Man Made Music (MMM) is a strategic music and sound studio that unlocks the power of sound for entertainment, brands and people. MMM builds unique sonic identity architectures that efficiently and effectively tie media, spaces, products and devices together. The company also provides music supervision, artist partnerships, user interface sound design and live events solutions, as well as television, film, and new media themes and underscores.
TDL and MMM collaborated on this project to determine whether specific acoustic environments can change people’s perception of time and their emotional states. Past work has shown that people in negative emotional states make worse decisions, and that the feeling of waiting engenders frustration and anger. Thus, in situations where people are forced to wait, the acoustic environment created during this time may be a determinant of various important outcomes – from brand loyalty to subsequent decision making.
This report integrates and synthesises current perspectives and research in auditory and temporal psychology to provide an overview of time perception, its impact, and reasons for distortions in time perception. As a second step, we conducted an MTurk experiment to measure the effect of auditory stimuli on retrospective time estimates and emotional responses. This allowed us to, in collaboration with MMM, create actionable recommendations that can be implemented by sonic designers who want to create an environment more conducive to positive feeling, brand loyalty and ultimately better decision making.
What you can expect from this document
Our report provides recommendations to promote better sound design, grounded in existing insights from behavioral science and our own empirical research. The lay-reader can expect to gain an in-depth understanding of how sound influences a range of behaviours from shopping habits, to time perception. A more seasoned sound designer can use this report to identify the conditions under which time is underestimated and negative emotions are mitigated. This can allow them to tailor interventions to the goals of an environment – for example, to improve decision making, reduce stress or promote healing.
How does sound affect our everyday lives?
Sound is a completely pervasive feature of modern life – even the most quotidian activities such as driving, shopping, or eating come with a soundtrack. Whether it’s an uplifting beat on the radio or the clinking of forks in a restaurant, we usually can’t help but experience the sounds around us and be affected by them.
Performance in a range of behaviours from clerical tasks, to mental arithmetic, to time reaction tasks can be influenced by our acoustic environment, (Sanders 1961; Woodhead, 1964; Fischer, 1972) from car horns, construction work, to gusts of wind. The onset and offset of noise usually leads to a deterioration of performance (Broadbent, 1979), and exposure to unpredictable noise generates frustration and leads to poorer outcomes in tasks such as proofreading (Glass & Singer 1972). Even bird sounds in urban spaces affect people’s behaviour (Davies et al., 2013).
The impact that sound has on us is hard to overstate and is most easily demonstrable when we think about the sub-category of sound that we call music. Ancient humans long ago, surprisingly universally, began to harness and organise sound into music. Evolutionary scientists believe prehistoric humans developed musical cultures because music coordinates emotions, facilitates communication, encourages support, and reinforces identity (Black, 2013).This continues to be true in the modern world. For better and worse, sound has been shown to have real psychological effects that influence a wide range of behaviours. And yet, despite continuous advances in designing the musical sub-category of sound, surprisingly little work has been done to advance the sonic environments that surround the modern urban dweller. With that said, let us look to music to see what a few of its known effects on our feelings and actions are – while reading about them, consider how non-musical sounds may have similar effects on us at almost all times.
Katy Perry, an American singer and songwriter, may have been speaking to this ancient behavioral phenomenon with the lyric ‘Chained To The Rhythm’. Research has demonstrated that, in general, music in stores leads to customers lingering and spending more money. Furthermore, when fast music is played in supermarkets, shoppers move around more quickly, but spend less compared to when slow tempo music is playing, and restaurant goers will eat more slowly and purchase more drinks at the bar when given a side of slow rather than fast music (Engel, Blackwell, & Miniard, 1990; Milliman, 1982, 1986).
One can recognise a brand not simply by its logo or product, but often by an accompanying “jingle”. Research has demonstrated that brand perception is highly influenced from the very first moment by the sounds associated with it, and may be the most stimulating component of a commercial (Hecker, 1984; Stout & Leckenby, 1988; Gorn, 1982; Park & Young, 1986). Music that is fast and has a greater range leads people to view a brand as “more energetic, sporty, exciting, refreshing, young and fun” while music with a slower tempo and less tonality creates an impression of “delicate, soft, relaxing, mature, natural and healthy” (Apaolaza-Ibáñez et al, 2010). The crucial element to remember is that music stimulates our emotions, which are then tied to our perception of a brand.
