共查询到20条相似文献，搜索用时 15 毫秒
1.
We present a new deterministic linear program for the network revenue management problem with customer choice behavior. The novel aspect of our linear program is that it naturally generates bid prices that depend on how much time is left until the time of departure. Similar to the earlier linear program used by van Ryzin and Liu (2004), the optimal objective value of our linear program provides an upper bound on the optimal total expected revenue over the planning horizon. In addition, the percent gap between the optimal objective value of our linear program and the optimal total expected revenue diminishes in an asymptotic regime where the leg capacities and the number of time periods in the planning horizon increase linearly with the same rate. Computational experiments indicate that when compared with the linear program that appears in the existing literature, our linear program can provide tighter upper bounds, and the control policies that are based on our linear program can obtain higher total expected revenues. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 相似文献
2.
Yongbo Xiao;Chen Hu;Qian Liu; 《海军后勤学研究》2024,71(3):333-350
It has been challenging for firms to effectively manage demand when they release products of one generation after another one. Motivated by the observations from the smartphone industry, this paper investigates the effectiveness of two demand management strategies in the presence of a product rollover: the upgrade program and price markdown policy. Under an upgrade program, a firm allows customers to upgrade their on-hand product to a new generation product that will be released in a future time. Under a markdown pricing policy, the firm offers a discount for the currently available product so as to induce waiting customers to make immediate purchases. The two demand management strategies target different groups of customers and have distinct impacts on customers' choices. Starting from the time-varying choice behavior of a heterogeneous group of customers, we study the optimal pricing decisions involved in the two strategies. Specifically, when customers are myopic in the sense that they only make a one-time purchasing decision upon arrival, we show that the firm should offer the upgrade program only when the innovation level of the new product is relatively high, and the firm's optimal upgrade price can increase over time. Generally, the firm should offer the upgrade program during the early selling period and adopt markdown pricing as the release date of the new product approaches. Numerical experiments reveal that the dynamic upgrade program and markdown pricing policies can help improve profit significantly. When customers are strategic in the sense that they can monitor the selling prices and make dynamic purchasing decisions until they buy a unit of product, we examine two coping strategies that a firm can adopt, and investigate how the strategic monitoring behavior may influence a firm's optimal selling decisions and profit. 相似文献
3.
We consider the problem of nonparametric multi-product dynamic pricing with unknown demand and show that the problem may be formulated as an online model-free stochastic program, which can be solved by the classical Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. We prove that the expected cumulative regret of the KWSA algorithm is bounded above by where κ1, κ2 are positive constants and T is the number of periods for any T = 1, 2, … . Therefore, the regret of the KWSA algorithm grows in the order of , which achieves the lower bounds known for parametric dynamic pricing problems and shows that the nonparametric problems are not necessarily more difficult to solve than the parametric ones. Numerical experiments further demonstrate the effectiveness and efficiency of our proposed KW pricing policy by comparing with some pricing policies in the literature. 相似文献
4.
Yongbo Xiao 《海军后勤学研究》2018,65(1):3-25
In many applications, managers face the problem of replenishing and selling products during a finite time horizon. We investigate the problem of making dynamic and joint decisions on product replenishment and selling in order to improve profit. We consider a backlog scenario in which penalty cost (resulting from fulfillment delay) and accommodation cost (resulting from shortage at the end of the selling horizon) are incurred. Based on continuous‐time and discrete‐state dynamic programming, we study the optimal joint decisions and characterize their structural properties. We establish an upper bound for the optimal expected profit and develop a fluid policy by resorting to the deterministic version of the problem (ie, the fluid problem). The fluid policy is shown to be asymptotically optimal for the original stochastic problem when the problem size is sufficiently large. The static nature of the fluid policy and its lack of flexibility in matching supply with demand motivate us to develop a “target‐inventory” heuristic, which is shown, numerically, to be a significant improvement over the fluid policy. Scenarios with discrete feasible sets and lost‐sales are also discussed in this article. 相似文献
5.
