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.     

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.     

Dublin’s Seventeenth Century Parishes and the Quality of Life

Social Indicators Research - The registers of Dublin’s parishes in the seventeenth century provide access to aspects of civic and religious life. In the registers are records of burials,...     

The Relationships between Activity and Quality of Life for Older Men and Women at Different Ages in Taiwan

This study investigated the relationships between types of activity and quality of life (QOL) for older men and women at different ages. Based on cross-sectional data that included 220 community-dwelling elderly persons aged 65 and older in southern Taiwan, the results showed that the participation rates in many activities declined with age for both genders. Social activity and solitary leisure activity were significantly associated with QOL for old-old men, but not for young-old men. Only social activity was significantly associated with QOL for young-old women, but there was no significant association between any activity and QOL for old-old women.     

Estimating urban lawn cover in space and time: Case studies in three Swedish cities

Lawns are considered monocultures and lesser contributors to sustainability than diverse nature but are still a dominating green area feature and an important cultural phenomenon in cities. Lawns have esthetical values, provide playground, are potential habitat for species, contribute to carbon sequestration and water infiltration, but also increase pesticides, fertilization, are monocultures and costly to manage at the same time. To evaluate the potential impact of lawns, whether positive or negative, it is of interest to estimate the total lawn cover in cities and its change over time. This is not a straightforward process, e.g., because many lawns are small and covered by trees. In this study we review the existing literature of lawn cover in cities and the different methodologies used for cover estimation. We found both pros and cons with NDVI and LiDAR data as well as manually interpreted aerial photos. The total cover of lawns in three case study cities was estimated to 22.5%. By extrapolating these percentages to all Swedish cities lawn cover was estimated to 2589 km² (0.6% of the terrestrial surface). The approximated total municipal management cost of lawns in all Swedish cities was 910,000,000 USD/ year. During 50 years lawn area almost doubled in relative cover and 56% of them were continuously managed. Since lawns constitute large parts of the urban greenery and are costly to manage it is highly relevant to consider their social, ecological and cultural value compared to alternatives, e.g., meadows with less intensive management.     

The Risk of James–Stein and Lasso Shrinkage

This article compares the mean-squared error (or ?₂ risk) of ordinary least squares (OLS), James–Stein, and least absolute shrinkage and selection operator (Lasso) shrinkage estimators in simple linear regression where the number of regressors is smaller than the sample size. We compare and contrast the known risk bounds for these estimators, which shows that neither James–Stein nor Lasso uniformly dominates the other. We investigate the finite sample risk using a simple simulation experiment. We find that the risk of Lasso estimation is particularly sensitive to coefficient parameterization, and for a significant portion of the parameter space Lasso has higher mean-squared error than OLS. This investigation suggests that there are potential pitfalls arising with Lasso estimation, and simulation studies need to be more attentive to careful exploration of the parameter space.     

Improving Weight of Evidence Approaches to Chemical Evaluations

Federal and other regulatory agencies often use or claim to use a weight of evidence (WoE) approach in chemical evaluation. Their approaches to the use of WoE, however, differ significantly, rely heavily on subjective professional judgment, and merit improvement. We review uses of WoE approaches in key articles in the peer‐reviewed scientific literature, and find significant variations. We find that a hypothesis‐based WoE approach, developed by Lorenz Rhomberg et al., can provide a stronger scientific basis for chemical assessment while improving transparency and preserving the appropriate scope of professional judgment. Their approach, while still evolving, relies on the explicit specification of the hypothesized basis for using the information at hand to infer the ability of an agent to cause human health impacts or, more broadly, affect other endpoints of concern. We describe and endorse such a hypothesis‐based WoE approach to chemical evaluation.     

Assessing Value Differences Between Leaders of Two Social Venture Types: Benefit Corporations and Nonprofit Organizations

This study considers key value differences between leaders of two types of social ventures: for-profit social benefit corporations and nonprofit organizations. The research question asks to what degree the value sets of leaders of benefit corporations are congruent with those of similarly situated individuals in nonprofit organizations. The results show the values of leaders working in benefit corporations and nonprofit organizations are in many ways aligned, but there are notable statistical differences. A sectoral association of values is also present with employees in both types of organization, especially when the previous work experience of employees is considered.