Consumers’ Cognitive, Emotional and Behavioral Responses towards

Background Music: An EEG Study

Athanasios Gkaintatzis

, Rob van der Lubbe

, Kalipso Karantinou

and Efthymios Constantinides

Department of Marketing and Communication, Athens University of Economics and Business,

Patision Street 76, Athens, Greece

Faculty of Behavioural, Management and Social Sciences (BMS), University of Twente,

Drienerlolaan 5, Enschede, Netherlands

Keywords: Neuromarketing, Electroencephalogram (EEG), Consumer Behavior.

Abstract: The physical environment affects individuals emotionally, behaviorally and cognitively. Servicescapes or

atmospherics studies the effect of environmental stimulation to consumers. Environmental stimuli affect

consumers’ attention and cause them emotions such as pleasure and arousal; those emotional responses

affect in turn consumers’ behavioral responses such us approach and avoidance tendencies towards the

environment. Hence, the level of arousal-nonarousal and the pleasure-displeasure experienced by a

consumer along with other intervening variables such as momentary mood and stimulus screening ability

will determine his/her approach-avoidance responses towards the environmental stimuli. The paper studies

atmospherics with neuromarketing and conventional marketing research methods: Specifically, using

electroencephalography (EEG) and surveys, it focuses on the effect of background music on Consumer’s

arousal, pleasure, attention and approach/avoidance tendencies. The results are expected to have significant

academic relevance both for the servicescapes / atmospherics and the neuromarketing / consumer

neuroscience research streams of literature and also managerial implications.

1 INTRODUCTION

This paper investigates atmospherics with

neuromarketing methods. Servicescapes or

atmospherics is a subfield of marketing which

applies environmental psychology to marketing

research in studying the effects of the environment

to consumers within it (Kotler, 1973; Bitner, 1992).

Neuromarketing or Consumer Neuroscience applies

neuroscience to marketing research and studies

consumers’ emotional, behavioral and cognitive

responses (Turley and Milliman, 2000; Mattila and

Wirtz, 2001).

2 LITERATURE REVIEW

Music has long been considered an efficient and

effective means for triggering moods and

communicating nonverbally (Bruner, 1990). It is

capable of evoking complex and affective behavioral

responses in consumers. Specifically, music affects

consumer behavior in retail environments (Milliman,

1982, Milliman, 1986; Yalch and Spangenberg,

1990) and influences their desire to affiliate in

buyer-seller interactions (Dube´, Chebat and Morin,

1995). Appropriately structured music acts on the

nervous system as a key on a lock, activating the

brain with corresponding emotional reactions

(Clynes and Netheim, 1982) and also plays an

important role among higher brain functions

(Bhattacharya, Petsche and Pereda, 2001). It is

therefore not surprising that music has become a

major subject of consumer research, both at the point

of purchase and in advertising (Bruner, 1990).

Previous research has been focused on specific

elements of music such as volume, pitch, tempo, and

rhythm are manipulated. Regarding tempo, Bruner

(1990) argues that slow tempo music reduces

anxiety, whereas faster tempo music is associated

with increased worry and emotionality. In this

respect, faster tempo music was associated with

positive affective states such as happiness and

excitement, whereas slow tempo music was

associated with feelings of sadness (Bruner, 1990).

Milliman proposed that consumers spent more time

and money in environments with slow-tempo music

314

Gkaintatzis, A., van der Lubbe, R., Karantinou, K. and Constantinides, E.

Consumers’ Cognitive, Emotional and Behavioral Responses towards Background Music: An EEG Study.

DOI: 10.5220/0008346603140318

In Proceedings of the 15th International Conference on Web Information Systems and Technologies (WEBIST 2019), pages 314-318

ISBN: 978-989-758-386-5

and took more time to eat their meals compared to

those in the fast-music condition (Milliman, 1982;

Milliman, 1986). Following Milliman, Vanderark

and Ely (1993) reported that high tempo and high

rhythmic content in the music led to an increase in

physiological arousal among consumers (Mattila and

Wirtz, 2001). Dube´ et al., (1995) proposed that

music-induced pleasure and arousal might have

independent effects on consumers’ desire to affiliate

in a buyer-seller interaction, with more desire to

affiliate associated with more pleasure and more

arousal. Even though there is ample extant research

on the effect of music on consumer behavior, there

are still many conflicting findings and inconclusive

results, posing an academic and managerial

challenge. Furthermore, music has been extensively

studied in the marketing literature using traditional

research methods. Little is however known about the

mental processes that underpin certain consumer

behaviors and the buying process. We aim to redress

such shortcoming by employing neuromarketing

methods that have the capacity to yield more precise

and objective results. In this study we will

investigate the effects of background music on

consumer behavior using a tool from the

Neuroscience domain namely

Electroencephalography (EEG) in combination with

classic questionnaires.

