1.4 Research questions and aims
This thesis had two main goals: (i) to gain a solid understanding of the role that behavioural economics can play to increase our understanding of music decision making, and (ii) to provide fruitful directions for future research. To achieve these goals, five research questions guided the present work:
• RQ1 - Where does music decision making sit within the music psychology literature?
• RQ2 - To date, which studies have utilised behavioural economics for research on music-related decision-making?
• RQ3 - How can insights from behavioural economics, such as bounded rationality, increase our understanding of musical behaviour?
• RQ4 - How can behavioural economics improve music-related decision making in real world applications?
• RQ5 - Which are the most fruitful areas for future research on the BEM?
Ten scientific publications were conducted to address these research questions (see section 2 for a summary of these studies highlighting their main contributions to the present thesis;
see Appendix A-J for the full texts). First, a bibliometric study visualizing all published literature on music psychology enabled the identification of an important gap in the music psychology literature, namely, a lack of a research agenda dedicated exclusively on music decision making (RQ1; see Appendix A for the full text). Second, a systematic literature review was conducted to provide an up-to-date account of all studies that have utilised behavioural economics for music research thus far (RQ2; Appendix B). The systematic review also identified fruitful avenues for future research on the BEM (RQ5). Furthermore, four empirical studies examined the role of bounded rationality and related concepts to increase our understanding of music decision making (RQ3; Appendix C-F). Finally, four studies focused on applying insights from behavioural economics to improve music-related decision making in real world situations (RQ4; Appendix G-J).
Chapter 2
Scientific Publications
This thesis was written cumulatively and comprises a total of ten scientific publications (seven are published in scientific journals and three were in preparation at the time this thesis was submitted). The full texts of the ten publications are provided in the appendices of this thesis as pre-prints. This section briefly summarises these publications (see Table 2.1 for a list of publications), highlighting their main contribution to the BEM. Although the methods and scientific goals of these studies are diverse, they can be categorised into three groups depending on how they support this thesis: Why the BEM? (see section 2.1), bounded rationality in music decision making (see section 2.2), and real world applications (see section 2.3).
10 Psychology: A Bibliometric Analysis of Psychology of Music, Music Perception, and Musicae Scientiae from 1973 to 2017. Music & Science, 2, 2059204318811786. https://doi.org/10.1177/2059204318811786
Anglada-Tort, M., Masters, N., Steffens, J., North, A., & Müllensiefen, D. (in prep.). The Behavioural Economics of Music: Systematic Literature Review and Future Directions. Manuscript in preparation.
Anglada-Tort, M., & Müllensiefen, D. (2017). The repeated recording illusion: the effects of extrinsic and individual difference factors on musical judgments. Music Perception: An Interdisciplinary Journal, 35(1), 94-117.
https://doi.org/10.1525/mp.2017.35.1.94
Anglada-Tort, M., Baker, T., & Müllensiefen, D. (2019). False mem- ories in music listening: exploring the misinformation effect and individual difference factors in auditory memory. Memory, 27(5), 612-627.
https://doi.org/10.1080/09658211.2018.1545858
Steffens, J., Till, N., & Anglada-Tort, M. (in prep.). I know that song: The effect of name recognition on listener choices when searching for music in playlists. Manuscript in preparation.
Anglada-Tort, M., Keller, S., Steffens, J., & Müllensiefen, D. (2020).
The impact of source effects on the evaluation of music for advertising:
Are there differences in how advertising professionals and consumers judge music? Advanced online publication, Journal of Advertising Research. http://dx.doi.org/10.2501/JAR-2020-016
Anglada-Tort, M., Schofield, K., Tabitha, T., & Müllensiefen, D. (in prep.). I’ve heard that brand before: The effect of music as a recognition cue to influence consumer choice. Manuscript in preparation.
Anglada-Tort, M., Thueringer, H., & Omigie, D. (2019). The busking experiment: A field study measuring behavioural responses to street music performances. Psychomusicology: Music, Mind, and Brain, 29(1), 46. https://doi.org/10.1037/pmu0000236
Anglada-Tort, M., Krause, K., & North, A. C. (2019). Popular music lyrics and musicians’ gender over time: A computational approach.
Psychology of Music. 0305735619871602.
https://doi.org/10.1177/0305735619871602
11 2.1 Why the BEM?
