A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

Robustness of a Class of Partial Diallel Cross Designs to the Unavailability of a Complete Block of Observations

Complete and partial diallel cross designs are examined as to their construction and robustness against the loss of a block of observations. A simple generalized inverse is found for the information matrix of the line effects, which allows evaluation of expressions for the variances of the line-effect differences with and without the missing block. A-efficiencies, based on average variances of the elementary contrasts of the line-effects, suggest that these designs are fairly robust. The loss of efficiency is generally less than 10%, but it is shown that specific comparisons might suffer a loss of efficiency of as much as 40%.     

TERRITORIAL RESTRICTIONS IN FRANCHISE CONTRACTS

Efficient contracts set incentives through the assignment of rights and profit shares., Although efficient contracts have been used to explain the nature of the firm, the use of contractual rights in specific business contracts is relatively unexplored. We analyze contractual rights in franchise systems, in particular the right to add franchisees. An exclusive territory assigned to an initial franchisee is not an immutable guarantee, but rather a starting point for subsequent renegotiation in the franchise relationship. Exclusivity is therefore profitable when franchisee efforts are critical to the venture. A sample of franchise contracts reveals evidence consistent with the model's prediction.     

Low dose risk estimation via simultaneous statistical inferences

Summary.  The paper develops and studies simultaneous confidence bounds that are useful for making low dose inferences in quantitative risk analysis. Application is intended for risk assessment studies where human, animal or ecological data are used to set safe low dose levels of a toxic agent, but where study information is limited to high dose levels of the agent. Methods are derived for estimating simultaneous, one-sided, upper confidence limits on risk for end points measured on a continuous scale. From the simultaneous confidence bounds, lower confidence limits on the dose that is associated with a particular risk (often referred to as a bench-mark dose ) are calculated. An important feature of the simultaneous construction is that any inferences that are based on inverting the simultaneous confidence bounds apply automatically to inverse bounds on the bench-mark dose.     

Lifestyle Options and Economic Strategies: Subsistence Activities in the Mississippi Delta1

Abstract "Subsistence" and "informal economy" are contrasted in their utility as sociological concepts and their ability to explain a variety of activities in two rural Mississippi Delta communities. Literature on subsistence stresses that the desired outcome of participation is not an increase in income but the social rewards of participation itself. Two underlying dimensions of participation in these activities are documented through the literature and through a confirmatory factor analysis of empirical data: life-style choice and economic strategy. These were constructed into indexes and examined individually and in combination as dependent variables using regressors at the community, household, and individual levels. Community ties were weakly associated with participation in such activities. Whites and those with higher incomes participated more in lifestyle choice oriented activities. Participation in general was statistically related to households needing less weekly income and being of larger size. Potential connections with persistent rural poverty are discussed.     

Differentiated leader–member exchange,justice climate,and performance: Main and interactive effects

Leaders form different quality leader–member exchange (LMX) relationships with their subordinates. This variable treatment termed LMX differentiation can have negative effects on individuals' behavior and attitudes. In this study, we examined the cross-level main effect of justice climate on task performance and the moderating role of justice climate on the relationship between LMX differentiation and task performance. We tested these two hypotheses using a field study of 90 subordinates nested under 27 supervisors. Procedural justice climate, not distributive justice climate, was found to positively influence subordinate task performance. Further, distributive justice climate, not procedural justice climate, was found to moderate the LMX differentiation–task performance relationship; such that the relationship was positive when distributive justice climate was high and negative when distributive justice climate was low. Findings and future directions are discussed.     

How to reduce workload--augmented reality to ease the work of air traffic controllers

In the future the air traffic will rise--the workload of the controllers will do the same. In the BMWi research project, one of the tasks is, how to ensure safe air traffic, and a reasonable workload for the air traffic controllers. In this project it was the goal to find ways how to reduce the workload (and stress) for the controllers to allow safe air traffic, esp. at huge hub-airports by implementing augmented reality visualization and interaction.     

Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing

This paper concerns the forecasting of seasonal intraday time series that exhibit repeating intraweek and intraday cycles. A recently proposed exponential smoothing method involves smoothing a different intraday cycle for each distinct type of day of the week. Similar days are allocated identical intraday cycles. A limitation is that the method allows only whole days to be treated as identical. We introduce a new exponential smoothing formulation that allows parts of different days of the week to be treated as identical. The result is a method that involves the smoothing and initialisation of fewer terms. We evaluate forecasting up to a day ahead using two empirical studies. For electricity load data, the new method compares well with a range of alternatives. The second study involves a series of arrivals at a call centre that is open for a shorter duration at the weekends than on weekdays. Among the variety of methods considered, the new method is the only one that can model in a satisfactory way in this situation, where the number of periods on each day of the week is not the same.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.