教育本该不一样

教育本该不一样，因材施教、有教无类，说的就是不同。教育不从根本上由“批发”改为“零售”，我们就培养不出创新人才、杰出人才，甚至于培养不出我们常说的有用人才。为了培养创新人才，教育内容要力求全面，教育目标要力求明确，教育的方法要务求得当。     

Does obligational contracting lead to better performance? A comparison of global carmakers’ supply chain management approaches in Australia

Supply chain management (SCM) has been recognised as key to automobile manufacturers’ (‘buyers’) competitive advantage. However, the performance implication of two different approaches towards SCM, obligational contracting (OCR) vs. arm’s length contracting (ACR), remains inconclusive in the current literature. By focusing on examining how multiple global automobile manufacturers’ SCM practices result in different performance outcomes in the one-country setting of Australia, we are able to ascertain the direct impact of SCM approaches on buyers’ performance. We also provide detailed analysis on the specific influence of each distinguishing feature of the OCR/ACR approaches on different aspects of performance. Through a more nuanced investigation of the links between SCM approaches and automobile manufacturers’ performance at the firm level, this research contributes to a better understanding of the topic with managerially applicable insights.     

Preference aggregation and atoms in measures

This paper examines the aggregation of preferences with a finitely additive measure space of agents. We consider three types of non-dictatorship axioms: non-dictatorship, coalitional non-dictatorship, and atomic non-dictatorship. First, we show that the existence of an atom is a necessary and sufficient condition for the existence of a social welfare function that satisfies weak Pareto, independence of irrelevant alternatives, and coalitional non-dictatorship. Second, we simultaneously impose non-dictatorship and coalitional non-dictatorship, and specify a necessary and sufficient condition for the finitely additive measure that guarantees the compatibility among the axioms. Third, we impose all non-dictatorship axioms and show that the corresponding measure is extremely restricted.     

我国银行理财业务发展趋势研究

对国内商业银行理财业务的发展状况进行了简要概述， 进而对理财业务开展过程中的一些问题进行了分析， 强调指出市场化应该成为银行理财业务转型升级和创新发展的方向， 并提出了实现市场化发展方向的若干具体措施。     

Brexit: Tracking and disentangling the sentiment towards leaving the EU

On 23 June, 2016, the UK held a referendum to decide whether to stay in the European Union or leave. The uncertainty surrounding the outcome of this referendum had major consequences for public policy, investment decisions, and currency markets. We discuss some of the subtleties involved in smoothing and disentangling poll data in light of the problem of tracking the dynamics of the intention to Brexit, and propose a multivariate singular spectrum analysis method that produces trendlines on the unit simplex. The trendline yield via multivariate singular spectrum analysis is shown to resemble that of local polynomial smoothing, and singular spectrum analysis presents the nice feature of disentangling the dynamics directly into components that can be interpreted as changes in public opinion or sampling error. The merits and disadvantages of some different approaches for obtaining smooth trendlines on the unit simplex are contrasted, in terms of both local polynomial smoothing and multivariate singular spectrum analysis.     

Crime prediction by data-driven Green’s function method

We develop an algorithm that forecasts cascading events, by employing a Green’s function scheme on the basis of the self-exciting point process model. This method is applied to open data of 10 types of crimes happened in Chicago. It shows a good prediction accuracy superior to or comparable to the standard methods which are the expectation–maximization method and prospective hotspot maps method. We find a cascade influence of the crimes that has a long-time, logarithmic tail; this result is consistent with an earlier study on burglaries. This long-tail feature cannot be reproduced by the other standard methods. In addition, a merit of the Green’s function method is the low computational cost in the case of high density of events and/or large amount of the training data.     

Predicting bank insolvencies using machine learning techniques

Proactively monitoring and assessing the economic health of financial institutions has always been the cornerstone of supervisory authorities. In this work, we employ a series of modeling techniques to predict bank insolvencies on a sample of US-based financial institutions. Our empirical results indicate that the method of Random Forests (RF) has a superior out-of-sample and out-of-time predictive performance, with Neural Networks also performing almost equally well as RF in out-of-time samples. These conclusions are drawn not only by comparison with broadly used bank failure models, such as Logistic, but also by comparison with other advanced machine learning techniques. Furthermore, our results illustrate that in the CAMELS evaluation framework, metrics related to earnings and capital constitute the factors with higher marginal contribution to the prediction of bank failures. Finally, we assess the generalization of our model by providing a case study to a sample of major European banks.     

The effect of economic policy uncertainty on China’s housing market

This study examines the relationship between economic policy uncertainty (EPU) and housing price at the macro-level in China as a developing country. The empirical evidence indicates that EPU has a leading effect on China’s housing market. In general, the housing market is prosperous when economic policy is stable and there is a positive relationship between housing price variation and EPU, which means housing market risk grows under unstable economic policies in this developing economy. Moreover, economic policy variation affects low-amplitude changes in housing prices. A variation of policy uncertainty enhances the risk premium of the housing market. By contrast, the level of EPU influences high-amplitude changes in housing prices, which reflects the trend of EPU dominating China's housing market.     

Hotel environmental management initiative (HEMI) scale development

Owing to a lack of construct reliability and validity of environmental management measurements, advancements in understanding hotels’ environmental management practices have been somewhat limited. The goal of this paper is to propose a uniform and parsimonious scale that captures Hotels’ Environmental Management Initiative (HEMI) with the most common three dimensions in the hotel industry: environmental resource conservation efforts, environmental policy and training, and environmental public relation efforts. After the refinement of the initial items, the scale was confirmed with cross-cultural data obtained from full-time hotel employees in two Asian countries. The twenty-one item HEMI scale demonstrated a satisfactory level of content, convergent, discriminant, cross, and criterion-related validity. The proposed HEMI scale will serve as a useful tool for future hospitality scholars who would like to further explore the impact of hotels’ environmental management initiatives on employees’ attitudes and behaviors toward the environment and their environmental performance.