Perceived quality, emotions, and behavioral intentions: Application of ...

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Journal of Business Research 62 (2009) 451 – 460

Perceived quality, emotions, and behavioral intentions: Application of an extended Mehrabian–Russell model to restaurants SooCheong (Shawn) Jang 1 , Young Namkung ⁎ Department of Hospitality and Tourism Management, Purdue University, 700 W. State Street, West Lafayette, IN 47907-0327, USA Received 21 May 2006; accepted 31 January 2008

Abstract In order to address a lack of comprehensive evaluation of restaurant quality, this study extends Mehrabian and Russell's stimulus–organism– response framework by incorporating restaurant-specific stimuli and including restaurant-specific measures of emotion. Using structural equation modeling, this study shows that atmospherics and service function as stimuli that enhance positive emotions while product attributes, such as food quality, act to relieve negative emotional responses. Results also suggest that positive emotions mediate the relationship between atmospherics/ services and future behavioral outcomes. The results are theoretically and practically meaningful because they address the relationships among three types of perceived quality (product, atmospherics, and service), customer emotions (positive/negative), and behavioral intentions in the restaurant consumption experience. Managerial implications, limitations, and future research directions are also suggested. © 2008 Elsevier Inc. All rights reserved. Keywords: Perceived quality; Emotions; Behavioral intentions; Restaurant management; Mehrabian–Russell Model

1. Introduction Since Kotler (1973) introduced the term “atmospherics” the effect of physical stimuli on consumer behavior has been of consistent interest to marketing practitioners and scholars (Bitner, 1992; Turley and Milliman, 2000). In the past three decades, researchers have recognized the influence of atmospherics as tangible cues in customer evaluations of service quality, and ultimately in repeat purchase, in a variety of service settings (Baker, 1987; Bitner, 1992). Along similar lines, Mehrabian and Russell's (1974) study in environmental psychology suggests that environmental stimuli (S) lead to an emotional reaction (O) that, in turn, drives consumers' behavioral response (R) based on the stimulus–organism– ⁎ Corresponding author. College of Hotel and Tourism Management Kyung Hee University 1 Hoegi-dong, Dongdaemun-gu, Seoul, 130-701, Korea. Tel.: +82 2 961 2185; fax: +82 2 964 2537. E-mail addresses: [email protected] (S.(S.) Jang), [email protected] (Y. Namkung). 1 Tel.: +1 765 496 3610; fax: +1 765 494 0327. 0148-2963/$ - see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2008.01.038

response (S–O–R) paradigm. The model posits that consumers have three emotional states in response to environmental stimuli: pleasure, arousal, and dominance (Mehrabian and Russell, 1974). These emotional responses result in two contrasting behaviors: either approach or avoidance. Approach behavior involves a desire for staying, exploring, and affiliating with others in the environment (Booms and Bitner, 1980), whereas avoidance behavior includes escaping from the environment and ignoring communication attempts from others (Donovan and Rossiter, 1982). Applying Mehrabian and Russell's model, many studies have been conducted on the role of environmental stimuli as a predictor of emotional responses, such as pleasure or arousal and as a predictor of consumer behaviors, such as extra time spent in a store and actual incremental spending (Donovan and Rossiter, 1982; Wakefield and Blodgett, 1994, 1996). Despite the great contribution of Mehrabian and Russell's model to the literature, it is undeniable that environmental stimuli provide only limited information about customer evaluations of perceived quality in many service settings, because environmental stimuli are only a subset of overall service

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S.(S.) Jang, Y. Namkung / Journal of Business Research 62 (2009) 451–460

