The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0956-4233.htm
IJSIM
18,1
6
The role of arousal congruency
in influencing consumers’
satisfaction evaluations
and in-store behaviors
Jochen Wirtz
Received 22 November 2005
Revised 24 April 2006
Accepted 21 June 2006
NUS Business School, National University of Singapore,
Singapore
Anna S. Mattila
School of Hospitality Management, Pennsylvania State University,
University Park, Pennsylvania, USA, and
Rachel L.P. Tan
Singapore Airlines, Singapore
Abstract
International Journal of Service
Industry Management
Vol. 18 No. 1, 2007
pp. 6-24
q Emerald Group Publishing Limited
0956-4233
DOI 10.1108/09564230710732876
Purpose – It is widely accepted that consumers enter into a service consumption experience with a
set of expectations, including affective expectations. This research aims to investigate the matching
effects between arousal-level expectations and perceived stimulation (i.e. arousal congruency) on
satisfaction and in-store behaviors.
Design/methodology/approach – A 3 (under-stimulation, arousal congruency and understimulation) perceived arousal congruency) £ 2 valence (pleasant or unpleasant environment)
factorial design was employed and tested across two service settings, a music store and a book store.
A short narrative was used to induce arousal level expectations (high and low). Subjects were then
exposed to a video clip in which the actual arousal of the store environment was manipulated at three
levels (high, moderate, low). Consequently, subjects could perceive the store environment to match their
expectations (arousal congruency), exceed their expectations (over-stimulation) or to fall short of their
expectations (under-stimulation). Half of the video clips showed a pleasant store environment, whereas
the other half of the videos involved an unpleasant store environment. Satisfaction and in-store
behaviors served as the two dependent variables in this study.
Findings – The results of this study indicate that the valence of the service environment (pleasant or
unpleasant) moderates the arousal-congruency effect on satisfaction and in-store behaviors. Satisfaction
in pleasant service environments was maximized at arousal congruency, while such matching effects
failed to influence satisfaction in unpleasant settings. For in-store approach behaviors, perceived
under-stimulation, compared with over-stimulation, had a positive effect on in-store behaviors.
Practical implications – The findings of this study indicate that retailers need to pay attention not
only to the pleasantness of the store environment, but also to arousal level expectations regarding the
servicescape.
Originality/value – This paper posits a hitherto neglected theory that affective expectations, which
reflect people’s expectations about how they expect to feel in a given situation, might be equally
important in influencing customer responses in a service setting.
Keywords Consumer behaviour, Stores and supermarkets, Environmental psychology, Service climate
Paper type Research paper
Introduction
It is widely accepted that consumers enter into a consumption experience with a set
of expectations of what they would like to happen. Yet, previous research in the
consumer satisfaction literature has mainly examined the role of cognitive
expectations in the post-purchase evaluation process (Phillips and Baumgartner,
2002). In this study, we propose that affective expectations might be equally
important in influencing customer responses in a service setting. Affective
expectations reflect people’s expectations about how they anticipate to feel in a
given situation (Wilson et al., 1989).
Our focus is on introducing arousal level expectations as a key variable of interest in
the interplay between emotions and the servicescape (Bitner, 1992; Morrin and Chebat,
2005; Pullman and Gross, 2004; Vilnai-Yavetz and Rafaeli, 2006). Arousal level
expectations are particularly important in the context of retail services. For example,
after a boring day at work, a consumer might want to visit a hip music store with a
funky environment or go to an exciting discotheque. Similarly, she/he might prefer to
patronize a calming and relaxing book store after a hectic day in the office, or relax in a
spa (Wirtz et al., 2000). Yet, arousal as an affective dimension has been largely ignored
in the service literature (Rafaeli and Kluger, 2000).
To close that gap, the primary objective of this study is to gain a richer
understanding of the role of arousal-congruency on consumer satisfaction responses
and in-store behaviors in retail and service settings. Arousal congruency is achieved
when the actual store environment matches the consumer’s desired arousal level.
Conversely, exceeding or falling short of expected arousal levels results in perceived
over- or under-stimulation.
The specific objectives of this study are two-fold. First, we develop and test the idea
that the valence of the service environment (pleasant or unpleasant) moderates the
arousal-congruency effect on satisfaction and in-store behaviors. We advance that
satisfaction in pleasant service environments is maximized at arousal congruency,
while such matching effects fail to influence satisfaction in unpleasant settings. In the
latter, satisfaction is proposed to be uniformly low.
Second, we seek to clarify differences between satisfaction (an evaluative response)
and in-store behaviors (behavioral responses), and to illustrate the importance of
doing so. We propose that while consumers’ satisfaction evaluations in pleasant
environments are mainly a function of arousal congruency, their behavioral responses
are more stimulus-driven. Specifically, we suggest that under-stimulation should lead
to low levels of satisfaction but high levels of in-store behaviors. Under such
conditions, consumers are motivated to increase arousal through their own actions (i.e.
engage in affiliative behaviors, such as explore the environment, spend more time and
money in the store and approach service staff) to move closer to their desired level of
stimulation. Conversely, over-stimulation should lead to low approach behaviors as the
goal is to reduce stimulation.
Literature and hypotheses
Affective expectations and moderating effects of valence
Prior to discussing the affective expectations model, it is important to establish the
larger emotions framework used in this study. Consistent with recent work in
prototypical emotional episodes (Russell and Feldman, 1999), we postulate that
The role of
arousal
congruency
7
IJSIM
18,1
8
consumer responses to retail environments can be described by two dimensions, namely
degree of pleasantness and degree of activation or arousal. The valence continuum refers
to the hedonic quality of an affective experience (Feldman, 1995), while activation refers
to a sense of mobilization or energy (Russell and Feldman, 1999). In this study, we are
interested in the joint effects of arousal and valence of the environment on satisfaction
and in-store behavioral responses. We chose Meharabian and Russell’s circumplex
model as our emotions framework since this model is strongly supported in
environmental psychology, and it is arguably the most widely applied model of affect
in the context of service environments (Bitner, 1992; Donovan and Rossiter, 1982;
Donovan et al., 1994; Hui et al., 1997; Mattila and Wirtz, 2000, 2001; Wirtz and Bateson,
1999; Wirtz et al., 2000). However, we acknowledge that other conceptualizations of
emotions such as discrete emotion models (Izard, 1977; Plutchik, 1980) might be more
applicable to other research contexts, especially when interpersonal discrete emotional
responses such as anger, disgust or guilt are studied (Wirtz, 1994).
The affective expectation model (AEM) postulates that people’s preferences are
determined by affective expectations and by stimulus information (Dodges and
Klaaren, 2000; Geers and Lassitier, 2002; Wilson et al., 1989). In this study, we focus on
arousal level expectations, and it can be argued that such expectations are positive in
valence in a typical consumer behavior setting (i.e. consumers desire positive outcomes
when purchasing products and services). Similar to cognitive expectations, affective
expectations are postulated to guide an individual’s perceptions of new information
and facilitate the processing of congruent information (Bower, 1981; Niedenthal and
Setterlund, 1994 for studies supporting emotion-congruent information processing).
