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International Journal of Hospitality Management 32 (2013) 287–294

Contents lists available at SciVerse ScienceDirect

International Journal of Hospitality Management

journa l homepage: www.e lsev ier .com/ locate / i jhosman

motional intelligence and adaptability – Service encounters between casinoosts and premium players

atherine Prenticea,∗, Brian E.M. Kingb

Faculty of Business & Enterprise, Swinburne University of Technology, 91 Lancaster Dr, Point Cook, Victoria 3030, AustraliaCentre for Tourism & Services Research, Victoria University, PO Box 14428, Melbourne, Victoria 8001, Australia

r t i c l e i n f o

eywords:asino industryremium playerasino hostsdaptabilitymotional intelligenceervice performance

a b s t r a c t

The premium player segment has been widely acknowledged as the largest single contributor to casinorevenues. So-called casino hosts are an important influence on player perceptions of service qualityand ultimately on loyalty and casino profitability in their capacity as service representatives servicingthis segment. To date little research has investigated the relationship between casino hosts and premiumplayers. This study focused on service encounters between casino hosts and premium players, particularlyin the case of relationships between emotional intelligence, adaptability and the service performance ofcasino hosts. A mediation model involving these constructs was proposed and tested, drawing upontheory and the relationship that has been established between basic personality traits and surface traits.

In the current study emotional intelligence was identified as a basic personality trait, and adaptability isviewed as a surface trait. The results arising from a structural equation analysis confirmed the validityof the mediation model and found that the inclusion of adaptability as a mediator into the relationshipbetween emotional intelligence and service performance provided a greater proportion of variance thana model which excluded mediation. Based on the research findings implications for researchers andpractitioners were outlined.

© 2013 Elsevier Ltd. All rights reserved.

. Introduction

The premium player segment is widely acknowledged asccounting for a disproportionately large share of casino revenuesnd profits. Reports have indicated that premium players accountor only about 5% of gamblers in Las Vegas, but produce about 40% ofhe gross gaming win (High Roller’s Vegas, 1998). Of the revenuesenerated from table games about 90% comes from about 3% ofhese players (Kale, 2003). Approximately 10 premium clients mayccount for as much as a third of the Baccarat revenues of majoras Vegas casinos (cited by Hannum and Kale, 2004). These figuresre indicative of the importance and magnitude of this segmentor the casino industry. The phenomenon has attracted increasingttention as a critical driver of the recent development and expan-ion of mega casinos in the Asia Pacific region. For example, Casinoe Genting in Malaysia has invested massively in the development

f two additional luxurious VIP clubs (Club Elite and Club Max-ms) to accommodate premium players. The architectural conceptf Crown Macau has a focus on high-end gamblers. Genting Sentosa

∗ Corresponding author. Tel.: +61 406 627622.E-mail addresses: cathyjournalarticles@gmail.com (C. Prentice),

rian.king@vu.edu.au (B.E.M. King).

278-4319/$ – see front matter © 2013 Elsevier Ltd. All rights reserved.ttp://dx.doi.org/10.1016/j.ijhm.2012.06.004

in Singapore has constructed lavish VIP gaming facilities. Howeverdespite the significant impact of premium players on casinos, littleresearch has been undertaken on this market.

Marketing to the premium-play sector commonly involvesemphasising three components: casino amenities, the value ofincentives offered to players, and casino hosts (Kilby et al., 2005).When the competition to attract premium players intensifies, thefirst two components no longer suffice for gaining competitiveadvantage since they are commonplace in most casino settings(Johnson, 2002; Klein, 2000). It is the casino hosts, who are in directcontacts with premium players, who have become the major fac-tor in attracting and retaining these players (Kale, 2005; Prenticeand King, 2011a). Given the importance of their roles, it is surpris-ing that researchers have provided such scant insights into thesefrontline staff within the literature.

As indicated above, premium players are the major source ofcasino revenues, and casino hosts are their primary point of con-tact. How they perform in the context of service encounters willbe a critical determinant of player assessments about the of casinoservice provision. Within the services marketing literature, service

quality is commonly acknowledged as linking directly with cus-tomer loyalty and retention and with company profitability (e.g.Zeithaml et al., 1996). This link has been empirically validated inthe casino context (see Kale and Klugsberger, 2007; Prentice and

