On subset selection from logistic populations

Some distributional results are derived for subset selection from logistic populations, differing only in their location parameter. The probability of correct selection is given. Exact and numerical results concerning the expected subset size are presented.     

我国内部控制强制披露政策的干预效应研究——来自断点回归的经验证据

聚焦我国非国有控股主板上市公司,严格筛选样本,构造精确断点回归模型,专注研究我国全面内部控制评价和披露政策本身的因果干预效应。研究发现,我国的内部控制强制披露政策有正的干预效应,内部控制政策的实施使得公司对资源的利用效率和效果得以提高,合规本身对企业来讲意义重大。建议进一步推进我国上市公司全面内部控制建设和披露工作,将强制实施范围扩展到非主板上市公司,在全部上市公司范围内实施内部控制强制披露和审计。     

Millsian causation

The Directed Acyclic Graph (DAG) theory of causation is based on the assumption that randomly sampling the variables of a causal system will yield a joint probability distribution that satisfies the Markovian condition. It is shown here that this condition can be split into two parts, one of which is named the Millsian condition. It is further shown that the Millsian condition alone implies that causally unrelated sets of variables are conditionally independent given their common causes, very likely a key requirement stated by John Stuart Mill 150 years ago. In Millsian causation, unlike Markovian causation, it is possible for an indirect cause to be associated with its effect even when controlling for the intermediate direct causes. This phenomenon is explained by taking into account the existence of potential causal modulation.     

优化班级奖助学金评选机制的实践和探索——云南农业大学经济管理学院个案分析

近年来,随着各类奖助学金的增加,学生对获得奖助学金尤其是高额奖助学金的期望值大为提高,如何在学生中公正、公平、公开地解决奖助学金评选问题,已成为学生关注的热点,也是摆在学生工作者面前的难题。本文首先介绍了经济管理学院班级奖助学金评选工作的现状,在结合问卷调查分析结果以及总结具体的改进实践工作经验的基础上,提出了优化班级奖助学金评选机制的改进措施。     

效果推理视角下天生国际化企业的战略选择研究

本文运用探索性案例研究方法,基于效果推理理论,结合资源依赖理论与资源基础观相关观点,对两家在非洲手机市场获得非凡业绩的中国天生国际化企业的战略选择与匹配的问题进行研究。研究发现,天生国际化企业的资源基础与市场导向能够影响战略选择决策逻辑。其中,资源约束与先动型市场导向的企业倾向于实施效果逻辑,而资源支持与反应型市场导向的企业倾向于实施因果逻辑。资源基础与市场导向通过效果逻辑与因果逻辑影响天生国际化企业战略选择类型。具体而言,资源约束与先动型市场导向的企业通过效果逻辑选择并实施利基市场战略,资源支持与反应型市场导向的企业通过因果逻辑选择并实施产品标准化战略,且两种战略均能与市场环境形成匹配。     

层次分析法在货物配载问题中的应用

适当的货物配载方式的选择将会大大降低运输费用,从而减少企业的物流成本并提高客户服务水平。论文采用层次分析法科学地分析了车辆选择过程中的各种影响蹲素,并得出它们的重要性排序。对物流企业的配货战略决策提供了方便可行的分析方法,简化了决策过程,具有一定的实用性。     

Bayesian and Frequentist Inference for Ecological Inference: The R×C Case

In this paper we propose Bayesian and frequentist approaches to ecological inference, based on R × C contingency tables, including a covariate. The proposed Bayesian model extends the binomial-beta hierarchical model developed by K ing , R osen and T anner (1999) from the 2×2 case to the R × C case. As in the 2×2 case, the inferential procedure employs Markov chain Monte Carlo (MCMC) methods. As such, the resulting MCMC analysis is rich but computationally intensive. The frequentist approach, based on first moments rather than on the entire likelihood, provides quick inference via nonlinear least-squares, while retaining good frequentist properties. The two approaches are illustrated with simulated data, as well as with real data on voting patterns in Weimar Germany. In the final section of the paper we provide an overview of a range of alternative inferential approaches which trade-off computational intensity for statistical efficiency.     