Insulting people is never likely to elicit a positive response, but combining it with exposure to music can actually make people more likely to administer electric shocks to others than those subjected to ‘silent’ insults (Konecni, 1975). On the other hand, music can also create positive outcomes by increasing how attractive men are judged by women (May & Hamilton, 1980) and making people feel more powerful (Hsu, Huang, Nordgren, Rucker, & Galinsky, 2015). Music can influence mood (Bruner, 1990; Fried & Berkowitz, 1979) and mood mediates between the experience of waiting for a service and a customer’s evaluation of the service provider (Baker & Cameron, 1996; Houston, Bettencourt, & Wenger, 1998; Hui, Thakor, & Gill, 1998; Hui & Tse, 1996; Taylor, 1994). Exposure to music also has effects on a range of other issues such as delinquency (Bleich, Zillmann, & Weaver, 1991), helpfulness (Fried & Berkowitz, 1979), pain management, economic recession (Zullow, 1991), suicide (Stack & Gundlach, 1992), and even warfare (Simonton, 1987).
Not all music is equal however. Whether music is perceived as positive or negative depends on a mixture of factors such as tempo, pitch, mode, genre, and volume (Bruner, 1990; Kellaris & Rice, 1993). Pieces of moderate complexity generally are preferred to those of either low or high complexity (Hargreaves & North, 1997). These musical characteristics have been shown to affect behaviour differently. Shoppers will buy the more expensive wine when listening to classical music compared to ‘Top 40’ hits (Areni & Kim, 1993). Younger people buy more clothes when exposed to ‘background’ music while older shoppers showed the same effect when louder foreground music was played, but in general all people spend less money while listening to familiar music (Yalch & Spangenberg, 1990). Group discussions become more gregarious in the presence of soothing music (Valerie N. Stratton & Zalanowski, 1984) and those stuck on hold for a call service hang up more frequently when relaxing music was played on the line compared to jazz or country music (Ramos, 1993).
Time perception is poorly understood
One area of specific focus for scholars has been the effect of sound on perceptions of time. Beyond the differences between types of sounds and experiences already mentioned above, it has been found that simply having any on-hold telephone music may be more effective than silence in shortening the perception of time and persuading customers to stay on the line (North, Hargreaves, & Mckendrick, 1999).
Music appears to lead people to make more inaccurate estimations of time passed.
While each day has 24 hours for everyone, how each person experiences this time varies greatly. “Just as Einstein’s theory of relativity tells us that there is no such thing as absolute time, neither is there an absolute mechanism for measuring time in the brain” (Hammond, 2013, p. 54). Stanford neuroscientist David Eagleman has suggested that “our sense of time is surprisingly easy to manipulate … whether it’s actual duration or the order in which things happen”.
Why and how does this happen?
Models of time perception
Memory based models posit that the more information that is processed in a period of time, the more memories are created and thus a longer estimate of time is created. Music, rather than silence, requires more processing and therefore should lead us to overestimate time passed.
However, a more popular theory is that music causes a disruption to our internal clocks (Fraisse, 1984; Kellaris & Mantel, 1994; Kellaris, Mantel, & Altsech, 1996; Zakay, 1989). We have a limited pool of attentional resources and in this zero-sum game more attention devoted to non-temporal tasks comes at the cost of properly accounting for time. When music increases arousal our internal pacemaker is thought to accelerate, resulting in an overestimation of the time elapsed (Droit-Volet, Ramos, Bueno, & Bigand, 2013; Oakes, 2003). This is what leads to the feeling of ‘time flying’.
The tendency for people to increasingly choose a reward in the short-term rather than future, even when the latter is of a greater amount
A behavioral approach
Daniel Kahneman argued that episodes in our mind are represented by a few critical moments, especially the beginning, the peak, and the end. “Duration is neglected … the mind is good with stories, but it does not appear to be well designed for the processing of time (Kahneman, 2011, p. 407). Behavioural economics has opened the door to greater insight with the recognition that time discounting is a fundamental characteristic of human decision making (Frederick, Loewenstein, & O’Donoghue, 2002). For example, higher rates of discounting lead an individual to shift consumption to the present rather than save for the future. This tension between the present and the future is most evident when we are forced to wait. This subcase of time passing is quite interesting because it is when time perception is most acute. As we will explore in the rest of this paper, waiting is deeply impactful on a both a personal and societal level.
A life in waiting
Even in our modern fast-paced world, waiting is inevitable – in fact, Americans spent 37 billions hours waiting each year. This waiting incurs economic costs due to lost time, but the effects are more deeply felt than that. Since waiting is usually something we do prior to another activity, the frame of mind that the waiting leaves us with can obviously affect that next activity. In cases where that activity is particularly important (e.g. a visit to the doctor or to the bank), this effect can have very real and serious impacts on our lives. The next section examines what these impacts might be and suggests a methodology for testing them.
37 Billion Hours
Amount of time Americans spend waiting annually
– (Timex, 2012)
Despite time perception being long the subject of psychology research, we have only recently begun to understand that the experience of waiting is defined only partly by the objective length of the wait. “Often the psychology of queuing is more important than the statistics of the wait itself”(Larson in Stone, 2012).
