The Service Industries JournalVol. 28, No. 8, October 2008, 1151–1165ISSN 0264-2069 print/1743-9507 online# 2008 Taylor & FrancisDOI: 10.1080/02642060802188023http://www.informaworld.comDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

83In this respect, the physical environment of a service situation is important because it can eitherenhance or suppress customers’ emotions, which may influence customer satisfaction and subsequentbehaviors (Sayed, Farrag, & Belk, 2003; Wakefield & Blodgett, 1999).In service consumption situations, SERVICESCAPE, defined as “the man-made, physicalsurroundings as opposed to the natural or social environment” (Bitner, 1992), has beenstudied for more than a decade. SERVICESCAPE has been accepted as an important determinantof customer psychology (e.g. satisfaction and emotion) and behavior (e.g. patronage andpositive word-of-mouth), when a service is consumed primarily for hedonic reasons and whencustomers spend moderate to long time in the service delivery setting (Wakefield & Blodgett,1994). For instance, customers of upscale restaurants often spend 2 hours or more, sensing physicalsurroundings consciously and unconsciously before, during, and after their meal. Whilefoods and services should be of acceptable quality, pleasing SERVICESCAPE (e.g. lighting,de´cor, and layout) may influence the degree of positive emotions and subsequent behavior(Donovan & Rossiter, 1982; Mehrabian & Russell, 1974).Although there is a substantial amount of research about the impact of the physical environmenton human psychology and behavior, previous research has confined itself to one or a fewparticular physical environmental elements (e.g. music, color, and aroma). In other words,studies about the combined effect of physical environments have been scarce. In addition,researchers have paid limited attention to understanding how physical environments influencecustomers within the service industry context. Since physical environments are obviously oneof influential factors toward a customer’s psychological states and behaviors in service industries,there is a need to understand how customers’ emotional states and behavior changedepending upon their perception of environmental elements. Thus, this study intended to fillthe research gaps by investigating the influences of customer perceptions of physical environmenton their emotions and their intended behaviors in the service industry, especially in theupscale restaurant setting.The primary purpose of this study was to investigate how customers’ perceptions of diningenvironments influence customer emotions and behavioral intentions (BI) in the upscale restaurantcontext. To achieve this purpose, this study proposed a conceptual model by modifying theMehrabian–Russell’s (1974) environmental psychology model. To assess how customers perceivedining environments, DINESCAPE, defined as man-made physical and human surroundingsin the dining area of upscale restaurants (Ryu & Jang, 2008) was used in this study. Thus,the specific objectives of this paper were (1) to examine the construct validity of a modified

Mehrabian–Russell (1974) model (M–R model) in the upscale restaurant context, (2) to investigatethe effects of customers’ perception on dining environments on emotional states (pleasureand arousal) and BI, and (3) to test the interdependence between pleasure and arousal in themodified M–R model.M–R modelThe M–R (1974) model, which presented a role of physical environments, has received muchattention in environmental psychology, retailing, and marketing. This model is divided intothree parts: environmental stimuli, emotional states, and approach or avoidance responses.The environment creates an emotional response in individuals which, in turn, elicits eitherapproach or avoidance behavior. The application of the model facilitates understanding theeffects of environmental changes on emotions and human behavior. The model suggests that1152 K. Ryu and S. JangDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

84environment has an individual put at an emotional state that can be characterized as one of three:pleasure, arousal, and dominance, and these three emotional states mediate approach–avoidancebehaviors in a wide range of environments. Pleasure refers to the extent to which individuals feelgood, happy, pleased, or joyful in a situation, while arousal denotes the degree to which individualsfeel stimulated, excited, or active. Dominance dimension means the extent to which aperson feels influential, in control, or important. However, empirical studies have reportedthat pleasure and arousal underlie affective responses to any environments while dominancedid not have a significant effect on approach or avoidance behaviors (Russell & Pratt, 1980;Ward & Russell, 1981). Thus, dominance in relation to approach or avoidance behavior hasnot been given much attention in recent studies. Therefore, this study also used only two dimensionsof emotional states: pleasure and arousal.It is noted that physical environment could be considered the same as the first component ofthe M–R model: environmental stimuli. In addition, BI in this study is congruent withapproach–avoidance behavior, which is the third component of M–R model. Therefore, theM–R model, which incorporates the concepts of the physical environment, emotions, andapproach–avoidance behaviors, could be used as a theoretical framework for this study.Environmental psychologists (Donovan & Rossiter, 1982; Mehrabian & Russell, 1974)believe that people’s feelings and emotions ultimately influence what they do and how theydo it. Further, people respond with different sets of emotions to different environments, andthese emotions prompt them to approach or avoid the environment. Approach behaviors arepositive responses (e.g. a desire to stay in a particular facility) whereas avoidance behaviorsmean negative responses. As an example, pleasure could increase the time shoppers spend instores as well as the amount of money they spend (Baker, Levy, & Grewal, 1992; Donovan &Rossiter, 1982; Donovan, Rossiter, & Nesdale, 1994). Therefore, two hypotheses are proposedhere regarding the relationship between emotions and BI in the upscale restaurant setting.H1: Pleasure will have a positive effect on BI.H2: Arousal will have a positive effect on BI.Physical environment, emotions, and BI

