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The possibility of product substitution due to a stockout provides retailers with a buffer against lost sales but can also complicate the management of inventory because both substitute and primary demand affect inventory levels. Since most retailers make their inventory decisions around a desired service level (e.g., fill rate), it is important to understand how customer substitution behavior can influence different measures of customer service. In this study, an extensive theoretical framework is presented and used to develop a decision tree approach for predicting realized item and category fill rates. We find that item fill rate is primarily a function of the target service level of the focal item and the willingness to switch from an alternate item to the focal item. Category fill rate is influenced by the target service level of both items, with willingness to switch amplifying their effect. The decision tree approach is found to be an accurate predictor in most cases, however, it tends to overestimate item fill rate when the willingness to substitute from the alternate item increases. The approach also accurately predicts category fill rates, outside of scenarios with asymmetric substitutability. [ABSTRACT FROM AUTHOR]

Larger product assortments have been found to have both positive and negative impacts on firms that offer them. More product variety allows firms to increase sales by either selling to a larger customer base or by encouraging current customers to purchase more frequently and in greater quantities. However, more product variety is also associated with lower operational performance. In this research, we investigate the impact of product variety on firm performance in a retail setting. Using data gathered from a large retailer over a 32‐week period for 12 product categories, we develop a multiple stage regression model and find that the effects of product variety on inventory levels, stockout rates and sales differ across more hedonic and more utilitarian product categories. Furthermore, we find that the product variety decision itself is moderated by the hedonic or utilitarian nature of the product category. Implications of the findings for theory and retail management are discussed. [ABSTRACT FROM AUTHOR]

As more firms look to implement omnichannel strategies to mitigate the inherent information barriers between online and offline channels, understanding the outcomes of these initiatives is critical. This study empirically examines the impact of the decision to share brick‐and‐mortar (B&M) store product availability information with customers, specifically focusing on the scenario where a discrepancy exists in the product assortment of online and offline channels. We investigate the impact of this information sharing strategy on customer research shopping trajectories using a proprietary dataset collected from a leading North American retailer. Using a difference‐in‐differences approach, we find that this strategy helps boost the overall sales from customers who reside within the trade area of a retail store. At the channel level, the policy induces customers to migrate from the B&M channel to the online channel after learning that the product selection offered at their local retail store may not meet their needs, resulting in a significant increase in online sales, but a slight decrease in B&M sales. From an operational perspective, our empirical evidence suggests that sharing retail store product availability information leads to more customers using the expedited shipping service when shopping online. Furthermore, we also discover a slight increase in the overall return rate. We conclude by providing managerial implications on the functionality of the online and B&M channels and how retailers can coordinate services offered by both channels to improve the utility customers receive from the brand. Highlights • This study examines the impact of sharing brick‐and‐mortar (B&M) store product availability on sales, order fulfillment, and product returns in an omnichannel context. • Using a quasi‐field experimental design based on proprietary data collected from a leading North American retailer, this study shows that customers utilize this new information to adjust their shopping plans and avoid unsuccessful shopping trips, leading to increased sales for the brand. • This study underscores the benefits of improving information transparency between a firm and its customers. It also contributes to the discussion on omnichannel product assortment planning and the future role of B&M stores. [ABSTRACT FROM AUTHOR]

This study empirically assesses the value of decisions on offering delivery variety (the number of different methods of truck transport used to deliver products to buyers). Rooted in the literature on demand and supply integration, we develop the relationship between delivery variety decisions and sales through the mediating role of unit fill rate. We find that a decision to increase delivery variety will indirectly improve sales through the mediating role of the fill rate. Furthermore, our results suggest that decisions on order variety (the number of ordering methods offered to buyers) moderates this mediation effect. A decision to increase order variety enhances the benefits of delivery variety. We estimate our models using archival data including deliveries, order fulfillment, sales records, and other operational data over three years. When the number of delivery methods increases from 1 to 3, fill rates increase by 1.22% and sales increase by 15.39%, and when the number of order methods increases from 1 to 4, the impact of delivery variety on fill rates increases by an additional 0.39% and on sales by an additional 4.68%. These findings provide empirical support for the integration of demand and supply associated with decision making in supply chains and underscore the need for top management to consider the complementary benefits of delivery variety and order variety on order fulfillment and sales. [ABSTRACT FROM AUTHOR]

This article studies the impacts of product variety along two dimensions: product-line variety and pack-size variety. Previous research has often found that increased product variety is associated with increased sales. Interestingly, we find that this is not always the case, once the negative impact of product variety on fill rates is introduced. Specifically, product-line variety has a positive total effect on sales, but pack-size variety has a negative total effect on sales. We also investigate potential nonlinear impacts (with decreasing marginal effects) of product-line and pack-size variety, and find the result to be one of diminishing returns. [ABSTRACT FROM AUTHOR]

This article offers an expanded classification of methodologies used in systems analysis. Of these methods, one in particular-simulation-is explored in some detail. Issues associated with building and running a model, as well as analyzing its results, are examined within the context of supply chain management. It is claimed that the ability to conduct simulation studies, along with the ease of misinterpreting their results, has greatly increased over time. [ABSTRACT FROM AUTHOR]