Waiting leads to poorer decision making
We can inherently sense if we are spending too much time on an unrewarding activity and each person has a personal threshold for waiting, after which point they begin to accumulate stress (Gzyl & Osuna, 2013). The pace and intensity of stimuli in modern life may be exacerbating this natural instinct by creating expectations that can’t be rewarded fast enough. This is especially the case with web-based services when even a delay of 400 milliseconds — literally the blink of an eye — is too long (Lohr, 2012).
Mental Accounting Perspective:
If the time spent waiting is distracted or occupied, it is perceived at a smaller cost
All of this waiting and stress can have serious negative effects on our decision making. The longer customers wait before making a consumption decision, the more they purchase and when people are in a negative emotional state they prefer to take immediate action rather than wait. Impatient children and adolescents are more likely to spend money on alcohol and cigarettes, have a higher body mass index (BMI) and are less likely to save money (Sutter et al. 2013). This is why there has been a focus on improving the experience of waiting when eliminating the actual long wait time is impossible.
Mitigating the costs of waiting through design
Interior designers and architects have been cognizant of the effects of waiting on the psyche and have responded by modifying the physical spaces we inhabit. For example, mirrors were added to elevators during the construction boom of high-rise buildings to distract patrons (Stone, 2012) and music has been shown to act as a treatment for stress (V. N. Stratton, 1992).
In the context of sound, it has also been found that a period of waiting is judged shorter when there is accompanying music than when there is none (Guéguen & Jacob, 2002; North & Hargreaves, 1999; Roper & Manela, 2000; V. N. Stratton, 1992). This is consistent with the mental accounting perspective; furthermore, using sound can do more than reduce stress associated with waiting – it can decrease pain, anxiety, the amount of anesthesia needed and reduces the time needed to induce sedation. it can actually make patients more receptive to health advice in the consultation and more likely to ask for advice (Wicke, Lorge, Coppin, & Jones, 1994; Wolff et al., 2010). Therefore, there are opportunities to have a positive impact on decision making through clever sound design.
As mentioned above, a significant part of our lives are spent waiting, and most of the important things we do are prefaced by a period of waiting. We’ve seen that the psychological effects of waiting have ramifications for our decision making capabilities, but also that music can mediate our moods and behaviors. Two questions then arise:
- Are we being subtly nudged towards poorer decisions by something as seemingly innocuous as the sounds we hear while waiting?
- Are we doing our best to optimize the sonic environments we create in urban spaces and beyond in order to maximize decision making outcomes?
In an effort to address these questions, we performed an experiment that exposed people to various sonic environments during a period of waiting. The next section shares our methodology and results.
Design And Materials
We chose an experimental design to test the simple idea that sound significantly impacts our perception of time, our feelings, and even our attitudes (e.g trust). Experiments, compared with observational studies, offer the advantage of a controlled environment which enables us to measure precisely the effects of a treatment on an outcome, thus establishing cause and effect relationships. This in turn enables us to make predictions about future outcomes.
Experiment: Between-Groups Design
- Participants completed a listening exercise online in the presence of one of seven audio samples*:
- Ambient music**
- Background sounds from a coffee shop**
- On-hold message
- Pop Song**
- Audio book
- White noise
- Participants then made a retrospective estimation of the time spent on the exercise and answered questions about their emotional response to the audio.
- Retrospective time estimates
- Series of multi-item scales measuring emotional responses to auditory stimuli created specifically for this study by MMM
- Stimuli consisted of audio excerpts played for 47 seconds
* While the style of the music was generally familiar to the participants, the specific composition was not
** These conditions employed non-vocal excerpts
The study was conducted online via Amazon Mechanical Turk (MTurk) using paid volunteers ($1 each), restricted to those using US IP addresses, to complete a Human Intelligence Task (HIIT). A pilot of 20 subjects was run, which allowed us to see that the experimental design was effective at getting people through the experiment. In the final MTurk experiment 239 participants volunteered.
Anyone without a HIT ID (i.e. non MTurk subjects who did the survey for fun) as well as anyone whose worker ID appeared in the results more than once (i.e. someone who did the experiment twice) were eliminated from the sample. Subjects were also removed if they did not complete the entire experiment, pressed any key before audio sample ended, did not press any key within 3 seconds of hearing the end of the audio sample, guessed that the sample was less than 25 seconds in length, or guessed that the sample was over 120 seconds.
The final sample was 184 participants (females = 87, male = 97) between the ages of 18 and 65 years. Twenty-one to thirty-five participants were assigned to each condition, with each participant being tested individually.
The experiment took place on an individual basis. Participants were given the option to consent to participating in a “Survey with an audio component”. Participants completed a short sound test to make sure their personal headphones or speakers were functioning properly.
