Skip to Main content Skip to Navigation

Optimization of Retailers' Strategies in Price- and Carbon Emission- Sensitive Market

Erfan Asgari 1
1 G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production
G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production
Abstract : This work studies the retailer's profit maximization problem and investigates his/her optimal strategies in a price- and greenness- sensitive market. This work starts with a benchmark model where a retailer offers one kind of product to customers. The products are produced by a supplier and sent to the retailer. The retailer keeps the products in a warehouse near the customers to serve them as soon as one arrives. The demand for the products is random and follows the Poisson distribution. The customers' arrival mean rate is sensitive to retail price and carbon emission level of the product. The refilling time of the retailer's warehouse is also random and follows Exponential distribution. The problem consists of deciding the product's price, carbon emission level, and order size. We solve the problem by an analytical approach and provide the closed-form expressions of the optimal solutions.The benchmark model is extended in the way that retailer offers two substitutable products to customers. The demand for each product depends on its price and carbon emission level (decreasing) and depends on the other product's price and carbon emission level (increasing). The retailer's profit maximization problem is formulated in a stochastic environment under different settings (decision variables) and is solved by an analytical approach. According to the results, the market is distinguished into three categories: 1- Greenness-Driven Switchovers market, 2- Price-Driven Switchovers market, and 3- Neutral market. Different market structures provide useful insights.Dynamic competition between two retailers, which each of them has its supplier, is considered. Retailers offer two substitutable products that each of them offers one kind of product. Two symmetric mathematical models decide the products' prices, carbon emission levels, and order sizes. Each retailer's decision affects the other retailer's decision. The general problems are solved by an analytical approach and determined the Nash equilibrium. However, in practice, there are many situations where an existing retailer is already operating in the market, and a new retailer enters the market. Two situations are considered and solved: 1- Competition without reaction and 2- Competition with partial reaction. The close-form expressions of the optimal solutions are presented for all scenarios.This work ends its studies by introducing a non-linear demand function. In the literature, all studies consider a linear demand function (to the best of our knowledge). However, our partners in project ANR CONCLuDE found out that the linear function is not sufficient. Thus, a new non-linear demand function is considered concerning carbon emission improvement. Our partners' studies also reveal that improving greenness leads to increasing the demand for a certain amount of market potential, and after that, it is constant. The second demand function is called cap. The benchmark model is re-formulated with different demand functions and solved. Then, closed-form expressions of optimal solutions are presented. A numerical example is conducted to compare profits with different demand functions. The non-linear cap is considered as a reference and compared to others. The results reveal that when the maximum attracted costumers are low (below 20%), the linear cap model performs better than others do. When it is high, the non-linear model performs better.
Document type :
Complete list of metadata
Contributor : Abes Star :  Contact
Submitted on : Tuesday, May 18, 2021 - 11:31:08 AM
Last modification on : Thursday, May 20, 2021 - 3:20:23 AM


Version validated by the jury (STAR)


  • HAL Id : tel-03228544, version 1



Erfan Asgari. Optimization of Retailers' Strategies in Price- and Carbon Emission- Sensitive Market. Modeling and Simulation. Université Grenoble Alpes [2020-..], 2021. English. ⟨NNT : 2021GRALI001⟩. ⟨tel-03228544⟩



Record views


Files downloads