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ing, 2011b). Consistent with the service profit chain concept andith relationship marketing theory, host service performance willave implications for casino profitability. On this basis, under-tanding the antecedents of host performance could impact onlayer retention and casino revenues. To date the research thatas been undertaken on factors affecting service performance hasentred on organisational and individual characteristics (see Singht al., 1994). Employee personal characteristics are closely associ-ted with service performance in the case of encounters involvingntense personal contact, because such interactions require con-iderable emotional investment and emotional management skillsn the part of employees (Price et al., 1995). With reference to theasino context, Prentice and King (2011a) have argued that encoun-ers between hosts and players are emotionally charged, and thatost emotional intelligence provides a means of dealing with suchlayers. They also reported the positive influence of emotional

ntelligence on service performance.Despite its positive impact on frontline employees, emotional

ntelligence has been classified as a personality trait when it iseasured using the self-report method (see Petrides and Furnham,

001). The effects of personality traits on employee performanceave been discussed extensively in the context of sales and servicesee Brown et al., 2002). The effects of basic personality traits onatings of service performance are insubstantial albeit statisticallyignificant (Brown et al., 2002; Park and Holloway, 2003). The smallariance may be attributable to the distance between personalityraits and actual focal behaviours or performance. When conceptu-lised as being more closely related to service interactions, surfaceraits may provide a more effective prediction of employee perfor-

ance (see Brown et al., 2002). Brown et al. (2002) and Prenticend King (2012) have shown that predictions of variance maye enhanced by incorporating surface traits into the relationshipetween basic personality traits and service performance.

Drawing on the findings of previous studies, the current paperrgues that service encounters between casino hosts and pre-ium players are not exclusively emotional, but highly variable and

equire hosts to be adaptable when dealing with unpredictable andolatile clients. It will enhance host performance, if the relation-hip that connects emotional intelligence and service performancencorporates the concept of adaptability. On the basis of Brownt al.’s discussion of traits theory, adaptability is proposed as aurface trait mediating between emotional intelligence and hostervice performance. The following section reviews the relevant lit-rature on these dimensions and proposes a series of hypotheses.hough it is acknowledged as rather specialised, such research maynform behaviours in other areas where service staff are dealing

ith demanding customers.

. Relationship between emotional intelligence and hostdaptability

Emotional intelligence may be defined as the capacity to per-eive and manipulate emotional information without necessarilynderstanding it, and to understand and manage emotions with-ut necessarily perceiving feelings well or fully experiencing themMayer and Salovey, 1997; Salovey and Mayer, 1990). Emotionalntelligence related research has become commonplace over theast two decades. Its popularity may be explained by the capac-

ty of emotional intelligence to account for a greater portion ofariance in job performance that is unexplained by traditionalntelligence (Goldstein et al., 2002). Since emotions are preva-

ent in the workplace, particularly where service encounters occuretween frontline employees and customers, the emotional capac-

ty of employees may play a determining role in their behavioursnd performance during interactions with fellow employees and

ospitality Management 32 (2013) 287–294

clients. Prentice and King (2011a) have elaborated the emotionalnature of service encounters between casino frontline employeesand players and reported a positive relationship between host emo-tional intelligence and service performance.

In its original form adaptability was viewed as the deploymentof adaptive selling behaviours in a selling environment. The conceptrequires selling behaviours to be altered and/or adjusted during thecourse of interactions with customers, or across customer interac-tions based on perceptions of messages about the relevant sellingsituation (Spiro and Weitz, 1990; Weitz et al., 1986). Adaptabilityrequires the salesperson to adjust to different customer commu-nication styles and to perform five activities through the sellingprocess (Spiro and Weitz, 1990). The concept is widely acknowl-edged as an effective predictor of selling effectiveness and salesperformance (e.g., Anglin et al., 1990; Park and Holloway, 2003;Weitz et al., 1986). To date, it is somewhat surprising that verylimited research has been undertaken on the antecedents of adapt-ability.

According to Weitz et al. (1986) the effectiveness of the adap-tive approach depends on the ability and skills of the employeein the relevant technique. The practice of adaptive behaviourduring service encounters involves a capacity to recognise thatdifferent sales situations entail different selling approaches andsufficient employee confidence to alter their sales approach dur-ing the course of interactions with customers (Spiro and Weitz,1990). Employees vary in their capacities, attributable in part totheir personality traits. A few studies have examined the influenceof individual characteristics such as cognitive style and motiva-tion on employee adaptability (McIntyre et al., 2000; Roman andIacobucci, 2010). Since adaptive behaviour concerns personal inter-actions that occur in service encounters, and entail an emotionalcomponent, employee emotional abilities may help to facilitateadaptability.

