The long-term role of non-traditional banking in profitability and risk profiles: Evidence from a panel of U.S. banking institutions

The goal of this empirical study is to identify empirically and on a panel basis how non-traditional bank activities affect directly the profitability and risk profiles of the financial institutions involved in such activities. Through a dataset that covers 1725 U.S. financial institutions involved in non-traditional bank activities spanning the period 2000–2013 and the methodology of panel cointegration, the empirical findings document that non-traditional bank activities exert a positive effect on both the profitability and the insolvency risk. The results could be important for regulators given they could serve as a pre-warning signal that sends a clear message to regulators about the potential systemic risk that exists within the financial markets.     

Urban Sensing by Crowdsourcing: Analysing Urban Trip behaviour in Zurich

The research on which this essay is based sought to provide a deeper understanding of live urban activities. The main idea was to obtain in‐depth trip information by integrating sensing technology with crowdsourcing‐based methods. Location and acceleration sensors embedded in smartphones can deliver useful trip information. Research had previously been conducted to find an accurate data analysis algorithm for high‐level data mining, an efficient sensing method for power saving. As a proof of concept, this essay presents a case study of Zurich that successfully implemented previous research achievements in the real environment. It established that urban travel behaviour can, in fact, be collected by sensors embedded in mobile devices, and that the data thus obtained can be used to measure the characteristics of trip behaviour in cities by means of an advanced classifying algorithm and analysis. The strength of this research is its pioneering role in clearing the ground for future urban data collection methods and planning strategies. Specifically, this study could provide answers to the following key questions: How can crowdsourcing be applied to the collection of urban transportation data? What kinds of information can be extracted from the crowdsourced mobile sensing platform? What kinds of knowledge, within the transportation domain, can be derived from the above?     

Comparing efficiency of holding business model and individual management model of airports

This research compares the efficiency of holding business model to individual management model of airports, employing some robust non-parametric partial frontier-based methods to compare the statistical distributions of efficiency, under different scenarios, to find out which group of airports yields better global performance. The comparison between groups will follow a Malmquist index decomposition, which seems to be the most appropriate tool for within- and inter-group performance comparison. For this purpose, a sample of 145 airports from three continents is utilized. The results provide evidence that European airports are the most productive ones, and within this cluster, the individual management model presented a significant frontier shift with respect the holding cluster frontier, meaning that the former is much more productive than the latter.     

Exploring the relationship between truck load capacity and traffic accidents in the European Union

Applying econometric techniques to EU28 panel data and controlling for explanatory variables such as road types, we find that increased truck load capacity does not necessarily aggravate road traffic safety. Specifically, heavy trucks do not seem to be linked with greater numbers of traffic fatalities/accidents, medium trucks appear to be the worst performers in terms of fatalities, and light trucks seem to be the worst for accidents. In summary, our results clarify the complex relationship between truck load capacity and road safety, pointing to the existence of a negative correlation for accidents per capita and an inverse U-shaped curve for fatalities per capita.     

Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain

Location selection plays a crucial role in the retail and service industries. A comprehensive location selection model and appropriate analytical technique can improve the quality of location decisions, attracting more customers and substantially impacting market share and profitability. This study developed a data mining framework based on rough set theory (RST) to support location selection decisions. The proposed framework consists of four stages: (1) problem definition and data collection; (2) RST analysis; (3) rule validation; and (4) knowledge extraction and usage. An empirical study focused on a restaurant chain to demonstrate the validity of the proposed approach. Twenty location variables relevant to five location aspects were examined, and the results indicated that latent knowledge can be identified to support location selection decisions.     

Unemployment in Greece: Evidence from Greek regions using panel unit root tests

The purpose of the paper is to examine the nature of Greek regional unemployment. The paper contributes to the literature assessing the stochastic properties of Greek unemployment rate in the context of the Greek regions by relying on various univariate and panel unit root tests. In particular, recently developed and more powerful panel unit-root tests that control for structural breaks, heterogeneity and cross-sectional dependence in the panel are employed. The results show that in all cases, after taking into account the fact that regional unemployment rates in Greece are subject to a structural break, the null hypothesis of a unit root is not rejected, indicating that the Greek regional unemployment series are non-stationary with the presence of a structural break.     