When the incoming information is expectation-consistent, then matching effects
should occur (Geers and Lassitier, 1999; Wilson et al., 1989). Conversely, in situations
where the new information is noticeably incongruent, people are predicted to scrutinize
the discrepancy due to contrast effects (Geers and Lassitier, 1999). This mismatch
between prior expectations and actual stimuli tends to have a negative impact on
subsequent evaluations. In this paper, we propose that satisfaction should be enhanced
when the actual store environment meets the individual’s desired arousal, whereas any
discrepancy (over- or under-stimulation) should lead to less positive evaluations.
In addition, we argue that the valence of the environment moderates the impact of
arousal congruency effects on satisfaction evaluations.
Relying on the negativity effect, we propose that the negative valence of the
environment overshadows any other cue, including arousal level expectations. Robust
findings from various areas of psychology suggest that the power of bad events is
greater than that of good ones (for a recent review see Baumeister et al., 2001). For
example, people are quick to form bad impressions or bad stereotypes because
negatively valenced information is more thoroughly processed than positive
information (Baumeister et al., 2001). The positive-negative asymmetry effect is
well-established in the impression formation literature (Anderson, 1965; Skowronski
and Carlston, 1989). If the impact of bad information is generally stronger than the good,
then we propose that the valence of an unpleasant physical environment should
overshadow the power of other environmental cues including its arousal-eliciting
qualities. In other words, the valence of the environment becomes the major determinant
of consumer reactions. Consequently, low levels of satisfaction are expected in
unpleasant settings regardless of arousal levels. Furthermore, independent of initial
arousal level expectations, low arousal may result in the lowest levels of dissatisfaction
and avoidance behaviors, as low arousal is generally seen as the optimum level in
unpleasant environments (Berlyne, 1960; McClelland et al., 1953). Taken together, we
predict the following:
The role of
arousal
congruency
H1. In pleasant environments, satisfaction will be maximized at the point of
arousal-congruency (i.e. at the match condition, where the desired level of
stimulation and the actual level are matched). Over- or under-stimulation will
result in reduced satisfaction.
9
H2. Arousal congruency will be a more important predictor of satisfaction in
pleasant than in unpleasant environments. Specifically, satisfaction in the
latter will be uniformly low as it is mostly driven by the valence (i.e.
unpleasantness) of the environment rather than by arousal congruency.
In-store behavioral responses to arousal congruency
We argue that in addition to satisfaction, one needs to assess in-store behavioral
responses to fully understand consumers’ affective reactions to shopping environments.
Prior research in emotions indicates that feelings and behavior can be disassociated
from one another (Lang, 1979; Mineka, 1979). For example, a person can be afraid
(negative emotion combined with high arousal) of roller-coater rides and yet go on one
(Rachman, 1984).
We rely on the optimal arousal theories as a framework to explain the impact of
arousal on consumers’ approach-avoidance behaviors (Berlyne, 1960, 1967; Mehrabian
and Russell, 1974; Zuckerman, 1979). Previous research shows that high levels of
arousal have a negative impact on approach behaviors (North and Hargreaves, 2000;
Mehrabian and Russell, 1974). In other words, highly arousing environments exceed
the optimal level of arousal for most people, thus resulting in a desire to escape or flee
the store. Yet, in this paper we extend previous literature by demonstrating that it is
not the absolute level of arousal that matters – rather perceived over- or
under-stimulation drives people’s behavioral responses. In pleasant environments,
when the actual arousal level is congruent with the consumer’s arousal level
expectations, then optimal arousal level has been reached. Consequently, positive
in-store behaviors should be maximized in the arousal congruency condition.
Although our prediction for the arousal congruency condition closely matches that
for satisfaction in pleasant environments, it is important to note that the theoretical
frameworks are different (i.e. affective expectations model for satisfaction versus
optimal arousal theories for in-store behaviors). Both frameworks predict optimal
response behaviors (i.e. satisfaction and in-store behaviors) for the arousal congruency
condition, but their predictions differ in situations when actual arousal falls short of
arousal level expectations. Under-stimulation is expected to result in low levels of
satisfaction while inducing high levels of positive in-store behaviors. When the
environment is less arousing than expected, then consumers are motivated to actively
engage in approach behaviors (Berlyne, 1960; Steenkamp and Baumgartner, 1992).
Such efforts will lead them closer to the optimal arousal level. Conversely, when the
retail environment exceeds consumers’ desired arousal levels, in-store behaviors
should be reduced.
IJSIM
18,1
As with satisfaction, we propose that unpleasant environments will lead to low
levels of approach behaviors as people want to minimize time spent in such settings.
Taken together, these arguments lead us to the following predictions:
H3. In pleasant environments, in-store approach behaviors will be maximized at
the point of arousal-congruency.
10
H4. In pleasant environments, under-stimulation will lead to higher levels of
in-store approach behaviors than over-stimulation.
H5. In unpleasant environments, in-store approach behaviors will be uniformly
low as such behaviors are mostly driven by the valence (i.e. unpleasantness)
of the environment rather than by arousal-congruency.
Method
Overview
In this study, a 3 (under-stimulation, arousal congruency or under-stimulation) £ 2
valence (pleasant or unpleasant environment) factorial design was employed and
tested across two service settings, a music store and a book store. A short narrative
was used to induce arousal level expectations (high and low). Subjects were then
exposed to a video clip in which the actual arousal of the store environment was
manipulated at three levels (high, moderate, low). As a result of these manipulations,
subjects could perceive the store environment to either match their expectations
(arousal congruency), exceed their expectations (over-stimulation) or to fall short of
their expectations (under-stimulation). Half of the video clips showed a pleasant store,
whereas the other half of the videos involved an unpleasant environment. Satisfaction
and in-store behaviors served as the two dependent variables in this study.
A total of 506 respondents drawn from the general public (52 percent) and from a
university sample (48 percent) participated in the study. The general public
respondents were intercepted on a busy high street and walked to the nearby facility
where the experiment was conducted. Participants at the university were recruited in
the university canteen. All participants received a small gift as appreciation for their
participation. The gender split of the respondents was about equal, with 53 percent
males. About 19 percent of respondents were between 15 and 20 years old, 58 percent
between 21 and 30 years, and 23 percent were older than 30 years. We had 242 and 264
respondents, respectively, for the music and the book store scenarios.
Research context, manipulations, and stimuli development
Research context. The two service genres, a music store and a book store, were chosen
as the research contexts because we needed a setting in which arousal level expectations
could be realistically manipulated. A second reason for selecting these two services was
that they were believed to be highly relevant to a wide spectrum of people. As such,
respondents would be able to imagine themselves in the service settings they were
exposed to.
Arousal level expectations. We used a role-play scenario method to manipulate
desired arousal. The narrative for creating high arousal level expectations read as
follows:
Sam has had an unexciting week at work. Having heard of the opening of a new music store
(book store), Sam has decided to visit the store, and hopes that the new shop would offer a
place for upbeat listening (new and interesting items/readings) in a vibrant and lively
environment, and that the music store (book store) visit would be refreshing.