To measure customer perceptions about the physical environment, this study used the DINESCAPEscale (Ryu & Jang, 2008). DINESCAPE exclusively covers the internal dining environmentof restaurants but does not deal with external environments (e.g. parking space andbuilding design) or non-dining internal environments (e.g. restroom and waiting area). SixDINESCAPE constructs (facility aesthetics, lighting, ambience, layout, dining equipment, andemployees) and the measurement items used in this study are presented in Table 1. As explainedin the M–R model, the physical environments of restaurants are expected to influence customers’emotional states, and thus ultimately affect BI. Therefore, this section provides the explanationabout six DINESCAPE elements and proposes hypotheses for the impacts of physicalenvironments on emotions and BI.Facility aestheticsFacility aesthetics refer to architectural design, along with interior design and de´cor, all of whichcontribute to the attractiveness of the dining environment (Wakefield & Blodgett, 1994). Oncecustomers enter the dining area of an upscale restaurant, they often spend hours observingThe Service Industries Journal 1153Downloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

85(consciously or subconsciously) the interior of the dining area, which is likely to affect their attitudestowards the restaurant (Baker, Berry, & Parasuraman, 1988). In addition to the appeal ofthe architectural design, customers may be influenced by the color schemes of the dining area.Different colors lead to different moods, emotions, and feelings, and subsequently influence BI(Bellizzi & Hite, 1992; Crowley, 1993; Gorn, Chattopadhyay, Yi, & Dahl, 1997; Mikellides,1990). Other aspects of interior design, such as furniture, pictures/paintings, plants/flowers, orwall decorations may also serve to enhance the perceived quality of dining environments, creatingemotions (pleasure and arousal) in a customer and influencing BI. Thus, it is proposed that:H3a: Facility aesthetics will have an effect on pleasure.H3b: Facility aesthetics will have an effect on arousal.H3c: Facility aesthetics will have an effect on BI.LightingLighting can be one of the most salient physical stimuli in upscale restaurants. Restaurateursmay experientially learn that subdued, warm, and comfortable lighting symbolically conveysfull service and relatively high prices, whereas bright lighting may symbolize quick serviceand lower prices. Research has shown the impact of lighting level preferences on individuals’Table 1. Measurement properties.Factors (Cronbach’salphas)Standardized factorloadings Item reliabilitiesCompositereliabilities AVE1. DC1: Facility aesthetics(0.87)0.90 0.65FA1/FA2/FA3/FA4/FA5 0.84/0.78/0.81/0.80/0.80 0.71/0.61/0.66/0.64/0.64

2. DC2: Lighting (0.91) 0.94 0.85LI1/LI2/LI3 0.91/0.90/0.95 0.83/0.81/0.903. DC3: Ambience (0.89) 0.93 0.87AM1/AM2 0.95/0.92 0.90/0.854. DC4: Layout (0.85) 0.89 0.73LA1/LA2/LA3 0.86/0.92/0.76 0.74/0.85/0.585. DC5: Dining equipment(0.83)0.87 0.69SP1/SP2/SP3 0.83/0.86/0.80 0.69/0.74/0.646. DC6: Employees (0.80) 0.88 0.78EM1/EM2 0.96/0.80 0.92/0.647. Pleasure (0.93) 0.96 0.85PL1/PL2/PL3/PL4 0.91/0.95/0.95/0.89 0.83/0.90/0.90/0.798. Arousal (0.81) 0.85 0.66AR1/AR2/AR3 0.84/0.84/0.76 0.71/0.71/0.589. Behavioral intention (0.90) 0.92 0.75BI1/BI2/BI3/BI4 0.92/0.95/0.77/0.80 0.85/0.90/0.59/0.64Note: FA1: Attractive paintings/pictures, FA2: Appealing Wall de´cor, FA3: Beautiful plants/flowers, FA4: Warm colors,FA5: High-quality furniture, LI1: Warm lighting, LI2: Welcoming lighting, LI3: Comfortable lighting, AM1: Relaxingmusic, AM2: Pleasing music, LA1: Enough seat space, LA2: Crowded seating arrangement, LA3: Easy-to-movelayout, DE1: High-quality tableware, DE2: Attractive linens, DE3: Attractive table setting, EM1: Attractiveemployees, EM2: Neat and well-dressed employees, PL1: Unhappy–happy, PL2: Annoyed–pleased, PL3: Bored–entertained, PL4: Disappointed–delighted, AR1: Depressed–cheerful, AR2: Calm–excited, AR3: Indifferent–surprised, AR4: Sleepy–awake, BI1: Patronage, BI2: Recommendation, BI3: Staying longer, BI4: Spending more.AVE ¼ Average variance extracted.1154 K. Ryu and S. JangDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

