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

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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

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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

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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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