Bonuszahlungen an Geschäftsführungen: Wodurch werden Gerechtigkeitsurteile von Erwerbstätigen beeinflusst?

Managerial compensation in large companies is subject to many critical concerns; this holds particularly for bonus payments. Empirical evidence shows that nearly three quarter of the German population perceive managers’ incomes as unfairly high. Based on an own survey, we examine what drives fairness perceptions of bonus payments for managers: When do employees assess bonus payments for managers within their own company as unfairly high? Under which conditions do they accept high bonus payments? The analyses show that acceptance decreases with the estimated amount of bonus paid. It increases, however, if aspects of procedural and distributive justice are taken into account.     

Examination and visualisation of the simplifying assumption for vine copulas in three dimensions

Vine copulas are a highly flexible class of dependence models, which are based on the decomposition of the density into bivariate building blocks. For applications one usually makes the simplifying assumption that copulas of conditional distributions are independent of the variables on which they are conditioned. However this assumption has been criticised for being too restrictive. We examine both simplified and non‐simplified vine copulas in three dimensions and investigate conceptual differences. We show and compare contour surfaces of three‐dimensional vine copula models, which prove to be much more informative than the contour lines of the bivariate marginals. Our investigation shows that non‐simplified vine copulas can exhibit arbitrarily irregular shapes, whereas simplified vine copulas appear to be smooth extrapolations of their bivariate margins to three dimensions. In addition to a variety of constructed examples, we also investigate a three‐dimensional subset of the well‐known uranium data set and visually detect the fact that a non‐simplified vine copula is necessary to capture its complex dependence structure.     

Estimation of a linear model under microaggregation by individual ranking

Summary Microaggregation by individual ranking is one of themost commonly applied disclosure control techniques for continuous microdata. The paper studies the effect of microaggregation by individual ranking on the least squares estimation of a multiple linear regression model. It is shown that the traditional least squares estimates are asymptotically unbiased. Moreover, the least squares estimates asymptotically have the same variances as the least squares estimates based on the original (non-aggregated) data. Thus, asymptotically, microaggregation by individual ranking does not result in a loss of efficiency in the least squares estimation of a multiple linear regression model. I thank Hans Schneeweiss for very helpful discussions and comments. Financial support from the Deutsche Forschungsgemeinschaft (German Science Foundation) is gratefully acknowledged.     

Exploring Strategy Implementation Consistency Over Time: The Moderating Effects of Industry Velocity and Firm Performance

In this paper we empirically investigate the temporal development of a firm’s strategy implementation consistency (SIC), i.e. the alignment between firms’ resource allocation decisions (RAD) and their articulated corporate concept (Noda and Bower, 1996; Burgelman and Grove, 1996; Love et al., 2002; Mintzberg, 1978). Doing so, we test whether (1) SIC is more likely to increase or decline over time, (2) whether firms competing in (low) high-velocity environments in fact show different temporal patterns in SIC, and (3) whether overperforming firms succeed in conserving their level of SIC. For our analysis we draw on 6238 RAD of 20 publicly listed firms with European origin over a period of 4–6 years. Applying maximum likelihood ordered logit estimation, our results indicate that the likelihood of an alignment of RAD and a firm’s corporate concept decreases over time. In line with scholars’ perception of high-velocity environments, we find that the firms in our sample competing under such conditions show no clear trend in SIC. These firms tend to “zig-zag” over time – swaying off and pulling back to their strategic course independent of the timing of the announcement of a corporate concept. We also find that overperforming firms are unsuccessful in preserving their SIC at the same level over time. Based on the empirical findings the paper discusses implications for theory and derives suggestions for corporate level managers on how to balance SIC and strategic flexibility.     

The therapeutic misconception: a threat to valid parental consent for pediatric neuroimaging research

Neuroimaging research has brought major advances to child health and wellbeing. However, because of the vulnerabilities associated with neurological and developmental conditions, the parental need for hope, and the expectation of parents that new medical advances can benefit their child, pediatric neuroimaging research presents significant challenges to the general problem of consent in the context of research involving children. A particular challenge in this domain is created by the presence of therapeutic misconception on the part of parents and other key research stakeholders. This article revierws the concept of therapeutic misconception and its role in pediatric neuroimaging research. It argues that this misconception can compromise consent given by parents for the involvement of their children in research as healthy controls or as persons with neurological and developmental conditions. The article further contends that therapeutic misconception can undermine the research ethics review process for proposed and ongoing neuroimaging studies. Against this backdrop, the article concludes with recommendations for mitigating the effects of therapeutic misconception in pediatric neuroimaging research.     

The cost of not knowing the radius

Robust Statistics considers the quality of statistical decisions in the presence of deviations from the ideal model, where deviations are modelled by neighborhoods of a certain size about the ideal model. We introduce a new concept of optimality (radius-minimaxity) if this size or radius is not precisely known: for this notion, we determine the increase of the maximum risk over the minimax risk in the case that the optimally robust estimator for the false neighborhood radius is used. The maximum increase of the relative risk is minimized in the case that the radius is known only to belong to some interval [r _l ,r _u ]. We pursue this minmax approach for a number of ideal models and a variety of neighborhoods. Also, the effect of increasing parameter dimension is studied for these models. The minimax increase of relative risk in case the radius is completely unknown, compared with that of the most robust procedure, is 18.1% versus 57.1% and 50.5% versus 172.1% for one-dimensional location and scale, respectively, and less than 1/3 in other typical contamination models. In most models considered so far, the radius needs to be specified only up to a factor , in order to keep the increase of relative risk below 12.5%, provided that the radius–minimax robust estimator is employed. The least favorable radii leading to the radius–minimax estimators turn out small: 5–6% contamination, at sample size 100.      

Research evaluation and journal quality weights

Research evaluations based on quality weighted publication output are often criticized on account of the employed journal quality weights. This study shows that evaluations of entire research organizations are very robust with respect to the choice of readily available weighting schemes. We document this robustness by applying rather different weighting schemes to otherwise identical rankings. Our unit of analysis consists of German, Austrian and Swiss university departments in business administration and economics.     

Knowledge Management in Strategic Alliances: A Review of Empirical Evidence

Knowledge‐related and organizational learning processes in alliances have received much attention throughout the last 25 years. The field has generated a rapidly growing body of empirical evidence on how knowledge is managed in alliances. However, the sphere is highly complex, fragmented, incoherent, and heterogeneous in terms of the theoretical approaches applied. This paper presents an integrative and organizing framework for the empirical literature on knowledge management in strategic alliances. It illustrates how the knowledge management outcomes of knowledge creation, transfer and application are determined by four distinct sets of factors: knowledge characteristics, partner characteristics, partner interaction, and active knowledge management. Based on this framework, this review analyses and integrates empirical evidence in order to identify where findings converge and where results conflict. So far, research has focused strongly on singular interrelations between these four sets of factors and the transfer of knowledge. Conversely, the questions of how knowledge is created, retained, retrieved and applied and how the interplay of the different factors affects knowledge management in strategic alliances remain widely unexplored. The review concludes with a summary of the current state of the art in empirical research and discusses some promising avenues for future investigation.