考虑零售商策略性库存的双渠道供应链定价及协调

针对双渠道供应链环境下,零售商将前期采购的部分产品作为策略性库存用于后期销售的情形,建立了制造商为主方的两周期Stackelberg动态博弈模型,分析了零售商持有策略性库存对双渠道供应链成员定价决策的影响。研究结果表明,零售商可以通过持有策略性库存影响制造商的批发价格决策,进而影响传统零售渠道和电子直销渠道之间的零售价格竞争。特别地,当单位库存持有成本较小时,持有策略性库存能够增加零售商利润。同时,为了缓解渠道冲突和双重边际化问题,构造了基于电子渠道直销价格的批发价格折扣和固定转移支付的组合契约。最后,通过数值分析,验证了此种组合契约同时协调零售商策略性库存决策和双渠道供应链成员两周期定价决策的有效性。     

The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR

As a representative emerging financial market, the Chinese stock market is more prone to volatility because of investor sentiment. It is reasonable to use efficient predictive methods to analyze the influence of investor sentiment on stock price forecasting. This paper conducts a comparative study about the predictive performance of artificial neural network, support vector regression (SVR) and autoregressive integrated moving average and selects SVR to study the asymmetry effect of investor sentiment on different industry index predictions. After studying the relevant financial indicators, the results divide the Shenwan first-class industries into two types and show that the industries affected by investor sentiment are composed of young companies with high growth and high operative pressure and there are a great number of investment bubbles in those companies.     

关于影子价格的一个理论误区

对影子价格的理论基础进行了研究,通过对线性规划及其对偶问题经济涵义的分析,揭示了以线性规划中的影子价格为基础定义国民经济评价中的影子价格是一个理论误区,并指出影子价格的理论定义应为帕累托最优状态下的均衡价格.     

考虑价格折扣的两级供应链库存模型

该文把供应链资金流区分为内部资金流和外部资金流,对供应链管理中的库存费用流动过程进行了分析;建立了考虑价格折扣的两级供应链库存数学模型,并运用一种简单而有效的逼近方法求出了模型最优解,确定了供应链中各企业的最佳订货批量;最后用数值实例说明了该方法的有效性。     

基于负荷率差别定价的分时输配电价优化模型

输配电价是电力市场改革的关键,是推进售电市场放开的重要基础.随着输配电价改革不断深入,不同类型的输配电价定价方法亟待研究.本文以大工业用户输配电价为研究对象,首先,引入汉森门槛模型,内生性划分大工业用户的负荷率区间;其次,建立输配电网长期增量成本分摊模型,提出基于负荷率差别的输配电价定价方法,并借鉴分时电价思想,构建基于负荷率差别定价的分时输配电价协调优化模型,设计分电压等级、计及负荷率差别的分时输配电价;最后,以我国中部H省大工业用户为例,验证所提模型可行性.研究结果表明,所提分时输配电价定价方法吸收了负荷率电价和分时电价优点,能够兼顾效率与公平,同时有效调节电力用户需求,实现削峰填谷,一定程度缓解输配电网阻塞问题.     

需求依赖价格和交货期的供应链协调模型

在一个两层供应链系统中,基于对价格和交货期敏感的需求,构建了Stackelberg和收益共享两种决策模型,并给出了最优价格和响应时间的求解过程,通过比较说明收益共享契约有助于提高整个供应链的收益.最后讨论了收益共享契约下渠道收益的分配问题.     

影子价格理论的应用误区分析

资源的影子价格是对资源合理配置的重要依据,是企业调整与优化生产方案的一个重要参考因素,本文运用线性规划有关理论并结合具体实例,探讨了一些关于影子价格理论应用的不正确提法,提出影子价格的新内涵:影子价格是对瓶颈资源的价值估计和对其重要性的认可,并且从中得出一些有益的结论.     

Short‐term salmon price forecasting

This study establishes a benchmark for short‐term salmon price forecasting. The weekly spot price of Norwegian farmed Atlantic salmon is predicted 1–5 weeks ahead using data from 2007 to 2014. Sixteen alternative forecasting methods are considered, ranging from classical time series models to customized machine learning techniques to salmon futures prices. The best predictions are delivered by k‐nearest neighbors method for 1 week ahead; vector error correction model estimated using elastic net regularization for 2 and 3 weeks ahead; and futures prices for 4 and 5 weeks ahead. While the nominal gains in forecast accuracy over a naïve benchmark are small, the economic value of the forecasts is considerable. Using a simple trading strategy for timing the sales based on price forecasts could increase the net profit of a salmon farmer by around 7%.     

An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting

For forecasting nonstationary and nonlinear energy prices time series, a novel adaptive multiscale ensemble learning paradigm incorporating ensemble empirical mode decomposition (EEMD), particle swarm optimization (PSO) and least square support vector machines (LSSVM) with kernel function prototype is developed. Firstly, the extrema symmetry expansion EEMD, which can effectively restrain the mode mixing and end effects, is used to decompose the energy price into simple modes. Secondly, by using the fine‐to‐coarse reconstruction algorithm, the high‐frequency, low‐frequency and trend components are identified. Furthermore, autoregressive integrated moving average is applicable to predicting the high‐frequency components. LSSVM is suitable for forecasting the low‐frequency and trend components. At the same time, a universal kernel function prototype is introduced for making up the drawbacks of single kernel function, which can adaptively select the optimal kernel function type and model parameters according to the specific data using the PSO algorithm. Finally, the prediction results of all the components are aggregated into the forecasting values of energy price time series. The empirical results show that, compared with the popular prediction methods, the proposed method can significantly improve the prediction accuracy of energy prices, with high accuracy both in the level and directional predictions. Copyright © 2016 John Wiley & Sons, Ltd.     

银行卡网络价格结构与刷卡消费组合决策模型

针对银行卡网络价格结构与刷卡消费之间复杂的关联问题,引入双边市场理论和组合决策思想,以实现银行卡网络整体发展为目标,基于Wright等设计的银行卡网络交换费优化模型,建立了银行卡网络价格结构与刷卡消费组合决策模型.通过加入扰动因子、采用双适应值比较和保留边界不可行解改进了粒子群算法,解决了模型的求解难题,为合理制定银行卡网络价格结构提供了一种新方法,同时拓宽了双边市场理论的应用领域,在电子支付管理领域具有广阔的应用前景.