基于新消费者行为理论的供应链应急预案研究

本文利用应急管理中的分级思想和新消费者行为理论,提出了应急事件下,估计供应链损失的新方法.通过该方法能够比较容易地算出供应链应急损失值,然后把该值与应急预案的阀值进行比较,从而确定供应链应急预案的启动时机.     

模糊环境下考虑缺货和延期支付的Stackelberg均衡策略

在具有价格弹性需求的两层供应链系统中,考虑到价格弹性指数的模糊性和供应链延期支付策略,建立了含缺货的制造商-零售商协调模型.运用符号距离反模糊化方法将其转化为确定模型.基于遗传算法,设计了其求解方法,获得了制造商最优信用期和零售商最优零售价.数值结果表明:模糊环境下的延期支付策略降低了产品的市场零售价,同时增加了供应链中各成员的利润,因此实现了供应链协调.进一步分析显示当模糊价格弹性指数的上(下)界变化反映出的不确定性减弱时,制造商提供更长的信用期,且制造商和零售商的利润均增加(减少).     

基于供应链金融的随机需求条件下的订货策略

本文将供应链金融中的融资问题融入到允许延迟支付的报童模型中,同时考虑了订货商的销售情况对偿还能力的影响,融资利息、销售收入利息以及支付信用期等现金管理要素,建立起订货商在连续随机需求条件下的库存管理模型,通过对模型的求解与灵敏度分析,对供应链金融模式下订货商的订货策略进行了深入探讨,得出了一系列有益的结论。所建立的模型同时为中小销售型企业提供一种新的资金获取以及确定订货策略的方法。     

委托-代理下人力资源有效激励模式与退出机制设计

在假定产出可以观测的条件下,首先比较员工素质信息是完全信息和非对称信息下不同产出差异,再讨论基于利润分享激励模式下不同激励效应,最后设计出根据员工自愿选择策略而实现的企业存优弃劣的有效退出机制.     

在找寻中孤独，在撕裂中前行——《爱历元年》的女性悲歌

《爱历元年》的女性悲歌表明王跃文对爱情婚姻所持的依然是男权中心的理想主义态度。《爱历元年》揭示了秩序化的社会道德和理性的婚姻形式下,女性个体存在的孤独本质和对情爱的强烈渴望;展示了在激情的眩惑与理性的撕裂下,现代女性无法逾越的精神困惑和生存无奈。这种理性的社会秩序和个人的情感欲望之间的冲突,是对现代人生命自由和人类生存困境的探索与超越,它以具有鲜活生命体验的欲望书写和属己的生命经纬激发着人们的体悟和反思。     

The Effect of Timing on Jump Bidding in Ascending Auctions

We investigate the role of timing in ascending auctions under the premise that time is a valuable resource. Traditional models of the English auction ignore timing issues by assuming that the auction occurs instantaneously. However, when auctions are slow, as Internet auctions used for procurement often are, there are significant opportunity or monitoring costs to bidders, and the choice of the size of the jump bid becomes a strategic decision. We study the choice in the experimental laboratory by systematically varying the opportunity costs associated with fast bidding. When time is more valuable bidders respond by choosing larger jump bids. Surprisingly, the economic performance of the auction is not significantly affected. We develop a simple model of ascending auctions with impatient bidders that provides insights into the effect jump bids have on auction performance.     

Models of Neurotoxicity: Extrapolation of Benchmark Doses in Vitro

In risk assessment, no observed exposure level (NOAEL) and benchmark dose (BMD) are usually derived either from epidemiological studies in humans or from animal experiments. In many in vitro studies, concentration-effect/response curves have been analyzed using different mathematical models finalized to the identification of EC50. In the present article, we propose a model to fit dose-response curves in vitro. The BMD approach has been used to compare the cell viability (MIT assay) of different rat (C6 and PC12, glial and neuronal, respectively) and human cell lines (D384 and SK-N-MC, glial and neuronal, respectively) after 24-hour exposure to the following neurotoxic substances: manganese chloride (MnCl2), methyl-mercury (Me-Hg), and the enantiomers of styrene oxide (SO). For all rat and human cell lines, the potency of the examined compounds was: MnCl2 < S-SO < R-SO < Me-Hg. A preliminary comparison with in vivo toxicity data for these substances gave rise to consistent results. Whereas a reasonable agreement between in vitro and in vivo data has been found for Mn and styrene oxide, a wide scatter of LOAEL has been reported for Me-Hg and these appear to be either much higher or lower than the BMD for the MIT assay we observed in vitro.     

网络时代的适时财务监控与公司治理

网络技术应用的普及使传统财务监控的变革已成为公司治理和财务管理的热点话题,本文简要揭示新概念——适时财务监控与公司治理的关系,剖析了公司不同管理层次的适时财务监控的实时需求,从公司治理的基本需要对公司价值流再造、公司信息系统变革和适时财务监控机制重构等三个方面进行了初步研究,为网络适时财务监控在公司治理实务中的应用提供了一个基本框架。     

A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter

In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^d_r, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^d_r, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^d_r. These results show that the bias of ^d_r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^d_r attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.