3 Discussion 25
3.4 Conclusion
Austin, Renwick, & McPherson, 2006; Renwick & Reeve, 2012, for reviews). However, it remains unclear why some individuals manage to persist through the challenges of learning and practicing, whereas others eventually quit. Research on behavioural time preferences can offer valuable insights to this issue. For example, research on delay discounting provides a unifying theoretical approach that that has been successfully applied to a number of similar issues in psychology, including those related to health, self-control, impulsivity, and risk taking (see Green & Myerson, 2004; Koffarnus, Jarmolowicz, Mueller, & Bickel, 2014;
Peters & Büchel, 2011; Reynlods, 2006, for reviews). In the context of music education, delay discounting predicts that in impatient students, the short-term temptation (e.g., quit- ting or not practising enough) foregoes the long-term goal (e.g., learning how to play an instrument). More importantly, the relationship between time and subjective reward can be modelled accurately using mathematical functions with few parameters, such as discount rate (how fast an individual’s subjective value decreases over time), which is associated with impulsivity and impatience (see Peters & Büchel, 2011, for a review). Thus, there is great potential for future research looking at whether the rate of delay discounting can be a reliable trait marker for music practice and learning. By incorporating such insights, one could help improve current educational methods in music, decreasing dropout rates and increasing the learning experience. For instance, there is evidence that framing effects and episodic future thinking can reduce significantly delay discounting (Koffarnus et al., 2014), as the better that individuals can imagine future outcomes, the more they value them.
3.4 Conclusion
Music psychology has examined various aspects of decision making related to musical behaviour using a wide variety of methods and techniques (see Deutsch, 2013; Hallam et al., 2016; Tan et al., 2017, for reviews). This body of research, however, would benefit from using a more sophisticated and unified framework dedicated exclusively on the study of music decision making, as well as incorporating insights from social sciences and economics. In contrast, economists have investigated music-related decision making with a focus on rational economic analysis instead of the psychological underpinnings known to be involved in music perception, cognition, and behaviour (see Byun, 2016; Cameron, 2016;
Krueger, 2005; Tschmuck, 2017, for reviews). To bridge this gap, this thesis proposes the BEM, a novel research framework that integrates knowledge from psychology, economics, and other disciplines to increase our understanding of human behaviours related to music.
Ten scientific publications (see Table 2.1 for a list of publications; see Appendix A-J for the full texts) were conducted to demonstrate the value of this novel approach, generating new insights into the study of music decision making.
The BEM has both theoretical and practical implications. First, it offers a multidisciplinary but unified framework to understand and improve music decision making in a variety of areas. Second, it merges two distinct bodies of research that have been largely unconnected
38 3.4 Conclusion
in the literature thus far. In particular, the BEM moves away from the rigid neoclassical assumption of rationality by incorporating insights from psychology, while still relying on falsifiable models from standard economics that are mathematically rigorous and can prove significant to address key problems in music research. Third, the BEM offers a solid understanding of those areas in behavioural economics that readily apply to music decision making, but also provides valuable directions for future research aiming to explore new areas, such as neuroeconomics, behavioural pricing, and behavioural game theory. These avenues for future research can improve our current knowledge in many areas within music psychology, including music composition and improvisation, performance evaluation, music preferences and consumption, and music education. Finally, since music is a potent and highly emotional stimulus, investigating music decision making can provide a novel testing ground for general theories on human behaviour and decision making. Thus, the BEM can be used as a toolkit to generate new ideas and accelerate progress in any area concerned with human behaviours related to music.
References
Allan, D. (2007). Sound Advertising: A Review of the Experimental Evidence on the Effects of Music in Commercials on Attention, Memory, Attitudes, and Purchase Intention.
Journal of Media Psychology, 12(3), 1–37.
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. doi:10.1525/mp.2017.35.1.94
Angner, E. (2012). A course in behavioral economics. Macmillan International Higher Education.
Ariely, D. (2008). Predictably irrational. Harper Audio.
Arne Brekke, K., & Johansson-Stenman, O. (2008). The behavioural economics of climate change. Oxford Review of Economic Policy, 24(2), 280–297. doi:10.1093/oxrep/grn012 Ashley, R. (2016). Musical Improvisation. In S. Hallam, I. Cross, & M. Thaut (Eds.), The
oxford handbook of music psychology. Oxford University Press.
