Graduate School of Communication
Master's programme Communication Science
Tempo to buy:
the effect of advertisement music tempo on purchase
intentions and attitude toward the product.
Supervisor: Bas van den Putte
Student: Stefano Perotto
“Music is the universal language of mankind” said Henry Wadsworth Longfellow in one of its poems. What this poet of the 19th century was able to hold in a single sentence is the evocative
power of music which has long fascinated the mankind. The communicational capacity of music is undeniably strong, emotions and moods can be conveyed universally with no risks of misunderstanding.
It is not surprising therefore that marketers got interested in understanding how this power might be profitable. The scientific community gave its contribution showing that “music used in marketing-related contexts is capable of evoking non-random affective and behavioral responses in consumers”(Bruner II, 1990; p. 99), in other words, music can be an useful tool in advertising to evoke a desired response on targets.
This communicative capacity can find a particularly relevant role in a world of advertising clutter. In a context where we are all reached from a multitude of selling messages, being over-exposed can lead to put in action resistance or ad avoidance strategies (Speck & Elliott, 1997). Music can be an excellent instrument to distract the target and convey a message without triggering resistance (Knowles & Linn, 2004).
The advertising literature have so far mainly focused on pitch-related ( melody, mode, harmony) and texture-related (timbre, volume) effects on listeners while the time-related (rhytm, tempo, phrasing) component have been investigated more extensively in the environmental context (Bruner II, 1990). This branch of research has brought to light that music tempo can be a significant predictor of consumers purchase behavior. Specifically, for a consumer who is approaching the purchase for pleasure and not for necessity, a fast music tempo lead to a higher chance of buying ( Velitchka, Kaltcheva, & Weitz, 2006).
advertising context and therefore to understand to what extent the music tempo of an advertisement effect the likelihood of a purchase the product and the attitude toward it. If this pattern would find a confirm, important indications would be provided to practitioners that aim to optimize the implementation of their advertisements.
In 1982 Gerald Gorn sparked renewed interest in the role of music in commercials with a classical-conditioning approach experiment. This study showed how the affective response to music can effect the attitudes towards a product and therefore the intentions to buy it. A specific component of music, that is tempo, have been investigated in retail stores (Andersson, Kristensson, Wästlund, & Gustafsson, 2012), web-shops (Ding & Lin, 2011), restaurants (Millman, 1986) and radio advertisements (Booker & Wheatley, 1994) but the literature is insufficient to establish a link between music tempo in advertisements, the attitude towards the advertised product and the intentions to buy it. Therefore it is aimed to answer the following research question:
RQ: To what extent does music tempo in an advertisement influence the attitude
towards the advertised product and the intention to purchase it?
The purchase intent of an individual consist in the implied promise to one's self to buy the product in the near future (Tariq, Nawaz, Nawaz & Butt, 2013) and even though it can be improved, self reported purchase intention is still the best way to predict purchase behaviors (E.g. Chandon, Morwitz & Reinartz, 2005).
Within the advertising context, music has proved to influence the attitude toward the product, for instance, the aforementioned experiment of Gorn (1982) showed with striking results how a unique exposure of music matched with a product led to significant differences of responses between those who saw the product paired with sad music from those who saw the same product paired with happy music. The experiment presented some methodological questionable choices (Kellaris & Cox, 1989) but it clearly showed how the emotive tone of the music was associated to the product influencing the attitude towards it.
The underlying mechanism of this process is well explained from the elaboration likelihood model (ELM) of Petty and Cacioppo (1986). This model illustrate how individuals with a higher need for cognition are “more likely to think about and elaborate cognitively on issue-relevant information when forming attitudes than individuals low in need for cognition” (Petty & Cacioppo 1986, p.1). The authors go further concluding that individuals in the latter condition are less affected by the quality of the arguments within the message and more from peripheral cues presented with the message. Message elements like erotic stimuli, humor, celebrity endorsement or music can influence the evaluation of a message even though they are not intrinsically correlated with it.
