Product demand sensitivity and the corporate diversification discount

Siraj, Ibrahim; Hassan, M. Kabir; Maroney, Neal

doi:10.1016/j.jfs.2020.100748

Cited by 2 publications

(2 citation statements)

References 45 publications

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“…Finally, some researchers have analyzed lot-sizing decisions with price-sensitive demand, including exploring all-quantity discounts to generate an optimal lot-sizing decision [22][23][24][25]. Recent studies have also looked at product demand sensitivity variations using discounts and price patterns [26][27][28][29][30].…”

Section: Literature Reviewmentioning

confidence: 99%

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A Mathematical Model for an Inventory Management and Order Quantity Allocation Problem with Nonlinear Quantity Discounts and Nonlinear Price-Dependent Demand

Alejo-Reyes

Mendoza

Cuevas

et al. 2023

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This article focuses on solving the order quantity allocation problem for retailers. It considers factors such as quality constraints, nonlinear quantity discounts, and price-dependent demand. By formulating it as a nonlinear maximization problem, the article aims to find the best combination of suppliers and order quantity out of infinite solutions to maximize the retailer’s profit. The main contribution of this research is a new mathematical model that can solve the problem of quality constraint and demand in a single step. This problem is complex due to the number of equations, their nonlinear nature, and the various trade-offs given by the market. Additionally, this research considers demand as output and includes price-dependent demand, which is more realistic for retailers. The proposed model was tested using an example from the recent literature and showed better results than the previously published best solution regarding profit maximization.

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Section: Literature Reviewmentioning

confidence: 99%

“…Since Q i and j i are positive numbers, no combination can satisfy Equation (26). Since this situation (low perfect rate situation) might be possible in real life, it is highly desirable that models can deal with it.…”

Section: Model Analysismentioning

confidence: 99%