To ensure that they paid attention, participants were asked to turn off any potential distractions and to look at a cross in the centre of a white screen for the duration of the audio sample. Participants were instructed to listen for the sound of a ‘single beep’ which signalled the beginning of an audio track, and then to press ‘any key’ as quickly as possible after hearing a ‘double beep’ which signalled the end of the audio track. Participants were instructed not to press any key before the single beep and to answer within 1.5 seconds of the double beep – the actual cutoff was decided at the time of data analysis. Instructions included information that subjects would be asked questions relating to what they heard between the two beeps. It is important to note that subjects anticipated answering questions about the music, but could not anticipate the duration estimation task specifically.
Participants were then presented with a white screen with a cross in the middle and each person heard only one of the music conditions, at random, with a single and double deep set at uniform distances apart for each condition. A brief questionnaire was administered to each participant after they pressed any key following the double beep.
- Time Perception: Participants were asked to estimate retrospectively the length of time in seconds they had waited, and to rate on a scale of 1-10 how confident they were of this estimate
- Emotional Response: Participants responded to eleven questions about reactions to the sample by assigning ratings on a 5-point scale (“Not at all”/ “To a small extent”/ “To some extent”/ “To a moderate extent”/ “To a large extent”) if the audio sample made them feel the following emotions: Fear, Anger, Sadness, Joy, Disgust, Surprise, Trust, Anticipation, Excitement, Relaxation, and Annoyance. This was followed by four general questions on the same scale:
- “To what extent do you think the audio made time pass faster?”
- “To what extent did you enjoy the audio sample?”
- “To what extent did you find the audio sample predictable?”
- “To what extent would you like to hear more of the audio sample?”
- General Demographic Questions: Participants were then asked if they completed the task using headphones or speakers; for their age, sex, education level, rural or urban residence; how often they listened to music; the musical genre they enjoyed most; and their preference for slow or fast paced music.
After completing the experiment, participants were given a HIT ID – this is a number they needed to enter on MTurk in order to then be compensated.
Results from the experiment are summarized in the following table:
Table 1. Average Time and Emotion Estimations Per Acoustic Condition
|N. of Subjects||24||21||26||24||27||27||35||184|
|Time passed faster||2.4||2.0||1.8||2.8||1.3||2.5||1.8||2.0|
|Found music Predictable||1.7||1.9||3.2||1.9||1.7||1.8||2.6||2.2|
|Wanted to Hear More||2.9||1.5||1.2||2.3||1.4||2.1||1.6||1.8|
Overall, our results suggest that acoustic environments do have an impact on time perception, emotional responses, and attitudes. To test the significance of these results, we performed a regression analysis to see the effect of various determines on our outcome variables.
Going back to our core results, we find that the most accurate time estimates on average were given by those in the Coffeeshop condition. The time passed fastest on average for those in the Ambience condition (8.04 seconds less than actual time, or 17% quicker), and slowest for those in the Story condition (3.19 seconds more than actual time passed, or 7% slower).
A shortening of time should be greater for subjects who enjoy the acoustics, however our results do not show a huge difference in time perception between those who stated that they enjoyed the music to a large extent compared to those who did not enjoy the music at all. That Ambience and Story received the shortest and longest time estimations, respectively, on average suggests time perception does not seem to be related to enjoyment – something that goes against existing thinking and is quite interesting considering the general approaches brands typically take in combating time perception.
In our regression analysis, we found a significant underestimating effect of Ambience on time perception (p-value 0.01, coefficient -0.13), when converting time into a binary outcome variable depending on whether estimate was more or less than 47 seconds. Time estimates are also found to be underestimates due to feelings of joy, trust, and excitement. This appears to confirm findings in the existing literature about the effects of positive environments on time perception. Ambience is also associated with lower levels of anticipation than Silence. In fact, anticipation ranked highest on average in the Silence condition. The PopSong condition also elicited significant feelings of joy, relaxation, and trust compared to Silence.
Determinants of Time Perception
One important question we wanted to answer in this experiment was what range of feelings have positive and negative effects on time perception. We found that the ones that were significantly correlated with a reduction in time perception were joy (p-value 0.04, coefficient -0.32) and excitement (p-value 0.05, coefficient -0.33). In addition we found a trend toward significance in relaxation (p-value 0.06, coefficient -0.39). With these characteristics in mind, we can think about how to design sonic environments that reduce time perception.
Trust is a particularly important outcome variable when waiting time is a preface to important decisions such as in the context of a medical appointment or a financial advisor session. For this reason, we ran a linear logistic regression to test the effects of various variables on trust. Somewhat surprisingly, we found a very strong significant relationship between the time estimate and the trust rating – such that a longer time estimate meant lower trust (p-value 0.04, coefficient -2.44). So although the Story and Pop Song conditions are very much enjoyed, and people want to hear more of them, they perform quite poorly on generating trust ratings. This is interesting because trust is an attitude that is notoriously difficult to design for. Although we can imagine creating sounds that case happiness or sadness, creating trust is something that has not been solved but is actually far more important from a branding/marketing/sales/decision quality perspective.
