Dynamic Pricing with Volume Discounts in Online Settings

نویسندگان

چکیده

According to the main international reports, more pervasive industrial and business-process automation, thanks machine learning advanced analytic tools, will unlock than 14 trillion USD worldwide annually by 2030. In specific case of pricing problems, which constitute class problems we investigate in this paper, estimated unlocked value be about 0.5 per year. particular, paper focuses on e-commerce when objective function is profit maximization only transaction data are available. This setting one most common real-world applications. Our work aims find a strategy that allows defining optimal prices at different volume thresholds serve classes users. Furthermore, face major challenge, settings, dealing with limited We design two-phase online algorithm, namely PVD-B, capable exploiting incrementally an fashion. The algorithm first estimates demand curve retrieves average price, subsequently it offers discounts differentiate for each threshold. ran 4-month-long A/B testing experiment collaboration Italian company, our PVD-B - corresponding A configuration has been compared human specialists B configuration. At end experiment, produced total turnover 300 KEuros, outperforming performance 55%. company collaborated decided adopt 1,200 products since January 2022.

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ژورنال

عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence

سال: 2023

ISSN: ['2159-5399', '2374-3468']

DOI: https://doi.org/10.1609/aaai.v37i13.26845