Impact of music on consumer behaviour
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An exploration of happy/sad and liked/disliked music effects on shopping intentions in a women’s clothing store service setting
Greg Broekemier
University of Nebraska at Kearney, Kearney, Nebraska, USA
Ray Marquardt Arizona State University-Polytechnic Campus, Mesa, Arizona, USA, and
James W. Gentry University of Nebraska-Lincoln, Lincoln, Nebraska, USA
Abstract Purpose – The purpose of this paper is to determine which two dimensions of music, happy/sad or liked/disliked, have significant effects on shopping intentions, thereby providing guidance for decision-makers in service environments. Design/methodology/approach – Subjects viewed videotapes of an unfamiliar store in an experimental research design. Subjects were exposed to one of several musical treatments while viewing and were asked to speak their thoughts about the store aloud. Happy/sad musical treatments were determined through pretests while subjects’ unprompted comments were used to assess like/dislike for the music. Subjects also reported intentions to shop in the stimulus store. The hypothesized model was then tested. Findings – Happy/sad music had a significant direct effect on shopping intentions while the direct effect of liked/disliked music was marginally significant. However, the combination of the two music dimensions investigated is perhaps most noteworthy. Shopping intentions were greatest when subjects were exposed to happy music that was liked. Research limitations/implications – Only a women’s clothing store service setting with a limited target market was utilized. Care should be taken when generalizing beyond this setting and subject group. Practical implications – Happy music that is liked by the target market can significantly increase intentions to shop in a retail service environment. Originality/value – Little research has been done investigating the effects of the affective, or happy/sad, component of music in service settings. This study helps fill that gap in the literature. In addition, studies investigating music’s effects in retail environments often examine only one dimension of music. The value of assessing effects of multiple dimensions of music is demonstrated.
Keywords Music, Service levels, Shopping
Paper type Research paper
An executive summary for managers can be found at
the end of this article.
Introduction
Atmospherics, including music, have received considerable
attention in the retail/services literature since Kotler (1974)
used the term to describe the conscious designing of space in
store environments to create certain effects in buyers.
Atmospherics consist of elements such as brightness, size,
shape, volume, pitch, scent, freshness, softness, smoothness,
and temperature. Milliman and Fugate (1993, p. 68) defined
an atmospheric variable as “any component within an
individual’s perceptual field which stimulates one’s senses
and thus affects the total experience of being in a given place
at a given time”. Morrison and Beverland (2003) consider
music to be an important variable in creating in-store
experiences and connecting with customers’ emotions while
North and Hargreaves (1998) believe the role of music in
consumer research is of considerable theoretical interest as
well. Turley and Milliman (2000) conceptualized atmospheric
variables as stimuli leading to some cognitive affect within the
individual that, in turn, leads to some behavioral response.
Several researchers have indeed reported links between
atmospherics and retail patronage or patronage intentions.
Baker et al. (1992) found that store patronage is influenced, to
some degree, by store environments while Schlosser (1998)
reported that intentions to shop in fictional stores was
influenced by atmospheric variables. Chebat et al. (2000)
discussed a physical environment’s ability to influence
behaviors in stores much as Bitner (1992) believes that
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0887-6045.htm
Journal of Services Marketing
22/1 (2008) 59–67
q Emerald Group Publishing Limited [ISSN 0887-6045]
[DOI 10.1108/08876040810851969]
Received: March 2005 Revised: December 2005 Accepted: May 2006
59
service businesses, including retail stores, can influence
behaviors of patrons. Retail patronage intentions have been found to be more highly correlated with consumers’ beliefs
about physical attractiveness of retail service environments than with merchandise quality, general price level, selection,
and six other store/product beliefs (Darden et al., 1983). Milliman and Fugate (1993, p. 72) state that “buying
behavior is encouraged (purchase probability increases) through positive atmospheric outcomes, therefore marketers
must carefully plan an appropriate atmosphere”. Some atmospheric factors are more easily controlled by
