iBundle: an efficient ascending price bundle auction
Proceedings of the 1st ACM conference on Electronic commerce
Bundling Information Goods: Pricing, Profits, and Efficiency
Management Science
Pricing information bundles in a dynamic environment
Proceedings of the 3rd ACM conference on Electronic Commerce
Preference elicitation in combinatorial auctions
Proceedings of the 3rd ACM conference on Electronic Commerce
Bundling and Competition on the Internet
Marketing Science
Combinatorial Auctions
Approximating revenue-maximizing combinatorial auctions
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Multi-unit combinatorial reverse auctions with transformability relationships among goods
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Multi-unit combinatorial reverse auctions with transformability relationships among goods
WINE'05 Proceedings of the First international conference on Internet and Network Economics
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In this paper, we consider the design of an agent that is able to autonomously make optimal bundling decisions when selling multiple heterogeneous items within existing online auctions. We show that while bundling the items together into a single lot is effective at reducing listing costs, it also results in a loss in auction revenue. To address this loss we introduce a novel bundling strategy, that we call pick-a-bundle, that can be implemented within any existing auction format. We show, mainly using simulations, that this new bundling strategy generates greater expected revenue than the complete bundle of all items, and, by inducing additional competition between bidders, it usually generates greater expected revenue than using separate auctions for each item. In order for our agent to accurately and efficiently calculate its expected revenue when using our new strategy, we derive a novel polynomial time algorithm for calculating the probability distributions of the sum of the top order statistics of i.i.d. variables drawn from any arbitrary distribution. Furthermore, we include in our analysis the strategic behaviour, in terms of bid shading, that the buyers may consider in our new auction format.