企业社会责任信息披露影响因素研究综述

近年来,企业社会责任信息披露影响因素已成为企业社会责任研究的重要组成部分。国内外学者在公司特征和公司治理等方面对社会责任信息披露影响因素的研究已取得丰富的研究成果。本文主要从公司特征和公司治理两个方面对国内外的研究进行述评,并在此基础上对进一步研究提出了建议。     

盈余管理实证研究综述

首先以国外研究的历程为主线提炼出盈余管理研究的总体思路;其次,从审计、公司治理两个角度详细介绍了国内外盈余管理实证研究的主要成果,由于盈余管理程度的大小通常用总应计项目、操纵性应计来反映,故对国内外在应计项目方面的研究进行了对比;最后,在总结国内盈余管理研究差距和不足的基础上,提出了进一步的研究方向和设想.     

金融发展与贫困减缓关系的文献综述

本文主要从金融角度研究贫困,发现金融发展主要通过经济增长、金融服务和金融危机这三个渠道影响贫困减缓,为此将国内外文献进行综述。     

实践回应中的领导者价值观研究百年演变

结合管理实践,从领导理论发展的主体脉络、概念化层次视角下的领导2个方面,对百年来国内外领导者价值观研究演变过程中的主要成果进行了归纳和总结,并指出了领导者价值观研究对实践的指导意义,最后提出了领导者价值观研究的未来展望。     

领导力来源的主要因素研究

目前,国内外有很多学者对领导力的来源进行了深入的研究,但不同的学者对领导力的来源因素有不同的看法,导致无法得出一个普遍认可的关于领导力的定义。因此,对领导力主要来源因素的研究就显得尤为重要。在深入分析国内外学者对领导力来源因素研究成果的基础上,笔者试提出自己的观点和见解,以供参考。一、领导力来源的四个主要因素在借鉴前人研究成果的基础上,笔者结合问卷调查     

宏观经济、融资约束与企业资本结构研究现状综述

本文对宏观经济和融资约束与企业资本结构的国内外研究现状进行了综述,总结了国内外关于宏观经济、融资约束与企业资本结构调整以及其选择两个方面的研究现状。对比国内外学者的研究,探讨了国内研究仍然存在的不足。     

基于层次分析法的汽车供应商评价模型

本文通过对汽车供应商影响因素的研究,结合国内外对供应商评价指标的文献研究,整理出了本文主要从质量管理能力,产品服务竞争力,设计开发能力,生产能力,财务能力,综合能力6个主要指标,以及18个次要指标,以此作为多方位,多角度,多层次评价供应商的基础,通过层次分析法结合实例,进行定量计算和定性的分析,对潜在供应商选择进行评价,验证了指标的合理性和可行性。     

生猪产业风险金融综合治理研究综述

目前,生猪市场价格波动剧烈,产业风险亟待金融治理。国内研究动态主要集中在生猪产业金融化治理、生猪产业投融资、生猪电子交易平台、生猪保险、生猪期权期货等五个方面,国外研究动态则主要集中在三个方面。本文最后结合国内外动态对构建生猪产业金融风险治理体系的必要性和可行性进行评述。     

品牌基础问题研究评述

品牌问题一直是国际营销学术界的研究热点领域。对文献总结发现,在品牌基础问题的理论和方法研究中,主要集中在品牌认识、品牌选择和品牌发展3个方面。国内外研究者从不同的理论出发运用不同方法解释了品牌的认识、选择和发展,主要是分别从消费者和企业2个角度来分析和探讨品牌问题,但是缺乏二者之间互动关系的研究,使得品牌基础问题的研究不能为企业品牌创建、品牌战略和品牌延伸提供合理建议。     

集体智慧的内涵及研究综述

基于对集体智慧的内涵、组成及形成过程的探讨,综述了国内外关于集体智慧的优越性、影响因素及应用研究,构建了集体智慧的理论研究框架。该框架从个体智慧贡献、集体智慧形成及集体智慧平台发展3个方面梳理了集体智慧发展的影响因素,并整合了集体智慧的主要应用领域。     

通货膨胀下的联合库存选址模型研究

研究了通货膨胀对涉及一个供应商、多个候选配送中心和零售商的三级分销网络设计的影响.不同于传统的联合库存选址模型,所研究的模型考虑了整个系统的相关成本的时间价值,其目标是使在一定的通货膨胀率下总的选址、运输和库存成本之和的现值最小.为此,建立了一个非线性的整数规划模型,该模型为无容量约束问题的扩展模型,属于NP-hard问题.提出了3种基于不同编码形式的遗传算法用于求解该模型,并通过不同规模的算例对3种算法进行了有效性的分析和对比.最后,通过对各算例的计算结果的分析,发现随着通货膨胀率的增长,为了使这个分析网络的总成本现值最小,需要增加建立的DC的数量.     

Dynamic scheduling of manufacturing job shops using extreme value theory

Most job shop scheduling approaches reported in the literature assume that the scheduling problem is static (i.e. job arrivals and the breakdowns of machines are neglected) and in addition, these scheduling approaches may not address multiple criteria scheduling or accommodate alternate resources to process a job operation. In this paper, a scheduling method based on extreme value theory (SEVAT) is developed and addresses all the shortcomings mentioned above. The SEVAT approach creates a statistical profile of schedules through random sampling, and predicts the quality or 'potential' of a feasible schedule. A dynamic scheduling problem was designed to reflect a real job shop scheduling environment closely. Two performance measures, viz. mean job tardiness and mean job cost, were used to demonstrate multiple criteria scheduling. Three factors were identified, and varied between two levels each, thereby spanning a varied job shop environment. The results of this extensive simulation study show that the SEVAT scheduling approach produces a better performance compared to several common dispatching rules.     

