Forecasting the Sales of Music Albums: A Functional Data Analysis of Demand and Supply Side P2P Data
Il-Horn Hann
Associate Professor of Information Systems
RH Smith School of Business
University of Maryland
November 20, 2009
Alter Hall 405, 1000am – 1130am
Abstract
We predict the sales of music albums by utilizing demand and supply side P2P data using a functional data
analysis (FDA) approach. We find that the characteristics of the functional form of downloading behavior explain
first-week sales by more than 60% after controlling for album characteristics. By updating our forecasts from 4
weeks to 1 week prior to the album release date, we examine the dynamic changes across different quantiles of
the sales-distribution for the demand- and supply-side P2P data. We find that the gap between downloading
effect on sales among high-quantile vs. low-quantile albums reach the highest level one week before the release
date.
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