CCM在公路工程项目进度管理中的实证分析

本文论述了CCM技术以及项目进度延迟的原因。并采用基于TOC的CCM技术,对公路工程 项目进度管理进行了实证分析。通过分析结果与传统方法的比较,论证CCM技术在公路工程项目进度管 理中的实用价值。     

基于Markov链的物流园区需求灰色预测模型改进

物流因区是一项大型基础设施投资项目，在规划与设计上需要有一定的超前意识，而需求预测则是园区规划超前意识的重要依据。目前。国内外对物流园区需求预测方法的研究和实践基本上还处于发展阶段．至今尚未形成完整科学、操作性强的方法体系，现有的需求预测大体上是借鉴史通运输规划的模型．进行研究的过程中灰色模型预测有局限性。其预测结果与真实值之间存在一定误差，因而可以考虑利用Markov链提出改进方案。     

基于顾客满意度的绿色采购决策研究

从提高顾客满意度(CS)的视角,研究了生态供应链(ESC)环境下绿色采购决策优化问题。利用两状态、时间离散的Markov链描述了CS的动态转移过程,以赋值形式引入利润变量,建立了ESC绿色采购决策的随机优化模型,体现了顾客导向的思想;并且给出了应用算法释例。     

Monitoring recessions: A Bayesian sequential quickest detection method

Monitoring business cycles faces two potentially conflicting objectives: accuracy and timeliness. To strike a balance between these dual objectives, we propose a Bayesian sequential quickest detection method to identify turning points in real time with a sequential stopping time as a solution. Using four monthly indexes of real economic activity in the United States, we evaluated the method’s real-time ability to date the past five recessions. The proposed method identified similar turning-point dates as the National Bureau of Economic Research (NBER), with no false alarms, but on average, it dated peaks four months faster and troughs 10 months faster relative to the NBER announcement. The timeliness of our method is also notable compared to the dynamic factor Markov-switching model: the average lead time was about five months when dating peaks and two months when dating troughs.     

On exact D-optimal designs with 2 two-level factors and n autocorrelated observations

In this paper we consider the exact D-optimal designs for estimation of the unknown parameters in the two factors, each at only two-level, main effects model with autocorrelated errors. The vector of the n random errors in the observed responses is assumed to follow a first-order autoregressive model (AR(1)). The exact D-optimal designs seek the optimal combinations of the design levels as well as the optimal run orders, so that the determinant of the information matrix of BLUEs for the unknown parameters is maximized. Bora-Senta and Moyssiadis (1999) gave some conjectures about the exact D-optimal designs based on their experience of several exhaustive searches. In this paper their conjectures are partially proved to be true.Received: January 2003 / Accepted: October 2003Partially supported by the National Science Council of Taiwan, R.O.C. under grant NSC 91-2115-M-008-013.Supported in part by the National Science Council of Taiwan, R.O.C. under grant NSC 89-2118-M-110-003.     

两阶段供应链企业间合作博弈分析

合作是供应链管理的核心。文中以一个供应商和一个零售商组成的供应链系统为背景,研究了两阶段供应链,运用合作博弈理论进行了分析,强调建立伙伴关系,实现"双赢"。     

动态比较优势与中国目标产业选择实证分析

通过动态比较优势的理论模型，可揭示后进国家政策介入的必要性和有效性；采用独立随机增量过程马尔可夫链方法，可对中国制造业动态比较优势进行经验验证和预测。结果显示，弱比较劣势产业是目标产业。该些产业的优势状态保持不变或上移的概率高达80％以上，表明它们具有较大的潜在比较优势。     

A Closer Look at the Relation between GARCH and Stochastic Autoregressive Volatility

We show that, for three common SARV models, fitting a minimummean square linear filter is equivalent to fitting a GARCH model.This suggests that GARCH models may be useful for filtering,forecasting, and parameter estimation in stochastic volatilitysettings. To investigate, we use simulations to evaluate howthe three SARV models and their associated GARCH filters performunder controlled conditions and then we use daily currency andequity index returns to evaluate how the models perform in arisk management application. Although the GARCH models produceless precise forecasts than the SARV models in the simulations,it is not clear that the performance differences are large enoughto be economically meaningful. Consistent with this view, wefind that the GARCH and SARV models perform comparably in testsof conditional value-at-risk estimates using the actual data.     

Moments of renewal shot-noise processes and their applications

In this paper, we study the family of renewal shot-noise processes. The Feynmann–Kac formula is obtained based on the piecewise deterministic Markov process theory and the martingale methodology. We then derive the Laplace transforms of the conditional moments and asymptotic moments of the processes. In general, by inverting the Laplace transforms, the asymptotic moments and the first conditional moments can be derived explicitly; however, other conditional moments may need to be estimated numerically. As an example, we develop a very efficient and general algorithm of Monte Carlo exact simulation for estimating the second conditional moments. The results can be then easily transformed to the counterparts of discounted aggregate claims for insurance applications, and we apply the first two conditional moments for the actuarial net premium calculation. Similarly, they can also be applied to credit risk and reliability modelling. Numerical examples with four distribution choices for interarrival times are provided to illustrate how the models can be implemented.