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Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters

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  • Guidolin, Mariangela
  • Guseo, Renato

Abstract

In this paper, we develop a new innovation diffusion model for two competing products, which allows us to evaluate the effect of competition both on the dynamics of within-product and cross-product word-of-mouth and on the definition of the residual market potential of each product. This model, which we call Lotka–Volterra model with churn, LVch, generalizes another model for competition, the unbalanced competition and regime change diachronic model (UCRCD), which assumes a common residual market and a delayed entrance for the second product. We compare the performance of these models in describing the competition between two blockbuster formats in the music industry, the compact cassette and the compact disc. In particular, we analyze the evolution of these technologies in the U.S. market for pre-recorded music, for which annual sales data are available from 1973 to 2012, and find that the LVch model outperforms the UCRCD. An interesting aspect of this application relies on the fact that there is a single product, the music album, which is commercialized in two different formats, so that competition arises between formats and not between two products in the same commercial category.

Suggested Citation

  • Guidolin, Mariangela & Guseo, Renato, 2015. "Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 35-46.
  • Handle: RePEc:eee:tefoso:v:99:y:2015:i:c:p:35-46
    DOI: 10.1016/j.techfore.2015.06.023
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    1. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    2. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    3. Yan, Hong-Sen & Ma, Kai-Ping, 2011. "Competitive diffusion process of repurchased products in knowledgeable manufacturing," European Journal of Operational Research, Elsevier, vol. 208(3), pages 243-252, February.
    4. Tang, Yinan & Zhang, J.W., 2005. "A competition model for two CPU vendors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 465-480.
    5. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    6. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    7. Gary M. Erickson, 1992. "Empirical Analysis of Closed-Loop Duopoly Advertising Strategies," Management Science, INFORMS, vol. 38(12), pages 1732-1749, December.
    8. Prasad A. Naik & Ashutosh Prasad & Suresh P. Sethi, 2008. "Building Brand Awareness in Dynamic Oligopoly Markets," Management Science, INFORMS, vol. 54(1), pages 129-138, January.
    9. Renato Guseo & Cinzia Mortarino, 2010. "Correction to the Paper “Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost”," Operations Research, INFORMS, vol. 58(5), pages 1522-1523, October.
    10. Pradeep K. Chintagunta & Naufel J. Vilcassim, 1992. "An Empirical Investigation of Advertising Strategies in a Dynamic Duopoly," Management Science, INFORMS, vol. 38(9), pages 1230-1244, September.
    11. Baláž, Vladimír & Williams, Allan M., 2012. "Diffusion and competition of voice communication technologies in the Czech and Slovak Republics, 1948–2009," Technological Forecasting and Social Change, Elsevier, vol. 79(2), pages 393-404.
    12. Frank M. Bass & Anand Krishnamoorthy & Ashutosh Prasad & Suresh P. Sethi, 2005. "Generic and Brand Advertising Strategies in a Dynamic Duopoly," Marketing Science, INFORMS, vol. 24(4), pages 556-568, February.
    13. Erickson, Gary M., 2009. "An oligopoly model of dynamic advertising competition," European Journal of Operational Research, Elsevier, vol. 197(1), pages 374-388, August.
    14. Pradeep K. Chintagunta & Dipak C. Jain, 1995. "Empirical Analysis of a Dynamic Duopoly Model of Competition," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 4(1), pages 109-131, March.
    15. Sergei Savin & Christian Terwiesch, 2005. "Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost," Operations Research, INFORMS, vol. 53(1), pages 26-47, February.
    16. Gary M. Erickson, 2009. "Advertising Competition in a Dynamic Oligopoly with Multiple Brands," Operations Research, INFORMS, vol. 57(5), pages 1106-1113, October.
    17. Sorger, Gerhard, 1989. "Competitive dynamic advertising : A modification of the Case game," Journal of Economic Dynamics and Control, Elsevier, vol. 13(1), pages 55-80, January.
    18. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    19. Guseo, Renato & Mortarino, Cinzia, 2012. "Sequential market entries and competition modelling in multi-innovation diffusions," European Journal of Operational Research, Elsevier, vol. 216(3), pages 658-667.
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    Cited by:

    1. Foucart, Renaud & Wan, Cheng & Wang, Shidong, 2018. "Innovations and technological comebacks," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 1-14.
    2. Pasquale L. Scandizzo & Marco Ventura, 2016. "Innovation and imitation as an interactive process," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 25(8), pages 821-851, November.
    3. Mariangela Guidolin & Renato Guseo, 2020. "Has the iPhone cannibalized the iPad? An asymmetric competition model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(3), pages 465-476, May.
    4. Cerqueti, Roy & Quaranta, Anna Grazia & Ventura, Marco, 2016. "Innovation, imitation and policy inaction," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 22-30.
    5. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    6. Thangeda, Rahul & Kumar, Niraj & Majhi, Ritanjali, 2024. "A neural network-based predictive decision model for customer retention in the telecommunication sector," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    7. Andrea Savio & Luigi De Giovanni & Mariangela Guidolin, 2022. "Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics," Forecasting, MDPI, vol. 4(2), pages 1-18, April.

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