Umgang mit Jugenddelinquenz

For the German Juvenile Delinquency Court Association (Deutsche Vereinigung für Jugendgerichte und Jugendgerichtshilfen e.V.), which comprises researchers and practitioners in the field alike, the Lower Saxony Crime Research Institute (Kriminologisches Forschungsinstitut Niedersachsen e.V.), one of the most important institutions in Germany, in 1998 has compiled a detailed study ?Exclusion, Violence and Delinquency in the Life of young people — children and adolescents as victims and perpetrators“, comprising an extensive review of the literature with extensive own research results. The study takes a politically clear position: juvenile delinquency declines in quantity and intensity. Contradictory findings are based on statistical bias. Consequently, the policy of decriminalization — putting educational before correctional measures — has to be vigorously continued. The study displays a wealth of statistical material — and a wealth of serious, sometimes unforgivable methodological mistakes. At several occasions the authors explicitly dump unwanted findings. The considerable discrepancies between the main text body and the executive summary for the hurried reader further undermines confidence in the professionalism of the authors.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

Bayesian adaptive dose‐escalation procedures for binary and continuous responses utilizing a gain function

One of the main aims of early phase clinical trials is to identify a safe dose with an indication of therapeutic benefit to administer to subjects in further studies. Ideally therefore, dose‐limiting events (DLEs) and responses indicative of efficacy should be considered in the dose‐escalation procedure. Several methods have been suggested for incorporating both DLEs and efficacy responses in early phase dose‐escalation trials. In this paper, we describe and evaluate a Bayesian adaptive approach based on one binary response (occurrence of a DLE) and one continuous response (a measure of potential efficacy) per subject. A logistic regression and a linear log‐log relationship are used respectively to model the binary DLEs and the continuous efficacy responses. A gain function concerning both the DLEs and efficacy responses is used to determine the dose to administer to the next cohort of subjects. Stopping rules are proposed to enable efficient decision making. Simulation results shows that our approach performs better than taking account of DLE responses alone. To assess the robustness of the approach, scenarios where the efficacy responses of subjects are generated from an E _max model, but modelled by the linear log–log model are also considered. This evaluation shows that the simpler log–log model leads to robust recommendations even under this model showing that it is a useful approximation to the difficulty in estimating E _max model. Additionally, we find comparable performance to alternative approaches using efficacy and safety for dose‐finding. Copyright © 2015 John Wiley & Sons, Ltd.     

An Experimental Test of Loss Aversion

This paper experimentally investigates a preference condition for loss aversion in the framework of cumulative prospect theory (CPT). We propose the concepts of absolute and relative loss premiums in order to measure the extent of loss aversion and to derive notions of increasing, constant, and decreasing loss aversion. While in only one of the 28 choice situations analyzed loss neutrality and loss seeking can be rejected, about 51% of all choices are loss averse and, due to the large extent of loss aversion revealed by these choices, the average loss premium is positive for most choice situations. Female subjects exhibit both a more frequent occurrence and a larger extent of loss aversion.     

Should I Stay or Should I Go? Explaining Turnover Intentions with Organizational Identification and Job Satisfaction*

The social identity approach is a powerful theoretical framework for the understanding of individuals' behaviour. The main argument is that individuals think and act on behalf of the group they belong to because this group membership adds to their social identity, which partly determines one's self‐esteem. In the organizational world, social identity and self‐categorization theories state that a strong organizational identification is associated with low turnover intentions. Because identification is the more general perception of shared fate between employee and organization, we propose that the relationship between identification and turnover will be mediated by job satisfaction as the more specific evaluation of one's task and working conditions. In four samples we found organizational identification feeding into job satisfaction, which in turn predicts turnover intentions.     

Drittmittel als Performanzindikator der Wissenschaftlichen Forschung

Resources within and between higher education and research institutions are increasingly allocated according to scientific performance. Evaluation exercises and the measurement of research performance take on a new role in this context. Third party research income is a performance indicator which is rather easy to measure and is used in most of the new performance-based evaluation procedures. This paper sets out to scrutinize the meaning and validity of third party research income. We studied research teams from three different research fields with a mixed quantitative / qualitative approach. The focus is on the causal relations between institutional / input indicators, third party research income as another input indicator, and a variety of output indicators of scientific production. An important result is that third party money has a positive effect on performance only below a certain and discipline-specific threshold. Further analysis shows that output performance is to a great extent field-specific. The context conditions for scientific production differ greatly, so that comparative performance assessments are only valid within homogeneous research fields. Another important result is that output performance is multidimensional and cannot be measured by bibliometric indicators only. These findings have implications for the rationality of the evaluation assessment exercises as well as for the funding decisions of science foundations, ministries of science and — increasingly, the heads of universities and departments. These topics are discussed in the last chapter as well as the implications for further research.     

Integration of Stochastic Effects and Data Uncertainties into the Design of Process Equipment

Stochastic effects and data uncertainties are present in any engineering calculation. Their impact may be particularly important if they concern the design of process equipment. A calculation model for the dynamic behavior of a heat exchanger and procedures to deal with the related uncertainties are presented. Their propagation through the calculation by means of a Monte Carlo approach is shown. The temperature at the heat exchanger outlet and the step response of a sudden variation in the heat exchanger inlet temperature are simulated and evaluated by way of example. It is demonstrated that the inclusion of stochastic effects and uncertainties provides a more reliable basis for design decisions and hence reduces the probability of errors.     

What is Loss Aversion?

A behavioral definition of loss aversion is proposed and its implications for original and cumulative prospect theory are analyzed. Original prospect theory is in agreement with the new loss aversion condition, and there utility is capturing all effects of loss aversion. In cumulative prospect theory loss aversion is captured by both the weighting functions and the utility function. Further, some restrictions apply for the weighting functions involved in the latter model.We are indebted to Michèle Cohen and Peter Wakker for helpful comments. The suggestions of an anonymous referee have improved the presentation of the paper.     

The Development of Students' Mathematics Self‐Concept in Relation to Gender: Different Countries,Different Trajectories?

Gender differences in the development of children's and adolescents' academic self‐perceptions have received increasing attention in recent years. This study extends previous research by examining the development of mathematics self‐concept across grades 7–12 in three cultural settings: Australia (Sydney; N=1,333), the United States (Michigan; N=2,443), and Germany (four federal states; N=4,688). Results of latent growth curve models document very similar patterns of self‐concept development in males and females in the three settings. First, gender differences in favor of boys were observed at the beginning of the observation period (grade 7). Second, gender was not significantly related to self‐concept change in either group, meaning that initial differences persisted across time. Third, the results provided no evidence that the form of the longitudinal change trajectories for mathematics self‐concept differed across the cultural settings. This pattern of results is inconsistent with explanatory models that predict converging or diverging gender differences in mathematics self‐concept. Furthermore, the results indicate that self‐concept development may be highly similar across western cultural settings.     

Insurance demand and social comparison: An experimental analysis

This paper analyzes whether social comparison can explain the low take-up of disaster insurance usually reported in field studies. We argue that risks in the case of disasters are highly correlated between subjects whereas risks for which high insurance take-up can be observed (e.g. extended warranties or cell phone insurance) are typically idiosyncratic. We set up a simple model with social reference points and show that in the presence of inequality aversion social comparison makes insurance indeed less attractive if risks are correlated. In addition we conducted a simple experiment which confirms these theoretical results. The average willingness to pay for insurance is significantly higher for idiosyncratic than for correlated risks.