Detecting changes in task length due to task‐switching in the presence of repeated length‐biased sampling

Clinical work is characterised by frequent interjection of external prompts causing clinicians to switch from a primary task to deal with an incoming secondary task, a phenomenon associated with negative effects in experimental studies. This is an important yet underexplored aspect of work in safety critical settings in general, since an increase in task length due to task‐switching implies reduced efficiency, while decreased length suggests hastening to compensate for the increased workload brought by the unexpected secondary tasks, which is a potential safety issue. In such observational settings, longer tasks are naturally more likely to have one or more task‐switching events: a form of length bias. To assess the effect of task‐switching on task completion time, it is necessary to estimate counterfactual task lengths had they not experienced any task‐switching, while also accounting for length bias. This is a problem that appears simple at first, but has several counterintuitive considerations resulting in a uniquely constrained solution space. We review the only existing method based on an assumption that task‐switches occur according to a homogeneous Poisson process. We propose significant extensions to flexibly incorporate heterogeneity that is more representative of task‐switching in real‐world contexts. The techniques are applied to observations of emergency physicians’ workflow in two hospital settings.     

Altruistic Individualists: Motivations for International Volunteering Among Young Adults in Switzerland

Modernization theory posits a change from traditional or “collective” forms to modern or “reflective” forms of volunteering. In a research project using a combined qualitative–quantitative approach, the motivation of 118 young Swiss adults who showed an interest in international volunteering was investigated. Qualitative analysis revealed 12 different motives which could be categorized into three different groups: A first group called “Achieving something positive for others,” a second group named “Quest for the new,” and a third group of motives labeled “Quest for oneself.” Motivations of young Swiss adults for international volunteering clearly show the characteristics of “reflexive” volunteers. Most respondents displayed a combination of motives while for only 11% of them altruism (“Achieving something positive for others”) was the one and only driving force behind their interest in international volunteering. The inductively constructed typology of motives can be a useful planning device for organizations that run or intend to set up an international volunteering program for young adults.     

Modeling Phytosanitary Risk of Unintended Commodity Use: The Example of U.S. Potato Exports to Mexico

Diversion of commodities from their intended use to an unintended use, e.g., when commodities intended for consumption are used as seed for planting, is an important issue in agricultural trade that has implications for the establishment of pests and pathogens in an importing country and for the appropriate strength of plant health measures. Consequently, understanding and accurately characterizing the risk of diversion from intended use is highly relevant to policymakers, trading partners, and in trade dispute arbitration. To our knowledge, no risk assessments have ever accounted for the likelihood of diversion from intended use. Here we present an approach to analyzing this risk using diversion of U.S. table stock potatoes to seed for planting by Mexican potato producers as a case study. We use probabilistic pathway models to characterize the movement of white, yellow, and russet potatoes from the United States into Mexico at current and double export volumes. We then model the likelihood of these potatoes being diverted for seed and the subsequent establishment of bacteria, nematode, and virus pests in Mexico. Our approach demonstrates how diversion from intended use can be quantified in one scenario and, in particular, how it can be analyzed to estimate the magnitude of diversion required to produce a high risk of pest establishment.     

The Detrimental Side Effects of Minimum Wage Laws

The adverse effects of minimum wage legislation demonstrate how a government policy presumably intended to help people worst off in society can actually end up causing far more harm than good. In this case, the victims are unskilled laborers. By making it illegal for employers to pay unskilled workers wages equal to their marginal revenue productivity, it causes unemployment for all workers whose productivity happens to be below the minimum wage. It also widens the wage gap between whites and minorities because there are disproportionate numbers of unskilled and uneducated minorities compared with whites.     

Structural impacts on the occurrence and effectiveness of transformational leadership: An empirical study at the organizational level of analysis

This article empirically investigates the role of organizational structure in the transformational leadership (TFL) process. We examine organizational centralization, formalization, and size as antecedents of an organization's TFL climate, and as moderators of the relationship between TFL climate and productive organizational energy (POE). Hypotheses are tested using a sample of 125 organizations. Results show that both the centralization and size of an organization are negatively related to its TFL climate, whereas formalization has a positive association. Further, while there is a positive linkage between TFL climate and POE, both centralization and formalization moderate this relationship. The TFL climate–POE linkage is diminished under conditions of high centralization, and it is enhanced under conditions of high formalization. These findings point to the role of organizational structure as a boundary condition for both the occurrence and the effectiveness of TFL in organizations. The paper concludes by acknowledging its limitations and discussing its implications for practice and research.     

Benchmark Analysis for Quantifying Urban Vulnerability to Terrorist Incidents

We describe a quantitative methodology to characterize the vulnerability of U.S. urban centers to terrorist attack, using a place-based vulnerability index and a database of terrorist incidents and related human casualties. Via generalized linear statistical models, we study the relationships between vulnerability and terrorist events, and find that our place-based vulnerability metric significantly describes both terrorist incidence and occurrence of human casualties from terrorist events in these urban centers. We also introduce benchmark analytic technologies from applications in toxicological risk assessment to this social risk/vulnerability paradigm, and use these to distinguish levels of high and low urban vulnerability to terrorism. It is seen that the benchmark approach translates quite flexibly from its biological roots to this social scientific archetype.