Why does organizational identification relate to reduced employee burnout? The mediating influence of social support and collective efficacy

Although prior studies have consistently shown that organizational identification can reduce employees' stress and burnout, little is known about the mediating processes that underlie this relationship. Against this backdrop and building on recent theoretical work on the social identity model of stress, the present research tests a two-step mediation model for the organizational identification–burnout link. Specifically, it is hypothesized that employees who strongly identify with their organization are particularly likely to receive social support from their colleagues. This, in turn, should promote a sense of collective efficacy and, as a consequence, negatively relate to burnout. Data from a study with 192 Italian high schoolteachers supported the hypotheses.     

Anticipated (Grand-)Parental Childcare Support and the Decision to Become a Parent

Based on a cost-reduction argument, this study explored whether anticipated childcare support from their mothers influenced adult daughters’ decisions to have their first child. Using six waves of the German Family Panel (pairfam), discrete-time hazard models (N = 3155 women) were estimated for the transition to the decision to have the first child. Anticipated childcare support from the women’s mothers was approximated by the travelling distance between adult daughters and their mothers, a measure whose suitability was tested empirically. The results indicated that women in a position to anticipate having access to childcare support in the future decided to make the transition to parenthood earlier. This finding highlights both the strength of social interaction effects on fertility decision-making and the importance of intergenerational relationships for individual fertility histories already at their very beginning.     

Applying multivariate techniques to high-dimensional temporally correlated fMRI data

In first-level analyses of functional magnetic resonance imaging data, adjustments for temporal correlation as a Satterthwaite approximation or a prewhitening method are usually implemented in the univariate model to keep the nominal test level. In doing so, the temporal correlation structure of the data is estimated, assuming an autoregressive process of order one.We show that this is applicable in multivariate approaches too - more precisely in the so-called stabilized multivariate test statistics. Furthermore, we propose a block-wise permutation method including a random shift that renders an approximation of the temporal correlation structure unnecessary but also approximately keeps the nominal test level in spite of the dependence of sample elements.Although the intentions are different, a comparison of the multivariate methods with the multiple ones shows that the global approach may achieve advantages if applied to suitable regions of interest. This is illustrated using an example from fMRI studies.     

Gender, Nonstandard Work Schedules, and Marital Quality

Relatively few studies have focused on the effects of working late and rotating shifts on marital dynamics. This study addressed the limitations of prior studies by sampling from a sector of the economy (i.e., grocery and drug store workers) where shift work and rotating schedules were common, and by controlling for numerous accompanying disruptive effects of shift work on marital quality. Results show that working late shifts reduces marital quality among men, whereas among women, job-family spillover explained away marital quality effects of working rotating schedules. These results suggest that more than men, women remain largely responsible for family life irrespective of work schedules, yet further research on how family lives are affected by work schedules is needed.     

User acceptance of cooperative maneuver-based driving--a summary of three studies

Modern cars offer drivers support with the help of a number of driver assistance systems. Those systems aim to relieve drivers through assumption of sub parts of the driving task (e.g. in case of an Adaptive Cruise Control by regulation of vehicle speed and time gap to preceding vehicle). Today, systems are controlled and monitored separately which leads to efforts to combine the functionality of all systems in an overlying assistance for drivers. The approach of the University of Technology Darmstadt is called Conduct-by-Wire and can be seen as a cooperative maneuver-based driving paradigm, where the driver gives maneuver command to the systems which are automatically executed. This paper summarizes the results of three studies which investigated the user acceptance of this driving paradigm. Overall, it can be said that the acceptance of the system depends on personal traits of the driver and on the driving situation. Almost all participants are willing to use Conduct-by- Wire for routine tasks such as commuting, which makes the systems interesting for company cars. Still, there remain a number of drivers who are not willing to use such a highly automated system at all.     

Bivariate pointing movements on large touch screens: investigating the validity of a refined Fitts' Law

On the basis of three empirical studies Fitts' Law was refined for bivariate pointing tasks on large touch screens. In the first study different target width parameters were investigated. The second study considered the effect of the motion angle. Based on the results of the two studies a refined model for movement time in human-computer interaction was formulated. A third study, which is described here in detail, concerns the validation of the refined model. For the validation study 20 subjects had to execute a bivariate pointing task on a large touch screen. In the experimental task 250 rectangular target objects were displayed at a randomly chosen position on the screen covering a broad range of ID values (ID= [1.01; 4.88]). Compared to existing refinements of Fitts' Law, the new model shows highest predictive validity. A promising field of application of the model is the ergonomic design and evaluation of project management software. By using the refined model, software designers can calculate a priori the appropriate angular position and the size of buttons, menus or icons.     

A small world on feet of clay? A comparison of empirical small-world studies against best-practice criteria

Small-world studies were introduced by Milgram and others in the 1960s and 1970s. These studies, and a majority of variants conducted by others, display a number of methodological weaknesses that bias their results. While no explicit methodological standard exists for these studies, here I derive a number of best-practice criteria for small-world studies by pointing out mistakes of previous studies, and by applying methodological standards from other empirical research areas. Improving the methodology of letter referral studies is important, because such studies could still be useful in a number of contexts today, especially for the exploration of factors affecting targeted search processes.     

Politicized expertise – an analysis of the political dimensions of consultants' policy recommendations to developing countries with a case study of McKinsey's advice on REDD+ policies

This article argues that expertise must be seen as politicized. Most of the existing research on the role of experts in policy-making neglects that there are many political factors which influence what and whose expertise is sought and used. This article looks at the role consultants play in shaping public policy in developing countries. Applying concepts from different disciplines a theoretical framework is developed to examine in what ways such politicized expertise undermines notions of neutrality and legitimacy. This framework is then applied to a case study looking at the advice that McKinsey & Company has given developing countries on their deforestation and Reducing Emissions from Deforestation and Forest Degradation policies.     

Judgmental overconfidence: Three measures, one bias?

Overconfidence is used to explain various instances of detrimental decision making. In behavioral economic and finance models, it is usually captured by misperceiving the reliability of signals and results in overweighting private information. Empirical tests of these models often fail to find evidence for the predicted effects of overconfidence. These studies assume, however, that a specific type of overconfidence, i.e. “miscalibration,” captures the underlying trait. We challenge this assumption and borrow the psychological methodology of single-cue probability learning to obtain a direct measure for misperceiving signal reliability. Our findings indicate that the perception of signal precision and measures of miscalibration are unrelated. We thus conclude that in order to test the theoretical predictions of the overconfidence literature in economics and finance, one cannot rely on the well-established miscalibration bias.