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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.04.002 Byline: Hisashi Kurata (a), Dong-Qing Yao (b), John J. Liu (c) Keywords: Supply chain management; Pricing; Brand management; Channel competition; Comparative statics Abstract: This paper analyzes channel pricing in multiple distribution channels under competition between a national brand (NB) and a store brand (SB), where an NB can be distributed both through a direct channel (e-channel) and an indirect channel (local stores) but an SB can be distributed only through an indirect channel. We first explore cross-brand and cross-channel pricing policies. Formulating the problem as a Nash pricing game, we reach two findings: (1) brand loyalty building is profitable for both an NB and an SB; and (2) marketing decisions are more restrictive for an NB channel than they are for the SB channel. We next assess supply chain coordination and reach two findings: (1) wholesale price change does not coordinate the supply chain and (2) an appropriate combination of markup and markdown prices can achieve both supply chain coordination and a win-win outcome for each channel. Author Affiliation: (a) School of Business Administration, The University of Wisconsin-Milwaukee, 3202 N. Maryland Ave., Milwaukee, WI 53201, USA (b) College of Business and Economics, Towson University, 8000 York Road, Towson, MD, 21252-0001, USA (c) Department of Logistics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Article History: Received 10 March 2005; Accepted 3 April 2006

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.01.009 Byline: Hisashi Kurata (a), John J. Liu (b) Keywords: Marketing-operations interface; Promotion; Inventory decision; Markov-switching model; Supply chain management Abstract: In considering the retailer-supplier supply chain, this paper analyzes how a retailer reasonably decides both the depth and frequency of the price discount promotion including or excluding a supplier's inventory decision. Assuming that the promotion frequency used by the retailer is probabilistic, we model a promotion-inventory decision under an AR(1) demand with a Markov switching promotion regime. After obtaining the optimal promotion plan, our analysis also considers the behavior of the optimal promotion decision; the retailer's price format selection, either an Every-Day-Low-Price policy (EDLP) or a Promotion policy (HiLo); and the impact of information sharing of promotion status on the system's performance. Our results suggest that a retailer tends to overpromote if inventory cost is excluded in its promotion decision, that increasing the market share is a preferable action for both the retailer and the supplier, that total margin and price-elasticity play an important role in selecting the price format, and that the profitability for a supplier of sharing promotion information depends on the transition probabilities of the Markov switching regime. Author Affiliation: (a) School of Business Administration, University of Wisconsin-Milwaukee, 3202 N. Maryland Avenue, Milwaukee, WI 53201, USA (b) Department of Logistics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Article History: Received 23 August 2004; Accepted 8 January 2006

A modeling framework is developed to examine the effect of retail-pricing policies on the choice between make-to-stock and make-to-order in operations management.

Inventory pooling is a technique that is widely used to cope with supply chain uncertainty. Naturally, however, product availability at a given store also influences the customer’s purchasing decisions. Hence, a centralised inventory system with a long delivery lead time carries the risk of losing sales to customers who are product-availability-conscious. Assuming a supply chain of a supplier and multiple retailers, we study how inventory pooling works when product-availability-conscious customers abandon a given purchase if the items are not available at a given store. Developing a model with two random variables, Poisson demand and Bernoulli customer response to out-of-stock, we explore who should stock products – a supplier, a retailer, or both – in the context of a product-availability effect on sales. We then propose decision processes by which a supply chain can find the best inventory system based on supply chain size, demand rate, and inventory costs for both supplier and retailer. We also discuss the coordination required between a retailer and a supplier that must synchronise an optimal inventory system. [ABSTRACT FROM PUBLISHER]

Abstract: In retailing practice, customers may actively respond in one of the following ways after experiencing stockout of a preferred brand: switch to a substitutable brand, switch to another store (where the preferred brand could be available), or delay purchase (backlogging). This paper presents a model of active customer responses to stockout of fashion products. In the single‐period model, a retailer maximizes profit by selling two substitutable brands through two different stores. Analytical results and numerical experiments suggest that active response to stockout increase the retailer's profitability due to (a) additional revenue from backlogging and brand and store switching and (b) decrease in optimal order size resulting in lower holding costs. Omnichannel fulfillment offers additional opportunities for retailers to benefit from active responses to stockout. [ABSTRACT FROM AUTHOR]

Two characteristics of e-commerce, the ability to micromarket (ie, customising a marketing plan according to customers’ purchasing patterns) and the ability to selectively offer item availability information (ie, manipulating whether or not to display the total number of items available to customers), considerably increase firms’ potential to improve their performance. This paper considers e-business in the hotel and airline industries, which has two customer segments: one is the leisure segment, which focuses more on price, and the other group is the business segment, which focuses heavily on schedule. We propose an analytical model that determines the optimal pricing and demonstrates that e-business can improve its revenue by taking into account customer segmentation when offering item availability information to customers. We provide numerical examples that demonstrate that accuracy in segmenting customers and the size of each segment will influence the performance of customised marketing planning. We also present managerial implications derived from these analytical findings.Journal of Revenue and Pricing Management (2007) 5, 305–314. doi:10.1057/palgrave.rpm.5160054 [ABSTRACT FROM AUTHOR]