团队科学创造力的提升需重视团队成就目标导向——被调节的中介效应

基于创造力成分等多维理论，构建以团队反馈寻求行为为中介变量，团队凝聚力为调节变量的被调节的中介效应模型，以期深入解释创新团队成就目标导向如何影响其团队科学创造力。基于129个理工科大学生科技创新团队数据，研究结果表明，团队学习目标导向和团队表现目标导向分别与团队科学创造力有显著的正向和负向关系；团队反馈寻求行为在团队成就目标导向与团队科学创造力间起部分中介作用；团队凝聚力负向调节团队反馈寻求行为与团队科学创造力间的关系，并弱化了团队成就目标导向通过团队反馈寻求行为对团队科学创造力的间接影响。结论对提高科技创新团队科学创造力有一定指导价值。     

基于AHP-TOPSIS模型的京津冀家政服务人力资源供给质量评价研究

依托已有的研究成果构建了家政服务人力资源供给质量评价指标体系,利用AHP-TOPSIS模型对京津冀家政服务人力资源供给质量进行了评价和排名,并使用障碍度模型分析了员工制、准员工制、培训学校、中介制四种类型家政机构人力资源供给质量的关键制约因素,在此基础上,给出了不同类型家政机构人力资源供给质量改善的针对性建议,为家政服务人力资源供给质量的改善提供参考依据。     

经济带:新发展阶段的新愿景

经济带已成为承东启西、连南贯北的"经济主骨架",在国民经济整体格局中的战略地位日益凸显,对我国经济发展具有重大战略意义.经济带的形成有其深刻的理论基础和现实条件,我国"两横"——长江经济带和陇海兰新经济带,以及"三纵"——沿海经济带、京广京哈经济带、包昆经济带五条经济带,需要进一步集聚经济要素,破除要素流动壁垒,提升节点城市能级,推动区域经济合作,以经济带建设推动我国经济高质量发展.     

The Moderating Effects of Status-Consumption Motive and Age in the Relationship between CSR Advertising Appeal Type and Purchase Intentions

The primary purpose of this study was to examine factors that influence the effectiveness of benefit appeal types (i.e., help-other vs. help-self) in Corporate Social Responsibility advertising. To that end, we designed and administered a between-subjects experiment where participants viewed one of the two CSR advertisements crafted with help-self and help-other benefit appeals. Results provided evidence supporting the moderating effects of status-consumption motives and age on purchasing intentions. Additional analysis suggested consumers younger than 48 years old were more likely to be persuaded by a help-other ad appeal when they didn't have strong desires for status consumption. Results were discussed in light of the self-concept theory and value-expressive framework in CSR advertising.     

Monitoring the foreign exchange rate benchmark fix

ABSTRACT

We develop a Manipulation Index (ManIx) that captures the potential manipulation intention of dealers during the World Markets/Reuters (WMR) benchmark (London Close) period at 4 pm London time through a unique algorithm and simulation. The application of this model (using a dataset with dealers’ identities) can identify banks that are prone to potential manipulative behavior. The results concerning the identified banks are validated by the regulatory investigations. Implementation of this algorithm allows regulators better direct their limited resources towards more targeted in-depth investigation.     

中国高端装备制造业自主技术创新效率稳定性及影响因素研究

在全面实施创新驱动发展战略的时代背景下，揭示中国高端装备制造业自主技术创新效率稳定性，测度相关因素的影响强度与方向，对揭示中国高端装备制造业自主技术创新规律，制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素，采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究，结果表明，中国高端装备制造业自主技术创新效率存在一定波动性，且各细分行业技术创新效率内部稳定性较差，产业自主技术创新效率整体稳定性不高；自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性，其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响，而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性，政策因素与市场因素分别具有显著和非显著负向影响，外源性创新因素具有显著正向影响，且影响强度较大。在此基础上，提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。     

INTERNATIONAL RESERVE MANAGEMENT: A DRIFT‐SWITCHING REFLECTED JUMP‐DIFFUSION MODEL

We study the cost of shocks, that is, jump risk, with respect to reserve management when the reserve process is formulated as a drift‐switching jump diffusion with a reflecting barrier at 0. Inspired by the Brownian drift switching model, our model results in a more realistic dynamic behavior of international reserves than the buffer stock model. The new model can capture both the jump behavior in reserve dynamics and the leptokurtic feature of the increment distribution which has a higher peak and two asymmetric heavier tails than the normal distribution. Through the selection of an initial distribution that reflects certain steady state behaviors, the reserve process becomes a regenerative process. This selection enables us to derive a closed‐form expression for the total expected discounted cost of managing reserves, thus helping us to numerically find management strategies that minimize costs. The numerical results show that shocks at the reserve level have a significant effect on reserve management strategies and that model misspecification can result in nonnegligible additional costs.     

Why will Trump lose the trade war?

ABSTRACT

The escalating U.S.–China trade conflicts have increasingly shadowed the outlook of the world economy. The Trump administration aims to achieve its strategic goals including reducing current account deficits, promoting the U.S. manufacturing sector, and curbing Chinese high-tech industries by waging the trade war against China. This paper argues that the current account deficits and the declining manufacturing sector in the U.S. are mainly driven by its internal structural factors, such as low saving rates, high labor costs, and rising service sector, rather than by the import competition from China. Moreover, the trade war further deteriorates the U.S. current account deficits and erode its comparative advantage, and it forces China to invest more in technological innovation and human capital, and thus promote its progress in high-tech industries. Thus, the U.S. will not be able to achieve its strategical goals and eventually lose the trade war.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Information Entropy-Based Housing Spatiotemporal Dependence

The Journal of Real Estate Finance and Economics - In the existing housing literature, there has been no academic consensus on how to combine the spatial dependence and the temporal dependence...