86emotional responses (Kumari & Venkatramaiah, 1974; Kurtich & Eakin, 1993). Kumari andVenkatramaiah (1974) reported that illumination is directly associated with the changes in physiologicalarousal. In addition, the type of lighting could influence an individual’s perception ofthe quality of space, changing his/her awareness of physical, emotional, and psychologicalaspects of the space and accordingly altering BI (Kurtich & Eakin, 1993). Thus, it is proposedthat:H4a: Lighting will have an effect on pleasure.H4b: Lighting will have an effect on arousal.H4c: Lighting will have an effect on BI.AmbienceAmbience means intangible background characteristics that tend to affect the non-visual sensesand may have a subconscious effect on customers. These background conditions usually includemusic, scent, and temperature (Baker, 1987). Previous research has shown that backgroundmusic can (1) affect customer perceptions of stores (Mattila & Wirtz, 2001; North & Hargreaves,1998); (2) increase sales (Mattila & Wirtz, 2001; North & Hargreaves, 1998); (3) influence purchaseintentions (Baker et al., 1992; North & Hargreaves, 1998); (4) generate significantlyenhanced affective response such as satisfaction and relaxation (Oakes, 2003); (5) increase shoppingtime and waiting time (Yalch & Spangenberg, 2000); (6) decrease perceived shopping timeand waiting time (Baker & Cameron, 1996; Hui, Dube, & Chebat, 1997; Yalch & Spangenberg,2000); and (7) influence dining speed (Milliman, 1986). In addition, the influence of pleasantscents as a powerful tool to increase sales has gained much attention in retail businesses(Bone & Ellen, 1999; Hirsch, 1995; Mattila & Wirtz, 2001). Ambient odors might also influencea consumer’s mood, emotion, or subjective feeling state (Bone & Ellen, 1999; Hirsch, 1995).

Psychological research also suggests that certain temperatures are associated with negativeemotions. For example, Bell and Baron (1977) argued that low temperatures (e.g. around628F or lower) were associated with negative affective states. Thus, it is proposed that:H5a: Ambience will have an effect on pleasure.H5b: Ambience will have an effect on arousal.H5c: Ambience will have an effect on BI.LayoutLayout means the way in which objects (e.g. machinery, equipment, and furnishings) arearranged within the environment. Just as the layout in discount stores facilitates the fulfillmentof functional needs, a well-designed layout can also facilitate fulfillment of hedonic or pleasureneeds (Wakefield & Blodgett, 1994). A layout may have a direct effect on customers’ qualityperceptions, pleasure, and excitement levels, and indirectly on the desire to return (Wakefield& Blodgett, 1994). Service or retail facilities that are specifically designed to add some levelof pleasure or excitement to the service experience, such as in upscale restaurants, shouldensure that the layout plan is appropriate for their customers. Thus, the following hypothesesare proposed:H6a: Layout will have an effect on pleasure.H6b: Layout will have an effect on arousal.H6c: Layout will have an effect on BI.The Service Industries Journal 1155Downloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

87Dining equipmentRaajpoot (2002) found that the service product was one of the most important tangible qualitiesof restaurant services. The dining equipment dimension should be an especially importantelement in upscale restaurant design. Upscale restaurants should be designed to deliver a prestigiousimage to attract upper-class customers to their intended market. For example, highqualityflatware, china, glassware, and linen can be good tools to influence customers’ qualityperceptions. The way in which the table is decorated (for instance, with an attractive candle)can also make customers feel that they are in a prestigious or elegant environment. Eventhough this dimension has not been much examined in the academia probably because it isvery unique and valid only to restaurants, dining equipment is presumed to influence diners’emotional states and is eventually connected to BI. Thus, the hypotheses are proposed asfollows:H7a: Dining equipment will have an effect on pleasure.H7b: Dining equipment will have an effect on arousal.H7c: Dining equipment will have an effect on BI.EmployeesSocial elements refer to people (employees and customers) in the service setting (Baker, 1987).The social factors usually include employee appearance/number and the dress or physicalappearance of other customers. However, since it is difficult to control physical appearance ofother customers in the restaurant industry, only employee appearance as well as number wasused to assess social elements, and they were labeled as employees. Baker et al. (1992)studied the effects of social cues (number/friendliness/appearance of employees) and reportedthat the more social cues present in the store environment, the higher the customers’ arousal.

