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。     

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.     

How is Benevolent Leadership Linked to Employee Creativity? The Mediating Role of Leader–Member Exchange and the Moderating Role of Power Distance Orientation

Previous research has shown that virtuous leader behavior in the form of benevolent leadership has considerable impact on employee creativity. However, little is known as to how and under what conditions these constructs are linked. In the current research, we proposed and tested a moderated mediation model positing leader–member exchange (LMX) as a mediator, and employee power-distance orientation as a moderator of this relationship. Two studies were conducted to test our hypothesized model. In Study 1, repeated measured data collected from 284 Chinese employees in an information technology company demonstrated that benevolent leadership had a lagged effect on LMX. In Study 2, analyses of multisource and lagged data from 391 Chinese employees in 42 research and development teams, and their direct supervisors indicated that benevolent leadership was positively related to supervisor-rated employee creativity via LMX. In addition, the relationship between benevolent leadership and LMX was stronger for employees high in power-distance orientation. Theoretical implications of benevolent leadership’s research and practical contributions concerning promoting creativity in organizations where benevolent leaders prevail are also discussed.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

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.     

Flood Risk and Salience: New Evidence from the Sunshine State

A growing literature finds evidence that flood risk salience varies over time, spiking directly following a flood and then falling off individuals' cognitive radar in the following years. In this article, we provide new evidence of salience exploiting a hurricane cluster impacting Florida that was preceded and followed by periods of unusual calm. Utilizing residential property sales across the state from 2002 through 2012, our main estimate finds a salience impact of ?8%, on average. The salience effect persists when we base estimation only on spatial variation in prices to limit confounding from other simultaneous changes due to shifting hedonic equilibria over time. These effects range from housing prices decreases of 5.4–12.3% depending on the year of sale. Understanding flood risk salience has important implications for flood insurance and disaster policy, the benefits transfer literature, and, more broadly, our understanding of natural disaster resilience. JEL Classification: Q51, Q54, R21     

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...     

Further Mining the Predictability of Moving Averages: Evidence from the US Stock Market

Most studies on the predictability of moving average (MA) technical analysis use the discrete (buy/sell) trading recommendations. However, it is possibly incomplete or unreliable to explore the predictability of MA by only employing its generated trading signals. To further explore the forecastability of MA, we study its measurable impact on the stock market returns by using a conventional predictive regression framework. Our empirical study on the US stock market with respect to more detailed price information finds, (i) that the proposed predictor, MADP (MA based on daily prices) shows significant predictability in‐ and out‐of‐sample, and significantly outperforms the historical average (HA) benchmark as well as the MA based on monthly prices, (ii) that the predictability of MADP centers on the short‐term lags (within the most recent 10 days) and disappears when lags are beyond 20 days, and (iii) that the economic evaluation of the portfolios based on trading strategies confirms the superior performance of MADP with short‐term lags against the benchmark even though considering transaction costs.