2.1 Why the BEM?
To understand the need and value of the BEM, two literature reviews were conducted addressing three research questions (see Table 2.1; RQ1, 2 and 5). The first literature review identified a notable gap in the music psychology literature, showing that to date, there is no research agenda dedicated exclusively to decision making in the context of music (RQ1).
The second review constitutes one of the core parts of this thesis, providing an up-to-date account of studies utilising behavioural economics for research on music decision making (RQ2), as well as identifying fruitful avenues for future research on the BEM (RQ5).
2.1.1 Visualizing music psychology (S1)
This study aimed to analyse all literature published in the three most prominent scientific journals in the field of music psychology (see Appendix A for the full text). Namely, Psychology of Music, Music Perception, and Musicae Scientiae. Using all available literature in Scopus, a total of 2,089 peer-reviewed articles, 2,632 authors, and 49 countries were analysed, covering a period of 44 years (1973–2017). Visualization and bibliometric techniques were used to investigate the growth of publications, author and country productivity, collaborations, and research trends. Thus, the results of this study present objective and measurable patterns seen across the development of music psychology research included within these three journals. For example, from 1973 to 2017, there was a clear increase in music psychology research, with a total growth rate of 11%. A core feature of this paper is the visualization network map of music psychology (see Figure2.1). The network map shows the most influential keywords in the literature (i.e., keywords used by the authors to define their publications) as well as how they co-occur with others, creating different research trends and themes. For instance, the keywords “music” and “emotion” are the most influential keywords in the literature, which is in line with the general interest and significant increase in research on music and emotion (e.g., Eerola & Vuoskoski, 2013). The map also provides an overlay visualization that adds a time dimension to each keyword (i.e., colour-coding each keyword based on the average publication year), which suggests different trends in the popularity of each keyword over time. Thus, the network map is useful in summarizing the complex field of music psychology in a single picture.
Overall, this study contributed to the literature by providing the first large-scale bibliometric analysis that investigates general research trends and gaps in the field of music psychology.
Using bibliometric techniques to visualize the past and present of research in music psychology enables critical observations and conclusions, opening many interesting avenues for future research in the field. In the context of the BEM, this was important to identify a gap in the literature. Namely, there is currently no research agenda dedicated exclusively to study decision making in music. Despite this, decision making is inherent to many of the influential concepts and research trends identified in the study, including, music performance, creativity, improvisation, perception, music preference, music listening, and
12 2.1 Why the BEM?
music therapy.
Fig. 2.1 Network visualization map of keyword co-occurrences in music psychology.
The map shows the 75 most influential keywords used by researchers to describe their articles and how often they co-occur with others, indicating main research trends and themes in music psychology. The width of the line shows the strength of the co-occurrence between keywords, while the size of the circle indicates the total
number of occurrences. The colour of the circle indicates the average year of publications.
2.1.2 The Behavioural Economics of Music (S2)
This paper is the core theoretical contribution of this thesis. The paper conducted a systematic literature review to provide an up-to-date account of studies utilising behavioural economics to investigate music decision making (see Appendix B for the full text). Using a robust search strategy that is highly representative of the behavioural economics literature, the systematic review identified a total of 33 papers within four BEM areas that readily apply to music decision making. Thus, the paper is organised around these areas, enabling the reader to fully understand the scope of existing research as well as giving direction for future research within each area. The main findings, organised by BEM area, are summarised below:
1. Heuristics and biases: the systematic review identified 16 studies applying six cog- nitive biases and heuristics to various aspects of musical behaviour (see Table 2.2 for definitions and music examples). Several studies confirmed that individuals rely on judgmental heuristics when listening to and evaluating music, allowing them to simplify complex decisions into easier-to-calculate operations, but also leading to systematic errors. Studies on processing fluency showed that fluency manipulations in music, such as repetition and consonance, can
13 2.1 Why the BEM?
influence music perception and, in turn, affect preferential judgments. Finally, studies on framing effects found that presenting the same music stimuli with different contextual information can systematically change a person’s preferences for the music.
2. Social decision making: nine studies showed that music decision-making is largely influenced by social preferences and information. Firstly, social preferences, such as reciprocity and guilt, are important to understand consumers’ motivation to engage in different revenue models for music consumption, including voluntary payments for music. Social preferences can also help better understand pricing strategies in the concert industry. Secondly, peer effects can play a determinant role in music preferences and choices, which in turn can influence the music market and determine outcomes such as the next successful artist or hit song.