Austin, J. R., Renwick, J. M., & McPherson, G. E. (2006). Developing motivation. In G. E. McPherson (Ed.), The child as musician: A handbook of musical development (pp. 213–238). Oxford University Press.
Beaty, R., Frieler, K., Norgaard, M., & Merseal, H. (2020). Spontaneous melodic productions of expert musicians contain sequencing biases seen in language production. Retrieved from https://osf.io/p8gmj/download
Blumenthal-Barby, J. S., & Krieger, H. (2015). Cognitive biases and heuristics in medical decision making: A critical review using a systematic search strategy. Medical Decision Making, 35(4), 539–557. doi:10.1177/0272989X14547740
Bradlow, E. T., & Fader, P. S. (2001). A bayesian lifetime model for the “hot 100” billboard songs. Journal of the American Statistical Association, 96(454), 368–381. doi:10.1198/
016214501753168091
Burke, A. E. (1996). How effective are international copyright conventions in the music industry? Journal of Cultural Economics, 20(1), 51–66. doi:10.1007/s10824-005- 1060-z
Byun, C. H. C. (2016). The economics of the popular music industry. Springer.
Cameron, S. (2015). Music in the marketplace: a social economics approach. doi:10.5860/
choice.192595
Cameron, S. (2016). Past, present and future: music economics at the crossroads. Journal of Cultural Economics, 40(1), 1–12. doi:10.1007/s10824-015-9263-4
Cartwright, E. (2018). Behavioral Economics. Routledge.
Chernev, A., Böckenholt, U., & Goodman, J. (2012). Choice overload: A conceptual review and meta-analysis. 25(2), 333–358. doi:10.1016/j.jcps.2014.08.002
Coleman, J., & Fararo, T. (1992). Rational choice theory. Sage Publications.
40 References
Dawes, R., & Hastie, R. (2010). Rational choice in an uncertain world: The psychology of judgment and decision making. Sage Publications.
Decrop, A., & Derbaix, M. (2014). Artist-Related Determinants of Music Concert Prices.
Psychology and Marketing, 31(8), 660–669. doi:10.1002/mar.20726
Dellavigna, S. (2009). Psychology and economics: Evidence from the field. Journal of Economic Literature, 47(2), 315–372. doi:10.1257/jel.47.2.315
Deutsch, D. (2013). Psychology of music. Elsevier.
Dhami, S. (2016). The foundations of behavioral economic analysis. Oxford University Press.
Dimaggio, P., & Mukhtar, T. (2004). Arts participation as cultural capital in the United States, 1982-2002: Signs of decline? Poetics, 32, 169–194. doi:10.1016/j.poetic.2004.02.005 Eerola, T., & Vuoskoski, J. K. (2013). A review of music and emotion studies: Approaches, emotion models, and stimuli. Music Perception, 30(3), 307–340. doi:10.1525/MP.2012.
30.3.307
Elliott, C. (1995). Race and Gender as Factors in Judgments of Musical Performance. Bulletin of the Council for Research in Music Education, (127), 50–56.
Elliott, C., & Simmons, R. (2011). Factors determining UK album success. Applied Eco- nomics, 43(30), 4699–4705. doi:10.1080/00036846.2010.498349
Evans, J. S. B. T. (2008). Dual-Processing Accounts of Reasoning, Judgment, and Social Cognition. Annual Review of Psychology, 59(1), 255–278. doi:10.1146/annurev.psych.
59.103006.093629
Fehr, E., & Rangel, A. (2011). Neuroeconomic Foundations of Economic Choice—Recent Advances. Journal of Economic Perspectives, 25(4), 3–30. doi:10.1257/jep.25.4.3 Flôres, R. G., & Ginsburgh, V. A. (1996). The Queen Elisabeth Musical Competition How
fair is the final ranking. Journal of the Royal Statistical Society, 45, 97–104.