Tombs and McColl-Kennedy (2003) also argued that employees are related to the desiredsocial density, which influences customer affective and cognitive responses as well as repurchaseintentions. Thus, the following hypotheses about employees are proposed:H8a: Employees will have an effect on pleasure.H8b: Employees will have an effect on arousal.H8c: Employees will have an effect on BI.Impact of arousal on pleasureThe M–R model posited that pleasure and arousal were the two orthogonal dimensions representingindividual emotional or affective responses to a wide range of environments.However, more studies expressed their opposition to the independency of pleasure andarousal dimensions. For example, Donovan and Rossiter (1982) reported a positive relationshipbetween pleasure and arousal dimensions. Donovan et al. (1994) also pointed out a possiblefailure to construct an unambiguous arousal factor, possibly because the pleasure and arousalfactors are independent, yet correlated factors. Furthermore, some marketing studies claimedthat arousal influences pleasure (Babin & Attaway, 2000; Chebat & Michon, 2003; Wakefield& Baker, 1998). Thus, the following hypothesis is proposed:H9: Arousal will have an effect on pleasure.1156 K. Ryu and S. JangDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

88The mediating role of emotionThe research framework of this study took a few steps toward a more complete picture of howperceived physical environments, emotions, and BI were related. Particularly, the mediatingrole of emotions between physical environments and BI was also investigated in this study.Some previous studies suggest a direct link between physical environments and outcomes suchas customer satisfaction and BI (Chang, 2000; Chebat & Michon, 2003). For example, customerswho are strongly motivated by the ambience dimension are more likely to be satisfied, to repatronizethe restaurant, and to engage in positive behaviors such as talking positively about theirexperience. However, a few previous studies have demonstrated that the path fromperceived physicalenvironment to future intentions was not significant in the environmental psychology model(Chang, 2000). There exits no consistency in the mediating role of emotion. Thus, it was worthy ofre-testing emotion as a mediator between physical environments on behavioral responses.Therefore, modifying the M–R model, the following conceptual model regarding therelationships among latent variables was proposed as presented in Figure 1. The dotted linesin Figure 1 signify modified paths from the original M–R model.MethodologyMeasurementThe questionnaire designed for this study was divided into three parts: customers’ perception ofdining environments, emotional states, and BIs. First, to assess how customers perceived theFigure 1. Proposed relationships between latent variables.

Note: Solid lines, links and constructs in the original modified Mehrabian–Russell model; dotted lines, added links and construct to theoriginal Mehrabian–Russell model.

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89quality of dining environments, respondents were asked to rate each DINESCAPE item using a7-point Likert scale (1 ¼ strongly disagree, 7 ¼ strongly agree). The questionnaire included alist of 21 measurement items for six dimensions (facility aesthetics, lighting, ambience, layout,dining equipment, and employees) of the DINESCAPE scale as presented in Table 1.Secondly, emotional states were measured using eight items representing pleasure andarousal dimensions suggested by Mehrabian and Russell (1974). The original Mehrabian andRussell items were slightly adapted to fit the upscale restaurant setting. Subjects evaluatedtheir emotional responses to the physical environment of the upscale restaurant. All itemswere rated on semantic differentials (scale: 23_þ3), in which an emotion and its oppositeconstituted the two ends of the scale. The scale of pleasure consisted of four bipolar measures:unhappy–happy (PL1); annoyed–pleased (PL2); bored–entertained (PL3); disappointed–delighted (PL4). The measure of arousal comprised the following four items: depressed–cheerful (AR1); calm–excited (AR2); indifferent–surprised (AR3); sleepy–awake (AR4).Thirdly, to measure BI, Mehrabian and Russell’s (1974) four aspects of approach–avoidancebehaviors and the scale suggested by Zeithaml, Berry, and Parasuraman (1996) were adaptedto fit the upscale restaurant situation. Subjects were asked to react to the following fourstatements: “I would like to come back to this restaurant in the future” (BI1), “I would recommendthis restaurant to my friends” (BI2), “I am willing to stay longer than I planned atthis restaurant” (BI3), and “I am willing to spend more than I planned at this restaurant”(BI4). Participants responded to these items using a 7-point Likert scale (1 equals; stronglydisagree, 7 ¼ strongly agree).Data and analysisThe data were collected from customers at upscale restaurants in which average guestchecks were more than $20 and which offered full table service and high-quality ambience.Using a convenience-sampling approach, 319 responses were collected at three upscalerestaurants in Midwest and Northwest states. Customers were asked to participate in thestudy, and those who agreed were given a survey questionnaire as they were finishing the endof their main entre´e. After deleting incomplete questionnaires, 253 were finally used fordata analysis.As suggested by Anderson and Gerbing (1988), data were analyzed using the two-stepapproach in which the measurement model was first confirmed and then the structural modelwas tested. Structural equation modeling (SEM) with latent variables via LISREL 8.54 wastested to determine the adequacy of the M–R model by representing the constructs of themodel and testing the hypotheses.ResultsMeasurement modelA series of confirmatory factor analysis (CFA) using maximum likelihood estimation onthe covariance matrix were conducted to test the factor structure of the measurement model(Anderson & Gerbing, 1988). The primary objective of CFA was to assess the convergentand discriminant validities of the construct measures. Based on the results of the first CFA,