3. Behavioural time preferences: four studies found that behavioural time preferences can give a deeper insight into how music is valued and consumed over time. Two studies found that when consuming music online, consumers disproportionally prioritise im- mediate benefits over future gains, providing solid evidence for hyperbolic discounting in music consumption.
The two other studies focused on time preferences for music consumption in terms of its hedonic value. They showed that listeners’ ability to predict pleasure in their future music consumption is rather low and when choosing music repeatedly over time, listeners do not always choose music that maximizes their pleasure but instead seek variety.
4. Dual-process theory: four studies showed that exploring the interaction between System-1 and System-2 processes in the brain can help increase our understanding of how musicians make decisions while performing, as well as the mediating role of music expertise.
14 2.1 Why the BEM?
Overall, the examination of these studies enabled to gain a solid understanding of the role that behavioural economics has played in music research thus far. Furthermore, it was clear from the review that the BEM is a relatively new approach and behavioural economics has just begun to be applied in the domain of music. For example, the vast majority of the retrieved studies were published in the last 10 years and over half of them in the last five years. The findings also suggested that the BEM is fairly multi-disciplinary. While half of the studies came from the music psychology literature, the other half came from behavioural economics. Finally, the paper concluded by providing fruitful ideas and directions for future research, both within the identified BEM areas and beyond.
Table 2.2 Heuristics and biases identified in the systematic review (S2).
Definition Music Example
Human tendency to evaluate easy-to-process information more positively than similar but more difficult-to-process information (Reber et al., 2004).
When judging the frequency and probability of events, people rely on the ease with which examples come to their minds (Tversky &
Kahneman, 1974).
People estimate the likelihood of an event by comparing it to an existing event of similar characteristics that already exists in their minds (Tversky & Kahneman, 1974).
Human tendency to rely heavily upon our emotional state when making judgments and decisions (Slovic et al., 2002). how they felt at its peak (i.e., the most intense point) and at its end (Kahneman &
Listeners falsely remember sounds that come easily to their minds (Vuvan et al.,
Listeners evaluate a music experience based on the most intense moment and at the end (Rozin, et al., 2004).
15 2.2 Bounded rationality in music decision making
2.2 Bounded rationality in music decision making
To further develop the BEM within this thesis, four empirical studies explored whether bounded rationality and related insights from behavioural economics may prove valuable for music research (RQ3). The four studies showed that when making musical judgments and decisions, listeners are limited by their mental capacity (e.g., memory constraints), time, and information available (e.g., song titles, post-event information, or descriptions about the performer). Consequently, listeners rely on cognitive biases and heuristics that do not depend on the music stimuli themselves.
2.2.1 The repeated recording illusion (S3)
This study investigated the extent to which listeners are limited by memory constraints and the context when evaluating music performance (see Appendix C for the full text). To do so, a novel experimental paradigm was developed, namely, the repeated recording illusion.
In this paradigm, participants (N= 72) were told to listen to three “different” musical performances of an original piece. However, unbeknownst to them, they were exposed to the same repeated recording three times in succession. Each time, the recording was accompanied by a text suggesting a low, medium, or high prestige of the performer.
Participants evaluated the music using several rating scales (i.e., liking, timing, tone quality, pitch accuracy, emotional quality, and overall quality). The procedure was repeated using a piece of highly familiar rock music and a piece of unfamiliar classical music. Potentially related extrinsic factors (i.e., explicit information and repeated exposure) and individual differences were investigated.
Results showed that most participants (75%) believed that they had heard different musical performances while, in fact, they were identical. In the two music conditions, participants evaluated the same recording significantly more positively when it was presented with a high-prestige text compared to low and medium texts. However, the position of the recording only had a significant impact on the familiar music condition. To capture higher-order interactions between extrinsic and individual difference factors, a regression tree model based on permutation tests was computed. The dependent variable was a one-factor solution indicated by a Principal Component Analysis, where a negative score indicated an overall negative evaluation and a positive score an overall positive evaluation. The predictor variables were prestige effect, the position of the recording, music conditions (classical-unfamiliar vs. rock-familiar), and seven individual difference variables, including age, personality, and musicality. Figure2.2 shows the structure of the regression tree the model, which shows that only 3 of the predictor variables had a significant impact on performance evaluation, i.e., explicit information, repeated exposure, and the music condition. Note that none of the individual differences were significant predictors.
