湿地公路与农田水利建设关系分析

湿地因其特殊的自然状况，公路交通建设投资大，成绩显著，但农田水利设施损失严重，正确处理好湿地公路建设与农田水利建设的矛盾，有利于发展交通建设和解决三农问题。文章从公路交通与农田水利现状分析出发，试图找到湿地交通发展与农田水利建设的平衡点，形成公路建设，农田水利建设共同发展的良好循环。     

Hybrid governance and governance performance in industrial purchasing relationships

Hybrid governance arrangements (e.g. joint action, long-term contracting and vertical coordination) feature regularly as an effective response to inter-firm dependence in the literature of business-to-business relationships. However, current empirical work has paid little attention to whether such governance arrangements really do improve governance efficacy and reduce transaction costs. The present study focuses on the governance efficacy of vertical coordination in industrial business-to-business relationships. Building on transaction costs arguments, the author examines whether vertical coordination is an effective means for adapting to inter-firm dependence, realized as the substantial employment of specific assets.Empirical findings from a survey of 170 industrial supplier–buyer relationships demonstrate that when asset specificity reaches a certain level, greater vertical coordination reduces ex post transaction costs significantly. On the other hand, this efficacy pattern is modest or non-existent in relationships with low asset specificity.The research findings support the basic TCA assumption that the performance of hybrid governance arrangements is highly dependent on a situation of substantial inter-firm dependence with subsequent small-number conditions.     

基于主成份分析的江苏省各市区经济发展潜力评价

本文选取15项适当的主要经济指标构建了评价指标体系,基于主成分分析法和SPSS12.0数据处理,对江苏省13个市(区)进行了定量分析。根据各地区的综合得分以及排名评价了江苏各市区的经济发展水平同时指出了各地区社会经济发展不平衡的原因,提出相应的对策,为挖掘江苏社会经济发展的潜力提供了一定的借鉴作用。     

On the Use of Value Efficiency Analysis and Some Further Developments

The purpose of this paper is to discuss the use of Value Efficiency Analysis (VEA) in efficiency evaluation when preference information is taken into account. Value efficiency analysis is an approach, which applies the ideas developed for Multiple Objective Linear Programming (MOLP) to Data Envelopment Analysis (DEA). Preference information is given through the desirable structure of input- and output-values. The same values can be used for all units under evaluation or the values can be specific for each unit. A decision-maker can specify the input- and output-values subjectively without any support or (s)he can use a multiple criteria support system to assist him/her to find those values on the efficient frontier. The underlying assumption is that the most preferred values maximize the decision-maker's implicitly known value function in a production possibility set or a subset. The purpose of value efficiency analysis is to estimate a need to increase outputs and/or decrease inputs for reaching the indifference contour of the value function at the optimum. In this paper, we briefly review the main ideas in value efficiency analysis and discuss practical aspects related to the use of value efficiency analysis. We also consider some extensions.     

Applying efficiency measurement techniques to the measurement of productivity change

Deterministic frontier analysis (DFA), stochastic frontier analysis (SFA), and data envelopment analysis (DEA) are alternative analytical techniques designed to measure the efficiency of producers. All three techniques were originally developed within a cross-sectional context, in which the objective is to compare the efficiencies of producers. More recently all three techniques have been extended for use in a panel data context. In the latter context it is possible to measure productivity change, and to decompose measured productivity change into its sources, one of which is efficiency change. However when efficiency measurement techniques, particularly SFA, have been applied to panel data, it has infrequently been made clear what the objective of the analysis is: the measurement of efficiency, which may vary through time as well as across producers, or the measurement and decomposition of productivity change. In this paper I explore the use of each technique in a panel data context. I find DFA and DEA to have achieved a more satisfactory reorientation toward productivity measurement than SFA has.     

Why I am a Psychology Major: An Empirical Analysis of Student Motivations

The underlying “architecture of the decision to pursue a degree in psychology was quantified using the Method of Sorting technique to identifying the critical issues necessary to make this choice. Multidimentsional scaling procedures were employed to construct a three-dimensional map representing the relationships between reasons for selecting psychology as a major. Freshman and senior psychology majors (N = 165) from a regional university and a large research-based institution rated the relative importance of items in their decision-making process. Hierarchical clustering procedures revealed seven different groups of students. Although significant differences associated with class standing were not found, institutional affiliation did influence cluster composition. Reflecting local emphases, students at the regional institution had a greater interest in Counseling Psychology, whereas those at the research-based school focused on Clinical Psychology. This semantic map and the associated item clusters arising from psychology student data provides an empirical basis for, amongst other things, course selection, faculty-initiated program design or revision, strategic niche marketing, and student retention.     

基于多元统计分析的封闭式基金业绩评价

本文引入在险价值(VaR)和基金折价率指标,利用因子分析和聚类分析方法对基金业绩进行综合评价。实证分析发现我国封闭式基金收益率优于市场收益率,少数几只基金业绩相对突出,实现低风险高收益的目标。但封闭式基金折价幅度较大,基金内部收益水平与外部评价状况背离,反映了市场投资者的投资非理性现象。     

微观经济杠杆值域的聚类分析——以我国能源类上市公司2003年数据为例

本文提出一个研究微观经济杠杆值域的新思路,按照“竞争性工商企业评价指标体系”中所确定的财务指标对2003年我国能源类19家上市公司进行聚类分析,把样本按财务指标值相近程度分为3类,然后对这3类公司的微观经济杠杆值域进行分析解释,得出2003年我国能源类上市公司按“竞争性工商企业评价指标体系”的财务指标分类后的微观经济杠杆值域。     

基于精细供应链战略的精细物流模式

从供应链角度出发，阐述了精细物流的内涵，构造了一种新的精细物流结构模式以实现精细供应链目标并总结了该模式的特征，最后又提出了精细物流的两种实施策略及关键步骤。     

A sequential model for cracking down on street markets for illicit drugs

This paper develops a sequential decision-making model for assisting law enforcement officials in allocating resources during a crackdown operation on illicit drug markets. The sequential crackdown model (SCM) considers a probabilistic framework, where the probability of incarceration of a dealer and the probability of dealing are modeled as a function of the size of a drug market, crackdown enforcement level, drug dealer's financial hardship, and other market characteristics.The model was developed and tested in consultation with enforcement officials from Philadelphia, PA and Camden, NJ. We present a detailed, step-by-step implementation scheme for updating parameters on each day of the crackdown. Parameter estimation along with examples of model usage is provided. Through these examples, we illustrate how the SCM could be helpful in understanding the response of illicit drug markets to various enforcement strategies. We further show conditions under which an alternating crackdown policy (referred to as a crackdown-backoff) or a consistent use of maximum possible enforcement would be optimal strategies for managing a drug crackdown operation. Within the context of the model and parameter estimates, we show that a much quicker and less costly collapse could be implemented if the available enforcement resources are increased. Finally, the model provides possible conditions under which a crackdown operation would be unsuccessful in eliminating a drug market.