Comparing predicted prices in auctions for online advertising

B-Tier
Journal: International Journal of Industrial Organization
Year: 2012
Volume: 30
Issue: 1
Pages: 80-88

Authors (4)

Bax, Eric (not in RePEc) Kuratti, Anand (not in RePEc) Mcafee, Preston (Google Research) Romero, Julian (Purdue University)

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Online publishers sell opportunities to show ads. Some advertisers pay only if their ad elicits a user response. Publishers estimate response rates for ads in order to estimate expected revenues from showing the ads. Then publishers select ads that maximize estimated expected revenue.

Technical Details

RePEc Handle
repec:eee:indorg:v:30:y:2012:i:1:p:80-88
Journal Field
Industrial Organization
Author Count
4
Added to Database
2026-01-26