Music is of interest therefore as a peripheral cue that can influence the way a message is processed. This attention to music and its effects has focused also on one of its relevant components: tempo (Bella, et.al 2001). The past literature agrees in assuming that a fast tempo is considered as happy or more than a slow one, evoking more joyful and exhilarating feelings compared with tranquil and sentimental (Bruner, 1990), but the emotive response to music may be only the last ring of the chain. As argued by Kellaris and Kent (1983) the complex nature of the musical stimuli and the consequent responses, might require to investigate the “objective properties of sound as antecedents of emotional outcomes”(Kellaris & Kent, 1983, p. 382) in other words, research should focus on what comes before, and on a
more basic level than the emotional response. To a deeper understanding of this phenomena these two authors propose three dimensions of response: pleasure, arousal and surprise. These three elements, according to the authors, are elicited by three basic musical properties ( tempo, tonality and texture). The environmental literature instead, ground on the PAD (pleasure, arousal, dominance) model proposed from Mehrabian and Russel (1974). Specifically, following studies (E.g. Velitchka, Kaltcheva & Weitz, 2006) focused only on pleasantness and arousal because these two variables explain most of the variance in affect and behavior (Russell, 1980; Russell & Pratt, 1980). The present study will follow this line considering pleasantness and arousal as antecedents of emotional responses to music tempo.
The literature provides a strong relation between arousal and music tempo, in fact many studies showed how a faster music tempo is more effective than a slow one in inducing a higher level of arousal (E.g. Scherer & Oshinsky, 1977; Sweeney & Wyber 2002; Zhu & Meyers-Levy, 2005; Day et al. 2009), an energetic rythm elicitate excitement while sedate music lead to peaceful emotions (Gabrielsson & Lindstrom, 2001).
Based on the literature presented, it is hypothesized that faster tempo leads to higher arousal:
H1: The level of arousal will be higher with faster advertisement music tempo.
Music tempo has not been studied largely in the field of advertisement, that is why the present study tries to add research on this topic. Booker and Wheatley (1994) found out that the music tempo in a radio advertisement positively effected attitudes and purchase intentions toward the music itself and not toward the product. These finding may be explained by the intrinsic features of the medium (radio) which cannot count on the visual stimuli, and hence might be insufficient to link through a classical-conditioning effect, product and music tempo.
More extensive is the research about music tempo in places of direct purchase such as retail stores (Andersson, Kristensson, Wästlund, & Gustafsson, 2012), web-shops (Ding & Lin, 2011) and restaurants (Millman, 1986). While the previous literature was consistent in considering a pleasant environment positively related to shopping attitudes and behaviors (e.g Sherman, Mathur, & Smith, 1997; Yoo, Park, and MacInnis, 1998) such agreement was not found for arousal. For instance, Millman's (1986) conclusions report that arousal has a negative effect on purchase intentions and spending, while Sherman, Mathur, and Smith (1997) had opposite findings. Donovan and Rossiter's results in 1982 are in line with Sherman and colleagues conclusions but in 1994 they failed to confirm those findings (Donovan, Rossiter, Marcoolyn, & Nesdale, 1994).
The experiment conducted by Velitchka, Kaltcheva and Weitz (2006) gave a possible explanation to the mixed findings about the relations between music tempo, arousal and purchase intentions. They found that high levels of arousal led to higher levels of purchase if consumers had a recreational motivation orientation (hedonic products). While if customers were task-oriented (utilitarian products) a high level of arousal was a predictor for low levels of purchase. This process is explained by the fact that task oriented individuals are in need for cognition because they have a specific goal, therefore a high level of arousal is an obstacle to their energy-demanding task. Conversely, subjects with a recreational motivation get satisfaction from the shopping activity itself, therefore a high level of arousal is perceived as pleasant. The effect of arousal on purchase intentions is mediated by pleasantness (Lunardo & Mbengue, 2009) . Same pattern have been found in the on-line context from Ding and Lin (2011) but the results are significant only for hedonic products and not for utilitarian ones.
