Expertise in Online Markets

Despotakis, S; Ravi, R; Sayedi, A; Hafalir, IE

Expertise in Online Markets

Despotakis, S Ravi, R Sayedi, A Hafalir, IE

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Publisher:: INFORMS
Publication Type:: Journal Article
Citation:: Management Science, 2017, 63, (0025-1909(print)), pp. 3895-3910
Issue Date:: 2017-11-01

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Field	Value	Language
dc.contributor.author	Despotakis, S
dc.contributor.author	Ravi, R
dc.contributor.author	Sayedi, A
dc.contributor.author	Hafalir, IE
dc.date.accessioned	2020-09-21T01:54:41Z
dc.date.available	2016-02-12
dc.date.available	2020-09-21T01:54:41Z
dc.date.issued	2017-11-01
dc.identifier.citation	Management Science, 2017, 63, (0025-1909(print)), pp. 3895-3910
dc.identifier.issn	1526-5501
dc.identifier.issn	1526-5501
dc.identifier.uri	http://hdl.handle.net/10453/142786
dc.description.abstract	We examine the effect of the presence of expert buyers on other buyers, the platform, and the sellers in online markets. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item, modeled as its common value. We show that nonexperts may bid more aggressively, even above their expected valuation, to compensate for their lack of information. As a consequence, we obtain two interesting implications. First, auctions with a “hard close” may generate higher revenue than those with a “soft close.” Second, contrary to the linkage principle, an auction platform may obtain a higher revenue by hiding the item’s common-value information from the buyers. We also consider markets where both auctions and posted prices are available and show that the presence of experts allows the sellers of high-quality items to signal their quality by choosing to sell via auctions.
dc.language	en
dc.publisher	INFORMS
dc.relation.ispartof	Management Science
dc.relation.isbasedon	10.1287/mnsc.2016.2530
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Operations Research
dc.title	Expertise in Online Markets
dc.type	Journal Article
utslib.citation.volume	63
utslib.location.activity	United States of America
utslib.for	150202 Financial Econometrics
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Economics Discipline
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2020-09-21T01:54:30Z
pubs.issue	0025-1909(print)
pubs.publication-status	Published
pubs.volume	63
utslib.citation.issue	0025-1909(print)

Abstract:

We examine the effect of the presence of expert buyers on other buyers, the platform, and the sellers in online markets. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item, modeled as its common value. We show that nonexperts may bid more aggressively, even above their expected valuation, to compensate for their lack of information. As a consequence, we obtain two interesting implications. First, auctions with a “hard close” may generate higher revenue than those with a “soft close.” Second, contrary to the linkage principle, an auction platform may obtain a higher revenue by hiding the item’s common-value information from the buyers. We also consider markets where both auctions and posted prices are available and show that the presence of experts allows the sellers of high-quality items to signal their quality by choosing to sell via auctions.

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http://hdl.handle.net/10453/142786