marketers than others. Music is one factor that is ordinarily
highly controllable, ranging from loud to soft, fast to slow, vocal to instrumental, heavy metal to hit-oriented rock, or
classical to contemporary urban. Yalch and Spangenberg (1993, p. 632) state that “music is a particularly attractive
atmospheric variable because it is relatively inexpensive to provide, is easily changed, and is thought to have predictable
appeals to individuals based on their ages and lifestyles”. Music, when matched with the interests of patrons, may add
to consumer excitement (Wakefield and Baker, 1998). While Hume et al. (2003) did not find behavioral effects of music on wine purchases in a music congruence (fit) study, many
researchers (Milliman, 1982, 1986; Yalch and Spangenberg, 1990; Areni and Kim, 1993; Gulas and Schewe, 1994;
Wakefield and Baker, 1998; and Mattila and Wirtz, 2001) have reported that shoppers’ behaviors in retail service
environments can be affected by the background music played in retail environments. Morrison and Beverland (2003)
speculate that if there is not a synergistic match between store type and music, the effects on consumers could be
negative or confusing. Retail shoppers themselves have also acknowledged the
importance of music as an atmospheric variable. Rubel (1996) discussed a poll conducted by the Gallup Organization in which 91 percent of retail customers surveyed said music
had an effect on their shopping behavior. That same poll revealed that 86 percent of these customers said music added
to the atmosphere of a store, while music influenced the purchase decisions of 33 percent of respondents. Results such
as this add support to the idea that music can be a very important atmospheric variable. Notwithstanding the previous discussion, there is still much
to be learned about the effects of music in various marketing
settings. Music, while easily controlled by retailers, has many dimensions, some of which we know little about. Since
Bruner (1990), in a review of published and some unpublished research, reported that relatively few studies have examined the effects of music in retail stores, there has
been considerable published research regarding music’s effects in retail environments. However, music is a complex
construct and examinations that investigate only one aspect of music may be limited. The purpose of this paper, then, is to explore the
relationship between an important atmospheric variable,
music, and shopping intentions. More specifically, the effects of two aspects of music, the affective (happy/sad)
dimension and subjects’ liking/disliking of music, both separately and in combination, on respondents’ intentions to
shop in a particular retail service environment, a women’s fashion clothing store, are examined. This investigation allows for a more thorough and realistic examination of music’s
effects than many previous studies provide.
Literature review
Bruner’s (1990) conclusion that more studies involving music
and various aspects of marketing were needed is of particular
note since music has long been considered to be an efficient
and effective means for triggering moods and communicating
nonverbally. Research has shown that music can influence
consumers’ responses to advertising and to retail
environments. Findings include changes in emotional states,
attitude toward the ad and toward the brand, purchase
intention and behavior (Dube et al. 1995). In one such examination of ambient factors of store
environments, Baker et al. (1992) operationalized a low
ambient store environment as one playing background
classical music with soft lighting and a high ambient store
environment as one using foreground top-40 music and bright
lighting. Music tempo was held constant, as it was in the
present research study, and a statistically significant
interaction between ambient and social factors was reported.
However, the happy/sad component of music was not
examined and shopping intentions were not assessed. Subsequently, Herrington and Capella (1996) investigated
the effects of the preferential dimension of music, i.e. the
degree to which the shopper likes or dislikes background
music. Based on a sample of 89 grocery store shoppers, these
researchers reported that musical preference can have a
positive impact on the amount of time and money shoppers
spend in a grocery store. While this finding is of interest to
retail managers, assessing effects of the emotional component
of music should add to the body of knowledge as well.
Happy and sad music
Music is not an objective fact to the average listener. Rather,
music is defined in terms of the meaning assigned by the
listener (Herrington and Capella, 1994). In addition to
cognitive characteristics and structural characteristics (e.g.
