浅议施工企业构建项目经理激励与约束机制

一、目前施工企业项目经理的管理现状及存在的问题 第一．多数施工企业项目经理仍然实行委派制或任命制．用人方式单一,企业内部缺乏竞争机制。第二．项目经理与企业员工统一实行仍带有一定行政级别工资色彩的岗位工资制,使其地位、责任与收入出现反差,在受到现有市场经济社会注重价值体现的影响下．很难起到应有的激励和约束作用．相反从一定程度上助长了灰色收入和腐败行为的发生。第三,项目经理奖罚机制不完善,制度不健全．激励与制约力度欠缺,短期行为严重。     

激励机制在火电施工项目薪酬管理中的应用探讨

目前,在火电施工企业中大多普遍采用岗位绩效工资制的薪酬制度,其有自身优点,但是随着社会整体工资结构多元化及企业间人才竞争的加剧,单纯的绩效工资制的缺点与不适应性已充分暴露,单一的岗位绩效工资制已经不能够满足现在企业管理的需求。本文根据火电施工项目的特点以及管理方式,探讨在薪酬的保障因素以及激励因素之间进行的调整,强化薪酬的激励作用,薪酬以岗位责任、业绩、承担风险等重要因素确定,将薪酬向为企业关键、核心人才适当倾斜。     

高校薪酬制度分析与激励型薪酬计划构建

本文分析了高校现行薪酬制度激励效能方面存在的不足,提出构建高校激励型一揽子薪酬计划。主要内容有:设计岗位津贴与绩效考核结果挂钩的岗位绩效津贴制;借鉴多任务代理理论中有关思想,提出对教师工作量与工作质量的协同管理方法;同时构建延期分配计划,以发挥薪酬体系的长期激励作用,补偿教师的职业风险损失。     

基于岗位工薪制下的专家积分制评价体系设计探索

岗位工薪制是适合现代企业管理的科学薪资分配体系,本文对岗位工薪制下专家积分评价体系进行探讨,提出了专家积分制评价体系设计思路,通过建立动态积分管理办法,公平评价核心技术员工业绩,有效激励,达到薪资分配为企业战略服务的目标．     

激励因素在销售管理工作中的应用研究

本文以企业中销售管理激励问题为研究对象,讨论销售过程中销售人员的激励因素问题。通过对销售岗位与一般岗位差异性的分析,认为销售人员的激励管理有别于其他企业行政管理岗位。讨论了目前企业中销售人员激励的现状,提出了构建销售人员激励管理体制,以通过对激励行为的科学引导来实现对销售人员的有效管理,提高企业的绩效管理的有效性。     

以岗位绩效沟核心的现代企业工资制度探索

按照建立现代企业工资收入分配制度的要求，兖矿集团结合公司实际，积极探索建立以岗位绩效工资为主的基本工资制度，创新完善经营管理者年薪制、生产人员计件工资制、销售人员业绩提成制、研发人员长效激励工资制、引进人才协议工资制，建立起了以岗位绩效为核心的工资制度体系。     

从转换机制入手 加强农村基层组织建设

先修渠,后放水;先送神,后扒庙;先生产,后断粮——改革乡级体制。引进竞争激励机制,改传统的任命制为民主竞争选举制——改革村级体制。     

以人力资源管理改革创新推进民办高校竞争力提升

近二十年来,民办高校在国家政策的支持下得到了较快的发展。如今,面对日趋复杂的竞争环境,民办高校如何凭借其自主性及灵活性,通过对人力资源规划、专业以及岗位分析、工作绩效激励等现代人力资管理的核心要素的分析及研究,探索及建立一套适合本校的人力资源管理制度,取得竞争优势。     

基于社会偏好的企业岗位管理激励效应研究——以中国水电企业为背景的实证分析

文章运用中国电力企业的调查数据实证分析了岗位管理与员工激励及其绩效之间的内在关系,结果表明,除了具有传统经济学视角上的提高组织人力资源配置效率功能外,有效的岗位管理还能够对组织员工产生很强的激励效应,进而提升其工作绩效.而且,有别于注重员工经济偏好的传统物质激励系统,有效岗位管理对员工的激励效应主要是通过满足其社会偏好来体现.     

结合企业实际创新薪酬管理

目前,我国企业薪酬管理存在着由于激励与约束机制不健全而导致薪酬分配平均主义的问题,如一些企业在进行薪酬设计时不以岗位分析为前提,不考虑岗位之间的差异,致使薪酬管理缺乏激励作用,甚至成为企业发展的桎梏.21世纪是人力资源竞争的时代,传统的薪酬策略和薪酬实践己经越来越不适应新的发展形势,如何利用好薪酬管理激励杠杆调动员工的积极性,是当前企业急需探讨和解决的问题之一.近年来,宣钢针对企业亟需大批专业技术过硬、生产操作娴熟的骨干人员的现状,注重企业薪酬管理的创新实践,从而有效地激活企业内部人力资源管理,实现员工与企业的共同发展.     

