Joint pricing, assortment, and inventory decisions for a retailer's product line

Maddah, Bacel; Bish, Ebru K.

doi:10.1002/nav.20209

Cited by 87 publications

(54 citation statements)

References 20 publications

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“…This may help explain the numerical findings of Maddah and Bish (2007), which assumes a logit demand model but uses a different approximation. They found that offering the most popular products may not be optimal, but still gives a profit very close to the optimal profit (see Tables 1-3 therein).…”

Section: The Monopoly Casementioning

confidence: 99%

“…Using a continuous approximation, they found a similar monotonic assortment result holds in a supply chain. Maddah and Bish (2007) and Bish and Maddah (2004) studied a joint pricing, assortment, and inventory decision model for logit demand (still without demand substitution). They used numerical experiments to show that a monotonic assortment is nearly optimal and concluded that inventory cost tends to limit product variety.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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A Static Approximation for Dynamic Demand Substitution with Applications in a Competitive Market

Hopp

2008

Operations Research

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We propose a static approximation of dynamic demand substitution behavior based on a fluid network model and a serviceinventory mapping. This approximation greatly enhances our ability to analyze the interdependent inventory/service, price, and product assortment decisions in noncompetitive and competitive scenarios with demand substitution. We demonstrate that the approximation is well behaved and then apply it to two previously intractable applications. First, we study a price and service competition between single-product retailers. After establishing a unique pure-strategy Nash equilibrium, we find that competition results in lower price, higher demand, and a higher level of inventory. We also observe that the aggregate profit and inventory level increase to positive constants as the number of retailers goes to infinity. Second, we study a duopolistic competition on price, service, and product assortment. We establish a pure-strategy Nash equilibrium for the product assortment competition and identify a condition for uniqueness. We find that competition on both price and product assortment results in lower price and less variety for each competitor, but the total number of products and the aggregate inventory level in a duopoly market are both likely to be higher than in a monopolistic market.

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Section: The Monopoly Casementioning

confidence: 99%

Section: Introduction and Literature Reviewmentioning

confidence: 99%

A Static Approximation for Dynamic Demand Substitution with Applications in a Competitive Market

Hopp

2008

Operations Research

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“…For example, Kraus and Yano (2003) considered a probabilistic choice model based on share-of-surplus model and Maddah and Bish (2007) used a multinomial logit choice model for customer choice process. Also in the literature, assortment planning problem may be considered dynamically for a multi-period horizon (e.g., Hall et al, 2010;Talebian et al, 2014, Rabbani et al, 2014 or applied in an oligopolistic environment instead of a monopolistic one (e.g.…”

Section: Literature Of Assortment Planningmentioning

confidence: 99%

Integrating assortment selection, pricing and mixed-bundling problems for multiple retail categories under cross-selling

Rabbani¹,

Salehi²,

Farshbaf‐Geranmayeh³

2017

10.5267/j.uscm

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This paper optimizes joint mixed bundling, assortment planning and pricing problems for complementary retail categories that comprise substitutable items. These categories are divided into one primary category and multiple secondary categories and based on cross-selling effect, customers of primary category can opt to buy from other categories. It is assumed that the bundle can comprise one product of each offered complementary categories. A mixed-integer nonlinear programming is proposed that maximizes total profit by optimizing strategy of bundling, assortment selection and prices of single products and the bundle under a maximumsurplus customer choice model. Then because of computational considerations, this model is linearized and converted to a mixed-integer linear programming; whereby exact solution for even large-scale problems can be obtained. The results show that if cross-selling effect between product categories is overlooked or bundling of products is not allowed, then significant profit losses, will be resulted. To the best of our knowledge, this is the first study on bundling strategies in assortment selection decisions.Growing Science Ltd. All rights reserved. 7

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“…Mahajan and van Ryzin (2001), Cachon et al (2005), Caro and Gallien (2007) and Maddah and Bish (2007) extend van Ryzin and Mahajan (1999) in various ways. Gaur and Honhon (2006) show that for a locational choice model, the products in the optimal assortment are located far from each other in the attribute space, indicating maximum differentiation, with no substitution between products in the assortment.…”

Section: Literature Reviewmentioning

confidence: 99%

A Demand Estimation Procedure for Retail Assortment Optimization with Results from Implementations

Fisher

Vaidyanathan

2014

Management Science

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We consider the problem of choosing, from a set of N potential stock-keeping units (SKUs) in a retail category, K SKUs to be carried at each store to maximize revenue or profit. Assortments can vary by store, subject to a maximum number of different assortments. We view a SKU as a set of attribute levels and also model possible substitutions when a customer's first choice is not in the assortment. We apply maximum likelihood estimation to sales history of the SKUs currently carried by the retailer to estimate the demand for attribute levels and substitution probabilities, and from this, the demand for any potential SKU, including those not currently carried by the retailer. We specify several alternative heuristics for choosing SKUs to be carried in an assortment. We apply this approach to optimize assortments for three real examples: snack cakes, tires, and automotive appearance chemicals. A portion of our recommendations for tires and appearance chemicals were implemented and produced sales increases of 5.8% and 3.6%, respectively, which are significant improvements relative to typical retailer annual comparable store revenue increases. We also forecast sales shares of 1, 11, and 25 new SKUs for the snack cake, tire, and automotive appearance chemical applications, respectively, with mean absolute percentage errors (MAPEs) Fader and Hardie (1996).

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Joint pricing, assortment, and inventory decisions for a retailer's product line

Cited by 87 publications

References 20 publications

A Static Approximation for Dynamic Demand Substitution with Applications in a Competitive Market

A Static Approximation for Dynamic Demand Substitution with Applications in a Competitive Market

Integrating assortment selection, pricing and mixed-bundling problems for multiple retail categories under cross-selling

A Demand Estimation Procedure for Retail Assortment Optimization with Results from Implementations

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