3 EXPERIMENTAL DESIGN

On the basis of the above mentioned approach, the

purpose of this study is to manipulate the tempo and

specifically the Beats Per Minute (BPM) of music

while keeping all the other elements of music

unchanged during the consumer decision-making

process, and examine how the consumer behavior is

affected. By manipulating BPM, different

servicescapes or to be more precise musicscapes,

can be created. Musicscapes display significant

relationships between specific musical variables and

desired consumer behavioral outcomes (Oakes,

2000). According to the literature, 80 or lower BPM

is considered as slow tempo musicscape, between 80

and 120 is considered as moderate and 120 or more

is considered as fast tempo musicscpae (Milliman,

1986; Kellaris and Kent, 1993; Bruner, 1990;

Edworthy and Waring, 2006). In this experiment,

there will be three different such conditions: a 70

BPM, a 120 BPM and a 170 BPM condition. Non-

vocal music is chosen, because we want to focus on

the effect of music on consumer behavior; not on the

effect of linguistics. Specifically, a violin piece is

chosen, because it can reach high BPM without

producing noise in the ears of the listener and it is

also coherent with the product selecting task; the

product in question is bolted wine.

Participants will be asked to perform a task while

being exposed to the three different musicscapes

conditions in random order. They will have to make

a binary choice between bottles of wine, one

presented in the right side of the computer screen

and one presented in the left. The side that each

bottle will be presented will be random. This task is

chosen, because we want to replicate a hedonic

servicescape. Hedonic services are those that

provide consumers with values such as excitement,

playfulness and entertainment and according to the

literature, arousal has a bigger effect on pleasure and

satisfaction in hedonic servicescapes than in

utilitarian servicescapes (Babin, Darden and Griffin,

1994).

Great effort will be made to keep all other

conditions such as temperature, air quality, humidity

and cleanliness constant and similar for all

participants. A pretest will also be conducted to

adjust the volume of the music. In addition,

feedback from the pretest sample is expected to help

with the wording of the questions and the

questionnaire layout.

4 METHODS

4.1 Electroencephalography (EEG)

Electroencephalography (EEG) is a non-invasive

medical imaging technique that records the

extracellular electrical activity of the brain,

generated by the action potentials of neurons

(Abhang, Gawali, and Mehrotra, 2016; Alix,

Ponnusamy, Pilling and Hart, 2017) and it is a

widely used method in consumer neuroscience. EEG

is chosen as a research method, because it has

advantages such high-tempoal resolution (Abhang et

al., 2016; Cohen, 2014; Michel and Murray, 2012;

Ramsøy, 2014), and can capture fast, dynamic, time

sequenced cognitive events (Cohen, 2014); next to

that is a relatively low-cost neuromarketing

technique. Furthermore, EEG is capable of

measuring visual attention, which is one of the main

purposes of this study.

In order the EEG measurements to be done, two

computers will be used: one for presentation and one

for recording, both of them connected with the

BrainVision ActiPower Amplifier. BrainVision

Recorder and BrainVision Analyzer will be used in

Consumers’ Cognitive, Emotional and Behavioral Responses towards Background Music: An EEG Study

315

order to collect the data and analyze them.

Participants will be sited in a comfortable chair 60

cm away from the presentation computer. The EEG

will be recorded continuously from 32 active

Ag/AgCl electrode sites: AFz, AF3, AF4, AF7, AF8,

F1, F2, F5, F6, FCz, FC3, FC4, FT7, FT8, C3, C4,

C5, C6, CPz, CP3, CP4, TP7, TP8, P1, P2, P5, P6,

POz, PO3, PO4, PO7, and PO8 using an EasyCap-

62 channel cap with standard international 10–20

system layout. The occulograms (EOG) will be also

recorded continuously from 5 electrodes attached

around the eyes of the participants.

