Stochastic dynamics of music album lifecycle: An analysis of the new market landscape

• Published in: International journal of human-computer studies Vol. 65; no. 1; pp. 85 - 93
• Main Authors: Bhattacharjee, Sudip, Gopal, Ram D., Lertwachara, Kaveepan, Marsden, James R.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: London Elsevier Ltd 2007; Elsevier
• Subjects: Applied sciences; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Exact sciences and technology; Intellectual property rights; Lifecycle; Memory and file management (including protection and security); Memory organisation. Data processing; Ranking chart; Software; Ranking chart; Intellectual property rights; Lifecycle; Process dynamics; Resource allocation; Modeling; Information dissemination; Copyright; Life cycle; Uncertain system; Consumer; User interface; Musical acoustics; Survival probability; Digital protection; Digital rights management; Computer security; Monitoring; Landscape; Probabilistic approach; Markets; Information access; File sharing; Longevity; Distributed system; Surveillance; Music
• ISSN: 1071-5819; 1095-9300
• DOI: 10.1016/j.ijhcs.2006.08.004

The rapid emergence of file sharing networks has enabled easier information dissemination and product access to potential consumers. At the same time, copyright protection technologies for securing digital products have been compromised repeatedly. To analyze the ensuing impacts on the market landscape for music products (a digital good), we develop a stochastic model of distribution of music album longevity on the Billboard Chart. We find that since the advent of file sharing networks and other market forces (such as legal changes in copyright laws, introduction of digital rights management systems and legitimate online music download offerings), the lifecycle of music albums has shortened with lowered probabilities of survival for each week. While the probability of survival past the first week is markedly lower, the future portends well for albums that do survive on the charts beyond the first week. This is consistent with the rapid diffusion of information on music albums in the changed market landscape. Integrating this insight with user activity on online computer networks, we estimate the continued success of albums on the charts. This analysis helps to create a more dynamic decision process on resource allocation to promote and market music products. Using the robust stochastic model parameters as a benchmark, we estimate a logistic regression model which helps us make quality decisions in an uncertain environment through early monitoring of the success of music albums.