteristics have an important impacton decision-making strategy selection(Shanteau, 1992a). The procedure was de-signed to ensure that all cues were availableat the same time to the decision-makers inthe form of a table. Presenting all the cues atthe same time and in a format facilitating com-parison may have prompted participants totake them all into account. However, Garcia-Retamero and Dhami (2009) used a similartask format and still found a predominanceof TTB strategies for experts.

A second, and probably more relevant,explanation of the discrepancy with previ-ous findings relates to the unique context ofpersonnel selection and the (high) stakes ofthe hiring decision. Selecting individuals tofulfil expectations for a specific job is a costly,risky and time-consuming process (Hunter,Smith, 1998) and has to be professionallyjustified if asked by third party. All job can-didates have the right to ask why they wereunsuccessful or successful, as well as man-agers and even special commissions. There-fore, when so many resources are being ex-pended, recruiters are expected to use themost sophisticated and complex methods.Using a decision strategy like the fast andfrugal TTB strategy could appear as a lackof competence and professionalism; whereasusing the WADD strategy (because it is ex-haustive and complex) could appear as asymbol of competence and professionalism.Furthermore, from an ethical perspective, itcan be considered that choosing a candi-date from among many others, can only befair if all the cues are examined – the selec-tion has to be justified. One could argue thata decision context, where no cue completelyoutweighs the other, reduces the possibilityof using the TTB strategy. We do not be-lieve this was the case here. In addition, ac-

cording to Gigerenzer and Goldstein (1996),when no cue outweighs the others, a deci-sion-maker using the TTB strategy shouldchoose an option randomly, which did nothappen in our sample.

Experts Identified MoreRelevant Cues than Novices

Our results suggest that experts differedsubstantially from novices in setting cueweights to the characteristics of the appli-cants; mainly in weighing ‘assessment cen-tres’, ‘years of education’, and ‘graphology’.Experts allocated more importance to cuespredicting future organisational performance(i.e., job experience) when compared withnovices. Conversely, novices allocated moreimportance to cues not predicting future per-formance (i.e., hobbies). However, it is worthnoting that although experts better identi-fied the cues relevant to the hiring decisionthan novices, they failed to allocate zeroweight to irrelevant cues. This finding is inline with the results of Highhouse (2008)showing that HR managers were using non-predictive cues to make a hiring decision.However, contrary to his suggestion, suchmalpractice does not seem to be caused byexpertise since in these results expertise ap-pears to improve the identification of relevantcues.

Concluding Comments

The present research sheds light on thechoice of decision-making strategy and itsrelation to expertise in offering a controver-sial finding. If substantiated by further re-search, these findings represent an impor-tant contribution to the domain of decision-making strategy and expertise. To rule out


the effect of the mode of presentation as adeterminant of the use of WADD, future stud-ies should investigate the effect of variousmodes of presentation of job applicants onthe hiring decision. More ecological formatscould be studied, such as the traditionalcover letter and Curriculum Vitae. Further-more, these findings are specific to the per-sonnel selection context. Since the choice ofdecision-making strategy is context depen-dent, further study is needed in other ap-plied settings. Finally, the better performanceof experts than novices in cue weighing in-dicates the need of training and experienceto enhance practice. A potential implicationof the present findings for practitioners isthat it highlights the potential needs ofmentoring new recruiters.

Received August, 29, 2012

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PRI ROZHODOVANÍ O PRIJATÍ DO ZAMESTANIA POUŽÍVAJÚ EXPERTIKOMPENZATÓRNE STRATÉGIE ČASTEJŠIE AKO NOVÁČIKOVIA

R. H a n á k, M. S i r o t a, M. J u a n c h i c h

Súhrn: Predchádzajúci výskum ukázal, že väčšina začiatočníkov využíva rozsiahly početpremenných kompenzatórnym spôsobom pri rozhodovaní (t.j. kompenzatórne stratégie), kýmväčšina expertov využíva obmedzený počet relevantných premenných nekompenzatórnymspôsobom (t.j. nekompenzatórne stratégie). Testovali sme všeobecnú platnosť týchto záverovv kontexte personálnych výberov na vzorke študentov ako začiatočníkov a skúsených rekruiterovako expertov. V realistickom prostredí sme skúmali účinok expertnosti na subjektívne a objektívnemeranie rozhodovacích stratégií. Výsledky ukázali, že oproti predchádzajúcemu výskumu ajzačiatočníci aj experti používali najmä kompenzatórne stratégie a experti ju používali častejšienež začiatočníci. V zhode s predchádzajúcim výskumom, experti viac než laici priradili prirozhodovaní vyššiu váhu premenným, ktoré mali vyššiu prediktívnu validitu. Diskutovali smeteoretické a praktické implikácie našich zistení.

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