Skip to main content
SpringerLink
Log in

Der Beitrag der Informatik zur Musikwirtschaftsforschung

  • Chapter
  • First Online:
Musikwirtschaftsforschung

Part of the book series: Musikwirtschafts- und Musikkulturforschung ((MUSIK))

  • 1725 Accesses

Zusammenfassung

Dieser Artikel widmet sich der Perspektive der Informatik in der Musikwirtschaftsforschung. Zunächst wird der Erkenntnisgegenstand der Musikwirtschaftsforschung aus dieser Perspektive dargelegt und das zur Verfügung stehende Methodeninstrumentarium aufgezeigt. Dabei untermauert diese Arbeit, dass die Perspektive der Informatik in der Musikwirtschaftsforschung neben einem deskriptiven auch einen normativen Charakter hat; somit beschäftigt sich dieser Bereich auch mit der Konstruktion und Evaluierung von Artefakten in der realen Welt der Musikwirtschaft. Anhand von konkreten Beispielen werden Problemstellungen und Forschungsfragen, die sich der Informatik in der Musikwirtschaftsforschung stellen, erläutert; dies sind im Speziellen die Forschungsbereiche (i) Musikempfehlungssysteme, (ii) Kompetenzaufbau im Einsatz von Technologie sowie (iii) Monitoring und Reporting der digitalen Musiknutzung.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 24.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 34.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  • Adler, M. (2006). Stardom and Talent. In V. A. Ginsburgh & D. Throsby (Hrsg) Handbook of the economics of art and culture (S. 896-906), Amsterdam: North Holland.

    Google Scholar 

  • Anderson, C. (2006). The Long Tail: Why the Future of Business is Selling Less of More. New York: Hyperion.

    Google Scholar 

  • Baskerville, R., Lyytinen, K., Sambamurthy, V., & Straub, D. (2011). A response to the design-oriented information systems research memorandum. European Journal of Information Systems 20 (1), 11-15. doi:https://doi.org/10.1057/ejis.2010.56.

  • Bauer, C. (2012). Bands as Virtual Organisations: Improving the Processes of Band and Event Management with Information and Communication Technologies. Frankfurt am Main, Berlin, Bern, Bruxelles, New York, Oxford, Wien: Peter Lang.

    Google Scholar 

  • Bauer, C., Kholodylo, M., & Strauss, C. (2017). Music Recommender Systems: Challenges and Opportunities for Non-Superstar Artists. 30th Bled eConference, Bled, Slovania, 18.-21. Juni.

    Google Scholar 

  • Bauer, C., & Kratschmar, A. (2015). Designing a Music-controlled Running Application: a Sports Science and Psychological Perspective. ACM SIGCHI Extended Abstracts of Conference on Human Factors in Computing Systems (CHI 2015), Seoul, South Korea, 18.-23. April.

    Google Scholar 

  • Bauer, C., & Schedl, M. (2017). Introducing Surprise and Opposition by Design in Recommender Systems. 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017): 2nd Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2017), Bratislava, Slovakia, 9. Juli.

    Google Scholar 

  • Bauer, C., & Strauss, C. (2015). Educating artists in management: an analysis of art education programmes in DACH region. Cogent Education 2 (1). doi:https://doi.org/10.1080/2331186x.2015.1045217.

  • Bauer, C., & Strauss, C. (2017). The dark side of Web 2.0: From self-marketing to self-destruction of music artists. GRES-IT Workshop Proceedings. Working Papers on Information Systems, Information Business and Operations, 02/2016, Vienna, Austria, 22. September 2016.

    Google Scholar 

  • Bauer, C., Viola, K., & Strauss, C. (2011). Management skills for artists: ‘learning by doing’? International Journal of Cultural Policy 17 (5), 626-644. doi:https://doi.org/10.1080/10286632.2010.531716.

  • Bauer, C., & Waldner, F. (2013). Reactive Music: When User Behavior affects Sounds in Real- Time. CHI 2013 Extended Abstracts on Human Factors in Computing Systems, Paris, France, 27. April – 2. Mai.

    Google Scholar 

  • Baym, N. K. (2010). Rethinking the Music Industry. Popular Communication 8 (3),177-180. doi:https://doi.org/10.1080/15405702.2010.493419.