tempo, volume), music can be interpreted in emotional terms,
i.e. “the affective component,” as well (Agmon, 1990). One of
the most fundamental dimensions of a musical composition is
its emotional tone; some songs may be rated as “happy” while
other songs may be considered “sad” (Bruner, 1990). More specifically, Sparshott (1994, p. 27) states that “the
affective quality of music is such that if a competent hearer is
asked to apply to it one of two contrasted mood words or
feeling words (e.g., sad rather than gay), the hearer will easily
be able to comply and the responses of hearers tend to be
significantly in agreement. Some musical pieces are typically
and properly heard as actually having the quality of a named
emotion (actually being mournful), in the sense that the name
of the emotion in question will in suitable circumstances be
not merely accepted, but volunteered as truly descriptive of
it.” Music then, through its various elements, can arouse and
express feelings such as happiness or sadness. In addition, it is
possible for listeners to identify a feeling associated with a
particular musical piece in a consistent manner. Thus, one
should be able to test the effect of the affective (happy/sad)
component of music. In their review of previous literature, Herrington and
Capella (1994) report being unable to find any known tests of
the relationship between retail patronage and the affective
component of music. However, researchers have investigated
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
60
the affective component of music in several other marketing
contexts. Gardner (1985) proposed that in theory, positively valenced
(happy) music should lead to positive moods which should
encourage positive evaluations and behaviors. In a field
experiment involving music in retail stores, Yalch and
Spangenberg (1993) found that store perceptions, at least in
part, were explained by music effects, although they examined
only music type effects, not happy/sad effects of music.
Shoppers perceived a store’s departments to have more
desirable characteristics, and purchased more, when certain
types of music were played. These findings support the view
that music may influence individuals’ shopping behaviors, or
their shopping intentions. In a study investigating the effect of happy/sad music on
purchase intentions in an advertising context, Alpert and
Alpert (1990) did not find support for Gardner’s (1985)
proposed relationship. Their results, generated in a study
using greeting cards paired with both happy and sad music,
suggest that sad music produced higher purchase intentions
than happy music did. Cards did not differ in overall purchase
intent. However, the background music used did make a
statistically significant difference. Multiple comparison results
showed that the cards appearing with sad music were
significantly more likely to be selected for purchase than
those appearing with happy music. One explanation offered by Alpert and Alpert (1990) for
their results is that the sad music they used may have been
more congruent with the stimulus greeting card than their
happy music was. Alternatively, Kellaris and Kent (1994)
suggested that the happy music used by Alpert and Alpert
(1990) may simply have been more distracting than the sad
music and that speed (tempo) be held constant in future
research. Although Baker et al. (1992) found a statistically significant
interaction between ambient and social factors in a retail
setting, the affective (happy/sad) component of the musical
selections they chose was not examined. Therefore a study is
needed which isolates the effects of an ambient factor, music,
and allows tests of the main effect(s) of specific music
characteristics. To that end, Baker et al. (1992) suggested that retailers
interested in the music component of the ambient factor
should explore aspects such as loudness, tempo, or
respondents’ liking/disliking of specific music selections.
This study, then, tests the impact of one aspect of music
related to retail store environments, the affective component,
upon individuals’ intentions to shop in a store. In addition,
the mediating effect of whether happy or sad musical
selections are liked or disliked is investigated. Based upon the mixed happy/sad music results discussed,
and the call for investigations exploring the liked/disliked
dimension of music in service environments, three hypotheses
are proposed. The first hypothesis involves the affective
component of music.
H1. Subjects who judge the stimulus music as happy
should have greater intentions to shop in the stimulus
store than subjects who judge the stimulus music to be
sad.
Liked/disliked music
Areni and Kim (1993), in an investigation of different types of
background music, found that customers selected more
expensive merchandise when classical music, as opposed to
top-forty music, was played in the background in a wine store.
These authors, based upon MacInnis and Park’s (1991)
results, concluded that music “fit” in a persuasion context
accounted for this result. While a part of music “fit” may be
customers’ liking for music played, Areni and Kim (1993) did
not directly measure the construct of liking for the particular
musical selections they used. Shen and Chen (2006) also
reported music congruence effects in a cross-cultural
advertising study but neither liking nor happy/sad elements
of the music were investigated. Thorgaard et al. (2005) investigated the “pleasant/
unpleasant” effects of music in Denmark postanaesthesia
care unit service settings and found a significant positive
correlation among patients between pleasant music and
satisfaction with stay. In advertising contexts, Gorn (1982)
reported that listening to liked music enhanced brand
preference relative to listening to disliked music while Blair
and Shimp (1992) concluded that association with disliked
music led to negative attitudes toward a brand. While Yalch and Spangenberg (1990) did not support the
notion that liked music is necessarily the most appropriate
music to use in all situations, North and Hargreaves (1996)
reported that liking for music played in a quasi-retail
experimental setting was positively correlated with how
happy subjects would be to return to an environment,
supporting the notion that liked music may attract people to
an environment. In a study of music arousal (tempo) effects,
Mattila and Wirtz (2001) found that desirable music choices
influence intentions to shop in a particular store. Therefore,
shopping intentions regarding a retail store environment and
liked/disliked music should be related in the following
manner.
