航空公司与旅行社的协作机制研究

旅行社是航空公司机票销售网络中非常重要的一环。作为一种特殊的机票代理,为了应对旅游旺季的旅客需求,旅行社往往会提前较长时间从航空公司预订机票。对于航空公司来说,提前预订机票给旅行社是降低销售风险的一个重要途径。在进行机票预订交易时,双方都必须进行慎重的决策;旅行社决策最优的预订数量;航空公司决策最优的供给量。本文正是在对双方各自最优决策探讨的基础上,对双方的协作机制进行了研究。在模型中,我们考虑了双方的缺票损失、航空公司的超额预订等因素。双方协作的目标是在实现整体收益最大化的基础上,同时实现航空公司和旅行社各自的收益更大化。本文提出了一种中间价格调整的协作机制,并说明了这种机制的可行性和收敛性。     

基于多级折扣价格的易逝品订货策略研究

基于价格折扣条件下的报童模型,研究了分销商面向折拐的需求价格曲线.采用呈等差数列下降的多级折扣价格销售产品,以期望利润最大为目标,给出了求解最优折扣次数的算法,进而得到相应的分销商最优订货量.与需求价格曲线的斜率b不变时相比较,b增大对最优订货量无显著影响;b减小对最优订货量有显著影响.     

国内航线收益管理问题研究（A）

航线收益管理的核心是价格细分，根据旅客不同时间段的需求特征和价格弹性，结合市场的订票情况、市场竞争变化、公司政策和价格变化等因素。对航班未来客座率的变化进行科学的、准确的预测，从而对旅客执行不同的价格标准，最大限度地开发市场潜在需求。其基本手段是通过不同等级舱位与不同时期订票构成的票价组合，以及通过管理协调与业务流程再造，在不增加企业成本的情况下，以最快速的反应和最恰当的价格细分，使航空公司出售尽可能多的产品，从而达到收益最大化目的。文章从收益管理的基本形式及其理论依据、管理协调、业务流程再造等方面说明上述问题。     

航空客运舱位控制和超售综合静态建模研究

本文研究航空运输收益管理的舱位控制和超售综合静态建模问题.通过将机票销售过程模拟成排队过程,以收益最大化为目标函数,首先给出了单航段单等级票价下的超售水平公式.然后将该思路推广到多等级票价情况,应用动态规划方法建立了舱位控制和超售综合控制静态模型,在建立了两个定理的基础上,由该模型进一步推导出了各等级舱位最优订座限制的决策方程.最后分析了一个实例以说明决策方程的应用.     

在线渠道折扣促销下的双渠道供应链合作广告协调研究北大核心CSSCI

针对制造商在线渠道与传统零售渠道同时存在价格和广告竞争下的合作广告问题,建立双渠道供应链的价格折扣和广告需求模型,分别求出了集中决策和Stackelberg主从博弈下的均衡广告投入和广告分担比例,分析了价格折扣变化对合作广告决策的影响,并探讨了渠道市场结构影响下的最优价格折扣水平。研究结果表明,价格折扣的提高将降低零售商广告投入的积极性;当价格折扣水平小于某一临界值,随着价格折扣的加大,制造商将提高在线渠道的折扣促销广告投入。通过对比集中决策和Stackelberg主从博弈下均衡的广告投入和价格折扣水平,在制造商分担部分传统零售商促销广告投入的基础上,设计一个在线渠道收益共享协调契约,可实现供应链系统协调。     

电力市场竞价上网的拍卖机制设计

竞价上网是电力行业实现市场化的基础条件,竞价机制设计是深化市场化改革亟需探讨的议题。基于离散多物品逆向拍卖的理论框架对电力市场竞价上网的交易机制进行建模,在考虑需求状态、市场结构和报价区间等现实情形下刻画出统一价格（UPA）和差别价格（DPA）两种常用竞价机制下发电厂商的均衡报价策略,并从期望收益和生产效率两个视角进行机制比较。结果表明：（1）在低需求状态下,两种机制的市场均衡价格均为未被调用的最高效率发电厂商（机组）的边际成本;在高需求状态下,UPA存在多重纯策略均衡,DPA出现混合策略均衡。（2）在需求确定（较短报价区间）的情形下,DPA比UPA更可能形成更低的均衡价格;在需求不确定（较长报价区间）的情形下,对称发电厂商在两种机制下具有相同的期望收益。（3）两种机制在生产效率方面的比较是不确定的,具体取决于模型参数和UPA多重均衡的选择。本文的研究结论为完善电力竞价上网交易机制和深化电力体制改革提供理论基础和决策借鉴。     

