This paper addresses the simultaneous determination of pricing and inventory replenishment strategies in the face of demand uncertainty. More specifically, we analyze the following single item, periodic review model. Demands in consecutive periods are independent, but their distributions depend on the item's price in accordance with general stochastic demand functions. The price charged in any given period can be specified dynamically as a function of the state of the system. A replenishment order may be placed at the beginning of some or all of the periods. Stockouts are fully backlogged. We address both finite and infinite horizon models, with the objective of maximizing total expected discounted profit or its time average value, assuming that prices can either be adjusted arbitrarily (upward or downward) or that they can only be decreased. We characterize the structure of an optimal combined pricing and inventory strategy for all of the above types of models. We also develop an efficient value iteration method to compute these optimal strategies. Finally, we report on an extensive numerical study that characterizes various qualitative properties of the optimal strategies and corresponding optimal profit values.

In this paper, we investigate the equilibrium behavior of decentralized supply chains with competing retailers under demand uncertainty. We also design contractual arrangements between the parties that allow the decentralized chain to perform as well as a centralized one. We address these questions in the context of two-echelon supply chains with a single supplier servicing a network of (competing) retailers, considering the following general model: Retailers face random demands, the distribution of which may depend only on its own retail price (noncompeting retailers) or on its own price as well as those of the other retailers (competing retailers), according to general stochastic demand functions.decentralized supply chains, coordination mechanisms, uncertain demands, inventory strategies

We address a fundamental two-echelon distribution system in which the sales volumes of the retailers are endogenously determined on the basis of known demand functions. Specifically, this paper studies a distribution channel where a supplier distributes a single product to retailers, who in turn sell the product to consumers. The demand in each retail market arrives continuously at a constant rate that is a general decreasing function of the retail price in the market. We have characterized an optimal strategy, maximizing total systemwide profits in a centralized system. We have also shown that the same optimum level of channelwide profits can be achieved in a decentralized system, but only if coordination is achieved via periodically charged, fixed fees, and a nontraditional discount pricing scheme under which the discount given to a retailer is the sum of three discount components based on the retailer's (i) annual sales volume, (ii) order quantity, and (iii) order frequency, respectively. Moreover, we show that no (traditional) discount scheme, based on order quantities only, suffices to optimize channelwide profits when there are multiple nonidentical retailers. The paper also considers a scenario where the channel members fail to coordinate their decisions and provides numerical examples that illustrate the value of coordination. We extend our results to settings in which the retailers' holding cost rates depend on the wholesale price.Coordination, Pricing, Quantity Discounts, Supply Chain Management

This paper develops a stochastic general equilibrium inventory model for an oligopoly, in which all inventory constraint parameters are endogenously determined. We propose several systems of demand processes whose distributions are functions of all retailers' prices and all retailers' service levels. We proceed with the investigation of the equilibrium behavior of infinite-horizon models for industries facing this type of generalized competition, under demand uncertainty. We systematically consider the following three competition scenarios. (1) Price competition only: Here, we assume that the firms' service levels are exogenously chosen, but characterize how the price and inventory strategy equilibrium vary with the chosen service levels. (2) Simultaneous price and service-level competition: Here, each of the firms simultaneously chooses a service level and a combined price and inventory strategy. (3) Two-stage competition: The firms make their competitive choices sequentially. In a first stage, all firms simultaneously choose a service level; in a second stage, the firms simultaneously choose a combined pricing and inventory strategy with full knowledge of the service levels selected by all competitors. We show that in all of the above settings a Nash equilibrium of infinite-horizon stationary strategies exists and that it is of a simple structure, provided a Nash equilibrium exists in a so-called reduced game. We pay particular attention to the question of whether a firm can choose its service level on the basis of its own (input) characteristics (i.e., its cost parameters and demand function) only. We also investigate under which of the demand models a firm, under simultaneous competition, responds to a change in the exogenously specified characteristics of the various competitors by either: (i) adjusting its service level and price in the same direction, thereby compensating for price increases (decreases) by offering improved (inferior) service, or (ii) adjusting them in opposite directions, thereby simultaneously offering better or worse prices and service.

Consider a central depot (or plant) which supplies several locations experiencing random demands. Orders are placed (or production is initiated) periodically by the depot. The order arrives after a fixed lead time, and is then allocated among the several locations. (The depot itself does not hold inventory.) The allocations are finally received at the demand points after another lag. Unfilled demand at each location is backordered. Linear costs are incurred at each location for holding inventory and for backorders. Also, costs are assessed for orders placed by the depot. The object is to minimize the expected total cost of the system over a finite number of time periods. This system gives rise to a dynamic program with a state space of very large dimension. We show that this model can be systematically approximated by a single-location inventory problem. All the qualitative and quantitative results for such problems can then be applied.inventory and production, approximations, stochastic models