H2. Shopping intentions will be greater when subjects are
exposed to liked music.
Bruner (1990) suggests that any musical composition consists
of at least three primary dimensions: a physical dimension
(volume, pitch, tempo, rhythm), an emotional tone, and a
preferential dimension (the degree to which a shopper likes
the music). There may well be a compounding effect of these
dimensions. Based on the review of literature, it appears that
playing happy or sad music which subjects like will enhance
shopping intentions while playing sad music that subjects
dislike will curtail individuals’ shopping intentions. The
following hypothesis was generated to test whether liking or
disliking for music mediates the effects of the emotional
component (happy or sad perceptions) of music.
H3. Music that is both happy and liked will be associated
with the greatest intentions to shop in the stimulus
store.
Methodology
Overview
Subjects viewed a videotape of an unfamiliar retail store for
this study and were asked to describe their image of the store
aloud as they viewed the tape. As an image of the stimulus
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
61
store was formed, each subject was exposed to one of the
different music treatments discussed later. Since individuals may respond to music differently, Aylott
and Mitchell (1998) suggest that research regarding music
should be conducted with relatively homogeneous market
segments. Retail stores with such narrow target markets might
reap higher benefits from environmental manipulation than
stores aimed at multiple market segments (Turley and
Milliman, 2000). The target market for this limited line
fashion clothing store was described as females aged 15-34.
The store manager stated that the majority of her frequent
shoppers are between the ages of 18 and 24. The 126 subjects
included in this study closely fit these target ages, as shown in
Table I.
Stimulus
The stimulus used in this study was a videotape of a typical
store visit to one of a small chain of 26 stores in Southern
California. Baker et al. (1992) found videotaped stimuli to be a realistic method for examining the impact of store
environmental situations on consumers while Dube et al. (1995) utilized a video simulation of a bank service
environment. The use of a videotaped stimulus has several
advantages to researchers when compared to conducting field
experiments in stores. These advantages include the ability to
control for the effects of salespeople, crowding, time of day,
and changes in displays; all of which could influence people’s
shopping intentions or behaviors. Holding these variables
constant provides a degree of exacting control that would be
extremely difficult to achieve in a field setting. Therefore, this
methodology was deemed desirable for this investigation. An unknown store was deemed necessary to help insure
that subjects knew nothing about the stimulus store except the
information to which they were exposed in the experimental
setting. This complete lack of familiarity should eliminate
possible confounds noted by Donovan et al. (1994), whereby those familiar with a store may have experienced pre-
conditioned approach or avoidance responses to a store’s
atmosphere. The taping session was done before the store opened so that
few, if any, people would appear in the videotape. Any
salespeople who inadvertently appeared were deleted through
the editing process described later. It was feared that
including people in the stimulus tape might introduce a
confound into the study. Approximately one hour’s worth of videotape was shot in
the store and the tape was then edited by a professional
videographer for the visual content. A common store path had
been determined for the store by observing customers on days
prior to the taping, so the tape represented a “typical” store
visit. Displays and other store aspects which seemed to have
stopping power, were kept in frame for relatively long periods
of time. The tape was edited to be about five minutes in
length, as it was felt that a longer tape would become tiresome to subjects. The tape was then pretested to see if subjects could
recognize it as something “new”. All pretest subjects, most of whom were from the Midwest, were able to identify the store as a store that they had not been in, or even heard of. In a 1992 study involving retail store environments, Baker
et al., 1992, measured intentions to behave rather than actual behavior, as did Donovan and Rossiter (1982). These authors all considered intentions to buy to be a suitable proxy for approach behavior. Similarly, shopping intention was the dependent variable in this study.