We incorporate strategic customer waiting behavior in the classical economic order quantity (EOQ) setting. The seller determines not only the timing and quantities of the inventory replenishment, but also the selling prices over time. While similar ideas of market segmentation and intertemporal price discrimination can be carried over from the travel industries to other industries, inventory replenishment considerations common to retail outlets and supermarkets introduce additional features to the optimal pricing scheme. Specifically, our study provides concrete managerial recommendations that are against the conventional wisdom on “everyday low price” (EDLP) versus “high-low pricing” (Hi-Lo). We show that in the presence of inventory costs and strategic customers, Hi-Lo instead of EDLP is optimal when customers have homogeneous valuations. This result suggests that because of strategic customer behavior, the seller obtains a new source of flexibility—the ability to induce customers to wait—which always leads to a strictly positive increase of the seller's profit. Moreover, the optimal inventory policy may feature a dry period with zero inventory, but this period does not necessarily result in a loss of sales as customers strategically wait for the upcoming promotion. Furthermore, we derive the solution approach for the optimal policy under heterogeneous customer valuation setting. Under the optimal policy, the replenishments and price promotions are synchronized, and the seller adopts high selling prices when the inventory level is low and plans a discontinuous price discount at the replenishment point when inventory is the highest. 相似文献
6.
We deal with dynamic revenue management (RM) under competition using the nonatomic‐game approach. Here, a continuum of heterogeneous sellers try to sell the same product over a given time horizon. Each seller can lower his price once at the time of his own choosing, and faces Poisson demand arrival with a rate that is the product of a price‐sensitive term and a market‐dependent term. Different types of sellers interact, and their respective prices help shape the overall market in which they operate, thereby influencing the behavior of all sellers. Using the infinite‐seller approximation, which deprives any individual seller of his influence over the entire market, we show the existence of a certain pattern of seller behaviors that collectively produce an environment to which the behavior pattern forms a best response. Such equilibrium behaviors point to the suitability of threshold‐like pricing policies. Our computational study yields insights to RM under competition, such as profound ways in which consumer and competitor types influence seller behaviors and market conditions. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 365–385, 2014 相似文献
7.
Capacity providers such as airlines often sell the same capacity to different market segments at different prices to improve their expected revenues. The absence of a secondary market, due to the nontransferability of airline tickets, gives rise to an opportunity for airlines to broker capacity between consumers with different willingness to pay. One way to broker capacity is by the introduction of callable products. The idea is similar to callable bonds where the issuer has the right, but not the obligation, to buy back the bonds at a certain price by a certain date. The idea of callable products was introduced before under the assumption that the fare-class demands are all independent. The independent assumption becomes untenable when there is significant demand recovery (respectively, demand cannibalization) when lower fares are closed (respectively, opened). In this case, consumer choice behavior should be modeled explicitly to make meaningful decisions. In this paper, we consider a general consumer choice model and develop the optimal strategy for callable products. Our numerical study illustrates how callable products are win-win-win, for the capacity provider and for both high and low fare consumers. Our studies also identify conditions for callable products to result in significant improvements in expected revenues. 相似文献
8.
This article investigates the optimal inventory and admission policies for a “Clicks‐and‐Bricks” retailer of seasonal products that, in addition to selling through its own physical and online stores, also sells through third‐party websites by means of affiliate programs. Through postings on partners' webpages, an affiliate program allows a retailer to attract customers who would otherwise be missed. However, this retailer needs to pay a commission for each sale that originates from the website operators participating in the program. The retailer may also refer online orders to other sources (such as distributors and manufacturers) for fulfillment through a drop‐shipping agreement and thus earns commissions. This would be an option when, for example, the inventories at the physical stores were running low. Therefore, during the selling horizon, the retailer needs to dynamically control the opening/closing of affiliate programs and decide on the fulfillment option for online orders. On the basis of a discrete‐time dynamic programming model, the optimal admission policy of the retailer is investigated in this paper, and the structural properties of the revenue function are characterized. Numerical examples are given to show the revenue impact of optimal admission control. The optimal initial stocking decisions at the physical stores are also studied. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009 相似文献
9.
This article is concerned with the determination of pricing strategies for a firm that in each period of a finite horizon receives replenishment quantities of a single product which it sells in two markets, for example, a long‐distance market and an on‐site market. The key difference between the two markets is that the long‐distance market provides for a one period delay in demand fulfillment. In contrast, on‐site orders must be filled immediately as the customer is at the physical on‐site location. We model the demands in consecutive periods as independent random variables and their distributions depend on the item's price in accordance with two general stochastic demand functions: additive or multiplicative. The firm uses a single pool of inventory to fulfill demands from both markets. We investigate properties of the structure of the dynamic pricing strategy that maximizes the total expected discounted profit over the finite time horizon, under fixed or controlled replenishment conditions. Further, we provide conditions under which one market may be the preferred outlet to sale over the other. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 531–549, 2015 相似文献
10.
