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h 62 (2009) 451–460

Journal of Business Researc

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 atmo-
spherics as tangible cues in customer evaluations of service
quality, and ultimately in repeat purchase, in a variety of ser-
vice 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: jang12@purdue.edu (S.(S.) Jang), ynamkung@khu.ac.kr
(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 stim-
uli: 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 eval-
uations of perceived quality in many service settings, because
environmental stimuli are only a subset of overall service

452 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 dif-
ferent 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 per-
son 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. Ac-
cording 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 ex-
citement 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 spend-
ing 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 frame-

work for emotional responses to environmental stimuli. Al-
though the major structural dimension of affective experience
is often found to be the ubiquitous bipolar continuum of
pleasantness–unpleasantness (Russell, 1983), several limita-
tions in its application to consumption-related emotion studies
have been recognized. For example, Westbrook (1987) noted
that the unipolar view for investigating consumption experi-
ences appears more suitable because the bipolar conceptualiza-
tion 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

453S.(S.) Jang, Y. Namkung / Journal of Business Research 62 (2009) 451–460

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 pri-
mary emotions: interest, joy, surprise, sadness, anger, disgust,
contempt, fear, shame and guilt. Its flexibility and comprehen-
siveness 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. Accord-
ing 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 ex-
perience, “food quality,” which includes an appealing taste,
freshness, menu item variety, and appealing presentation, in-
fluences 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 ex-
perience 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 spe-
cific service environments (Lin, 2004). Wakefield and Blodgett
(1994) suggested that service facilities should provide ample
space to facilitate exploration and stimulation within the en-
vironment, especially in upscale restaurants. Interior design of a
restaurant may influence how long customers will stay in the

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 per-
ceptions 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 eval-
uation. 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 emo-
tional 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.

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

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

Moreover, previous researchers have incorporated beha-
vioral intentions, such as willingness to repurchase, will-
ingness 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 be-
haviors 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 restau-
rants. 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 re-
lationships among perceived quality (product attributes, atmo-
spherics, 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 val-
idated 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 state-
ments?” (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 emo-
tion dimensions: positive (joy, excitement, peacefulness, and
refreshment) and negative (anger, distress, disgust, fear and

455S.(S.) Jang, Y. Namkung / Journal of Business Research 62 (2009) 451–460

shame) emotion. The emotion items were measured on a 7-
point 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 industry-
specific stimuli may be more important in full service res-
taurants, 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 sub-
sequent structural model. The multiple-item scales of six
constructs were subjected to a confirmatory factor analysis to
determine whether the manifest variables reflected the hypothe-
sized latent variables. The adequacy of the individual items was

Table 1
Reliabilities and confirmatory factor analysis properties

Constructs Cronbach’s alpha Standardized factor loadi

Product quality .90
P1/P2/P3/P4 .88/.73/.89/.87

Atmospherics .90
A1/A2/A3/A4/A5 .77/.83/.88/.89/.69

Service quality .91
S1/S2/S3/S4 .81/.90/.88/.81

Emotion (positive) .91
E1/E2/E3/E4 .87/.79/.88/.83

Emotion (negative) .94
E5/E6/E7/E8/E9 .84/.91/.95/.80/.86

Behavioral Intentions .97
B1/B2/B3 .95/.97/.95

assessed by composite reliability, convergent validity, and dis-
criminant 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 con-
firmatory factor analysis (CFA) with a maximum likelihood to
estimate the measurement model by verifying the underlying
structure of constructs. This study also checked unidimension-
ality, 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 confirma-
tory 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 min-
imum 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 validitysignifies that a construct
does not significantly share information with the other construct.
That is, the six-factor confirmatory measurement model demon-
strated the soundness of its measurement properties. The χ2 value
with 260 degrees of freedom was 619.437 (pb0.001). 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 esti-
mated (Fig. 2, Table 2). The estimation produced the following

ngs Item reliabilities Composite reliabilities AVE

.87 .63
.86/.90/.85/.86

.88 .64
.89/.88/.87/.87/.91

.89 .66
.91/.87/.87/.90

.85 .58
.87/.89/.87/.88

.94 .76
.93/.92/.91/.94/.92

.95 .87
.96/.95/.96

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

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

statistics: χ2 (261)=620.261 (pb0.001), χ
2/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 sup-
ported, although the sign was in the expected direction. Hy-
pothesis 1b for predicting a negative relationship between
product quality and negative emotion was supported (γ21=

Table 2
Structural parameter estimates

Hypothesized path Standardized pa

H1a: Product quality→emotion (positive) .03
H1b: Product quality→emotion (negative) −.42
H2a: Atmospherics→emotion (positive) .33
H2b: Atmospherics→emotion (negative) −.04
H3a: Service quality→emotion (positive) .39
H3b: Service quality→emotion (negative) −.19
H4: Emotion (positive)→behavioral intentions .17
H5: Emotion (negative)→behavioral intentions −.04
H6: Product quality→behavioral intentions .18
H7: Atmospherics→behavioral intentions .32
H8: Service quality→behavioral intentions .24

Note: ⁎⁎⁎pb0.001, ⁎⁎pb0.01, ⁎pb0.05.

−.42, t=−2.68, pb .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, pb.05) sig-
nificantly influenced positive emotion. In contrast, hypothesis
2b for predicting a negative relationship between atmospherics
and negative emotion was not supported. As expected in hy-
pothesis 3a, service quality had a significant impact on positive

th coefficients t-value Results

0.170 Not supported
−2.679⁎⁎ Supported
2.352⁎ Supported

−0.252 Not supported
3.785⁎⁎⁎ Supported

−1.752 Not supported
3.168⁎⁎ Supported

−0.989 Not supported
1.603 Not supported
3.179⁎⁎ Supported
3.143⁎⁎ Supported

457S.(S.) Jang, Y. Namkung / Journal of Business Research 62 (2009) 451–460

emotion (γ13=.39, t=3.79, pb.001). On the contrary, hypoth-
esis 3b for predicting a negative …

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