不确定需求环境下多级库存系统优化与协调模型研究

论文首先将模糊随机变量扩展为混合随机变量,并用来描述不确定需求.然后对多级单周期库存系统在模糊随机和混合随机需求环境下的优化与协调问题作了研究,提出了通过集成库存管理使库存系统整体收益期望值最大化的优化模型和协调合作伙伴利益的数量折扣契约模型,并根据遗传算法理论和计算机模拟技术设计了求解模型的智能算法.最后通过实例对模型进行了仿真分析.     

两种激励条件下三级供应链产品质量控制策略研究

本文基于四阶段Stackelberg博弈分析,研究了在三级供应链中如何进行产品质量控制策略问题。构建了由制造商、零售商与最终顾客组成的三级供应链博弈模型,制造商进行产品质量决策,即生产高质量产品或者低质量产品,零售商进行产品采购决策和零售定价决策,最终顾客根据两种产品质量水平和零售价格的差异,决定产品的购买数量;当零售商采购高质量产品时,制造商将会向其提供价格折扣策略;当零售商采购低质量产品时,制造商将会向其提供延迟付款策略。运用最优化原理,求解了制造商的产品质量水平、价格折扣、延迟付款期限和零售商的零售价格、最终顾客的购买数量,及期望收益函数。进行了算例分析,结果表明:高质量产品零售价格关于价格折扣下降幅度更大,而低质量产品零售价格关于延迟付款期限下降幅度更大;制造商提供的价格折扣越大、延迟付款期限越长,其期望收益将会减少,此时零售商的期望收益将会增加,最终顾客产品需求量将会增加;制造商的总期望收益函数将呈现"倒U"型,求解了期望收益的最大值及各契约参数的值,结果证明所提出的产品质量控制策略是可行的。     

销售不定期客票背景下双航班的联合机票控制研究

航空公司收益管理的基本思想是针对不同的细分市场,将同一舱位的座位以不同的价格进行销售,以实现机票收益的最大化.以前有关机票动态控制的研究基本上都是基于单个航班的,本文则考虑部分行程灵活的旅客在不同航班之间的可能转移行为,研究了两个航班的联合座位动态控制决策.在模型中,结合实际生活中航空公司提前以超低折扣价销售部分不定期客票的做法,本文将航空公司机票销售过程划分为五个阶段,并着重研究了最后两个阶段的(联合)机票控制策略,深入分析了收益函数的结构性质.     

引入乘客博弈的民航收益管理决策优化

基于航班收益最大化目的,研究机票浮动定价与座位存量分配控制相结合,给出两者实时动态调整的优化方法,提出一种改进的遗传算法.首次在收益管理系统中融人乘客与航空公司的博弈性,提出收益管理K线图研究思想,以直观反映价格波动和市场变化情况.提出虚拟舱位容量概念,以减少旅客市场的季节性影响.仿真运算结果显示,该方法通过直接获取潜在需求数据,能够提高航班座位利用率,并使航空公司不同航班在原有收益管理系统基础上分别提高2%至10%甚至更高的收益.     

