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 antecedents of digital collaboration through an enhanced digital platform for destination management: A micro-DMO perspective

While the tourism sector shifts towards digital transformation, Destination Management Organisations (DMOs) often struggle to adapt to their changing technological environment. This study explores the antecedents of digital collaboration and develops a framework for micro-DMOs to enhance effective destination management through digital technologies. An integrated sequential qualitative approach was adopted by conducting multi-phase interviews, in addition to designing and trialling a real-world trial digital platform. The research provides empirical evidence that digital collaboration is essential for micro-DMOs, necessitating them to transform their current “websites” into digital platforms which act as a hub for business stakeholders to actively be involved in. Antecedents of successful digital collaboration include mutuality, trust, control, and leadership which may be manifested differently from non-digital collaboration. Additionally, the study identifies three aspects for digital collaboration; marketing, networking and knowledge sharing that demands specific attention. Our results have theoretical, methodological, and practical implications for academia, industry and policymakers.     

300MW循环流化床锅炉NO_x控制分析

本文从300MW循环流化床锅炉燃烧控制和烟气排放现状出发,对300MW循环流化床锅炉NOx排放超标的原因、现状进行深入分析,探讨了控制NOx达标排放的措施,从而为300MW循环流化床锅炉的安全运行、环保达标排放控制提供参考和积累经验。     

Political competition,tax salience and accountability. Theory and evidence from Italy

This paper argues that electoral competition may hinder rather than foster political accountability, especially when elected officers can choose among a number of tax instruments. We develop a political agency model showing that politicians in more competitive jurisdictions use less salient tax instruments more intensely. Defining salience as visibility or, analogously, as voters' awareness of the costs associated with specific government revenue sources, we argue that voters are less likely to hold politicians to account for the associated tax burden of a less salient instrument. This in turn implies that strategic politicians will more heavily rely on less salient revenue sources when electoral competition is stronger. Using data on Italian municipal elections and taxes over a 10-year period, we determine the degree of salience of various tax instruments, including property taxes (high salience) and government fees for official documents (low salience). We then show that mayors facing stronger competition for re-election use less salient tax instruments more intensely.     

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.     

Is China’s Manufacturing Industry Efficient? Evidence from an Energy-Rebound Effect Perspective

Majority of the increase in global energy consumption is from China; hence, studying energy issues, especially in China’s manufacturing industry (CMI), is worthwhile and of much interest in the academic field. Based on the translog cost function, we develop a research framework to study the rebound effect of CMI. Considering the effect of asymmetric energy price, we augment the energy-cost function with asymmetric influence constraint of energy price. Again, we add time series data of CMI’s capital, labor, energy, and mid-input to the model to calculate the direct rebound effect of CMI. We find that the rebound effect of CMI is 44.2%, and CMI still has large energy-conservation potentials. Based on the results of this study, some policy recommendations are provided.     

Productivity efficiency analysis of the airlines in China after deregulation

Using data envelopment analysis and the Malmquist productivity index, this paper studies productivity efficiency of various airlines in China after the Chinese government deregulated the aviation industry in 2005. The results show that the productivity efficiency of non-state-owned airlines improves rapidly and eventually exceeds state-owned airlines after the deregulation policy. Among the state-owned airlines, the productivity of the local airlines and their technical changes are better than those of the central airlines.     

A new hub and spoke system proposal: A case study for Turkey's aviation industry

In this paper, we are proposing a multi-objective mathematical model for the selection of a newly constructed hub and spoke system. The objectives of this model are maximizing aircraft utilization and revenue whilst reducing the commercially infeasible network detour factor. The sensitivity analysis of the model is tackled using weights related to the objectives as well as the network detour factor. The number of available aircraft and the range that an aircraft can reach are also considered in this model. Since Istanbul has already got a hub and spoke system with busy airports on both sides of the city, the model is applied to three other major cities of Turkey, Ankara, Antalya, and Izmir. The test data consists of over 90 cities in Europe and in the Middle East. The data includes unit passenger revenues and operating costs for the segments, distances between cities and hubs, expected load factors and flying times of segments. The scenarios are tested under specific expectations of airline network experts and the results are visualized by using Pareto front graphs. Compared to other candidates, Antalya stands out as a good choice for a new hub and spoke system in Turkey. The results of this model could be helpful for airlines and other airports in Turkey in order to identify their potential and competitive position in relation to their counterparts.