A New Look at the Psychometric Paradigm of Perception of Hazards

The psychometric paradigm has been the most influential model in the field of risk analysis. The "cognitive maps" of hazards produced by the paradigm seem to explain how laypeople perceive the various risks they face. Because most of the studies used aggregated data, analyzed using principal component analysis, it is not known whether the model neglects individual differences in risk perception. There has been much criticism on the fact that few studies have examined individual differences in the cognitive representation of hazards. In order to detect and describe the internal structure of the three-way data, we conducted a three-way component analysis (3MPCA). Data for the present analysis were derived from a mail survey conducted in Switzerland. Participants were asked to judge 9 attributes for 26 hazards. Individual differences in the cognitive representation of hazards were correlated with external variables (e.g., general trust). The results suggest that methods permitting individual differences should be used more frequently and that utilizing different methods could provide greater insight into the cognitive representation of risks.     

The Relationship Between Visioning Behaviours of Leaders and Follower Burnout

This paper investigates whether the perceived visioning behaviours of leaders influence the burnout process experienced by their followers. A structural equation model was used to examine these relationships using a sample of 480 senior managers from an Australian law-enforcement organization. Differences in the relationships between the two factors of visioning behaviour and aspects of burnout were identified. Inspirational motivation (concept-based) reduced the central factor of burnout, namely emotional exhaustion (psychological strain). Inspirational motivation (image-based) had a positive effect on personal accomplishment (self) and reduced depersonalization. The paper discusses the implications for leaders and followers and identifies directions for future research.     

Understanding the theory behind the Last Planner System using the Language-Action Perspective: two case studies

Since the Last Planner System® (LPS) was devised in the early 90s, a number of studies have pointed out the need to understand the underlying theory in which it is based on. The Language-Action Perspective (LAP) has been suggested as a suitable approach to understand the management of commitments in the LPS. This paper aims to assess the contribution of LAP to understand construction planning and control systems based on LPS. Two case studies were carried out in different construction companies, both highly experienced on the use of LPS. The results reveal the role of LAP for creating explicit representations of commitment flows that can be used to explain the sources of complexity and failures in planning systems, as well as for describing the profile of planning and control meetings.     

The surprising effectiveness of earliest operation due-date sequencing

In make-to order production, schedule reliability is very important but still not sufficiently accomplished in industrial practice by the vast majority of companies. It has been known for long that processing the orders at a workstation in the order of their operation due-dates can compensate for lateness in the arrival at the workstation within certain boundaries. The paper analyses the effectiveness of earliest operation due date (EODD) sequencing by comparing it to an optimistic theoretical boundary. The surprising result is that EODD can nearly fully exploit the theoretical potential. It should therefore be used in practice whenever schedule reliability is important, with only few exceptions. Its effectiveness though is increasing with the workstation’s WIP level and thus is in conflict with the objective to reduce WIP levels and throughput times. A simple forecasting model allows to assess the extent to which lateness can be compensated by EODD sequencing and which schedule compliance can be achieved.     

Generating a smallest binary tree by proper selection of the longest edges to bisect in a unit simplex refinement

In several areas like global optimization using branch-and-bound methods for mixture design, the unit n-simplex is refined by longest edge bisection (LEB). This process provides a binary search tree. For \(n>2\), simplices appearing during the refinement process can have more than one longest edge (LE). The size of the resulting binary tree depends on the specific sequence of bisected longest edges. The questions are how to calculate the size of one of the smallest binary trees generated by LEB and how to find the corresponding sequence of LEs to bisect, which can be represented by a set of LE indices. Algorithms answering these questions are presented here. We focus on sets of LE indices that are repeated at a level of the binary tree. A set of LEs was presented in Aparicio et al. (Informatica 26(1):17–32, 2015), for \(n=3\). An additional question is whether this set is the best one under the so-called \(m_k\)-valid condition.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Reduction in Dietary Acrylamide Exposure—Impact of Potatoes with Low Acrylamide Potential

Acrylamide forms primarily from a reaction between reducing sugars (e.g., glucose and fructose) and an amino acid (asparagine, Asn) formed naturally in foods, including potatoes. This reaction occurs when carbohydrate‐rich foods are heated at temperatures above 120 °C. Multiple potato varieties were transformed with potato genomic DNA that results in down‐regulation of the expression of the asparagine synthetase‐1 gene (Asn1), significantly reducing synthesis of free Asn, and consequently lowering the potential to form acrylamide during cooking. These potatoes with low acrylamide potential (LAP) were tested in agronomic trials, and processed into French fries and potato chips. Decreased levels of acrylamide were measured in these cooked food products when derived from LAP potatoes compared with those derived from conventional potatoes. These reductions can be directly attributed to reduction in Asn levels in the LAP potatoes. The corresponding average reduction in exposure to acrylamide from French fry and potato chip consumption is estimated to be 65%, which would amount to approximately a 25% reduction in overall dietary exposure. Considering that children consume nearly three times more acrylamide than adults on a per kg body weight basis, they would experience the most impact from the reduced acrylamide associated with LAP potatoes. The potential public health impacts, in context of dietary acrylamide exposure reduction, are discussed in this study.     

The Use of Simulation to Reduce the Domain of “Black Swans” with Application to Hurricane Impacts to Power Systems

Recently, the concept of black swans has gained increased attention in the fields of risk assessment and risk management. Different types of black swans have been suggested, distinguishing between unknown unknowns (nothing in the past can convincingly point to its occurrence), unknown knowns (known to some, but not to relevant analysts), or known knowns where the probability of occurrence is judged as negligible. Traditional risk assessments have been questioned, as their standard probabilistic methods may not be capable of predicting or even identifying these rare and extreme events, thus creating a source of possible black swans. In this article, we show how a simulation model can be used to identify previously unknown potentially extreme events that if not identified and treated could occur as black swans. We show that by manipulating a verified and validated model used to predict the impacts of hazards on a system of interest, we can identify hazard conditions not previously experienced that could lead to impacts much larger than any previous level of impact. This makes these potential black swan events known and allows risk managers to more fully consider them. We demonstrate this method using a model developed to evaluate the effect of hurricanes on energy systems in the United States; we identify hurricanes with potentially extreme impacts, storms well beyond what the historic record suggests is possible in terms of impacts.