竞争环境下基于乘客分类的航空客运机票控制和动态定价综合模型

假定航空公司以提供折扣票的方式将乘客分为两类,并通过动态控制折扣票的销售和对普通票实行动态定价来最大化自身的期望收益.应用动态规划建立了竞争环境下两航空公司的折扣机票控制和普通机票动态定价综合模型,讨论了普通机票价格均衡的存在性,并给出航空公司基于已卖出的机票数量接受或拒绝乘客购买折扣票的阈值.最后,通过算例讨论了不同参数对均衡价格、阈值和期望收益的影响.     

乘客策略行为下考虑需求学习的航空客运动态定价策略研究

研究航空公司在需求学习下的动态定价策略。通过假设乘客到达率不确定以及具有策略等待行为,运用贝叶斯理论和博弈论对航空公司需求学习下的多周期动态定价问题进行建模,探讨了机票最优定价策略的充分条件,并通过分析航空公司收益函数的性质,得到了最优定价随时间和已出售机票数量的变化趋势。最后应用算例分析了需求学习的效果,得出:需求学习能够缓解需求不确定带来的损失,但不能完全消除;乘客策略程度越大,需求学习效果越明显。     

面向战略型消费者的产品创新与定价策略

考虑垄断制造商面向战略型消费者时的产品创新与定价问题。运用消费者效用理论和博弈论等方法,构建静态和动态定价下制造商和消费者两期决策模型并求解分析。结果表明,消费者是否购买以及何时购买产品取决于升级换代产品的价格阈值。与静态定价相比较,动态定价能使制造商获得更多期望收益,但会降低消费者剩余、弱化制造商的产品创新积极性,并且这种弱化现象在产品价值折扣系数较高的情况下尤为明显。战略消费者购买行为对制造商的产品创新、期望收益和消费者剩余的影响,不仅依赖于制造商选择何种定价策略,还取决于产品价值折扣系数的大小。研究结论为消费者的产品购买和升级换代提供了理论建议,为企业的产品创新和定价提供了决策参考。     

航空公司超额订票的收益分析

研究了航空公司超额预订机票的收益问题 .通过建立多等级票价模型 ,分别对一个航班和两个航班超额订票的收益进行研究 ,并讨论收益对预订票数、未到乘客数等参量的敏感性 .     

基于粒子群算法的航班舱位控制研究

首先介绍了收益管理提出的背景思想,在对航班收益管理基本概念作简要阐述的情况下,给出了期望边际座位收入理论.提出了在北京到上海的单航程航段下,航空公司会提供出发时间不同但航程相同的连续两个航班.旅客在没能购买到期望的航班舱位时,会以一定的概率选择购买下一航班的机票或者取消订票,改乘其他交通运输工具.旅客对于某一航班的座位需求主要由固有需求和上一航班需求的转移两部分构成.基于这样的角度建立了两航班机票预售模型,不考虑动态订座,no-show和超售等情况,并利用算法对模型进行了求解和分析.最后得出结论当航班票价等级数量较少时,为高票价等级安排较多数量座位可提高航班收入.而当航班票价等级数量比较多时,为低票价等级多安排一些座位可为航班提高收入.     

搜寻成本下可替代产品的定价策略与库存决策

为探寻存在搜寻成本情况下消费者购买可替代产品时的定价与库存问题,从消费者效用出发,对厂商收益构建了基于马尔可夫决策过程的优化模型。在消费者方面,分析了其购买与继续搜寻的条件,并分别在搜寻成本不变和搜寻成本边际递减的情况下研究了消费者保留效用的变化情况以及购买相应产品的概率。此外,与很多相关文献不同的是,由于搜寻成本的存在,该情形下的消费者并不一定会在完成购买之前搜寻完所有的产品。在厂商方面,根据实际情况构建不同搜寻顺序下的收益模型并求解出最优定价策略与库存策略,并将定价模型与库存策略扩展到了动态的环境,为厂商制定价格及库存方案提供相应的决策支持。     

基于数字仿真的收益管理整合决策

对航空公司收益管理进行机票定价和座位存量分配的整合研究。应用计算机仿真算法动态构造民航收益管理系统中的需求预测模型,并根据航班收益最大化原则,确定价格与座位存量分配,根据需求变化实时调整价格和座位存量。仿真运算结果显示,该算法可以使航空公司不同航班收益比固定价格提高2%以上。     

