Impacts of Power Structure on Supply Chains with Uncertain Demand

In this study, we use a game‐theory‐based framework to model power in a supply chain with random and price‐dependent demand and examine how power structure and demand models (expected demand and demand shock) affect supply chain members' performance. We demonstrate that whether a firm benefits from its power depends on the expected demand model but not on demand shock model. A firm benefits from its power only for linear but not for constant elasticity expected demand. The impact of power structure on supply chain efficiency depends on the models of both expected demand and demand shock. With additive shock, supply chain efficiency is highest (lowest) when neither firm dominates for linear (constant elasticity) expected demand. With multiplicative shock, the supply chain efficiency is highest with a power retailer (manufacturer) for linear (constant elasticity) expected demand. The manufacturer always benefits from a reduction in demand uncertainty. However, the retailer loses (benefits) from demand uncertainty reduction for linear (constant elasticity) expected demand. With a power retailer, the retail price is always on the higher end for linear expected demand, and the customer service level is the lowest for constant elasticity expected demand. Consequently, consumers do not necessarily benefit from a power retailer.     

非奇次空间动态极值估计的模型与应用

传统EVT方法是从静态的角度,研究超额数据的性质。然而,它没有同时考虑极端数据发生的时间所隐含的充分信息。本文首次在国内提出了非奇次空间动态极值理论(ITD-EVT)的概念,克服了EVT的上述缺陷,在极端数据的基础上考虑了时间因素,并引入多个解释变量,使极值分布的是三个参数为时变的,用二维泊松分布过程建立动态空间模型,是文中一大特色。把TD-EVT运用于极端情况下风险值的估计中,对金融风险管理、资产定价等问题有较大的理论和现实意义。     

航空客运平行航班动态定价模型

航空公司在同一航线上,提供多个不同时刻起飞的航班,我们称这样的航班为平行航班。本文应用随机控制理论建立了两个平行航班动态定价连续时间数学模型,证明了最优策略的性质,得到了最优动态定价综合策略,并给出了最优控制的时间阈值点。数值实验结果表明,这种时间阈值点的综合控制策略不仅易于实施,而且,应用该优化模型得到的总收入比两个平行航班独立决策时得到的总收入大。     

Contingency Strategies in Managing Supply Systems with Uncertain Lead‐Times

The globalization of markets and geographic dispersion of production facilities, combined with a heavy outsourcing of supply chain processes, have substantially increased the exposure of supply chains to supply lead‐times of long and uncertain nature. In this paper, we study the potential use of two contingency strategies on top of the conventionally used time buffer—statically planned safety lead‐time (SL)—approach to deal with the lead‐time uncertainty. These are (1) the ex‐ante planning for disruption safety stock (DSS) to be released when a “disruption” (in this case, late delivery of the order) occurs; and (2) the ex‐post dynamic emergency response (DER), which dynamically decides on the timing and size of an emergency order to be placed. Our work elaborates on the optimal parameter setting for these strategies, compares their added values when used to complement the traditional SL approach, and examines how the use of the contingency strategies affects the SL and corresponding cycle length of a periodic review system. Our research finds that: (1) the above contingency strategies reduce the reliance on the SL and are cost effective when the coefficient of variation (CV) of the uncertain lead‐time is high; (2) it is important to re‐optimize the SL to account for the contingency plans; and (3) re‐optimization of the cycle length to account for the presence of the contingency responses, as opposed to using an EOQ‐determined cycle length, does not significantly improve the cost performance. However, such re‐optimization does well in the SL approach when the CV of the uncertain lead‐time is high.     

A Choice‐Based Dynamic Programming Approach for Setting Opaque Prices

Opaque pricing is a form of pricing where certain characteristics of the product or service are hidden from the consumer until after purchase. In essence, opaque selling transforms a differentiated good into a commodity. Opaque pricing has become popular in service pricing as it allows firms to sell their differentiated product at higher prices to regular brand loyal customers while simultaneously selling to non‐brand loyal customers at discounted prices. We use a nested logit model in combination with logistic regression and dynamic programming to illustrate how a service firm can optimally set prices on an opaque sales channel. The choice model allows the characterization of consumer trade‐offs when purchasing opaque products while the dynamic programming approach allows the characterization of the optimal pricing policy as a function of inventory and time remaining. We compare optimal prices and expected revenues when dynamic pricing is restricted to daily price changes. We provide an illustrative example using data from an opaque selling mechanism ( Hotwire.com ) and a Washington DC‐based hotel.     