Conversely, the narrative for inducing low arousal level expectations described the
following situation:
Sam has had a hectic week at work. Having heard of the opening of a new music store (book
store), Sam has decided to visit the store, and hopes that the new shop would offer a place for
quiet listening (quiet browsing) in a leisurely and idyllic environment, and that the music
store (book store) visit would be relaxing.
We chose a projective role play cum video simulation for this study for several reasons.
First, this method enabled us to inject sufficient variance into the independent
variables while minimizing idiosyncratic responses to the research context (Havlena
and Holbrook, 1986; Wirtz and Bateson, 1999). Second, the scenario method has been
shown to have ecological validity in service research involving consumer emotions and
complex cognitive processes (Bateson and Hui, 1992; Echeverri, 2005; Lemmink and
Mattson, 1998). Third, this method works best when respondents are familiar with the
research context (Dabholkar, 1996). Accordingly, our scenarios involved common
service encounters.
Actual arousal and pleasure manipulations. We first developed two videos, one
portraying a typical large book store, and the other a large music store (the identity of
the retailers was not revealed in the videos). These videos were then edited via music
tempo, sound and lighting manipulations. Three different music tempos 145 bpm (fast),
105 bpm (moderate) and 60 bpm (slow) were used to create high, moderate and low
arousal environments (Milliman, 1982, 1986). Next, we controlled for the sound levels
using a decibel meter. The suggested “soft” or low arousal level was ascertained to be
below 60 db (typical background music in retail environments), moderate arousal was
set at about 90 db (typical foreground music in retail environments), and high arousal
was induced with volume over 100 db (Kellaris and Altsech, 1992). Finally, to further
ensure that our arousal manipulations were effective, we used different color filters.
In the low arousal conditions, we used a yellow-orange filter for a soft lighting effect
while dimming the brightness levels. The original store illumination level (moderately
brightly lit) was kept intact for the moderate arousal conditions. For the high arousal
conditions, the lighting filter was saturated to increase the brightness effect (Valdez
and Mehrabian, 1994).
After re-engineering the musical pieces to elicit different arousal levels, the
manipulation of high-low pleasure levels was conducted. For the unpleasant
conditions, “white” noise was engineered, whereas the music pieces were left intact for
pleasant conditions. Care was taken that the noise was seen as an integral part of the
ambient service environment and not due to a faulty recording or viewing equipment.
A series of pre-tests were conducted to ensure that our manipulations were perceived
as intended. In total, we conducted four pretests. The first test guided the selection of a
pleasant piece of music that was not disliked by any respondent. The second tested
that the tempo, volume and white noise edits of the music piece were perceived as
intended in terms of their arousal intensity and pleasure level. The third checked the
arousal quality of the lighting manipulations in the videos, and the fourth pretest
The role of
arousal
congruency
11
IJSIM
18,1
12
ensured that the vignettes manipulating arousal level expectations were effective. The
pleasure and arousal measures employed in the pre-tests were the same as those used
in the study proper (see the measures section for details).
Experimental procedure
A total of 48 experimental sessions were held where groups of 10-15 subjects were
randomly assigned to one of the experimental conditions. At the beginning of each
session, subjects were told the cover story, which stated that they were participating in
a market study for a new music (book) store design. Respondents were then exposed to
the role-play scenario which manipulated desired arousal, and they were given
instructions to imagine themselves as the character described in the scenario. The
manipulation check for this variable was administered after respondents had read
the scenario. Subjects were then instructed to imagine that they had arrived at the new
store and to imagine themselves in the service environment depicted in the video
simulation. Next, subjects were asked to view a three-minute video clip of the music
(book) store experience, in which actual arousal and pleasure were manipulated. The
video was shown in a darkened seminar room using an LCD projector and a high
quality sound system giving subjects a vivid impression of the store environment. The
viewing experience was highly involving, somewhat similar to watching a film in a
movie theater. Having viewed the video clip, subjects completed the remainder of the
questionnaire which contained the pleasure and arousal manipulation checks, arousal
congruency, the dependent variables (satisfaction and in-store approach behavior), and
finally demographics. After each session, respondents were debriefed about the real
purpose of the study.
Measures
Desired arousal manipulation check. Mehrabian and Russell’s (1974) six-item semantic
differential scale of arousal was adapted to measure desired arousal for the store visit.
The original scale was modified to measure desired arousal in the way the question
was posed to the respondents. Specifically, subjects were asked to rate how they “hope
to feel” while being in the store, rather than how they “actually felt” in the store (Wirtz
et al., 2000). The scale items included calm-excited, sleepy-wide awake, and
sluggish-wild. The scale items were summated and used as an index for desired
arousal (for Cronbach a values, means and STDs see Table I).
Cronbach a Mean STD
Table I.
Summary scale statistics
and Pearson correlation
coefficients
1.
2.
3.
4.
5.
6.
Pleasure
Actual arousal
Desired arousal
Arousal congruency
In-store approach behavior
Satisfaction
0.92
0.93
0.93
0.94
0.93
0.94
3.95
4.57
4.08
0.38
3.23
2.99
1
Pearson correlation coefficients
2
3
4
5
6
1.65
1.0
1.41 20.06
1.0
1.45
0.06
0.05
1.0
a
1.24 20.11
0.60b 2 0.66b
1.0
1.69
0.69b 20.34b
0.06 20.31b 1.0
1.99
0.63b 20.05
0.17b 20.22b 0.66b 1.0
Notes: Scales 1 to 3 refer to manipulation checks. All scales range from 1 to 7, except arousal
congruency, which ranges from 2 3 to þ 3. Unless indicated otherwise, the correlation coefficients are
insignificant at p . 0.10. aSignificant at p , 0.01, bsignificant at p , 0.001
Actual arousal and pleasure manipulation checks. After viewing the video, the original
Mehrabian and Russell (1974) 12-item semantic differential scale for actual arousal and
pleasure felt was administered to measure emotional responses to the store
environment (e.g. calm-excited, sleepy-wide awake, and sluggish-wild for actual
arousal, and unhappy-happy, despairing-hopeful, melancholic-contented, and
annoyed-pleased for pleasure). The six items for the two scales were summated.
Arousal congruency. To directly measure perceived under/over-stimulation, we
adapted Mehrabian and Russell’s (1974) arousal scale. The scale items were relaxation
level, excitement level, alertness level, stimulation level and calmness level, measured
on a seven-point scale, anchored in 1 ¼ “much higher than desired” and 4 “just as
desired,” and 7 ¼ “much lower than desired. A series of pretests was conducted on this
scale, with the last pretest of a 100 respondents showing good reliability.
Satisfaction. Overall, satisfaction with the retail experience was measured using a
three-item scale in a seven-point Likert format (ranging from “strongly disagree” to
“strongly agree,” (Oliver, 1997). The three items captured the degree of satisfaction
with the music store/book store, the enjoyment of the entire store visit, and their
evaluation that the choice to come to the store was a good one.