In this article, we develop a stochastic approximation algorithm to find good bid price policies for the joint capacity allocation and overbooking problem over an airline network. Our approach is based on visualizing the total expected profit as a function of the bid prices and searching for a good set of bid prices by using the stochastic gradients of the total expected profit function. We show that the total expected profit function that we use is differentiable with respect to the bid prices and derive a simple expression that can be used to compute its stochastic gradients. We show that the iterates of our stochastic approximation algorithm converge to a stationary point of the total expected profit function with probability 1. Our computational experiments indicate that the bid prices computed by our approach perform significantly better than those computed by standard benchmark strategies and the performance of our approach is relatively insensitive to the frequency with which we recompute the bid prices over the planning horizon. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011 相似文献
11.
We consider the joint pricing and inventory‐control problem for a retailer who orders, stocks, and sells two products. Cross‐price effects exist between the two products, which means that the demand of each product depends on the prices of both products. We derive the optimal pricing and inventory‐control policy and show that this policy differs from the base‐stock list‐price policy, which is optimal for the one‐product problem. We find that the retailer can significantly improve profits by managing the two products jointly as opposed to independently, especially when the cross‐price demand elasticity is high. We also find that the retailer can considerably improve profits by using dynamic pricing as opposed to static pricing, especially when the demand is nonstationary. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009 相似文献
12.
Ride-hailing platforms such as Uber, Lyft, and DiDi have achieved explosive growth and reshaped urban transportation. The theory and technologies behind these platforms have become one of the most active research topics in the fields of economics, operations research, computer science, and transportation engineering. In particular, advanced matching and dynamic pricing (DP) algorithms—the two key levers in ride-hailing—have received tremendous attention from the research community and are continuously being designed and implemented at industrial scales by ride-hailing platforms. We provide a review of matching and DP techniques in ride-hailing, and show that they are critical for providing an experience with low waiting time for both riders and drivers. Then we link the two levers together by studying a pool-matching mechanism called dynamic waiting (DW) that varies rider waiting and walking before dispatch, which is inspired by a recent carpooling product Express Pool from Uber. We show using data from Uber that by jointly optimizing DP and DW, price variability can be mitigated, while increasing capacity utilization, trip throughput, and welfare. We also highlight several key practical challenges and directions of future research from a practitioner's perspective. 相似文献
13.
Alec Morton 《海军后勤学研究》2006,53(8):748-760
Many revenue management problems have a network aspect. In this paper, we argue that a network can be thought of as a system of substitutable and complementary products, and the value of a revenue management model should be supermodular or submodular in the availability of two resources as the resources are economic substitutes or complements. We demonstrate that this is true in the case of a two‐resource dynamic stochastic revenue management model and show how this applies for multi‐resource deterministic static revenue management models. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006 相似文献
14.
We consider a periodic review model over a finite horizon for a perishable product with fixed lifetime equal to two review periods. The excess demand in a period is backlogged. The optimal replenishment and demand management (using price) decisions for such a product depend on the relative order of consumption of fresh and old units. We obtain insights on the structure of these decisions when the order of consumption is first‐in, first‐out and last‐in, first‐out. For the FIFO system, we also obtain bounds on both the optimal replenishment quantity as well as expected demand. We compare the FIFO system to two widely analyzed inventory systems that correspond to nonperishable and one‐period lifetime products to understand if demand management would modify our understanding of the relationship among the three systems. In a counterintuitive result, we find that it is more likely that bigger orders are placed in the FIFO system than for a nonperishable product when demand is managed. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013 相似文献
15.
We present a time decomposition for inventory routing problems. The methodology is based on valuing inventory with a concave piecewise linear function and then combining solutions to single‐period subproblems using dynamic programming techniques. Computational experiments show that the resulting value function accurately captures the inventory's value, and solving the multiperiod problem as a sequence of single‐period subproblems drastically decreases computational time without sacrificing solution quality. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010 相似文献
16.
