政策工具视角的中国装配式建筑政策文本量化研究

为了更科学地进行政策分析和研究,评测已有装配式建筑政策体系完善与否,从政策工具的视角,将基本政策工具、装配式建筑驱动主体和产业价值链组合成一个三维研究框架.利用该框架,运用内容分析法对中国现有13份中央政府级装配式建筑政策文本中采用的政策工具进行计量和分析.得出环境型和供给型政策工具过溢,针对企业和科研机构的政策工具缺失,装配式建筑产业价值链维度的政策工具滞后于其价值实现环节等结论,并为完善装配式建筑政策体系提出建议.     

中国“三农”问题研究现状及其成果评价——基于国家社科基金项目及其成果论文的计量分析

随着国家社科基金项目对“三农”问题研究的资助力度不断加强,相关研究发展迅速且成果卓著,对此进行整体梳理,既有助于总结以往研究的经验,也有益于相关问题研究的不断深入.文章以1991-2015年立项的3 375项“三农”问题国家社科基金项目及其18 770篇成果论文为研究对象,对项目信息、成果论文、研究热点与评价等方面进行计量分析,全面呈现中国“三农”问题近30年的发展与研究状况.研究表明,农民、新生代农民工、新农村等为“三农”问题的研究热点,有关农民、农民工的论文最受关注且被引频次最高.     

社会网络对民间金融风险的作用——基于社会网络结构的理论与实证分析

社会网络对民间金融风险的影响已被广泛认可,但是,究竟什么样的网络结构有抑制风险的作用,什么样的网络结构有扩增风险的作用？以资金互助会为例,将互助会涉及的社会网络按结构特征分为单个会的会内网络和多个会的会间网络,研究可知：（1）越紧密的会内网络结构以及越大的网络规模越有利于民间金融风险的控制。（2）跨会网络具有抑制和扩增风险两种作用,它是协同监督和惩罚机制生效的基础,因而对风险具有控制作用,但这种作用只在中介成员为会首时才显著;同时,它也构成了风险传播的通道,导致资金被分散到多个会中,因而提升了系统性风险。     

二元学习与创新绩效的作用机制——组织内部协作网络的调节作用

组织学习是驱动企业创新、实现技术追赶与超越追赶的关键因素,如何合理组织企业的利用式和探索式学习是企业构建研发体系的关键问题。学界对二元学习是否有利于企业的创新绩效存在截然不同的观点。同时,组织内部的情境因素是影响组织二元学习和创新绩效关系的最根本因素,组织内部研发协作网络是二元学习的重要载体。基于美国半导体行业企业十年间的专利数据,实证研究发现,不同维度的二元学习对企业创新绩效具有不同的影响,联合二元学习能够积极影响企业的创新绩效,平衡二元学习则会降低企业的创新绩效;内部研发协作网络密度在二元学习和创新绩效的关系中具有显著的调节作用,企业的内部协作网络密度越高,联合二元学习对企业创新绩效的积极影响越弱,平衡二元学习对创新绩效的负影响则加剧。     

兰州市洒水治污政策变迁路径与动力研究——基于定性比较分析法

以兰州市洒水车治污政策为研究案例,应用清晰集定性比较分析法（Crisp-set QCA）研究地方政府具体环保政策的变迁问题。分析发现,自上而下的政治压力、公众舆论压力、媒介压力、专家压力以及领导变更等五类8个解释变量可以作为案例政策变迁的驱动因素,其中,中央媒介压力是政策变迁的必要条件。按照不同的驱动因素组合,兰州洒水治污政策变迁有4种演进路径,其中,最短路径是“中央媒介压力且网络媒介压力”与“领导批示且中央媒介压力”。此外,在本政策案例中,领导批示不但没有促成政策变迁,甚至不构成变迁的必要条件。无论是“地方领导留言板”,还是“门户网站留言板”均非政策变迁的充分或必要条件,因此未能彰显公民参与在政策问题建构中的权力扩大,公众并没有实质拥有建构权,也未能成为建构主体,仅依赖互动平台的构建是无法打破原有的政策问题建构秩序的,因而也不能促使政策变迁彰显民意。     