  • Bernardo, F., & Marins, L. G. (2014). Disintermediation Effects on Independent Approaches to Music Business. International Journal of Music Business Research 3 (2), 7-27.

    Google Scholar 

  • Boer, D., Fischer, R., Strack, M., Bond, M. H., Lo, E., & Lam, J. (2011). How shared preferences in music create bonds between people: values as the missing link. Personality and Social Psychology Bulletin 37 (9), 1159-1171.

    Google Scholar 

  • Bonneville-Roussy, A., Rentfrow, P. J., Xu, M. K., & Potter, J. (2013). Music through the ages: trends in musical engagement and preferences from adolescence through middle adulthood. Journal of Personality and Social Psychology 105 (4), 703-717.

    Google Scholar 

  • Brown, R. A. (2012). Music preferences and personality among Japanese university students. International Journal of Psychology 47 (4), 259-268.

    Google Scholar 

  • Calandrino, J. A., Kilzer, A., Narayanan, A., Felten, E. W., & Shmatikov, V. (2011). „You Might Also Like:“ Privacy Risks of Collaborative Filtering. 32nd IEEE Symposium on Security and Privacy (SP 2011), Oakland, CA, 22.-25. Mai.

    Google Scholar 

  • Caves, R. E. (2000). Creative Industries: Contracts Between Art and Commerce. Cambridge, MaA: Harvard University Press.

    Google Scholar 

  • Cebrián, T., Planagumà, M., Villegas, P., & Amatriain, X. (2010). Music recommendations with temporal context awareness. 4th ACM Conference on Recommender Systems (RecSys 2010), Barcelona, Spain, 26.-30. September.

    Google Scholar 

  • Celma, Ò., & Herrera. P. (2008). A New Approach to Evaluating Novel Recommendations. 2nd ACM Conference on Recommender Systems (RecSys 2008), Lausanne, Switzerland, 23.-25. Oktober.

    Google Scholar 

  • Cheng, Z., & Shen, J. (2014). Just-for-Me: An Adaptive Personalization System for Location- Aware Social Music Recommendation. International Conference on Multimedia Retrieval (ICMR 2014), Glasgow, UK.

    Google Scholar 

  • Cheng, Z., & Shen, J. (2015). VenueMusic: A Venue-Aware Music Recommender System. 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2015), Santiago, Chile, 9.-13. August.

    Google Scholar 

  • Coy, W., Nake, F., Pflüger, J.-M., Rolf, A., Seetzen, J., Siefkes, D., & Stransfeld, R. (Hrsg.) (1992). Sichtweisen der Informatik, Theorie der Informatik. Wiesbaden: Vieweg+Teubner Verlag.

    Google Scholar 

  • Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 4. Aufl., Los Angeles, London, New Delhi, Singapore, Washington, DC: Sage.

    Google Scholar 

  • Daniel, R., & Daniel, L. (2014). Breaking down barriers: the implementation of work integrated learning strategies to transition creative and performing artists to industry. Australian Collaborative Education Network Conference (ACEN 2014), Gold Coast Queensland, Australia, 1.-3. Oktober.

    Google Scholar 

  • Ferwerda, B. Vall, A., Tkalcic M., & Schedl, M. (2016). Exploring Music Diversity Needs Across Countries. 24th Conference on User Modeling, Adaptation and Personalization (UMAP 2016), Halifax, Canada, 13.-17. Juli.

    Google Scholar 

  • Fleder, D., & Hosanagar, K. (2007). Recommender systems and their impact on sales diversity. 8th ACM Conference on Electronic Commerce (EC 2007), San Diego, CA, 11-15 June.

    Google Scholar 

  • Hennekam, S., & Bennett, D. (2016). Self-management of work in the creative industries in the Netherlands. International Journal of Arts Management 19 (1), 31-41, 97.

    Google Scholar 

  • Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. Management Information Systems Quarterly 28 (1), 75-105.

    Google Scholar 

  • Knees, P., Andersen, K., Said, A., & Tkalcic, M. (2016). Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP). UMAP 2016 Extended Proceedings: Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP), Halifax, NS, CA, 16. Juli.