three items were deleted due to their low squared multiple correlations. Once these items1158 K. Ryu and S. JangDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

90were deleted, CFA was conducted again. Table 1 presents the Cronbach’s alphas and factor loadingsof the observed items on the latent constructs as estimated by the CFA. Cronbach’s alphas oflatent constructs were satisfactory for all seven constructs (0.80–0.93), indicating acceptableinternal consistency (Nunnally, 1978). The item reliabilities ranged from 0.58 to 0.92, indicatingan acceptable level of reliability (Hair, Anderson, Tatham, & Black, 1998). The compositereliabilities of constructs ranged from 0.85 to 0.96. These values indicated adequate internal consistencyof multiple indicators for each construct in the model since they exceeded 0.70 (Hairet al., 1998). Convergent validity was indicated because factor loadings on their underlying constructswere significant at 0.05 (Anderson & Gerbing, 1988). All latent variables also met thecriteria for discriminant validity since average variance extracted (AVE) for each constructwas greater than the variance explained between the associated constructs (r2) (Fornell &Larcker, 1981). In sum, the assessment of the measurement model showed good evidence ofreliability and validity for the operationalization of the latent variables.Table 2 presents the intercorrelations among the latent variables. All the correlationsbetween constructs were in the expected direction and all were significant (a ¼ 0.05). The correlationsindicated that pleasure (0.64) played a more important role than did arousal (0.44) indetermining BIs. Pleasure was most highly correlated with ambience (0.66), followed by facilityaesthetic (0.52), layout (0.52), and employees (0.52). Similarly, arousal was also most highlyassociated with ambience (0.56), followed by employees (0.49), facility aesthetic (0.48), andlayout (0.45). Finally, it was worth noting that the two independent constructs (pleasure andarousal) were somewhat highly correlated (r ¼ 0.44). The significant positive correlationsuggested a possibility that pleasure and arousal might be causally related as argued by someresearchers (Babin & Attaway, 2000; Chebat & Michon, 2003; Donovan et al., 1994).The overall model fit was evaluated by the chi-square test and other goodness-of-fit statistics.The chi-square test of measurement model was significant (x 2(339) ¼ 966.54, p ¼ 0), which indicatedthat the model did not fit the data. However, since the chi-square statistic is very sensitiveto a large sample size, researchers typically tend to discount the chi-square test and resort toother indices for evaluating the model fit (Bearden, Sharma, & Teel, 1982). Other widelyused goodness-of-fit indices consistently showed that the measurement model fit the data well[x2/df ¼ 2.85; comparative fit index (CFI) ¼ 0.97; Tucker–Lewis index (TLI) ¼ 0.96; rootmean square error of approximation (RMSEA) ¼ 0.07].Table 2. Correlations among the latent constructs.Construct 1 2 3 4 5 6 7 8 91 Facility aesthetics 12 Lighting 0.68 13 Ambience 0.57 0.63 14 Layout 0.51 0.48 0.63 1

5 Dining equipment 0.58 0.52 0.50 0.56 16 Employees 0.45 0.35 0.58 0.54 0.62 17 Pleasure 0.52 0.48 0.66 0.52 0.41 0.52 18 Arousal 0.48 0.46 0.56 0.45 0.39 0.49 0.44 19 Behavioral intention 0.38 0.35 0.48 0.38 0.30 0.39 0.64 0.44 1Note: All correlations are significant at p ¼ 0.05.The Service Industries Journal 1159Downloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