Because there is no support to postulate a similar relation between music tempo and utilitarian products the present study will focus solely on hedonic products. Perhaps, the relation between arousal, attitudes and purchase intentions for utilitarian products might be
an interesting subject in a later stage.
Grounding on the presented literature the following hypothesis are formulated:
H2: A higher level of arousal will lead to a higher level of pleasantness (for hedonic
H3: Fast music tempo in the advertisement will enhance the purchase intentions of,
and the attitude toward hedonic products.
H4: Pleasantness is positively correlated with the intention to purchase the product
and the attitude toward it.
The aim of the present study is to apply the findings of music tempo in environments, to an advertising context. In order to do so it is necessary to take into consideration the main difference that distinguish the purchase in a retail, from the purchase that may take place after being exposed to an advertisement, the lapse of time. While in a retail the purchase can take place immediately, the exposure to an advertisement is likely to happen in a place where it is not possible to buy the product. Mehrabian and Russell (1987) define arousal as a fleeting and temporary emotional state, which implies that after a certain amount of time sufficient to extinguish the arousal state, pleasantness would not be triggered and therefore the whole process would be compromised. It is possible anyway that the positive association between the pleasant feeling and the product would persist over time through memory. Once a subject pair a certain product with a positive feeling and a positive attitude this association should survive over time and preserve the attitude toward the product and the intention to purchase it. Supposing that recalling the message would act as a recall also for the attitudes and the intentions related to the message two different school of thought present opposing results about arousal and recall. According to some authors arousal would increase attention and hence lead to “longer-lasting memory traces” and recall of the message (Surendra & Churchill,
1987, p.5) while for others high-tempo music is more energy-demanding and thus slow tempo music brings a higher recall of the message (Hahn & Hwang, 1999). Due to these conflicting results and the lack of evidence it is not possible to formulate an hypothesis therefore it is asked:
RQ2: To what extent the effect of music tempo on purchase intentions and attitude
toward the product change over time?
Participants and procedure
The study was conducted in December 2014 through an on-line questionnaire sent to a convenience sample. Participants were asked to fill out the questionnaire on two different occasions with a 24 hours span from one to the other. Among the 146 subjects that accessed the questionnaire only 84 participants submitted it on the first wave, between them 27 completed the follow-up. The sample was composed for the 44% by female (n=37).
The main experiment was a single factor (fast tempo vs slow tempo) between-subjects design due to assess participants' responses depending on the music tempo of the video game commercial. The follow-up tested purchase intentions and attitude towards the product over time, 24 hours after the main experiment.
The subjects were randomly assigned to one of the two experimental conditions from the program Qualtrics, 43 participants received the slow condition, 41 the fast one.
In order to create the recreational orientation needed for the experiment, respondents were told to dive themselves into a scenario and imagine that they were looking for a new
video game. Furthermore, participants were told that the aim of the study was to investigate the relation between colors and visual stimuli in game advertisements.
Materials and measures
Commercial. Following Ding and Lin's (2012) pre-test results, the product category of
video games was considered as a legitimate example of hedonic product.
Music tempo. In their experiments Gorn (1982), Milliman (1982) and Ding and Lin
(2012) indicated a music tempo equal or faster than 94 beats per minute (bpm) as a fast one and an equal or slower tempo than 72 bpm as a slow one. The present study adopted these parameters and the soundtrack of the video game commercial was slowed down to 70 bmp (slow version) and speeded up to 102 bpm (fast version).
Development of stimuli. A pre-test was conducted to select the video game
commercial lowest in arousal effects in order to reduce interference with the arousal elicited by the music tempo. 17 Subjects expressed, after viewing the video with no sound, their level of arousal on the six items scale adopted in the main experiment and described afterwards. Two videos were selected for the pre-test: “SimCity E3 Gameplay Trailer“ (www.youtube.com/watch?v=tQNagqH6mO4) and “Wild - Gamescom 2014 Trailer” (www.youtube.com/watch?v=8sYw2X2iYLw). The latter video, produced by Wild Sheep Studio in August 2014 for an on-line campaign, scored lowest in arousal effects (M=4,59) and therefore selected for the experiment.