Treatments
Happy and sad musical selections with varying degrees of liking were used as independent variables. Pretests were conducted to find happy and sad musical selections that were both liked and disliked by some subjects and which met the following tempo (beats per minute) conditions. Milliman (1982) found a range of 22 bpm between subjects’
perceptions of fast/slow music, therefore the bpms of all music chosen for this study were within a 22 bpm range so that no songs would be perceived as faster or slower than others. Since Kellaris and Kent (1991) found that subjects tend to prefer tempos that fall within a range of 68-178bpm, no songs whose bpms fell outside these parameters were used. Volume was also held constant for each song in order to eliminate this potential confounding variable. The chosen songs were then dubbed onto videotapes of the
stimulus store by a professional tape editor. Songs were typically less than five minutes in length so portions of them were repeated. No song was repeated more than approximately one and a half times on any tape. These were the treatments that subjects were exposed to in this research. Each subject was exposed to only one, randomly-selected musical treatment.
Data collection
Data were collected in individual sessions in a laboratory setting, in which a television with the videotape player connected was set up in a private room. As individuals viewed the stimulus, they were asked to speak their thoughts aloud. After viewing the tape, respondents were asked several questions regarding the music and their intentions to shop in the store. Music was not mentioned prior to, or during, the viewing of the videotape by the researcher. Since subjects would be speaking their thoughts aloud, it was believed that individual interviews were best suited to the collection of data for this study. Each respondent took approximately fifteen minutes to complete the tasks.
Measures Happy/sad music Immediately after viewing the tape, subjects provided their ratings of the degree of happy/sad music for the music perception measure by completing one seven-point bipolar item with “very happy” and “very sad” as the end points. Each subject was exposed to only one music treatment. For data analysis, very happy music was coded as 7, while very sad music was coded as 1.
Liked/disliked music Similarly to a procedure used by North and Hargreaves (1996), the numbers of positive, neutral, and negative music
Table I Subjects’ ages
Ages Frequency %
15-17 30 24
18-24 73 58
25-34 23 18
Total 126 100
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
62
comments (complaints) were counted after subjects completed their individual sessions and subjects’ like/dislike for musical selections was inferred by these comment types. Utilizing music comments made during the quasi-store “visit,” as opposed to asking about music only after subjects leave an experimental setting adds value to this study in several ways. One, reliance on subjects’ recall, which may be flawed, is not an issue, and two, subjects received no prompting from researchers to discuss music. Thus, this method provides a relatively stringent test of music’s impact upon subjects. Those subjects who made negative comments were
considered as disliking the music while those who made positive comments regarding the music they heard were considered as liking the music. No subjects made both positive and negative comments about the music to which they were exposed. Those who made neutral music comments only or who did not comment on the music were considered to be neutral regarding the music. Table II shows several typical examples of each comment type. The “liked music” group was coded as 3, the “neutral
music” group was coded as 2, and the “disliked music” group was coded as 1. Both complaints and positive music comments constitute particularly strong responses to the music since much attention was being paid to the visual stimulus.
H3 involved the combination of happy/sad music with liked/ disliked music. Data to test this hypothesis were generated using both the happy/sad measure and the procedure for measuring liking/disliking for the music described above.
Shopping intentions
Shopping intentions were measured with a seven-point bipolar item using “definitely would shop in this store” and “definitely would not shop in this store” as end points. “If the construct being measured is sufficiently narrow or is unambiguous to the respondent, a single item measurement may suffice” (Sackett and Larson, 1990; Wanous and Reichers, 1996). Pretest respondents reported this shopping intention item to be easily understood and clear to them and no subjects questioned this item during the experiment itself. Some subjects even elaborated upon this item with emphatic statements, always in support of the direction of their written responses. Responses to this item were coded as 7 ¼ definitely would shop and 1 ¼ definitely would not shop.