stimuli. That is, other aspects of service stimuli, in addition to environmental stimuli, exist and may have important but different roles in service settings. For example, within a restaurant context, product stimuli such as food taste, freshness, and presentation, compose a set of stimuli, which, along with physical environment, may act as a significant predictor of emotional responses and future behaviors (Kivela et al., 1999). Due to the hedonic nature of a quality restaurant experience, human interactions are essential in creating satisfaction and future re-visits (Stevens et al., 1995). In other words, the level of service provided by restaurant employees may be another critical component of restaurant service quality. Thus, overall service stimuli should be considered in seeking to better understand customer restaurant experience. In academia, little attention, however, has been paid to other stimuli in service environments. To fill this important research niche, this study extends Mehrabian and Russell's framework of physical stimuli, consumer emotions, and behavioral response by adding restaurant industry-specific stimuli as an example of the service experience situation: an extended MR model. Therefore, the goal of this study was to propose and test a more comprehensive model consisting of perceived quality (three stimuli), emotions, and behavioral intentions beyond Mehrabian and Russell's paradigm. More specifically, the primary objectives of this study were 1) to assess the effects of perceived quality on emotions and behavioral intentions and 2) to test the mediating role of emotions between perceived quality and behavioral intentions in the restaurant context. 2. Theoretical background 2.1. Mehrabian–Russell model Mehrabian and Russell (1974) posited that environmental stimuli influence an individual's emotional state, which in turn affects approach or avoidance responses. In their stimulus– organism–response model, the stimuli are external to the person and consist of various elements of physical atmosphere (Bagozzi, 1986). The organism refers to internal processes and structures intervening between stimuli external to the person and the final actions or responses (Bagozzi, 1986). This implies that the effect of atmosphere (the stimulus) on consumer behavior is mediated by the consumer's emotional state. According to Mehrabian and Russell (1974), emotional states fall into three basic domains: pleasure, arousal, and dominance. Dominance, however, has been shown to have a non-significant effect on behavior (Donovan and Rossiter, 1982; Donovan et al., 1994; Russell and Pratt, 1980). In addition, responses to an environment can be classified as approach or avoidance behavior: approach includes a desire to stay, to look around and explore the environment, and to communicate with others in the environment, whereas avoidance is comprised of the opposite behaviors (Mehrabian and Russell, 1974). Mehrabian and Russell (1974) conceptualized their model for a variety of environments, and the model has been much applied in both retail and services domains (Machleit and Mantel, 2001). For example, Bagozzi and colleagues (1999)

examined the S–O linkage of the Mehrabian and Russell model demonstrating that emotions associated with consumption are formed in response to a specific appraisal made by the consumer (Bagozzi et al., 1999). Baker and colleagues (1992) reported associations between store environment and the emotional states of pleasure and arousal. Wakefield and Baker (1998) suggested that the overall architectural design and décor of a mall are the key environmental elements in generating excitement among customers. Moreover, Donovan and Rossiter (1982) and Donovan et al. (1994) examined the O–R linkage of the Mehrabian and Russell model and maintained that pleasure is a powerful determinant of approach–avoidance behaviors within stores, including spending more than anticipated. The two studies indicated that pleasure influenced intended approach and actual approach behaviors. Further, arousal interacted with pleasure such that it increased approach behaviors in pleasant environments while it decreased avoidance behaviors in unpleasant environments. Baker et al. (1992) found that not only pleasure but also arousal were positively related to willingness to buy. Dubé et al. (1995), focusing specifically on the affiliation component of approach– avoidance, similarly found that higher levels of pleasure and arousal increased the desire to affiliate with staff in a bank setting. 2.2. An extended Mehrabian–Russell (MR) model 2.2.1. Unipolar approach to emotional responses Mehrabian and Russell's (1974) scale offers a bipolar framework for emotional responses to environmental stimuli. Although the major structural dimension of affective experience is often found to be the ubiquitous bipolar continuum of pleasantness–unpleasantness (Russell, 1983), several limitations in its application to consumption-related emotion studies have been recognized. For example, Westbrook (1987) noted that the unipolar view for investigating consumption experiences appears more suitable because the bipolar conceptualization allows for ambivalence or the joint occurrence of pleasant and unpleasant states, as well as indifference or the occurrence of neither pleasant nor unpleasant states. Babin and colleagues (1998) demonstrated that, despite its convenience, the bipolar view was inadequate for capturing consumer emotions, showing that feeling a negative emotion does not preclude the occurrence of a positive emotion. Research on personal reports of individual affective experiences has indicated two largely independent, unipolar dimensions corresponding to positive and negative affect (Abelson et al., 1982). Along this line, Yalch and Spangenberg (2000) have dealt with emotional responses within a discrete positive and negative emotion scheme instead of a pleasure and arousal scheme, testing the relationship between two types of emotions and postpurchase behavioral intentions. Their findings supported that when shoppers experience positive emotions in a shopping area, they are more likely to adopt approach behavior; conversely, negative emotions are more likely to produce avoidance behavior. Hence, these studies have suggested that the unipolar view is more appropriate in understating consumption emotion because