Each version of the soundtrack was pre-tested to check if the stimuli were recognized properly as slow and fast tracks. 17 Participants to the pre-test rated the perceived speed of the track on a five-point semantic scale (fast = 1, slow = 5). The two versions of the soundtrack of “Wild - Gamescom 2014 Trailer” were weakly identified as slow (M=2,95) and fast ( M=1,65) therefore the tempo of the soundtracks was further manipulated. The music tempo
have been speeded up and slowed down at the top of the technical possibilities: 66bmp (slow), 118bpm (fast).
Manipulation. Every participant received an identical questionnaire but different
stimuli. The 'fast tempo' group watched the Wild commercial paired with the fast version of the soundtrack. The 'slow tempo' group watched the Wild commercial paired with the slow version of the soundtrack.
The questionnaire measured the following variables (in the presented order).
Purchase intentions (PI). The intention to purchase the advertised video game was
assessed through a seven-point Likert scale (1 = Do not agree at all and 7 = Agree completely) on the following statements: “ I will purchase Wild video game”, “Given a choice, my friends will choose Wild video game“, “It is highly likely that I will purchase Wild video game“, “I would like to recommend Wild video game to my friends” (Moon, Chadee & Tikoo, 2008). (α=.912).
Attitude toward the product (ATP). The attitude toward the product was measured
with a scale specifically composed for hedonic products from Voss, Spangenberg, and Grohmann (2003). The scale presents five items on a five-point semantic differential: not fun versus fun; dull versus exciting: not delightful versus delightful: not thrilling versus thrilling: unenjoyable versus enjoyable (α=.924).
Arousal. The construct of arousal was measured through a nine-point semantic scale
on six items; relaxed versus stimulated; excited versus calm; frenzied versus sluggish; dull versus jittery; wide awake versus sleepy; unaroused versus aroused (Velitchka et al. 2006). (α=.905)
with a nine-point semantic scale on four items; displeased versus pleased; satisfied versus dissatisfied; pleasant versus unpleasant; unhappy versus happy (Velitchka et al. 2006)(α=.916)
Control variables. Three control variables were tested. Participants were asked to
indicate their gender (Male or Female); whether they already owned the product (Yes or No) and (to check the possibility that the editing of the music went into conflict with the original video) the fit between music and video on a seven-point Likert scale (1= not fitting at all, 7= very fitting).
Manipulation check. The last question was due to check the validity of the
manipulation. Participants were asked to express on a five-point Likert scale whether the tempo of the music was perceived as fast or slow (1=slow and 5=fast).
Delay of time. To test the responses on the dependent variables over time, the PI and
ATP were reassessed after 24 hours. An on-line follow-up was sent to the participants who voluntarily indicted their email address.
To check whether our manipulation was effective we asked our participants to express how fast the music tempo was perceived. A one-way ANOVA yielded a significant effect of our manipulation , F (1,83)= 5.8, p= .018, participants' perception of the music speed differ significantly depending on the manipulation (slow: M= 2,76, SD= 0,969; fast: M= 3,26, SD= 0,928).
In order to proceed with the analysis every scale collecting by several items a variable has been computed in a unique scale expressing the variable itself. Negative items among the
arousal and pleasantness scales have been inverted so the scales expressed uniformly the factor.
A principal component analysis (PCA) showed that each scale used in the experiment (PI, ATP, Arousal and Pleasantness) loaded on a single factor. Every component had an eigenvalue lower than 1.
The preliminary analyses confirmed the validity of the measurements adopted in the questionnaire, it is thus possible to proceed and analyze whether the control variables have a significant effect on the dependent variables assessed. The general linear models revealed that among all the dependent variables measured in the experiment (first wave and second wave) only the perceived fit of the music had a significant effect on the dependent variables measured in the main experiment while gender and the variable due to assess if participants ever own the product did not showed meaningful effects in none of the measurements (Table 1).