91Structural modelAfter confirming the measurement model, the structural model was then examined. Andersonand Gerbing (1988) suggest using two criteria to evaluate the causal model: fit indices andpath significance. The results of the standardized parameter estimates and t-values are reportedin the upper part of Table 3, and those of the model-fit estimates of the structural modelare shown in the lower part of Table 3. For the overall model, based on model-fit indices(x2/df ¼ 2.85; RMSEA ¼ 0.075; TLI ¼ 0.96; CFI ¼ 0.97), the estimated model provideda good fit to the data. Customer perceptions of dining environments explained 69% of variancein pleasure and 35% of variance in arousal. The overall variance explained in BI was 56%,indicating the model of this study could well predict and explain customer BI.Figure 2 shows the direction and magnitude of the paths of the structural diagram. Solid linesof the Figure 2 indicate statistically significant paths and dotted lines show non-significant paths.As presented in Table 3 and Figure 2, pleasure was statistically significant predictors of customers’BI in upscale restaurants. The results showed that pleasure influenced BI in a positive way(b ¼ 0.46; t ¼ 3.54), supporting H1. However, the coefficient for the effect of arousal on BI(b ¼ 0.08; t ¼ 0.56) was not significant, not supporting H2.Table 3. Structural parameter estimates.Hypothesized pathStandardized pathcoefficients t-value HypothesisH1: Pleasure!BI 0.46 3.54__ SupportedH2: Arousal!BI 0.08 0.56 Not supportedH3a: Facility aesthetic!Pleasure 0.22 3.47__ SupportedH4a: Lighting!Pleasure 20.10 21.35 Not supportedH5a: Ambience!Pleasure 0.36 5.41__ SupportedH6a: Layout!pleasure 0.15 2.51_ SupportedH7a: Dining equipment!Pleasure 20.08 21.07 Not supportedH8a: Employees!pleasure 0.02 0.41 Not supportedH3b: Facility aesthetic!Arousal 0.15 2.19_ SupportedH4b: Lighting!Arousal 0.13 1.58 Not supportedH5b: Ambience!Arousal 0.11 1.53 Not supportedH6b: Layout!arousal 0.04 0.65 Not supportedH7b: Dining equipment!arousal 20.04 20.50 Not supportedH8b: Employees!Arousal 0.15 3.02__ SupportedH3c: Facility aesthetic! BI 0.36 3.33__ SupportedH4c: Lighting! BI 20.11 20.86 Not supportedH5c: Ambience! BI 0.04 0.36 Not supportedH6c: Layout! BI 0.15 1.56 Not supportedH7c: Dining equipment!BI 20.13 21.07 Not supportedH8c: Employees!BI 0.32 4.15__ SupportedH9: Arousal! Pleasure 0.60 7.57__ SupportedR2 (Pleasure) 0.69R2 (Arousal) 0.35R2 (Behavioral intention) 0.56Goodness-of-fit statistics: x 2(340) ¼ 969.59, (p ¼ 0); x2/df ¼ 2.85; RMSEA ¼ 0.075; TLI ¼ 0.96;

CFI ¼ 0.97Note: _p , 0.05, __p , 0.01; BI ¼ behavioral intention; RMSEA ¼ root mean square error of approximation;TLI ¼ Tucker–Lewis Index; CFI ¼ comparative fit index.1160 K. Ryu and S. JangDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

92The results also revealed causal relationships between customers’ perceptions of physicalenvironments and emotional states. The estimate of the standardized path coefficient indicatedthat the linkage between facility aesthetics and pleasure was significant (b ¼ 0.22; t ¼ 3.47),which supported H3a. Moreover, the linkage between facility aesthetics and arousal was significant(b ¼ 0.15; t ¼ 2.19). Therefore, H3b was also supported. The paths from lighting topleasure (b ¼ 20.10; t ¼ 21.35) and to arousal (b ¼ 0.13; t ¼ 1.58) were not significant,so both H4a and H4b were not supported. The parameter estimates for the path from ambienceto pleasure (b ¼ 0.36; t ¼ 5.41) was significant, but path from ambience to arousal(b ¼ 0.11; t ¼ 1.53) was not significant, which supported H5a but not H5b. The estimateFigure 2. Causal relationships between latent variables.