Emotional intelligence has been widely acknowledged as hav-ing a positive impact on roles which involve personal interactions,such as service representative (Ashkanasy and Daus, 2005; Prenticeand King, 2011a). It may affect the adaptive behaviours of frontlineemployees in such contexts. It is associated with communicationskills and those with superior emotional intelligence are said tobe more effective at communicating their ideas, goals and inten-tions (Goleman, 1998). Since effective use of the adaptive approachentails communicative ability, emotional intelligence on the part ofthe frontline employee, may help explain why they adopt an adap-tive approach. Boorom et al. (1998) noted an association betweenrelational communication skills and the adoption of appropriateapproaches towards customers. Since the context of the presentstudy involves service encounters between casino hosts and pre-mium players, it is anticipated that such interactions will beemotionally loaded. The emotional intelligence of the casino hostwill be critical for adopting an adaptive approach and managingemotional encounters. Consistent with the context of the study anddrawing upon the foregoing discussion, the following hypothesis isproposed:

Hypothesis 1. Emotional intelligence is associated with casinohost adaptability; the more emotionally intelligent the host is, themore adaptable when dealing with casino premium players.

3. Relationship between adaptability and host serviceperformance

As has been noted above, the concept of adaptability has been

widely cited in the sales literature. Previous studies have identifieda gap in the relationship between adaptability and performance inthe service sector. Adaptability is evident in service settings whenservice employees exhibit flexibility and adapt their behaviours

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o meet the changing needs and requests of customers duringhe course of service encounters. Researchers such as Bitner et al.1994) and Bitner et al. (1990) have indicated that service employ-es should recognise customer needs, and that dissatisfaction mayrise when inappropriate behaviours are evident during the servicencounter. Humphrey and Ashforth (1994) provided evidence of aink between adaptability on the part of employees and customererceptions of service quality.

Although relatively little research has investigated serviceanagement practices in the casino context, an examination of

ambling motives may help to explain how employee adaptabilityffects player perceptions of service performance. Reasons explain-ng casino gambling include: socialisation, boredom, hedonism andisk-seeking (see Cotte, 1997). Some explanations view casinos as aocial context within which gambling and socialising occurs. Thesere classified as socialisers. Others gamble to escape from everydayedium and are classified as escapists (see Klebanow, 2008). Accord-ng to Klebanow, socialisers tend to establish relationships withasino employees and other gamblers, whereas escapists remainnonymous and avoid attention. Gambling motives are consistentith behaviours within casinos and influence their interactionsith casino hosts. In view of the variety of gambling motives, casinoosts need to be adaptable when dealing with different customersince such adaptability indicates a capacity to tailor behaviourso the customer, and to adjust rapidly to customer reactions (see

eitz et al., 1986). Such capacities may subsequently impactn performance evaluations, since meeting customer needs hasmplications for customer satisfaction. Consistent with the afore-

entioned discussion, the following hypothesis is established:

ypothesis 2. Adaptability will have positive influence host per-ormance.

. Relationship between emotional intelligence and hosterformance

Within the relevant literature emotional intelligence has beenonceptualised as a pure intelligence model (Mayer and Salovey,990, 1997), and as a mixed model comprised of both cognitivebility and personality (Bar-On, 1997; Goleman, 1995, 1998). Con-istent with these conceptualisations, the objective performancepproach is adopted to measure the intelligence model, whereashe self-reporting method is used for the mixed model. Of thearious available methods, self-reporting has been the more com-only used to measure this construct and appears to have good

alidity (Van Rooy and Viswesvaran, 2004). From the perspec-ive of construct operationalisation, Petrides and Furnham (2001)ndicate that measuring emotional intelligence through self-reportuestionnaires leads to operationalisation of the construct as a per-onality trait (classified as trait EI). Trait EI is expected to function aspersonality trait and operate within the personality domain. Sub-

equent to this classification, a number of studies have investigatedelf-reporting emotional intelligence as a personality trait andithin the personality domain (e.g. Petrides et al., 2007; Prentice

nd King, 2012).Personality traits have been discussed extensively as a valid

redictor of employee performance in a variety of contexts (e.g.rei and McDaniel, 1998; Spivey et al., 1979). However, Brownt al. (2002) have noted that such traits cannot explain the sizeableariance in ratings of employee service performance. Brown et al.roposed the incorporation of second traits (referred to as surfaceraits) into the basic personality traits–performance relationship.

n their study, Brown et al. identified customer orientation as aurface trait and investigated its mediation role in the relationshipetween personality traits and service performance. Their resultsonfirmed the mediation model and the incorporation of customer

ospitality Management 32 (2013) 287–294 289

orientation as a surface trait enhancing the evaluation of serviceperformance. Since self-reporting emotional intelligence is classi-fied as a personality trait, its influence on performance evaluationmay be enhanced by the addition of a surface trait.