Results of the General linear model testing control variables and conditions on first (P.I & A.T.P, N= 84) and second wave (P.I 2 & A.T.P 2, N =27)
Sum of squares
Degrees of freedom
Mean squares F-values p-values
PI Gender 0,455 1 0,455 0,211 0,648 Already owned 0,008 1 0,008 0,004 0,952 Fit music 11,358 1 11,358 5,255 0,025 Music tempo 4,714 1 4,714 2,181 0,144 ATP Gender 0,312 1 0,312 0,395 0,532 Already owned 0,012 1 0,051 0,065 0,799
Fit music 12,131 1 12,131 15,368 0,000 Music tempo 1,988 1 1,988 2,518 0,117 PI 2 Gender 0,261 1 0,261 0,392 0,538 Already owned 0,001 1 0,001 0,002 0,966 Fit music 0,090 1 0,090 0,135 0,717 Music tempo 0,218 1 0,218 0,328 0,573 ATP 2 Gender 1,610 1 1,610 2,376 0,137 Already owned 0,194 1 0,194 0,286 0,598 Fit music 0,847 1 0,847 1,250 0,276 Music tempo 0,009 1 0,009 0,013 0,910
Considering these results the variable 'fit of the music' has been taken into consideration in further analyses.
To have a clear prospective of the analytical process, in the aforementioned GLM it was also tested whether the music tempo had a significant effect on the dependent variables, that is, if our manipulation sorted a significant effect. Table 1 shows that music tempo did not played a significant role for any of the dependent variables (first wave and second wave).
H1. First of all, it was run a GLM to see if there was a significant difference in the
distribution of arousal scores between participants exposed to slow music tempo in the advertisement and participants in the fast music tempo condition. The fit of the music was introduced as control variable. The test showed no significance F (1, 83) = 0,150, p = .700, H1 had to be rejected since there was no significant difference in arousal level between people who watched the advertisement with a slow music tempo and people who were exposed to the fast music condition. Nonetheless there was a significance for the music fit (Table2).
Results of the General linear model testing the effect of music tempo and music fit on arousal (N=84).
Sum of squares
Degrees of freedom
Mean squares F-values p-values
Music tempo 0,334 1 0,334 0,150 0,700 Fit music 32,800 1 32,800 14,728 0,000
H2. The second hypothesis stated that arousal would have been positively correlated
with the reported feeling of pleasantness. A regression analysis was run to determinate if arousal was a predictor of pleasantness and the fit of the music was included in the regression model. The test showed no significant interaction for the control variable included in the model (Table 3) but an interesting connection was found between arousal and pleasantness. Although the causality is not fully clear (does arousal create pleasantness or vice versa), it emerged that participants who gained a feeling of arousal also had a feeling of pleasantness (Table 3). A regression showed that the variance in arousal is for 33,2% explained by the variance in pleasantness, F(2, 81) = 2,03, p <.01 with an R2 of .352, therefore H2 has been
accepted. An increase of one point of the scale of pleasantness corresponded to an increase of around 0,5 points on the scale of arousal and vice versa (table 3). But, as we concluded before, these feelings are not caused by the tempo of the music, but have to be explained from other variables.
Results of the regression analysis testing pleasantness depending on arousal and music fit (N=84).
B SE B β
Arousal 0,498 0,091 0,000
Fit music 0,129 0,095 0,179
H3. In the third hypothesis it was assumed that a faster music tempo would have
brought an increase on the intentions to purchase the product and on the attitude toward it. Table 1 already showed how the music tempo did not play a relevant role in the model but to investigate further we tested with a regression the relationship between music tempo and the dependent variables. The fit of the music has been included in the model. The results of the regression with music tempo as independent variable and purchase intentions as dependent variable are consistent with the results of the initial GLM (the relationship is not significant, table 4), same for attitude toward the product (the relationship is not significant, table 4). The perceived fit between music and video showed instead a significance on both dependent variables, for P.I = F(2,81) = 3,320, p = 041with R2 of 0,76 and for A.T.P= F(2,81) = 8,566, p < .
Results of the regression analyses testing the DV depending on tempo and music fit (N=84).
