all users buy the product, and the optimal price and flexibility levels decrease
as permeability increases. When permeability rises above the critical value,
the number of users who buy decreases, and the optimal price and flexibility
˲ A platform vendor who also sells
digital content (which he licenses from
copyright owners) will find it optimal
to allow very flexible use by platform
customers and to set a low price for
content; most of the vendor’s profit is
from platform sales. Copyright owners’
revenue is low, because prices are low
and sharing of content is common.
˲ Tension between the platform vendor and copyright owner is observed in
the real world. In 2005, the Financial
Times quoted a music executive as saying, “Our music is not something to be
given away to sell iPods.”
Nearly all mass-market services—email,
Web search, social networks, recommendations, user content, and ad networks, for example—seem beset by attempts to manipulate and distort. New
services, such as the semantic Web, are
assumed to be immune only while they
remain niche. Yet to date the design of
Internet protocols and services, including monetization efforts, have often
been guided by technology rather than
economics; and users have been modeled in caricature as either cooperative
or malicious, the later to be dealt with by
security measures. In truth, few users are
benevolent and fewer still are vandals.
Even the most vilified of participants—
spammers—are acting in response to
rational economic considerations. Understanding how to align the incentives
of participants with systemwide objectives is fundamental to the design of the
next generation of Web-scale services.
Increasingly, design teams will require
dual expertise in social science and
computer science, adding competence
in economics, sociology, and psychology to more traditionally recognized
requirements such as algorithms, interfaces, systems, machine learning, and
In this article we focused on computational challenges in Internet-based
(specifically Web-based) commerce. Yet
people are starting to use smartphones
and other handheld devices to do much
of what they used to do with Internet-connected desktop or laptop PCs. To
what extent these handheld devices will
ultimately behave like networked PCs is
unclear, and thus we leave to a future article the needed discussion of computational challenges in mobile commerce.
Joan Feigenbaum was supported in
part by NSF grants CNS-0331548,
CNS-0428422, and IIS-0534052. David
Parkes was supported in part by NSF
grants DMS-0631636, IIS-0534620, IIS-
0238147, an Alfred P. Sloan Research
Fellowship, and Yahoo! Research and
Microsoft Research awards; he gratefully acknowledges helpful conversations
with Yochai Benkler, Chris Kelty, Johan
Pouwelse, and Sven Seuken.
1. acquisti, a. The Economics of Privacy; www.heinz.cmu.
2. acquisti, a. Privacy in electronic commerce and the
economics of immediate gratification. in Proceedings
of the 5th Electronic Commerce Conference. acm
(2004), 21–29; www.heinz.cmu.edu/~acquisti/papers/
3. adar, e. and huberman, b. free riding on gnutella.
First Monday 5 (2000), 2.
4. altman, a. and tennenholtz, m. an axiomatic approach
to personalized ranking systems. in Proceedings of
the 20th International Joint Conference on Artificial
Intelligence (2007), 1187–1192.
5. anderson, r. why information security is hard—an
economic perspective. in Proceedings of the 17th
Annual Computer Security Applications Conference
(2001), 358–365; www.cl.cam.ac.uk/~rja14/Papers/
6. benkler, y. coase’s penguin, or, linux and the nature of
the firm. The Yale Law Journal 112 (2002), 369–446.
7. bergemann, D., eisenbach, t., feigenbaum, J., and
shenker, s. flexibility as an instrument in digital rights
management. in Proceedings of the 2005 Workshop
on Economics of Information Security; http://
8. bolton, g., greiner, b., and ockenfels, a. engineering
trust: strategic behavior and the production of
reputation information. working paper, harvard
business school, 2007.
9. chawla, s., Dwork, c., mcsherry, f., smith, a., and
wee, h. toward privacy in public databases. in
Proceedings of the 2nd Theoretical Cryptography
Conference. springer lncs 3378 (2005), 363–385;
10. chen, y., fortnow, l., lambert, n., Pennock, D.m., and
wortman, J. complexity of combinatorial market
makers. in Proceedings of the 9th Conference on
Electronic Commerce. ACM (2008), 190–199.
11. chen, y. goel, s., and Pennock, D.m. Pricing
combinatorial markets for tournaments. in
Proceedings of the 40th Symposium on Theory of
Computation (2008), 305–314.
12. cramton, P., shoham, y., and steinberg, r., eds.
Combinatorial Auctions. mit Press, cambridge, ma,
13. Dhajima, r., tygar, D., and heart, m. why phishing
works. in Proceedings of the Conference on Human
Factors in Computer Systems. acm (2006), 581–590.