大型低速重载径向动压轴承研究

为了开发大型贯流式水轮发电机组径向轴承,在试验台上采用了360的模型轴承对1740可倾6瓦块原型轴承进行模拟试验研究,最高试验比压3.37 MPa、最低线速度3.77 m/s、最高线速度22.62 m/s。试验表明:载荷、进油压力、转速、进油温度和安装间隙比等,对轴承油温升、油流量、功耗、瓦温及油膜厚度等都存在不同程度的影响,其中载荷和转速的影响比较显著。按照模型轴承指导设计的红岩子机组1740轴承已在电站可靠运行,同时开发了径向轴承热弹流计算程序,可以预测径向轴承的油膜压力、油膜温度、油膜厚度、损耗、流量等参数。     

Diverging Paths? A Comparative Look at Childcare Policies in Japan,South Korea and Taiwan

This article compares state policies to support childcare in Japan, South Korea and Taiwan, using fuzzy set ideal type analysis to determine the nature of institutional arrangements with respect to labour, money and time provisions. We then note their implications for familialization and defamilialization in the three countries. Our analysis suggests a common pattern towards the increased use of financial support amongst the three countries over time; however, this commonality does not mean their childcare policies are converging, as the financial supports differ in focus, with Japan concentrating on familialization by valuing family care, and Korea exclusively employing policy to facilitate the use of market‐based care services. For its part, Taiwan has been strengthening familialization by increasing the leave compensation to value time off to provide care. The different labour, money and time dimensions vis‐à‐vis the familialization/defamilialization matrix suggest varying implications of institutional arrangements for gender.     

R&D cooperation in collaborative consumption of research equipment: An ERGM approach

High-tech research infrastructure is essential for state-of-the-art research, but requires many resources. Relatively weak actors, such as SMEs, cannot secure enough of those. Applying the concept of collaborative consumption via digital platforms, we examine the cooperative behavior of Korean SMEs that share research equipment to overcome their lack of resources. Also, we analyze configurations of a collaborative consumption network using the Exponential Random Graph Model. Network structural factor analysis shows sufficient effects of network positive feedback through cooperative consumption with a variety of popular providers and attributes analysis shows that SMEs frequently engage in collaborative consumption with their counterparts in the same region. This new cooperative model can achieve a virtuous cycle of policies, as it increases the efficiency of research infrastructure, preventing the unnecessary building of new research equipment and enabling relocation of underutilized infrastructure and online reservation of equipment.     

Sensitivity,uncertainty, and decision analyses in the prioritization of research

The evaluation of hazards from complex, large scale, technologically advanced systems often requires the construction of computer implemented mathematical models. These models are used to evaluate the safety of the systems and to evaluate the consequences of modifications to the systems. These evaluations, however, are normally surrounded by significant uncertainties related to the uncertainty inherent in natural phenomena such as the weather and those related to uncertainties in the parameters and models used in the evaluation.

Another use of these models is to evaluate strategies for improving information used in the modeling process itself. While sensitivity analysis is useful in defining variables in the model that are important, uncertainty analysis provides a tool for assessing the importance of uncertainty about these variables. A third complementary technique, is decision analysis. It provides a methodology for explicitly evaluating and ranking potential improvements to the model. Its use in the development of information gathering strategies for a nuclear waste repository are discussed in this paper.     

Three‐Stage Decision‐Making Model under Restricted Conditions for Emergency Response to Ships Not under Control

A ship that is not under control (NUC) is a typical incident that poses serious problems when in confined waters close to shore. The emergency response to NUC ships is to select the best risk control options, which is a challenge in restricted conditions (e.g., time limitation, resource constraint, and information asymmetry), particularly in inland waterway transportation. To enable a quick and effective response, this article develops a three‐stage decision‐making framework for NUC ship handling. The core of this method is (1) to propose feasible options for each involved entity (e.g., maritime safety administration, NUC ship, and ships passing by) under resource constraint in the first stage, (2) to select the most feasible options by comparing the similarity of the new case and existing cases in the second stage, and (3) to make decisions considering the cooperation between the involved organizations by using a developed Bayesian network in the third stage. Consequently, this work provides a useful tool to achieve well‐organized management of NUC ships.