Perception of Perception of Time
As a final step in our analysis, we wanted to find out whether people’s ratings of their own time perception in fact coincided with their actual perception – i.e. we tested ‘meta-perception’. In other words, did people retrospection about which sample was most effective at making time pass quickly coincide with their actual time estimates?. The results were quite surprising. Although Ambience (the sample that was actually most effective) was rated by people as being third most effective (2.4 vs 2.0). The sample rated as the most effective when people were asked was actually the Pop Song (2.8 vs 2.0). Consider that the actual time estimate on Pop Song was 44.5 seconds, which in fact quite poor compared to Ambience and even underperformed Silence (at 44.0 seconds). Furthermore, people rated the Story as being a 2.5 in effectiveness at reducing time perception, whereas it actually performed by far the worst at 51 seconds. These results lead us to believe that people are surprisingly bad at estimating what the effect of their sonic environment on them has been, even in retrospect.
Effects of our Sonic Samples
As a first step in this section, we outline the effects that each of the sonic samples had on various outcome measures. The two tables below summarise our core results according to whether a stimulus is correlated with an increase or decrease in a response, ranked according to effect sizes. For example, in table 2, we can see that Story and Ambience cause an increase in sadness. These tables should provide a guide for those wishing to manipulate sound environments in order to evoke certain responses.
Table 2. Increase Effects
|Increase in Response|
Table 3. Decrease Effects
|Decrease in Response|
Tying all of the results together with the story of how acoustic environments shape behavior, this study points to several interesting insights that can help us improve the design of sonic environments in the future. First of all, our results strongly support the idea that the sonic environment we are exposed to during waiting times influences our perception of time, feelings and attitudes. Although this effect was visible across sound samples, we found that the Ambience condition was particularly successful – it shortened perception of time by 19% and generated 39% higher ratings of joy than the average sample and 40% higher ratings of trust.
In general, greater arousal is thought to increase the speed of our internal clocks, and lead to time distortions. This may be the case with the Ambience condition, which evoked a number of emotional responses and led to time underestimates, indicating that the higher state of emotional arousal disrupted individuals’ internal clocks and led to them feeling that time passed by faster. It is no surprise then that Ambience was also the acoustic environment that most subjects wanted to hear more of.
Toward Sonic Nudges
Earlier in this document, we discussed the wide body of research which details the subsequent impact emotional states have on our decision-making behaviours. In particular sadness, which the Ambience condition elicited strong feelings of has been shown to influence a wide range of human activity. Sadness has been found to increase impatience in financial decisions, leading individuals to accept 13-34% less money immediately to avoid waiting 3 months for payment (Lerner and colleagues, 2013). Sadness has also been shown to reverse the endowment effect- made famous by Kahneman et al (1991) . Sadness also makes one more likely to favour high-risk, high-reward options (Raghunathan & Pham, 1999). People induced to feel sad were likely to set a lower selling price for an item they were asked to sell (Lerner et al., 2004).
It is not difficult to imagine how the other emotions piqued in this study such as joy and relaxation can affect behaviours such as financial decision making, customer satisfaction, charitable giving, etc. In particular, organisations might be interested in evoking feelings of trust in their brand through acoustic environments by featuring ambient or pop song melodies. Therefore we should carefully and actively consider the acoustic environments around us during critical decision-making moments and how these can be altered to bring about the most benefit to the decision-maker.
In this final section, we review with the key takeaways are for an organization wishing to improve the sonic environment of those it serves. Such an organization can use the insights gathered here as a starting point to more critically question the effects they have on their audience. Whether their intention is to increase brand loyalty, improve decision making during a critical process, or simply create a positive experience for their customers, organizations should move toward a more deliberate use of sound.
Here are a few insights we’ve uncovered in this paper, which could be useful:
- Sonic Design Works: Different sonic environments affects our perception of time differently – so far it seems that if one wants to reduce the perception of time, they need to use sounds that create feelings of joy, excitement and relaxation. Ambient music seems to be one environment that does this quite well, but there are likely many others that can be aligned with various real-world goals.
- Intuition Is Wrong: People are bad at estimating the effect of their sonic environment on them, even in retrospect. This is likely true for sound designers as well, unless they make a deliberate effort to test those effects. It is our belief that organizations have a duty to better understand these effects and use them for the betterment of those they serve.
- Enjoyment Is Not Effectiveness: Enjoyment of a sonic environment is not correlated with reduced time perception. Therefore, it is important to go beyond sonic environments that are likely to score well in appreciation (e.g. our story) but may in fact have negative effects.
- Unlocking Trust: Lower perceived time is very strongly correlated with trust – this is quite interesting because no other feature that we tested seems to have an effect even close to as strong. Thus, sonic designers who need to create a feeling of trust may wish to use ‘time perception’ is an easier to design for proxy.