Penalizing passenger’s transfer time in computing airlines revenue

Airline strategic alliances result in a form of cooperation where firms can access the resources of others network members in order to create added value for their passengers. The shortcoming of this process is that each member of the network makes individual revenue management decisions to maximize its own income, resulting in a sub-optimal income for the network members.To deal with this problem, this paper suggests a resource allocation based on a transfer pricing mechanism, to cooperatively divide the revenue of a passenger between network members. The method penalizes the total time that a passenger takes for reaching the final destination. The model takes into consideration that the profit is independent of the number of available seats (with a maximum determined for each airline). The method computes the optimal transfer pricing and, at the same time, optimizes the quantity of seats (the booking limits). The solution results in a strong Nash equilibrium, which incorporate both the transfer prices and booking limits. We describe the transfer pricing process using an ergodic, finite and continuous-time Markov game model for multiple players. The revenue of each airline in the supply chain will depend on the number of flight transfers and the transit time of the passenger at the airports: the longer the time to the final destination, the lower the price. We compute a collaborative equilibrium point, useful for understanding the resulting revenue of each member of the network. For solving the game, we employ an iterative method based on a proximal approach that involves time penalization. In our final contribution, we present results from a numerical example, which validates the proposed Markov game model and measures the benefits of the transfer pricing resource allocation.     

基于收益管理的邮轮客舱分配与定价模型

基于收益管理的思想对邮轮客舱分配与定价问题进行了研究。结合邮轮运营中的个性化特点，例如消费者团体人员构成多样、较长的预售周期以及救生位和儿童看护人员的数量限制等。在不失一般性的前提下，建立了整数规划模型用以确定在预售周期内的不同预售阶段中各种客舱类型的待售数量及其价格，以达到使邮轮公司收益最大化的目的。实验分析表明，该模型在实际应用中是有效的且呈现出显著的年增长趋势，可明显提高邮轮公司的收益。此外，设计了一种基于韦伯分布的EM算法用以解决模型中涉及到的需求量的无约束估计问题。数值算例研究表明，该算法收敛速度快且无约束估计过程可靠有效。     

随机需求下考虑不同竞争情形的网约车平台动态定价

针对乘车需求波动下网约车平台间存在乘车需求竞争和乘运供应竞争的最优定价问题，以平台期望收益最大化为目标，运用最优控制论方法，构建不同竞争情形下的网约车平台动态定价模型，并利用哈密尔顿函数及模型推导，求得最优动态竞争价格解以及乘运供应率与需求率的变化轨迹。结果表明：平台最优动态竞争价格随市场需求的波动而动态变化，且最优价格可以有效调控平台供应能力，促使平台供需匹配，优化平台期望收益。此外，乘车需求市场竞争越激烈，平台最优价格越低，而乘运供应市场竞争越激烈，最优价格越高。平台间竞争的加剧将降低平台的期望收益，且平台期望收益随着固定佣金报酬率的提高先增大后减小。     

Optimal Dynamic Upgrading in Revenue Management

We consider a revenue management problem involving a two compartment aircraft flying a single leg, with no cancellations or over‐booking. We apply the practice of transforming a choice revenue management model into an independent demand model. Within this assumed independent model, there are two sets of demands, business and economy, each with multiple fare class products. A business passenger can only be accepted into business. An economy passenger can be accepted into economy or upgraded into business. We define a two‐dimensional dynamic program (DP) and show that the value function is sub‐modular and concave in seat availability in the two compartments. Thus the bid prices are non‐decreasing with respect to these state variables. We use this result to propose an exact algorithm to solve the DP. Our numerical investigation suggests that in contrast to standard backward induction, our method could be included in production revenue management systems. Further, when the economy compartment is capacity constrained, we observe a substantial monetary benefit from optimal dynamic upgrading compared to the static upgrading procedures currently used in practice.     

A Comparison of Unconstraining Methods to Improve Revenue Management Systems

Asuccessful revenue management system requires accurate demand forecasts for each customer segment. The forecasts are used to set booking limits for lower value customers to ensure an adequate supply for higher value customers. The very use of booking limits, however, constrains the historical demand data needed for an accurate forecast. Ignoring this interaction leads to substantial penalties in a firm's potential revenues. We review existing unconstraining methods and propose a new method that includes some attractive properties not found in the existing methods. We evaluate several of the common unconstraining methods against our proposed method by testing them on intentionally constrained simulated data. Results indicate our proposed method outperforms other methods in two of three data sets. We also test the revenue impact of our proposed method, expectation maximization (EM), and “no unconstraining” on actual booking data from a hotel/casino. We show that performance varies with the initial starting protection limits and a lack of unconstraining leads to significant revenue losses.     