it is able to indicate that the customer feels happiness and unhappiness at the same time. Since each emotion can have unique influences on behavioral response within a unipolar framework, human behavior depends on the relative efficacy of positive and negative emotional states. Therefore, instead of Mehrabian and Russell's pleasure–arousal framework, this study adopted a unipolar approach, based on Izard's (1977) Differential Emotions Scale (DES), to consumption emotions in response to perceived quality: positive and negative emotions. Izard's (1977) differential-emotions measure postulates 10 primary emotions: interest, joy, surprise, sadness, anger, disgust, contempt, fear, shame and guilt. Its flexibility and comprehensiveness allows these emotion labels to be used extensively in diverse contexts (Holbrook, 1986; Westbrook, 1987). 2.2.2. Synthesis of stimuli in restaurants In a restaurant setting, many stimuli could influence the customer's emotional state. These stimuli encompass both tangible and intangible features of the restaurant such as product attributes, physical environments, and service aspects. According to Campbell-Smith (1967), food, atmosphere, and service are the key elements in restaurants that broaden the appeal of the meal experience. As for product attributes, previous studies have noted that the most essential part of the restaurant experience, “food quality,” which includes an appealing taste, freshness, menu item variety, and appealing presentation, influences customer satisfaction (Johns and Tyas, 1996; Kivela et al., 1999; Raajpoot, 2002). Studies have focused on different food quality attributes such as presentation (Raajpoot, 2002), healthy components (Johns and Tyas, 1996), and freshness (Acebrón and Dopico, 2000; Johns and Tyas, 1996; Kivela et al., 1999) and have reported that these attributes serve as tangible cues of service quality in restaurants. In line with this discussion, we propose the first two research hypotheses. Hypothesis 1a. Customer perception of product quality has a positive effect on positive emotion. Hypothesis 1b. Customer perception of product quality has a negative effect on negative emotion. The other important stimulus of during a restaurant experience is “physical environment” or “atmospherics.” Scholars have researched physical environment in restaurant settings and its effect on customer perceptions of quality and subsequent responses. Restaurant customers are likely to use atmospherics as tangible cues to make judgments (Levitt, 1981). The various atmospheric elements within a service setting include visual and auditory cues such as function, space, design, color, lighting, and music. Spatial perception can convey a sense of coziness and intimacy (Ching, 1996) and help consumers form a mental picture that precedes emotional response and judgment of specific service environments (Lin, 2004). Wakefield and Blodgett (1994) suggested that service facilities should provide ample space to facilitate exploration and stimulation within the environment, especially in upscale restaurants. Interior design of a restaurant may influence how long customers will stay in the

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restaurant (Wakefield and Blodgett, 1996), and environmental design has an impact on service satisfaction (Andrus, 1986). Color is a strong visual component of a physical setting that draws customer attention and stimulates emotional responses (Bellizzi and Hite, 1992; Bellizzi et al., 1983). Lighting influences perceptions of form, color, and texture (Ching, 1996), and its harmony with color and decor makes the experience more pleasant (Steffy, 1990). Music is also a positive auditory cue for stimulating emotions and behaviors in a restaurant setting (Baker et al., 1992; Hui et al., 1997). Based on a review of the atmospherics literature, we propose the next two research hypotheses. Hypothesis 2a. Customer perception of atmospherics has a positive effect on positive emotion. Hypothesis 2b. Customer perception of atmospherics has a negative effect on negative emotion. Another component of stimuli in the restaurant experience is “service quality,” which has been extensively researched in service marketing. Because services in the hospitality industry rely heavily on the service providers' interpersonal skills (Nikolich and Sparks, 1995), the interaction between customer and service provider can have a substantial impact on the consumer evaluation of restaurant services. The reliability of the service provider, the responsiveness of the service provider, the assurance provided by the service staff, and the empathy shown to consumers could be understood as intangible social cues that produce perceived quality evaluations and customer satisfaction (Brady and Robertson, 2001). In hospitality industries, the performance of contact employees is critical to customer perceptions of the service offering. Stevens et al. (1995) measured restaurant service quality using DINESERV, an adaptation of the SERVQUAL scale, to examine service provider and customer interaction during service delivery and claimed that service quality was an important antecedent for customer evaluation. Therefore, the following two research hypotheses are proposed. Hypothesis 3a. Customer perception of service quality has a positive effect on positive emotion. Hypothesis 3b. Customer perception of service quality has a negative effect on negative emotion. 2.2.3. Behavioral intention as a surrogate indicator of actual behavior An extension of the relationships between stimuli and emotional responses leads to consumer behaviors. Donovan and Rossiter (1982) provided empirical evidence that the pleasure and arousal derived from the physical environment influence retail outcomes (time spent browsing the store's environment, the tendency to spend more money than originally planned, and the likelihood of returning to the store). Similarly, Baker et al. (1992) found that not only pleasure but also arousal were positively related to willingness to buy.