While various approaches to mitigating the bullwhip effect have been proposed, the composition of the underlying supply chain is often taken for granted. This article develops a set of simulation models to investigate changes to the supply chain itself and their impact on the bullwhip effect, on-hand inventory, and stockouts. It is shown that particular supply chain networks have an impact on the bullwhip effect. Furthermore, the impact of supply chain networks on the bullwhip effect is moderated by the demand forecasting technique used. Finally, supply chain networks, forecasting techniques, and their interactions are found to influence on-hand inventory levels and stockout rates for firms within the supply chain. Results also suggest that no one particular type of supply chain network dominates in terms of dampening the bullwhip effect, lowering on-hand inventory levels, or reducing stockout rates. The optimal network depends on the forecasting technique used and other supply chain factors. [ABSTRACT FROM AUTHOR]

Customer service, based on economical logistics operations across the supply chain, is key to the realization of sustainable levels of profitability in Internet retailing. Concentrating on inventory and product-release operations, an empirical simulation model suggests that inventory centralization and market demand growth positively affect the level of cost-effective service received by online shoppers. The results also show that under increasing demand levels, Internet retailers can provide optimal service to consumers by fulfilling orders through inventories located at their own facilities and avoid relying on inventories held elsewhere in the supply chain. [ABSTRACT FROM AUTHOR]

The article examines alternative inventory approaches of emergency transshipments to order splitting and their effects on total cost drivers. Emergency transshipments are employed in order to maintain inventory presence in local markets. By keeping decentralized facilities open and stocked, a firm is able to fill immediately a large proportion of demand from inventory, thereby preserving high levels of customer service through minimal average order cycle times. When demand is unexpectedly high and cannot be filled from on-hand inventory, an emergency transshipment from another facility with sufficient stock also preserves high levels of customer service through maximal inventory availability. The difference in leadtime pooling between transshipments and order splitting is the timing of order placement. All parts of the split order are placed with suppliers at the same time. If the vendors offer approximately the same customer service in terms of leadtime means and variances, then ail the shipments should be received at roughly the same time. In the case of transshipments, however, because the order placements are independent, there is no reason to expect any relationship between receipts.

Suggests alternative forms of the square root law which more accurately predict the reduction in total inventory caused by a single consolidation of stock-keeping locations. Primary savings resulting from reduction in safety stock; Decrease of cycle stocks through centralization.

The focus of this article is to show, how a portfolio effect model can be employed to evaluate the use of transshipments to reduce safety stocks in a company and under what conditions it may be effective to do so. A transshipment occurs when goods are shipped to the customer from a facility other than the primary one. The reason for using transshipments is that, when customer demand is greater than on-hand inventory at a primary stocking facility, inventory from other locations can be used to avoid a stockout. While the primary drawbacks associated with transshipments are increased transportation costs and response times, the chief benefit is increased inventory availability or, conversely, reduced safety stocks. In order to test the applicability of the portfolio effect model to the case of transshipments, a single-echelon logistics system is considered. Representing this exemplary system, a simulation model has been developed having the same five assumptions underlying the portfolio effect model when applied to transshipments.

Recent logistics research has focused attention on the effects of consolidating multilocation inventory facilities on safety stock. This discussion has centered around the square-root law and the portfolio effect. The body of literature has now reached the point at which alternative models produce substantially different results. The purpose of this paper is twofold: (1) to analyze two contrasting theoretical approaches, both incorporating lead times, for estimating the portfolio effect and (2) to examine the effect of lead times, in part using actual firm data, on the portfolio effect. First, pertinent multilocation literature relating to the portfolio effect is reviewed. Second, two portfolio effect models are discussed and compared. Third, industrial data are used to explore consolidation issues. Finally, sensitivity analysis of the preferred model is performed, and managerial implications are identified. [ABSTRACT FROM AUTHOR]

The article focuses on the use of transshipments to fill demand only when the stock-keeping facility in the originating market cannot fill the demand. Application of the portfolio effect model to transshipments has been previously considered in a restrictive case. Specifically, a set proportion of demand in a market is transshipped from stock-keeping facilities located in different markets, regardless of whether there is sufficient inventory in the originating market. Transshipments enable a firm to obtain statistical economies of scale. These have been defined as advantages that result from the pooling of uncertainty and the principal potential benefits are fewer stock outs and lower safety stock levels. Holding the level of aggregate inventory constant, a transshipment policy improves overall inventory availability because a location's stock can be used to meet not only its own demand but also excess demand from other locations. The rewards of transshipments do not come without a cost.

The article focuses on a model of safety stock centralization entitled the portfolio effect. The purpose of this is to relax the two restrictive assumptions underlying the portfolio effect and to extend it to the centralization of safety stock from n locations to m locations. This allows for greater flexibility in analyzing the effects of changes in one or more specific variables. For example, the resulting model contains specifications of average demand and lead time service, including estimates of variance for each facility in the system, the proportion of safety stock that is moved from a decentralized facility to a centralized one, and the policies that establish a firm's exposure to a stockout. Use of the model allows the manager to measure the effects not only of various consolidation strategies but also of changes in safety stock strategy and lead time service. The process starts with the formulation of the portfolio effect as presented by W. Zinn, M. Levy, and D.J. Bowersox. This is expressed in terms of the ratio of total safety stock for all consolidated facilities to total safety stock for all non consolidated facilities.