Are EU trade preferences really effective? An impact evaluation assessment of the Southern Mediterranean Countries’ case

This work assesses the causal impact of the EU trade preferences granted to the Southern Mediterranean Countries (SMCs) in agriculture and fishery products over the period 2004–2014. It overcomes some of the weaknesses of previous assessments and presents several methodological improvements. Firstly, it relies on a continuous treatment – i.e. preferential margins – to capture the ‘average treatment effect’ of trade preferences, rather than on a binary treatment based on dummy variables. Secondly, it uses highly disaggregated data at sectoral level in order to evaluate properly the preferential treatment. Thirdly, it applies a non-parametric matching technique for continuous treatment – specifically, a generalized propensity score matching. The results show, on the one hand, that the impact of the EU preferences is positive and significant on SMCs trade and is better evaluated using impact evaluation techniques. On the other hand, they demonstrate that the relationship between preferences and trade flows is asymmetric and warn against the risk of providing too much of a good thing. These results raise important issues for policy-making. First, they demonstrate that raising the level of preferences is not the solution to foster the SMCs trade towards EU. Second, that the policy-makers should put more emphasis on complementary factors other than trade barriers.     

Is the protection of beach and dune vegetation compatible with tourism?

The paradox of development vs. protection and conservation of the coasts highlights the need to determine if tourism and conservation can be compatible rather than opposite activities. We analyzed the spatial and temporal changes in vegetation cover, composition and diversity in three beaches located in the state of Veracruz (Mexico) with different levels of tourism activity (Natural, Trailer Park and Hotels). We calculated tourist density and evaluated vegetation cover, species richness and diversity and analyzed the changes before and after three holiday seasons (winter, spring and summer). The Natural site had the highest vegetation cover (42.8 m²), species richness (14) and diversity (1.50), and Trailer Park the lowest (4.9 m², 8 species, and 0.897 respectively). The BACI (Before-After-Control-Design) analysis showed no significant differences before and after the holiday seasons. Our results show how low and medium density tourism can be compatible with the protection of beach and coastal dune vegetation.     

Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology

This research proposes a novel method of identifying and understanding the holistic overview of emerging technologies’ unintended consequences. Latent Semantic Analysis (LSA) text mining technique is employed to yield multiple groups of contextually similar terms from future-oriented data sources, comprising both experts’ and the public's concerns regarding future technologies. Resulting term clusters are considered as new abstractions, or so-called scenarios, of future social impacts. Furthermore, the study acquires greater depth and breadth in conceptualizing social impacts through considering condition- and value-related terms as key linking factors to previous social impact-related literature. Our proposed methodology seeks to gain insights into the utilization of future-oriented data sources for the foresight activity, hoping to mitigate public skepticism and pursue a better social acceptance of emerging technologies.     

Vision (im)possible? The effects of in-store signage on customers’ visual attention

We used two eye-tracking field experiments to investigate the extent to which in-store signage is used during navigation and decision making, and how the viewing of signage influences customers’ visual attention and choice behavior. One hundred and seventy-five customers at a grocery store were exposed to signage stimuli while carrying out predefined shopping tasks. Experiment 1 shows that attention toward signage is affected by customers’ levels of store familiarity and in-store search stage (navigation vs. decision making). Experiment 2 demonstrates that signage has a considerable impact on the direction and magnitude of customers’ visual attention during decision making.     

The effects of oil price shocks on inflation in the G7 countries

This study examines the effects of three types of oil price shocks on inflation in the G7 countries with a new method of isolating oil price shocks. Based on monthly data from January 1997 to January 2019, we find that each oil price shock has the largest effect on U.S. inflation among the G7 countries and each country’s response to oil price shocks is different. Moreover, a rolling-window analysis shows that supply shocks, demand shocks and risk shocks have dynamic effects on inflation. The effect of supply shocks on inflation is strong before the financial crisis, but weakens during the crisis. However, the effect of demand shocks increases sharply in this time. The effect of risk shocks mainly occurs during the financial crisis and the European debt crisis. In addition, this study uses two ways to verify the robustness of the results. Our empirical results have important implications for policymakers and manufacturers, since the results provide a good explanation for the response of inflation in the G7 countries to the oil price shocks from different sources.     