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Moreover, previous researchers have incorporated behavioral intentions, such as willingness to repurchase, willingness to purchase more in the future, and willingness to recommend the store to others, within the Mehrabian– Russell's framework (Baker et al., 2002; Hightower et al., 2002; Macintosh and Lockshin 1997). Donovan and Rossiter (1982) were interested in understanding patronage intentions, such as willingness to return to the store and to deliver good word-of-mouth to fellow customers, because of the need to forecast customer buying behavior. Behavioral intention is defined as “the degree to which a person has formulated conscious plans to perform or not perform some specified future behavior” (Warshaw and Davis, 1985, p. 214). That is, intention to perform a behavior is the proximal cause of such a behavior (Shim et al., 2001). Because behavioral intentions have been specified as a surrogate indicator of actual behavior in marketing studies (Fishbein and Ajzen, 1975), this study also used behavioral intentions as an outcome construct influenced by emotions. Therefore, this leads to the next two research hypotheses. Hypothesis 4. Customer positive emotion has a positive effect on behavioral intentions. Hypothesis 5. Customer negative emotion has a negative effect on behavioral intentions. Although the Mehrabian and Russell model did not propose an S–R linkage, various studies in environmental psychology have shown that perceived quality of the physical environment influences consumer behavior (Donovan and Rossiter, 1982; Hui and Bateson, 1991). Wakefield and Baker (1998) found that in retail environments atmospherics play an important role in determining a shopper's desire to stay longer in a shopping area. Tai and Fung (1997) showed that environmental stimuli are positively related to the level of pleasure experienced in the store, which, in turn, leads to positive in-store shopping behaviors such as willingness to stay longer, willingness to spend more, and a desire to explore the store. Sweeney and Wyber (2002) also found that music influenced customer behavioral intentions: a willingness to buy at the store and a willingness to recommend the store. Milliman (1986) found that music tempo influenced consumption duration at tables and bars in restaurants. Caldwell and Hibbert (2002) also demonstrated that music is one of the atmospheric elements that affect restaurant patron's behavior. Besides the relationship between physical environment and behavioral intentions, Kivela and colleagues (1999) noted the importance of food in explaining dining satisfaction and predicting return patronage at restaurants and claimed that food quality was a significant predictor of consumer satisfaction and behavioral intentions. Also, quality perception is known to positively affect intended behaviors in service settings (Boulding et al., 1993). Therefore, the following hypotheses are proposed: Hypothesis 6. Customer perceptions of product quality have a positive effect on behavioral intentions.

Hypothesis 7. Customer perceptions of atmospherics have a positive effect on behavioral intentions. Hypothesis 8. Customer perceptions of service quality have a positive effect on behavioral intentions. With the above hypotheses, this study proposes an extended MR model as shown in Fig. 1. The model displays the relationships among perceived quality (product attributes, atmospherics, and service aspects), emotions (positive/negative), and behavioral intentions. Perceived quality is treated as an exogenous variable, whereas customer emotions and behavioral intentions are considered endogenous variables. 3. Methodology 3.1. Measurement items To empirically test the hypotheses, multi-item scales validated in previous studies were identified and modified to fit the study setting. A questionnaire was created that contained three constructs relating to the customer's restaurant experience: perceived quality, emotions, and behavioral intentions. The perceived quality of the restaurant experience included three constructs: product attributes (Johns and Tyas, 1996; Kivela et al., 1999; Raajpoot, 2002), atmospherics (Bitner, 1992; Kotler, 1973; Wakefield and Blodgett, 1994, 1996), and service aspects (Brady and Robertson, 2001; Stevens et al., 1995). Each construct of perceived quality was measured using a 7-point scale: “How much do you agree or disagree with these statements?” (1 = extremely disagree and 7 = extremely agree). Based on Izard's (1977) categorization of emotions, the researchers generated a pool of emotion items embedded in the restaurant experience through in-depth interviews with students and faculty members at a mid-western university in the U.S. The generated items were categorized as two discrete emotion dimensions: positive (joy, excitement, peacefulness, and refreshment) and negative (anger, distress, disgust, fear and

Fig. 1. An Extended MR Model with perceived quality, emotions, and behavioral intentions.


