Pricing and referrals in diffusion on networks

• 成果类型: Article
• 署名作者: Leduc, Matt V.; Jackson, Matthew O.; Johari, Ramesh
• 署名单位: Stanford University; Stanford University; International Institute for Applied Systems Analysis (IIASA); Canadian Institute for Advanced Research (CIFAR); The Santa Fe Institute
• 刊物名称: GAMES AND ECONOMIC BEHAVIOR
• ISSN/ISSBN: 0899-8256
• DOI: 10.1016/j.geb.2017.05.011
• 发表日期: 2017
• 页码: 568-594
• 关键词: Network games; technology adoption; social learning; Word-of-mouth; Network diffusion; Dynamic pricing; Referral incentives

摘要

When a new product or technology is introduced, potential consumers can learn its quality by trying it, at a risk, or by letting others try it and free-riding on the information that they generate. We propose a dynamic game to study the adoption of technologies of uncertain value, when agents are connected by a network and a monopolist seller chooses a profit maximizing policy. Consumers with low degree (few friends) have incentives to adopt early, while consumers with high degree have incentives to free ride. The seller can induce high degree consumers to adopt early by offering referral incentives-rewards to early adopters whose friends buy in the second period. Referral incentives thus lead to a 'double-threshold strategy' by which low and high-degree agents adopt the product early while middle degree agents wait. We show that referral incentives are optimal on certain networks while inter-temporal price discrimination is optimal on others. (C) 2017 Elsevier Inc. All rights reserved.