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 in corporate annual reports during the global financial crisis

This paper analyses impression management (IM) during the global financial crisis (GFC). It examines the differences in multiple textual characteristics and attributions between a highly positive performance period (2002–2007) and the GFC period (2008–2012), within the setting of Spain, where these two economic cycles were extreme. In contrast to previous research, companies' extreme poor performance in our sample is driven by an exogenous event. The findings do not show clear evidence of IM based on textual characteristics specifically linked to the GFC. Companies tried not to use overt IM and, to some extent, tried to clarify the impact of the crisis on performance. They were under great scrutiny and probably preferred to tell a more careful story. However, a general pattern of IM was still present during the GFC in the form of consistent positive attributions, favourable benchmarks and enhancement practices. In essence, the crisis did not fully stop IM practices, but rather influenced the way IM was produced. Overall, our results show that IM was lower during the GFC than in the case of poor performance in normal macroeconomic conditions found by previous literature. The results also show that the narratives of firms in the finance and real estate sectors were the most reactive to the GFC, probably linked to their key role in the crisis.     

How do policy levers shape the quality of a national health system?

Poor quality of care may have a detrimental effect on access and take-up and can become a serious barrier to the universality of health services. This consideration is of particular interest in view of the fact that health systems in many countries must address a growing public-sector deficit and respond to increasing pressures due to COVID-19 and aging population, among other factors. In line with a rapidly emerging literature, we focus on patient satisfaction as a proxy for quality of health care. Drawing on rich longitudinal and cross-sectional data for Spain and multilevel estimation techniques, we show that in addition to individual level differences, policy levers (such as public health spending and the patient-doctor ratio, in particular) exert a considerable influence on the quality of a health care system. Our results suggest that policymakers seeking to enhance the quality of care should be cautious when compromising the level of health resources, and in particular, health personnel, as a response to economic downturns in a sector that traditionally had insufficient human resources in many countries, which have become even more evident in the light of the current health crisis. Additionally, we provide evidence that the increasing reliance on the private health sector may be indicative of inefficiencies in the public system and/or the existence of features of private insurance which are deemed important by patients.     

Local mobilisations and the formation of environmental networks in a democratizing Tunisia

ABSTRACT

This study examines the environmental protests that occurred in Tunisia after the 2011 uprisings. It analyses the factors underpinning the rise of the environmental networks during the period of transition (2011–2014). It details the mobilising strategies that were crucial for the networks’ growth or survival during this period of institutional instability. The study shows how networks leaders were able to bring together social and political actors from different backgrounds and ideological orientations. It is argued that the ability of networks to develop new distinctive collective identities was crucial for network sustainability. Those networks and actors who did not develop new clearly defined environmental identities and continued to rely importantly on pre-existing (authoritarian) structures and practices were more negatively impacted by ideological cleavages and political calculations. Empirically, the contribution builds on interviews and observations, as well as documents collected from Tunisian municipalities between 2013 and 2015. Conceptually, the research proposes a bottom-up perspective that highlights the interplay between micro- and macro-dynamics and strategies during a political transition. The analysis details the actors’ capacity to build alliances via interpersonal relations at the micro level, and their strategies to engage with institutional actors and processes.     

客户集中度、市场环境与存货管理效率

客户处在供应链的下游,对企业存货的采购、生产和销售都会产生重要影响,而多变的市场环境也在无形当中影响着客户与企业之间的关系。从企业所处行业、地区产品市场和客户三个角度所带来的市场环境变化入手,采用2011—2017年我国沪深两市A股制造业上市公司的数据,实证分析客户集中度与企业存货管理效率之间的关系。研究发现:(1)客户集中度越高,企业存货管理效率越高；(2)产品市场竞争力度越强,客户集中度对企业存货管理效率的影响越大；(3)产品市场发育越好,客户集中度对企业存货管理效率的影响越大。进一步研究发现,当企业因客户生产经营原因导致需求发生较大变化时,客户集中度对企业存货管理效率的正向影响更加显著。研究结论表明,政府应当注重市场竞争力的提升和良好经营环境的建设,使得企业在维护客户关系的同时充分发挥客户集中度对企业存货管理效率的积极作用。     