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93from ambience to pleasure showed the greatest standardized parameter estimate among all thepaths connecting physical environments to pleasure. This indicates that ambience is the mostinfluential factor towards customers’ pleasure. This finding provides restaurateurs with practicalinformation on how important ambience is in creating pleasant environment. The pathfrom layout to pleasure (b ¼ 0.15; t ¼ 2.51) was found to be significant, which supportedH6a. However, the path from layout to arousal (b ¼ 0.04; t ¼ 0.65) was not significant,so H6b was rejected. The results also indicated that neither H7a (dining equipment topleasure: b ¼ 20.08; t ¼ 21.07) nor H7b (dining equipment to arousal: b ¼ 20.04; t ¼ 20.50)was supported. The path from employees to pleasure (b ¼ 0.02; t ¼ 0.41) was not significant,but the path from employees to arousal (b ¼ 0.15; t ¼ 3.02) was significant. Thus, only H8bwas supported. This finding suggested that employees are another critical component inupscale restaurants in order to create arousal emotion. In short, as the perceived qualityof the facility aesthetics, ambience, and layout, the level of customers’ pleasure emotionbecomes stronger, whereas facility aesthetics and employees enhance arousal emotion inrestaurant customers.As the result of the relative contribution of each construct of physical environment toemotional states, ambience (b ¼ 0.36) emerged as the primary explanatory variable for pleasure,followed by facility aesthetic (b ¼ 0.22) and layout (b ¼ 0.15). However, facility aesthetics(b ¼ 0.15) and employees (b ¼ 0.15) were the major explanatory variable for arousal. Interestingly,layout was a significant predictor only for pleasure, not for arousal. In addition, employeeswere a significant predictor only for arousal, not for pleasure. The other two causal paths–lightingand dining equipment–were found to be not significant, which indicated these aspects did

not critically influence the changes in customer emotional states. Regarding the relative importanceof pleasure and arousal to BI, the higher positive coefficient for the causal path from pleasureto BI (b ¼ 0.46) was observed than that for the path from arousal to BI (b ¼ 0.08). That is,pleasure was the more influential emotion that could improve customers’ BI than arousal, whichwas consistent with previous studies (Chebat & Michon, 2003; Donovan & Rossiter, 1982).Because pleasure appeared to be a major contributor to BI in upscale restaurants, it is importantfor restaurant operators to generate pleasure-generating environment by enhancing perceivedquality of facility aesthetics, ambience, and layout.Table 3 and Figure 2 also showed the hypothesized relationship between physical environmentsand BI in the modified M–R model. The path between facility aesthetic and BI was significant(b ¼ 0.36; t ¼ 3.33), and the path between employees and BI was also significant(b ¼ 0.32; t ¼ 4.15). Therefore, H3c and H8c were supported. However, all the other hypothesizedrelationships between physical environments and BI were not supported. Interestingly,facility aesthetics also indirectly influenced BI through pleasure. That is, facility aestheticshad both direct and indirect effect on BI.While the direct effect of arousal on BI was not significant (b ¼ 0.08; t ¼ 0.56), the directeffect of arousal on pleasure (b ¼ 0.60; t ¼ 7.57) and the direct effect of pleasure on BI(b ¼ 0.46; t ¼ 3.54) were significant. Thus, the indirect effect of arousal on BI through pleasurewas significant at an alpha level of 0.01. That is, the arousal only indirectly influencedBI through pleasure. In addition, the significant result of the arousal-to-pleasure obviouslyimplies the interdependence of the two emotional constructs. The use of interdependencebetween arousal and pleasure as well as the mediating role of emotion allows a better understandingof the relationships among arousal, pleasure, and BI.1162 K. Ryu and S. JangDownloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

94ConclusionThis study intended to discover the impact of customer perceptions of physical environments onpleasure and arousal emotions in addition to BI. Modifying the M–R model, this study proposeda theoretical model and tested it in an upscale restaurant setting. The findings indicated whichenvironmental elements produced pleasure and arousal, so that restaurateurs could use the findingsas a guide in planning pleasant and arousing environments. Certain attributes were moreimportant than others in enhancing customers’ perception of physical environment, theiremotions, and BI, so the results have implications for determining how management efficientlyallocates business resources. First, this study showed that a dimension among the dining environmentalfeatures directly influencing both pleasure and arousal emotions was facility aesthetics.Particularly, facility aesthetics (paintings/pictures, plants/flowers, furniture, color, and wallde´cor) are likely to differentiate a restaurant from its competitors. Major renovation or replacement