Mengnan Wang;Juliang Zhang;T. C. E. Cheng; 《海军后勤学研究》2024,71(5):645-659
To encourage consumers to reuse their used products, some manufacturers launch second-hand platforms while others adopt sharing platforms. Which platform benefits them more is an interesting problem for such manufacturers. To address this problem, we propose a two-period model in which heterogeneous consumers decide whether to buy new products in Period 1 or to rent (buy) used products on the platform in Period 2. Under a proportional transaction fee, we show that the two platforms can benefit the manufacturer if the unit production cost is high, and the valuation difference is low or the number of high-value consumers in Period 1 is fewer than in Period 2. Moreover, the two platforms are equivalent when the salvage value is 0. When the salvage value is positive, the second-hand platform benefits the manufacturer more than the sharing platform. The sharing platform induces the manufacturer to set a higher sale price than the second-hand platform when the unit production cost is high and there are fewer high-value consumers in Period 1. Otherwise, the sale and reselling prices are higher under the second-hand platform. We also consider the cases with a general consumer valuation distribution, multiple product life cycles, and a fixed transaction fee. Our findings can help manufacturers make the decision on platform choice to handle used products. 相似文献
17.
Kyle Y. Lin 《海军后勤学研究》2004,51(4):501-521
Consider a sequential dynamic pricing model where a seller sells a given stock to a random number of customers. Arriving one at a time, each customer will purchase one item if the product price is lower than her personal reservation price. The seller's objective is to post a potentially different price for each customer in order to maximize the expected total revenue. We formulate the seller's problem as a stochastic dynamic programming model, and develop an algorithm to compute the optimal policy. We then apply the results from this sequential dynamic pricing model to the case where customers arrive according to a continuous‐time point process. In particular, we derive tight bounds for the optimal expected revenue, and develop an asymptotically optimal heuristic policy. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004. 相似文献
18.
We evaluate the effect of competition on prices, profits, and consumers' surplus in multiperiod, finite horizon, dynamic pricing settings. In our base model, a single myopic consumer visits two competing retailers, who offer identical goods, in a (first order Markovian) probabilistic fashion—if the posted price exceeds the consumer's valuation for the good, he returns to the same store in the following period with a certain probability. We find that even a small reduction in the return probability from one—which corresponds to the monopoly case at which prices decline linearly—is sufficient to revert the price decline from a linear into an exponential shape. Each retailer's profit is particularly sensitive to changes in his return probability when it is relatively high, and is maximized under complete loyalty behavior (i.e., return probability is one). On the other hand, consumer surplus is maximized under complete switching behavior (i.e., return probability is zero). In the presence of many similar consumers, the insights remain valid. We further focus on the extreme scenario where all consumers follow a complete switching behavior, to derive sharp bounds, and also consider the instance where, in this setting, myopic consumers are replaced with strategic consumers. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011 相似文献
19.
We consider a dynamic pricing model in which the instantaneous rate of the demand arrival process is dependent on not only the current price charged by the concerned firm, but also the present state of the world. While reflecting the current economic condition, the state evolves in a Markovian fashion. This model represents the real‐life situation in which the sales season is relatively long compared to the fast pace at which the outside environment changes. We establish the value of being better informed on the state of the world. When reasonable monotonicity conditions are met, we show that better present economic conditions will lead to higher prices. Our computational study is partially calibrated with real data. It demonstrates that the benefit of heeding varying economic conditions is on par with the value of embracing randomness in the demand process. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 66:73–89,2019 相似文献
20.
In this article, we consider an online retailer who sells two similar products (A and B) over a finite selling period. Any stock left at the end of the period has no value (like clothes going out of fashion at the end of a season). Aside from selling the products at regular prices, he may offer an additional option that sells a probabilistic good, “A or B,” at a discounted price. Whenever a customer buys a probabilistic good, he needs to assign one of the products for the fulfillment. Considering the choice behavior of potential customers, we model the problem using continuous‐time, discrete‐state, finite‐horizon dynamic programming. We study the optimal admission decisions and devise two scenarios, whose value functions can be used as benchmarks to evaluate the demand induction effect and demand dilution effect of probabilistic selling (PS). We further investigate an extension of the base MDP (Markov Decision Process) model in which the fulfillment of probabilistic sales is uncontrollable by the retailer. A special case of the extended model can be used as a benchmark to quantify the potential inventory pooling effect of PS. Finally, numerical experiments are conducted to evaluate the overall profit improvement, and the effects from adopting the PS strategy. © 2014 Wiley Periodicals, Inc. Naval Research Logistics, 61: 604–620, 2014 相似文献