Surface traits, also referred to as surface behaviours, indicate apersistent tendency towards certain behaviours in particular sit-uations, and manifest themselves as dispositions, inclinations ortendencies to behave in certain ways. They are more abstract thanconcrete behaviours and differ from basic personality traits, whichare more enduring and can predict behaviours in diverse situa-tions (Brown et al., 2002; Moven and Spears, 1999). Brown et al.(2002) have suggested that personality traits may be too distantfrom actual focal behaviours to predict employee performance. Sur-face traits are aligned with specific behaviours that impact directlyon performance evaluation. Since adaptability may be described asa tendency towards adjusting behaviours during service encoun-ters, this description is consistent with the concept of surface traits.On the basis of the foregoing discussion, this study proposes adapt-ability as a surface trait and investigates its relationship with traitemotional intelligence and service performance in the context ofcasino premium players. Drawing on Brown et al.’s study, the fol-lowing hypotheses are proposed:

Hypothesis 3. Adaptability will mediate the relationship betweentrait emotional intelligence and host performance.

Hypothesis 4. With adaptability as a mediator, the mediationmodel will explain more variance in host performance than a modelwithout mediation.

5. Methods

5.1. Participants

The setting for the study was one of the largest casino and enter-tainment operations located within the Asia Pacific region. Therespondent sample was drawn from all casino hosts who workedwithin the premium-play gaming areas of the survey casino andhad direct interactions with premium players. This approach wasadopted because the casino is sufficiently large to generate an ade-quate sample. Secondly, emotional intelligence has been commonlyacknowledged as important in the provision of frontline service.Thirdly, a single entity was chosen because of the need to con-trol for a variety of extraneous, uncontrollable variables, such asdifferent corporate and cultural values, market performance, andgeographic location.

From a total of 400 surveys distributed to prospective respon-dents, 261 usable responses were returned (65%). Of the total usablesample, 120 were male, and 141 were female. The age of the par-ticipants ranged from 18 to 55, and 90% were in the 18–35 agegroup. Almost a quarter (37 or 24.3%) had completed their stud-ies at secondary school level, with the rest possessing a diploma oruniversity degree. It may be concluded that the respondents wererelatively well educated.

5.2. Measures

5.2.1. Emotional intelligenceConsistent with Petrides and Furnham’s (2000) conceptualisa-

tion of trait EI, the present study uses the self-report EI test (SREIT)developed by Schutte et al. (1998). This test was in turn based onan earlier “ability model” which was first developed by Saloveyand Mayer (1990). It is a 33-item self-report measure that includes

items such as “By looking at their facial expression, I recognizethe emotions people are experiencing” and “I easily recognize myemotions as I experience them.” The scale items are displayed inAppendix A. According to Schutte et al. (1998), the scale had the

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enefit of generating correlations with theoretically related con-tructs, such as alexithymia, attention to feelings, clarity of feelings,ood repair, optimism and impulse control. It exhibited good inter-

al consistency and test–retest reliability, predictive validity, andiscriminant validity with strong results for each analysis (Schuttet al., 1998). These positive attributes led to its adoption in the cur-ent study. Data were collected on a five-point Likert scale withrepresenting strongly disagree and 5 representing strongly agree.

hese labels indicate the extent to which each item describes them.igher total scores are reflective of greater self-report emotional

ntelligence. The Cronbach alpha coefficient reported for this scaleas .91.

.2.2. AdaptabilityHartline and Ferrell’s (1996) 10-item unidimensional adaptabil-

ty scale was used for the purposes of measuring host adaptability.he authors operationalised employee adaptability as the abilityf service employees to adjust their behaviours to the interper-onal demands of service encounters. In the current investigationhe 10 items were reworded to suit the casino context, withtems 4, 6 and 10 being negatively worded. This involved assess-ng the adaptive behaviour of casino hosts when adjusting theirpproach towards premium players during service encounters. Par-icipants were asked to indicate their level of agreement withach item, using a five-point Likert scale ranging from “stronglyisagree” to “strongly agree.” Higher scores are reflective oftronger adaptability. The applicable Cronbach alpha coefficientas .86.

.2.3. PerformanceThe performance measure that has been used in the present

tudy was consistent with the approach to staff performanceppraisal employed by the survey organisation. This approachnvolves measuring the service performance of employees and theirontributions against the requirements and standards applicableo the relevant job and against their peers. As was the case with

ost previous research on performance measurement the studyelied on respondent self-reporting (e.g. Brown et al., 2002; Buschnd Bush, 1978; Sujan et al., 1994). Churchill et al. (1985) haveemonstrated that self-reporting does not generally lead to biasedutcomes or inflated assessments. Each item was assessed using ave-point scale, ranging from 1 (lowest) to 5 (highest). The appli-able Cronbach alpha coefficient for this scale in the present studyas .78.