Results
The direct effect of happy/sad music on shopping intentions, the direct effect of liked/disliked music on shopping intentions, and the effect of happy/sad music on shopping
intentions mediated by individuals’ liking/disliking for the
music were assessed using LISREL 8.3 (Jöreskog and
Sörbom, 2000) in a manner similar to Borucki and Burke’s
(1999) and Bryman and Cramer’s (1990) single-item measure
analyses. The model shown in Figure 1 was used to test the
hypotheses. Table III shows the total effects, direct effects, and indirect
effects of hearing happy/sad music on subjects’ shopping
intentions. Table IV shows the total effects, direct effects, and
indirect effects of hearing liked/disliked music on subjects’
shopping intentions. These results show that happy/sad music has a significant
direct effect on shopping intentions (p ¼ 0:000), while the direct effect of liked/disliked music was marginally significant
(p ¼ 0:057). The indirect effect of happy/sad music was marginally significant at the 0.05 level (p ¼ 0:067). Happy/sad music also had a relatively small, but significant, direct effect
on like/dislike for the music (p ¼ 0:001), indicating that most, but not all subjects liked the happy music more than the sad
music. Thus, whether music was happy or sad did influence
people’s liking for the music. Perhaps even more intriguing than the direct effect of
happy/sad music on shopping intentions is the test of the
mediating effect of being exposed to liked or disliked happy/
sad music. While playing happy music significantly increased
subjects’ intentions to shop in the stimulus store, shopping
intentions were greatest when the music was liked as well. The
combination of happy music that is liked by a store’s target
market is more powerful than either happy music or liked
Table II Examples of comment types
Positive I like the music
This music makes me feel like shopping
Like spending money
All right, they’re playing my music Negative That music is irritating
That music is depressing
Neutral They’re playing music
They have music on
Figure 1
Table IV Effects of liked/disliked music on shopping intentions
Direct Indirect Total
Effects 0.449 0.449
p ¼ 0:057 p ¼ 0:057
Table III Effects of happy/sad music perceptions on shopping intentions
Direct Indirect Total
Effects 0.303 0.067 0.370
p ¼ 0:000 p ¼ 0:065 p ¼ 0:000
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
63
music alone. Perhaps some marketers treat music as a
relatively simple construct when, as demonstrated by these
results, careful consideration of the interaction of music’s dimensions may yield the greatest positive effects on
customers’ behaviors.
Discussion
Happy/sad music and shopping intentions
While a number of investigations of various properties of
music and their effects on shoppers in retail service environments have been reported, little research has been
conducted regarding the effects of the affective, or happy/sad,
component of music in these settings. This study demonstrates that this component of music can significantly
effect intended shopping behaviors. In addition, clear implications for retail managers regarding happy/sad and
liked/disliked music are evident. H1 is supported. Subjects’ intentions to shop in the
stimulus store were higher if they were exposed to music they
perceived to be happy. Although this finding runs counter to some results from the Advertising literature, it does support
results reported in most literatures. Based upon these results,
retailers would see greater intentions to shop, or perhaps to return, if music perceived as happy was played in their stores.
Liked/disliked music and shopping intentions
H2 is supported. The result of the effect of liked/disliked music on shopping intentions, although only marginally significant, is noteworthy. Similar to findings reported by
Mattila and Wirtz (2001) in their investigation of high and low arousal music, desirable music choice influences
intentions to shop in a particular retail environment. Playing
liked music produced the largest direct effect on subjects’ likelihood of shopping in the stimulus store. As like/dislike for
music is assessed in more types of service settings with differing target markets, it is becoming apparent that retail
managers must insure that they are playing music that their
target markets like in their stores.
Effects of happy/sad music mediated by like or dislike
Perhaps more importantly regarding the happy/sad dimension
of music, shopping intentions were highest when subjects
heard happy music that they liked, thus providing support for hypothesis three. The managerial implication of this result is
that while playing either happy music or liked music alone should increase shopping in stores, retailers should take care
to play happy music that is liked by their target markets in
order to achieve the greatest positive effect of music on patronage behavior toward retail service environments. It should not be difficult for retail managers to identify
music that is perceived to be both happy and that is liked,
particularly if music tempo is not controlled. Pretest respondents were easily able to classify music as happy or
sad and subjects who took part in the experiment were quite
vocal regarding their like or dislike of the music to which they were exposed. While some may say that many store retailers
are already playing appropriate musical selections, it must be noted that since not all subjects in this study liked the happy
music or disliked the sad music; “liked” and “happy” are not
necessarily synonymous. Focus groups consisting of actual and/or potential customers may be appropriate. Controlling
these characteristics of musical selections appears to be
relatively simple for retail service providers and should result
in increased number of store visits.