In-store approach-avoidance behavior. A four-item, seven point semantic differential
measure of approach-avoidance was used to measure the intended in-store behavioral
responses to the physical environment (adapted from Donovan and Rossiter, 1982).
We included the following items that related to in-store behaviors: to explore the store,
to spend more time than planned, to spend more money than planned, and to be
friendly towards strangers in the store.
Initial analysis
We combined the music and book store samples as store type neither had main nor
interaction effects at p . 0.10 with any of the other independent variables on our
dependent variables of satisfaction and in-store behavior. In addition, the store-level
analysis yielded identical results to a combined sample analysis. For reasons of
parsimony, we present the combined sample analysis in this section.
Reliability and validity of measures
The relationship between the dependent variables of satisfaction and approach/
avoidance scales was checked using an exploratory factor analysis with oblique rotation
as satisfaction and in-store behaviors were correlated. The measure of sampling
adequacy (MSA) was excellent at 0.90. The factor analysis resulted in a clean two-factor
structure (all factor loadings exceeded 0.86). The first factor consisted of the three
satisfaction items (satisfied, enjoyed visit and good choice), while the second factor
comprised of the in-store approach-avoidance items of exploration (explore, spend time),
spending (spend money), and affiliation (feel friendly towards others). The total variance
explained was 83.2 percent. The Cronbach a values indicated high reliability of all scales
used (Table I).
To ensure that our manipulation checks measure separate constructs, an
exploratory factor analysis was conducted on the actual arousal, desired arousal
and actual pleasure scales. As expected, the results indicate a three-factor solution
with 74.1 percent overall variance explained by the three constructs. All the factor
loadings were high and loaded on their expected factors. Moreover, the correlations
The role of
arousal
congruency
13
IJSIM
18,1
14
coefficients in Table I show that the manipulation checks were not significantly
correlated, suggesting clean manipulations.
Also, as intended, arousal congruency was determined by actual arousal and
desired arousal. Actual arousal was negatively correlated to in-store behavior, but
showed no significant correlation with satisfaction. Furthermore, in contrast to actual
arousal, desired-arousal showed no significant correlation with in-store approach
behavior. These initial findings suggest a differential impact of actual arousal on
in-store approach behavior and satisfaction, and of actual arousal and desired-arousal
on in-store approach behavior, which will be explored further in the hypothesis testing
section.
Assessment of manipulations
As expected, subjects who expected a highly arousing store environment scored
significantly higher on the desired arousal manipulation check than their low arousal
expectations counterparts, X high desired arousal ¼ 5:44 and X low desired arousal ¼ 2:73,
t ¼ 57.1, p , 0.001. Consequently, the target-arousal manipulation was successful.
Similarly, subjects who were shown pleasant store environments rated the store as
significantly more pleasant than subjects shown unpleasant stores, X high pleasure ¼ 5:46
and X low pleasure ¼ 2:38, t ¼ 59.8, p , 0.001. In other words, the valence of the
environment was perceived as intended. Finally, the means for actual arousal are as
expected, X low arousal ¼ 2:71, X medium arousal ¼ 5:05, and X high arousal ¼ 5:77 for the low,
moderate and high arousal video clips. All comparisons were significant at p , 0.05
level. Taken together, these results indicate that our manipulations were effective.
Hypothesis testing
Arousal congruency was manipulated through the actual arousal and desired arousal
conditions. For reasons of parsimony and to allow us to directly test our hypotheses,
we coded the summated arousal congruency scale into three categories:
under-stimulation (scale mean , 3.5), arousal congruence (3.5 # scale mean , 4.5),
and over-stimulation (scale mean $ 4.5). The satisfaction and in-store approach
behavior mean scores across the experimental conditions are shown in Figure 1. The
ANOVA tables for satisfaction and in-store behavior are shown in Tables II and III,
respectively.
Satisfaction response
The results from an ANOVA table indicate a significant main effect for both
pleasure and arousal congruency on satisfaction, and these main effects are qualified
by a significant two-way interaction (Table II). We expected that, in pleasant
environments, arousal congruency would lead to higher satisfaction levels than
either perceived under- or over-stimulation (H1). The cell means shown in Figure 1
clearly support this hypothesis. Satisfaction is highest in the arousal congruency
condition (X congruency ¼ 5:98), and equally low in the two mismatch conditions
(X under – stimulation ¼ 2:18, and X over – stimulation ¼ 2:06). The contrast between the
under-stimulation and arousal congruency is highly significant (t ¼ 22.7; p , 0.001),
as is the contrast between arousal congruency and over-stimulation (t ¼ 33.3;
p , 0.001). The contrast between the under- and over-stimulation means is not
significant at t ¼ 0.74, p . 0.10. Together, these findings provide support for H1.
The role of
arousal
congruency
Satisfaction
6.00
5.98
5.50
5.00
15
4.50
4.00
3.50
Understimulation
3.00
Congruency
2.50
2.00
2.18
2.06
1.81
1.50
Overstimulation
1.96
1.56
1.00
Low pleasure
High pleasure
In-Store Approach Behavior
6.00
5.50
5.00
5.00
4.50
4.28
4.00
3.50
3.44
Understimulation
Congruency
3.00
2.75
2.50
Overstimulation
2.00
2.03
1.50
1.69
1.00
Low pleasure
High pleasure
Conversely, the mean satisfaction ratings are uniformly low in unpleasant
environments. These results are congruent with our valence-moderation hypothesis.
Here, the contrast between under-stimulation and arousal congruency was not
significant (t ¼ 1.39; p . 0.10), and satisfaction dropped significantly in the
over-stimulation condition (t ¼ 4.72; p , 0.05), but much less so than in the pleasant
Figure 1.
Satisfaction and in-store
behaviors as a function of
arousal congruency and
pleasure
IJSIM
18,1
16
Table II.
Two-way ANOVA of
pleasure and arousal
congruency on
satisfaction
Table III.
Two-way ANOVA of
pleasure and arousal
congruency on in-store
behaviors
environment condition. Together, these findings support that arousal congruency
plays an insignificant or at least a much weaker role in unpleasant environments than
in pleasant environments, confirming H2.
In-store behaviors
As with satisfaction, the significant main effects for pleasure and arousal congruency
on in-store behavior were qualified by a significant two-way interaction (Table III).
However, the magnitude of the interaction was lower with in-store-behaviors than with
satisfaction, as indicated by lower partial h 2 scores.
We expected that in pleasant store environments, arousal congruency would lead to
maximized approach behaviors as an optimal level of arousal is achieved (H3). The
means shown in Figure 1 are congruent with this prediction. On the other hand, we
predicted in H4 that compared to over-stimulation, under-stimulation should lead to
enhanced affiliative behaviors in pleasant environments. Under conditions of
under-stimulation, subjects were expected to be motivated to engage in affiliate
behaviors such as exploring the environment or talking to others in the store in order to
move themselves closer to the optimal stimulation level. Again, our data lend support
for this hypothesis. The mean approach behavior rating in the under-stimulation
condition is significantly higher than that in the over-stimulation condition
((X understimulaton ¼ 4:28, X overstimulaton ¼ 3:44, t ¼ 4.65, p , 0.05). This pattern of
results associated with under-stimulation is clearly different from that observed for
satisfaction. In other words, under-stimulation seems to result in relatively low levels
of satisfaction, but higher levels of approach behaviors.