.3. Procedure

A self-report questionnaire was developed using a paper-encil test. Information was collected about adaptability, emotional

ntelligence, and host performance. Respondents were given anssurance of anonymity in the instructions which accompa-ied each of the documents. The survey packets included aover letter, which provided an introduction and explanation ofhe significance and objectives of the research, an expressionf thanks to prospective respondents, a consent form, a ques-ionnaire, and a pre-paid envelope. Detailed instructions werencluded to guide respondent participation. The questionnaire was

istributed to prospective respondents during work shifts, andould be completed at home or at off-peak times during week-ay work shifts. Responses were required within 2 months ofeceipt.

ospitality Management 32 (2013) 287–294

6. Results and analysis

6.1. Factor analysis

6.1.1. Emotional intelligenceAlthough the original SREIT was unifactorial, a number of

researchers (e.g. Ng et al., 2010; Petrides and Furnham, 2000;Saklofske et al., 2003) have attested its multi-dimensionality, andthe findings were inconsistent. Despite the challenge of inconsis-tency, a four-factor solution has been commonly cited (see Gignac,2005). Consistent with the four factors that were identified inPetrides and Furnham’s (2000) exploratory factor analysis, theresearchers in the present study opted to deploy confirmatoryfactor analysis (CFA) to generate the four-factor model for SREIT.The CFA analyses were based on a Pearson Co-variance matrixand Maximum Likelihood Estimation (MLE). Following Hu andBentler’s (1999) suggestion, two absolute close-fit indices (SRMRand RMSEA) and two incremental close-fit indices (TLI and CFI)were chosen to evaluate model fit, with SRMR and RMSEA < .06 andTLI and CFI > .95 considered as good fitting. The results show that thefour-factor model produced �2(251) = 534.21, p < .001, SRMR = .048and RMSEA = .051, indicating a good model fit. Though the incre-mental close-fit index values (CFI = .946 and TLI = .937) were slightlylower than .95, they were considered acceptable (see Gignac, 2005).The results of standardised residual co-variances and modificationindex values indicate no conspicuously significant changes to themodel. The average variance extracted for each factor was over.50, indicative of adequate convergence (Fornell and Larcker, 1981).Furthermore, the composite reliability was acceptable for each ofthe factors. All of the factor loadings shown in Table 1 were posi-tive and statistically significant. On this basis, the four-factor modelwas supported. Consistent with Petrides and Furnham’s (2000) sug-gestion, the four factors were labelled “Mood Regulation” (MR),“Appraisal of Emotions” (AE) “Social Skills” (SS) and “Utilisation ofEmotions” (UE) with Cronbach alpha coefficients of .88, .79, .74, and.69 respectively. The results were comparable with those evidentin previous research (Petrides and Furnham, 2000; Saklofske et al.,2003).

To identify the measurement model that best fits the data, assuggested by Wilkins et al. (2007), three competing models wereanalysed. The first model tested emotional intelligence as a single-factor construct. The second operationalised emotional intelligenceas a first-order four-factor model. The third operationalisedemotional intelligence as second-order construct, with the fouraforementioned first-order factors being sub-dimensions. Theresults indicate that the second model is more desirable, as it pro-duced better model fitting values (CFI = .949, TLI = .951, SRMR = .043,RMSEA = .054, �2(247) = 462.17, p < .001) against the values gen-erated from the first model (CFI = .827, TLI = .811, SRMR = .063,RMSEA = .067, �2(271) = 627.35, p > .05) and from the third model(CFI = .917, TLI = .923, SRMR = .056, RMSEA = .062, �2(257) = 597.52,p < .05). On this basis, the first-order four-factor emotional intelli-gence will be used for the purposes of subsequent analysis.

6.2. Method of analysis

The hypotheses were tested using structural equation mod-elling. To examine the mediation effect of adaptability betweenemotional intelligence and host performance, two substantivemodels were estimated and compared through the use of acompeting model analysis. The four SREIT factors were enteredfor the purposes of model testing, as shown in Fig. 1. In the

first case (the direct effects model), the effect of the four-factoremotional intelligence on host performance was estimated. Thesecond case (the mediation model), represents the hypothesisedmodel and involved estimating the effects of (1) the four-factor

C. Prentice, B.E.M. King / International Journal of Hospitality Management 32 (2013) 287–294 291

Table 1The results of confirmatory factor analysis for SREIT.

