Seller's Pricing Discrimination Strategies under Adoption of Online Big Data Technology

With the rapid development of big data technology, a seller can identify its targeted customers precisely and comprehensively. Therefore, the seller can take pricing discrimination strategies when facing heterogeneous customers. This paper uses a two-stage game model to learn and compare the seller's three types of pricing strategies: no discrimination, two-part discriminatory pricing, and personalized discriminatory pricing. We found that sellers' profit adopting a discriminatory pricing strategy is higher than that of a traditional single pricing strategy. At the same time, for the comparison of the two discriminatory pricing strategies, customers find that the company is more likely to adopt a discriminatory pricing strategy. The cost of strategy and data input is low, and the company adopts a personalized and more favorable price discrimination strategy. Otherwise, it adopts a double price discrimination pricing strategy.