Leader political skill and casino dealer morale: the mediating role of follower perceptions of leader–member exchange

Our study investigated the follower perceptions of leader–member exchange (FPLMX) as a mediator between leader political skill (LPS) and follower morale and tested these relationships using data obtained from casino dealers in Korea. Social astuteness, interpersonal influence, networking ability, and apparent sincerity are the indicators of LPS, while follower morale is composed of job satisfaction and affective organizational commitment. The results from structural equation modeling suggest that the research model we have proposed is viable. Broadly speaking, FPLMX is a partial mediator between LPS and follower morale.     

Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market

We study the economic and non-economic sources of stock return comovements of the emerging Indian equity market and the developed equity markets of the US, UK, Germany, France, Canada and Japan. Our findings show that the probability of extreme comovements in the economic contraction regime is relatively higher than in the economic expansion regime. We show that international interest rates, inflation uncertainty and dividend yields are the main drivers of the asymmetric return comovements. Findings reported in the paper imply that the impact of interest rates and inflation on return comovements could be used for anticipating financial contagion and/or spillover effects. This is particularly critical since during extreme market conditions, the tail return comovements can potentially reveal critical information for active portfolio management.     

Threat of termination and firm innovation

This study investigates how the ex-ante threat of termination affects firm performance in innovation measured by number of patents and citations. Empirical results show that the threat of termination is negatively associated with both measures of firm innovation. This relation however is sensitive to industry structure. The negative effect of the threat of termination on innovation is statistically significant only for high-tech firms. For low-tech firms there is no statistically significant relation between the threat of termination and firm innovation. One plausible explanation is that high-tech firms are inherently risky and have higher rates of project failure. Adding the risk of higher threat of termination makes the manager more risk averse and forces her to avoid investing in value increasing innovations. Managers in low-tech firms don’t face such pressures. The policy implication is that high-tech firms should lower threat of termination and increase tolerance for project failure to encourage innovation.     

Economic Implications of Further Harmonisation of Electronic Communications Regulation in the EU

There are some aspects of the European RFEC and its implementation today that could benefit from increased harmonisation; there are others in which substantial accommodation to local, national or regional circumstances and preferences is desirable or required.     

A Brief Survey of Modern Optimization for Statisticians

Modern computational statistics is turning more and more to high‐dimensional optimization to handle the deluge of big data. Once a model is formulated, its parameters can be estimated by optimization. Because model parsimony is important, models routinely include non‐differentiable penalty terms such as the lasso. This sober reality complicates minimization and maximization. Our broad survey stresses a few important principles in algorithm design. Rather than view these principles in isolation, it is more productive to mix and match them. A few well‐chosen examples illustrate this point. Algorithm derivation is also emphasized, and theory is downplayed, particularly the abstractions of the convex calculus. Thus, our survey should be useful and accessible to a broad audience.     

Estimate of Suspended Sediment Concentration from Monitored Data of Turbidity and Water Level Using Artificial Neural Networks

Artificial neural networks (ANNs) are promising alternatives for the estimation of suspended sediment concentration (SSC), but they are dependent on the availability data. This study investigates the use of an ANN model for forecasting SSC using turbidity and water level. It is used an original method, idealized to investigate the minimum complexity of the ANN that does not present, in relation to more complex networks, loss of efficiency when applied to other samples, and to perform its training avoiding the overfitting even when data availability is insufficient to use the cross-validation technique. The use of a validation procedure by resampling, the control of overfitting through a previously researched condition of training completion, as well as training repetitions to provide robustness are important aspects of the method. Turbidity and water level data, related to 59 SSC values, collected between June 2013 and October 2015, were used. The development of the proposed ANN was preceded by the training of an ANN, without the use of the new resources, which clearly showed the overfitting occurrence when resources were not used to avoid it, with Nash-Sutcliffe efficiency (NS) equals to 0.995 in the training and NS = 0.788 in the verification. The proposed method generated efficient models (NS = 0.953 for verification), with well distributed errors and with great capacity of generalization for future applications. The final obtained model enabled the SSC calculation, from water level and turbidity data, even when few samples were available for the training and verification procedures.     

Second-party and third-party punishment in a public goods experiment

We experimentally investigate whether third-party punishment is more effective than second-party punishment to increase public goods contribution. In our experiment, third parties first played the standard public goods game and then made punishment decisions as independent bystanders. We find that third parties punished more frequently, severely and less antisocially, resulting in a higher contribution level than that driven by second-party punishment. The third party’s exaggerated emotion towards free riders is proposed to explain their superior punishment effectiveness.     

福斯特对马克思生态唯物主义思想的建构

约翰·贝拉米·福斯特作为北关生态学马克思主义流派中的领军人物之一，他从20世纪80年代开始研究马克思的生态思想．对马克思的生态唯物主义思想作了一个系统清晰的梳理。在对马克思唯物主义思想建构的过程，福斯特主要通过考察伊壁鸠鲁、费尔巴哈以及达尔文等人的思想对马克思生态唯物主义思想的形成产生的深远影响。在他们的启发和影响下，马克思最终完成了自然、历史和实践的统一。