Scale item Factorloadings

Alpha 1 Alpha 2 Compositereliability

Ave.

MR .88 .90 .91 .7610 .561

3 .52323 .53214 .64121 .65612 .55228 .475

2 .72031 .587

AE .79 .93 .93 .7118 .67325 .54129 .453

5 .56219 .42532 .48522 −.61715 .521

9 .544

SS .74 .73 .87 .6511 .417

4 .49913 .49530 .67126 .618

6 .42224 .52316 .487

1 .4638 .517

33 .761

UE .67 .55 .69 .557 .468

20 .71317 .59827 .671

Fit indices: �2(251) = 534.21, �2/df = 5.42, p = .000, SRMR = .048, RMSEA = .051,CFI = .946, TLI = .927. MR, Mood Regulation; AE, Appraisal of Emotions; SS, SocialSkills; UE, Utilisation of Emotions; Alpha 1, Cronbach alpha for this study; Alpha 2,C

etpshftiaS

MR

UE

AE

Host

performance

SS

Adaptability

intelligence on the part of the host, the greater the adaptability indealing with casino premium players. In particular, MR (Beta = .51,

TD

ET

ronbach alpha from Petrides and Furnham (2000). Ave, average variance extracted.

motional intelligence on adaptability, (2) the four-factor emo-ional intelligence on host performance, and (3) adaptability onerformance. The mediation effects of adaptability may con-idered to be established if the mediation model yields (1)igher variances, (2) a significant relationship between the

our-factor emotional intelligence on adaptability, (3) substan-ially reduced or insignificant effect of the four-factor emotionalntelligence on performance, and (4) a significant effect for adapt-

bility on performance. This approach is consistent with that ofingh et al.’s (1994) study.

able 2escriptive statistics and bi-variate correlations.

M SD EI MR

EI 134.5 14.73MR 51.21 2.41 .67** .76AE 18.25 2.88 .56** .60**

SS 18.8 2.67 .62** .55**

UE 31.57 3.75 .69** .53**

Adapt 17.4 2.78 .41** .50**

HP 20.75 3.34 .34** .51**

I, emotional intelligence; MR, Mood Regulation; AE, Appraisal of Emotions; SS, Social Skhe figures in bold are squared multiple coefficients.** Correlation is significant at the .01 level (2-tailed).

Fig. 1. The hypothesised mediation model between first-order four-factor emo-tional intelligence, adaptability and host performance.

7. Results

7.1. Measurement validity

Prior to the conduct of the structural equation analyses, itemscorresponding to each dimension of emotional intelligence weresummed to obtain a composite score for MR, AE, SS and UE.Consistent with Hartline and Ferrell’s (1996) study, the presentresearchers conceived of adaptability as a composite measure, asummed indicator was used for the construct. The co-variancematrix was an input to the structural equation analysis. Descrip-tive statistics and bivariate correlations for the study variablesare presented in Table 2. It was found that the four SREIT factorsare significantly correlated (p < .01). The values range from .42 to.60, indicating no redundancy or violation of multicolinearity. Thecorrelations between the four factors of emotional intelligence,adaptability and performance ratings range from .36 to .51. Theshared variance between these concepts does not exceed 30%,which suggests that they are empirically distinct constructs. Thesquared multiple coefficients values shown in Table 2 indicate thatall items have a significant loading on their corresponding con-structs, demonstrating adequate convergent validity.

7.2. Hypothesis testing

Consistent with Hypothesis 1, Table 3 reveals that emotionalintelligence explained 46% of the variance in host adaptability(R2 = .46, p < .0005). This indicates that the greater the emotional

t = 5.83, p < .0005) and AE (Beta = 0.27, t = 3.28, p < .001) made sig-nificant contribution to host adaptability. In turn, the incidence

AE SS UE Adapt HP

.71

.42** .65

.54** .51** .55

.36** .36** .44** .53

.32** .28** .49** .37** .52

ills; UE, Utilisation of Emotions; HP, host performance.

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Table 3Results of mediation model testing: adaptability as the mediator between trait emo-tional intelligence and host performance.