Limitations
A first limitation regards controlling the tempo of the music in
this study. With tempo held relatively constant, some of the
emotional impact of music may have been lost. Typically, sad
music would be associated with slower tempos while happy
music would be more “upbeat.” The affective music effects
found in this study must be very strong to overcome this likely
loss of emotional impact. A second limitation is that this study utilized only one
service setting, a women’s fashion apparel store. Although the
music preference results reported here support Herrington
and Capella’s (1996) results from a study conducted in a
grocery store setting, music effects in other retail
environments may differ. Those researchers did not
investigate effects of happy/sad music. Third, only female subjects within a relatively narrow age
range were involved in this study. In an investigation of the
role of gender in preference for music, McCowan et al. (1997) found significant gender differences. Therefore, it may be that
males like/dislike different music than females. Based upon
the two previous limitations, caution must be exercised in
attempting to generalize these results to other service settings
and samples until more investigations are completed. Finally, it should be noted that data were collected in 1992.
However, the authors believe that music’s effect on shopping
intentions is a relatively time-insensitive topic. The disparate
times that various studies cited in this paper were conducted,
and are cited in the literature, support the contention that
these effects should be relatively stable over time. The
literature review did not reveal any evidence to contradict this
assertion.
Future research
Research is needed in a variety of retail service settings with
different target markets to determine the generalizability of
these results and studies are needed where tempo is not
controlled to measure the full effect of happy/sad music
dimensions. Additional research is also needed in a retail store
context to discover if shoppers are conscious of lyrics, tempo,
or both when exposed to retail store settings in attempts to
assess what makes music “liked” in retail store environments. More research in which actual behavior is related to
intentions in further explorations of the apparent effects of
happy/liked music should also be helpful to retailers and other
service providers. Future research might also consider the situational
characteristics of the consumer as well as environmental
variables. More specifically, Mick and DeMoss (1990) noted
that consumers may be likely to purchase more when they are
very happy (purchasing as a reward) or very sad (purchasing
for therapeutic reasons). Thus it may be that there is
congruence between the individual’s mood and the type of
music that is the most effective. Kaltcheva and Weitz (2006) report a link between
consumers’ motivational orientations and the pleasantness
of a store environment. Music may, at least in part, impact
this pleasantness dimension. Therefore, research investigating
the correspondence of music and consumers’ motivational
orientations may be of value.
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
64
Conclusions and recommendations
Although the happy/sad music results of this study are
inconsistent with Alpert and Alperts (1990) investigation
using greeting cards, the significant direct and indirect effects
that happy/sad music had on shopping intentions support the
notion that researchers and retailers need to concern
themselves with this aspect of music perception specifically.
According to subjects, this music element does influence their
retail patronage intentions. In addition, a number of subjects
who mentioned music attributed particular affective words
such as “depressing” to the music while some even described
how the music made them feel regarding their experimental
“shopping” experiences. Increased knowledge about the
effects of the affective component of music is clearly desirable. This examination of liking/disliking for the music supports
North and Hargreaves’ (1996) results and expands them.
North and Hargreaves (1996) reported that individuals are
more likely to return to an environment when music they like
is played. This study, in addition, suggests that consumers are
more likely to visit new service environments that play music
they like. Indeed, retail advertisers should be able to use this
information to design more appealing advertisements when
attempting to attract new shoppers to their stores. Retail managers need to make informed music choices
involving their store types and target markets. Herrington and
Capella (1994, p. 52) presented the following question and
answer, “How can background music help customers to fulfill
purchase needs? By playing the right type of music!” The
results of this study indicate that happy music that is liked by
the target market is the “right” music and can significantly
increase intentions to shop in a retail service environment. Therefore, it is important that retail managers know the
music that their target market likes and play happy selections
in that genre or by those liked artists. An example would be
Gwen Stefani’s “Haul a Back” song that was on a recent play
list at a local retailer with a target market similar to that of the
experimental store’s in this study. Liking for artists and songs
may be something that changes frequently so managers of
service environments should also establish specific points
during selling seasons when they consider adding new musical
selections and deleting others. Conducting focus groups of
customers or convening customer panels would allow
managers to determine the appropriateness of their musical
selections.
