Service-Oriented Computing for intelligent train maintenance

The purpose of this work is to apply the servicization of enterprise information systems in maintenance, particularly in the management of the maintenance process of the component parts of trains. Service Oriented Architecture (SOA) is an architectural approach that permits servicization since it provides a flexible set of design principles used during the modeling practices (abstraction and realization). With a view to supporting the model-driven engineering of software systems, Mode Driven Architecture (MDA) is a design approach delivering a set of guidelines for the configuring of specifications in systems development. Therefore, the combination of these two approaches can be fruitful to address the challenging issues the enterprise information system is facing today. Our study is based on a methodological approach using the MDA models for the automatic generation of web service. The case study concerns a Railways Maintenance Workshop (RMW) at Sidi Bel Abbes (Algeria). Finally, the information system for the management of maintenance of the component parts of passengers and baggage railcars, using the generated solution, is realized and deployed. This software helps to have better management of the RMW by the effective planning of interventions, improve performance by increasing reliability, traceability, and availability of the equipment (parts).     

Pairs trading strategies in a cointegration framework: back-tested on CFD and optimized by profit factor

Statistical arbitrage is based on pairs trading of mean-reverting returns. We used cointegration approach and ECM-DCC-GARCH to construct 98 pairs of 152 stocks of 3 currencies. Stocks trading is done by Contract for Difference (CFD), a financial derivative product which facilitates short selling and provides a leverage up to 25 times. To measure the performance of a leveraged strategy, we introduced the profit factor which is the annualized return rate per unit risk. And the historical risk is measured by maximum drawdown. We compared three main strategies: percentage, standard deviation of cointegration long-term residuals and Bollinger Bands (dynamic standard deviation), with and without double confirmation of short-term standard deviation modelled by ECM-DCC-GARCH. Each of the three main strategies is optimized by two optimizers: absolute profit and profit factor. The optimization period goes from 2012–01-01 to 2014–12-31, and validation period is from 2015–01-01 to 2016–06-01. Our results showed that the USD Bollinger Bands strategy without double confirmation and optimized by profit factor, outperformed other strategies and provided the highest annualized return rate per unit risk; 32% of our sample pairs ended up in loss, and 94% of which are explained by a cointegration break during the testing period.     

Far from the madding crowd: collective wisdom in prediction markets

We investigate market selection and bet pricing in a repeated prediction market model. We derive the conditions for long-run survival of more than one agent (the crowd) and quantify the information content of prevailing prices in the case of fractional Kelly traders with heterogeneous beliefs. It turns out that, apart some non-generic situations, prices do not converge, neither almost surely nor on average, to true probabilities, nor are they always nearer to the truth than the beliefs of all surviving agents. This implies that, in general, prediction market prices are not maximum likelihood estimators of the true probabilities. However, when more than one agent survives, the average price emerging from a prediction market approximates the true probability with lower information loss than any individual belief.     

Convex risk measures for the aggregation of multiple information sources and applications in insurance

We propose a novel class of convex risk measures, based on the concept of the Fréchet mean, designed in order to handle uncertainty which arises from multiple information sources regarding the risk factors of interest. The proposed risk measures robustly characterize the exposure of the firm, by filtering out appropriately the partial information available in individual sources into an aggregate model for the risk factors of interest. Importantly, the proposed risks can be expressed in closed analytic forms allowing for interesting qualitative interpretations as well as comparative statics and thus facilitate their use in the everyday risk management process of the insurance firms. The potential use of the proposed risk measures in insurance is illustrated by two concrete applications, capital risk allocation and premia calculation under uncertainty.     

