The impact of recommender systems and pricing strategies on brand competition and consumer search

As a type of internet and business intelligence technology, recommender systems have been widely adopted by store brands to improve brand competition and to affect consumers’ search behaviors in the e-commerce market. This paper studies the effects of recommender systems and pricing strategies on the competition between store brands and national brands and on consumers’ search behaviors. We develop game models without and with recommender systems and analyze the equilibrium solutions under uniform pricing and differential pricing strategies. The results show that the brand-preference consumers’ market share will affect the strategy choice of recommendation system and differential pricing for the store brand. When the store brand is recommended, the store brand should adopt the differential pricing strategy and the price of the store brand will exceed that of the national brand. Furthermore, we also find that when the brand-preference consumers’ market share is low and the reservation price difference is high, the store brand can gain the competitive advantage by improving recommendation strength. In addition, a recommender system attracts consumers by converting their search costs into the recommendation costs of the system.