Finally, as advanced in H5, we expected uniformly low in-store behaviors in
unpleasant store environments. As hypothesized, the mean in-store behavioral
response ratings were low across all arousal congruency conditions. In fact, in-store
behaviors were reduced at increasing levels of stimulation (X understimulaton ¼ 2:75, and
X arousal congruency ¼ 2:03, with a significant contrast effect of t ¼ 4.10, p , 0.05; and
X over-stimulation ¼ 1:69 with a significant contrast to congruency at t ¼ 5.70, p , 0.05).
Source of variation
df
Sum of squares
Mean square
F
Sig.
h2
Pleasure (P)
Arousal congruency (AC)
P£AC
Error
Total
1
2
2
500
505
270.1
553.3
398.0
300.2
1,991.2
270.1
276.6
199.0
0.6
449.9
460.7
331.4
, 0.001
, 0.001
, 0.001
0.47
0.65
0.57
Source of variation
df
Sum of squares
Mean square
F
Sig.
h2
Pleasure (P)
Arousal congruency (AC)
P£AC
Error
Total
1
2
2
500
505
443.5
103.0
52.7
575.1
1,441.9
443.5
51.5
26.3
1.2
385.6
44.8
22.9
, 0.001
, 0.001
, 0.001
0.44
0.15
0.08
Discussion, implications and further research
This research advances our understanding of the role of environment-induced affect in
consumer satisfaction and in-store behaviors. Previous research in services clearly
demonstrates the importance of emotions in understanding customer satisfaction and
in-store behavioral responses (Van Dolen et al., 2002; Mattila and Enz, 2002; Mattila
and Wirtz, 2000; Morrin and Chebat, 2005; Wirtz et al., 2000). Overall, our findings
indicate that satisfaction in pleasant service environments is driven by arousal level
expectations being met by the arousal quality of the service environment, while such
matching effects are much weaker or even fail to influence satisfaction in unpleasant
settings. However, consumers’ in-store behavioral responses to service environments
do not necessarily mirror their satisfaction evaluations. We advance that optimal
stimulation is the key to understanding consumers’ in-store behaviors. These findings
are further elaborated upon below.
Consistent with the affective expectations model (Geers and Lassitier, 1999; Phillips
and Baumgartner, 2002; Wilson et al., 1989), we argue that consumers’ evaluative
responses to service environments are formed with reference to prior expectations
about how they would like to feel in the actual environment. In our context of two types
of retail environments, arousal congruency enhanced satisfaction in pleasant service
settings, thus indicating matching effects in expectation-congruent service
environments. Conversely, subjects exhibited low satisfaction levels, when the actual
arousal elicited by the pleasant store environment was not consistent with prior
expectations. As expected, under- or over-stimulation was perceived in a negative light,
thus providing additional support for the affective expectations model.
Following our valence moderation hypothesis, we argue that arousal congruency
effects should be minimal in unpleasant service environments. Robust findings from
various areas of psychology suggest that the power of negative events or stimuli is
greater than that of positive ones (Anderson, 1965; Averill, 1980; Baumeister et al.,
2001; Skowronski and Carlston, 1989). In this study, satisfaction was uniformly low in
unpleasant environments, thus indicating that the negative valence of the environment
largely overshadowed the effects of arousal-level expectations.
As an alternative hypothesis, the affect-as-information framework might partially
explain our findings regarding satisfaction. Recent work on the affect-as-information
framework suggests that people use their own feelings as an input to everyday
judgments (Albarracin and Kumkale, 2003; Ottati and Isbell, 1996; Schwarz and Clore,
1983). Affect is in fact an integral part of evaluative judgments (Gohm and Clore, 2000,
p. 91). Consequently, people are likely to ask themselves “how do I feel about it?” when
asked to assess their level of satisfaction with retail environments (Schwarz, 2001).
These affective reactions are particularly salient when the judgment involves hedonic
criteria (Adaval, 2001; Pham, 1998; Yeung and Wyer, 2004). Consequently, it seems
logical to propose that consumers use their feelings as input to their satisfaction
judgments. Unfortunately, our methodology does not allow us to scrutinize the
information processing consequences of arousal congruency. Thus, future research is
needed to investigate this possibility.
In addition to satisfaction, we wanted to contrast stimulus seeking behaviors with
evaluative responses. We postulated that optimal stimulation influences consumers’
in-store behaviors. In pleasant environments, the optimal arousal level is achieved
when the actual arousal matches the consumer’s a priori expectations, thus leading to
The role of
arousal
congruency
17
IJSIM
18,1
18
high levels of affiliative behaviors like talking to others, feeling friendly towards
others, exploring the store, and spending time in the store (Donovan and Rossiter, 1982;
Mehrabian and Russell, 1974). In our study, arousal congruency led to maximized
satisfaction and in-store behaviors. When the pleasant environment fell short of
arousal level expectations, this perceived under-stimulation also facilitated positive
in-store behaviors although the magnitude of the effect was lower than in our
congruency conditions. When experiencing under-stimulation, our findings suggest
that consumers are motivated to engage in approach behaviors in order to bring their
arousal levels closer to the optimal level. This finding is consistent with work in
clinical psychology suggesting that low arousal conditions enhance affiliative
behaviors (Berlyne, 1971; Borling, 1981; Mezzano and Prueter, 1974). It is important to
note that these favorable behavioral responses occurred despite low levels of
satisfaction with the shopping environment. Consequently, satisfaction and in-store
behaviors do not necessarily go hand-in-hand. As expected, over-stimulation led to low
levels of approach behaviors as the actual environment was perceived as too
stimulating.
Finally, as with satisfaction, in-store behaviors were uniformly low in unpleasant
settings. In fact, approach behaviors that were at low levels to begin with, further
declined at increasing stimulation levels, and this finding was independent of arousal
congruency.
To conclude, the present research adds to the growing literature documenting the role
of atmospheric cues on consumer evaluations and in-store behaviors. The results of this
study indicate that consumer satisfaction is strongly influenced by arousal congruency
in pleasant environments, whereas satisfaction responses in unpleasant conditions
appear to be more valence-driven. The response patterns were slightly different with
in-store behaviors. Perceived under-stimulation, regardless of the level of satisfaction,
had a positive effect on in-store behaviors, thus suggesting that satisfaction alone might
not be adequate in explaining consumer responses to retail settings.