of the architectural design could be one good option to have better facility aesthetics, butrestaurateurs should not overlook less expensive options such as changing paintings/pictures andplants/flowers.One of the most significant factors affecting customers’ emotion (pleasure) was ambience. Itis important to recognize that the physical elements of ambience such as music, aroma, andtemperature can be controlled to a large extent by management, and it is probably among oneof the least expensive means to enhance customer perceptions of physical surroundings. Forinstance, music can be a more highly controllable physical element than other physical elementswithout much cost. Restaurateurs can easily change background music, varying its volume,genre, and tempo based on the customer preferences to help them feel pleased, excited, orrelaxed. Thus, restaurateurs should seriously consider physical attributes related to ambienceas an operational tool.Another major physical feature directly affecting customers’ emotions (arousal) was employees.In the eyes of the customer, the employees could be an important dimension of an upscalerestaurant’s image. Employees of restaurants have this important role until the service deliveryprocess is completed. The results of this study supported the strong influence of employees on customers’arousal state, so service organizations planning to enhance customer arousal need to considerthe employees’ style when hiring them. The style can be expressed in two ways: professionalappearance and attractiveness. The style of the employees should be congruent with the restaurantimage to maximize the effect of the social elements upon customer perceptions. Finally, layoutinfluenced the degree of pleasure. Thus, restaurateurs should provide physically and psychologicallyample space to facilitate pleasurable experience in the dining area.The overall results reinforced the importance of understanding the impact of emotions oncustomers’ behavior intentions. The findings revealed that not only pleasure derived fromdining environment directly influenced BI, but arousal also affected BI through a mediator, pleasure.Some restaurateurs might overlook emotional impact when cognitive elements (e.g.quality of food, food variety, price, and location) are emphasized. The findings indicated thatthe emotional responses evoked by the dining environments determined the extent to which customersintended to come back, to recommend the restaurant to friends or others, to stay longerthan anticipated, and to spend more than originally planned. Thus, restaurateurs should understandhow important the physical environments are in generating positive emotions such as pleasurein restaurants. The results also suggest implications for researchers. Many researchers in theThe Service Industries Journal 1163Downloaded By: [2007- 2008 National Sun Yat Sen University] At: 00:36 16 February 2009

95service field have paid attention to service evaluation, examining satisfaction or service quality

without taking customer emotions into account. Future studies should be directed toward incorporatingkey emotions into designing and managing service processes.Non-significant relationships between some physical environmental constructs (e.g. lighting,dining equipment) and emotions or BI were also found in the study. The non-significant pathscould be attributed to the expectation of customers towards upscale restaurants and prior experience.Customers may consider the high quality of physical surroundings in upscale restaurants tobe natural through their past experience. Thus, the high qualities of some physical attributesmight not excite their emotions or drive BI.This study has some limitations. The data were collected using convenience-samplingmethod in three upscale restaurants located in Midwestern and Northwestern states in the US.Thus, the limitation in generalizability of the results is not deniable. Nevertheless, this studyuniquely contributes to the literature by modeling customers’ perception of the dining environment,emotional states, and BIs, based upon the proposed modified version of the M–R model.There are some suggestions for future research. Given the great diversity of service industries,more research is needed to examine the effects of physical surroundings across various serviceindustries. Demographic differences (gender and age) could be also pursued in future researchbecause customers’ reaction to physical environment may be different depending upon theirdemographic characteristics. Lastly but not least, it is also worth doing longitudinal study fora specific restaurant. Researchers can watch how customers’ perceptions of quality of physicalenvironment changes over time (e.g. opening time and one or 2 years later) and how those perceptionscan influence customer responses, such as customer emotions, restaurant image, customersatisfaction, and subsequently their approach–avoidance behaviors.ReferencesAnderson, J.C., & Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommended two-stepapproach. Psychological Bulletin, 103(3), 411–423.Babin, B.J., & Attaway, J.S. (2000). Atmospheric affect as a tool for creating value and gaining share of customer.Journal of Business Research, 49(2), 91–99.Baker, J. (1987). The role of the environment in marketing services. In J.A. Czepeial, C.A. Congram, & J. Shananhan(Eds.), The services challenges: Integrating for competitive advantage (pp. 79–84). Chicago: American MarketingAssociation.Baker, J., Berry, L.L., & Parasuraman, A. (1988). The marketing impact of branch facility design. Journal of RetailBanking, 10(2), 33–42.Baker, J., & Cameron, M. (1996). The effects of the service environment on affect and consumer perception of waitingtime: An integrative review and research propositions. Journal of the Academy of Marketing Science, 24(4), 338–349.Baker, J., Levy, M., & Grewal, D. (1992). An experimental approach to making retail store environmental decisions.Journal of Retailing, 68(4), 445–460.Bearden, W.O., Sharma, S., & Teel, J.E. (1982). Sample size effects on chi-square and other statistics used in evaluatingstructural equations. Journal of Marketing Research, 19(4), 425–430.Bell, P.A., & Baron, R.A. (1977). Aggression and ambient temperature: The facilitating and inhibiting effects of hot andcold environments. Bulletin of the Psychonomic Society, 9(6), 443–445.Bellizzi, J.A., & Hite, R.E. (1992). Environmental color, consumer feelings, and purchase likelihood. Psychology andMarketing, 9(5), 347–363.Bitner, M.J. (1992). Servicescapes: The impact of physical surroundings on customers and employees. Journal ofMarketing, 56(2), 57–71.Bone, P.F., & Ellen, P.S. (1999). Scents in the marketplace: Explaining a fraction of olfaction. Journal of Retailing,75(2), 243–262.

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