Pricing Decision within an Inventory Model for Complementary and Substitutable Products

Abstract

A combination of substitutable and complementary products is very important for any business industry to make all-round profit from different aspects. How deterioration affects complementary products or substitutable products is discussed in this study. This study investigates the pricing and inventory decisions for complementary and substitutable items which are deteriorating in nature. Four models are analyzed where the demand of one product is dependent upon the selling price and the price of another product. This paper tries to compute the optimum prices and order quantities to optimize the total profit, which is the main aim. Theoretically, this model is solved by a classical optimization method. Numerical examples demonstrate the applicability of this model. Results conclude that the total profit is dependent on the degree of substitutability and complementarity. A sensitivity analysis of optimal solutions is given to test the stability of the proposed model.

Optimal Multiple Attribute Decision Model for Key Parameters of Online Group Buying Product

“…This study focused on the selling price of online group purchases and considered various parameters, such as the upper limit of demand L, the unit cost c, the influence coefficient of the price on demand E, etc. This study used the grey correlation ranking method and grey multi-attribute decision-making (TOPSIS) to further determine the optimal shelf-time, inventory quantity, and selling price (key parameters) of commodities in order to design a plan that makes the maximum profit for the industry and provides the best service to customers [6][7][8][9][10][11][12]. In previous studies, Ni et al [9], considered the optimal fixed-price decisions, Deng et al [10] considered the optimal price and maximum deal size, and Lu et al [2] considered effect of behavior on workplace relationships in online group purchasing.…”

“…In order to consider the integration results of all the properties of plan e j with the estimation according to different properties, consider the TC * j weights of different properties, as shown in Equation (12). The calculation of A j is shown in Equation (13).…”

“…Therefore, this study focuses on the selling price of online group buying products and considers various parameters, such as the upper limit of demand L, the unit cost c, the influence coefficient of price on demand E, etc. This study uses the grey correlation ranking method and grey multi-attribute decision-making (plan selection) to further plan the optimal shelf-time, inventory quantity, and selling price (key parameters) of commodities in order to design a plan that makes maximum profit for the industry and provides the best service to customers [6][7][8][9][10][11][12].…”

Impact of cost of substitution and joint replenishment on inventory decisions for joint substitutable and complementary items under asymmetrical substitution

“…Under two-way substitution, Pan et al (2018) developed an inventory replenishment model for two-inventory based substitutable items with full substitution and obtained the optimal replenishment cycle time and ending inventory levels, Chen et al (2019) developed an inventory model for Joint replenishment decision-taking shortages, partial demand substitution, and defective items and Mokhtari (2018) developed an EOQ model for two-substitutable items where one item is composed with two complementary components and considered joint ordering policy and full substitution. Taleizadeh et al (2019) studied the pricing decision of two items where items may be complementary or substitutable and Edalatpour et al 2019analyzed simultaneous pricing and inventory decisions for complementary and substitutable items considering nonlinear holding cost. To best of our knowledge, research paper with parameter cost of substitution, joint replenishment, complementary and substitutable items and partial substitution, together is not available in the literature to obtain the optimal ordering quantities, optimal total cost and extreme value of substitution.…”

Optimum Design of a Transportation Scheme for Healthcare Supply Chain Management: The Effect of Energy Consumption

“…The demand Dm h i t that occurs in one working shift must be fully covered within the same shift in one trip to maintain energy efficiency [55]. In addition, the maximum demand of one hospital per day is assumed to be 30 units or less [56].…”