Managerial implications
The findings of this study indicate that retailers need to pay attention not only to the
pleasantness of the store environment, but also to arousal eliciting elements of the
servicescape (Bitner, 1992). In this study, satisfaction was maximized when the level of
excitement in the environment matched the consumer’s prior expectations. This means
that service firms need to attract the right target segment whose desired level of
stimulation is consistent with the firm’s positioning, and then engineer the promised
excitement level. To achieve arousal congruency, managers need to first understand
consumers’ desired arousal levels. Although customers differ in their arousal
seeking-tendencies (i.e. some prefer razzle-dazzle type environments and others feel
more comfortable in calm settings), service managers usually have a good
understanding of their target segment’s arousal level expectations. For example,
spectators at a football game are likely to have high levels of desired arousal, while
consumers patronizing a fine dining restaurant are likely to have low levels of desired
arousal. As a result, firms need to match the actual servicescape to customer
expectations in terms of excitement level.
There are several avenues for engineering actual arousal levels in a service
environment. For instance, fast tempo and high volume music increase arousal,
whereas low tempo low volume music has the opposite effect (Holbrook and Anand,
1990). Similarly, warm colors such as orange, yellow and red tend to increase arousal
(Valdez and Mehrabian, 1994). In contrast, cool colors such as blue and green are
associated with feelings of calmness (Zollinger, 1999). Arousal qualities in the
environment can also be managed by ambient scents (Mattila and Wirtz, 2001), as
illustrated by the use of leather, citrus and baby powder scents in the Aventura Shoe
Store in Chicago (Levy and Weitz, 2004).
In addition, service firms can manage consumers’ expected arousal level via its
integrated communications strategy. For example, a clothing store can portray itself as
a cozy place for relaxed shopping (e.g. Victoria’s Secret), or it can position itself to be
hip and energizing for the young (e.g. Hot Topic). Proper communication messages
would enable consumers to form realistic expectations of the arousal level in the
shopping environment and then appropriately self-segment themselves into their
desired service environment, thus leading to pleasurable experiences.
Our results further suggest that consumers’ in-store behavioral responses to the
environment might not always be in synch with their satisfaction evaluations. More
specifically, under-stimulation resulted in higher in-store approach behaviors than
over-stimulation, even though satisfaction was equally low in both conditions. In other
words, over-stimulation might sometimes backfire. Hence, careful monitoring of the
arousal-eliciting elements of the physical environment is needed if the goal is to make
customers approach sales staff or stay in the store for extended periods of time.
Finally, our results regarding potentially unpleasant servicescapes are
straight-forward. Here, the atmospherics should either be improved, or if that is not
possible, they should be designed so as to minimize arousal. Soothing colors such as
blue or green can be used to create calm environments. Alternatively, playing
slow-tempo, classical music can induce similar effects.
Limitations and further research directions
The scope of this study was limited to exploring the impact of affect on satisfaction
evaluations and in-store behaviors. However, cognitive influences, such as
disconfirmation, are also critical for fully understanding consumers’ satisfaction
formation processes (Phillips and Baumgartner, 2002). Because this study
operationalized arousal congruency to be similar to the disconfirmation construct, it
provides a fruitful starting point for the study of both the affective and cognitive
components of the satisfaction equation. This research relied on desired arousal as an
expectation standard. However, service quality research indicates that consumers have
a range of cognitive expectations bounded by desired, adequate and tolerated
expectations (Zeithaml et al., 1993). Future work is needed to show if the zone of
tolerance concept is applicable to affective expectations. In a similar vain, potential
threshold levels could be explored, such as, how bad an environment has to become in
order for a customer to neglect previously held expectations?
Another limitation of our work is that we used a scenario method to manipulate
desired arousal and videos as a proxy for the actual consumption experience. The
potential disadvantage of this method is that subjects may not be able to fully project
themselves into the imaginary scenarios, and therefore not respond in an identical
manner as they would in a real life service consumption situation. Investigating
different types of service settings, respondent groups, and a replication using a field
The role of
arousal
congruency
19
IJSIM
18,1
20
experiment and/or survey would provide a richer understanding of the relative
contribution of arousal congruency on pleasure and satisfaction. Furthermore, the
impact of non-visual and non-audible environmental stimuli such as scents was
ignored in our research design. Therefore, to establish external validity, sampling in
actual retail environments is needed to fully capture the “holistic effects of a store
environment” (Chebat and Dube , 2000).
The focus of the present study was on hedonic services. Hence, it would be
interesting to see if our findings extend to stores selling utilitarian goods and services
such as computer stores. Arousal may play a very different role in utilitarian settings
where cognitive effort is needed for choosing products and services, and a stimulating
environment may be seen as interfering with this process. Furthermore, different
approach behaviors are desirable for different types of retail or service concepts. In a
supermarket or department store that has few staff and is largely based on self-service,
desirable approach behaviors would be spending more time in the store, browsing
more, increasing impulse buying and as a result increasing overall spending. In a
service environment that is heavily geared towards front line staff serving customers
and helping them assemble the right solution for their needs (e.g. in a travel agency,
higher end kitchen or appliance store, or a high end clothing store) approaching service
staff should be added to that list of desirable behaviors. Our two retail contexts were
somewhere in between a clear full-service or a self-service concept, as customers can
either browse by themselves, or can approach service staff to help them find particular
titles, selections or make suggestions, which all should increase overall sales. Future
work could explore the impact of the type of service concept and arousal congruency
on alternative approach behaviors.
Finally, alternative interpretations of arousal posit a two-dimensional view of
activation (Gorn et al., 1997; Henthorne et al., 1993; Smith and Apter, 1975; Thayer,
1989). For example, in Thayer’s (1989) framework, the two arousal dimensions
are called tension and energy. In Apter’s (1976) model, excitement and relaxation are
considered separate dimensions of arousal, and the two states can co-occur. Future
work should examine whether the two-dimensional view of arousal can enrich our
understanding of arousal congruency effects on satisfaction and in-store behaviors
beyond the more parsimonious model used in this present study.
References
Adaval, R. (2001), “Sometimes it just feels right”, Journal of Consumer Research, Vol. 28 No. 1,
pp. 1-17.
Albarracin, D. and Kumkale, G.T. (2003), “Affect as information in persuasion: a model of affect
identification and discounting”, Journal of Personality and Social Psychology, Vol. 84 No. 3,
pp. 453-69.
Anderson, N.H. (1965), “Averaging versus adding as stimulus-combination rule in impression
formation”, Journal of Personality and Social Psychology, Vol. 2, pp. 1-9.
Apter, M.J. (1976), “Some data inconsistent with the optimal arousal theory of motivation”,
Perceptual and Motor Skills, Vol. 43, pp. 1209-10.
Averill, J.R. (1980), “On the paucity of positive emotions”, in Blankstein, K.R., Pliner, P. and
Polivy, J. (Eds), Advances in the Study of Communication and Affect,Vol. 6, Plenum Press,
New York, NY, pp. 7-45.
Bateson, J.E.G. and Hui, M. (1992), “The ecological validity of photographic slides and videotapes
in simulating the service setting”, Journal of Consumer Research, Vol. 19, pp. 271-81.
Baumeister, R., Bratslavsky, E., Finkenauer, C. and Vohs, K. (2001), “Bad is stronger than good”,
Review of General Psychology, Vol. 5 No. 4, pp. 323-70.
