Co-constructing a Conceptual Understanding of System Enactment

Clinical Social Work Journal - System enactments are co-created phenomena characterized by confounding and emotionally charged multi-person interactions that emerge through the convergence of...     

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.     

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。     

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.

     

Benevolence-dominant,authoritarianism-dominant,and classical paternalistic leadership: Testing their relationships with subordinate performance

We propose a new typology of paternalistic leadership styles based on how leaders demonstrate authoritarianism and benevolence, the two essential components of this type of leadership. Benevolence-dominant paternalistic leadership refers to leaders' sole dependence on the use of benevolence without their strong assertion of authority, whereas authoritarianism-dominant paternalistic leadership is based mainly on authoritarianism itself; classical paternalistic leadership, which best fits early observations of paternalistic leaders, refers to the salient combination of both leadership components. We used two distinct samples and methods to test this typology and the association with subordinate performance. Across the two studies, a field investigation with Taiwanese military supervisor-subordinate dyads and a hypothetical scenario experiment with U.S. working adults, we found a positive relationship between classical paternalistic leadership and subordinate performance as strong as that between benevolence-dominant paternalistic leadership and performance. Our findings echo the phenomenon that paternalistic leaders tend to combine benevolence with authoritarianism to affect subordinate performance.     

Leader-member exchange as a linking pin in the idiosyncratic deals - Performance relationship in workgroups

In the current investigation, idiosyncratic deals (i-deals; individualized work arrangements) are modeled as differentiated resources that shape leader-member exchange (LMX) relationships in workgroups. We integrate literature on leader-member exchange (LMX) with research on i-deals to argue that employee evaluations of i-deals received from the grantor –typically the leader- enhance employee perceptions of LMX, which in turn become instrumental in generating positive performance outcomes. Furthermore, because workgroup characteristics have potential implications on the relationship between a deal grantor and the deal recipient, drawing upon social identity theory of leadership, we reason that the i-deals-LMX relationship is affected by the overall value congruence among the group members. Cross-level moderated mediation analyses on multi source data obtained from 289 employees nested in 60 workgroups showed that the mediational role of LMX in the i-deals to performance outcomes relationship was weaker in high value congruence groups.     

LGBTQ Women,Appearance Negotiations,and Workplace Dress Codes

The purpose of this study was to explore LGBTQ women’s experiences with unwritten or formal dress codes at work. I asked: What are LGBTQ women’s experiences in the workplace with appearance management, and what are LGBTQ women’s experiences navigating the written and unwritten dress codes in the workplace? To answer the research question, interviews were conducted with 24 self-identifying LGBTQ women. Six key themes emerged from the data. Themes included (1) expressed sexual identity in appearance, (2) unwritten dress codes in work environments did not always allow for expression of sexual identity in appearance, (3) motivations for pressure or desire to conceal expression of sexual identity in appearance at work, (4) negotiations of revealing or concealing sexual identity in appearance in the workplace impacted levels of comfort and confidence, (5) verbal and nonverbal negative experiences related to appearance at work, and (6) received compliments about appearance at work.