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.     

Linking Decision Theory and Quantitative Microbial Risk Assessment: Tradeoffs Between Compliance and Efficacy for Waterborne Disease Interventions

Achieving health gains from the U.N. Sustainable Development Goals of universal coverage for water and sanitation will require interventions that can be widely adopted and maintained. Effectiveness—how an intervention performs based on actual use—as opposed to efficacy will therefore be central to evaluations of new and existing interventions. Incomplete compliance—when people do not always use the intervention and are therefore exposed to contamination—is thought to be responsible for the lower‐than‐expected risk reductions observed from water, sanitation, and hygiene interventions based on their efficacy at removing pathogens. We explicitly incorporated decision theory into a quantitative microbial risk assessment model. Specifically, we assume that the usability of household water treatment (HWT) devices (filters and chlorine) decreases as they become more efficacious due to issues such as taste or flow rates. Simulations were run to examine the tradeoff between device efficacy and usability. For most situations, HWT interventions that trade lower efficacy (i.e., remove less pathogens) for higher compliance (i.e., better usability) contribute substantial reductions in diarrheal disease risk compared to devices meeting current World Health Organization efficacy guidelines. Recommendations that take into account both the behavioral and microbiological properties of treatment devices are likely to be more effective at reducing the burden of diarrheal disease than current standards that only consider efficacy.     

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.     

Effects of Firm-specific and Country-specific Advantages on Relative Acquisition Size in Service Sector Cross-Border Acquisitions: An Empirical Examination

Using a sample of 348 service sector cross-border acquisitions by U.S. firms in 44 countries during 1990–2006, our study seeks to identify factors that influence relative acquisition size (acquisition transaction value as a percentage of acquiring firm's asset value). Our findings indicate that firm-specific advantages (FSAs) in the form of available financial slack and target industry knowledge were positively associated with relative acquisition size. However, contrary to expectations, we observed a negative relationship between cross-border acquisition experience and relative acquisition size. In addition, our results suggest that country-specific advantages (CSAs) associated with higher market potential, lower political risk, and greater cultural similarity contributed to increased relative acquisition size in service industry cross-border acquisitions. Finally, our analysis reveals that the relationship between available financial slack and relative acquisition size is contingent on cultural similarity with the relationship being more pronounced when cultural similarity is high.     

Generalized perfect domination in graphs

Let k be a positive integer and G=(V,E) be a graph. A vertex subset D of a graph G is called a perfect k-dominating set of G, if every vertex v of G, not in D, is adjacent to exactly k vertices of D. The minimum cardinality of a perfect k-dominating set of G is the perfect k-domination number γ _kp (G). In this paper, we give characterizations of graphs for which γ _kp (G)=γ(G)+k?2 and prove that the perfect k-domination problem is NP-complete even when restricted to bipartite graphs and chordal graphs. Also, by using dynamic programming techniques, we obtain an algorithm to determine the perfect k-domination number of trees.     

Social Networking and Individual Perceptions: Examining Predictors of Participation

Social networking is a process and practice that draws people and organizations together in an electronic medium. This article explores social interaction-based theories to suggest a social networking participation model that may help organizations understand acceptance or rejection of participation. Responses from 191 public administrators were analyzed using structural equation modeling (SEM), focusing on relationships between participation and five constructs: perceived usefulness, perceived ease of use, perceived improvement potential (PIP), intra-organizational trust, and type of use. The study found favorable model fit statistics that support positive correlations between the latent variables examined and participation in social networking activities. The results demonstrate the potential of the survey instrument to serve as an adoption and participation model to predict and promote social networking activities as they relate to perceived performance improvement.     

Linking Process Quality and Resource Usage: An Empirical Analysis

Motivated by an increasing adoption of evidence‐based medical guidelines in the delivery of medical care, we examine whether increased adherence to such guidelines (typically referred to as higher process quality) is associated with reduced resource usage in the course of patient treatment. In this study, we develop a sample of US hospitals and use cardiac care as our context to empirically examine our questions. To measure a patient's resource usage, we use the total length of stay, which includes any additional inpatient stay necessitated by unplanned readmissions within thirty days after initial hospitalization. We find evidence that higher process quality, and more specifically its clinical (as opposed to its administrative) dimensions, are associated with a reduction in resource usage. Moreover, the standardization of care that is achieved via the implementation of medical guidelines, makes this effect more pronounced in less focused environments: higher process quality is more beneficial when the cardiac department's patient population is distributed across a wider range of medical conditions. We explore the implications of these findings for process‐oriented pay‐for‐performance programs, which tie the reimbursement of hospitals to their adherence to evidence‐based medical guidelines.     

Experimental Games on Networks: Underpinnings of Behavior and Equilibrium Selection

In this paper, we describe a series of laboratory experiments that implement specific examples of a general network structure. Specifically, actions are either strategic substitutes or strategic complements, and participants have either complete or incomplete information about the structure of a random network. Since economic environments typically have a considerable degree of complementarity or substitutability, this framework applies to a wide variety of settings. We examine behavior and equilibrium selection. The degree of equilibrium play is striking, in particular with incomplete information. Behavior closely resembles the theoretical equilibrium whenever this is unique; when there are multiple equilibria, general features of networks, such as connectivity, clustering, and the degree of the players, help to predict informed behavior in the lab. People appear to be strongly attracted to maximizing aggregate payoffs (social efficiency), but there are forces that moderate this attraction: (1) people seem content with (in the aggregate) capturing only the lion's share of the efficient profits in exchange for reduced exposure to loss, and (2) uncertainty about the network structure makes it considerably more difficult to coordinate on a demanding, but efficient, equilibrium that is typically implemented with complete information.     

Distance domination in graphs with given minimum and maximum degree

For an integer \(k \ge 1\), a distance k-dominating set of a connected graph G is a set S of vertices of G such that every vertex of V(G) is at distance at most k from some vertex of S. The distance k-domination number \(\gamma _k(G)\) of G is the minimum cardinality of a distance k-dominating set of G. In this paper, we establish an upper bound on the distance k-domination number of a graph in terms of its order, minimum degree and maximum degree. We prove that for \(k \ge 2\), if G is a connected graph with minimum degree \(\delta \ge 2\) and maximum degree \(\Delta \) and of order \(n \ge \Delta + k - 1\), then \(\gamma _k(G) \le \frac{n + \delta - \Delta }{\delta + k - 1}\). This result improves existing known results.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.