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Journal of Services Marketing
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Corresponding author
Greg Broekemier can be contacted at: [email protected]
Executive summary and implications for managers
This summary has been provided to allow managers and executives a rapid appreciation of the content of the article. Those with a particular interest in the topic covered may then read the article in toto to take advantage of the more comprehensive description of the research undertaken and its results to get the full benefit of the material present.
Come next Christmas and you cannot guarantee snow on the
ground, or getting the gifts you want. What you can bank on is that shops are likely to bombard you with carols and seasonal songs. Pop star Roy Wood and his band Wizard will,
no doubt, be in the mix with: “Well I wish it could be Christmas, every day. When the kids start singing and the
band begins to play.” Thank goodness it is not Christmas every day, will be the
reaction of some customers who feel irritated to despair, or shop somewhere else, just because the store owners think the
choice of music will cheer everyone up and put them in a spending mood. It does not always work like that, and retail managers need to
try to find out what is best for them. Christmas may be a special
case, with the overplaying of even well-liked songs driving people to distraction. But for the rest of the year, what is played to put shoppers in the right mood for buying needs careful
choice as it is not as simple as just saying cheery, upbeatmusic is best. Additionally, what is right for a store selling clothing to
teens and twentysomethings will be different from that in an establishment catering for an older generation who like their
musical entertainment in gentler, quieter mode. It is understandable why stores like music. It is relatively
cheap to provide, change and control. Shoppers themselves acknowledged music’s importance for atmosphere. In a Gallup
poll 91 per cent of retail customers surveyed said music had an effect on their shopping behavior, 86 per cent that music added to the atmosphere of a store, while music influenced the
purchase decisions of 33 per cent of respondents. However, Greg Broekemier et al. note there is still much to
be learned about the effects of music in various marketing
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
66
settings. Their study on effects of happy/sad and liked/disliked music in women’s clothing stores, support the view that people who judge the stimulus music as happy have greater intentions to shop in the store than those who judge it to be sad; and shopping intentions are greater when people are exposed to music they like. Happy/sad music has a significant direct effect on shopping
intentions while the direct effect of liked/disliked music was marginally significant. The indirect effect of happy/sad music was marginally significant. Happy/sad music also had a relatively small, but significant, direct effect on like/dislike for the music, indicating that most, but not all subjects liked the happy music more than the sad music. Thus, whether music was happy or sad did influence people’s liking for the music. Perhaps even more intriguing than the direct effect of happy/ sad music on shopping intentions was the test of the mediating effect of being exposed to liked or disliked happy/ sad music. While playing happy music significantly increased subjects’ intentions to shop in the stimulus store, shopping intentions were greatest when the music was liked as well. The combination of happy music that is liked by a store’s target market is more powerful than either happy music or liked music alone. Perhaps some marketers treat music as a relatively simple
construct when, as demonstrated by these results, careful consideration of the interaction of music’s dimensions may yield the greatest positive effects on customers’ behaviors. According to subjects, this music element does influence
their retail patronage intentions. Increased knowledge about
the effects of the affective component of music is clearly desirable. This study supports previous research reporting that people
are more likely to return to an environment when music they like is played. In addition, it suggests that consumers are more likely to visit new service environments that play music they like. Indeed, retail advertisers should be able to use this information to design more appealing advertisements when attempting to attract new shoppers to their stores. Retail managers need to make informed music choices
involving their store types and target markets. The results of this study indicate that happy music that is liked by the target market is the “right” music and can significantly increase intentions to shop in a retail service environment. Therefore, it is important that retail managers know the music that their target market likes and play happy selections in that genre or by those liked artists. They should also be aware that liking for artists and songs
may be something that changes frequently so managers should also establish specific points during selling seasons when they consider adding new musical selections and deleting others. Conducting focus groups of customers or convening customer panels would allow managers to determine the appropriateness of their musical selections.
(A précis of the article “An exploration of happy/sad and liked/ disliked music effects on shopping intentions in a women’s clothing store service setting”. Supplied by Marketing Consultants for Emerald.)
An exploration of happy/sad and liked/disliked music effects
Greg Broekemier, Ray Marquardt and James W. Gentry
Journal of Services Marketing
Volume 22 · Number 1 · 2008 · 59–67
67
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