较差质量数据下的返回弹道计算及对落点影响的分析

针对某老式卫星返回时雷达跟踪数据曾发生的测量异常及质量较差等情况，为解决此类数据在返回弹道及落点计算中出现的实际困难以及给出应对措施，基于工程实际情况给出了三种不同建模类型下的弹道计算方法——当前统计解耦扩展卡尔曼滤波（EKF）、动力学建模无迹卡尔曼滤波（UKF）、多项式滑窗最小二乘估计算法，并应用该次质量较差的实际观测数据进行了算法应用效果分析与落点计算情况对比，对计算中的经验及教训进行了总结。研究结果表明，所给出的三种算法在面对较差质量数据时性能差异较大，在工程实际应用中可考虑将多种算法互为参考。研究结果及其经验教训对卫星返回弹道及落点的实时估计的工程实施有一定的参考价值。     

Optimal order display in limit order markets with liquidity competition

Order display is associated with benefits and costs. Benefits arise from increased execution-priority, while costs are due to adverse market impact. We analyze a structural model of optimal order placement that captures trade-off between the costs and benefits of order display. For a benchmark model of pure liquidity competition, we give a closed-form solution for optimal display sizes. We show that competition in liquidity supply incentivizes the use of hidden orders to prevent losses due to over-bidding. Thus, because aggressive liquidity competition is more prevalent in liquid stocks, our model predicts that the proportion of hidden liquidity is higher in liquid markets. Our theoretical considerations ares supported by an empirical analysis using high-frequency order-message data from NASDAQ. We find that there are no benefits in hiding orders in il-liquid stocks, whereas the performance gains can be significant in liquid stocks.     

The repercussions and challenges of COVID-19 in the hotel industry: Potential strategies from a case study of Indonesia

The COVID-19 pandemic has hit the tourism and hospitality sector hard. Hotel managers face uncertainty in this environment in order to survive. This study explores the impact of COVID-19 on the hospitality industry, particularly hotels in Indonesia, one of the largest developing countries. It examines the challenges faced by hotel managers and the strategies used to survive. Through the lens of complexity theory, we discuss whether the strategies being deployed are beneficial, redundant, or detrimental for hospitality businesses. Based on semi-structured interviews with 13 hotel managers in Jakarta, Bandung, and Bali, the findings shed light on the various challenges to hotels. We also highlight which challenges could turn into opportunities. The findings show that the strategies that managers are deploying could be detrimental in the future. Potential future research directions are also discussed.     

新冠肺炎疫情对中小微外贸企业的影响及对策

突如其来的新冠肺炎对全球经济造成了很大的影响,我国对外贸易当然更是无法幸免。但总体而言,笔者认为,短期影响虽然十分严重,但正在逐步消弭;中期影响需要认真对待,损失基本可控;长期影响更加深刻,但是依然可以化解——我国以及我省对外经济贸易总体向好的态势有望保持。然而,面广量大的中小微外贸企业原本就身体单薄,这场突如其来的疫情,无疑又是雪上加霜,日子更加艰难,亟待关注与帮扶。     

Drivers of research impact: evidence from the top three finance journals

We study the characteristics of all published papers in the top three finance journals (JF, JFE and RFS), and how these paper characteristics affect the number of citations in Google Scholar and the Web of Science database. First, we find the characteristics in the universalist perspective remain constant while the characteristics in the constructivist and presentation perspectives increase over time. Second, some characteristics are significantly different between the high-impact and the low-impact papers. Third, paper quality, research method, journal placement and paper age are the most important drivers. Last, different drivers play different roles in different journals.