Frederiks, E. R., Stenner, K., & Hobman, E. V. (2015). Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour. 41, 1385–1394. doi:10.1016/j.rser.2014.09.026
Glimcher, P. W., & Fehr, E. (2014). Neuroeconomics: Decision making and the brain.
doi:10.1016/B978-0-12-416008-8.00003-6
Goldstein, D. G., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109(1), 75–90. doi:10.1037/0033-295x.109.1.75 Greb, F., Schlotz, W., & Steffens, J. (2018). Personal and situational influences on the
functions of music listening. Psychology of Music, 46(6), 763–794. doi:10.1177/
0305735617724883
Griffiths, N. K. (2008). The effects of concert dress and physical appearance on perceptions of female solo performers. Musicae Scientiae, 2, 273–290. doi:https://doi.org/10.1177/
102986490801200205
Hallam, S., Cross, I., & Thaut, M. (2016). Oxford handbook of music psychology (second edition). Oxford University Press.
Hendricks, K., & Sorensen, A. (2009). Information and the Skewness of Music Sales. Journal of Political Economy, 117(2), 324–369. doi:10.1086/599283
Hiller, R. S. (2016). The importance of quality: How music festivals achieved commercial success. Journal of Cultural Economics, 40(3), 309–334. doi:10.1007/s10824-015- 9249-2
Holt, F. (2010). The economy of live music in the digital age. European Journal of Cultural Studies, 13(2), 243–261. doi:10.1177/1367549409352277
41 References
IFPI. (2019). International Federation of the Phonographic Industry (IFPI) Global Music Report 2018. Retrieved from http://www.ifpi.org/downloads/GMR2019.pdf
Impett, J. (2016). Making a mark: the psychology of composition. In S. Hallam, I. Cross, &
M. Thaut (Eds.), The oxford handbook of music psychology. Oxford University Press.
Jabbar, H. (2011). he behavioral economics of education: New directions for research.
Educational Researcher, 40(9), 446–453.
Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics.
American Economic Review, 93(5), 1449–1475.
Kahneman, D. (2011). Thinking , Fast and Slow. Macmillan.
Kolb, B. M. (2000). You call this fun? Reactions of young first-time attendees to a classical concert. MEIEA Journal, 1(2), 13–29.
Konecˇni, V. (1982). Social interaction and musical preference. In D. Deutsch (Ed.), The psychology of music (pp. 497–516). Academic Press.
Konecni, V. J., & Sargent-Pollock, D. (1976). Choice between melodies differing in complex- ity under divided-attention conditions. Journal of Experimental Psychology: Human Perception and Performance, 2(3), 347–356. doi:10.1037/0096-1523.2.3.347
Koschate-Fischer, N., & Wüllner, K. (2017). New developments in behavioral pricing re- search. Journal of Business Economics, 87(6), 809–875. doi:10.1007/s11573-016- 0839-z
Krueger, A. B. (2005). The economics of real superstars: The market for rock concerts in the material world. Journal of Labor Economics, 23(1), 1–30. doi:10.1086/425431 Lamont, A., & Greasley, A. (2016). Musical preferences. In S. Hallam, I. Cross, & M. Thaut
(Eds.), The oxford handbook of music psychology. Oxford University Press.
Lamont, A., Greasley, A., & Sloboda, J. (2016). Choosing to Hear Music. In S. Hallam, I. Cross, & M. Thaut (Eds.), The oxford handbook of music psychology (pp. 1–20).
Oxford University Press.
Lantos, G. P., & Craton, L. G. (2012). A model of consumer response to advertising music.
Journal of Consumer Marketing, 29(1), 22–42. doi:10.1108/07363761211193028 Larsen, G., & Hussels, S. (2011). The significance of commercial music festivals. In S.
Cameron (Ed.), Handbook on the economics of leisure (pp. 250–270). doi:10.4337/
9780857930569.00022
Liebowitz, S. J. (2004). Will MP3 downloads annihilate the record industry? The evidence so far. Advances in the Study of Entrepreneurship, Innovation, and Economic Growth, 15, 229–260. doi:10.1016/S1048-4736(04)01507-3
Liebowitz, S. J. (2006). File sharing: Creative destruction or just plain destruction? Journal of Law and Economics, 49(1), 1–28. doi:10.1086/503518
Linnemann, A., Wenzel, M., Grammes, J., Kubiak, T., & Nater, U. M. (2018). Music listening and stress in daily life—a matter of timing. International Journal of Behavioral Medicine, 25(2), 223–230. doi:10.1007/s12529-017-9697-5
Lonsdale, A. J., & North, A. C. (2012). Musical taste and the representativeness heuristic.
