关键词: 在线评价, 评价呈现机制, 定价策略

Abstract: This study explores optimal pricing strategies and online review provision policies for firms selling substitutable products in markets with social learning. Using a two-period model, we compare two common review policies: displaying reviews separately for each version (the separated policy) and aggregating reviews across all versions (the aggregated policy). We find that online reviews generally induce firms to adopt penetration pricing strategies. The optimal review policy depends crucially on two factors: product display quality and consumer learning speed. The aggregated policy is more profitable for low-quality products with slow learning, as it mitigates quality assessment noise through information aggregation. Conversely, the separated policy outperforms for high-quality products with rapid learning, as it provides precise quality signals. Within optimized thresholds, each policy achieves a triple-win: increasing firm profits, consumer welfare, and social surplus.

Key words: online reviews, review provision policy, pricing strategy