TITLE

Estimation of Consumer Demand with Stock-Out Based Substitution: An Application to Vending Machine Products

AUTHOR(S)
Anupindi, Ravi; Dada, Maqbool; Gupta, Sachin
PUB. DATE
December 1998
SOURCE
Marketing Science;1998, Vol. 17 Issue 4, p406
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Abstract The occurrence of temporary stock-outs at retail is common in frequently purchased product categories. Available empirical evidence suggests that when faced with stock-outs, consumers are often willing to buy substitute items. An important implication of this consumer behavior is that observed sales of an item no longer provide a good measure of its core demand rate. Sales of items that stock-out are right-censored, while sales of other items are inflated because of substitutions. Knowledge of the true demand rates and substitution rates is important for the retailer for a variety of category management decisions such as the ideal assortment to carry, how much to stock of each item, and how often to replenish the stock. The estimated substitution rates can also be used to infer patterns of competition between items in the category. In this paper we propose methods to estimate demand rates and substitution rates in such contexts.We develop a model of customer arrivals and choice between goods that explicitly allows for possible product substitution and lost sales when a customer faces a stock-out. The model is developed in the context of retail vending, an industry that accounts for a sizable part of the retail sales of many consumer products. We consider the information set available from two kinds of inventory tracking systems. In the best case scenario of a perpetual inventory system in which times of stock-out occurrence and cumulative sales of all goods up to these times are observed, we derive Maximum Likelihood Estimates (MLEs) of the demand parameters and show that they are especially simple and intuitive.However, state-of-the-art inventory systems in retail vending provide only periodic data, i.e., data in which times of stock-out occurrence are unobserved or "missing." For these data we show how the Expectation-Maximization (EM) algorithm can be employed to obtain the MLEs of the demand parameters by treating the stock-out times as missing data....
ACCESSION #
1697999

 

Related Articles

  • "Stack Them High, Let 'em Fly": Lot-Sizing Policies When Inventories Stimulate Demand. Balakrishnan, Anantaram; Pangburn, Michael S.; Stavrulaki, Euthemia // Management Science;May2004, Vol. 50 Issue 5, p630 

    In some retail contexts, stocking large quantities of inventory may not only improve service levels, but can also stimulate demand. For products having demand rates that increase with inventory levels, we analyze the effect of stocking decisions on firm profitability to develop managerial...

  • Store inventory can affect demand: Empirical evidence from magazine retailing Koschat, Martin A. // Journal of Retailing;Jun2008, Vol. 84 Issue 2, p165 

    In retailing, inventory analysis and inventory practice have traditionally been based on the assumption that underlying demand does not vary with inventory levels. A growing body of research supports the contention that the validity of this assumption has significant implications for optimal...

  • Calculation of Theoretical Brand Performance Measures from the Parameters of the Dirichlet Model. Rungie, Cam; Goodhardt, Gerald // Marketing Bulletin;May2004, Vol. 15, p1 

    The Dirichlet Model is used in marketing to provide a probability density function for the repeated purchases, by shoppers over a period of time, of the competing brands within a product category. The model is used to analyze a range of measures which report on the performance and competitive...

  • Shopper Marketing. Wyner, Gordon; Bell, David; Corsten, Daniel; Knox, George // Marketing Management;Mar/Apr2011, Vol. 20 Issue 1, p44 

    The article discusses the impact of the increasing role of technology on shopper marketing process. It notes that the growing interest in shopper marketing reflects the interests of some manufacturers in managing their brands at retail as well as the interest of the retailers in growing category...

  • Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information. Frank Chen; Drezner, Zvi; Ryan, Jennifer K.; Simchi-Levi, David // Management Science;Mar2000, Vol. 46 Issue 3, p436 

    An important observation in supply chain management, known as the bullwhip effect, suggests that demand variability increases as one moves up a supply chain. In this paper we quantify this effect for simple, two-stage supply chains consisting of a single retailer and a single manufacturer. Our...

  • MINING ASSOCIATION RULES FOR SELECTIVE INVENTORY CONTROL. Bala, Pradip Kumar // Journal of the Academy of Business & Economics;3/20/2008, Vol. 8 Issue 2, p75 

    For selective inventory control, items are categorized in ABC classes. However, demand of some of the B or C class items may have an impact on the demand of some A class items. Shortages on such B or C class items can cause severe reductions in the demand of dependent A items and resulting in...

  • Tourism destination brand identity: The case of Slovenia. Konecnik, Maja; Go, Frank // Journal of Brand Management;Jan2008, Vol. 15 Issue 3, p177 

    This paper explores the concept of tourism destination brand identity from the supply-side perspective, in contrast to those studies that have focused on the demand-driven, tourists' perceived tourism destination brand image. Both researchers and practitioners have concluded that an analysis of...

  • ASSORTMENT CHOICE IN WHOLESALE AND RETAIL MARKETING. Balderston, F. E. // Journal of Marketing;Oct56, Vol. 21 Issue 2, p175 

    The article discusses the issue of assortment choice in both wholesale and retail marketing. The article defines assortment as the number of different items available for sale, as well as the dimensions along which items are classified, including trade designation, quality levels, number of...

  • Modeling Store Choice Based on Censored Preference Data. Malhotra, Naresh K. // Journal of Retailing;Summer86, Vol. 62 Issue 2, p128 

    In this article we propose a stochastic model of store choice based on censored preference data. The data is censored in that information on intensity of preference is obtained only for the stores in the acceptable set. We discuss the theoretical rationale supporting the model and describe an...

Share

Read the Article

Courtesy of VIRGINIA BEACH PUBLIC LIBRARY AND SYSTEM

Sign out of this library

Other Topics