Boiling the Frog Optimally: An Experiment on Survivor Curve Shapes and Internet Revenue

25 Pages Posted: 22 Feb 2013 Last revised: 20 May 2014

See all articles by Christina Aperjis

Christina Aperjis

Hewlett-Packard Enterprise - Social Computing Lab

Ciril Bosch-Rosa

Technische Universität Berlin

Daniel Friedman

University of California, Santa Cruz - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Bernardo A. Huberman

CableLabs

Date Written: May 19, 2014

Abstract

When should a necessary inconvenience be introduced gradually, and when should it be imposed all at once? The question is crucial to web content providers, who in order to generate revenue must sooner or later introduce advertisements, subscription fees, or other inconveniences. Assuming that eventually people fully adapt to changes, the answer depends only on the shape of the survivor curve S(x), which represents the fraction of a user population willing to tolerate inconveniences of size x (Aperjis and Huberman 2011).

We report a new laboratory experiment that, for the first time, estimates the shape of survivor curves in several different settings. We engage laboratory subjects in a series of six desirable activities, e.g., playing a video game, viewing a chosen video clip, or earning money by answering questions. For each activity we introduce a chosen level x 2 [xmin; xmax] of a particular inconvenience, and each subject chooses whether to tolerate the inconvenience or to switch to a bland activity for the remaining time.

Our key finding is that, in general, the survivor curve is log-convex. Theory suggests therefore that introducing inconveniences all at once will generally be more profitable for web content providers.

Keywords: Internet monetization, online advertising, pricing, reference points, adaptation, laboratory experiment

Suggested Citation

Aperjis, Christina and Bosch-Rosa, Ciril and Friedman, Daniel and Huberman, Bernardo A., Boiling the Frog Optimally: An Experiment on Survivor Curve Shapes and Internet Revenue (May 19, 2014). Available at SSRN: https://ssrn.com/abstract=2215403 or http://dx.doi.org/10.2139/ssrn.2215403

Christina Aperjis

Hewlett-Packard Enterprise - Social Computing Lab ( email )

1501 Page Mill Road
Palo Alto, CA 9434
United States

Ciril Bosch-Rosa

Technische Universität Berlin ( email )

Straße des 17. Juni 135,
Fakultat VII, Sekretariat H52
Berlin, 10623
Germany

Daniel Friedman

University of California, Santa Cruz - Department of Economics ( email )

Social Sciences I
Santa Cruz, CA 95064
United States
831-459-4981 (Phone)
831-459-5900 (Fax)

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Bernardo A. Huberman (Contact Author)

CableLabs ( email )

400 W California Ave
Sunnyvale, CA 94086
United States

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