The flood algorithm—a multivariate, self-organizing-map-based, robust location and covariance estimator

Self-organizing maps (SOMs) introduced by Kohonen (Biol. Cybern. 43(1):59–69, 1982) are well-known in the field of artificial neural networks. The way SOMs are performing is very intuitive, leading to great popularity and numerous applications (related to statistics: classification, clustering). The result of the unsupervised learning process performed by SOMs is a non-linear, low-dimensional projection of the high-dimensional input data, that preserves certain features of the underlying data, e.g. the topology and probability distribution (Lee and Verleysen in Nonlinear Dimensionality Reduction, Springer, 2007; Kohonen in Self-organizing Maps, 3rd edn., Springer, 2001).     

Evidence for the need to distinguish between self-initiated and organizationally imposed overload in studies of work stress

This study attempts to enhance our understanding of the inconsistencies reported in the literature concerning the relationship between work overload and work outcomes. We tested the proposition that work overload should be divided into two constructs based on its source: self-initiated overload (SIO), and organization-imposed overload (OIO). Based on the work stress and job crafting literatures, we expected that SIO and OIO would tend to relate differentially to the work outcomes of job satisfaction, emotional exhaustion, work–family conflict, job performance, and helping organizational citizenship behaviours. A study was conducted using three samples, the first consisting of full-time employed students in three countries (N?=?116), the second consisting of the nursing staffs of six private hospitals in Switzerland, and the third consisting of 161 middle manager–supervisor dyads in Switzerland. Two different measures of SIO and OIO were used. SIO was found to have a more beneficial relationship with the work outcomes than OIO, general supporting our hypothesis. Theoretical and practical implications are discussed.     

The aura of charisma: A review on the embodiment perspective as signaling

Charismatic leaders have consistently been shown to affect followers' performance, motivation, and satisfaction. Yet, what precisely constitutes charisma still remains somewhat enigmatic. So far, research has mainly focused on leader traits, leader behaviors, or the leader follower-relationship, and the subsequent consequences of each on followers' self-concepts. All of these approaches share the notion that leader charisma depends on an explicit interaction between leader and follower. With the present review paper, we extend extant theorizing by arguing that charisma is additionally informed by embodied signals that flow directly from either the leader or the immediate environment. We introduce the embodiment perspective on human perception and describe its utility for theoretically understanding the charismatic effect. Correspondingly, we review studies that show which concrete embodied cues can support the charismatic effect. Finally, we discuss the variety of new theoretical and practical implications that arise from this research and how they can complement existing approaches to charismatic leadership.     

DIMENSIONS OF MACROECONOMIC UNCERTAINTY: A COMMON FACTOR ANALYSIS

Uncertainty about the future course of the economy is a potential driver of aggregate fluctuations. To identify the distinct dimensions of uncertainty in the macroeconomy, we construct a large dataset covering all types of economic uncertainty. We then identify two fundamental factors that account for the common dynamics in this dataset. These factors are interpreted as macroeconomic uncertainty. The first factor captures business cycle uncertainty, while the second factor represents oil and commodity price uncertainty. While both types of uncertainty generate a decline in output, time‐varying oil and commodity price uncertainty is more important for fluctuations in real activity. However, nonlinearities seem to amplify the effect of business cycle uncertainty during the global financial crisis. (JEL C32, C38, E32)     

How Accurate are German Work-time Data? A Comparison of Time-diary Reports and Stylized Estimates

This study compares work time data collected by the German Time Use Survey (GTUS) using the diary method with stylized work time estimates from the GTUS, the German Socio-Economic Panel, and the German Microcensus. Although on average the differences between the time-diary data and the interview data is not large, our results show that significant deviations exist between these two techniques for certain types of individuals, especially those with long working hours and flexible work schedules. We also show that stylized work time estimates have insufficient variation to reproduce a true picture of working hours.