Overall, these findings highlight the fallibility of music evaluation and support the notion of bounded rationality in musical behaviour, showing that musical judgments are limited by
16 2.2 Bounded rationality in music decision making
memory constraints, cognitive biases, and the context. The influence of explicit information and the partial effect of repeated exposure are discussed in terms of the anchoring heuristic (Tversky & Kahneman, 1974) and processing fluency (Reber, Schwarz, & Winkielman, 2004).
Fig. 2.2 The influence of non-musical factors on music performance evaluation.
The regression tree model is useful in identifying the most predictive variables influencing music performance evaluation, as well as specific conditions that lead to particularly high (left node, 3) and low (right node, 9) ratings. The tree model can be interpreted by starting at the top and following each branch down, to arrive at a
terminal node. A path to a terminal node describes the interaction of experimental conditions that lead to a particular subset of ratings.
17 2.2 Bounded rationality in music decision making
2.2.2 False memories in music listening (S4)
When people listen to music or experience music in a live performance, they are normally exposed to related information at some point after the event. This study examined for the first time whether post-event misinformation can induce false memories in music (see Appendix D for the full text). Though misinformation effects have been demonstrated extensively within visual tasks, they have not yet been explored in the realm of non-visual auditory stimuli. Besides, the study explored individual difference factors potentially associated with false memory susceptibility in music, including age, suggestibility, personality, and musical training. In two music recognition tasks, participants (N = 151) listened to an initial music track, which unbeknownst to them was missing an instrument.
They were then presented with post-event information which either did or did not suggest the presence of the missing instrument. The presence of misinformation resulted in significantly poorer performance on the music recognition tasks (d = .43), suggesting the existence of false musical memories. A random forest analysis indicated that music expertise was not significantly associated with misinformation susceptibility. These findings support previous research on the fallibility of human memory and demonstrate, to some extent, the generality of the misinformation effect to a non-visual auditory domain. In the context of the BEM, this is important to further support the notion of bounded rationality in music decision making, in particular demonstrating the fallibility of memory-based judgments of music.
2.2.3 Names and titles matter: Linguistic fluency and the affect heuris- tic (S5)
This study manipulated the song titles and artist names presented with music to examine the influence of two well- known heuristic principles on aesthetic and value judgments of music:
processing fluency (Experiment 1) (Reber et al., 2004) and the affect heuristic (Experiment 2) (Slovic, Finucane, Peters, & MacGregor, 2002) (see Appendix E for the full text). In Experiment 1, the same music excerpts were presented with easy-to-pronounce (fluent) and difficult-to-pronounce (disfluent) names. The names consisted of a list of Turkish names that were shown in a previous study to be fluent or disfluent to English speakers (Shah &
Oppenheimer, 2007). Native English-speaking participants (N= 48) listened to the music stimuli and provided evaluations on different scales measuring aesthetic properties (e.g., like, emotional expressivity, quality) and subjective value of the music (e.g., likelihood to attend a concert of the artists or to recommend the song to a friend). Results indicated a main significant effect of fluency. In particular, participants evaluated the same music excerpts significantly more positively when presented with fluent names than when presented with disfluent names.
In Experiment 2 (N= 100), the same procedure was used, but instead manipulating the emotional content of the titles. Thus, the music excerpts were presented with positive (e.g.,
18 2.2 Bounded rationality in music decision making
Kiss), negative (e.g., Suicide), and neutral (e.g., Window) titles. This time, at the end of the experiment, participants also performed an unexpected free recall task (i.e., write down the songs they remembered). In both aesthetic and subjective value evaluations, presenting the music with negative titles resulted in the lowest judgments. When looking at the effects of emotionality on memory, results showed that music excerpts presented with neutral and negative titles were remembered significantly more often than positive titles.
Overall, these findings suggest that like any other human judgments, evaluations of music also rely on heuristic principles that do not necessarily depend on the aesthetic stimuli themselves. These heuristics operate even when the information processed is minimal, such as changing the linguistic properties of titles presented with music.
2.2.4 The effect of name recognition on listener choices (S6)
When searching for and choosing music in playlists, individuals may rely on judgment heuristics to make fast (in terms of computing time) and frugal (in the use of information) decisions. This study addressed this issue by investigating for the first time the role of the recognition heuristic on musical choices when listeners search for music in playlists (see
When searching for and choosing music in playlists, individuals may rely on judgment heuristics to make fast (in terms of computing time) and frugal (in the use of information) decisions. This study addressed this issue by investigating for the first time the role of the recognition heuristic on musical choices when listeners search for music in playlists (see