shame) emotion. The emotion items were measured on a 7point scale ranging from 1 (In this restaurant, I do not feel this emotion at all) to 7 (In this restaurant, I feel this emotion strongly). Behavioral intention was operationalized with responses to three items using a 7-point scale (1 = extremely disagree and 7 = extremely agree) based upon Zeithaml et al.'s (1996) study. The measurement items operationalized for testing hypotheses are presented in Appendix A. 3.2. Data collection and analyses A pilot test, using 40 students at a mid-western university in the U.S. who had visited a full service restaurant within the last 4 weeks, was conducted to ensure the reliability of the scales. Several modifications were made based on feedback from the pilot test. Before the questionnaire was finalized, three managers at full-service restaurants and two faculty members familiar with the topic area further reviewed the questionnaire, and slight revisions in wording were made based on their suggestions. Because emotional experiences elicited by service industryspecific stimuli may be more important in full service restaurants, rather than fast food or limited service restaurants, the data used for this study were collected from four mid-to-upper scale restaurants: two in a mid-western city and two in an eastern city in the U.S. Self-administered questionnaires were distributed by restaurant staffs to randomly selected customers who were waiting for checks after dinner. In all, 347 customers were asked to complete a survey on a voluntary basis, and a total of 290 completed questionnaires were obtained and used in this study. The demographic characteristics of the respondents included a mean age of 39 years, more females (60.3%), and a Caucasians majority (77%). The data were analyzed following Anderson and Gerbing's (1988) two-step approach: a measurement model and a subsequent structural model. The multiple-item scales of six constructs were subjected to a confirmatory factor analysis to determine whether the manifest variables reflected the hypothesized latent variables. The adequacy of the individual items was

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assessed by composite reliability, convergent validity, and discriminant validity. Once the measures were validated, structural equation modeling (SEM) was used to test the validity of the proposed model and the hypotheses. 4. Results As mentioned earlier, this study first conducted a confirmatory factor analysis (CFA) with a maximum likelihood to estimate the measurement model by verifying the underlying structure of constructs. This study also checked unidimensionality, reliabilities, and validities of the six-factor measurement model before testing the structural model (Table 1). The level of internal consistency in each construct was acceptable, with Cronbach's alpha estimates ranging from .90 to .97 (Nunnally, 1978). All of the composite reliabilities of the constructs were over the cutoff value of .70, ensuring adequate internal consistency of multiple items for each construct (Hair et al., 1998). Convergent validity was satisfied in that all confirmatory factor loadings exceeded .73 and were significant at .01 (Anderson and Gerbing, 1988). In addition, the average variance extracted (AVE) of all constructs exceeded the minimum criterion of .50, indicating that a large portion of the variance was explained by the constructs (Fornell and Larcker, 1981; Hair et al., 1998). Discriminant validity was tested by comparing the average variance extracted (AVE) with the squared correlation between constructs (Fornell and Larcker, 1981). The AVEs were greater than the squared correlations between any pair of constructs, suggesting discriminant validity. Discriminant validity signifies that a construct does not significantly share information with the other construct. That is, the six-factor confirmatory measurement model demonstrated the soundness of its measurement properties. The χ2 value with 260 degrees of freedom was 619.437 (p b 0.001). Given the known sensitivity of the χ2 statistics test to sample size, several widely used goodness-of-fit indices demonstrated that the confirmatory factor model fit the data well (χ2/df = 2.382, NFI =0.977, CFI= 0.986, IFI =0.986, RMSEA =0.069). As the next step, the proposed structural model was estimated (Fig. 2, Table 2). The estimation produced the following

Table 1 Reliabilities and confirmatory factor analysis properties Constructs

Cronbach's alpha

Product quality P1/P2/P3/P4 Atmospherics A1/A2/A3/A4/A5 Service quality S1/S2/S3/S4 Emotion (positive) E1/E2/E3/E4 Emotion (negative) E5/E6/E7/E8/E9 Behavioral Intentions B1/B2/B3

.90

Standardized factor loadings

Item reliabilities

.88/.73/.89/.87

.86/.90/.85/.86

.77/.83/.88/.89/.69

.89/.88/.87/.87/.91

.81/.90/.88/.81

.91/.87/.87/.90

.87/.79/.88/.83

.87/.89/.87/.88

.84/.91/.95/.80/.86

.93/.92/.91/.94/.92

.95/.97/.95

.96/.95/.96

.90 .91 .91 .94 .97

Composite reliabilities

AVE

.87

.63

.88

.64

.89

.66

.85

.58

.94

.76

.95

.87

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Fig. 2. An extended MR model with parameter estimates.

