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1. Introduction
The selection and sale of inventory is the raison d’etre of all merchandise retailing (Fisher and Raman, 2010). The problem becomes more complicated when there are a large number of products to display, but limited available shelf space. Low margins, the growing need for operational efficiency and ever greater customer orientation are therefore forcing retailers to develop efficient decision support systems to manage product availability. Despite heavy investment in point-of-sale technology, retailers are still losing potential revenue due to their inability to get the right goods to the right places at the right time. There is also empirical evidence that assortments have become so excessive and reducing variety significantly increases sales (Boatwright and Nunes, 2001; Sloot and Verhoef, 2008). Iyengar and Lepper (2000) suggest that consumers are more likely to purchase consumer goods when offered only a limited array of choices. Boatwright and Nunes (2001) found that significant item reductions (up to 54 percent) resulted in an average sales increase of 11 percent across 42 categories examined, and sales growth in more than two-thirds of these categories. Studies show that between 45 and 84 percent of demand can be substituted (e.g. Gruen et al., 2002; van Woensel et al., 2007; Xin et al., 2009). The average potential for substitution depends on product-, situation- and consumer-specific characteristics and is generally higher for fresh products (Xin et al., 2009).
In addition, Kuhn and Sternbeck (2013) show that operational planning questions are impacted by assortment decisions. Retailers need to match consumer demand with shelf supply by balancing variety (number of products) and shelf service levels (number of items of a product). Offering broader assortments thus limits appropriate service levels and vice versa, because shelf space is scarce. For example, a retailer can list more brands, but then has less space for each brand (given that shelf space is limited) and needs to reorder the items more frequently, which reduces storage duration but increases the risk of running out of stock. The problem becomes especially critical for perishable items, i.e. fresh goods with a limited shelf life. Hence, an advanced category planning model needs to balance supply and demand effects.
Most retailers have now adopted software programs for creating allocation plans. However, as...