Berlyne, D.E. (1960), Aesthetics and Psychobiology, Meredith, New York, NY.
Berlyne, D.E. (1967), “Arousal and reinforcement”, in Levine, D. (Ed.), Nebraska Symposium on
Motivation,Vol. 15, University of Nebraska Press, Lincoln, NE, pp. 1-110.
Berlyne, D.E. (1971), Aesthetics and Physiobiology, Appleton-Century-Crofts, New York, NY.
Bitner, M.J. (1992), “Servicescapes: the impact of physical surroundings on customers and
employees”, Journal of Marketing, Vol. 56, pp. 57-71.
Borling, J.E. (1981), “The effects of sedative music on alpha rhythms and focused
attention in high-creative and low-creative subjects”, Journal of Music Therapy, Vol. 18,
pp. 101-8.
Bower, G. (1981), “Mood and memory”, American Psychologist, Vol. 36, pp. 129-48.
Chebat, J-C. and Dube , L. (2000), “Evolution and challenges facing retail atmospherics”, Journal of
Business Research, Vol. 49 No. 2, pp. 89-90.
Dabholkar, P.A. (1996), “Consumer evaluations of new technology-based self-service options: an
investigation of alternative models of service quality”, International Journal of Research in
Marketing, Vol. 13, pp. 29-51.
Dodges, S.D. and Klaaren, K.J. (2000), “Talking about safe sex: the role of expectations and
experience”, Journal of Applied Social Psychology, Vol. 30 No. 2, pp. 330-49.
Donovan, R.J. and Rossiter, J.R. (1982), “Store atmosphere: an environmental psychology
approach”, Journal of Retailing, Vol. 58, pp. 34-57.
Donovan, R.J., Rossiter, J.R., Marcoolyn, G. and Nesdale, A. (1994), “Store atmosphere and
purchasing behavior”, Journal of Retailing, Vol. 70 No. 3, pp. 283-94.
Echeverri, P. (2005), “Video-based methodology: capturing real-time perceptions of customer
processes”, International Journal of Service Industry Management, Vol. 16 No. 2,
pp. 199-210.
Feldman, L. (1995), “Valence and arousal: individual differences in the structure of affective
experience”, Journal of Personality and Social Psychology, Vol. 69 No. 1, pp. 153-66.
Geers, A. and Lassitier, D. (1999), “Affective expectations and information gain: evidence for
assimilation and contrast effects in affective experience”, Journal of Experimental Social
Psychology, Vol. 35, pp. 394-413.
Geers, A. and Lassitier, D. (2002), “Effects of affective expectations on affective experience: the
moderating role of optimism-pessimism”, Personality and Social Psychology Bulletin,
Vol. 28 No. 8, pp. 1026-39.
Gohm, C. and Clore, G. (2000), “Individual differences in emotional experience: mapping available
scales to processes”, Personality and Social Psychology Bulletin, Vol. 26, pp. 679-97.
Gorn, G.J., Amitava, C., Yi, T. and Dahl, D.W. (1997), “Effects of color as an executional
cue in advertising: they’re in the shade”, Management Science, Vol. 43 No. 10, pp. 1387-400.
Havlena, W.J. and Holbrook, M.B. (1986), “The varieties of consumption experience: comparing
two typologies of emotion in consumer behavior”, Journal of Consumer Research., Vol. 13,
pp. 174-84.
Henthorne, T.L., Latour, M.S. and Natarajaan, R. (1993), “Fear appeals in print
advertising: an analysis of arousal and ad response”, Journal of Advertising, Vol. 22
No. 2, pp. 59-69.
The role of
arousal
congruency
21
IJSIM
18,1
22
Holbrook, M.B. and Anand, P. (1990), “Effects of tempo and situational arousal on the listener’s
perceptual and affective responses to music”, Psychology of Music, Vol. 18, pp. 150-62.
Hui, M., Dube , L. and Chebat, J-C. (1997), “The impact of music on consumer’s reactions to
waiting for services”, Journal of Retailing, Vol. 73 No. 1, pp. 87-104.
Izard, C.E. (1977), Human Emotions, Plenum Press, New York, NY.
Kellaris, J.J. and Altsech, M.B. (1992), “The experience of time as a function of musical loudness
and gender of listener”, in Holman, R.H. and Solomon, M.R. (Eds), Advances in Consumer
Research,Vol. 19, Association for Consumer Research, Provo, UT, pp. 725-9.
Lang, P. (1979), “A bio-informational theory of emotion imagery”, Psychophysiology, Vol. 16,
pp. 495-512.
Lemmink, J. and Mattson, J. (1998), “Warmth during non-productive retail encounters: the
hidden side of productivity”, International Journal of Research in Marketing, Vol. 15,
pp. 505-17.
Levy, M. and Weitz, B.A. (2004), Retailing Management, McGraw-Hill, New York, NY.
McClelland, D., Atkinson, J., Clark, R. and Lowell, E. (1953), The Achievement Motive,
Appleton-Crofts, New York, NY.
Mattila, A.S. and Enz, C. (2002), “The role of emotions in service encounters”, Journal of Service
Research, Vol. 4 No. 4, pp. 268-77.
Mattila, A.S. and Wirtz, J. (2000), “The role of pre-consumption affect in post-purchase evaluation
of services”, Psychology & Marketing, Vol. 17 No. 7, pp. 587-605.
Mattila, A.S. and Wirtz, J. (2001), “Congruency of scent and music as a driver of in-store
evaluations and behaviour”, Journal of Retailing, Vol. 77 No. 2, pp. 273-89.
Mehrabian, A. and Russell, J.A. (1974), An Approach to Environmental Psychology,
Massachusetts Institute of Technology, Cambridge, MA.
Mezzano, J. and Prueter, B. (1974), “Background music and counseling interaction”, Journal of
Counselling Psychology, Vol. 21, pp. 84-6.
Milliman, R. (1982), “Using background music to affect the behavior of supermarket shoppers”,
Journal of Marketing, Vol. 46, pp. 86-91.
Milliman, R. (1986), “The influence of background music on the behavior of restaurant patrons”,
Journal of Consumer Research, Vol. 13, pp. 286-9.
Mineka, S. (1979), “The role of fear in theories of avoidance, learning, flooding and extinction”,
Psychological Bulletin, Vol. 86, pp. 985-1010.
Morrin, M. and Chebat, J-C. (2005), “Person-place congruency: the interactive effects of shopper
style and atmospherics on consumer expenditures”, Journal of Service Research, Vol. 8
No. 2, pp. 181-91.
Niedenthal, P.M. and Setterlund, M. (1994), “Emotion congruence in perception”, Personality and
Social Psychology Bulletin, Vol. 20, pp. 401-10.
North, A. and Hargreaves, D. (2000), “Musical preferences during and after relaxation and
exercise”, The American Journal of Psychology, Vol. 113 No. 1, pp. 43-67.
Oliver, R.L. (1997), Satisfaction: A Behavioral Perspective on the Consumer, McGraw-Hill,
New York, NY.