    Google Scholar 

  • Kulle, J., (1998). Ökonomie der Musikindustrie: Eine Analyse der körperlichen und unkörperlichen Musikverwertung mit Hilfe von Tonträgern und Netzen. Frankfurt am Main: Peter Lang.

    Google Scholar 

  • Langenheder, W., Müller, G., & Schinzel, B. (Hrsg.) (1992). Informatik cui bono?: GI-FB 8 Fachtagung, Freiburg, 23.-26. September 1992, Informatik aktuell. Berlin: Springer.

    Google Scholar 

  • Laplante, A.. (2014). Improving music recommender systems: what can we learn from research on music tags? 15th International Society for Music Information Retrieval Conference (ISMIR 2014), Taipei, Taiwan, 27.-31. Oktober.

    Google Scholar 

  • Limper, J., & Lücke, M. (Hrsg.). (2013). Management in der Musikwirtschaft. Edition Kreativwirtschaft. Stuttgart: Kohlammer.

    Google Scholar 

  • March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems 15 (4), 251-266.

    Google Scholar 

  • Menger, P.-M. (1999). Artistic Labor Markets and Careers. Annual Review of Sociology 25 (1), 541-574. doi:https://doi.org/10.1146/annurev.soc.25.1.541.

  • Michel, N. J. (2006). The impact of digital file sharing on the music industry: An empirical analysis. Topics in Economic Analysis & Policy 6 (1), 1-22.

    Google Scholar 

  • Mietzner, D., & Kamprath, M. (2013). A Competence Portfolio for Professionals in the Creative Industries. Creativity and Innovation Management 22 (3), 280-294. doi:https://doi.org/10.1111/caim.12026.

  • Montag Stiftung Bildende Kunst Bonn, Akademie der bildenen Künste Wien & Verlag für moderne Kunst. (2008). Job Descriptions: KünstlerInnen in einer veränderten Berufswelt. 3. Symposium der Reihe „Heraus aus dem Elfenbeinturm!“, Nürnberg, 17.-18. Oktober.

    Google Scholar 

  • Mulligan, M. (2013). The Death of the Long Tail: The Superstar Music Economy. Media Insights & Decisions in Action.

    Google Scholar 

  • Österle, H. Becker, J., Frank, U., Hess, Th., Karagiannis, D., Krcmar, H., Loos, P., Mertens, P., Oberweis, A., & Sinz, E. J. (2010). Memorandum on design-oriented information systems research. European Journal of Information Systems 20 (1), 7-10.

    Google Scholar 

  • Peffers, K., Rothenberger, M., Tuunanen, T., & Vaezi, R. (2012). Design Science Research Evaluation. 7th International Conference on Design Science Research in Information Systems (DESRIST 2012), Las Vegas, NV, 14.-15. Mai.

    Google Scholar 

  • Prat, N., Comyn-Wattiau, I., & Akoka, J. (2014). Artifact evaluation in information systems design-science research: a holistic view. 18th Pacific Asia Conference on Information Systems (PACIS 2014), Chengdu, China, 24.-28. Juni.

    Google Scholar 

  • Pries-Heje, J., Baskerville, R., & Venable, J. R. (2008). Strategies for Design Science Research Evaluation. European Conference on Information Systems (ECIS 2008), Galway, Ireland, 9.-11. Juni.

    Google Scholar 

  • Rechenberg, P. (2000). Was ist Informatik? München: Hanser Fachbuch.

    Google Scholar 

  • Schedl, M. (2016). The LFM-1b Dataset for Music Retrieval and Recommendation. ACM International Conference on Multimedia Retrieval (ICMR 2016), New York, NY, 6.-9. Juni.

    Google Scholar 

  • Schedl, M,, Gómez, E., & Urbano, J. (2014). Music Information Retrieval: Recent Developments and Applications. Foundations and Trends in Information Retrieval 8 (2-3), 127-261.

    Google Scholar 

  • Schelepa, S., Wetzel, P., & Wohlfahrt. G. (2008). Zur sozialen Lage der Künstler und Künstlerinnen in Österreich: Endbericht. Wien: L & R Social Research.