statistics: χ2 (261) = 620.261 (p b 0.001), χ2/df = 2.376, NFI = 0.98, CFI = 0.99, IFI = 0.99, RMSEA = 0.069. The model's fit as indicated by these indexes was deemed satisfactory; thus, it provides a good basis for testing the hypothesized paths. Hypothesis 1a, which hypothesized a positive relationship between product quality and positive emotion, was not supported, although the sign was in the expected direction. Hypothesis 1b for predicting a negative relationship between product quality and negative emotion was supported (γ21 =

− .42, t = − 2.68, p b .01). The results of the first two hypotheses show that just having a high quality product may not be enough to create positive emotion, while providing low quality products may cause customers to have negative emotion. As predicted by hypothesis 2a, atmospherics (γ12 = .32, t = 2.35, p b .05) significantly influenced positive emotion. In contrast, hypothesis 2b for predicting a negative relationship between atmospherics and negative emotion was not supported. As expected in hypothesis 3a, service quality had a significant impact on positive

Table 2 Structural parameter estimates Hypothesized path

Standardized path coefficients

t-value

Results

H1a: Product quality → emotion (positive) H1b: Product quality → emotion (negative) H2a: Atmospherics → emotion (positive) H2b: Atmospherics → emotion (negative) H3a: Service quality → emotion (positive) H3b: Service quality → emotion (negative) H4: Emotion (positive) → behavioral intentions H5: Emotion (negative) → behavioral intentions H6: Product quality → behavioral intentions H7: Atmospherics → behavioral intentions H8: Service quality → behavioral intentions

.03 − .42 .33 − .04 .39 − .19 .17 − .04 .18 .32 .24

0.170 − 2.679⁎⁎ 2.352⁎ − 0.252 3.785⁎⁎⁎ − 1.752 3.168⁎⁎ − 0.989 1.603 3.179⁎⁎ 3.143⁎⁎

Not supported Supported Supported Not supported Supported Not supported Supported Not supported Not supported Supported Supported

Note: ⁎⁎⁎p b 0.001, ⁎⁎p b 0.01, ⁎p b 0.05.


emotion (γ13 = .39, t = 3.79, p b .001). On the contrary, hypothesis 3b for predicting a negative relationship between service aspects and negative emotion was not supported. The findings suggest that atmospherics and service aspects are significant predictors of positive emotion but are not key determinants of negative emotion. That is, product attributes alone may not be sufficient enough to create positive emotion. Instead, nice atmospherics and service aspects along with the good quality of product attributes may be required to elicit positive emotion. Conversely, product attributes of a low quality may be more strongly associated with negative emotion as opposed to atmospherics and service quality. In summary, the results indicate that there is no single factor that stands out as being the determinant for the two types of emotions, because all three perceived quality factors play a role in creating either positive or negative emotion. Hypothesis 4 for linking positive emotion and behavioral intentions was supported (β31 = .17, t = 3.17, p b .01). Unexpectedly, hypothesis 5 for the relationship between negative emotion and behavioral intentions was not statistically significant. These findings suggest the possibility that positive emotion may be a better indicator for predicting consumer behavior in service settings than negative emotion. Although this study did not support the proposed effect of negative emotion on behavioral intentions, this may reflect that people are likely to eschew the expression of negative feelings, even on self-reported questionnaire. Thus, since product quality itself was the most influential criterion for generating negative emotions, managers should seriously consider the importance of product quality and its potential to elicit negative emotions. Hypothesis 6, which predicted a positive relationship between product quality and behavioral intentions was not supported. In contrast, hypothesis 7 for a positive relationship between atmospherics and behavioral intentions, was supported (γ32 = .32, t = 3.18, p b .01). Likewise, hypothesis 8 for predicting a positive relationship between service quality and behavioral intentions was also supported (γ33 = .24, t = 3.14, p b .01). These findings indicate a strong relationship between non-product related attributes (i.e., atmospherics and service attributes) and consumer behavioral intentions in service environments. One reason for there being no significant association between product quality and behavioral intentions could be related to the settings of this study. In upscale restaurants, the product itself, for example quality food, may not be the single essential experience that the average customer seeks. Accordingly, a quality product may not be enough to generate favorable behavioral outcomes. On the contrary, high-quality atmospherics and services in upscale restaurants may ensure consumers re-patronage. However, we cannot not exclude the possibility that product quality could indirectly be connected to unfavorable behaviors, including complaining to others and contemplating switching to competitors. To further investigate the mediating role of emotion, analyses suggested by Baron and Kenny (1986) were conducted in this study. Because negative emotion was not significantly related to behavioral intentions, this study checked only the