B SE B β PI Music tempo 0,471 0,321 0,146 Fit music -0,243 0,105 0,023 ATP Music tempo -0,317 0,194 0,107 Fit music 0,255 0,064 0,000
H4. The last experimental hypothesis stated that a higher feeling of pleasantness was
positively correlated with the dependent varibles. To test this hypothesis it was firstly checked if responses of pleasantness had a significant difference among groups, once again it was not the case t (82) = -0,89, p= 0,377, 95% CI [-0,363, 0,947], the music tempo did not significantly effected the pleasantness reported. Finally, a GLM analysis has been conducted to test the relation between pleasantness, P.I and A.T.P, like before the fit of the music took part of the aanlaysis. This last control variable showed a moderately significant effect (Table 5), but the model pinpoints that pleasantness do indeed have a significant effect on purchase intentions and on the attitude toward the product (Table 5). Yet, this pleasantness is not caused by the music used in the advertisement.
Results of the General linear models testing the DV depending on pleasantness and music fit (N=84).
Sum of squares
Degrees of freedom
Mean squares F-values p-values
PI Fit music 0,318 1 0,318 0,252 0,618 Pleasantness 106,173 27 3,932 3,108 0,000 ATP Fit music 0,443 1 0,443 1,052 0,309 Pleasantness 41,672 27 1,543 3,667 0,000
RQ2. To answer the second research question and understand how the process is
effected by the flow of time the same procedure than for the main experiment have been applied to those who have responded to the follow-up survey. In total, 27 participants completed the main questionnaire and the follow-up assessing the two dependent variables after 24 hours.
H1. Firstly a t-test was run to check if there were statistically relevant differences in the
levels of arousal between conditions. The test, consistent with the analyses conducted previously, showed a non-significant effect of music tempo on arousal t (25) = -0,53, p= .959, 95% CI [-1,13, 1,06]. Similarly to the main experiment, those who watched the advertisement with a fast music tempo did not differ significantly from those who watched the video with slow music. The H1 have to be rejected also for the follow-up.
H2. Following the second hypothesis it has been tested the relation between arousal
and pleasantness. Based on the correlation analysis with Sperman's rho there was a positive correlation between the two variables, r = 0.471, n = 27, p =.013. Consistent with the results
obtained for the main experiment there is a significant correlation between arousal and pleasantness, therefore H2 has been accepted also for the follow-up.
H3. The hypothesis assuming that music tempo would have had a positive effect on the
dependent variables has already been rejected previously (table 1); music tempo did not showed any relevant effect on P.I 2 and A.T.P 2. Nonetheless, it has been run a t-test in order to acquire more information about this relation. The test yielded no significant differences, as expected, between those who received the slow music video from those who received the fast music one, t (25) = -0,53, p= .959, 95% CI [-1,13, 1,06].
H4. Finally, the last hypothesis assuming that pleasantness was positively correlated
with the dependent variables was tested through two steps. At first, with a t-test it was verified whether the level of pleasantness between groups had a significant difference. The test showed that such difference was not significant t (25) = -0,53, p= .959, 95% CI [-1,13, 1,06]. Afterwards with a GLM the relation between pleasantness and the dependent variables measured in the follow-up. This last analysis showed that A.T.P2 was significantly correlated with pleasantness, however, this confirm did not emerged for P.I. 2 (table 6).
Results of the General linear models testing the DV2 depending on pleasantness (N=27).
Sum of squares
Degrees of freedom
Mean squares F-values p-values
Pleasantness 10,072 14 0,719 1,657 0,193
The results emerging from the follow-up echo the findings of the main experiment, H1 and H3 have been rejected since the music tempo did not played a relevant role in the process. The analyses showed a correlation between arousal and pleasantness as assumed in the H2, participants who had a higher level of arousal perceived also an higher level of pleasantness. Therefore H2 has been accepted, likewise H4 has been confirmed since pleasantness showed to be significantly correlated to the dependent variables. The only discrepancy between first and second wave refers to the relation between pleasantness and PI, significant in the main experiment but not in the follow-up. Because the music showed to play no role, it is not possible to give answer to the first and the second research questions.
