31 research outputs found

    Inventory Model with Seasonal Demand: A Specific Application to Haute Couture

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    In the stochastic multiperiod inventory problem, a vast majority of the literature deals with demand volume uncertainty. Other dimensions of uncertainty have generally been overlooked. In this paper, we develop a newsboy formulation for the aggregate multiperiod inventory problem intended for products of short sales season and without replenishments. A distinguishing characteristic of our formulation is that it takes a time dimension of demand uncertainty into account. The proposed model is particularly suitable for applications in haute couture, i.e., high fashion industry. The model determines the time of switching primary sales effort from one season to the next as well as optimal order quantity for each season with the objective of maximizing expected profit over the planning horizon. We also derive the optimality conditions for the time of switching primary sales effort and order quantity. Furthermore, we show that if time uncertainty and volume uncertainty are independent, order quantity becomes the main decision over the interval of the primary selling season. Finally, we demonstrate that the results from the two-season case can be directly extended to the multi-season case and the limited resource multiple-item case

    Inventory control policy of preventive lateral transshipment between retailers in multi periods

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    Purpose: Preventivelateral transshipment can respond to customers who will choose a substitute or to give up when the product is out of stock. Motivatedby the common practice, adecision-making model of preventive lateral transshipment with multi sellingperiods is developed. The purpose of the paper is to explore the optimal preventive lateral transshipment policy with multi selling periods. Design/methodology/approach: With adiscrete-time dynamic programming model, we take a dynamic programming approach and adopt backward induction to analyze two retailers’ preventive lateral transshipment policy. Findings: The optimal preventivelateral transshipment policy is a threshold policy which depends on both theremaining selling periods and inventory level. The above properties ensure thattwo retailers can control inventory with preventive lateral transshipment. Practical implications: The retailer can adjust inventory via the thresholdtype policy. The simple decisionrule which compares on-hand inventory level with the critical inventory level can be used to control inventory by preventive lateral transshipment. Originality/value: A discrete-timedecision-making model of preventive lateral transshipment policy isformulated. This model takes consideration of multi selling periods, whichis different from most existing researches on preventive lateraltransshipment.Peer Reviewe

    Analysis of Book Resale in Amazon Upgrade Framework: A Game-Theory Approach

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    Amazon recently began providing their customers with an innovative and contemporary service. This service supplies customers with the option to purchase an electronic version of a book after they have purchased a physical copy. This is similar to bundling an option of electronic book purchase to a physical one. Such a business practice provides consumers with an opportunity to resell brand new books, which will influence the welfare of publishers, retailers, and consumers. Using a two-period game theory model we discuss these impacts under two scenarios: monopoly of a retailer, as well as competition between retailers. We find that (1) Under a monopoly, the publisher sells at a higher rate, and the retailer sells at a lower rate in the equilibrium; consumers also see an increase in their total surplus; (2) Under competition, retailers who provide this bundle will gain a competitive advantage over the retailers who do not. Our research indicates that bundling a physical book with its digital version yields a win-win strategy for all players

    Implementation of the Newsvendor Model with Clearance Pricing: How to (and How Not to) Estimate a Salvage Value

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    The newsvendor model is designed to decide how much of a product to order when the product is to be sold over a short selling season with stochastic demand and there are no additional opportunities to replenish inventory. There are many practical situations that reasonably conform to those assumptions, but the traditional newsvendor model also assumes a fixed salvage value: all inventory left over at the end of the season is sold off at a fixed per-unit price. The fixed salvage value assumption is questionable when a clearance price is rationally chosen in response to the events observed during the selling season: a deep discount should be taken if there is plenty of inventory remaining at the end of the season, whereas a shallow discount is appropriate for a product with higher than expected demand. This paper solves for the optimal order quantity in the newsvendor model, assuming rational clearance pricing. We then study the performance of the traditional newsvendor model. The key to effective implementation of the traditional newsvendor model is choosing an appropriate fixed salvage value. (We show that an optimal order quantity cannot be generally achieved by merely enhancing the traditional newsvendor model to include a nonlinear salvage value function.) We demonstrate that several intuitive methods for estimating the salvage value can lead to an excessively large order quantity and a substantial profit loss. Even though the traditional model can result in poor performance, the model seems as if it is working correctly: the order quantity chosen is optimal given the salvage value inputted to the model, and the observed salvage value given the chosen order quantity equals the inputted one. We discuss how to estimate a salvage value that leads the traditional newsvendor model to the optimal or near-optimal order quantity. Our results highlight the importance of understanding how a model can interact with its own inputs: when inputs to a model are influenced by the decisions of the model, care is needed to appreciate how that interaction influences the decisions recommended by the model and how the model’s inputs should be estimated

    Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access

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    Dynamic spectrum access is a new paradigm of secondary spectrum utilization and sharing. It allows unlicensed secondary users (SUs) to exploit opportunistically the under-utilized licensed spectrum. Market mechanism is a widely-used promising means to regulate the consuming behaviours of users and, hence, achieves the efficient allocation and consumption of limited resources. In this paper, we propose and study a hybrid secondary spectrum market consisting of both the futures market and the spot market, in which SUs (buyers) purchase under-utilized licensed spectrum from a spectrum regulator, either through predefined contracts via the futures market, or through spot transactions via the spot market. We focus on the optimal spectrum allocation among SUs in an exogenous hybrid market that maximizes the secondary spectrum utilization efficiency. The problem is challenging due to the stochasticity and asymmetry of network information. To solve this problem, we first derive an off-line optimal allocation policy that maximizes the ex-ante expected spectrum utilization efficiency based on the stochastic distribution of network information. We then propose an on-line VickreyCClarkeCGroves (VCG) auction that determines the real-time allocation and pricing of every spectrum based on the realized network information and the pre-derived off-line policy. We further show that with the spatial frequency reuse, the proposed VCG auction is NP-hard; hence, it is not suitable for on-line implementation, especially in a large-scale market. To this end, we propose a heuristics approach based on an on-line VCG-like mechanism with polynomial-time complexity, and further characterize the corresponding performance loss bound analytically. We finally provide extensive numerical results to evaluate the performance of the proposed solutions.Comment: This manuscript is the complete technical report for the journal version published in INFORMS Operations Researc

    Inventory models with lateral transshipments : a review

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    Lateral transshipments within an inventory system are stock movements between locations of the same echelon. These transshipments can be conducted periodically at predetermined points in time to proactively redistribute stock, or they can be used reactively as a method of meeting demand which cannot be satised from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level denition, all in uence the best method of transshipping. Models of many dierent systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these dierences can be understood and gaps within the literature can be identied

    Optimal combined purchasing strategies for a risk-averse manufacturer under price uncertainty

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    Purpose: The purpose of our paper is to analyze optimal purchasing strategies when a manufacturer can buy raw materials from a long-term contract supplier and a spot market under spot price uncertainty. Design/methodology/approach: This procurement model can be solved by using dynamic programming. First, we maximize the DM’s utility of the second period, obtaining the optimal contract quantity and spot quantity for the second period. Then, maximize the DM’s utility of both periods, obtaining the optimal purchasing strategy for the first period. We use a numerical method to compare the performance level of a pure spot sourcing strategy with that of a mixed strategy. Findings: Our results show that optimal purchasing strategies vary with the trend of contract prices. If the contract price falls, the total quantity purchased in period 1 will decrease in the degree of risk aversion. If the contract price increases, the total quantity purchased in period 1 will increase in the degree of risk aversion. The relationship between the optimal contract quantity and the degree of risk aversion depends on whether the expected spot price or the contract price is larger in period 2. Finally, we compare the performance levels between a combined strategy and a spot sourcing strategy. It shows that a combined strategy is optimal for a risk-averse buyer. Originality/value: It’s challenging to deal with a two-period procurement problem with risk consideration. We have obtained results of a two-period procurement problem with two sourcing options, namely contract procurement and spot purchases. Our model incorporates the buyer’s risk aversion factor and the change of contract prices, which are not addressed in early studies.Peer Reviewe
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