1 This subject pool, which has been widely used in recent years, is broadly representative of Americans who are somewhat better educated and technologically aware than the average population (Berinsky, Huber, and Lenz 2012; Buhrmester, Kwang, and Gosling 2011).
Apaolaza-Ibáñez, V., Zander, M., & Hartmann, P.(2010) Memory, emotions and rock ‘n’ roll: The influence of music in advertising, on brand and endorser perception. African Journal of Business Management, 4 (17)
Areni, C. S., & Kim, D. (1993). The Influence of Background Music on Shopping Behavior: Classical Versus Top-Forty Music in a Wine Store. ACR North American Advances, NA-20. Retrieved from https://acrwebsite.org/volumes/7467/volumes/v20/NA-20
Baker, J., & Cameron, M. (1996). The Effects of the Service Environment on Affect and Consumer Perception of Waiting Time: An Integrative Review and Research Propositions. Journal of the Academy of Marketing Science, 24(4), 338–349. https://doi.org/10.1177/0092070396244005
Black, J. (2013). The Origin of Music. Ancient-origins.net. Available at https://www.ancient-origins.net/ancient-places-europe/origin-music-00972?nopaging=1
Berinsky, A. J., Huber, G. and Lenz. G. (2012). Evaluating Online Labor Markets for Experimental Research: Amazon.com’s Mechanical Turk. Political Analysis 20(3), 351–68.
Bleich, S., Zillmann, D., & Weaver, J. (1991). Enjoyment and consumption of defiant rock music as a function of adolescent rebelliousness. Journal of Broadcasting & Electronic Media, 35(3), 351–366. https://doi.org/10.1080/08838159109364130
Broadbent, D. E. (1979). Human performance and noise. In C. M. Harris (Ed.), Handbook of noise control. New York: McGraw-Hill,
Bruner, G. C. (1990). Music, Mood, and Marketing. Journal of Marketing, 54(4), 94–104. https://doi.org/10.2307/1251762
Buhrmester, M., Kwang, T. & Gosling, S. (2011). Amazon’s Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data? Perspectives on Psychological Science 6(1), 3–5.
Davies, W.J., Adams, M.D., Bruce, N.S., Cain, R., Carlyle, A., Cusack, P., Hall, D.A., Hume, K.I., Irwin, A., Jennings, P., Marselle, M., Plack, C.J., Poxon, J., (2013). Perception of soundscapes: an interdisciplinary approach. Appl. Acoust. 74 (2), 224–231.
Droit-Volet, S., Ramos, D., Bueno, J. L. O., & Bigand, E. (2013). Music, emotion, and time perception: the influence of subjective emotional valence and arousal? Frontiers in Psychology, 4, 417. https://doi.org/10.3389/fpsyg.2013.00417
Engel, J. F., Blackwell, R. D., & Miniard, P. W. (1990). Consumer behavior (6th ed). Chicago : Dryden Press. Retrieved from https://trove.nla.gov.au/work/10524553
Fisher, S. A. (1972) “distraction effect” of noise bursts. Perception, 1, 223-236.
Fraisse, P. (1984). Perception and Estimation of Time. Annual Review of Psychology, 35(1), 1–37. https://doi.org/10.1146/annurev.ps.35.020184.000245
Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time Discounting and Time Preference: A Critical Review. Journal of Economic Literature, 40(2), 351–401. https://doi.org/10.1257/002205102320161311
Fried, R., & Berkowitz, L. (1979). Music Hath Charms … And Can Influence Helpfulness1. Journal of Applied Social Psychology, 9(3), 199–208. https://doi.org/10.1111/j.1559-1816.1979.tb02706.x
Gardner WJ, Licklider JC, Weisz AZ (1960) Suppression of pain by sound. Science, 132, 32–33.
Gorn, G. J. (1982). The effects of music in advertising on choice behavior: A classical conditioning approach. Journal of Marketing, 46(1), 94-101.
Guéguen, N., & Jacob, C. (2002). The Influence of Music on Temporal Perceptions in an on-hold Waiting Situation. Psychology of Music, 30(2), 210–214. https://doi.org/10.1177/0305735602302007
Gzyl, H., & Osuna, E. E. (2013). A further extension of Osuna’s model for psychological stress. International Journal of Contemporary Mathematical Sciences, 8, 801–814. https://doi.org/10.12988/ijcms.2013.3225
Hammond, C. (2013). Time Warped: Unlocking the Mysteries of Time Perception (Reprint edition). Edinburgh: Harper Perennial.
Hargreaves, D. J., & North, A. C. (Eds.). (1997). The Social Psychology of Music. Oxford, New York: Oxford University Press.
Hecker, S. (1984). Music for advertising effect. Psychology & Marketing, 1, 3-8.
