地方债务治理对银行信贷资金"脱虚向实"的影响——基于国务院"43号文"准自然实验的经验考察

国务院"43号文"的实施,为研究地方债务的治理效果提供了一个准自然实验场景.研究发现:地方债务治理对银行金融资产没有产生影响,但会显著增加银行总贷款、个人贷款和企业贷款,有助于银行信贷资金的"脱虚向实";地方债务治理能显著增加银行实体行业贷款,但不能显著增加银行非实体行业贷款和建筑业贷款.机制检验发现,地方债务治理可以通过降低借款人和借款企业的融资成本,间接性地影响银行信贷资金配置.进一步研究发现,国务院"43号文"实施后,资产质量高的银行倾向于增加企业贷款和实体行业贷款,资产质量低的银行倾向于增加个人贷款;银行规模可以强化地方债务治理对银行贷款增长的促进作用.因此,为促进银行信贷资金的"脱虚向实",应提高地方债务治理水平,强化对银行业务的监管与引导,加强风险管理,保障银行资产质量.     

Can investors time their exposure to private equity?

Private equity performance, both for buyouts and venture capital, has been highly cyclical: periods of high fundraising have been followed by periods of low performance. Despite this seemingly predictable variation, we find modest gains, at best, to pursuing realistic, investable strategies that time capital commitments to private equity. This occurs, in part, because investors can only time their commitments to funds; they cannot time when commitments are called or when investments are exited. There is a high degree of time-series correlation in net cash flows even across commitment strategies that allocate capital in a very different manner over time.     

Go beyond tokens: Number and type both matter

Drawing upon token theory and critical mass theory, this study examines whether all female directors are equally considered as tokens. We argue that inside female directors are less likely than outside female directors to be considered as tokens because they are more powerful and influential. Using a 10-year sample of Chinese publicly listed firms on the Shanghai or Shenzhen Stock Exchanges from 2008 to 2017, we find that even one inside female director can make a significant contribution to corporate social responsibility (CSR), while outside female directors do not have a positive effect on CSR until their number reaches the critical mass (i.e., three). The results suggest that the predictions of token theory and critical mass theory vary across female director types. These findings contribute to the current literature by integrating female director typology with their numerical representation to explain their token status.     

组织支持感与员工创造力——相对组织支持感和情感承诺的影响

从自我提升视角出发，基于社会比较理论与社会交换理论，分析组织支持感影响员工创造力的过程机制，相对组织支持感的调节作用以及情感承诺与创造力之间的曲线关系。基于458份企业员工与主管的配对样本，研究结果表明：相对组织支持感显著正向调节了组织支持感与情感承诺之间的关系，情感承诺与员工创造力呈显著的倒U型关系，情感承诺在组织支持感与创造力关系之间起到了瞬时中介作用。研究结果拓展了对组织支持感的影响机制及其边界条件的分析，深化了情感承诺与员工创造力关系的检验。     

江淮汽车成功开拓哈萨克斯坦市场的经验与启示

产能合作是当前和未来促进中哈两国经济协同发展的核心方式,江淮汽车成功进入哈萨克斯坦,对于推进两国制造业产能合作具有重要意义.充分利用国家政策、对接哈萨克斯坦汽车工业发展战略和市场需求、选择恰当国际市场进入模式和营销策略、培植核心竞争力以及积极应对哈萨克斯坦市场的激烈竞争是江淮汽车成功进入哈萨克斯坦市场的关键因素.我国企业应有效对接哈萨克斯坦经济战略,积极参与中哈产能合作;精准目标市场定位,优化产品结构;选择合适的市场进入模式,积极开展本地化生产;不断提升企业的核心竞争力.     

房建工程地基基础施工关键技术探究

地基处理技术是近年来我国房屋建筑工程施工中一种较常见的施工处理技术,多见于房屋建筑工程中的软土地基施工环节。通过以往的房屋建筑经验,如果直接在软土地基上进行建筑施工,地基区域软土很容易会影响房屋建筑工程的稳定性,所以,在针对这一部分软土区域的施工环节,需要针对拟施工的地基软土区域进行处理,提升其软土的稳定性。到目前,地基处理技术已经在我国房屋建筑工程施工中广泛应用,这一技术应用过程中存在的不足也逐渐凸显,如何针对这一技术的不足予以完善,以此提升地基处理技术对房屋建筑质量的积极影响,成为了现阶段房屋建筑地基基础施工质量提升的重要环节之一。     

我国“一带一路”沿线地区风险投资时空分布及影响因素研究

深入分析我国“一带一路”沿线地区风险投资时空格局及影响因素，有助于促进创新创业与企业发展、提高区域科技创新水平。运用空间分析方法和空间计量模型，对2003-2018年我国“一带一路”沿线139个城市风险投资的时空分布特征及影响因素进行分析，结果表明：①沿线地区的风险投资发展具有不均衡性，呈现为沿海高、西部低的分异格局；②风险投资的全局自相关系数均为正，呈现出明显的空间集聚特征；③风险投资机构数、国家高新区数量、风险投资退出、政府引导基金发展、财政科技支出对区域风险投资具有显著促进作用，环境污染对风险投资有一定抑制作用。随着ESG投资理念逐渐获得认可，沿线地区可以通过提升绿色发展水平促进风险投资发展。     

智能制造有利于增加企业技术创新投入吗——基于智能制造试点的准自然实验

智能制造是我国制造业转型升级的主攻方向,而如何准确客观评价智能制造的实施效果成为亟待解决的问题.从技术创新投入视角,将智能制造试点政策实施视为一次准自然实验,采用2011-2019年制造业上市企业面板数据,通过PSM-DID方法研究智能制造对企业技术创新投入的影响.研究结果表明,智能制造显著影响企业技术创新投入,即通过提升客户集成度、供应商集成度进而提高企业技术创新投入,且促进作用仅发生在民营企业和非高新技术行业中.该发现扩展了现有研究外延,同时,为解决当前国际困局和促进智能制造的持续推广提供了重要实践价值.     

Crowdsourcing-based semantic relation recognition for natural language questions over RDF data

ABSTRACT

Natural language query systems over RDF data need to rely on the semantic relations in query. First, we propose the new crowdsourcing model that used to produce semantic relations dataset. The model not only inherits completeness of the iterative model and accuracy of the parallel model, but also saves human resources. Second, we mine the rules of semantic relation recognition from the correlations between dependency structures and semantic relations. Third, we propose an algorithm of semantic relation recognition for natural language query over RDF data, and experiments demonstrate that it can recognize more semantic relations than existing methods.