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mediating effect of positive emotion. Thus, the structural equation model was re-estimated by constraining the direct effect of positive emotion on behavioral intentions (β31 = 0). Baron and Kenny's (1986) first three conditions were met in the original structural model (γ12, β31, and γ32 were significant). The fourth condition was also satisfied; the parameter estimate between atmospherics and behavioral intentions (γ32 = .32, t = 3.18) in the mediating model became less significant (partial mediation) than the parameter estimate (γat to bi = .40, t = 3.87) in the constrained model. Similarly, a partial mediating role for positive emotion was observed between services and behavioral intentions (γ33 = .24, t = 3.14 vs. γs to bi = .32, t = 4.26). The difference in χ2 value between the constrained model (χ2 (262) = 630.247) and the mediating model (χ2 (261) = 620.261) was statistically significant (χ2d(1) = 9.986, p b .05), indicating that the mediating model is a significant improvement over the constrained model. In addition, the magnitude of the indirect effect of positive emotion from atmospherics to behavioral intentions was .561, whereas the direct effect was .33. Moreover, the indirect effect of positive emotion on behavioral intentions via service attributes (.663) was larger than the direct effect (.39). Thus, the mediating effects of emotion clearly demonstrate that excellent atmospherics and service attributes produce favorable future behavior outcomes through positive emotion. 5. Discussion 5.1. Theoretical implications Previous research has applied the Mehrabian and Russell model to examine the role of environmental stimuli in the creation of emotions and consumer behaviors. However, few have taken into consideration the attributes that are potentially important for products and services. By making up for this gap in research, this study has several theoretical implications. First, this study considers additional constructs (i.e. product and service stimuli) along with atmospherics stimuli to create a more comprehensive evaluation. This allows for the empirical examination of the different effects each stimulus has on emotions and behavioral intentions in a restaurant consumption context. Thereby, the present study provides an extended Mehrabian–Russell Model encompassing the diverse aspects of stimuli in the contexts of products and services. Second, this research adopts a unipolar approach to emotional responses instead of Mehrabian and Russell's (1974) bipolar conceptualization and tests the role that each emotion plays. A discrete positive and negative scheme provides its unique influences on behavioral responses (Yalch and Spangenberg, 2000) as well as its association with each of the three quality stimuli: product, atmospherics, and services. Third, this study examines the way in which emotions mediate between perceived quality and consumer behavioral intentions (Bagozzi et al., 1999; Baker and Cameron, 1996). The mediating effects demonstrate how consumer perceptions of atmospherics and services can affect his or her behavioral intentions via the creation of positive emotion. The results also

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empirically support that emotions have a stronger positive indirect effect than the direct effect from atmospherics / services on behavioral intentions. Fourth, the results show that not all the proposed relationships are supported and that the effects of each quality stimuli in association with emotions and behavioral intentions vary. By embracing diverse quality stimuli in service settings, this empirical evidence could establish the important link among product quality, atmospherics, service quality, emotions, and behavioral intentions rooted in the Mehrabian-Russell Model (1974).

relationship between negative emotion and behavioral intentions was not significant. However, this finding should not be viewed as denigrating the significance of negative emotion in behavioral outcomes. Since people do not often reveal their negative emotions, the proposed relationship may not have been successfully assessed in this empirical study. Accordingly, future research should be directed toward the relationship between negative emotion and behavioral intentions and their linkage to product quality.