    Google Scholar 

  • Schulze, G. (2003). Superstars. In R. Towse (Hrsg.), A Handbook of Cultural Economics (S. 431-436). Cheltenham, UK: Edward Elgar Publishing.

    Google Scholar 

  • Seufert, W., Schlegel, R., & Sattelberger, F. (2015). Musikwirtschaft in Deutschland: Studie zur volkswirtschaftlichen Bedeutung von Musikunternehmen unter Berücksichtigung aller Teilsektoren und Ausstrahlungseffekte. Bundesverband Musikindustrie e. V.; Bundesverband der Veranstaltungswirtschaft e. V.; deutscher musikverleger-Verband e. V.; Europäischer Verband der Veranstaltungszentren e. V.; Gesellschaft zur Verwertung von Leistungsschutzrechten mbh LivemusikKommission e. V.; Society of Music Merchants e. V.; Verband der deutschen Konzertdirektionen e. V.; Verband unabhängiger musikunternehmen e. V.

    Google Scholar 

  • Söndermann, M. (2010). Monitoring zu ausgewählten wirtschaftlichen Eckdaten der Kulturund Kreativwirtschaft 2010: Langfassung. Köln: Büro für Kulturwirtschaftsforschung.

    Google Scholar 

  • Song, Y., Dixon, S., & Pearce, M. (2012). A Survey of Music Recommendation Systems and Future Perspectives. 9th International Symposium on Computer Music Modelling and Retrieval (CMMR 2012), London, United Kingdom, 19-22 June.

    Google Scholar 

  • Stigler, George J., & Becker, Gary S. (1977). De Gustibus Non Est Disputandum. The American Economic Review 67 (2), 76-90.

    Google Scholar 

  • Tschmuck, P. (2012). Creativity and Innovation in the Music Industry. 2. Aufl. Berlin, Heidelberg: Springer.

    Google Scholar 

  • Venable, J. R., Pries-Heje, J., & Baskerville, R. (2012). A Comprehensive Framework for Evaluation in Design Science Research. 7th International Conference on Design Science Research in Information Systems (DESRIST 2012), Las Vegas, NV, 14.-15. Mai.

    Google Scholar 

  • Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. Management Information Systems Quarterly 37 (1), 21-54.

    Google Scholar 

  • Wang, X., Rosenblum, D., & Wang, Y. (2012). Context-aware mobile music recommendation for daily activities. 20th ACM International Conference on Multimedia (MM 2012), Nara, Japan, 29. Oktober – 2. November.

    Google Scholar 

  • Wilde, T., & Hess, Th. (2007). Forschungsmethoden der Wirtschaftsinformatik: Eine empirische Untersuchung. Wirtschaftsinformatik 49 (4), 280-287.

    Google Scholar 

  • Zhang, M., & Hurley, N. (2008). Avoiding Monotony: Improving the Diversity of Recommendation Lists. 2nd ACM Conference on Recommender Systems (RecSys 2008), Lausanne, Switzerland, 23.-25. Oktober.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut für Computational Perception Johannes Kepler, Universität Linz Altenberger, Straße 69, 4040, Linz, Österreich

    Christine Bauer

Authors
  1. Christine Bauer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christine Bauer .

Editor information

Editors and Affiliations

  1. Institut für Kulturmanagement, Universität für Musik und darstellende K, Wien, Austria

    Peter Tschmuck

  2. Institut für Kunst, Universität Paderborn, Paderborn, Nordrhein-Westfalen, Germany

    Beate Flath

  3. M33 Höfe, Hochschule Macromedia, Berlin, Germany

    Martin Lücke

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Fachmedien Wiesbaden GmbH

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Bauer, C. (2018). Der Beitrag der Informatik zur Musikwirtschaftsforschung. In: Tschmuck, P., Flath, B., Lücke, M. (eds) Musikwirtschaftsforschung. Musikwirtschafts- und Musikkulturforschung. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-19399-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-19399-7_6

  • Published:

  • Publisher Name: Springer VS, Wiesbaden

  • Print ISBN: 978-3-658-19398-0

  • Online ISBN: 978-3-658-19399-7

  • eBook Packages: Social Science and Law (German Language)

Publish with us

Policies and ethics

Search

Navigation