Ottati, V. and Isbell, L. (1996), “Effects of mood during exposure to target information on
subsequently reported judgments: an on-line model of misattribution and correction”,
Journal of Personality and Social Psychology, Vol. 71, pp. 39-53.
Pham, M. (1998), “Representativeness, relevance and the use of feelings in decision making”,
Journal of Consumer Research, Vol. 25 No. 2, pp. 144-59.
Phillips, D. and Baumgartner, H. (2002), “The role of consumption emotions in the satisfaction
response”, Journal of Consumer Psychology, Vol. 12 No. 3, pp. 243-52.
Plutchik, R. (1980), Emotion: A Psychoevolutionary Synthesis, Harper & Row, New York, NY.
Pullman, M. and Gross, M. (2004), “Ability to experience design elements to elicit emotions and
loyalty behaviors”, Decision Sciences, Vol. 35 No. 3, pp. 551-78.
Rachman, S. (1984), Fear and Courage, 2nd ed., Freeman, New York, NY.
Rafaeli, A. and Kluger, A. (2000), “Affective reactions to physical appearance”, in Ashkanasy, N.,
Haertel, C. and Zerbe, W. (Eds), Emotions in the Workplace: Research, Theory and Practice,
Quorum Books, Westport, CT, pp. 141-55.
Russell, J. and Feldman, L. (1999), “Core affect, prototypical emotional episodes, and other things
called emotion: dissecting the elephant”, Journal of Personality and Social Psychology,
Vol. 76 No. 5, pp. 805-19.
Schwarz, N. (2001), “Feelings as information: implications for affective influences on information
processing”, in Martin, L.L. and Clore, G.L. (Eds), Theories of Mood and Cognition: A
User’s Guidebook, Erlbaum, Mahwah, NJ, pp. 159-76.
Schwarz, N. and Clore, G. (1983), “Mood, misattribution and judgments of well-being”, Journal of
Personality and Social Psychology, Vol. 45, pp. 513-23.
Skowronski, J.J. and Carlston, D.E. (1989), “Negativity and extremity biases in impression
formation: a review of explanation”, Psychological Review, Vol. 105, pp. 131-41.
Smith, K.C.P. and Apter, M.J. (1975), A Theory of Psychological Reversal, Picton, Chippenham.
Steenkamp, J-B. and Baumgartner, H. (1992), “The role of optimum stimulation level in
exploratory consumer behavior”, Journal of Consumer Research, Vol. 19, pp. 434-48.
Thayer, R. (1989), The Biopsychology of Mood and Activation, Oxford University Press,
New York, NY.
Valdez, P. and Mehrabian, A. (1994), “Effect of color on emotions”, Journal of Experimental
Psychology, Vol. 123 No. 4, pp. 394-409.
Van Dolen, W., Lemmink, J., Ruyter, K. and De Jong, A. (2002), “Customer-sales employee
encounters: a dyadic perspective”, Journal of Retailing, Vol. 78 No. 4, pp. 265-79.
Vilnai-Yavetz, I. and Rafaeli, A. (2006), “Aesthetics and professionalism of virtual servicescapes”,
Journal of Service Research, Vol. 8 No. 3, pp. 245-59.
Wilson, T.D., Lisle, D.J., Kraft, D. and Wetzel, C.G. (1989), “Preferences as expectation-driven
inferences: effects of affective expectations on affective experience”, Journal of Personality
and Social Psychology, Vol. 56 No. 4, pp. 519-30.
Wirtz, J. (1994), “The affect literature in psychology – a review for consumer behaviourists”,
Asian Journal of Marketing, Vol. 3, pp. 49-70.
Wirtz, J. and Bateson, J.E.G. (1999), “Consumer satisfaction with services: integrating the
environmental perspective in services marketing into the traditional disconfirmation
paradigm”, Journal of Business Research, Vol. 44 No. 1, pp. 55-66.
Wirtz, J., Mattila, A.S. and Tan, R.L.P. (2000), “The moderating role of target-arousal on the
impact of affect on satisfaction – an examination in the context of service experience”,
Journal of Retailing, Vol. 76 No. 3, pp. 347-65.
Yeung, C. and Wyer, R. (2004), “Affect, appraisal and consumer judgment”, Journal of Consumer
Research, Vol. 31 No. 2, pp. 412-24.
Zeithaml, V., Berry, L. and Parasuraman, A. (1993), “The nature and determinants of customer
expectations of service”, Journal of the Academy of Marketing Science, Vol. 21 No. 1,
pp. 1-12.
The role of
arousal
congruency
23
IJSIM
18,1
24
Zollinger, H. (1999), Heinrich Color: A Multidisciplinary Approach, Verlag Chimica Acta (VHCA)
Weinheim, Wiley-VCH, Zurich, pp. 71-9.
Zuckerman, M. (1979), Sensation Seeking: Beyond the Optimal Level of Arousal, Lawrence
Erlbaum, Hillsdale, NJ.
About the authors
Jochen Wirtz (PhD, London Business School) is an Associate Professor of Marketing at the
National University of Singapore and Co-Director of the UCLA – NUS Executive MBA Program.
Jochen’s research focuses on services marketing and has been published in over 60 academic
articles in journals such as Harvard Business Review, Journal of Consumer Psychology, Journal of
Retailing, and Journal of the Academy of Marketing Science. Jochen serves on the editorial review
boards of seven journals, including the Cornell Quarterly, International Journal of Service
Industry Management and Journal of Service Research. He co-authored over 10 books, including
the fifth edition of Services Marketing – People, Technology and Strategy (with Christopher
Lovelock) published by Prentice-Hall. His latest book, Flying High in a Competitive Industry –
Cost-effective Service Excellence at Singapore Airlines, was published by McGraw-Hill in 2006.
Jochen has received over a dozen research and teaching awards, including the University-level
“Outstanding Educator Award” in 2003. Jochen Wirtz is the corresponding author and can be
contacted at: [email protected]
Anna S. Mattila is an Associate Professor and Professor in Charge of Graduate Program at
the School of Hospitality Management at Pennsylvania State University. She holds a PhD from
Cornell University, an MBA from University of Hartford and a BS from Cornell University. Her
research interests focuses on consumer responses to service encounters and cross-cultural issues
in services marketing. Her work has appeared in the Journal of the Academy of Marketing
Science, Journal of Retailing, Journal of Service Research, Journal of Consumer Psychology,
Psychology & Marketing, Journal of Services Marketing, International Journal of Service Industry
Management, Cornell Hotel & Restaurant Administration Quarterly, Journal of Travel Research,
International Journal of Hospitality Management and Journal of Hospitality & Tourism Research.
Web-link: www.personal.psu.edu/faculty/a/s/asm6
Rachel L.P. Tan was a Masters of Science candidate during the conduct of this study at the
Department of Marketing, NUS Business School, National University of Singapore, and is now
with Singapore Airlines.
To purchase reprints of this article please e-mail: [email protected]
Or visit our web site for further details: www.emeraldinsight.com/reprints