Travel and tourism competitiveness index: The impact of air transportation,railways transportation,travel and transport services on international inbound and outbound tourism

The objective of the study is to examine the impact of air transportation, railways transportation, travel and transport services on international inbound and outbound tourism in a panel of 19 tourists - oriented countries, over a period of 1990–2014. By applying principal component analysis, the study constructs travel and tourism competitiveness index for inbound and outbound tourism. The main constructs of inbound tourism index include international tourists' arrival, tourism receipts, receipts of passengers' transports items and travel items while the constructs of the outbound index include international tourists' departure, tourism expenditures, and expenditures for passengers transport and travel items. The result of panel Fully Modified OLS (FMOLS) regression shows that the presence of air transportation, railways transportation, and trade openness positively affect inbound tourism index, while travel and transport services negatively affect tourism competitiveness index. The causality results confirm the bidirectional relationship between inbound tourism, air transportation, railways passengers carried, trade openness and travel and transport services, while there is a unidirectional causality running from inbound index to railway goods transported, from air transport freight to trade factor, and from travel services to air transport freight. Outbound tourism index confirmed the bidirectional causality relationship with air transportation, railways transportation, and travel and transport services, while the causality running from outbound index to trade factor, from air transport passenger carried to travel services, and from railway goods transported to trade and transport services, which support the unidirectional causality relationship between them. The variance decomposition results show that air transportation freight is the contributor that largely influences inbound-outbound tourism, while railways passengers carried and trade openness has the least share to influence inbound and outbound tourism index for the next 10-year period. The impulse response function indicates that air transportation, railways transportation, trade openness and travel services will positively impact on inbound truism while travel and transport services will positively affect outbound tourism for the next 10-year period. The study concludes with the importance of transportation sector that deem desirable to promote tourism worldwide. The concentration of different modes of transportation including air transportation, railways transportation, and travel and transport system would helpful to advance international tourism.     

The Post-entry Performance of Cohorts of Export Starters in German Manufacturing Industries☆

This paper investigates four cohorts of firms from German manufacturing industries that started to export between 1998 and 2002, and follows them for five years after the start. Export starters are a rare species and small in Germany. Around 30–40% of those starters studied became continuous exporters. The share of total exports contributed by export starters of a cohort is tiny in the start year, and it remains so over the years that follow. Contrary to the market selection hypothesis, there is no evidence that productivity in the start year is systematically related to survival in the export market. There is no evidence of a negative impact of a smaller firm size in the start year on the chance of surviving in the export market. Starting with a higher share of exports in total sales, however, tends to increase the probability of continuing to export.     

含有中间变量的农村信用社可持续经营效率评价

本文借助含有中间变量的两阶段DEA评价方法对陕西省涉农地区不同信用社的可持续经营效率进行了评价。得出了大部分涉农地区基层信用社存在存款严重不足、发放贷款效率比吸收存款效率高、非利息支出过多、非利息收入不足等结论。     

数据生产理论——数据资源权利配置的基础理论

人类正在进入数据驱动的时代,数据成为社会的基础资源,但数据一直被认为处于公共领域并妨碍着数据权利化,困扰着数据资源利用秩序的建立。描述特定对象的数据并不是天然存在的,而是被生产出来的,并将数据价值（预测分析、发现新知）的实现过程界分为原始数据生产（采集）、数据集生产（汇集性处理）和数据分析（分析性处理）三种行为,并将前两个行为称为数据生产,提出数据生产理论。数据生产理论首先应区分数据生产和数据分析,原始数据的生产是建立在分析原材料提供者基础之上,应承认其价值并配置适当权利,以满足各种分析目的的数据集的生产。同时,数据生产还应区别数据来源,来源于个人的数据并不一定是个人生产的,只有个人在提供或创制了数据时才是数据的生产者。因此,数据生产理论是在将数据视为一种资源的情形下为数据上权利配置提供理论支撑,通过配置相应权利,构筑从原始数据生产者到数据集生产者,再到数据分析者的数据利用秩序。