Online hot selling period and its impact on e-retailer’s pricing strategies

The express delivery industry is often overloaded in some hot online selling seasons, which causes consumers’ dissatisfaction. Under such a circumstance, the e-retailer can utilise two opposite strategies, i.e. to set-up either a low price with a pre-announced markdown pricing (PMDP) strategy, or a high price with a pre-announced markup pricing (PMUP) strategy for the hot selling period. As both the prices and the express service quality are different between the regular period and the hot selling period, consumers can strategically choose their purchase time, which will in turn influences the e-retailer’s pricing strategy. To investigate under what condition one pricing strategy will dominate the other, we propose a two period pricing model in which the selling season are divided into regular and hot selling period, and all consumers are assumed to be strategic. The e-retailer determines the prices over the two kinds of periods to maximise its profit. The comparison shows that a PMUP (resp. PMDP) strategy is preferred when the overloading degree in the hot selling period is slight (resp. heavy). Furthermore, we extend our model by incorporating the competition of traditional retailers.     

“负载-效用”两级均衡下智能电网实时电价定价策略

社会福利最大化下的实时电价定价机制未考虑电力系统各主体的利益独立性,无法实现电力系统各主体的收益效用均衡,另一方面可能造成用户负载峰谷的产生或者转移。将"负载-效用"两级均衡融入智能电网实时电价的定价优化,建立了实时电价定价策略的两级均衡模型。基于电网系统各主体的收益效用函数推导出采购电价与实时电价的定价机制,并在定价机制的基础上,设计了基于多目标遗传算法(NSGA-II)的模型求解算法。最后,数值仿真实验表明了两级均衡模型下的实时电价定价机制更能保证电网系统各参与方的收益效用均衡,也使得用户负载更加均衡。     

考虑通关水平的跨境物流服务供应链契约协调机制研究

为实现跨境物流服务供应链完全协调,运用Stackelberg博弈理论,构建由一个跨境物流服务供应商与一个物流服务集成商组成的二级供应链。采用因子分析法测度通关水平,分析通关水平对跨境物流服务供应链最优决策及协调运作的影响,设计可供跨境物流服务供应链完美协调的契约机制。研究表明,考虑通关水平使跨境物流服务供应链成员及供应链整体利润均得到提升;集中决策下跨境物流服务供应链整体利润总是高于分散决策;收益共享契约可实现跨境物流服务供应商及供应链整体决策的帕累托优化,但不能达到供应链的完全协调,而Nash协商改进的二部定价契约模型可实现供应链的完全协调。     

Congestion prevention in broadband wireless access systems: An economic approach

While the demand for mobile broadband wireless services continues to increase, radio resources remain scarce. Even with the substantial increase in the supported bandwidth in the next generation broadband wireless access systems (BWASs), it is expected that these systems will severely suffer from congestion, due to the rapid increase in demand of bandwidth-intensive multimedia services. Without efficient bandwidth management and congestion control schemes, network operators may not be able to meet the increasing demand of users for multimedia services, and hence they may suffer an immense revenue loss. In this paper, we propose an admission-level bandwidth management scheme consisting of call admission control (CAC) and dynamic pricing. The main aim of our proposed scheme is to provide monetary incentives to users to use the wireless resources efficiently and rationally, hence, allowing efficient bandwidth management at the admission level. By dynamically determining the prices of units of bandwidth, the proposed scheme can guarantee that the number of connection requests to the system are less than or equal to certain optimal values computed dynamically, hence, ensuring a congestion-free system. The proposed scheme is general and can accommodate different objective functions for the admission control as well as different pricing functions. Comprehensive simulation results with accurate and inaccurate demand modeling are provided to show the effectiveness and strengths of our proposed approach.     

动态定价策略下的精确库存成本建模与优化

提出一种更接近实际的需求率公式,在式中同时考虑了价格和出厂时间对客户需求率的影响.基于新的需求率公式,建立了动态定价策略下的精确库存持有成本模型和库存商品的利润函数.注意到利润函数的复杂性,使用遗传算法分析了利润函数的性质,得出最优定价时间、定价价格和最大利润的关系,并分析了库存持有成本变化和消费者购买欲望变化对各定价参数的影响.     