When Costs Are Unequal and Unknown: A Subtree Grafting Approach for Unbalanced Data Classification*

In binary classifications, a decision tree learned from unbalanced data typically creates an important challenge related to the high misclassification rate of the minority class. Assigning different misclassification costs can address this problem, though usually at the cost of accuracy for the majority class. This effect can be particularly hazardous if the costs cannot be specified precisely. When the costs are unknown or difficult to determine, decision makers may prefer a classifier with more balanced accuracy for both classes rather than a standard or cost‐sensitively learned one. In the context of learning trees, this research therefore proposes a new tree induction approach called subtree grafting (STG). On the basis of a real bank data set and several other data sets, we test the proposed STG method and find that our proposed approach provides a successful compromise between standard and cost‐sensitive trees.     

基于合作博弈的易腐性产品运输设施选择的费用分配

易腐性产品的价值会随着时间而损失,运输易腐性产品时,客户除了支付运输费用外还需要承担产品的价值损失。本文把易腐性产品的价值损失和运输费用之和作为总费用,应用合作博弈理论,把易腐性产品的运输设施选择的费用分配问题构造成费用分配博弈,证明了在易腐性产品线性价值损失的情况下,运输设施选择博弈的核心非空,且为子模博弈,并讨论核仁、夏普利值、τ-值等解。论文最后讨论了有约束运输的设施选择的费用分配博弈的解的情况,说明其核心也许为空,并提出了进一步研究的方向。     

On step fixed-charge transportation problem

The fixed-charge problem is a nonlinear programming problem of practical interest in business and industry. One of its variations is the fixed-charge transportation problem (FCTP) where fixed cost is incurred for every route that is used in the solution, along with the variable cost that is proportional to the amount shipped. That cost structure causes the value of the objective function Z to also behave like a step function. Each time we open or close a route the objective function jumps a step. The step fixed-charge transportation problem (SFCTP) is a variation of the FCTP where the fixed cost is in the form of a step function dependent on the load in a given route. While the value of the objective function Z in the FCTP is a step function, the introduction of the step fixed cost in the SFCTP results in the objective function Z being itself a step function with many more steps. Fixed-charge problems are usually solved using sophisticated analytical or computer software. This paper discusses the theory of SFCTP and presents a computationally simple heuristic algorithm for solving small SFCTPs.     

基于工序的成本管理及其应用研究

探索将传统预算快速转化为能满足项目赢得值评估法所要求的资源数据的方法,解决成本基础数据不易准确分摊到工程的最小工作包的问题,从而解决了现代项目成本信息化管理模式与我国传统工程造价管理模式脱节问题,力圖使基于工序的成本管理COA(Cost On Activity)得以真正实现。     

Cost-plus pricing when joint costs are present

Companies using cost-plus pricing often produce products that entail joint cost allocation. A problem they have encountered is that, while product prices are a function of the full cost, joint cost allocation methods using net realizable values depend on the product prices. This paper shows that when all costs and production quantities are known (or can be budgeted), it is possible to simultaneously determine unique product prices and cost allocations using the net realizable value method.     

JOINT PRODUCT COST ALLOCATION IN THE CONTEXT OF COST-PLUS PRICING DETERMINATIONS WITH NON-UNIFORM MARKUPS

Companies that use cost-based pricing sometimes manufacture products that involve joint cost allocation. A problem with this is that, while product prices are a function of the full cost, joint cost allocation methods using net realizable values depend on the product prices. This paper demonstrates that when all costs and production quantities are known or can be budgeted, it is possible to simultaneously determine unique product prices (having non-uniform markup rates) and cost allocations using the net realizable value method.     

The total cost bounds of the transportation problem with varying demand and supply

A transportation problem is a linear programming problem based on a network structure consisting of a finite numbers of nodes and arcs attached to them. In real world applications, the supply and demand quantities in the transportation problem are sometimes hardly specified precisely because of changing economic conditions. This paper investigates the transportation problem when the demand and supply quantities are varying. A pair of mathematical programs is formulated to calculate the objective value. The derived result is also in range, where the total transportation cost would appear. In addition to allowing for simultaneous changes in supply and demand values, the total cost bounds are calculated directly. Due to the structure of the transportation problem, the largest total transportation cost may not occur at the highest total quantities shipped. Since the total cost bounds are derived, it would be beneficial to decision-making.     

The P-Hub maximal covering problem and extensions for gradual decay functions

The p-hub maximal covering problem aims to find the best locations for hubs so as to maximize demands within a coverage distance with a predetermined number of hubs. Classically, the problem is defined in the framework of binary coverage only; an origin–destination pair is covered if the cost (time, etc.) is lower than the critical value, and not covered at all if the cost is greater than the critical value. In this paper, we extend the definition of coverage, introducing “partial coverage”, which changes with distance. We present new and efficient mixed-integer programming models that are also valid for partial coverage for single and multiple allocations. We present and discuss the computational results with different data sets.