Psychology of Music, 40(2), 131–142. doi:10.1177/0305735611425901
Maeshiro, T., Nakayama, S. I., & Maeshiro, M. (2011). Representation of decision making process in music composition based on hypernetwork model. In Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) (Vol. 6771 LNCS, pp. 109–117). doi:10.1007/978-3-642- 21793-7_13
Maymin, P. (2012). Music and the market: Song and stock volatility. North American Journal of Economics and Finance, 23(1), 70–85. doi:10.1016/j.najef.2011.11.004
42 References
Mortimer, J. H., Nosko, C., & Sorensen, A. (2012). Supply responses to digital distribution:
Recorded music and live performances. Information Economics and Policy, 24(1), 3–
14.
North, A. C., & Hargreaves, D. J. (1999). Music and driving performance. Scandinavian Journal of Psychology, 40, 285–292.
North, A. C., & Hargreaves, D. J. (2000). Musical preferences during and after relaxation and exercise. The American Journal of Psychology, 113(1).
North, A. C., & Hargreaves, D. J. (2008). The social and applied psychology of music. OUP Oxford.
Oakes, S. (2007). Evaluating Empirical Research into Music in Advertising: A Congruity Perspective. Article in Journal of Advertising Research, 47(1), 38–50. doi:10.2501/
S0021849907070055
Oberholzer-Gee, F., & Strumpf, K. (2009). File sharing and copyright. Innovation Policy and the Economy, 10, 19–55. doi:10.1086/605852
Oeusoonthornwattana, O., & Shanks, D. R. (2010). I like what I know: Is recognition a non-compensatory determiner of consumer choice? Judgment and Decision Making, 5(4), 310–325.
Peters, J., & Büchel, C. (2011). The neural mechanisms of inter-temporal decision-making:
understanding variability. Trends in cognitive sciences, 15(5), 20–37.
Pettijohn, T. F., Eastman, J. T., & Richard, K. G. (2012). And the Beat Goes On: Popular Billboard Song Beats Per Minute and Key Signatures Vary with Social and Economic Conditions. Current Psychology, 31, 313–317. doi:10.1007/s12144-012-9149-y Pettijohn, T. F., & Sacco, D. F. (2009). The Language of lyrics An analysis of popular
Billboard songs across conditions of social and economic threat. Journal of Language and Social Psychology, 28, 297–311. doi:10.1177/0261927X09335259
Pope, D. G., Price, J., & Wolfers, J. (2013). Awareness Reduces Racial Bias. Management Science, 64(11), 4988–4995.
Rayna, T., & Striukova, L. (2009). Monometapoly or the Economics of the Music Industry.
Prometheus, 27(3), 211–222. doi:10.1080/08109020903127778
Reber, R., Schwarz, N., & Winkielman, P. (2004). Processing fluency and aesthetic pleasure:
Is beauty in the perceiver’s processing experience? Personality and Social Psychology Review, 8(4), 364–382. doi:10.1207/s15327957pspr0804_3
Renwick, J. M., & Reeve, J. (2012). Supporting motivation in music education. In G. E.
McPherson & G. F. Welch (Eds.), Oxford handbook of music education (pp. 143–162).
Oxford University Press.
Rice, T. (2013). The Behavioral Economics of Health and Health Care. Annual Review of Public Health, 34(1), 431–447. doi:10.1146/annurev-publhealth-031912-114353 Saarikallio, S., & Erkkilä, J. (2007). The role of music in adolescents’ mood regulation.
Psychology of Music, 35(1), 88–109. doi:10.1177/0305735607068889
Salimpoor, V. N., van den Bosch, I., Kovacevic, N., McIntosh, A. R., Dagher, A., & Zatorre, R. J. (2013). Interactions between the nucleus accumbens and auditory cortices predict music reward value. Science, 340(6129), 216–219. doi:10.1126/science.1231059.
arXiv: arXiv:1011.1669v3
Samson, A. (2017). The Behavioral Economics Guide 2017. Behavioral Science Solutions Ltd.
Schramm, H., & Spangardt, B. (2016). Wirkung von Musik in der Werbung [Effects of music in advertising]. In Handbuch werbeforschung (Siegert, G, pp. 433–449). Wiesbaden, Germany: Springer VS.
