The research reported here was funded by a faculty research grant, Faculty of Economics and Commerce, University of Melbourne, and by the National Science Foundation award number SES-0724914. The authors are grateful to Phil Bonacich, Yik Ting Choi, Peter DiCola, Patti Donze, Sung Wook Joh, Lawrence Khoo, Bill Mason, Mediabase, Paul Porter, Matthew Salganik, Tom Valente, and Filippo Carlo Wezel, and to the anonymous reviewers. Direct correspondence to Gabriel Rossman, 264 Haines Hall, Los Angeles, CA 90095-1551; e-mail: email@example.com, Ph: (310) 206-8904, Fax: (310) 206-9838.
MODELING DIFFUSION OF MULTIPLE INNOVATIONS VIA MULTILEVEL DIFFUSION CURVES: PAYOLA IN POP MUSIC RADIO
Article first published online: 18 JUL 2008
© 2008 by American Sociological Association
Volume 38, Issue 1, pages 201–230, December 2008
How to Cite
Rossman, G., Chiu, M. M. and Mol, J. M. (2008), MODELING DIFFUSION OF MULTIPLE INNOVATIONS VIA MULTILEVEL DIFFUSION CURVES: PAYOLA IN POP MUSIC RADIO. Sociological Methodology, 38: 201–230. doi: 10.1111/j.1467-9531.2008.00201.x
- Issue published online: 17 OCT 2008
- Article first published online: 18 JUL 2008
Diffusion curve analysis can estimate whether an innovation spreads endogenously (indicated by a characteristic “s-curve”) or exogenously (indicated by a characteristic negative exponential curve). Current techniques for pooling information across multiple innovations require a two-stage analysis. In this paper, we develop multilevel diffusion curve analysis, which is statistically more efficient and allows for more flexible specifications than do existing methods. To substantively illustrate this technique, we use data on bribery in pop radio as an example of exogenous influence on diffusion.