Revenue Maximization on the Multi-grade Product.
Journal
Proceedings of the 2018 SIAM International Conference on Data Mining, SDM 2018, May 3-5, 2018, San Diego Marriott Mission Valley, San Diego, CA, USA.
Pages
576-584
Date Issued
2018
Author(s)
Abstract
The problem of revenue maximization, which aims at earning the highest revenue by properly pricing the product and/or seeding customers, is an important issue about utilizing the social influences. In this paper, we are interested in the marketing of the multi-grade product, where the different grades of a product from a company, such as iPhone 8, iPhone 8 Plus, and iPhone X, have both competitive and promotional relationships. For the study, a new diffusion model named MuG-IC (Multi-Grade IC) is first proposed based on the IC and the concave graph models to describe the phenomena of social influences regarding the multi-grade product. Afterwards, we then study the revenue maximization upon the MuG-IC and solve the problem by designing a novel algorithm named PS (Pricing-Seeding). The PS algorithm can give proper suggestions of pricing each grade of the product and seeding customers by tuning the suggestions in an iterative manner. The experiments conducted on the real network structure with simulated valuation distributions from Amazon.com demonstrate the effectiveness of the proposed algorithm.
Type
conference paper