Regarding the EEG analysis, special focus will be

paid to the Posterior-Contralateral Negativity (PCN),

which is an Event-Related-Potential (ERP) and an

Event-Related-Lateralization (ERL) measure.

Evoked potentials (EPs) and event-related potentials

(ERPs) are components of the EEG that arise in

response to diﬀerent kinds of stimuli, such as

auditory, gustatory, olfactory, somatosensory and

visual input (Ramsøy, 2014). ERPs can be

transformed into ERLs by calculating the contra-

ipsilated hemispherical difference for the relevant

electrodes (Van der Lubbe and Utzerath, 2013).

Parameters of the Posterior-Contralateral Negativity

(PCN), also known as the N2-posterior contralateral

(N2pc), will be analyzed in order to assess if a

certain bottle of wine caught participants’ visual

attention. The PCN expresses an increased

negativity in the visual area (posterior electrodes)

contralateral to the stimulus position in a time

window of approximately 175 and 300 ms (or even

less) after the stimulus presentation (Tollner, Muller

and Zehetleitner, 2011a; Tollner, Zehetleitner,

Gramann, and Muller, 2011b; Vossel, Geng and

Friston, 2015). The PCN measurement can be used

to indicate visual attention (Van der Lubbe,

Jaśkowski, Wauschkuhn, & Verleger, 2001).

Based on the assumption that PCN reflects the visual

allocation of attention based on perceptual stimulus

properties; the present study aims at showing that

PCN parameters can be used to assess and predict

consumers’ preferences for a specific product on the

base of external cues, in the case at hand different

bottles of wine. It is expected that individual visual

attention for a specific wine label are reflected by

EEG lateralization in the parieto-occipital area

(PO8/PO7 electrode pair. Therefore, it is

hypothesized that:

H1: A negative-going deflection (PCN) is indicative

of participants’ preferences for a bottle of wine.

Falkenstein, Hohnsbein and Hoormann (1994)

examined the influence of time pressure in a choice-

reaction task with visual and auditory stimuli in

which time pressure was manipulated. They focused

on the ERP component P3 latency, which reflects

processes involved in decision making and stimulus

evaluation. In this study pressure to the participants

will be induced by manipulating music’s BPM. It is

expected that an increase in BPM of music will lead

to an increase in participants’ reported stress and a

decrease in time needed to finish the task. Therefore,

it is hypothesized that:

H2: P3 latency is also expected to be affected by

time pressure.

The balance between activity in the left and right

frontal cortex, commonly referred to as asymmetric

frontal cortical activity, has served as a proxy for an

organism's motivational direction (i.e., approach vs.

avoidance) (Kelley, Hortensius, Schutter, Harmon-

Jones, 2017). According to the literature, greater

relative left (right) frontal cortical activity is

associated with approach (avoidance) motivation.

H3: Greater relative left frontal cortical activity is

associated with approach tendency of the participant

towards the medium tempo music. Greater relative

right frontal cortical activity is associated with

avoidance tendency of the participant towards the

extreme fast or extreme slow music.

4.2 Survey

After each music condition, participants will have to

answer a survey in order to measure their emotional

responses: pleasure and arousal (with 7 items and 7-

point likert scale from Mehrabian and Russel, 1974),

their cognitive responses: attention (with 5 items and

7-point likert scale from Brown and Ryan, 2003) and

satisfaction from background music (with 9 items

and 7-point likert scale from Oliver and Swan,

1989), and their behavioral responses:

approach/avoidance tendencies (8 items, 7-point

likert scale from Donovan and Rossiter, 1982)

It is expected that people prefer moderate arousal

level over extreme high or low when they do a task.

The hypotheses that will be tested is the following:

H4: While making a binary choice, listening to 120

BPM music piece is pleasant, satisfactory and leads

to approach tendency towards the environment.

Extreme fast or extreme slow music is unpleasant,

unsatisfactory and leads to avoidance behavior

towards the environment.

The faster response and more stressful is expected to

be in the 170 BPM music condition and the slower

response and less stressful in the 70 BPM music

condition. Therefore, it is hypothesized that:

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H5: An increase in BPM of music will lead to an

increase in participants’ reported stress and a

decrease in time needed to finish the task.

The faster the music, the more difficult it is expected

to be to complete the task. The last hypothesis will

be that:

H6: While the BPM of music are increasing

participant’s attention is decreasing.