基于策略型消费者购买习惯的产品动态定价决策研究

消费者具有浏览销量和评论的购买习惯.为分析此购买习惯对零售商定价的影响,以策略型消费者为研究对象,建立了受产品价格、销量与评论内容影响的效用函数,并构建了策略型消费者和零售商的两阶段博弈模型.同时,基于消费者购买习惯对零售商公布和调整价格的两种策略进行博弈和比较分析.结论表明,消费者通过浏览评论信息对产品质量的感知达到一定程度时,购买习惯改变了零售商总是降价的定价策略;零售商在公布价格策略中产品定价和收益高于调整价格策略;当消费者较具有耐心且对产品质量感知显著时,能提高消费者需求.研究结果对零售商的定价决策具有指导意义.     

收益管理中单产品动态定价的稳健模型研究

在收益管理的动态定价模型的研究中,由传统的确定性模型和随机模型所得到的定价策略常常受限制于需求估计的准确性,当对需求的估计出现偏差时定价策略可能达不到最大化收益的目的,因此定价策略即最优解的稳健性越来越受到研究者的重视。针对需求函数系数的不确定性,在未知需求分布的条件下,应用稳健最优化思想,提出了一种稳健的动态定价模型,并对模型的最优解和最大收益进行了数值模拟分析。     

VaR约束下最优比例再保险和投资策略问题

研究了VaR动态约束下保险人的最优投资和再保险策略选择问题.假设保险人选择比例再保险来分散索赔风险,并通过银行存款和投资股票的手段来增加额外收益,其中股票价格满足Heston模型.保险人的目标是寻求使其终端财富的期望效用最大的最优策略.引入VaR约束条件并采用期望效用最大化为准则,运用随机控制理论建立具有VaR约束的随机控制问题,采用动态规划推导HJB方程,并利用Lagrange函数等方法得到指数效用下VaR约束有效和无效时的最优策略.另外,考虑了仅投资情形下的最优投资策略.最后通过仿真对最优策略进行敏感性分析.     

Revenue management for low-cost providers

Low-cost providers have emerged as important players in many service industries, the most predominant being low-cost, or the so-called discount airlines. This paper presents models and results leading toward understanding the revenue management outlook for a discount pricing firm. A framework and model is formulated specifically for the airline industry, but is generalizable to low-cost providers in similar revenue management settings. We formulate an optimal pricing control model for a firm that must underprice to capture a segment of exogenous demand. Two specific model formulations are considered: a continuous deterministic version, and a discrete stochastic version. Structural results are derived for the deterministic case, providing insight into the general form of optimal underpricing policies. The stochastic results support the structural insight from the deterministic solution, and illuminate the effect of randomness on the underpricing policies.     

A continuous-time dynamic pricing model knowing the competitor’s pricing strategy

In this paper we consider a dynamic pricing model for a firm knowing that a competitor adopts a static pricing strategy. We establish a continuous time model to analyze the effect of dynamic pricing on the improvement in expected revenue in the duopoly. We assume that customers arrive to purchase tickets in accordance with a geometric Brownian motion. We derive an explicit closed-form expression for an optimal pricing policy to maximize the expected revenue. It is shown that when the competitor adopts a static pricing policy, dynamic pricing is not always effective in terms of maximizing expected revenue compared to a fixed pricing strategy. Moreover, we show that the size of the reduction in the expected revenue depends on the competitor’s pricing strategy. Numerical results are presented to illustrate the dynamic pricing policy.     

Network capacity management under competition

We consider capacity management games between airlines who transport passengers over a joint airline network. Passengers are likely to purchase alternative tickets of the same class from competing airlines if they do not get tickets from their preferred airlines. We propose a Nash and a generalized Nash game model to address the competitive network revenue management problem. These two models are based on well-known deterministic linear programming and probabilistic nonlinear programming approximations for the non-competitive network capacity management problem. We prove the existence of a Nash equilibrium for both games and investigate the uniqueness of a Nash equilibrium for the Nash game. We provide some further uniqueness and comparative statics analysis when the network is reduced to a single-leg flight structure with two products. The comparative statics analysis reveals some useful insights on how Nash equilibrium booking limits change monotonically in the prices of products. Our numerical results indicate that airlines can generate higher and more stable revenues from a booking scheme that is based on the combination of the partitioned booking-limit policy and the generalized Nash game model. The results also show that this booking scheme is robust irrespective of which booking scheme the competitor takes.     

