Submitted by Marcelo Sant'Anna (marcelos@fgvmail.br) on 2010-07-20T19:55:28Z No. of bitstreams: 1 dissertVF.pdf: 409746 bytes, checksum: ca7db8bc8077f795d693bed9b119adac (MD5) / Approved for entry into archive by Andrea Virginio Machado(andrea.machado@fgv.br) on 2010-07-22T12:27:19Z (GMT) No. of bitstreams: 1 dissertVF.pdf: 409746 bytes, checksum: ca7db8bc8077f795d693bed9b119adac (MD5) / Made available in DSpace on 2010-07-23T19:33:54Z (GMT). No. of bitstreams: 1 dissertVF.pdf: 409746 bytes, checksum: ca7db8bc8077f795d693bed9b119adac (MD5) Previous issue date: 2010-07-07 / We develop a model to study shelf space allocation in retail. Retailers compete for consumers not only choosing prices but also by the space allocated to each product on shelves. Our approach depart from the existing literature on shelf allocation, as we model the problem of price setting and shelf allocation in an oligopolistic retail market. We present a simple model of retail competition in which prices are dispersed in the crosssection of stores but shelf allocation is not.

No description available.

<p>In today's retail environment, there are many consumer packaged goods (CPG) in the same category with various brands and differential products under the same brand. These differential products appear in different dimension sizes, display facing areas, purchasing costs and selling prices which are competing for a limited space in retail store shelves. Product assortment and space allocation of the chosen products to a limited shelf space is becoming more and more important for retailers. In this thesis we critically review the existing literature of shelf space allocation optimization models and solution techniques. We then propose a comprehensive model for shelf space allocation for a product category. Products are allocated to a two-dimensional area of a shelf section where a shelf section consists of multilevel vertical shelves. We account for adjustable shelf heights and product and brand integrity in a shelf section. Unlike the existing optimization models in the literature, we model our demand not only as a function of the space allocated to a product, in terms of the number of display facings, but also as a function of vertical product location in a shelf section and price sensitivity. Stackability of the products is also considered and products can be stacked depending on their package. Our objective is to maximize the retailer's daily gross profit. We numerically show that incorporating price changes and adjustable shelf spaces can have major impacts on the retailers' profit. Finally, we provide directions and suggestions for future research in this growing area of research.</p> / Master of Applied Science (MASc)

This thesis includes three self-contained projects: In the first project Bidding strategies and their impact on the auctioneer's revenue in combinatorial auctions, focusing on combinatorial auctions, we propose a simple and efficient model for evaluating the value of any bundle given limited information, design bidding strategies that efficiently select desirable bundles, and evaluate the performance of different bundling strategies under various market settings. In the second project Retailer shelf-space management with promotion effects, promotional investment effects are integrated with retail store assortment decisions and shelf space allocation. An optimization model for the category shelf-space allocation incorporating promotion effects is presented. Based on the proposed model, a category shelf space allocation framework with trade allowances is presented where a multi-player Retailer Stackelberg game is introduced to model the interactions between retailer and manufacturers. In the third project Supply-chain oriented robust parameter design, we introduce the game theoretical method, commonly used in supply-chain analysis to solve potential conflicts between manufacturers at various stages. These manufacturing chain partners collaboratively decide parameter design settings of the controllable factors to make the product less sensitive to process variations.