5.2. Managerial implications

Our results should be interpreted with caution because of the limitations of the study. This study considered only mid-toupper scale restaurants. If this study had been conducted in different segments of the restaurant industry, results may have shown different relationships among the studied constructs. Full service restaurants are more likely to attract hedonic customers who pay more attention to restaurant environment. Future studies should examine the impact of the three qualities on emotions and behavioral intentions in other segments of the restaurant industry. The results, extending the Mehrabian and Russell's (1974) framework, suggest that atmospherics and service function as facilitators for enhancing positive emotions, while product quality functions as a means to ameliorate negative emotional responses. Given these findings, future research can examine why product quality does not have a significant impact upon positive emotions in restaurant settings and how negative emotions during a restaurant experience might be attenuated by product quality. Our results did not support the proposed effect of negative emotion on behavioral intentions, but there could be an indirect relationship between product quality and behavioral intentions that remains unrevealed in this study. Controlling for frequency of patronage at the restaurant might help explain these non-significant links. Customers who have experienced consistent product quality might view one disappointing meal as just an exception and might not have the same response as another customer whose experience was his or her first at that restaurant. Thus, additional research is needed to more deeply examine the association between negative emotions and behavioral intentions and their relationships with product quality. This study explored emotions as a mediator between perceived quality and behavioral intentions. Investigating different types of customers, in terms of age and gender, might show how different types of restaurant customers react to the three quality factors. Are emotional reactions universal? In what ways do emotions differ between genders or across culture? More research should be undertaken to measure emotional states prior to entering the restaurant, because a priori emotions may enhance positive emotions or aggravate negative emotions. Therefore, restaurant managers must further explore the role of emotions to fully understand the psychological process by which quality factors affect satisfaction and eventual future favorable behaviors in the restaurant consumption experience.

Besides theoretical implications, this study provides several managerial implications. The results of this study can help restaurant managers to better understand how each type of quality stimuli can contribute to eliciting either positive or negative emotion and eventually affect consumer behavioral intentions. With the hedonic nature of the restaurant experience, the role of atmospherics has an increasingly intuitive appeal for management to generate positive emotion and ensure positive behavioral intentions. At the same time, restaurants should provide high quality services to evoke positive emotions and eventually to generate future favorable behaviors. Moreover, the findings suggest that restaurateurs should pay attention to improving atmospherics and service quality to heighten customer's positive emotion and developing quality products to inhibit negative emotion. Although the association between product quality and behavioral intentions was not significant in this study, restaurant managers should not ignore the importance of product quality because it could act as a basic qualifier for restaurants (Sulek and Hensley, 2004). Customers may evaluate product quality in a more utilitarian aspect, which could potentially negate the effect of negative emotion in this study. Another possible explanation for the non-significant relationship between product quality and positive emotion might be a function of the expectations of restaurant consumers. Failure to have a good meal results in negative emotions, but “good enough” is not good enough to generate positive emotions. Customers may want to be delighted, not just satisfied, especially in quality restaurants. Product quality might have to exceed expectations to generate positive emotions. Therefore, in a competitive business environment, restaurant managers should maintain the quality of products at a level that meets or exceeds customer standards and provide additional effects with differentiated atmospherics and service aspects. Another managerial implication of this study is that positive emotion appeared to mediate the relationships between atmospherics/service and post-dining behavioral intentions. The role of positive emotion should be obvious given the hedonic nature of restaurants. Thus, restaurant managers could improve the probability of favorable behavioral intentions by making changes in atmosphere and improving service quality, which would elicit positive emotions. On the other hand, the

6. Limitation and future research


Appendix A Constructs and measurement items for an extended MR model Constructs

Label Items

Operationalization

Product quality

P1

Extremely disagree(1)– extremely agree(7)

P2 P3 P4 Atmospherics A1 A2 A3 A4

Service quality

A5 S1 S2 S3 S4

Emotion (positive)

E1 E2 E3

Emotion (negative)

E4 E5 E6

E7 E8 E9 Behavioral Intentions

B1 B2

B3

Food presentation is visually attractive The restaurant offers healthy options The restaurant serves tasty food The restaurant offers fresh food The facility layout allows me to move around easily The interior design is visually appealing Colors used create a pleasant atmosphere Lighting creates a comfortable atmosphere Background music is pleasing The restaurant serves my food exactly as I ordered it Employees are always willing to help me The behavior of employees instills confidence in me The restaurant has my best interests at heart Joy (joyful, pleased, romantic, welcoming) Excitement (excited, thrilled, enthusiastic) Peacefulness (comfortable, relaxed, at rest) Refreshment (refreshed, cool) Anger (angry, irritated) Distress (frustrated, disappointed, upset, downheartedness) Disgust (disgusted, displeased, bad) Fear (scared, panicky, unsafe, tension) Shame (embarrassed, ashamed, humiliated) I would like to come back to this restaurant in the future I would recommend this restaurant to my friends or others I would say positive things about this restaurant to others

I feel … not at all(1)– strongly(7)

Extremely disagree(1)– extremely agree(7)

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