多式联运数据交换区块链技术应用研究

针对多式联运数据交换中存在的数据中心化、作业协同效率不高等问题,对铁水联运、公铁联运过程中数据交换需求进行分析,阐述多式联运和区块链技术在数据共享、信任机制、安全机制和合约机制等方面的契合点,提出基于区块链的包括基础层、区块链核心层、应用服务层、应用接口和业务层的总体架构方案,设计基于联盟链的网络架构方式,模拟基于区块链技术的铁水联运运单流转过程,以实现共享数据的去中心化,提高多式联运作业的协同性和安全可靠性,促进多式联运"一单制"建设。     

基于变系数模型的我国资本流动审慎管理研究

本文采用事实测度法构建符合审慎特征的时变资本流动管理指标,并采用时变系数法考察了我国资本流动管理的有效性及其与短期资本流动的相关关系。研究发现,我国资本流动管理的有效性以2013年为界呈现出先减弱后增强的趋势。另一方面,仅依靠增强管理有效性而不增加管理强度难以有效防范突发事件冲击造成的大规模资本流动。此外,审慎型资本流动管理政策可以有效调控短期资本流动,且其对于资本流动的短期影响强于长期。     

Population ageing and inflation with endogenous money creation

This paper models a mechanism through which population ageing may induce a deflationary process. We propose an overlapping-generations model (OLG) with money created by credits (inside money) and intergenerational trade. The model links demographic factors, such as fertility rates and longevity, to prices. We show that lower fertility rates lead to smaller demand for credit and lower money creation, which in turn cause a decline in prices. Changes in longevity affect prices through real savings and the capital market. Furthermore, a few links between interest rates and inflation are addressed; they arise in the general equilibrium and are not thoroughly discussed in literature. Long-run results are derived analytically; short-run dynamics are simulated numerically.     

The new middle class in emerging markets: How values and demographics influence discretionary consumption

The rise of new middle‐class consumers in rapidly transforming emerging markets has attracted the attention of Western business executives. What they know about this growing segment of customers will determine whether they succeed or fail in these markets. The present study examines the factors that drive the discretionary consumption of this new middle class, including the effects of consumerist values, religious values, occupation, education levels, and ownership of fixed assets. The study draws its insights from data gathered from 391 new middle‐class consumers in Ankara, the second‐largest city in Turkey. The findings provide important implications for businesses, both indigenous and foreign. An overall implication is that managers ought to understand and qualify the new middle class in emerging markets not simply by their access to disposable income but by deeper attitudinal and behavioral characteristics.     

The role of psychological and socio-demographical factors for electric bike use in Norway

The electric bike (e-bike) is emerging as a new sustainable transport mode in Norway and has the potential to lead to increased cycling among the population. However, little is known about psychosocial determinants of e-bike use. The aim of the study was to examine the role of normative and environmental beliefs, the perceived attributes of e-bikes, and innovativeness and demographical factors related to e-bike use in a Norwegian sample. An online survey was used to collect data from 910 respondents, including both e-bike users (252) and non-users (658). The respondents were recruited via a commercial panel (response rate 42.04%) and a Facebook post. A structural equation modeling analysis was used to analyze the data. The structural model had a good fit to the data. The results showed that attitudes towards e-bike use followed by innovativeness were the most important predictors of e-bike use. The normative processes measured within the Norm Activation Model activated positive attitudes towards e-bike use, which in turn predicted e-bike use. There was a negative relationship between e-bike and conventional bike use, while a positive relationship was found between car and e-bike use. The results are discussed with regard to their implications for interventions aiming to promote e-bike use.     

农业创业情境下商业模式设计的影响机制研究——基于模糊集定性比较分析

农业创业者如何通过整合与管理资源与能力，设计新颖型商业模式创造更多价值，是实现乡村振兴战略的关键措施。文章基于资源编排、商业模式理论，以央视《致富经》栏目40个案例为样本，运用模糊集定性比较分析（fsQCA）方法，剖析资源编排、机会能力、创业学习所构成的前因变量组态对农业创业活动中商业模式设计的影响机制。研究发现，资源编排在农业创业活动中发挥不可或缺的关键作用；相较于资源结构化和资源捆绑，资源利用在新颖型商业模式设计中的作用更为突出；机会能力须与资源编排共同作用，方可实现新颖型商业模式设计；在资源编排作用缺乏时，创业学习的发挥有助于新颖型商业模式设计的形成。研究成果诠释了农业创业情境下资源编排、机会能力与创业学习对商业模式设计的影响机制，为开展农业创业活动提供指导。