Hill, C. (2016). The average American will spend 43 days of his life on hold. Retrieved 30 October 2017, from https://www.marketwatch.com/story/the-average-american-will-spend-43-days-of-his-life-on-hold-2016-02-04
Houston, M. B., Bettencourt, L. A., & Wenger, S. (1998). The relationship between waiting in a service queue and evaluations of service quality: A field theory perspective. Psychology and Marketing, 15(8), 735–753. https://doi.org/10.1002/(SICI)1520-6793(199812)15:8<735::AID-MAR2>3.0.CO;2-9
Hsu, D. Y., Huang, L., Nordgren, L. F., Rucker, D. D., & Galinsky, A. D. (2015). The Music of Power: Perceptual and Behavioral Consequences of Powerful Music. Social Psychological and Personality Science, 6(1), 75–83. https://doi.org/10.1177/1948550614542345
Hui, M. K., Thakor, M. V., & Gill, R. (1998). The Effect of Delay Type and Service Stage on Consumers’ Reactions to Waiting. Journal of Consumer Research, 24(4), 469–479. https://doi.org/10.1086/209522
Hui, M. K., & Tse, D. K. (1996). What to Tell Consumers in Waits of Different Lengths: An Integrative Model of Service Evaluation. Journal of Marketing, 60(2), 81–90. https://doi.org/10.2307/1251932
Kahneman D, Knetsch JL, Thaler RH. (1991). Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias. Journal of Economic Perspectives 5, 193-206
Kahneman, D. (2011). Thinking, fast and slow. Allen Lane.
Kellaris, J. J., & Mantel, S. P. (1994). The Influence of Mood and Gender on Consumers’ Time Perceptions. ACR North American Advances, NA-21. Retrieved from https://acrwebsite.org/volumes/7647/volumes/v21/NA-21
Kellaris, J. J., Mantel, S. P., & Altsech, M. B. (1996). Decibels, Disposition, and Duration: the Impact of Musical Loudness and Internal States on Time Perceptions. ACR North American Advances, NA-23. Retrieved from https://acrwebsite.org/volumes/7879/volumes/v23/NA-23
Kellaris, J. J., & Rice, R. C. (1993). The influence of tempo, loudness, and gender of listener on responses to music. Psychology & Marketing, 10(1), 15–29. https://doi.org/10.1002/mar.4220100103
Konecni, V. J. (1975). The mediation of aggressive behavior: Arousal level versus anger and cognitive labeling. Journal of Personality and Social Psychology, 32(4). Retrieved from https://psycnet.apa.org/record/1976-22361-001
Krishan, L. & Saxena, N. K. (1984) Perceived Time: Its Relatiosnhip with Locus of Control, Filled versus Unfilled Timer Intervals, and Perceiver’s Sex. Journal of General Psychology, 110, 275-281.
Leclerc, F., Schmitt, B., & Dubé, L. (1995). Waiting Time and Decision Making: Is Time like Money? Journal of Consumer Research,22(1), 110-119.
Lerner JS, Li Y, Weber EU. (2013). The financial costs of sadness. Psychological Science, 24, 72- 79
Lerner JS, Small DA, Loewenstein G. (2004). Heart strings and purse strings: Carryover effects of emotions on economic decisions. Psychological Science 15, 337-41
Lohr, S. (2012). Impatient Web Users Flee Slow-Loading Sites. The New York Times. Retrieved from https://www.nytimes.com/2012/03/01/technology/impatient-web-users-flee-slow-loading-sites.html
May, J. L., & Hamilton, P. A. (1980). Effects of musically evoked affect on women’s interpersonal attraction toward and perceptual judgments of physical attractiveness of men. Motivation and Emotion, 4(3), 217–228. https://doi.org/10.1007/BF00995420
Miller, E. G., Kahn, B. E., & Luce, M. F. (2008). Consumer Wait Management Strategies for Negative Service Events: A Coping Approach. Journal of Consumer Research, 34(5), 635–648. https://doi.org/10.1086/521899
Milliman, R. E. (1982). Using Background Music to Affect the Behavior of Supermarket Shoppers. Journal of Marketing, 46(3), 86–91. https://doi.org/10.2307/1251706
Milliman, R. E. (1986). The Influence of Background Music on the Behavior of Restaurant Patrons. Journal of Consumer Research, 13(2), 286–289.
Nielson, J. (1993). Response Time Limits: Article by Jakob Nielsen. Retrieved 30 October 2017, from https://www.nngroup.com/articles/response-times-3-important-limits/
Nielson, J. (1997). The Need for Speed. Retrieved 30 October 2017, from https://www.nngroup.com/articles/the-need-for-speed/
North, A. C., & Hargreaves, D. J. (1999). Can Music Move People?: The Effects of Musical Complexity and Silence on Waiting Time. Environment and Behavior, 31(1), 136–149. https://doi.org/10.1177/00139169921972038
North, A. C., Hargreaves, D. J., & Mckendrick, J. (1999). Music and on-hold waiting time. British Journal of Psychology, 90(1), 161–164. https://doi.org/10.1348/000712699161215
Oakes, S. (2003). Musical tempo and waiting perceptions. Psychology and Marketing, 20(8), 685–705. https://doi.org/10.1002/mar.10092
Park, C. W., & Young, S. M. (1986). Consumer response to television commercials: the impact of involvement and background music on brand attitude formation. Journal of Marketing Research, 23, 11-35.