User utility discovery for priority-based network resource pricing

While equilibrium analysis has been commonly used for network pricing under the assumption that user utility functions are precisely known, many researchers have criticized the validity of the assumption. In this paper, we propose a solution for bridging the gap between the existing theoretical work on optimal pricing and the unavailability of precise user utility information in real networks. In the proposed method, the service provider obtains increasingly more accurate estimates of user utility functions by iteratively changing the prices of service levels and observing the users’ service-level choices under various prices. Our study’s contribution is twofold. First, we have developed a general principle for estimating user utility functions. Especially, we present the utility estimation for dynamic user population. Second, we have developed a method for setting prices that can optimize the extraction of information about user utility functions. The extensive simulation results demonstrate the effectiveness of our method.     

A software architecture framework for on-line option pricing

The problem of growing computational complexity in the finance industry demands manageable, high-speed and real-time solutions in solving complex mathematical problems such as option pricing. In current option trading scenarios, determining a fair price for options “any time” and “anywhere” has become vital yet difficult computational problem. In this study, we have designed, implemented, and deployed an architecture for pricing options on-line using a hand-held device that is J2ME-based Mobile computing-enabled and is assisted by web mining tools. In our architecture, the client is a MIDP user interface, and the back end servlet runs on a standalone server bound to a known port address. In addition, the server uses table-mining techniques to mine real-time data from reliable web sources upon the mobile trader’s directive. The server performs all computations required for pricing options since mobile devices have limited battery power, low bandwidth, and low memory. We have parallelized and implemented various computational techniques such as binomial lattice and finite differencing. To the best of our knowledge, this is one of the first studies that facilitate the mobile-enabled-trader to compute the price of an option in ubiquitous fashion. This architecture aims at providing the trader with various computational techniques to avail (to provide results from approximate to accurate results) while on-the-go and to make important and effective trading decisions using the results that will ensure higher returns on investments in options.

On splitting-based numerical methods for nonlinear models of European options

We present a large class of nonlinear models of European options as parabolic equations with quasi-linear diffusion and fully nonlinear hyperbolic part. The main idea of the operator splitting method (OSM) is to couple known difference schemes for nonlinear hyperbolic equations with other ones for quasi-linear parabolic equations. We use flux limiter techniques, explicit–implicit difference schemes, Richardson extrapolation, etc. Theoretical analysis for illiquid market model is given. The numerical experiments show second-order accuracy for the numerical solution (the price) and Greeks Delta and Gamma, positivity and monotonicity preserving properties of the approximations.     

智能家居中基于实时电价的家用电器调度方案

针对现有调度方案中不能解决电器使用的不确定性和可再生能源的问题,提出了一种考虑不确定性的基于实时电价的家用电器任务调度方案,该方案采用线性规划的建模方法,以最小费用支出为优化目标,兼顾了PV光伏系统、家用蓄电池以及向电网出售剩余电力情况下的能量流动,用随机规划方法和蒙特卡罗模拟来解决电器使用过程中的不确定性,保证了用户满意度.最后经实验证明,该方案具有重要的实际意义.     

Optimal software pricing in the presence of piracy and word-of-mouth effect

We develop an analytical model that embeds empirical findings on software diffusion to examine optimal pricing strategies for a spreadsheet software product under coalescing effects of piracy and word-of-mouth through its entire life cycle. We find that the demand of the innovators has the most significant impact on the firm's pricing decision. Our research recommends market skimming pricing strategy if innovators' demand is high and the market penetration pricing strategy is preferred otherwise. Surprisingly, the increase of conversion rate of imitators to buyers never significantly alters the pricing strategy pre-determined by the demand of innovators. Most interestingly, the optimal profit from instituting a two prices policy for a software product with five years lifespan outperforms that from a one price policy by no more than 4%, a finding that corroborates the common one price policy observed in reality.