地方高校推行教师学术休假制度的现实意义与实施策略

教师学术休假是促进教师专业发展的重要形式，是教师自我完善的需要，是提升教师理论水平、科研能力和教学技能的主要手段，是提高教学质量的有效途径。探讨地方高校推行学术休假制的必要性，提出地方高校推行学术休假的建议，对地方高校教师队伍建设具有重要的现实意义。在实施策略上，应注重4个方面：（1）明确参加学术休假的对象主要是教师和教学科研人员；（2）根据教师职业发展的阶段性确定学术休假的时间；（3）合理设置学术休假人员遴选条件，首先应考虑为工作满5年以上的青年教师提供学术休假，其次应考虑为高级职称教师提供学术休假；（4）明确学术休假期间的教师待遇，并加强对学术休假人员的管理。     

基于质量意识的复杂产品质量控制激励策略

激励在复杂产品供应链中对主供协同合作关系及质量控制发挥了重要作用。本文研究基于主制造商在复杂产品生产研发前按照客户要求形成的质量意识的激励策略是否可以实现复杂产品质量控制问题。考虑具有质量意识的主制造商和其系统供应商组成的两级供应链，建立以主制造商为领导者的Stackelberg博弈模型，分别讨论无激励和存在激励时的主供生产最优决策。基于激励方式的不同，将激励策略分为根据供应商产品质量水平激励以及根据主制造商质量意识水平激励两种方式。研究结果表明激励是供应商加强协同合作、改进产品质量的内在动力，主制造商根据质量意识激励供应商可以进一步促使双方协同合作，提高产品质量，使双方获得更高的利润从而实现供应链整体利润最大化。此外用灵敏度分析发现提高主制造商质量意识水平可以增加双方协同合作努力程度，有效提升产品质量水平并实现帕累托改进。     

医疗信息共享对患者转移数量和服务质量水平影响研究

当前我国医院间存在严重的"信息孤岛"，医院参与医疗信息共享意愿不高，患者的诊疗信息被静态碎片化储存而无法充分有效地利用。考虑到医院进行医疗信息共享将降低患者转移成本，本文构建一个多阶段双寡头动态博弈模型研究医疗信息共享对医院竞争过程中患者转移数量和服务质量水平决策的影响。首先，根据是否存在转移成本，将患者分为新患者和经验性患者，借助Hotelling模型刻画患者的效用函数，分析患者就诊决策。然后，在政府价格规制和不考虑医院利他性情景下，构建了医院累积期望收益目标函数，使用动态规划方法，求解实现医院累积期望收益最大化的服务质量水平，获得了实现患者相互转移且医院在市场中共存的马尔可夫完美均衡。最后，根据医院参与医疗信息共享后患者转移成本降为零，分析与比较信息共享前后患者转移数量和服务质量水平变化。研究发现：在不同医院间本身存在患者转移背景下，医院参与信息共享后，患者转移数量增加但存在一个上限，增加的转移量与患者在医院间的转移成本呈正相关，与初始感知效用的差值范围呈负相关；医院参与信息共享后，均衡状态下的医院服务质量水平高于信息共享前的服务质量水平。因此，在不改变当前医保支付方式下，要加快推进医疗信息共享，政府部门可以根据医院的患者数量和服务质量水平变化对其进行定期补贴，以激励医院积极参与医疗信息共享，本文给出了这个补贴的量化表达。     

Impact of competitive conditions on supplier evaluation: a construction supply chain case study

This research proposes a multi-criteria decision-making (MCDM) framework and demonstrates the impact of competitive conditions on supplier evaluation process for construction supply chains. The paper focuses on the supply chain of a large-scale housing project in order to illustrate the role of competitive capability and suppliers’ profile and its influence on supplier evaluation based on prevailing supply/market conditions. Various scenarios are investigated to demonstrate the impact of competition on supplier evaluation. The contribution of the study lies in highlighting the impact of supply/market conditions on MCDM decisions causing supplier evaluation ‘imbalance’ and MCDM usage. It is expected that the study will be useful for project management, construction, supply chain management, sourcing professionals. The findings of the study are generalisable to projects-based situations such as petroleum refinery and ship building where bill of materials typically consists of thousands of items and a large number of suppliers are involved.