5 DATA PROCESSING AND

EXPECTED RESULTS

Following the hypotheses, attention is expected to

decrease and stress to increase, while BPM of music

are increasing. Arousal and heart rate is expected to

increase while BPM of music are increasing. It is

also expected that moderate arousal level induced

from the 120 BPM violin piece is pleasant and

satisfactory, leading to approach behavior; in

parallel, extreme high and extreme low arousal level

induced from 70 and 170 violin pieces is not

pleasant and satisfactory, leading to avoidance

behavior. In addition, the faster response and more

stressful is expected to be in the 170 BPM music

condition and the slower in the 70 BPM music

condition.

At the end of the study a final conclusion will be

drawn based on the results. The relative advantages

and disadvantages of survey and EEG and their

potential complementarity will be critically

evaluated. Academic and managerial implications

are also expected to come out, enabling better

utilization of music in consumer research and

practice when dealing with customer behavior.

Further research in this domain could be done by

including more neuromarketing techniques such as

Functional Near-Infrared Spectroscopy (fNIRS).

REFERENCES

Abhang, P. A, B. W. Gawali, and S. C. Mehrotra (2016).

Introduction to EEG-and speech-based emotion

recognition. Academic Press.

Alix, J. J. P., A. Ponnusamy, E. Pilling, and A. R. Hart

(2017). “An introduction to neonatal EEG”. In:

Paediatrics and Child Health 27.3, pp. 135–142.

Annett, M. (1970). “A classiﬁcation of hand preference by

association analysis”. In: British Journal of

Psychology 61.(3), pp. 303–321.

Babin BJ, Darden WR, Griffin M. Work and/or fun:

measuring hedonic and utilitarian shopping value. J

Consum Res 1994;20:644–56 [March].

Bach, M. (1996). The Freiburg Visual Acuity

Test???Automatic Measurement of Visual Acuity.

Optometry and Vision Science, 73(1), 49–53.

Baker, J. (1987), The role of the environment in marketing

services: the consumer perspective In J. Czepiel, C. A.

Congram, & J. Shanahan, eds. The Services

Challenge: Integrating for Competitive Advantage.

Chicago: American Marketing Association, pp.79-84.

Bhattacharya, J., Petsche, H., & Pereda, E. (2001). Long-

Range Synchrony in the γ Band: Role in Music

Perception. The Journal of Neuroscience, 21(16),

6329–6337.

Bitner, M.J., "Servicescapes: The Impact of Physical

Surroundings on Customers and Employees," Journal

of Marketing, vol. 56, no. 2, 1992, p. 67

Brown, K.W. & Ryan, R.M. (2003). The benefits of being

present: Mindfulness and its role in psychological

well-being. Journal of Personality and Social

Psychology, 84, 822-848.

Bruner, G. C. (1990). Music, mood, and marketing.

Journal of Marketing, 54(4), 94-104.

Clynes M., Nettheim N. (1982) The Living Quality of

Music. In: Clynes M. (eds) Music, Mind, and Brain.

Springer, Boston, MA

Cohen,M.X.(2014).Analyzingneuraltimeseriesdata:theorya

ndpractice. MIT Press.

Donovan, Robert and John Rossiter (1982), "Store

Atmosphere: An Environmental Psychology

Approach," Journal of Retailing, 58 (Spring), 34-57.

Dubé, L., Chebat, J.-C., & Morin, S. (1995). The effects of

background music on consumers’ desire to affiliate in

buyer-seller interactions. Psychology and Marketing,

12(4), 305–319.

Edworthy, J., & Waring, H. (2006). The effects of music

tempo and loudness level on treadmill exercise.

Ergonomics, 49(15), 1597–1610.

Falkenstein, M., Hohnsbein, J., & Hoormann, J. (1994).

Time pressure effects on late components of the event-

related potential (ERP). Journal of Psychophysiology,

8, 22–Fisher, J. D. (1974). Situation-specific variables

as determinants of perceived environmental aesthetic

quality and perceived crowdedness. Journal of

Research in Personality, 8(2), 177–188.

Kaplan, Stephen (1987), "Aesthetics, Affect, and

Cognition," Environment and Behavior, 19 (January),

3-32.

Kellaris, J. J., & Kent, R. J. (1993). An exploratory

investigation of responses elicited by music varying in

tempo, tonality, and texture. Journal of Consumer

Psychology, 2(4), 381–401.