考虑消费者渠道间需求异质性的BOPS服务模式下生鲜品零售定价策略

针对同时拥有线上和线下销售渠道的生鲜零售商,考虑消费者在渠道间的需求异质性,研究其采用BOPS服务模式后的定价策略。在建立线上线下同价策略模型的基础上,提出线上、线下单一渠道折扣策略以及面向BOPS顾客的折扣策略,进一步设计了联合定价策略,并利用数值实验加以验证和扩展。研究表明:线上渠道折扣与线下渠道折扣策略在有效性上互斥;配送成本适中且配送比例较高时,面向BOPS顾客的折扣策略优于其他两种折扣策略;消费者对折扣的敏感度越高,BOPS折扣策略的适用范围越广,优越性越明显;联合折扣策略可以在更大范围内提升零售商利润。     

Pricing of flexible products

The pricing of flexible products is a new price discrimination practice that can enable firms to increase revenues under capacity considerations. A flexible product is defined as a good or service with at least one product attribute not fully specified at the time of the purchase, leaving the seller with at least two alternatives for the final product design and the ability to assign consumers to one of these alternatives at a later date. Flexible products enable sellers to better utilized capacity, as well as, to segment consumers and price discriminate according to different levels of flexibility. We empirically analyze consumer purchase behavior for flexible products based on a large field study of a low-cost airline. At this low-cost airline, consumers can select the level of flexibility of the flexible product. We identify the drivers of purchase behavior by analyzing the impact of consumers?? flexibility and search behavior and the price discount of the flexible ticket. Further, we estimate the revenue and profit effects of flexible products.     

基于收益分成的多受让方两部技术转移定价策略研究

首先,从一般需求函数出发,得出两部技术转移定价法的一般解析表达式。然后,以线性需求函数为例,通过数值计算,对比分析了收益分成比例、最终产品价格、研发企业利润和受让方企业利润随着转让方和受让方股权比例的不同而变化的趋势。最后,分析得出,通过采用前期固定费用加后期收益分成的两部转移定价方法,不仅可以使研发企业的利润最优,同时还可以缓解技术受让方在单一定价方法下的一次性支出所带来的巨大资金压力和较高风险水平,并且将研发企业的利润与受让方的未来收益紧密联系,实现了双方的收益共享和风险共担。     

PRICE‐DEPENDENT INVENTORY MODELS WITH DISCOUNT OFFERS AT RANDOM TIMES*

We consider an inventory model with a supplier offering discounts to a reseller at random epochs. The offer is accepted when the inventory position is lower than a threshold level. We compare three different pricing policies in which demand is induced by the resellers price variation. Policy 1 is the EOQ policy without discount offers. Policy 2 is a uniform price, stock‐independent policy. Policy 3 is a stock level‐dependent, discriminated price policy. Assuming constant demand rates, expressions are obtained for the optimal order quantities, prices, and profits. The numerical experiments show that if it is better to accept a suppliers discount, then it benefits the reseller to transfer the discount to downstream customers.     

On the Use of Buy Up as a Model of Customer Choice in Revenue Management

We consider settings in which a revenue manager controls bookings over a sequence of flights. The revenue manager uses a buy‐up model to select booking limits and updates estimates of the model parameters as data are accumulated. The buy‐up model we consider is based upon a simple model of customer choice, wherein each low‐fare customer who is not able to purchase a low‐fare ticket will, with a fixed probability, “buy up” to the high fare, independent of everything else. We analyze the evolution of the parameter estimates (e.g., the buy‐up probability) and chosen booking limits in situations where the buy‐up model is misspecified, that is, in situations where there is no setting of its parameters for which its objective function gives an accurate representation of expected revenue as a function of the booking limit. The analysis is motivated by the common situation in which a revenue manager does not know precisely how customers behave but nevertheless uses a parametric model to make decisions. Under some assumptions, we prove that the booking limits and parameter estimates converge and we compare the actual expected revenue at the limiting values with that associated with the booking limits that would be chosen if the revenue manager knew the actual behavior of customers. The analysis shows that the buy‐up model often works reasonably well even when it is misspecified, and also reveals the importance of understanding how parameter estimates of misspecified models vary as functions of decisions.