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- W3136138139 abstract "We consider the problem of determining the optimal prices and product configurations of horizontally differentiated products when customers purchase according to a locational (Hotelling) choice model, and where the problem parameters are initially unknown to the decision maker. Both for the single-product and multiple-product setting we propose a data-driven algorithm that learns the optimal prices and product configurations from accumulating sales data, and we show that their regret -- the expected cumulative loss caused by not using optimal decisions -- after T time periods is O(T^{1/2 + o(1)}). We accompany this result by showing that, even in the single-product setting, the regret of any algorithm is bounded from below by a constant times T^{1/2}, implying that our algorithms are asymptotically near-optimal. A numerical study that compares our algorithms to a benchmark shows that our algorithm is also competitive on a finite time horizon." @default.
- W3136138139 created "2021-03-29" @default.
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- W3136138139 date "2020-01-01" @default.
- W3136138139 modified "2023-09-26" @default.
- W3136138139 title "Pricing and Positioning of Horizontally Differentiated Products with Incomplete Demand Information" @default.
- W3136138139 doi "https://doi.org/10.2139/ssrn.3682921" @default.
- W3136138139 hasPublicationYear "2020" @default.
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