Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Impression management techniques in crowdfunding: An analysis of Kickstarter videos using artificial intelligence

Crowdfunding entrepreneurs increasingly use videos to present their venture and themselves to potential investors. To do this effectively, they consciously or unconsciously use several impression management techniques. Based on human and automated (AI-based analysis) of technology-related videos, we determine which impression management techniques help crowdfunding creators to attract a higher number of backers and meet their financial targets. Our results indicate that self-presentation and exemplification techniques are positively associated with crowdfunding success, while intimidation is negatively related to crowdfunding success. Our findings show that automated analysis of videos using advanced AI can replace human coding since measures based on human coding become insignificant when AI-based measures are included in the analysis. This illustrates the insights companies can create through the large scale automated analysis of video content using AI, including outside of a crowdfunding context.     

No Room for Respectability: Boundary Work in Interaction at a Shanghai Rental

This article examines the dramaturgical challenges of doing boundary work for a group of college women living with non‐college women at an overcrowded rental. To regulate tenant conduct and maintain their sense of self‐worth, the college women engaged in defensive othering and constructed their identity as “high‐quality” people on the basis of their characterization of their less‐educated roommates as “low‐quality” people. Their strategy of gaining self‐worth at their roommates' expense violated basic rules of social interaction that require participants to give face to gain face. This study shows that, in addition to weakening group solidarity and reproducing social inequalities, defensive othering also undermines subordinates' effort to gain self‐worth in the co‐presence of other subordinates. A video abstract is available at http://tinyurl.com/yath4o65     

Perceptions of Risk and Vulnerability Following Exposure to a Major Natural Disaster: The Calgary Flood of 2013

Many studies have examined the general public's flood risk perceptions in the aftermath of local and regional flooding. However, relatively few studies have focused on large‐scale events that affect tens of thousands of people within an urban center. Similarly, in spite of previous research on flood risks, unresolved questions persist regarding the variables that might influence perceptions of risk and vulnerability, along with management preferences. In light of the opportunities presented by these knowledge gaps, the research reported here examined public perceptions of flood risk and vulnerability, and management preferences, within the city of Calgary in the aftermath of extensive flooding in 2013. Our findings, which come from an online survey of residents, reveal that direct experience with flooding is not a differentiating factor for risk perceptions when comparing evacuees with nonevacuees who might all experience future risks. However, we do find that judgments about vulnerability—as a function of how people perceive physical distance—do differ according to one's evacuation experience. Our results also indicate that concern about climate change is an important predictor of flood risk perceptions, as is trust in government risk managers. In terms of mitigation preferences, our results reveal differences in support for large infrastructure projects based on whether respondents feel they might actually benefit from them.     

人工智能时代企业管理变革的逻辑与分析框架

人工智能作为社会发展和技术创新的产物,已经成为新一轮科技创新和产业变革的核心驱动力,正在对世界经济、社会进步和人民生活产生极其深刻的影响。人工智能的商业应用会改变企业内部运作和生产经营的过程,为企业管理带来了诸多挑战和变革机遇。本文结合人工智能的特征与发展趋势,从管理对象、管理属性、管理决策和管理伦理四个方面对人工智能时代企业管理变革的逻辑进行了梳理,得出如下推论:第一,人工智能时代,被管理者将出现越来越多的"人工智能员工",以"社会人"为中心的管理理论和管理手段的适用性降低,如何管理"人工智能员工"以及协调人类员工与智能机器人的关系将对管理者提出挑战;第二,人工智能时代,管理属性不仅包括管理理论的科学性、管理实践的艺术性,还包括管理过程的技术性;第三,人工智能时代,将出现一批优秀的技术管理者,此时,技术管理者指的不是管理技术的人,而是掌握智能技术的管理者;第四,人工智能时代,管理者的决策环境得到优化,管理活动中的决策准则将由"满意决策"过渡为"最优决策";第五,人工智能时代,管理手段的智能化发展可能会加剧管理效率和管理伦理的冲突,管理者必须提升管理道德,经营过程中强化社会责任的履行;第六,随着人工智能技术发展,政府、社会团体和行业协会有必要从政策、法律与行业标准等多个方面构建人工智能发展伦理的多层次约束机制。     

信息不对称下理财产品刚性兑付成因研究

既然法律或者理财合同没有规定，为什么银行要对其发行的理财产品进行刚性兑付? 已有国内研究以定性分析为主，缺乏规范的模型分析; 已有国外研究或不能完全解释理财产品投资非标资产比例显著低于监管上限，或没有考虑银行理财产品存在事后信息不对称的现实，尚不能完全解释银行理财产品刚性兑付的成因。文章使用成本状态验证方法刻画关于到期收益的信息不对称，使用信息投资方法刻画关于银行努力程度的信息不对称，构建委托投资管理模型分析银行理财产品刚性兑付的形成机理。研究发现，刚性兑付有助于降低信息不对称导致的成本，从而增加银行收益; 当绕过监管的成本低于一定阈值时，刚性兑付便有利可图，银行因而选择刚性兑付。进一步分析表明，引入关于到期收益信息的不完美信号，有助于缓解激励问题、破解刚性兑付。     

基于问题解决的全面质量管理

指出了车间主管的角色在于创设工作场所，发挥员工潜力。归纳了4种类型的问题解决方法：自我否定，别人过错，鸵鸟型，问题解决型，分析了强有力车间的概念。依据全面质量管理标准，将其与问题解决相联系，给出了全面质量管理的特征，阐明了两者之间的关系。     

A Decision Framework for Managing Risk to Airports from Terrorist Attack

This article presents an asset‐level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast‐resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life‐cycle cost considering a 10‐year service period.     

论社区矫正中矫正地变更的若干问题

我国以社区矫正人员的居住地为矫正地。矫正地变更主要包括迁居型、暂离型、外出型三种类型。迁居型矫正地变更后，由新矫正地的社区矫正机构进行矫正；暂离型矫正地变更后，由现居住地矫正机构委托异地暂时居住地社区矫正机构进行矫正；外出型矫正地变更须由现矫正地社区矫正机构进行延伸矫正，并强化矫正措施。     

Paradoxes of risk management: Social responsibility and self-exclusion in Dutch casinos

This article deals with the basic contradictions of risk management and responsibility regarding problem gambling and self-exclusions, and draws special attention to the role knowledge production and science play in the construction and evaluation of gambling risks. This remarkable case of corporate social responsibility (CSR) is analyzed from a risk-governance perspective. It is grounded on a case study of the CSR practice of the Dutch casino monopoly, in particular the problem gambling mitigation and self-exclusion program of this corporation. The intentions and operations of this ‘responsible gambling’ practice constitute new business values and working norms. At the same time empirical evaluations of the self-exclusion program reveal that despite all the efforts put in the risk-management strategies, a significant part of the problem cannot be addressed at all. This points toward a major paradox of risk management. Overall the article highlights the ambiguous nature of risk management and responsible gambling.