工程项目中社会资本对合理风险分担的影响研究

经济活动总是嵌入在一定社会关系中的,因此,任何一个工程项目风险分担的合理性都应在社会资本的视域下考察与判断.本文通过理论分析构建工程项目中社会资本对合理风险分担的影响模型,并以30个成功建设项目为样本采集到126份有效数据,运用结构方程模型的方法进行实证分析.研究结果表明:(1)风险分担可分解为缔约阶段的风险初次分担和履约过程中的风险再分担,二者之间具有显著的互补与联动关系;(2)社会资本对风险初次分担的完备程度产生显著反向影响,而对事后支持制度产生显著正向影响,且对事后支持制度的总效应相对较大;(3)社会资本对风险再分担的规模与实施效率均产生显著正向影响,且对风险再分担的实施效率总效应最大.本研究有利于引导工程项目交易双方根据社会资本制定更为合理的风险分担方案,从而促使项目成功.     

集装箱码头堆场取箱时间窗优化研究

码头堆场是供装卸船舶存放集装箱的场所,同时也是向货主交接集装箱的地方.由于取箱车辆到达时间的不确定性,码头运营方需要在堆场进行大量的翻箱作业,消耗大量的劳动成本.首先对码头取箱时间窗优化机制进行了说明,构建了码头方补助金函数与车辆方的成本函数,获得了车辆方取箱的到达率函数,进而得到了码头方的翻箱次数公式.然后,描述了集...     

企业主集权:边界理论的新观点

与企业主关系亲近会让经理人获得更多授权吗?本文借助边界理论的分析框架提出了一种新的理论逻辑,强调家族涉入管理会影响企业主边界行为策略,进而影响控制权配置行为。基于双样本和两重测量的实证研究发现,家族涉入管理与企业主集权程度正相关,而目前学界普遍认同的企业主与经理关系亲近就会向后者更多授权的命题,仅在家族不涉入管理的情况下成立,在家族涉入管理的情况下并不成立。上述研究结果表明,家族涉入管理容易诱导企业主将家长身份与企业家身份一体化,把职业经理也纳入家长式集权管理之下,即使他们与企业主之间建立起泛家族化的亲近关系,也不易获得企业主的更多授权。     

公共研究机构高承诺工作系统的心理机制

在对公安部下属的4个省市的15家科研机构236名员工的两阶段调研基础上,从心理所有权角度,对公共研发机构高承诺工作系统的心理机制问题进行研究。结果发现,当将心理所有权作为高承诺工作系统与员工职业满意度之间的中介变量时,高承诺工作系统与员工职业满意度之间的关系不再显著,即组织的高承诺工作系统通过影响员工感受到的心理所有权状态,进而影响员工的职业满意度评价。     

面向开放式团队知识创新的动态标签关联网研究

知识创新是企业提高核心竞争力最重要的手段之一。当今世界经济一体化,全球创新方向正在向开放式创新转变。开放式创新环境下,跨组织、跨地域的开放式创新团队成为知识创新的主要载体。社会化标签能够使团队成员按照自己对知识的认知方式进行知识交互与协作,有利于促进开放式团队知识创新。但是由于标签标注的自由性,如何建立标签之间的关联关系以更有效地支持开放式环境中基于标签的知识管理与知识创新成为该领域的关键议题。本文研究并提出了面向开放式团队知识创新的动态标签关联网方法,并对该方法进行了应用研究,通过比较实验组和对照组的应用结果,可以发现面向开放式团队知识创新的动态标签关联网方法能够动态地展示标签之间的关联关系,从而支持开放式环境中的团队知识创新。     

中国育龄妇女生育集中度变化分析——基于“五普”、“六普”数据

新中国成立以来,结束了上千年的封建制度给妇女带来的桎梏,妇女的社会地位有了明显的提升,具体表现在社会活动的参与率有了显著的提高,同时妇女在生育行为方面也发生了巨大的变化。本文利用最近两次中国人口普查数据来分析育龄妇女的生育集中度变化情况,并以此对中国目前TFR很低的现象做了解释,据此推断中国在未来几年的时间,总和生育率在一定程度上会呈上升的变化趋势,但不可能在短期内回升到更替水平。     

Simultaneous edit-imputation and disclosure limitation for business establishment data

Business establishment microdata typically are required to satisfy agency-specified edit rules, such as balance equations and linear inequalities. Inevitably some establishments' reported data violate the edit rules. Statistical agencies correct faulty values using a process known as edit-imputation. Business establishment data also must be heavily redacted before being shared with the public; indeed, confidentiality concerns lead many agencies not to share establishment microdata as unrestricted access files. When microdata must be heavily redacted, one approach is to create synthetic data, as done in the U.S. Longitudinal Business Database and the German IAB Establishment Panel. This article presents the first implementation of a fully integrated approach to edit-imputation and data synthesis. We illustrate the approach on data from the U.S. Census of Manufactures and present a variety of evaluations of the utility of the synthetic data. The paper also presents assessments of disclosure risks for several intruder attacks. We find that the synthetic data preserve important distributional features from the post-editing confidential microdata, and have low risks for the various attacks.     

Rank aggregation using latent-scale distance-based models

Rank aggregation aims at combining rankings of a set of items assigned by a sample of rankers to generate a consensus ranking. A typical solution is to adopt a distance-based approach to minimize the sum of the distances to the observed rankings. However, this simple sum may not be appropriate when the quality of rankers varies. This happens when rankers with different backgrounds may have different cognitive levels of examining the items. In this paper, we develop a new distance-based model by allowing different weights for different rankers. Under this model, the weight associated with a ranker is used to measure his/her cognitive level of ranking of the items, and these weights are unobserved and exponentially distributed. Maximum likelihood method is used for model estimation. Extensions to the cases of incomplete rankings and mixture modeling are also discussed. Empirical applications demonstrate that the proposed model produces better rank aggregation than those generated by Borda and the unweighted distance-based models.

     

The effects of individually varying times of observations on growth parameter estimations in piecewise growth model

When using latent growth modeling (LGM), researchers often restrict the factor loadings, while the multilevel modeling (MLM) treats time as a metric variable. However, when individually varying times of observations are concerned in the longitudinal studies, the use of specified loadings would lead to inaccurate estimation. Based on piecewise growth modeling (PGM), this simulation study showed that (i) individually varying times of observations with larger boundaries got worse estimates and model fits when LGM was used; (ii) estimating the PGM across all the simulation situations was robust within MLM, whereas LGM got identically equal estimation with MLM only in the case of time boundaries of ±1 month or shorter; (iii) larger change of slope in piecewise modeling indicated better estimation.     

高校大学生奖学金使用状况调查及思考——以华南五校为例

高校奖学金制度在倡导优良学风、资助贫困学子等方面发挥着重要作用,但同时也存在着奖学金使用不科学、不合理的现象。通过对华南5校奖学金使用情况进行调查和访谈,分析了大学生奖学金使用状况,并提出了四点建议。