Abstract:

In the era of digital economy， with the advancement of artificial intelligence and digital mining technologies， firms are increasingly able to extract valuable information from consumer data. By creating precise consumer profiles， firms can engage in third-degree or even first-degree price discrimination. This gives rise to issues such as “big data discriminatory pricing” and personal information protection， posing significant challenges to government policymaking. A two-period dynamic duopoly model is constructed to study firms' pricing strategies and consumers' purchasing decisions. Based on the model， the fundamental characteristics and mechanisms of personalized pricing by firms are analyzed based on consumers' purchasing histories. Furthermore， a comparative analysis of different personal information protection policies is conducted from the perspective of welfare metrics and implications for management are provided.The main conclusions of this paper are as follows　First， under both mandatory and no personal information protection policies， the phenomenon of “big data-driven price discrimination” emerges. Under voluntary personal information protection policy， firms raise uniform prices in the second period to erect a “price barrier” for consumers， colluding tacitly to avoid repeated competition for new and existing consumers， while simultaneously engaging in first-degree price discrimination toward their loyal customers. Although this eliminates the appearance of “big data discriminatory pricing”， it weakens market competition and deprives all consumers of their surplus in the second period through personalized pricing. Second， under voluntary personal information protection policy， first-degree price discrimination does not result in deadweight loss to social welfare but does lead to an inequality in producer and consumer welfare. Optimal social welfare and producer surplus can be achieved， but the consumer surplus reaches its lowest level. In contrast， under no personal information protection policy， market competition is intensified by addressing initial market share asymmetries， resulting in suboptimal social welfare and consumer surplus but the lowest producer surplus. Inefficient allocation of information resources leads to unnecessary social welfare losses， suggesting that mandatory personal information protection policy only achieve minimal social welfare. Third， given that optimal producer and consumer surplus cannot be achieved simultaneously， the government should adopt a problem-oriented approach when selecting policies and carefully balance efficiency and equity considerations. Specifically， to address efficiency issues in the digital economy， the government could adopt voluntary personal information protection policy， transferring consumer surplus to firms to curb “big data discriminatory pricing” and thereby enhance overall social welfare. To address equity issues， the government could implement no personal information protection policy to foster market competition， improve consumer welfare， and achieve suboptimal social welfare.

Key words: digital economy, price discrimination, personal information protection, social welfare