The return policy has attracted considerable attention in the success of online selling, both in academia and the industrial world. On the first try, Pasternack [

20] addressed the well-known newsvendor problem for a seasonal product with a fixed price and stochastic demand. In his model, a percentage of the lot size may be returned from retailers to the manufacturer. Later, Kandel [

21] and Emmons and Gilbert [

22] extended Pasternack’s [

20] research to a case in which the demand is price sensitive. Emmons and Gilbert [

22] analyzed the impact of a return policy in pricing and inventory decisions on a supply chain comprised of a manufacturer and a retailer. Lau and Lau [

23] analyzed the pricing and return policies of a monopolistic manufacturer for single-period commodities. In addition, Webster and Weng [

24], and Yao et al. [

25] focused on return policies between the manufacturer and the retailer. Ringbom and Oz [

26] proposed methods to determine the optimal rates of partial refunds on customers’ no-shows and cancellations. According to Mukhopadhyay and Setaputra [

27], a good return policy increases a product’s demand. The reason for this is that some customers perceive the return as a motivator for their purchasing decisions. In the same year, Yue and Raghunathan [

28] examined the full return policy’s impact on the supply chain with information asymmetry. They found that the retailer always benefits from a full return policy, in all situations, whereas the manufacturer and the supply chain are better off under some circumstances. Yao et al. [

29] investigated the impact of price-sensitivity factors on features of return policy contracts in a single-period product, considering a stochastic and price-dependent demand. Yu and Wang [

30] proposed a multi-dimensional framework to obtain the optimal returns policies under the direct sale channel. Su [

31] studied the impact of full refund policies and partial refund policies on supply chain performance. On the other hand, Chen and Bell [

32] addressed the problem of the joint determination of price and inventory replenishment when clients return items to the vendor. They conclude that the vendor should change the price and order quantity to reduce the negative effect of returns. Subsequently, Bonifield et al. [

33] examined the relationship between quality and a flexible return policy. Afterward, Xiao et al. [

34] studied the supply chain coordination with customer returns behavior and a buyback policy. They consider the order quantity as a decision variable, and the retail price and refund amount as given. Later, Chen and Bell [

35] studied the impact of the returns from the customer on retailer’s price and order quantity, for both deterministic and stochastic demand, considering that returns from customers are dependent on the quantity sold or price, or both. One year later, Ai et al. [

36] analyzed the decisions of retailers and manufacturers on two competing supply chains selling a substitutable product, with a demand uncertainty in the cases when manufacturers use or do not use full return policies. In their paper, Chen and Grewal [

37] discussed how a new entrant retailer can practice either a full refund policy or a non-refund policy, to compete with a well-established retailer that always offers its customers a full refund. Afterward, Liu et al. [

38] examined a supply chain with a single manufacturer and a single retailer considering uncertain demand. They investigated how customer returns impact the retailer’s ordering decisions as well as the manufacturer’s and retailer’s profits. Recently, Yoo et al. [

39] analyzed the optimal pricing decision in a closed-loop supply chain under a return policy. Joint pricing and the environmental friendliness level model were presented by Giri and Bardhan [

40]. Heydaryan and Taleizadeh [

41] proposed a return policy depending on the selling price and refund amount for a two-echelon supply chain. They analyzed the proposed model by considering cooperative and non-cooperative games. Hu et al. [

42] studied a dynamic pricing problem when customers can return their purchased products. They showed that this return policy can increase profit when the initial inventory and demand are moderate and high, respectively. Noori-daryan and Taleizadeh [

43] modeled a pricing-inventory problem for a three-echelon supply chain. They considered the return policies between manufacturer, supplier and retailer. Ren et al. [

44] studied the pricing and return policies of online retailers. This research dealt with pricing and inventory models for a single product.

All of the reviewed studies have been focused on modeling and analyzing the return policy along with other decision variables for single products. Our model differs from those in the existing literature in that it analyzes the pricing, quality, and return policy for complementary products.