Raghunathan R, Pham MT. (1999). All negative moods are not equal: Motivational influences of anxiety and sadness on decision making. Organizational Behavior and Human Decision Processes, 79, 56-77
Ramos, L.-V. (1993). The Effects of On-Hold Telephone Music on the Number of Premature Disconnections to a Statewide Protective Services Abuse Hot Line. Journal of Music Therapy, 30(2), 119–129. https://doi.org/10.1093/jmt/30.2.119
Roper, J. M., & Manela, J. (2000). Psychiatric patients’ perceptions of waiting time in the psychiatric emergency service. Journal of Psychosocial Nursing and Mental Health Services, 38(5), 18–27.
Sanders, A. F. (1961). The influence of noise on two discrimination tasks. Ergonomics, 1961, 4, 253-258.
Stack, S., & Gundlach, J. (1992). The Effect of Country Music on Suicide. Social Forces, 71(1), 211–218. https://doi.org/10.1093/sf/71.1.211
Stone, A. (2012, August 18). Opinion | Why Waiting in Line Is Torture. The New York Times. Retrieved from https://www.nytimes.com/2012/08/19/opinion/sunday/why-waiting-in-line-is-torture.html
Stout, P. A., & Leckenby, J. D. (1988). Let the music play: music as a nonverbal element in television commercials. InS. Hecker and D. W. Stewart (Eds.), Nonverbal Communication in Advertising, (pp.207-233). Lexington, MA: Lexington Books.
Stratton, V. N. (1992). Influence of music and socializing on perceived stress while waiting. Perceptual and Motor Skills, 75(1), 334. https://doi.org/10.2466/pms.1918.104.22.1684
Stratton, V. N., & Zalanowski, A. (1984). The Effect of Background Music on Verbal Interaction in Groups. Journal of Music Therapy, 21(1), 16–26. https://doi.org/10.1093/jmt/21.1.16
Sutter, M., Kocher, G. ,Rützler, D. & Trautmann, S.T., (2013) Impatience and Uncertainty: Experimental Decisions Predict Adolescents’ Field Behavior American Economic Review, 58(2), 56-69.
Taylor, S. (1994). Waiting for Service: The Relationship between Delays and Evaluations of Service. Journal of Marketing, 58(2), 56–69. https://doi.org/10.2307/1252269
Timex. (2012). Timex Group :: Press Announcement – September 25, 2012 :: Survey Results: Where Does the Time Go? Timex Releases Results of Survey Detailing How Americans Spend Their Time. Retrieved 30 October 2017, from https://timexgroup.com/news/press-20120925-survey-data.html
Wicke, D. M., Lorge, R. E., Coppin, R. J., & Jones, K. P. (1994). The effectiveness of waiting room notice-boards as a vehicle for health education. Family Practice, 11(3), 292–295.
Wolff, L. S., Massett, H. A., Weber, D., Mockenhaupt, R. E., Hassmiller, S., & Maibach, E. W. (2010). Opportunities and barriers to disease prevention counseling in the primary care setting: a multisite qualitative study with US health consumers. Health Promotion International, 25(3), 265–276. https://doi.org/10.1093/heapro/daq030
Woodhead, M.(1964). The effect of bursts of noise on an arithmetic task. American Journal of Psychology, 77, 627-633.
Yalch, R., & Spangenberg, E. (1990). Effects of Store Music on Shopping Behavior. Journal of Consumer Marketing, 7(2), 55–63. https://doi.org/10.1108/EUM0000000002577
Zakay, D. (1989). Chapter 10 Subjective Time and Attentional Resource Allocation: An Integrated Model of Time Estimation**The research reported in this chapter was supported by research grants from the Israeli Academy of Science and the Basic Research Fund of Tel-Aviv University. The author wishes to thank Iris Levin and Yehoshua Tsal for their helpful comments on the manuscript. In I. Levin & D. Zakay (Eds.), Advances in Psychology (Vol. 59, pp. 365–397). North-Holland. Retrieved from https://www.sciencedirect.com/science/article/pii/S016641150861047X
Zullow, H. M. (1991). Pessimistic rumination in popular songs and newsmagazines predict economic recession via decreased consumer optimism and spending∗. Journal of Economic Psychology, 12(3), 501–526. https://doi.org/10.1016/0167-4870(91)90029-S