A model of advance selling with consumer heterogeneity and limited capacity

X. Wang () and Chenhang Zeng

Journal of Economics, 2016, vol. 117, issue 2, 137-165

Abstract: We study advance selling in a model with a capacity constraint for the seller and in the presence of both consumer heterogeneity and demand uncertainty. Buyers face different levels of uncertainty about their valuations in the advance selling period: one group of buyers (called informed buyers) know their individual valuations while the other group (called uninformed buyers) only know the distribution of their valuations. We find that the seller’s optimal pricing strategy depends on his capacity size as well as the size of informed buyers. For a small capacity size, the Constant Price strategy with the highest possible price is adopted. For sufficiently large capacity sizes, both Advance Purchase Discount and Advance Purchase Premium strategies may be optimal. In general, the larger the size of informed buyers the more likely an Advance Purchase Premium strategy is adopted. Copyright Springer-Verlag Wien 2016

Keywords: Advance selling; Capacity constraint; Consumer heterogeneity; Demand uncertainty; D42; L12 (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1007/s00712-015-0446-4 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: A Model of Advance Selling with Consumer Heterogeneity and Limited Capacity (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:jeczfn:v:117:y:2016:i:2:p:137-165

DOI: 10.1007/s00712-015-0446-4

Access Statistics for this article

Journal of Economics is currently edited by Giacomo Corneo

More articles in Journal of Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().