Bias in interview judgments of stigmatized applicants: a dual process approach

The abundance of research on interview discrimination has resulted in the conventional wisdom that stigmatizing applicant characteristics elicit biased interview judgments. Although this finding is robust across a wide variety of stigmatized groups, and despite the social importance of this effect, currently we lack understanding of the processes driving these biased decisions. The present dissertation contributes to the literature on personnel selection by investigating the mechanisms that drive bias in the job interviewer’s decision-making process. This dissertation starts by presenting an overview of the current understanding of interview bias, and highlights the challenges that need to be addressed by future research. Next, building on research from social- and cognitive psychology, a dual-process framework of interview bias is presented. Propositions from this framework will guide the present dissertation and will be investigated in several empirical studies. The introduction concludes with an overview of the chapters and empirical studies of this dissertation

Application of knowledge network analysis to identify knowledge sharing bottlenecks at an engineering firm

The knowledge of an organization’s employees is a valuable asset. Therefore organizations should ensure that their employees share their knowledge among each other. Knowledge exchanges between employees can be modelled as a network of relationships. To study these networks we have developed the Knowledge Network Analysis technique, which is based on Social Network Analysis and supports visual as well as quantitative analysis of knowledge networks. The goal of this technique is to identify bottlenecks in knowledge sharing in a particular knowledge area. In this paper we present the results of the application of Knowledge Network Analysis in an explorative case study. The goal of the case study is to explore the usefulness of Knowledge Network Analysis in identifying knowledge sharing bottlenecks. The case study results in a deeper understanding of how to translate the characteristics of the knowledge network and the employees in this network to the context of the case study organization. Moreover, the case study results have also been used to formulate recommendations to improve knowledge sharing at the case study organization

Bed level motions and sheet flow processes in the swash zone: Observations with a new conductivity-based concentration measuring technique (CCM+)

Detailed measurements of bed level motions and sheet flow processes in the lower swash are presented. The measurements are obtained during a large-scale wave flume experiment focusing on swash zone sediment transport induced by bichromatic waves. A new instrument (CCM+) provides detailed phase-averaged measurements of sheet flow concentrations, particle velocities, and bed level evolution during a complete swash cycle. The bed at the lower swash location shows a clear pattern of rapid erosion during the early uprush and progressive accretion during the middle backwash phase. Sheet flow occurs during the early uprush and mid and late backwash phases. Sheet flow sediment fluxes during these instances are highest in the pick-up layer. Sediment entrainment from the pick-up layer occurs not only during instances of high horizontal shear velocities but also in occurrence of wave–backwash interactions. As opposed to oscillatory sheet flow, the pivot point elevation of the sheet flow layer is time-varying during a swash event. Moreover, the upper sheet flow layer concentrations do not mirror the concentrations in the pick-up layer. Both differences suggest that in the lower swash zone the dynamics of the upper sheet flow layer are not only controlled by vertical sediment exchange (such as in oscillatory sheet flows) but are strongly affected by horizontal advection processes induced by the non-uniformity of the flow

Large deviations for the total queue size in non-Markovian tandem queues

We consider a $d$-node tandem queue with arrival process and light-tailed service processes at all queues i.i.d. and independent of each other. We consider three variations of the probability that the number of customers in the system reaches some high level $N$, namely during a busy cycle, in steady state, and upon arrival of a new customer. We show that their decay rates for large $N$ have the same value and give an expression for this value