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.     

Abusive Supervision and Well-Being of Filipino Migrant Workers in Macau: Consequences for Self-Esteem and Heritage Culture Detachment

Abusive supervision in the workplace has been shown to have important direct consequence in work and work relationship, and also indirect consequences to workers’ well-being and relationships outside work. Consequences of abusive supervision have not been studied among migrant workers whose status in the host country of work is dependent on maintaining the work contract. This study investigates abusive supervision in 247 Filipino migrant workers in Macau, who hold temporary work contracts and work visas to engage in various low-skilled work (e.g., domestic helper, security guard, etc.). The study tests a model representing the indirect consequences of abusive supervision on the self-esteem and acculturation orientation of migrant workers, in particular, on the tendency to reject their heritage culture in their attempt to acculturate in the host country. Mediation analysis indicated that abusive supervisory perceptions led to lower self-esteem (b = ?.19), which in turn relates to tendency to reject their heritage culture as part of acculturation (b = ?.45) [indirect effect = .08, 90 % CI .04, .15]. The rejection of heritage culture is interpreted as a coping response to the negative indirect consequences of abusive supervision perceptions that may be partly attributed to being a migrant Filipino worker. The results are discussed in terms of how the acculturation of migrant workers reflects aspects of their well-being that may be adversely affected by vocational-related stress in the host country.     

Multiple event times in the presence of informative censoring: modeling and analysis by copulas

Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

     

The mixed evacuation problem

A dynamic network introduced by Ford and Fulkerson is a directed graph with capacities and transit times on its arcs. The quickest transshipment problem is one of the most fundamental problems in dynamic networks. In this problem, we are given sources and sinks. Then the goal of this problem is to find a minimum time limit such that we can send the right amount of flow from sources to sinks. In this paper, we introduce a variant of this problem called the mixed evacuation problem. This problem models an emergent situation in which people can evacuate on foot or by car. The goal is to organize such a mixed evacuation so that an efficient evacuation can be achieved. In this paper, we study this problem from the theoretical and practical viewpoints. In the first part, we prove the polynomial-time solvability of this problem in the case where the number of sources and sinks is not large, and also prove the polynomial-time solvability and computational hardness of its variants with integer constraints. In the second part, we apply our model to the case study of Minabe town in Wakayama prefecture, Japan.     

The neglected mediating role of self-efficacy in the goal setting process in local public administrations

To analyse the role of self-efficacy in goal setting in public administrations, this study combines goal-setting theory, public service motivation literature and cognitive theory. Using partial least squares structural equation modelling (PLS-SEM), survey data from 105 German civil servants are analysed. The results underline the role of goal setting (represented by goal difficulty and specificity) in determining the self-efficacy of public servants. Public service motivation and goal specificity both increase public servants’ work performance; however, the effects of goal difficulty are negatively mediated by the employee’s self-efficacy. That finding reflects the central role of self-efficacy, which should not be ignored in the goal-setting processes of public administrations.     

Constructing Trustworthy Historical Narratives: Criteria,Principles and Techniques

Organizational scholars increasingly recognize the value of employing historical research. Yet the fields of history and organization studies struggle to reconcile. In this paper, the authors contend that a closer connection between these two fields is possible if organizational historians bring their role in the construction of historical narratives to the fore and open up their research decisions for discussion. They provide guidelines to support this endeavor, drawing on four criteria that are prevalent within interpretive organization studies for developing the trustworthiness of research: credibility; confirmability; dependability; and transferability. In contrast to the traditional use of trustworthiness criteria to evaluate the quality of research, the authors advance the criteria to encourage historians to generate more transparent narratives. Such transparency allows others to comprehend and comment on the construction of narratives, thereby building trust and understanding. Each criterion is converted into a set of guiding principles to enhance the trustworthiness of historical research, pairing each principle with a practical technique gleaned from a range of disciplines within the social sciences to provide practical guidance.     

Has Opposition to Immigration Increased in the United States after the Economic Crisis? An Experimental Approach

We employ two population‐level experiments to accurately measure opposition to immigration before and after the economic crisis of 2008. Our design explicitly addresses social desirability bias, which is the tendency to give responses that are seen favorably by others and can lead to substantial underreporting of opposition to immigration. We find that overt opposition to immigration, expressed as support for a closed border, increases slightly after the crisis. However, once we account for social desirability bias, no significant increase remains. We conclude that the observed increase in anti‐immigration sentiment in the post‐crisis United States is attributable to greater expression of opposition rather than any underlying change in attitudes.