Cross‐Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in disease‐specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and self‐efficacy (i.e., control). The 2015–2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved cross‐sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (March–May 2016) and one just after the first cases of local transmission (July–August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and self‐efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.     

Impact of Water Level Rise on Urban Infrastructures: Washington,DC, and Shanghai as Case Studies

The observed global sea level rise owing to climate change, coupled with the potential increase in extreme storms, requires a reexamination of existing infrastructural planning, construction, and management practices. Storm surge shows the effects of rising sea levels. The recent super storms that hit the United States (e.g., Hurricane Katrina in 2005, Sandy in 2012, Harvey and Maria in 2017) and China (e.g., Typhoon Haiyan in 2010) inflicted serious loss of life and property. Water level rise (WLR) of local coastal areas is a combination of sea level rise, storm surge, precipitation, and local land subsidence. Quantitative assessments of the impact of WLR include scenario identification, consequence assessment, vulnerability and flooding assessment, and risk management using inventory of assets from coastal areas, particularly population centers, to manage flooding risk and to enhance infrastructure resilience of coastal cities. This article discusses the impact of WLR on urban infrastructures with case studies of Washington, DC, and Shanghai. Based on the flooding risk analysis under possible scenarios, the property loss for Washington, DC, was evaluated, and the impact on the metro system of Shanghai was examined.     

Synergy from configuration of global production networks: drivers,mechanisms, and outcomes

Abstract

This paper explores the network synergies available from the configuration of highly dispersed, global production networks (GPNs). Synergy theory from the literature on intra-firm and inter-firm GPNs is examined in terms of drivers, mechanisms and outcomes. An explanatory model is developed and enriched via a series of extended case studies of firms undertaking re-configuration of their GPNs during the period 2003–2014. The primary finding is that firms create synergy in their GPNs by selecting specific configuration mechanisms, in response to a certain set of external drivers, in order to achieve certain synergistic outcomes. The paper classifies the main types of drivers, mechanisms and outcomes in terms of key variables and discusses their inter-connections and relationships.     

Making sense of pragmatic and charismatic leadership stories: Effects on vision formation

For some time, it has been argued that stories articulated by leaders are an important vehicle for exercising influence, but stories of leadership might also serve as a means for developing leadership potential. One critical activity involved in leadership is vision formation, which involves constructing and communicating a future state that guides followers in “making sense” of complex organizational events. Like leader visions, analyzing stories also, by nature, evokes sensemaking processes. As a result, analyzing stories of leadership may provide a natural means for practicing the art of sensemaking. In the present investigation, undergraduates were asked to read six short stories about incidents of either pragmatic or charismatic leadership in business settings. After reading each story, questions were asked to encourage sensemaking of story events, causes, and emotions. Participants were subsequently asked to formulate visions for leading a secondary school –– a transfer task. It was found that stronger visions were produced when participants were asked to analyze both story events and the causes of these events. The implications of these findings for the use of leadership stories in leader development initiatives are discussed.     

On the total outer-connected domination in graphs

A set S of vertices of a graph G is a total outer-connected dominating set if every vertex in V(G) is adjacent to some vertex in S and the subgraph induced by V?S is connected. The total outer-connected domination number γ _toc (G) is the minimum size of such a set. We give some properties and bounds for γ _toc in general graphs and in trees. For graphs of order n, diameter 2 and minimum degree at least 3, we show that $\gamma_{toc}(G)\le \frac{2n-2}{3}$ and we determine the extremal graphs.     

Quality Risk Ratings in Global Supply Chains

Extended enterprises face many challenges in managing the product quality of their suppliers. Consequently characterizing the quality risk posed by value‐chain partners has become increasingly important. There have been several recent efforts to develop frameworks for rating the quality risk posed by suppliers. We develop an analytical model to examine the impact of such quality ratings on suppliers, manufacturers, and social welfare. While it might seem that quality ratings would benefit high‐quality suppliers and hurt low‐quality suppliers, we show that this is not always the case. We find that such quality ratings can hurt both types of suppliers or benefit both, depending on the market conditions. We also find that quality ratings do not always benefit the most demanding manufacturers who desire high‐quality suppliers. Finally, we find that social welfare is not always improved by risk ratings. These results suggest that public policy initiatives addressing risk ratings must be carefully considered.     

Evaluating the Temporal Location of Feedback: Providing Feedback Following Performance vs. Prior to Performance

In order to make feedback as effective as possible, it is important to understand its function in the three-term contingency (TTC) and the impact of various factors involved in delivering feedback. Timing of feedback is one factor that can affect the impact of feedback on learner’s behavior. An analysis of timing of feeback may help us getting closer to better understanding how feedback functions in the TTC. The purpose of this study was to evaluate the effects of feedback at different temporal locations. Specifically, feedback was provided either immediately (a) after a teaching session or (b) before the following teaching session, on teaching performance of undergraduate psychology students. The results indicated that feedback provided before the teaching session was more effective in improving teaching skills than feedback that was provided after the session. These findings suggest that feedback may function primarily as an antecedent to future performance and not necessarily as a consequence for past performance. However, the behavioral mechanism that explains these results is not yet clear. Future studies should investigate this further by manipulating the content of feedback prior to the teaching performance.     

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.