2020
DOI: 10.1007/s10107-020-01495-0
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Revenue maximization in Stackelberg Pricing Games: beyond the combinatorial setting

Abstract: In a Stackelberg Pricing Game a distinguished player, the leader, chooses prices for a set of items, and the other players, the followers, each seek to buy a minimum cost feasible subset of the items. The goal of the leader is to maximize her revenue, which is determined by the sold items and their prices. Most previously studied cases of such games can be captured by a combinatorial model where we have a base set of items, some with fixed prices, some priceable, and constraints on the subsets that are feasibl… Show more

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Cited by 13 publications
(5 citation statements)
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“…Furthermore, the wholesale price in the Stackelberg game is also considerably higher than the sales margin of the retailer. Given that the follower cannot compete with the leader in profit payoffs, the follower tends to only minimize their cost (Böhnlein et al, 2021). The delivery lead‐time decision is very close to the delivery lead time limitation ( tdlvr).…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, the wholesale price in the Stackelberg game is also considerably higher than the sales margin of the retailer. Given that the follower cannot compete with the leader in profit payoffs, the follower tends to only minimize their cost (Böhnlein et al, 2021). The delivery lead‐time decision is very close to the delivery lead time limitation ( tdlvr).…”
Section: Discussionmentioning
confidence: 99%
“…Balcan et al [3] and Briest et al [7] provide a simple logarithmic approximation algorithm for Stackelberg games with shortest path followers. B öhnlein et al [5] extend the analysis of this simple algorithm beyond the combinatorial setting. Cristi and Schr öder [11] study the difference in revenue between positive and unrestricted prices.…”
Section: Related Literaturementioning
confidence: 99%
“…Balcan et al [6] and Briest et al [10] considered the power of single-price strategies. Böhnlein et al [9] extended the analysis of this simple algorithm beyond the combinatorial setting.…”
Section: Related Workmentioning
confidence: 99%