The negative spillover effect of food crises on restaurant firms: Did Jack in the Box really recover from an E. coli scare?

Despite the enormous impact of food crises on restaurants, limited understanding of their long-term impacts and associated factors has undermined crisis managers’ ability to handle crisis situations effectively. This article investigated the long-term impact of food crises on the financial performance of restaurant firms and identified the factors that influenced this impact. This explanatory study examined the case of Jack in the Box, whose 1993 Escherichia coli scare was the first and largest restaurant-associated food crisis in modern times. An event study method was used to uncover stock price movements of Jack in the Box, in conjunction with 73 unrelated food crises that occurred from 1994 to 2010. Stock prices of Jack in the Box exhibited significantly negative responses to other firms’ food crises, moreover, the negative spillover effect was stronger if the crisis occurred closer in time, was similar in nature, and was accompanied with no recall execution. These findings shed light on the long-term financial impact of food crises and offer insights for crisis managers to develop more effective crisis management strategies.     

Natural and anthropogenic influences on the year-round temperature dynamics of air and water in Postojna show cave,Slovenia

Air and groundwater temperatures were measured in a rimstone pool in Postojna Cave, to advise evaluation of the impact of natural and anthropogenic influences related to heat being initially transmitted into cave air by visitors. Such heat can accumulate both in the rock mass and in water. Results show that attention must be paid to temperature changes of rimstone pool water rather than those of cave air, especially during the winter. Thanks to good ventilation deep inside the cave, short-term air temperature increases related to higher visitor numbers have not influenced flowstone precipitation or the cave fauna. However, this situation might change if winter visitor numbers increased greatly. This study does not support a suggested increase in winter visits (currently the tourism low-season) and reduction of summer visits (currently the tourism high-season).     

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.     

目标价格改革试点对棉花市场的影响分析

[目的]通过分析棉花目标价格改革试点工作实施前后3年内(2011~2016年)棉花生产和需求变化情况,研究新疆目标价格改革对棉花市场的影响。[方法]运用3年滑动平均法,比较分析了棉花目标价格改革试点工作前后我国棉花产业的市场变化。[结果]自2014年棉花目标价格改革试点工作全面启动以来,生产方面:全国棉花种植结构日趋合理,新疆棉花种植优势明显,棉花市场价格形成机制初步建立,棉农利益得到了保护;市场需求影响方面:棉花价格逐步回归市场,国内外棉价差显著缩小,棉纺织企业经营状况趋于好转,棉花产业正在转型升级,但棉花市场整体需求不旺。[结论]试点工作取得了阶段性成效,但同时在信息化进程、棉花产业发展模式、生产力提升等方面暴露出一些问题亟待解决;下一步应进一步完善相关政策体系、加快棉花产业升级、加强科技创新,并推进信息化建设。     

区域产业发展视角的农业综合开发影响评估——基于对蔬菜产业的干预效应分析

【目的】通过定量方法准确评估农业综合开发对区域优势产业发展的影响有重要意义。【方法】从农业综合开发对蔬菜产业的项目干预效应入手,以县级为单位,将当年农业综合开发项目扶持内容包括蔬菜产业的县级单位划分为干预组,其他为控制组。采用可以有效解决样品选择偏差的倾向得分匹配方法,通过引入协变量、平衡检验、匹配等步骤,在控制组中找到与干预组成员单位特征相似的成员,构建反事实研究框架。【结果】结果得出,项目干预组比控制组区域的蔬菜播种面积占比高出1~3个百分点,说明农业综合开发项目对蔬菜产业的扶持对蔬菜播种面积的扩大有促进作用,利于蔬菜产业壮大。通过协变量影响力分析得出,地区的蔬菜生产优势是最重要的影响因素,从侧面证明了农业综合开发项目的扶持方向紧跟区域优势的政策宗旨。【结论】可见,通过有方向性的农业综合开发项目实施扶持特定产业对促进区域优势产业发展和实现农业结构优化是有效的。     

可行能力视角下农户参与农地整理规划的意愿与影响检验——基于安徽寿县4个典型镇的实证分析

[目的]提升农户参与的意愿与探寻有效参与机制。[方法]文章以安徽省寿县4个典型镇的147户农户与4个项目为调查对象,从农户的可行能力视角出发,运用Logistic模型研究农户参与农地整理规划意愿的驱动因素,运用ArcGIS10.0的空间分析功能检验农户参与对规划的影响。[结果]非农业收入比例、农地整理政策了解度、排灌沟渠布局、田间道路密度及公众参与机制等5类因素有显著推动作用;对规划的影响表现在较大程度优化了规划方案,提高了农地生产率等,但耕作田块扩大效应不显著、排灌沟渠存在空间集聚现象、偏好生产路建设及轻视田间林网工程建设等弊端制约了农业规模化经营、忽视规划全局性与环境效应等。[结论]可通过强化农地整理政策宣传力度、完善引导农户式的公众参与机制及基于农户可行能力视角构建农地整理规划效果的衡量尺度以提升农户参与的意愿与探寻有效参与机制。     

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.     

人- 组织匹配对创新行为的内在影响机制研究

员工是企业创新活动的主要实施者，其创新行为决定了创新的成败，但现有研究对员工创新行为的内在影响机制仍缺乏清晰刻画。本文基于社会认知理论，从心理因素的视角出发，探索人 - 组织匹配对创新行为的内在影响机制。通过收集数据，应用层次回归分析验证所提出的理论假设。结果表明，人-组织匹配不仅能对创新行为产生直接影响，还能够通过内部动机对创新行为产生间接影响。本文从理论上丰富了创新行为的相关研究，实践上为提升员工创新行为提出了对策建议。     

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.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.