An EM algorithm for the destructive COM-Poisson regression cure rate model

In this paper, we consider a competitive scenario and assume the initial number of competing causes to undergo a destruction after an initial treatment. This brings in a more realistic and practical interpretation of the biological mechanism of the occurrence of tumor since what is recorded is only from the undamaged portion of the original number of competing causes. Instead of assuming any particular distribution for the competing cause, we assume the competing cause to follow a Conway–Maxwell Poisson distribution which brings in flexibility as it can handle both over-dispersion and under-dispersion that we usually encounter in count data. Under this setup and assuming a Weibull distribution to model the time-to-event, we develop the expectation maximization algorithm for such a flexible destructive cure rate model. An extensive simulation study is carried out to demonstrate the performance of the proposed estimation method. Finally, a melanoma data is analyzed for illustrative purpose.     

上市公司董事会特征对公司绩效影响的分析

文章以沪深两市百强名单中的董事会作为研究对象,借助SPSS统计软件,分析上市公司董事会特征对公司绩效的影响。结果表明:四项董事会特征与公司绩效均没有明显的相关关系。这表明目前我国上市公司还未能通过优化董事会特征来提高董事会效率进而提高公司绩效,上市公司治理存在很大的改进空间。文章提出了优化董事会成员结构、优化薪酬制度、建立健全董事任用和绩效评估机制等对策建议。     

我国企业家成长机制探析

文章基于企业经营者在企业发展中的重要作用,提出了建立企业家成长机制的构想,并着重探讨了如何健全选拔与招聘、使用与考核、激励与约束、培训、流动等5个方面的机制。     

Anchoring the mission: A framework for understanding mission maintenance in professional service firms

Mission maintenance in professional service firms must balance the commercial and professional logics and prevent mission drift. Based on a case study of ‘auditing in action’ in a German professional service firm we argue that mission maintenance results from interactions between the practice and field level. We find that anchors on the field level target individuals’ discretionary choices by balancing competing demands from the commercial and professional logics on the practice level. Therefore, we identify anchoring as a central cross-level mechanism for maintaining the balance between routinizing for professional quality and ‘flexibilizing’ for efficiency on the practice level. With these findings we make two contributions to the literature: an analysis of how the field level can contribute to maintaining organisations’ missions in fields that have competing logics, and the identification of anchoring as a central mechanism to balance competing demands with the expectations of referent audiences on the field level.     

“When Should Manufacturers Want Fair Trade?”: New Insights from Asymmetric Information when Supply Chains Compete

We study a model of competing manufacturer/retailer pairs where adverse selection and moral hazard are coupled with promotional externalities at the downstream level. In contrast to earlier models mainly focusing on a bilateral monopoly setting, we show that with competing brands a ‘laissez‐faire’ approach towards vertical price control might not always promote productive efficiency. Giving manufacturers freedom to control retail prices is more likely to harm consumers when retailers impose positive promotional externalities on each other, and the converse is true otherwise. Our simple model also suggests that, with competing supply chains, consumers and manufacturers might prefer different contractual modes if promotional externalities have substantial effects on demands.     

Model occurrence and model selection in panel data sets

In this study we focus attention on model selection in the presence of panel data. Our approach is eclectic in that it combines both classical and Bayesian techniques. It is also novel in that we address not only model selection, but also model occurrence, i.e., the process by which ‘nature’ chooses a statistical framework in which to generate the data of interest. For a given data subset, there exist competing models each of which have an ex ante positive probability of being the correct model, but for any one generated sample, ex post exactly one such model is the basis for the observed data set. Attention focuses on how the underlying model occurrence probabilities of the competing models depend on characteristics of the environments in which the data subsets are generated. Classical, Bayesian, and mixed estimation approaches are developed. Bayesian approaches are shown to be especially attractive whenever the models are nested.     

Forecasting the US housing market

The recent housing market boom and bust in the United States illustrates that real estate returns are characterized by short-term positive serial correlation and long-term mean reversion to fundamental values. We develop an econometric model that includes these two components, but with weights that vary dynamically through time depending on recent forecasting performances. The smooth transition weighting mechanism can assign more weight to positive serial correlation in boom times, and more weight to reversal to fundamental values during downturns. We estimate the model with US national house price index data. In-sample, the switching mechanism significantly improves the fit of the model. In an out-of-sample forecasting assessment the model performs better than competing benchmark models.     

农业产业集群研究综述

目前关于农业产业集群的研究,主要是基于专业分工理论、成本优势理论、工业区位论、增长极理论、产业集群理论等几方面。我国学者对农业产业集群的研究主要集中在模式、政府作用、动力机制、发展路径、竞争优势、创新机制几个方面,在竞合机制与转型升级等方面的研究需要加强。     

区域间衰退产业竞争的博弈策略研究

衰退产业的有效调整是保证区域产业结构合理有效的重要前提。文章分析了产业间竞争关系,建立了产业博弈竞争模型并求解,并以两省纺织产业为例进行实力研究。     

Forecast Encompassing and Parameter Estimation*

A desirable property of a forecast is that it encompasses competing predictions, in the sense that the accuracy of the preferred forecast cannot be improved through linear combination with a rival prediction. In this paper, we investigate the impact of the uncertainty associated with estimating model parameters in‐sample on the encompassing properties of out‐of‐sample forecasts. Specifically, using examples of non‐nested econometric models, we show that forecasts from the true (but estimated) data generating process (DGP) do not encompass forecasts from competing mis‐specified models in general, particularly when the number of in‐sample observations is small. Following this result, we also examine the scope for achieving gains in accuracy by combining the forecasts from the DGP and mis‐specified models.