Assertion and Consensus Motives in Argumentations

Fair and non-manipulative argumentation plays a key role in contemporary German ethics and business ethics. The purpose of this paper was to examine the question whether psychological dispositions for this type of communication do exist. In three empirical studies consisting of 839 subjects it was possible to establish four argumentative motives. Furthermore, the data show that these motives are correlated with basic personality traits. These motives have also implications for social integration, rationality, use of information, time demand, and interpersonal trust in business communication. In sum, fair and non-manipulative argumentation is a realistic tool for solving everyday ethical problems. Thus, discourse ethics is not only good for theory but also good for practice. This revised version was published online in July 2006 with corrections to the Cover Date.     

The Travelling Salesman Problem on Permuted Monge Matrices

We consider traveling salesman problems (TSPs) with a permuted Monge matrix as cost matrix where the associated patching graph has a specially simple structure: a multistar, a multitree or a planar graph. In the case of multistars, we give a complete, concise and simplified presentation of Gaikov's theory. These results are then used for designing an O(m3 + mn) algorithm in the case of multitrees, where n is the number of cities and m is the number of subtours in an optimal assignment. Moreover we show that for planar patching graphs, the problem of finding an optimal subtour patching remains NP-complete.     

Generalized additive models with unknown link function including variable selection

The generalized additive model is a well established and strong tool that allows modelling smooth effects of predictors on the response. However, if the link function, which is typically chosen as the canonical link, is misspecified, estimates can be biased. A procedure is proposed that simultaneously estimates the form of the link function and the unknown form of the predictor functions including selection of predictors. The procedure is based on boosting methodology, which obtains estimates by using a sequence of weak learners. It strongly dominates fitting procedures that are unable to modify a given link function if the true link function deviates from the fixed function. The performance of the procedure is shown in simulation studies and illustrated by real world examples.     

Linearizable special cases of the QAP

We consider special cases of the quadratic assignment problem (QAP) that are linearizable in the sense of Bookhold. We provide combinatorial characterizations of the linearizable instances of the weighted feedback arc set QAP, and of the linearizable instances of the traveling salesman QAP. As a by-product, this yields a new well-solvable special case of the weighted feedback arc set problem.     

On the personnel assignment problem

Recent papers have developed methods for personnel assignment under risk of failure. In this paper, a two-parameter model is given. It uses both mean and standard deviation in the stochastic model to bring the risk of failure under control.     

Criminal Behavior Associated with Pathological Gambling

The influence of addictive gambling behavior on criminal behavior was examined in this study. A sample of pathological gamblers from in- and outpatient treatment centers and self-help groups (n = 300) and a sample of high and low frequency gamblers from the general population and army (n = 274) completed a comprehensive questionnaire which assessed social attachment, personality, pathological gambling and criminal behavior variables. The causal analysis of a Lisrel Model leads to the following results: addictive gambling behavior is an important criminogenic factor. This predisposing factor alone cannot sufficiently explain criminal behavior associated with pathological gambling. Personality variables also directly influence the intensity of criminal behavior. Social attachment variables have only an indirect effect. As far as property offenses are concerned, it was found that the direct causal effect of addiction behavior is greater than that of personality.     

Beratung virtueller Teams im interkulturellen Kontext – ein Bericht aus der Praxis

Tasks are nowadays increasingly assigned to teams composed of members from different cultures who have to work together regardless of country borders or time zones. This causes special challenges for all parties involved in such work settings. Consultancy has accordingly to face the resulting increase of complexity: within the scope of an intercultural consulting process it becomes vital to take into consideration the often postulated focus on both differences and commonalities as well as to consider the dynamics within team processes. This article tries to reflect our work with “virtual teams” which consist of members having different cultures. We try to combine popular intercultural models with a systemic-constructivistic approach as well as with knowledge about group dynamics in order to make sure that a productive outcome is possible in a consulting process. In doing so we work on three levels: individual reflection with the participants’ own culture which is then combined with those of the other team members and then finally the group’s specific team culture is addressed and discussed. At the end of the article we summarize implications for consulting and management when working with virtual teams in an intercultural setting.     

Regression Analysis of Multivariate Binary Response Variables Using Rasch-Type Models and Finite-Mixture Methods

A model is considered for the regression analysis of multivariate binary data such as repeated-measures data (for example, panel data) or multiple-indicators with measures of some underlying characteristic such as attitude or ability (for example, surveys or tests). The model is related to the usual Rasch model, the usual latent-class model, and other familiar models such as logistic regression. In addition to a regression specification, the model includes parameters that describe heterogeneity not accounted for by the predictors. In contrast to most other approaches, a nonparametric specification of the latent mixing distribution is used, leading to a formulation based on scaled latent classes. We examine the relationship between this model and several other models, give a tractable formulation of the likelihood function and likelihood equations, present an algorithm for maximum-likelihood estimation, and analyze marginal and conditional latent structures. The approach is illustrated with longitudinal data from the German Socioeconomic Panel.