Parameter Direct effects model Mediation model

Structural path Standardised coefficients Standardised coefficientsMR → AT .51***

AE → AT .27***

SK → AT .09UE → AT .13R2 = .46 for four-factor EI in AT

AT → HP .47***

R2 = .31 for AT in HP

MR → HP .34*** .16AE → HP .10 .06SK → HP .09 .05UE → HP .41*** .19**

R2 for HP .39*** .72***

Goodness of fit statistics�2 82 156df 22 35RMSEA .04 .03NNFI .96 .97CFI .97 .99

The direct effects model includes only the direct effects between EI or the four factorsof SREIT and host performance.The mediation model includes two direct effects: (1) EI or the four factors of SREITand adaptability; (2) adaptability and host performance.Notes: RMSEA, root mean square error of approximation; NNFI, nonnormed fit index;CFI, comparative fit index; MR, Mood Regulation; AE, Appraisal of Emotions; SK,Social Skills; UE, Utilisation of Emotions; AT, adaptability; HP, host performance.

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f adaptability produces a substantively significant effect on hosterformance (R2 = .31, p < .0005). These results supported Hypothe-es 1 and 2.

For the purposes of testing the mediation model, Table 3 sum-arises results from the structural equation analyses for the direct

nd mediation effects models. Drawing upon the fit index values,oth models have a reasonable fit with the data. The results indi-ate that relations between the study variables were consistentith the conditions of a mediation model, as noted previously. The

nalyses indicate a discernible mediating effect. However, the twoodels differ significantly in their capacity to explain variances in

erformance outcomes. The mediation model which incorporatesdaptability accounts for 72% of host service performance, com-ared with 39% in the case of the direct model. The effects of theour factors on host performance are attenuated after adaptabilityas been controlled. In particular, the effects of MR and AE on per-

ormance are reduced significantly from .34 to .16, and .41 to .19espectively. These results supported a partial mediation model,nd indicate that the mediation model provided additional vari-nce in the performance of hosts. On this basis, Hypotheses 3 andwere confirmed.

. Conclusions and discussion

This study has discussed the importance of the premium playeregment and the role of casino hosts as service representatives.ocusing on the service encounter between casino hosts andremium players, the research has investigated the relationshipetween emotional intelligence, adaptability and host perfor-ance. These relationships were examined by testing a mediationodel where adaptability functioned as a mediator between emo-

ional intelligence and service performance. The research hasrawn upon the surface trait theories discussed in Brown et al.’s2002) study, with emotional intelligence identified as a basic per-onality trait and adaptability as a surface trait. The rationale for

ospitality Management 32 (2013) 287–294

this investigation is that: (1) according to the theories of relation-ship marketing and the service profit chain, host performance hasimplications for casino profitability. Hence, it is important to under-stand the factors influencing performance evaluations; (2) theservice encounter between casino host and premium players incor-porates a substantial emotional component, and host emotionalintelligence offers a means of managing the encounter effectivelyand thereby influencing the evaluation of service performance;(3) host adaptability is also important in dealing with premiumplayers because of their volatility; finally, the surface traits con-cept indicates that the relationship between basic personality traitsand performance ratings can be improved by adding them asmediators.

The results of the structural equation analyses confirmed themerit of a partial mediation model and supported the hypothesisthat incorporating adaptability as a mediator enhances variance inthe performance ratings that is explained by emotional intelligencealone. This finding is consistent with the mediation relationshippostulated by Brown et al. (2002) between basic personality traits,surface traits and service performance evaluation. It also supportsPetrides and Furnham’s (2000) classification, whereby they notedthat trait EI is embedded within the framework of personality. Thefindings have the following implications: (1) the service encounterbetween casino hosts and premium players is not only emotionallycharged, but also variable. To manage such encounters efficiently,casino hosts need to be emotionally intelligent and adaptable whendealing with casino premium players. A combination of emotionalintelligence and adaptability will enhance performance evalua-tion more than a single attribute. Since emotional intelligence andadaptability are learned behaviours (see Boyatzis et al., 1995; Parkand Holloway, 2003; Slaski and Cartwright, 2002), casino hostscould benefit from relevant training to help them to improve pre-mium player satisfaction and loyalty, with likely consequencesfor casino profitability. (2) The myth that basic personality traitspredict performance ratings but that the predicting effects arenot substantial can be demystified by incorporating surface traits.Although service traits were introduced into the literature somedecades ago, they have been rather under-researched, particu-larly in the context of performance evaluation. The present studyhas added to knowledge about performance research and supple-ments the scholarly literature on surface traits. It also suggests thatresearchers should continue to identify additional surface traits andthat practitioners should consider this aspect during recruitmentand training.