The number of securities giving the maximum return in the presence of transaction costs

An essential element of any realistic investment portfolio selection is the consideration of transaction costs. Our purpose, in this paper, is to determine the maximum return and the corresponding number of securities to buy giving such return, whenever practical constraints features related to budget, buy-in thresholds, and transaction costs are taken into consideration. Dealing with the portfolio selection and optimization problem in the point of view of individual investors, we will arrive to get an analytic result, leading to a new and simple alternative solution to heuristic algorithms. Moreover, this result can be considered as another approach to integer optimization.     

非结构性模糊优选决策理论在供应商选择中的应用

针对企业在选择供应商中存在的问题,建立了一套比较全面的供应商指标评价体系,并且运用了非结构性模糊优选决策理论来进行供应商选择。最后通过一个算例,说明了该方法的应用。     

输电线路导线截面选择的优化设计

合理选择导线截面可以提高输电线路运行的经济性,促进降损节能。分析了按发热条件、按电压损耗条件、按经济电流密度等三种截面选择方法,并通过实例计算结果对比说明现行的按经济电流密度法选择的截面是偏大的。最后,设计了一种新的截面优化选择方法,实例计算结果验证了该方法是正确有效的。     

A New Decision Making Model for Subcontractor Selection and Its Order Allocation

All experts agree on the importance of subcontracting. The high impact of subcontractors on the construction process means that the selection of subcontractors is a sensitive activity. Previous investigations documented the selection of subcontractors based on criteria but did not consider the number of subcontracted tasks. This paper explores allocating the best portion of tasks to subcontractors while optimizing the risk and cost in the fixed project schedule. The study's main finding demonstrates that subcontractor selection without attention to the order allocation is not a realistic approach; therefore, a hybrid model that applies continuous ant colony and fuzzy set theory is proposed.     

多目标规划在建设项目投资方案比选中的应用

提出了解决建设项目投资方案比选问题的新思路，将其归结为多目标规划问题，分析了目前解决该问题的不足之处，建立了建设项目投资方案比选的多目标规划模型，并通过一具体实例用线性加权和法求得了该问题的有效解。     

基于遍历算法的多式联运运输方式选择

多式联运运输方式的合理选择可以有效地降低物流运输成本、节约物流运输时间,提高企业的物流服务水平。文中以多式联运经营者为决策视角,充分考虑运输距离、运输时间、中转费用及中转时间等诸多成本影响因素,构建多式联运路径优化模型,尝试运用遍历算法寻求货物从起点运至目的地过程中所有的运输方案包括所需运输成本及运输时间,以便为企业决策提供数据支持。     

Which covariates should be controlled in propensity score matching? Evidence from a simulation study

Propensity score matching is a widely‐used method to measure the effect of a treatment in social as well as medicine sciences. An important issue in propensity score matching is how to select conditioning variables in estimation of the propensity scores. It is commonly mentioned that variables which affect both program participation and outcomes are selected. Using Monte Carlo simulation, this paper shows that efficiency in estimation of the Average Treatment Effect on the Treated can be gained if all the available observed variables in the outcome equation are included in the estimation of propensity scores. This result still holds in the presence of non‐sampling errors in the observed control variables.     

Generalized smooth finite mixtures

We propose a general class of models and a unified Bayesian inference methodology for flexibly estimating the density of a response variable conditional on a possibly high-dimensional set of covariates. Our model is a finite mixture of component models with covariate-dependent mixing weights. The component densities can belong to any parametric family, with each model parameter being a deterministic function of covariates through a link function. Our MCMC methodology allows for Bayesian variable selection among the covariates in the mixture components and in the mixing weights. The model’s parameterization and variable selection prior are chosen to prevent overfitting. We use simulated and real data sets to illustrate the methodology.     

A goal-seeking approach to capital budgeting

This paper articulates how a goal-seeking model addresses a variation of the capital-budgeting problem. Focused toward technology modernization in the public sector, this multi-criteria optimization model explicitly considers the diverse functions of the organization. In particular, the synergism amongst the functions is modeled as a multiplicative value function. The model is solved by the “constraint reduced feasible-region method”, resulting in a non-convex mathematical program that produces numerical intricacies. Linearization of the criterion (objective) functions reduces such intricacy. An Army-modernization acquisition-study was used to illustrate the proposed model, showing that its non-inferior solutions are remarkably stable. Comparison is also made with other approaches, typically formulated as goal-setting programs. The model highlights how technology acquisitions are affected as the priorities of each organizational function changes.