“小舢舨”怎样迎战“航空母舰”——中小流通企业参与国际竞争面临的形势与对策

加入WTO后,国际大型流通企业以“航母”的形式冲击我国中小型流通企业这类型的“小舢般”,分析了国际“航母”成功的奥秘以及本国中小流通企业与国际商业航母的差距,提出了“小舢般”面临的严峻形势和迎战“航母”的基本策略。     

论国有企业的效率边界

确定国有企业效率边界的三种观点即计划经济观点、产权理论观点、“进退”观点都存在偏颇 ,应当通过国有企业内部交易费用和市场交易费用的比较来确定国有企业的效率边界。应用扩展型交易费用理论模型确定国有企业的效率边界综合性强 ,能进行定量分析 ,可避免主观判断 ,更为合理、科学 ,可为国有企业效率边界的战略性调整提供了一般性的评价标准     

碳配额交易体系下闭环供应链网络的生产与碳交易策略研究

人类的生产和消费等活动引起温室气体增加,已造成气候恶化等环境问题,在生产、消费等相关活动中减少碳排放量是业界、学界和政府等相关主体的普遍共识。针对高排放和低排放两类制造商、多个需求市场和一个碳交易中心组成的闭环供应链网络,在碳配额交易体系下,研究了企业的生产与碳减排策略。两类制造商基于政府分配的碳配额在碳交易中心进行碳排放权的买卖形成一个碳交易子网,同时,产品的买卖形成一个产品交易子网。针对所有企业成员的利润最大化目标,利用变分不等式把含约束的利润最大化非线性规划问题转化为变分不等式问题,并利用互补关系与变分不等式的等价性把需求市场消费者的购买行为转化为变分不等式,得到闭环供应链网络系统中产品交易量、生产量和碳交易策略满足的均衡条件,进一步获得闭环供应链网络达到Nash均衡状态时的条件。利用投影收缩算法求解所建模型,并给出了相关数值算例,通过比较静态分析得到了管理学启示。结果表明：供应链网络中存在企业利润目标与政府减排目标一致的情况,两类制造商间的碳交易额多数情况下是一致的,政府对不同类型制造商应设置不同的回收率。本研究可为政府和企业减排目标的实现提供指导和决策参考。     

考虑消费者低碳偏好的供应链减排微分博弈模型研究

针对由一个供应商和一个制造商构成的两级供应链,考虑消费者的低碳偏好和碳交易政策,建立分散决策和集中决策两种情形下的微分博弈模型解决供应链动态优化问题,比较两种情形下的最优均衡反馈策略、减排量的最优轨迹及最优利润,提出减排策略。通过数值仿真,进一步验证了命题的有效性;通过对消费者低碳偏好及碳交易价格进行灵敏度分析发现：随着低碳偏好的增加,供应商和制造商的减排量和供应链系统的利润均增加,并且政府在规划期内应及时调整碳交易政策,达到激励企业减排的效果。     

碳交易政策下节能服务公司参与供应链合作减排策略研究

在碳交易政策背景下,采用Stackelberg博弈模型来探讨节能服务公司参与的供应链合作减排策略问题。通过建立供应链上下游企业分散决策、集中决策、与节能服务公司合作三种模式下的博弈模型,对其利润和减排效果进行比较分析,得到了节能服务公司参与减排的条件和利润分享比例。研究表明：当供应链减排投资系数与节能服务公司减排投资系数的比值达到一定阈值时,供应链的最优选择是与节能服务公司合作;三种模式下供应链的总利润和减排率排序均为：与节能服务公司合作时最高,其次是集中决策,最后是分散决策。与节能服务公司合作的情况下,供应链减排率与节能效益分享比例呈现反向变动关系。最后通过算例对以上结果进行了验证和分析。     

恒生指数日收益率与成交量及未平仓和约关系的实证研究

本文对恒生指数当月期货日交易数据进行实证检验,发现恒指期货日收益率绝对值与成交量、未平仓和约之间呈现正相关关系;日收益率与成交量、未平仓和约存在不对称关系及滞后关系。同时本文以三者之间的滞后关系为基础,提出了以三者历史数据相互关系为基础的收益率预测经验公式,表明通过对不同交易动机产生的成交量及未平仓和约,以及三者之间关系的研究,可以获得有关未来收益率变化的信息。     

涨跌幅限制与股票价格行为分析

对于股票在达到涨跌幅限制后价格如何变化的解释有两种假设:信息假设和过度反应 假设. 通过对1997 年到2000 年上海证券交易所股票在达到涨跌幅限制后隔夜期间与交易期 间的非正常收益进行检验,以揭示达到涨跌幅限制后股票的价格行为. 结果表明在达到涨跌幅 限制后的隔夜期间股票价格存在价格持续现象,而在交易期间存在价格反转现象. 这个结果一 方面说明了沪市存在着过度反应,另一方面也说明了上海证券交易所10 %的涨跌幅限制在限 制噪声交易者的过度反应有一定的作用.     

COMBINING MULTIPLE MARKERS FOR MULTI‐CATEGORY CLASSIFICATION: AN ROC SURFACE APPROACH

The Receiver Operating Characteristic (ROC) curve and the Area Under the ROC Curve (AUC) are effective statistical tools for evaluating the accuracy of diagnostic tests for binary‐class medical data. However, many real‐world biomedical problems involve more than two categories. The Volume Under the ROC Surface (VUS) and Hypervolume Under the ROC Manifold (HUM) measures are extensions for the AUC under three‐class and multiple‐class models. Inference methods for such measures have been proposed recently. We develop a method of constructing a linear combination of markers for which the VUS or HUM of the combined markers is maximized. Asymptotic validity of the estimator is justified by extending the results for maximum rank correlation estimation that are well known in econometrics. A bootstrap resampling method is then applied to estimate the sampling variability. Simulations and examples are provided to demonstrate our methods.     

Information in Securities Markets: Kyle Meets Glosten and Milgrom

This paper analyzes models of securities markets with a single strategic informed trader and competitive market makers. In one version, uninformed trades arrive as a Brownian motion and market makers see only the order imbalance, as in Kyle (1985). In the other version, uninformed trades arrive as a Poisson process and market makers see individual trades. This is similar to the Glosten–Milgrom (1985) model, except that we allow the informed trader to optimize his times of trading. We show there is an equilibrium in the Glosten–Milgrom‐type model in which the informed trader plays a mixed strategy (a point process with stochastic intensity). In this equilibrium, informed and uninformed trades arrive probabilistically, as Glosten and Milgrom assume. We study a sequence of such markets in which uninformed trades become smaller and arrive more frequently, approximating a Brownian motion. We show that the equilibria of the Glosten–Milgrom model converge to the equilibrium of the Kyle model.     

How does information sharing affect first-tier suppliers’ flexibility? Evidence from the automotive industry in Sweden

This study addresses the critical research issue of how supplier delivery performance can be enhanced by integrating information sharing into volume and delivery flexibility. This study developed a research model to relate information sharing on demand forecasts and inventory data between original equipment manufacturers (OEMs) and first-tier suppliers. Based on a sample of 52 suppliers from automotive industry in Sweden, partial least squares structural equations modelling (PLS-SEM) was used to assess the model. The results confirm that sharing demand forecasts is a key enabler of supplier volume and delivery flexibility while sharing inventory data is not. The study contributes to enlarging the knowledge about supply chain management from the suppliers’ perspective. It also contributes to knowledge by validating the conceptual model and operationalisation of constructs. The study also has practical contribution in which management should focus on improving communication and collaboration practices with OEMs for effective sharing of demand forecasts.