Hedonic住宅特征价格模型的BP神经网络方法

房地产在金融市场中占有举足轻重的地位,其价格变化对整个金融市场有着显著的影响。采用特征价格模型,对美国一线城市2007年6月及2008年的房价进行了相关定价研究。对传统特征价格模型的属性因子进行了扩充,加入房产周边犯罪率因子进行模拟;在数值方法计算方面,首先对数据进行了Box-cox变换,分别采用BP神经网络及传统的最小二乘法进行数值模拟分析,结果表明,房价随犯罪事件类型及发生距离房地产的远近有-5.78%～2.08%的变化;在2008年与2007年6月的不同时段内,犯罪率的变化对房价的影响有所不同。BP神经网络模拟的价格与实际交易价格曲线比传统最小二乘模拟的价格曲线精度高出5.74个百分点。     

基于多分类器动态选择与成本敏感优化集成的电信客户流失预测研究

针对不同样本在特征空间中具有不同的区域特性和不同分类算法之间的预测互补性,在电信客户流失预测理论基础上,融合多分类器动态集成理论和成本敏感学习理论,建立了电信客户流失多分类器集成预测的利润函数,并提出了一类新的基于多分类器动态选择与成本敏感优化集成的电信客户流失预测模型.首先使用K均值聚类法聚类训练样本成多个分区;接着使用NaiveBayes算法、多层感知机算法和J48算法在各分区样本上构建客户流失预测子分类器;最后使用改进人工鱼群算法分别对各分区的子分类器进行成本敏感优化集成.实验结果表明,所提出的基于多分类器动态选择与成本敏感优化集成模型的分类性能不仅优于由训练集全体样本所构建的3个单模型,也优于基于改进人工鱼群算法优化集成这3个单模型而得到的集成模型.     

Efficient Semiparametric Estimation of the Fama–French Model and Extensions

This paper develops a new estimation procedure for characteristic‐based factor models of stock returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time‐varying weights and a set of univariate nonparametric functions relating security characteristic to the associated factor betas. We use a time‐series and cross‐sectional pooled weighted additive nonparametric regression methodology to simultaneously estimate the factor returns and characteristic‐beta functions. By avoiding the curse of dimensionality, our methodology allows for a larger number of factors than existing semiparametric methods. We apply the technique to the three‐factor Fama–French model, Carhart's four‐factor extension of it that adds a momentum factor, and a five‐factor extension that adds an own‐volatility factor. We find that momentum and own‐volatility factors are at least as important, if not more important, than size and value in explaining equity return comovements. We test the multifactor beta pricing theory against a general alternative using a new nonparametric test.     

Contract Pricing in Consumer Credit Markets

We analyze subprime consumer lending and the role played by down payment requirements in screening high‐risk borrowers and limiting defaults. To do this, we develop an empirical model of the demand for financed purchases that incorporates both adverse selection and repayment incentives. We estimate the model using detailed transaction‐level data on subprime auto loans. We show how different elements of loan contracts affect the quality of the borrower pool and subsequent loan performance. We also evaluate the returns to credit scoring that allows sellers to customize financing terms to individual applicants. Our approach shows how standard econometric tools for analyzing demand and supply under imperfect competition extend to settings in which firms care about the identity of their customers and their postpurchase behavior.     

论我国区域经济增长机制

区域经济增长机制是区域经济发展的源泉,包括动力机制、传递机制和协调机制。区域经济增长是区域经济发展的源泉,是保证区域经济持续、稳定和协调发展的重要基础。要实现区域经济高速增长,必须建立运行良好、系统完整的区域经济增长机制。