Investigation of the relationship between the four SREIT fac-tors and adaptability in this study has shown that trait EI issignificantly related to employee adaptability. The coefficient anal-ysis has shown that MR (managing emotions) and AE are theonly ones of the four trait EI factors that significantly influencethe criterion variable. This may be attributable to the organisa-tional boundary-spanning role occupied by casino hosts. Whenpracticing an adaptive approach in such settings, casino hostsmust deal with the gambler emotions that are evident duringwinning and losing. Emotional management skills can influencea customer’s formation of emotions and appraisals which inturn affects their attitudes and behaviours. A positive attitudeand strong behavioural intentions reflect the appropriatenessof the employee’s approach to customer contact. To be ableto manage emotions, one has to understand or appraise emo-tions effectively. These two processes are connected logically.The practice of adaptability, on the other hand, requires frontlineemployees to adjust their behaviours to meet the interpersonal

demands of service encounters based on perceived information.The perception process implies that the employee’s appraisalof customer emotions will facilitate the adjusting of encounterbehaviours.

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. Implications and future research

Although this study was conducted in the Asia Pacific region,he findings may be applicable to casinos in other settings such asas Vegas in the USA and casinos in Australia (e.g. Crown, Mel-ourne and Burswood, Perth) that cater to the premium playeregment. The following implications are proposed: first, in settingsuch as casinos where adaptability is applicable the results indicatehat emotional intelligence should be incorporated into person-el recruitment and selection; second, the influence of casinoost adaptability on performance through the effects of mediationuggests that training is required to build the capacity for adaptabil-ty, in order to improve employee performance and subsequentlynhance casino profitability, consistent with the concept of servicerofit chain and the theory of relationship marketing. Emotional

ntelligence should be integrated within casino training programso facilitate employee adaptability and behavioural adjustmentsuring interactions with casino players. As the investigation wasdministered to a single cohort, prospective researchers may exam-ne casinos in other different locations with a view to strengtheninghe capacity to generalise the findings. Finally it may also be worthncorporating player perceptions of casino hosts from a serviceuality perspective.

ppendix A. Item descriptions for the study variables

motional intelligence. I know when to speak about my personal problems to others. When I am faced with obstacles, I remember times I faced similar obstacles andvercome them. I expect that I will do well on most things I try. Other people find it easy to confide in me. I find it hard to understand the non-verbal messages of other people. Some of the major events of my life have led me to re-evaluate what is

mportant and not important. When my mood changes, I see new possibilities. Emotions are one of the things that make my life worth living. I am aware of my emotions as I experience them0. I expect good things to happen1. I like to share my emotions with others2. When I experience a positive emotion, I know how to make it last3. I arrange events others enjoy4. I seek out activities that make me happy5. I am aware of the non-verbal messages I send to others6. I present myself in a way that makes a good impression on others7. When I am in a positive mood, solving problems is easy for me8. By looking at their facial expressions, I recognise the emotions people arexperiencing9. I know why my emotions change0. When I am in a positive mood, I am able to come with new ideas1. I have control over my emotions2. I easily recognise my emotions as I experience them3. I motivate myself by imagining a good outcome to tasks I take on4. I compliment others when they have done something well5. I am aware of the non-verbal messages other people send6. When another person tells me about an important event in his or her life, Ilmost feel as though I experienced this event myself7. When I feel a change in emotions, I tend to come up with new ideas8. When I am faced with a challenge, I give up because I believe I will fail9. I know what other people are feeling just by looking at them0. I help other people feel better when they are down1.I use good moods to help myself keep trying in the face of obstacles2. I can tell how people are feeling by listening to the tone of their voice3. It is difficult for me to understand why people feel the way they do

ost adaptability. Every customer requires a unique approach. When I feel that my approach is not working, I can easily change to anotherpproach

. I like to experience with difference approaches. I don’t change my approach from one customer to another customer (negative). I am very sensitive to the needs of my customers. I find it difficult to adapt my style to certain customers (negative). I vary my approach from situation to situation

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8. I try to understand how one customer differs from another9. I feel confident that I can effectively change my approach when necessary10. I treat all customers pretty much the same (negative)

Host performance1. Punctuality and attendance2. Job knowledge3. Quantity of work4. Quality of work5. Human relations and customer relations6. Dependability7. Interest8. Initiative9. Diligence10. Appearance

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Catherine Prentice PhD is Lecturer in Marketing at Swinburne University, Vic,Australia. Her research interests include casino marketing, services and relation-ship marketing, relationship selling, emotional labour, emotional intelligence andthe FFM of personality.

Brian King is Professor of Tourism Management and Pro Vice-Chancellor at VictoriaUniversity in Melbourne, Australia. He has published widely in the field of tourismmarketing and is founding and current joint editor-in-chief of the internationaljournal Tourism, Culture & Communication.