Product Line Selection and Pricing with Modularity in Design

Hopp, Wallace J.; Xu, Xiaowei

doi:10.1287/msom.1050.0077

Cited by 125 publications

(71 citation statements)

References 31 publications

(36 reference statements)

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“…On the other hand, with a lenient return policy, or when returns are not allowed, the retailer offers some of the most popular products. Carrying popular products in a retail assortment is consistent with common intuition, previous work (e.g., van Ryzin and Mahajan 1999, Aydın and Ryan 2000, Hopp and Xu 2005, Maddah and Bish 2007, Cachon and Kök 2007, and industry practice (e.g., Cargille et al 2005, Olavson andFry 2006).…”

Section: When To Carry Eccentric Products? Optimal Retail Assortment supporting

confidence: 83%

“…A growing body of work explores relevant operational concerns such as inventory (van Ryzin and Mahajan 1999, Smith and Agrawal 2000, Aydın and Ryan 2000, Gaur and Honhon 2006, joint inventory-pricing decisions (Maddah and Bish 2007), substitution upon stockout (Honhon et al 2010), delivery leadtime (Alptekinoglu and Corbett 2010), and modularity in product design (Hopp and Xu 2005). Another line of research tackles strategic and competitive aspects such as entry deterrence (Bayus and Putsis 1999), channel coordination (Aydın and Hausman 2009), and competitive implications of consumer search (Cachon et al 2008), basketshopping behavior (Cachon and Kök 2007), brand preference (Kök and Xu 2011) and product satiation (Caro and Martinez-de-Albeniz 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

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When to Carry Eccentric Products? Optimal Retail Assortment under Consumer Returns

Alptekinoğlu

Grasas

2012

SSRN Journal

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To understand whether retailers should consider consumer returns when merchandising, we study how the optimal assortment of a price-taking retailer is influenced by its return policy. The retailer selects its assortment from an exogenous set of horizontally differentiated products. Consumers make purchase and keep/return decisions in nested multinomial logit fashion. Our main finding is that the optimal assortment has a counterintuitive structure for relatively strict return policies: It is optimal to offer a mix of the most popular and most eccentric products when the refund amount is sufficiently low, which can be viewed as a form of risk sharing between the retailer and consumers. In contrast, if the refund is sufficiently high, or when returns are disallowed, optimal assortment is composed of only the most popular products (a common finding in the literature). We provide preliminary empirical evidence for one of the key drivers of our results: more eccentric products have higher probability of return -conditional on purchase. In light of our analytical findings and managerial insights, we conclude that retailers should take their return policies into account when merchandising.

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Section: When To Carry Eccentric Products? Optimal Retail Assortment supporting

confidence: 83%

Section: Literature Reviewmentioning

confidence: 99%

When to Carry Eccentric Products? Optimal Retail Assortment under Consumer Returns

Alptekinoğlu

Grasas

2012

SSRN Journal

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“…Similar monotonic assortment results were shown in Aydin and Ryan (2000) (for the logit model), Hopp and Xu (2005) (for the Bayesian logit model), and van Ryzin and Mahajan (1999) (for the logit model and the trend-following population model). The first two models include price decisions but exclude inventory decisions.…”

Section: Introduction and Literature Reviewsupporting

confidence: 82%

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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“…Dreze et al (1994) study the impact of shelf space on sales and Boatwright and Nunes (2001) study assortment reduction by making sure that certain attributes are represented in the assortment. Hopp and Xu (2005) study the impact of product modularity in the optimal product line length from a manufacturer's perspective. Hopp and Xu (2006) study price, service, and assortment competition in a single category between two retailers and find that the retailers provide less variety and lower prices in competition.…”

Section: Related Literaturementioning

confidence: 99%

Category Management and Coordination in Retail Assortment Planning in the Presence of Basket Shopping Consumers

2007

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T his paper studies the assortment planning problem with multiple merchandise categories and basket shopping consumers (i.e., consumers who desire to purchase from multiple categories). We present a duopoly model in which retailers choose prices and variety level in each category and consumers make their store choice between retail stores and a no-purchase alternative based on their utilities from each category. The common practice of category management (CM) is an example of a decentralized regime for controlling assortment because each category manager is responsible for maximizing his or her assigned category's profit. Alternatively, a retailer can make category decisions across the store with a centralized regime. We show that CM never finds the optimal solution and provides both less variety and higher prices than optimal. In a numerical study, we demonstrate that profit loss due to CM can be significant. Finally, we propose a decentralized regime that uses basket profits, a new metric, rather than accounting profits. Basket profits are easily evaluated using point-of-sale data, and the proposed method produces near-optimal solutions.Key words: game theory; assortment planning; optimization History: Accepted by Wallace J. Hopp, marketing; received August 3, 2004. This paper was with the authors 14 1 2 months for 1 revision.Assortment planning is both extremely important and challenging for retailers. No assortment planning process is capable of accounting for all of the marketing and operational implications of its decisions due to limited data and the complexity of the task. Organizational forms such as category management (CM) (ACNielsen 1998) and assortment planning models in the literature (e.g., Kök and Fisher 2004) focus on the selection of products in a single category assuming store traffic is exogenous, i.e., prices and variety within a category influence demand conditional on a store visit, but does not influence store choice. For example, many retailers are adopting an "efficient assortment" strategy, which primarily seeks to find the profit maximizing level of variety by eliminating low-selling products (Kurt Salmon Associates 1993). However, if a retailer reduces variety in all categories based on single-category analyses, then the store becomes less attractive and some customers are likely to defect to other retailers, reducing store traffic. This concern is particularly relevant with respect to basket shoppers-consumers who desire to purchase from multiple categories. If a basket shopper does not find an item that she wants in one category, she may purchase her entire basket from another retailer (Bell and Lattin 1998). Although retailers are well aware of this interdependence across categories, there is little research on what can be done to address it. This paper develops a stylized model to evaluate CM at two competing retailers in the presence of basket shopping consumers. Each retailer offers two merchandise categories. Retailers determine prices and variety level in each category. Singl...

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Product Line Selection and Pricing with Modularity in Design

Cited by 125 publications

References 31 publications

When to Carry Eccentric Products? Optimal Retail Assortment under Consumer Returns

When to Carry Eccentric Products? Optimal Retail Assortment under Consumer Returns

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

Category Management and Coordination in Retail Assortment Planning in the Presence of Basket Shopping Consumers

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