IDEAS home Printed from https://ideas.repec.org/a/kap/jculte/v20y1996i2p145-164.html
   My bibliography  Save this article

The dynamics of product differentiation in the British record industry

Author

Listed:
  • Andrew Burke

Abstract

The paper conducts a statistical analysis of the dynamics of the sale of new music (product differentiation innovation) in the record industry. In pursuing this goal the paper generates new data and analyses a previously unutilized data set. The paper finds that there is a strong correlation between new music innovation in the audio singles and albums market. This is found to be mainly concurrent in the same quarter and to have a reasonably short product life. The paper discovers that these features also characterise the dynamics of record company performance. The research indicates that record companies are willing to sell singles at a loss due to advertising rather than learning externalities. At the industry level, the paper finds that new music innovation does not effect market size significantly and mainly causes ‘business stealing’ effects between record companies, with exceptional cases of multiplier effects. Copyright Kluwer Academic Publishers 1996

Suggested Citation

  • Andrew Burke, 1996. "The dynamics of product differentiation in the British record industry," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 20(2), pages 145-164, June.
    • Handle: RePEc:kap:jculte:v:20:y:1996:i:2:p:145-164
    DOI: 10.1007/s10824-005-5164-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10824-005-5164-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10824-005-5164-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Osborn, Denise R., 1990. "A survey of seasonality in UK macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 6(3), pages 327-336, October.
    2. Osborn, Denise R, et al, 1988. "Seasonality and the Order of Integration for Consumption," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(4), pages 361-377, November.
    3. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-692, December.
    4. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marc Bourreau & Michel Gensollen & François Moreau & Patrick Waelbroeck, 2013. "“Selling less of more?” The impact of digitization on record companies," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(3), pages 327-346, August.
    2. David Giles, 2007. "Increasing returns to information in the US popular music industry," Applied Economics Letters, Taylor & Francis Journals, vol. 14(5), pages 327-331.
    3. Seungkyu Shin & Juyong Park, 2018. "On-Chart Success Dynamics Of Popular Songs," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-18, May.
    4. David Giles, 2007. "Survival of the hippest: life at the top of the hot 100," Applied Economics, Taylor & Francis Journals, vol. 39(15), pages 1877-1887.
    5. Jonathan Gander & Alison Rieple, 2004. "How Relevant is Transaction Cost Economics to Inter-Firm Relationships in the Music Industry?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 28(1), pages 57-79, February.
    6. Mark Lorenzen & Lars Frederiksen, 2005. "On the Economics of Innovation Projects Product Experimentation in the Music Industry," DRUID Working Papers 05-23, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    7. Andrea Ordanini, 2006. "Selection models in the music industry: How a prior independent experience may affect chart success," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 30(3), pages 183-200, December.
    8. Harrie Hansman & Clara Mulder & René Verhoeff, 1999. "The Adoption of the Compact Disk Player: An Event History Analysis for the Netherlands," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 23(3), pages 221-232, August.
    9. Samuel Cameron, 2016. "Past, present and future: music economics at the crossroads," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 40(1), pages 1-12, February.
    10. Juan D. Montoro-Pons & Manuel Cuadrado-García, 2018. "“Let’s make lots of money”: the determinants of performance in the recorded music sector," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(2), pages 287-307, May.
    11. Andrew Burke, 1996. "How effective are international copyright conventions in the music industry?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 20(1), pages 51-66, March.
    12. Eric Strobl & Clive Tucker, 2000. "The Dynamics of Chart Success in the U.K. Pre-Recorded Popular Music Industry," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 24(2), pages 113-134, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michael Browne, 2016. "Liquidity effects on consumers’ imports in Trinidad and Tobago," Working Papers 2016-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    3. Hans Franses, Philip & Koehler, Anne B., 1998. "A model selection strategy for time series with increasing seasonal variation," International Journal of Forecasting, Elsevier, vol. 14(3), pages 405-414, September.
    4. Boswijk, H. Peter & Franses, Philip Hans & van Dijk, Dick, 2010. "Cointegration in a historical perspective," Journal of Econometrics, Elsevier, vol. 158(1), pages 156-159, September.
    5. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    6. Kavussanos, Manolis G. & Alizadeh-M, Amir H., 2002. "Seasonality patterns in tanker spot freight rate markets," Economic Modelling, Elsevier, vol. 19(5), pages 747-782, November.
    7. Koi Nyen Wong & Tuck Cheong Tang, 2009. "Exchange rate variability and the export demand for Malaysia's semiconductors: an empirical study," Applied Economics, Taylor & Francis Journals, vol. 43(6), pages 695-706.
    8. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    9. Sogiakas, Vasilios & Karathanassis, George, 2015. "Informational efficiency and spurious spillover effects between spot and derivatives markets," Global Finance Journal, Elsevier, vol. 27(C), pages 46-72.
    10. Éric Girardin & Velayoudom Marimoutou, 1997. "Les fondamentaux permettent-ils d'améliorer la prévision du taux de change franc-dollar ?," Revue Économique, Programme National Persée, vol. 48(3), pages 661-672.
    11. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465, November.
    12. Jorge Dresdner & Leonardo Letelier, 1997. "Cointegración de los Salarios Agregados en Chile: 1980-3-1995-3," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 34(101), pages 49-70.
    13. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    14. Héctor A. Valle S., 2003. "Pronósticos de inflación para Guatemala hechos con modelos ARIMA y VAR," Monetaria, CEMLA, vol. 0(4), pages 407-428, octubre-d.
    15. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    16. Jacqueline Pradel & Christophe Rault, 2003. "Exogeneity in Vector Error Correction Models with Purely Exogenous Long‐Run Paths," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 629-653, December.
    17. Dimitris Georgoutsos & George Kouretas, "undated". "The Pound Sterling And Franc Poincare In The 1920s: Long-Run Relationships, Speculation And Temporal Stability," Working Papers 9502, University of Crete, Department of Economics.
    18. Albertson, Kevin & Aylen, Jonathan, 2003. "Forecasting the behaviour of manufacturing inventory," International Journal of Forecasting, Elsevier, vol. 19(2), pages 299-311.
    19. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, August.
    20. Jesús R. González García, 2003. "La dinámica del consumo privado en México: un análisis de cointegración con cambios de régimen," Monetaria, CEMLA, vol. 0(4), pages 429-449, octubre-d.

    More about this item

    Keywords

    music industry; product differentiation; econometric methodology; demand;
    All these keywords.

    JEL classification:

    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • L30 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - General
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:jculte:v:20:y:1996:i:2:p:145-164. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.