43 References
Shah, A. K., & Oppenheimer, D. M. (2007). Easy does it: The role of fluency in cue weighting.
Judgment and Decision Making, 2(6), 371–379.
Simon, H. A. (1955). A Behavioral Model of Rational Choice. The Quarterly Journal of Economics, 69(1), 99–118. doi:10.2307/1884852
Simon, H. A. (1982). Models of Bounded Rationality. MIT press.
Slovic, P., Finucane, M., Peters, E., & MacGregor, D. G. (2002). Rational actors or rational fools: Implications of the effects heuristic for behavioral economics. Journal of Socio- Economics, 31(4), 329–342. doi:10.1016/S1053-5357(02)00174-9
Stevans, L. K., & Sessions, D. N. (2005). An empirical investigation into the effect of music downloading on the consumer expenditure of recorded music: A time series approach.
Journal of Consumer Policy, 28(3), 311–324. doi:10.1007/s10603-005-8645-y Strobl, E. A., & Tucker, C. (2000). The dynamics of chart success in the U.K. pre-recorded
popular music industry. Journal of Cultural Economics, 24(2), 113–134. doi:10.1023/
A:1007601402245
Sweeting, A. (2013). Dynamic Product Positioning in Differentiated Product Markets: The Effect of Fees for Musical Performance Rights on the Commercial Radio Industry.
Econometrica, 81(5), 1763–1803. doi:10.3982/ECTA7473
Tahler, R. (2015). Misbehaving: The Making of Behavioral Economics. WW Norton.
Tan, S., Pfordresher, P., & Harré, R. (2017). Psychology of music: From sound to significance.
Routledge.
Thaler, R. (1985). Mental Accounting and Consumer Choice. Marketing Science, 4(3), 199–
214. doi:10.1287/mksc.4.3.199
Tschmuck, P. (2017). The economics of music. Agenda Publishing.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232. doi:10.1016/0010-0285(73)90033-9 Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases.
Science, 185(4157), 1124–31. doi:10.1126/science.185.4157.1124
Varian, H. R. (2005). Copying and copyright. Journal of Economic Perspectives, 19(2), 121–138. doi:10.1257/0895330054048768
Waddell, G. (2018). Time to decide: A study of evaluative decision-making in music perfom- rance (Doctoral dissertation, Royal College of Music).
Wöllner, C., & Behne, K.-E. (2011). Seeing or hearing the pianists? A synopsis of an early audiovisual perception experiment and a replication. Musicae Scientiae, 15(3), 324–
342. doi:10.1177/1029864911410955
Zatorre, R. J., & Zald, D. H. (2011). Music. In J. A. Gottfried (Ed.), Neurobiology of sensation and reward. CRC Press.
Zullow, H. M. (1991). Pessimistic rumination in popular songs and news magazines pre- dict economic recession via decreased consumer optimism and spending. Journal of Economic Psychology, 12(3), 501–526.
Appendix A
Visualizing music psychology (S1)
This is an Accepted Manuscript of an article published by SAGE in Music & Science on 25th of January 2019. ©The Author(s) 2019. Reprinted by permission of SAGE Publications1, and available online: https://doi.org/10.1177/2059204318811786. The paper is not the copy of the record and may not exactly replicate the authoritative document published in the journal. For presentation in this thesis, the appendices of the paper have been removed and the passages referring to each Appendix in the text modified to indicate where to find the materials online. Moreover, there may be minor modifications in the text to guarantee a consistent typographic style throughout the thesis, such as the position of figures and tables. Please do not copy or cite without author’s permission.
Citation
Anglada-Tort, M., & Sanfilippo, K. R. M. (2019). Visualizing Music Psychology: A Bibliometric Analysis of Psychology of Music, Music Perception, and Musicae Scientiae from 1973 to 2017. Music & Science, 2, 2059204318811786. DOI:
https://doi.org/10.1177/2059204318811786.
Author contribution
The paper was written together with Dr. Sanfilippo (Goldsmiths, University of London). I conceived of the idea and the analysis strategy for the study, whereas all other aspects were done collaboratively.
