The Longer Tail: The Changing Shape of Amazon’s Sales Distribution Curve
Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER)
Yu Jeffrey Hu
Georgia Institute of Technology
Michael D. Smith
Carnegie Mellon University - H. John Heinz III School of Public Policy and Management
September 20, 2010
Internet consumers derive significant surplus from increased product variety, and in particular, the “Long Tail” of niche products that can be found on the Internet at retailers like Amazon.com. In this paper we analyze how the shape of Amazon’s sales distribution curve has changed from 2000 to 2008, and how this impacts the resulting consumer surplus gains from increased product variety in the online book market. Specifically, in 2008 we collected sales and sales rank data on a broad sample of books sold through Amazon.com and compare it to similar data we gathered in 2000. We then develop a new methodology for fitting the relationship between sales and sales rank and apply it to our data. We find that the Long Tail has grown longer over time, with niche books accounting for a larger share of total sales. Our analyses suggest that by 2008, niche books account for 36.7% of Amazon’s sales and the consumer surplus generated by niche books has increased at least five fold from 2000 to 2008. We argue that this increase is consistent with the presence of “secondary” supply- and demand- side effects driving the growth of the Long Tail online. In addition, our new methodology finds that, while power laws are a good first approximation for the rank-sales relationship, the slope is not constant for all book ranks, becoming progressively steeper for more obscure books.
Number of Pages in PDF File: 13
Keywords: Long Tail, electronic commerce, sales distribution, niche products, power lawworking papers series
Date posted: September 22, 2010 ; Last revised: October 2, 2010
© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo1 in 0.344 seconds