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We study the planar maximum coverage location problem (MCLP) with rectilinear distance and rectangular demand zones in the case where 'partial coverage' is allowed in its true sense, i.e., when [...]

This paper studies the incentive for vertical information sharing in competing supply chains with production technologies that exhibit diseconomies of scale. We consider a model of two supply chains each consisting of one manufacturer selling to one retailer, with the retailers engaging in Cournot or Bertrand competition. For Cournot retail competition, we show that information sharing benefits a supply chain when (1) the production diseconomy is large and (2) either competition is less intense or at least one retailer's information is less accurate. A supply chain may become worse off when making its information more accurate or production diseconomy smaller, if such an improvement induces the firms in the rival supply chain to cease sharing information. For Bertrand retail competition, we show that information sharing benefits a supply chain when (1) the production diseconomy is largo and (2) either competition is less intense or information is more accurate. Under Bertrand competition a manufacturer may be worse off by receiving information, which is never the case under Cournot competition. Information sharing in one supply chain triggers a competitive reaction from the other supply chain and this reaction is damaging to the first supply chain under Cournot competition but may be beneficial under Bertrand competition. Key words: supply chain management; supply chain competition; information sharing History: Received January 8, 2009; accepted September 7, 2010, by Martin Lariviere, operations management. Published online in Articles in Advance February 15, 2011., 1. Introduction In undertaking initiatives such as quick response, continuous replenishment, or vendor-managed inventory, manufacturers and retailers have sought to leverage information sharing to improve supply chain performance. Although the [...]

This paper presents a new model of probabilistic binary choice under risk. In this model, a decision maker always satisfies first-order stochastic dominance. If neither lottery stochastically dominates the other alternative, a decision maker chooses in a probabilistic manner. The proposed model is derived from four standard axioms (completeness, weak stochastic transitivity, continuity, and common consequence independence) and two relatively new axioms. The proposed model provides a better fit to experimental data than do existing models. The baseline model can be extended to other domains such as modeling variable consumer demand. Key words: probabilistic choice; first-order stochastic dominance; random utility; strong utility History: Received March 8, 2010; accepted October 19, 2010, by Peter Wakker, decision analysis. Published online in Articles in Advance January 28, 2011., 1. Introduction Empirical studies show that decisions under risk are often contradictory (e.g., Hey and Orme 1994). Such decisions are best captured through a model of probabilistic choice. Popular models [...]

In developing industries, firms have to decide whether and when to enter the market depending on the state of demand, existing firms in the industry, and the firm's capabilities. This paper investigates a model of increasing demand, in which firms decide when to enter the market anticipating the strategic behavior of other potential entrants, and the effects of entry on future potential entrants. This paper shows that the ability of early entry to deter future competitors' entry leads firms to enter the market at a rate faster than demand is expanding. If there is the potential for many firms to enter the market, firms may be less likely to enter because of future competitor entry to correct any market opportunities. If firms enter the market depending on their fixed capabilities rather than depending on the firm's circumstances at each moment in time, firms end up entering the market at a faster rate in the early periods. Key words: industry dynamics; strategic entry; competition History: Received August 26, 2009; accepted April 6, 2010, by Preyas Desai, marketing. Published online in Articles in Advance July 2, 2010., 1. Introduction In growing industries, potential entrants have to decide whether and when to enter the industry. For example, in the satellite radio industry in the late 1990s, XM, Sirius, [...]

We analyze the optimal design of a markdown pricing mechanism with preannounced prices. In the presence of limited supply, buyers who choose to purchase at a lower price may face [...]

In this paper, we consider the classical multifare, single-resource (leg) problem in revenue management for the case where demand information is limited. Our approach employs a competitive analysis, which guarantees a certain performance level under all possible demand scenarios. The only information required about the demand for each fare class is lower and upper bounds. We consider both competitive ratio and absolute regret performance criteria. For both performance criteria, we derive the best possible static policies, which employ booking limits that remain constant throughout the booking horizon. The optimal policies have the form of nested booking limits. Dynamic policies, which employ booking limits that may be adjusted at any time based on the history of bookings, are also obtained. We provide extensive computational experiments and compare our methods to existing ones. The results of the experiments demonstrate the effectiveness of these new robust methods. Key words: revenue management; robust optimization; competitive analysis History: Accepted by Candace A. Yano, operations and supply chain management; received July 28, 2006. This paper was with the authors 7 1/2 months for 3 revisions. Published online in Articles in Advance July 10, 2008., 1. Introduction The majority of successful revenue management (RM) implementations rely heavily on the use of demand information. Experts advise against rushing to optimization in RM without first fully implementing [...]

An important managerial question is the choice of the pricing rule. We study whether this choice depends on the uncertainty about the number of participating bidders by comparing expected revenues under discriminatory and uniform pricing within an auction model with affiliated values, stochastic number of bidders, and linear bidding strategies. We show that if uncertainty about the number of bidders is substantial, then the discriminatory pricing generates higher expected revenues than the uniform pricing. In particular, the first-price auction might generate higher revenues than the second-price auction. Therefore, uncertainty about the number of bidders is an important factor to consider when choosing the pricing rule. We also study whether eliminating this uncertainty, i.e., revealing the number of bidders, is in the seller's interests, and discuss the existence of an increasing symmetric equilibrium. Key words: discriminatory pricing; uniform pricing; auctions; demand uncertainty; stochastic number of bidders History: Accepted by David E. Bell, decision analysis; received February 22, 2007. This paper was with the authors 2 months for 2 revisions. Published online in Articles in Advance July 21, 2008., 1. Introduction The choice of the pricing rule is an important and complex managerial decision. The focus of this paper is on the effect of demand uncertainty, within an auction [...]

Measudring demand uncertainty is a key activity in supply chain planning, but it is difficult when demand history is unavailable, such as for new products. One method that can be [...]

A model that includes the changes in the demand rate at random time points into the inventory planning decision is developed. These demand variations may arise out of economic recessions, start or end of labor strikes, and other events that result in an increase or decrease in the rate of demand. System-point level-crossing theory is used to generate expressions for the distribution and expected value of on-hand inventory, ordering rate and the expected total cost rate for a particular ordering policy. The model shows that, regardless of the actual demand rate, the cost penalty for employing the same stocking decision is very minimal if the disruption in demand is relatively insignificant. It also shows that are benefits if the inventory levels are adjusted in situations where there is a major demand disruption.

The Capacitated Vehicle Routing Problem is defined in situations where customers are geographically spread within a given area and have to be served by a fleet of vehicles of the same capacity and kind. Optimal route, time and demand satisfaction are the objectives of the problem. A particular case of unsplit demands whereby a customer's demand may not be served by more than one vehicle is discussed. A probabilistic analysis of a class of heuristics is undertaken.

Bounds are provided on the value loss as influenced by optimal cost for restricting focus on a class of inventory stocking policies displaying myopic behavior for a given stopping time. The model used is a single-product inventory system with discrete time and linear procurement, holding and shortage costs. The myopic stocking policy is observed to be a default rule to adopt with immediate delivery systems with no economies of scale. Structural characteristics of the optimal value function that are unaffected by demand give bounds that strengthen the demand process subsequent to the stopping period. The bounding data derived facilitates consideration of possibly intractable demand processes in the analytical context. Consideration is given particularly to the additive and multiplicative shock models.