Kelley NJ, Hortensius R, Schutter DJ, Harmon-Jones E.

(2017). The relationship of approach/avoidance

motivation and asymmetric frontal cortical activity: A

review of studies manipulating frontal asymmetry.

International Journal of Psychophysiology : Official

Journal of the International Organization of

Psychophysiology.

Kotler, P. (1973). Atmospherics as a marketing tool.

Journal of Retailing 49(4), 48-64

Consumers’ Cognitive, Emotional and Behavioral Responses towards Background Music: An EEG Study

317

Mari & Poggesi (2013) Servicescape cues and

customer behavior: a systematic literature review

and research agenda, The Service Industries

Journal, 33:2, 171-199.

Lin, I.Y. (2010), “The interactive of Gestalt situations and

arousal seeking tendency on customers’ emotional

responses: Matching color and music to specific

servicescapes”, Journal of Services Marketing, Vol. 24

No. 4, pp. 294-304.

Mari, M., & Poggesi, S. (2013). Servicescape cues and

customer behavior: a systematic literature review and

research agenda. The Service Industries Journal, 33(2),

171–199.

Mattila, A. S., & Wirtz, J. (2001). Congruence of scent

and music as a driver of in-store evaluations and

behavior. Journal of Retailing, 77(2), 273–289.

Mehrabian, A. & Russell, J.A. (1974), An approach to

environmental psychology, Cambridge, MA. : MIT

Press.

Michel, Christoph M. and Micah M. Murray (2012).

“Towards the utilization of EEG as a brain imaging

tool”. In: NeuroImage 61.(2), pp. 371– 385.

Milliman, Ronald (1982), "Using Background Music to

Affect the Behavior of Supermarket Shoppers,"

Journal of Marketing, 46 (Summer), 86-91.

Milliman, Ronald (1986), "The Influence of Background

Music on the Behavior of Restaurant Patrons," Journal

of Consumer Re- search, 13 (September), 286-9.

Nasar, J. L. (1987). The Effect of Sign Complexity and

Coherence on the Perceived Quality of Retail Scenes.

Journal of the American Planning Association, 53(4),

499–509.

Oakes, S. (2000). The influence of the musicscape within

service environments. Journal of Services Marketing,

14(7), 539–556.

Oliver, R.L. and Swan, J.E. (1989) Consumer Perceptions

of Interpersonal Equity and Satisfaction in

Transactions: A Field Survey Approach. Journal of

Marketing, 53, 21.

Ramsøy,T.Z.(2014).Introduction to Neuromarketing and

Consumer Neuroscience. Neurons Inc.

Rosen, D. E., & Purinton, E. (2004). Website design:

Viewing the web as a cognitive landscape. Journal of

Business Research, 57, 787–794.

Schiffman, H. R. (2001). Sensation and perception (5th

ed.). New York: Wiley..

Sweeney, J. C., & Wyber, F. (2002). The role of

cognitions and emotions in the

music‐approach‐avoidance behavior relationship.

Journal of Services Marketing, 16(1), 51–69.

Tollner, T., H. J. Muller, and M. Zehetleitner (2011a).

“Top-down dimensional weight set determines the

capture of visual attention: Evidence from the PCN

component”. In: Cerebral Cortex 22.(7), pp. 1554–

1563.

Turley, L. ., & Milliman, R. E. (2000). Atmospheric

Effects on Shopping Behavior. Journal of Business

Research, 49(2), 193–211.

Van der Lubbe, R. H., Jaśkowski, P., Wauschkuhn, B., &

Verleger, R. (2001). Influence of time pressure in a

simple response task, a choice-by-location task, and

the Simon task. Journal of Psychophysiology, 15(4),

241.

Van der Lubbe, R. H., & Utzerath, C. (2013). Lateralized

power spectra of the EEG as an index of visuospatial

attention. Advances in cognitive psychology, 9(4),

184.

Vanderark, S. D., & Ely, D. (1993). Cortisol, Biochemical,

and Galvanic Skin Responses to Music Stimuli of

Different Preference Values by College Students in

Biology and Music. Perceptual and Motor Skills,

77(1), 227–234.

Vossel, S., J. J. Geng, and K. J. Friston (2015). Attention,

predictions and expectations, and their violation:

attentional control in the human brain. Frontiers Media

SA.

WEBIST 2019 - 15th International Conference on Web Information Systems and Technologies

318