14. Dwork, c. and naor, m. Pricing via processing or
combating junk mail. Crypto ’ 92. springer lncs 740
(1992) 139–147; www.wisdom.weizmann.ac.il/~naor/
15. edelman, b., ostrovsky, m., and schwarz, m. internet
advertising and the generalized second price auction:
selling billions of dollars worth of keywords. American
Economic Review 97 (2007), 242–259.
16. fehr, e. and camerer, c. measuring social norms and
preferences using experimental games: a guide for
social scientists. in Foundations of Human Sociality,
henrich, J., boyd, r., bowles, s., camerer, c., fehr, e.,
and gintis, h. eds. oxford university Press, oxford,
17. frey, b.s. and Jegen, r. motivation crowding theory.
Journal of Economic Surveys 15 (2001), 589–611.
18. hanson, r. logarithmic market scoring rules for
modular combinatorial information aggregation.
Journal of Prediction Markets 1 (2007), 3–15.
19. immorlica, n., Jain, K., mahdian, m., and talwar,
K. click fraud resistant methods for learning click-through rates. in Proceedings of the 1st Workshop
on Internet and Network Economics 3828. springer
lncs (2005) 34–45; www.ece.northwestern.
20. Jackson, m.o. mechanism theory. Encyclopedia of Life
Support Systems. Derigs, u., ed. eolss Publishers,
oxford, u.K., 2003.
21. Kamvar, s.D., schlosser, m.t., and garcia-molina, h.
the eigentrust algorithm for reputation management
in P2P networks. in Proceedings of the 12th
International World Wide Web Conference, (2003),
summary?doi= 10. 1. 1. 13.3109.
22. Kash, i.a., friedman, e.J., and halpern, J.y. optimizing
scrip systems: efficiency, crashes, boarders, and
altruists. in Proceedings of the 8th Conference on
Electronic Commerce. acm (2007), 305–315.
23. lambert, n., langford, J., wortman, J., chen, y.,
reeves, D., shoham, y., and Pennock, D.m. self-financed wagering mechanisms for forecasting. in
Proceedings of the 9th Conference on Electronic
Commerce. acm (2008), 170–179.
24. loder, t., Van alstyne, m., and wash, r. an economic
response to unsolicited communication. Advances in
Economic Analysis and Policy 1 (2006), article 2; www.
25. nisan, n., roughgarden, t., tardos, e., and Vazirani,
V. V., eds. Algorithmic Game Theory. cambridge
university Press, 2007.
26. Pennock, D.m. a dynamic pari-mutuel market for
hedging, wagering, and information aggregation.
in Proceedings of the 5th Conference on Electronic
Commerce. acm, 2004, 170–179.
27. Pouwelse, J.a., garbacki, P., wang, J., bakker, a.,
yang, J., iosup, a., epema, D.h. J., reinders, m. J.t, van
steen, m.r., and sips, h.J. tribler: a social-based
peer-to-peer system. Concurrency and Computation:
Practice and Experience 20 (2008), 127–138.
28. resnick, P. and sami, r. the influence-limiter:
Provably manipulation-resistant recommender
systems. Recommender Systems Conference. acm,
29. resnick, P., zeckhauser, r., swanson, J., and
lockwood, K. the value of reputation on ebay: a
controlled experiment. Experimental Economics 9
30. sandholm, t. expressive commerce and its application
to sourcing: how we conducted $35 billion of
generalized combinatorial auctions. AI Magazine 28
31. Varian, h.r. Position auctions. International Journal of
Industrial Organization 25 (2007), 1163–1178.
32. winkler, r., munoz, J., cervera, J., bernardo, J.,
blattenberger, g., Kadane, J., lindley, D., murphy, a.,
oliver, r., and rios-insua, D. scoring rules and the
evaluation of probabilities. TEST 5 (1996), 1–60.
33. workshops on ad auctions; http://research.yahoo.
34. workshops on economics of information security;
35. zhang, h. and Parkes, D.c. Value-based policy teaching
with active indirect elicitation. in Proceedings of the
23rd Conference on Artificial Intelligence. (2008),
Joan Feigenbaum ( email@example.com) is the
grace murray hopper Professor of computer science at
yale university, new haven, ct.
David C. Parkes ( firstname.lastname@example.org) is gordon
mcKay Professor of computer science at harvard
university, cambridge, ma.
David M. Pennock ( email@example.com)
is a principal research scientist at yahoo! research,
new york, ny.
© 2009 acm 0001-0782/09/0100 $5.00