Data-driven Kriging models based on FANOVA-decomposition

Kriging models have been widely used in computer experiments for the analysis of time-consuming computer codes. Based on kernels, they are flexible and can be tuned to many situations. In this paper, we construct kernels that reproduce the computer code complexity by mimicking its interaction structure. While the standard tensor-product kernel implicitly assumes that all interactions are active, the new kernels are suited for a general interaction structure, and will take advantage of the absence of interaction between some inputs. The methodology is twofold. First, the interaction structure is estimated from the data, using a first initial standard Kriging model, and represented by a so-called FANOVA graph. New FANOVA-based sensitivity indices are introduced to detect active interactions. Then this graph is used to derive the form of the kernel, and the corresponding Kriging model is estimated by maximum likelihood. The performance of the overall procedure is illustrated by several 3-dimensional and 6-dimensional simulated and real examples. A substantial improvement is observed when the computer code has a relatively high level of complexity.     

Determinants and effects of formal target agreements: an empirical investigation of German firms

We investigate organizational determinants and performance effects of formal target agreements for employees based on the IAB establishment panel, a representative panel of German establishments. The results show that establishments with a high employee turnover rate, a large proportion of temporary workers, and a highly qualified workforce are significantly more likely to implement target agreements. Also, establishments with works councils installed are more likely to do so, controlling, among others, for firm size. Concerning organizational performance, we apply a first-difference and a fixed effects approach and find that establishments that implement target agreements achieve around 5 % higher total sales compared to firms that did not introduce this practice. Hence, organizations seem to benefit from the implementation of formal target agreements for employees.     

Leadership and emotion management for complex tasks: Different emotions,different strategies

Emotions in the workplace influence a number of critical cognitive tasks including information processing and decision-making. Moreover, the effect of emotion on these operations is often emotion-specific. Given these unique effects, leaders may need to learn how to manage subordinates' discrete emotions, and not just general affect. This laboratory experiment examined the effects of leaders suggesting different regulation strategies after subordinates experienced anger or pessimism. Effects of these emotions under different leader-facilitated regulation strategies were evaluated with respect to planning, a critical organizational task, and perceptions of leader effectiveness. Results demonstrated that the type of leader-facilitated regulation strategy moderates the relationships of anger and pessimism to planning. The findings imply that leaders should understand the differential effects of discrete emotions, and be prepared to help subordinates manage emotions accordingly.     

Dynamic Reflections of Crimes,Quasi Democracy and Misery Index in Pakistan

Massive increase in crimes has coexisted with rising inflation and high unemployment for the last couple of decades especially during democratic governments in Pakistan. In this paper, we explore the relationship between crime rate, misery index and democracy in Pakistan from 1975 to 2013. Granger causality test proposed the unidirectional causality running from misery index to crime rate in Pakistan. Estimating the crime function via Pasaran’s conditional error correction model, we found the significant long run equilibrium relationship between Okun’s misery index and crime rate which implies that rising inflation and unemployment rate are the major driving forces towards increasing crime rates in Pakistan. Finally, empirical evidence from Okun’s misery index suggested that people are three times more miserable in quasi democratic periods than that of dictatorship. The Barrow’s misery index model verifies that people are twice worsening in quasi democratic periods. Likewise, reported crimes are nearly twice during quasi democracy than quasi dictatorship. The crime model provided the evidence that people during quasi democratic governments are more likely tending towards crime as compared to quasi dictatorship during the study period in Pakistan. This implicitly advocates the fact that half hearted efforts and ill structured apparatus of democracy can augment the tendency of crime and misery rather than solution of such concerns of the economy.     

Coaching,Training und Co – ist das alles Personalentwicklung?

This paper focuses on coaching and similar types of consulting in the field of personnel development. First the author discusses the current debate concerning personnel development; finally she describes the special goals, target-groups and issues of coaching, clinical supervision, mediation, mentoring and outplacement-consulting within the field of personnel development.     

Bounds for the traveling salesman paths of two-dimensional modular lattices

We present tight upper and lower bounds for the traveling salesman path through the points of two-dimensional modular lattices. We use these results to bound the traveling salesman path of two-dimensional Kronecker point sets. Our results rely on earlier work on shortest vectors in lattices as well as on the strong convergence of Jacobi–Perron type algorithms.     

Fibonacci helps to evacuate from a convex region in a grid network

This study considers an evacuation problem where the evacuees try to escape to the boundary of an affected area, which is convex, and a grid network is embedded in the area. The boundary is unknown to the evacuees and we propose an online evacuation strategy based on the Fibonacci sequence. This strategy is proved to have a competitive ratio of 19.5, which is better than the best previously reported result of 21.     

Generating synthetic data to produce public-use microdata for small geographic areas based on complex sample survey data with application to the National Health Interview Survey

Small area statistics obtained from sample survey data provide a critical source of information used to study health, economic, and sociological trends. However, most large-scale sample surveys are not designed for the purpose of producing small area statistics. Moreover, data disseminators are prevented from releasing public-use microdata for small geographic areas for disclosure reasons; thus, limiting the utility of the data they collect. This research evaluates a synthetic data method, intended for data disseminators, for releasing public-use microdata for small geographic areas based on complex sample survey data. The method replaces all observed survey values with synthetic (or imputed) values generated from a hierarchical Bayesian model that explicitly accounts for complex sample design features, including stratification, clustering, and sampling weights. The method is applied to restricted microdata from the National Health Interview Survey and synthetic data are generated for both sampled and non-sampled small areas. The analytic validity of the resulting small area inferences is assessed by direct comparison with the actual data, a simulation study, and a cross-validation study.     

Heterogeneity,school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model

With the aim of assessing the extent of the differences in the context of Italian educational system, the paper applies multilevel modeling to a new administrative dataset, containing detailed information for more than 500,000 students at grade 6 in the year 2011/2012, provided by the Italian Institute for the Evaluation of Educational System. Data are grouped by classes, schools and geographical areas. Different models for each area are fitted, in order to properly address the heteroscedasticity of the phenomenon. The results show that it is possible to estimate statistically significant “school effects”, i.e., the positive/negative association of attending a specific school and the student’s test score, after a case-mix adjustment. Therefore, the paper’s most important message is that school effects are different in terms of magnitude and types in the three geographical macro areas (Northern, Central and Southern Italy) and are dependent on specific students’ and schools’ characteristics.