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Maximizing profit of a food retailing chain by targeting and promoting [An article from: European Journal of Operational Research]
Book Details
Author(s)
G. Pauler, A. Dick
Publisher
Elsevier
ISBN / ASIN
B000P6ODSO
ISBN-13
978B000P6ODS6
Availability
Available for download now
Sales Rank
#9,666,278
Marketplace
United States 🇺🇸
Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
In this paper, we set up a House of Profit Model, an approach of maximizing profit of a food retailing chain by targeting and promoting valuable customers. Our model combines*segmentation analysis of households using Loyalty Card and Scanner Data, *price and promotion elasticity analysis, *simulation of effects of pricing and promotion, *price and promotion optimization to maximize profit. These components are well-known in the literature and each of them has received considerable independent study. However, in this study we combine each of these components into one consistent, application-orientated model. We then demonstrate using panel data that the combination has a synergic effect on the efficiency of estimation and the maximization of profit (e.g., price and promotion elasticity estimation is improved by conducting it within market segments rather than across an entire hetereogeneous population). These estimates are further improved by incorporating ''pass through''-a functional relationship between a retailer's unit prices and unit costs.
Description:
In this paper, we set up a House of Profit Model, an approach of maximizing profit of a food retailing chain by targeting and promoting valuable customers. Our model combines*segmentation analysis of households using Loyalty Card and Scanner Data, *price and promotion elasticity analysis, *simulation of effects of pricing and promotion, *price and promotion optimization to maximize profit. These components are well-known in the literature and each of them has received considerable independent study. However, in this study we combine each of these components into one consistent, application-orientated model. We then demonstrate using panel data that the combination has a synergic effect on the efficiency of estimation and the maximization of profit (e.g., price and promotion elasticity estimation is improved by conducting it within market segments rather than across an entire hetereogeneous population). These estimates are further improved by incorporating ''pass through''-a functional relationship between a retailer's unit prices and unit costs.
