Dynamic Pricing Of Multi-product Considering Consumer's Anticipated Regret

Due to the prevalence of consumers' strategic behavior,related issues have attracted sufficient attention from academics and retailers.However,most of the existing related literature just considers a single product situation,and rarely involves the consumers behavior.It is imperative to explore reasonable and effective multiple product pricing strategies based on consumers' strategic behaviors.On the basis of existing literature,this paper combines anticipated regret and dynamic pricing,and introduces anticipated regrets into the consumer utility function.On one hand,leading the invisible consumer regrets and the price of the product as mutually restricting variables integrated into the mathematical model.From the perspective of consumers,we analyze deeply how the consumers choose when to buy for maximized utilities according to the retailer's pricing strategy in the Stackelberg game between retailers and consumers,and give strategic consumers' decisions under different conditions.On the other hand,two replaced products are combined through price and profit.From the retailer point of view,constructs a two-stage dynamic pricing model,and use backward induction to reversed the pricing strategy leading to the market demand classification.Based on maximizing retailers' profit,this paper discusses all the retailers' product portfolio strategy,and gives the optimal pricing strategy for each scenario.Finally,this paper discusses the effect of the parameters changing in the dynamic pricing model on the retailer's optimal product pricing and profit by numerical analysis.The research shows that the cost and quality factors,and product's availability in the second stage will exert an impact on retailers' pricing strategy and benefit.