Inventory control under substitutable demand: A stochastic game application

Avsar, Z.M.; Baykal‐Gürsoy, Melike

doi:10.1002/nav.10018

Cited by 49 publications

(27 citation statements)

References 14 publications

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“…Rajaram (2001) presents a meanvariance analysis of assortment planning with no substitution. Also related are multi-item inventory models, either with a single resource constraint (e.g., Nahmias andSchmidt 1984, Downs et al 2001) or with substitutable products (e.g., McGillivray and Silver 1978, Parlar and Goyal 1984, Rajaram and Tang 2001, Avsar and Baykal-Gursoy 2002, Netessine and Rudi 2003. This group of papers does not consider the assortment problem and focuses on stocking decisions of the products in a given assortment.…”

Section: Related Literaturementioning

confidence: 99%

Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application

Kok

Fisher

2007

Operations Research

382

219

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Assortment planning at a retailer entails both selecting the set of products to be carried and setting inventory levels for each product. We study an assortment planning model in which consumers might accept substitutes when their favorite product is unavailable. We develop an algorithmic process to help retailers compute the best assortment for each store. First, we present a procedure for estimating the parameters of substitution behavior and demand for products in each store, including the products that have not been previously carried in that store. Second, we propose an iterative optimization heuristic for solving the assortment planning problem. In a computational study, we find that its solutions, on average, are within 0.5% of the optimal solution. Third, we establish new structural properties (based on the heuristic solution) that relate the products included in the assortment and their inventory levels to product characteristics such as gross margin, case-pack sizes, and demand variability. We applied our method at Albert Heijn, a supermarket chain in The Netherlands. Comparing the recommendations of our system with the existing assortments suggests a more than 50% increase in profits.

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Section: Related Literaturementioning

confidence: 99%

Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application

Kok

Fisher

2007

Operations Research

382

219

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“…Karjalainen [13], Lippman and McCardle [18], Mahajan and van Ryzin [19,20], Netessine and Rudi [24] and Netessine and Zhang [25] further study this problem for an arbitrary number of retailers. Anupindi and Bassok [3], Avsar and Baykal-Gursoy [4] and Nagarajan and Rajagopalan [23] analyze the impact of substitution in a multi-period setting with lost sales. To the best of our knowledge, this line of research has thus far been constrained within the single-period framework (or a multi-period framework with an assumption of lost sales), where the modeling of demand backlogging is not an issue and hence di®ers from our multiple-period problem.…”

Section: Literature Surveymentioning

confidence: 99%

Inventory competition and incentives to back-order

Netessine¹,

Rudi²,

Wang³

2006

IIE Transactions

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In this paper we consider the issue of inventory control in a multi-period environment with competition on product availability. Specifically, when a product is out of stock, the customer often must choose between placing a back-order or turning to a competitor selling a similar product. We consider a competition in which customers may switch between two retailers (substitute) in the case of a stock-out at the retailer of their first choice. In a multi-period setting, the following four situations may arise if the product is out of stock: (i) sales may be lost; (ii) customers may back-order the product with their first-choice retailer; (iii) customers may back-order the product with their second-choice retailer; or (iv) customers may attempt to acquire the product according to some other more complex rule. The question we address is: how do the equilibrium stocking quantities and profits of the retailers depend on the customers' back-ordering behaviors? In this work we consider the four alternative back-ordering scenarios and formulate each problem as a stochastic multiperiod game. Under appropriate conditions, we show that a stationary base-stock inventory policy is a Nash equilibrium of the game that can be found by considering an appropriate static game. We derive conditions for the existence and uniqueness of such a policy and conduct a comparative statics analysis. Analytical expressions for the optimality conditions facilitate managerial insights into the effects of various back-ordering mechanisms. Furthermore, we recognize that often a retailer is willing to offer a monetary incentive to induce a customer to back-order instead of going to the competitor. Therefore, it is necessary to coordinate incentive decisions with operational decisions about inventory control. We analyze the impact of incentives to backorder the product on the optimal stocking policies under competition and determine the conditions that guarantee monotonicity of the equilibrium inventory in the amount of the incentive offered. Our analysis also suggests that, counterintuitively, companies might benefit from making their inventories "visible" to competitors' customers, since doing so reduces the level of competition, decreases optimal inventories and simultaneously increases profits for both players. In this paper we consider the issue of inventory control in a multi-period environment with competition on product availability. Speci¯cally, when a product is out of stock, the customer often must choose between placing a back order or turning to a competitor selling a similar product. We consider a competition in which customers may switch between two retailers (substitute) in the case of a stock-out at the retailer of their¯rst choice. In a multi-period setting, the following four situations may arise if the product is out of stock: sales may be lost; customers may back-order the product with their¯rst-choice retailer; customers may back-order the product with their second-choice retailer; or customers may attempt to acquire t...

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“…Additionally, some research has considered channel substitution or market search. For instance, Avsar and BaykalGursoy [2] analyzed the equilibrium base stock policies for a decentralized-control system. Anupindi and Bassok [1], Netessine and Rudi [21], and Dai et al [8] studied a supply chain system and compared participant performance with respect to central-controlled and distributed-controlled situations.…”

Section: Previous Literaturementioning

confidence: 99%

Fashion products with asymmetric sales horizons

Chiang

2011

Naval Research Logistics

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Abstract:In this study, we explore an inventory model for a wholesaler who sells a fashion product through two channels with asymmetric sales horizons. The wholesaler can improve profitability by employing joint procurement and inventory reallocation as a recourse action in response to the dynamics of sales. In this research, a simple stochastic programming model is analyzed to specify the properties of the optimal inventory decisions.

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Inventory control under substitutable demand: A stochastic game application

Cited by 49 publications

References 14 publications

Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application

Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application

Inventory competition and incentives to back-order

Fashion products with asymmetric sales horizons

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