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.     

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。     

Dynamic capabilities and high-tech entrepreneurial ventures’ performance in the aftermath of an environmental jolt

This paper contributes to studies on dynamic capabilities (DCs) by showing that a neglected environmental contingency – i.e. the occurrence of a jolt – shapes the DCs–performance relationship. We focus on high-tech entrepreneurial ventures because these are the firms that jolts affect most; in so doing, we also advance the understanding of DCs in the entrepreneurship field. We argue that, in the aftermath of an environmental jolt, the high-tech entrepreneurial ventures that use internationalization and new product development capabilities to modify their resource configuration and regain environmental fit enjoy better performance. Econometric estimates on a sample of 340 Italian high-tech entrepreneurial ventures confronting the consequences of the global economic crisis that began in 2008 confirm that separately using these two DCs has a positive performance effect. This effect is stronger for relatively smaller ventures. Interestingly, despite synergies should arise from the combined use of the two DCs, we do not detect any superadditive effects.     

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.     

融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法研究

挖掘特定产品的需求模式无法从整体掌握该类产品的市场特征；短生命周期体验品因缺乏历史销售数据，并且销售总量波动性极大，尤其需要从整体掌握销售总量与产品属性间关系的需求特征规律，但又难以挖掘，亟待提出适用于该类产品的需求特征模式挖掘方法。基于按销售总量分区后各区的需求特征的规律性，提出了一种按销售总量分区、以已有产品介绍集和销售总量为源信息、适用于新产品开发前使用、融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法。该方法包括基于内容分析法的产品属性挖掘方法和基于关联分析的产品属性关系模式挖掘方法。前者可以得到较全面的产品属性；后者能够构建不同销售总量区间内产品集的属性关系模式，得到各区间的产品属性关系网，获得高销售总量区间具备，但中、低区间不具备的属性关系模式，从而获得需求特征模式。通过不断更新产品介绍集和销售总量并迭代挖掘，该方法能够动态挖掘需求特征模式。最后利用2013至2016年国产犯罪和爱情类电影数据验证了该方法的可行性，并得到了这两类电影的产品属性及近年的需求特征模式，可用于指导这两类电影的创作。     

Managing the Risk of Aggressive Dog Behavior: Investigating the Influence of Owner Threat and Efficacy Perceptions

Aggressive behavior in pet dogs is a serious problem for dog owners across the globe, with bite injuries representing a serious risk to both people and other dogs. The effective management of aggressive behavior in dogs represents a challenging and controversial issue. Although positive reinforcement training methods are now considered to be the most effective and humane technique to manage the risk of aggression, punishment‐based methods continue to be used. Unfortunately, there has been little scientific study into the various factors influencing whether dog owners choose to use positive reinforcement techniques to manage aggression in their dogs. As such, current understanding of how best to encourage and support dog owners to use these methods remains extremely limited. This article uses a survey methodology based on protection motivation theory (PMT) to investigate the factors that influence owner use of positive reinforcement methods to manage aggressive behavior, in an attempt to understand potential barriers and drivers of use. In addition, the article provides an initial exploration of the potential role of wider psychological factors, including owner emotional state, social influence, and cognitive bias. Findings show that the perceived efficacy of positive reinforcement methods and the perceived ability of owners to effectively implement the technique are both key factors predicting future intentions and current reported use. Future interventions should focus on enhancing owner confidence in the effective use of positive reinforcement techniques across multiple scenarios, as well as helping owners manage their own emotional responses when they encounter challenging situations and setbacks.     

考虑重复购买因素的品牌竞争对新产品扩散的影响研究——基于小世界网络的仿真环境

在对品牌竞争影响要素分析的基础上，考虑重复购买在新产品扩散过程中的调节效应，构建以消费者微观采纳机制为核心的新产品扩散的阈值模型，在小世界网络仿真情境下，运用多智能仿真方法对品牌竞争与新产品扩散之间的影响关系进行分析，研究结果表明：转换成本对新产品扩散的速度和深度的影响存在一定的"条件区域"，在该区域之外两者不存在显著的影响关系；进入时间与两种竞争性品牌的扩散速度存在一致的负向的影响关系，而对两种竞争性品牌的扩散深度的影响方向则相反；在此过程中，重复购买系数起着一定的调节效应，会在一定程度上放大或缩小转换成本及进入时间对新产品扩散的影响效应。通过本文的研究，不仅可以进一步丰富和完善竞争性产品创新扩散的相关理论，也可以为企业的新产品推广实践提供决策支持。