Optimal dynamic pricing of inventories with stochastic demand and discounted criterion

We consider a continuous time dynamic pricing problem for selling a given number of items over a finite or infinite time horizon. The demand is price sensitive and follows a non-homogeneous Poisson process. We formulate this problem as to maximize the expected discounted revenue and obtain the structural properties of the optimal revenue function and optimal price policy by the Hamilton-Jacobi-Bellman (HJB) equation. Moreover, we study the impact of the discount rate on the optimal revenue function and the optimal price. Further, we extend the problem to the case with discounting and time-varying demand, the infinite time horizon problem. Numerical examples are used to illustrate our analytical results.     

Approximate nucleolus-based revenue sharing in airline alliances

Alliances allow the airlines to extend their networks and increase the number of destinations they can access. Different from the traditional single airline approach, in an alliance, partner airlines may sell tickets for the same itinerary. In addition, one itinerary may consist of several flight legs, each of which may be operated by a different airline. A major issue that needs to be addressed is how to share the revenue generated from selling a ticket for a product among the individual airlines in a fair way. The fair allocation of the revenue has a critical importance for the long-term stability of the alliance. We model the problem as a cooperative game and show that the core of the game is non-empty. We propose to use a revenue proration scheme based on the concept of the nucleolus. The numerical studies reveal that the revenue shares can effectively be computed even for large alliance networks.     

Dynamic price competition with discrete customer choices

For many years, dynamic pricing has proven to be an effective tool to increase revenue in the airline and other service industries. Most studies, however, focused on monopolistic models and ignored the fact that nowadays consumers can easily compare prices on the Internet. In this paper, we develop a game-theoretic model to describe real-time dynamic price competition between firms that sell substitutable products. By assuming the real-time inventory levels of all firms are public information, we show the existence of Nash equilibrium. We then discuss how a firm can adapt if it knows only the initial – but not the real-time – inventory levels of its competitors. We compare a firm’s expected revenue under different information structures through numerical experiments.     

Maximizing revenue in the airline industry under one-way pricing

The paper describes a methodology that has been implemented in a major British airline to find the optimal price to charge for airline tickets under one-way pricing. An analytical model has been developed to describe the buying behaviour of customers for flights over the selling period. Using this model and a standard analytical method for constrained optimization, we can find an expression for the optimal price structure for a flight. The expected number of bookings made on each day of the selling period and in each fare class given these prices can then be easily calculated. A simulation model is used to find the confidence ranges on the numbers of bookings and these ranges can be used to regulate the sale of tickets. A procedure to update the price structure based on the remaining capacity has also been developed.     

A continuous-time seat control model for single-leg flights with no-shows and optimal overbooking upper bound

This article proposes a continuous-time model to combine seat control and overbooking policies for single-leg flights. We assume that demand is time-and-fare dependent and follows a Poisson process. No-show passengers receive refunds which depend on their fares. Overbooking penalty is a uniformly convex function of oversale. To maximize the expected revenue, airline managers seek optimal seat allocation among competing passengers. In the meantime, they need to determine an optimal aggregate overbooking upper bound, which balances the no-show refunds and oversale penalties. Our basic model shows (i) although the nested-fare structure does not hold for the face value of fares, its essence is preserved in the sense of net fares; i.e., the face value less the no-show refund; (ii) the optimal control policy is based on a set of pre-calculated time thresholds, which is easy to implement; and (iii) there exists an optimal overbooking upper bound, below which the value function strictly increases in the upper bound, and above which the value function stays constant. We further extend the basic model to consider fare-dependent no-show rates. Numerical examples are presented.     

中国民航机票折扣定价策略研究

在分析中国民航票价演变的基础上,研究了垄断航空公司折扣票价的利润最大化问题,对比分析了在单一价格、外生型价格歧视和内生型价格歧视三种情形下,折扣率对利润、价格和产出的影响,研究表明:内生型价格歧视的利润和产出大于外生型价格歧视下的利润和产出,而价格歧视下的利润大于单一价格下的利润,折扣票价的有效实施应以分隔各子市场为前提。进一步的研究应扩展到多级票价和动态定价中去。