Differential pricing in social networks with strategic consumers

• 成果类型: Article
• 署名作者: Zheng, Rui; Shou, Biying; Chen, Yingju
• 署名单位: Wuhan University of Technology; Wuhan University of Technology; City University of Hong Kong; Hong Kong University of Science & Technology
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.13999
• 发表日期: 2023
• 页码: 2638-2655
• 关键词: differential pricing; game theory; Network externality; social network; Strategic Consumers

摘要

This study analyzes a monopolistic seller's optimal differential pricing problem with strategic consumers connected in social networks. The consumers who purchase in the later period can get positive externalities from their friends who purchased in the early period but have to bear a utility discount for the delayed consumption. We first characterize consumers' strategic purchase decisions under general network structures. We then derive the optimal differential pricing strategies and demonstrate that different network structures lead to substantially different strategies. We find that when the intensity of the network externality effect is lower than a threshold and the influence matrix is symmetric, it is always optimal for the seller to conduct an increasing-pricing strategy. However, when the network externality effect is strong, a decreasing-pricing strategy may also be optimal. We further examine how the imbalance of influence, degree heterogeneity, and network topology impact the optimal pricing policy and profit. We find that when the intensity of network externality is relatively low, it is more profitable to sell products through many interconnected low-influencer networks; however, when the network externality intensity is high, it is better to sell through a few high-influencer networks. Finally, we show that the profit loss caused by uniform pricing strategies or by ignoring consumer network structures can be significant under certain conditions, thereby revealing the substantial value of differential pricing in social networks.