Previous literature outlined the influence of music tempo in store and on-line environments on the intentions to purchase. Specifically, a faster music tempo has showed to have a positive effect on purchase intentions if the context is recreationally oriented that is, the customer aim to buy an hedonic product. The goal of the present study was to investigate how the effects of music tempo emerged in the environmental setting would apply to the processing of an advertisement. The responses to music tempo in terms of purchase intentions (PI) and attitude toward the product (ATP) have been tested after the participants viewed a commercial about an hedonic product (videogame).
The first surprising outcome is that participants did not showed to be significantly aroused by music tempo. This variable actually showed no effects at all in the experiment. Of course, seen the purpose of the experiment this is a major lack. Given the strong link that the literature draw between music tempo and arousal it is assumed that the experimental condition failed in some of its components, in particular for what concern the musical stimulation. It is not clear the reason why a faster music tempo did not led to a higher level of
arousal but the experimental setting may neglect some of the aspects needed to obtain such response. For instance, the scenario created to evoke a recreational orientation may have been insufficient to actually obtain its purpose and thus the participants' mindset was not comparable to a real-life setting. An alternative reason behind the missing effect of music tempo may be indicated from the significance of the music fit. Participants' perception of fit between music and video has been assessed to check if the music editing interfered with the process. This variable has showed to be significant in those analyses that included music tempo, hence there is a possibility that those who perceived a fit between music and video got involved in the listening session, conversely, those who perceived a discrepancy between music and video did not enjoyed the experience and therefore reported a lower levels of arousal and pleasantness. Nonetheless the objective discrepancy between music and video appear to be too weak to bring such strong effect.
The number of respondents (84) and the sample obtained did not allowed to generalise the results to an extended population, but the findings on arousal and pleasantness provide interesting indications for future developments. The experiment in fact, confirm the relation between arousal, pleasantness and the positive effects of these two components on PI. According to previous finding in the environmental field ( E.g. Velitchka, Kaltcheva & Weitz, 2006) when people are oriented to evaluate the purchase of an hedonic product, arousal has a positive effects and thus lead to a pleasant state which enhance the likability of a purchase. The present study extended thus the aforementioned findings to an advertising context. The PAD model of Mehrabian and Russell (1987) holds in an advertisement context and therefore it appears to be worth of further studies.
Considering the limited number of respondents that completed the follow-up (27), the analyses conducted with those data cannot be considered more than a tentative investigation.
music of the original soundtrack was retained, it was not completely homogeneous. Music variations in pitches and accents may have interfered with the arousing effect making it not significant, different levels of arousal may have occurred during the listening and a measurement made only at the end of the listening session may have recorded only the latest amount of arousal. Considering the limits encountered in the selections of the materials, the video selected through the pretest was the one that scored lowest in arousal effect, even so, it scored 4.59 which is quite close to the midpoint (in a 9-point scale). A commercial lower in arousal effect would have allowed a clearer distinction of the arousal elicited by the music tempo, eventually showing the missing relationship between music tempo and arousal. Another limitation is related to the fact that a control variable due to asses the individual attitude toward videogames might have explained the reason why we did not find any significant results of music tempo on the dependent variable ATP. Each subject was possibly prone (or not) to videogames before undergoing the experiment and this has probably affected the ATP independently from the stimulations. Finally, the number of respondents was scarce because of a technical issue due to cell phones compatibility. The program used to create the questionnaire (Qualtrics) did not supported the display of videos on mobile devices, this explains why 146 subjects started the questionnaire but only 84 completed it. From the partial data it was possible to notice that almost all the incomplete surveys were stopped on the video section, supporting the belief of a technical issue.
Future research in the advertisement should focus on the relations between music tempo and arousal, to understand which variables impact the effect of one to the other. Furthermore, it would be interesting to understand the associations that the intention to purchase might has on the attitude toward the brand and toward the product, in order to exploit the benefits of music in advertisement.
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