1 The paper is deposited under the rems of the Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Visualizing music psychology: A bibliometric analysis of Psychology of Music, Music Perception, and Musicae
Scientiae from 1973 to 2017
Music psychology has grown drastically since being established in the middle of the 19th century. However, up to this date, no large-scale computational bibliometric analysis of the scientific literature in music psychology has been carried out. This study aims to analyze all published literature from the journals Psychology of Music, Music Perception, and Musicae Scientiae. The retrieved literature comprised a total of 2,089 peer-reviewed articles, 2,632 authors, and 49 countries. Visualization and bibliometric techniques were used to investigate the growth of publications, citation analysis, author and country productivity, collaborations, and research trends. From 1973 to 2017, with a total growth rate of 11%, there is a clear increase in music psychology research (i.e. number of publications, authors, and collabo- rations), consistent with the general growth observed in science. The retrieved documents received a total of 33,771 citations (M = 16.17, SD = 26.93), with a median (Q1 – Q3) of 7 (2 – 20).
Different bibliometric indicators defined the most relevant authors, countries, and keywords as well as how they relate and collaborate with each other. Differences between the three journals are also studied. This type of analysis, not without its limitations, can help understand music psychology and identify future directions within the field.
Keywords: music psychology; psychology of music; bibliometrics; scientometrics; visu- alization technique.
46 A.1 Introduction
A.1 Introduction
The beginnings of what we now regard as music psychology started in the middle of the 19th century as a branch of both psychology and musicology (Thaut, 2016). But music psychology has evolved and grown drastically since then. From a focus on psychoacoustics, perception, and the cognitive sciences, to health applications and the use of music in everyday life, music psychology has shifted and blossomed, establishing programs, labs and journals covering different research interests, geographical areas, and research groups.
Music Psychology can be defined as the scientific study of the psychological processes through which music is perceived, created, responded to, and incorporated to everyday life (Tan, Pfordresher, & Harré, 2017; Thompson, 2014). The field of music psychology therefore embraces an incredibly diverse and wide variety of topics, including the origins of music, music perception and cognition, responses to music (e.g. bodily, emotional, and aesthetical), the neuroscience of music, music development, music education, music performance, composition and improvisation, the use of music in everyday life, and music therapy and wellbeing (Hallam, Cross, & Thaut, 2016). But the psychology of music can also contribute to many other fields, including musical theory, ethnomusicology, computer science, aesthetics, health sciences, marketing and advertising. Researchers from all over the globe investigate these topics empirically, with more than 80 music cognition and science labs around the world (www.musicperception.org/smpc-resources.html). Various music psychology specific conference series have also begun to develop such as the International Conference on Music Perception and Cognition (ICMPC), founded in 1989, and the European Society for the Cognitive Sciences of Music (ESCOM), founded in 1991. In 2008, the International Conference of Students of Systematic Musicology (SysMus) was founded for students of systematic musicology, a broader field which encompasses music psychology.
The first research journal specifically dedicated to music psychology is Psychology of Music established in 1973. This multidisciplinary journal’s aim is to, "increase scientific understand- ing of all psychological aspects of music and music education". Music Perception, estab- lished in 1983, was developed with a primary focus on cognitive-psychological research with broader and multidisciplinary draw, including work from “psychology, psychophysics, neuro- science, music theory, acoustics, artificial intelligence, linguistics, philosophy, anthropology and cognitive science” (mp.ucpress.edu). In 1997, the European Society for the Cognitive Sciences of Music (ESCOM) was developed along with its journal Musicae Scientiae, which aims to include “empirical, theoretical and critical articles directed at increasing understand- ing of how music is perceived, represented and generated” (journals.sagepub.com/home/msx).
As a truly multidisciplinary subject, music psychology research is published in many other
47 A.1 Introduction
journals, including other APA journals and journals from related disciplines, such as musicol- ogy, music theory, music therapy, music education, aesthetics, marketing, and neuroscience.
This includes, for example, the Journal of Research in Music Education, International Jour- nal of Music Education, Journal of Music Therapy, Empirical Musicology Review, and Psychomusicology: Music, Mind, and Brain
The current research focuses on the three most prominent scientific journals in music psy- chology. Namely, Psychology of Music, Music Perception, and Musicae Scientiae. We used two
The current research focuses on the three most prominent scientific journals in music psy- chology. Namely, Psychology of Music, Music Perception, and Musicae Scientiae. We used two