Innere Bilder und beruflicher Lebensweg

This article gives an introduction into working with inner images. In the background of professional work and career there are inner images at work. They trigger which roles we take and which plays on which stages we choose or accept as meaningful. A Case study elaborately illustrates working with inner background images. Simple questions lead to relevant images, which influence professional life. A guide for interviewing and practical approaches can be found in the supplement.     

Unemployment,Vacancies and Unfair Dismissals

In most West European economies the annual number of grievance procedures settling individual complaints against unfair dismissals has been increasing since the 1960s. This development has very often been attributed to the enactment of legal regulations restricting the dismissal behaviour of firms. Econometric analyses using data from Germany and Great Britain show that labour market developments, namely the flow into unemployment and the vacancy rate, have a much stronger influence on the cyclical demand for grievance procedures than changes in the “legal infrastructure” of the labour market. Without denying the importance of institutional differences it appears that the individual costs of unemployment (which, ceteris paribus, rise as the flow into unemployment increases and the vacancy rate decreases) are superior predictors of the demand for grievance procedures than institutional changes strengthening or weakening employees' rights.     

Structural and Cognitive Aspects of Social Capital and All-Cause Mortality: A Meta-Analysis of Cohort Studies

Social capital covers different characteristics such as social networks, social participation, social support and trust. The aim of this study was to explore which aspects of social capital were predictive of mortality. Criteria for inclusion in the meta-analysis were: population based observational cohort studies (follow-up ≥5 years); study sample included the adult population; parts of social capital as the primary exposure variable of interest; reported a mortality outcome; and sample size >1,000 individuals. Twenty studies provided eligible data for the meta-analyses. A random effect model was used to estimate the combined overall hazard rate ratio effects of structural social capital such as social participation and social networks, and cognitive social capital including social support and trust in relation to mortality. The results showed that social participation and social networks were negatively associated with mortality. The impact of social networks attenuated somewhat when controlling for gender and age. While trust also appeared to be negatively associated with mortality, we remain cautious with this conclusion, since only two studies provided eligible data. Perceived social support failed to show a significant impact upon mortality. The findings suggest that people who engage socially and report frequent contacts with friends and family live longer.     

The impact of individual and collective reputation on wine prices: empirical evidence from the Mosel valley

Although of considerable practical importance, the separate impact of individual and collective reputation on firm performance (e.g. product prices) has not yet been convincingly demonstrated. We use a sample of some 70 different wineries offering more than 1,300 different Riesling wines from the Mosel valley to isolate the returns to individual reputation (measured by expert ratings in a highly respected wine guide) from the returns to collective reputation (measured by membership in two different professional associations where members are assumed to monitor each other very closely). We find that both effects are statistically significant and economically relevant with the latter being more important in quantitative terms than the former.     

Ein metrikbasierter Ansatz zur Messung der Aktualit?t von Daten in Informationssystemen

Due to the importance of using up-to-date data in information systems, this paper analyzes how the data quality dimension currency can be measured. Therefore, we design a probability based metric that allows for an objective and to a great extent automated assessment of data’s currency. In contrast to existing approaches, the resulting values of the new metric meet important requirements such as ratio scale and can be interpreted as probabilities. Hence, they can also be applied to calculate expected values for decision making in a methodically well-founded manner. Moreover, the metric can be adapted to the context of a particular application considering both, the specific characteristics of attribute values and supplemental data stored in the information system. The evaluation of the approach is based on six requirements for data quality metrics. Furthermore, the case of a mobile services provider illustrates the metric’s applicability and its practical benefit.     

Runtime and memory consumption analyses for machine learning R programs

R is a multi-paradigm language with a dynamic type system, different object systems and functional characteristics. These characteristics support the development of statistical algorithms at a high level of abstraction. Although R is commonly used in the statistics domain a big disadvantage are its runtime problems when handling computation-intensive algorithms. Especially in the domain of machine learning the execution of pure R programs is often unacceptably slow. Our long-term goal is to resolve these issues and in this contribution we used the traceR tool to analyse the bottlenecks arising in this domain. Here we measured the runtime and overall memory consumption on a well-defined set of classical machine learning applications and gained detailed insights into the performance issues of these programs.