THE OPTIMAL MARKETING & QUALITY-DISCOUNTING STRATEGY FOR A FIRM SELLING PERISHABLE GOODS / Elodie PRIORIS / 2020

Titre : THE OPTIMAL MARKETING & QUALITY-DISCOUNTING STRATEGY FOR A FIRM SELLING PERISHABLE GOODS Type de document : Mémoire Auteurs : Elodie PRIORIS, Auteur Année de publication : 2020 Importance : 21 p. Note générale : Pour accéder aux fichiers PDF, merci de vous identifier sur le catalogue avec votre compte Office 365 via le bouton CONNEXION en haut de page. Langues : Anglais (eng) Mots-clés : Management STRATEGIE ; MARKETING STRATEGIQUE ; FIXATION DES PRIX ; GESTION DE LA QUALITE Résumé : Many firms face challenges when trying to come up with an optimal marketing and pricing strategy. Marketing teams try to analyze the customers’ habits, categorize them and determine which customers to serve in order to generate higher profit. Then, according to the profile of the customers chosen to be served, revenue management teams set the price that will both satisfy the customers targeted and optimize the firm’s revenue. Revenue managers will have to take into account some criteria when determining the price of a product such as customers sensitivity to price, their sensitivity to quality and the quality of the product. This paper will focus on how marketing and revenue management teams can optimize the profit generated by one perishable good in a monopolistic setting. In this paper, we use non-linear mixed integer programming through 2 models to find the optimal marketing strategy and the optimal quality-discounting strategy. The data used in the numerical example of this paper are fictitious. Some retail shops mark their fresh products down by 50% when they are expected to expire shortly. This markdown strategy seems to be common. However, we think that this strategy should differ accordingly to the customers’ expectations which may vary depending on the type of product and its brand. Thus, we choose to build models hoping that they will be useful for managers and retailers to optimize the profit of a specific product. We have decided to run 2 models using Excel Solver to find the optimal profit. We have chosen to categorize the firm’s customers in 2 segments. The new segment which will tend to buy the product at its full price and as early as possible to buy a product of good quality. The old segment which will tend to buy the product with a discount later on and cares less about quality. We also came up with 2 categories for the product. It is considered either “new” (placed recently on shelves) or “old” (placed on shelves for quite a while and expires in a shorter time than the “new” product). In the first model, the 2 segments are interested in either buying the “new” or the “old” product. In the second model, only the new segment is interested in buying the “new” or the “old” product. By comparing, the profit generated in these 2 models, the firm knows if it should go after only after the new segment or after both segments. If the company’s marketing strategy is to go after the new segment, it will sell the product full price. However, if the company’s marketing strategy is to go after both segments, it will determine the percentage of discount to satisfy the old segment and when to introduce it. Based on the results of this seminar paper, we notice that the outcome of our 2 models can help managers take optimal decisions. After having established the quality and price sensitivity of their customers, they can determine the optimal marketing and quality-discounting strategy. These models also alert them about the dangers of cannibalization. If the new segment copies the behavior of the old one, there is a decrease in profit. However, our models also show some limitations. We have decided that all the members of one segment behave the same way knowing that in reality it is not the case. Moreover, we can never be sure of finding the optimal solution of a nonlinear problem. These two main limitations may affect the quality of our results. The remainder of this seminar paper is organized as follows. Section 2 gives us information about the benefits and drawbacks of marking down products. It also provides strategies about how to profitably implement markdowns. Section 3 introduces both our 2 non-linear programming models and a numerical example with its results and analysis. Finally, section 4 is a conclusion of this seminar paper. Programme : PGE-Rouen Spécialisation : Supply chain Management and purchasing Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=531067