Comparison of Chemical Screening and Ranking Approaches: The Waste Minimization Prioritization Tool versus Toxic Equivalency Potentials

Chemical screening in the United States is often conducted using scoring and ranking methodologies. Linked models accounting for chemical fate, exposure, and toxicological effects are generally preferred in Europe and in product Life Cycle Assessment. For the first time, a comparison is presented in this article of two of the prominent, but structurally different methodologies adopted to help screen and rank chemicals and chemical emissions data. Results for 250 chemicals are presented, with a focus on 12 chemicals of interest in the United Nations Environment Programme's Persistent Organic Pollutants global treaty negotiations. These results help to illustrate the significance of described structural differences and to assess the correlation between the methodologies. The scope of the comparison was restricted here to human health, although the insights would be equally useful in the context of the health of ecosystems. Illustrating the current types of chemical screening and emissions comparison approaches, the relative significance of the scenario and structural differences of the Waste Minimization Prioritization Tool (WMPT) and the Toxic Equivalency Potential (TEP) methodologies are analyzed. The WMPT facilitates comparison in terms of key physical-chemical properties. Measures for Persistence, Bioaccumulation, and Toxicity (PBT) are calculated. Each PBT measure is scored and then these scores are added to provide a single measure of relative concern. TEPs account for chemical fate, multipathway exposure, and toxicity using a model-based approach. This model structure is sometimes considered to provide a less subjective representation of environmental mechanisms, and, hence, an improved basis for screening. Nevertheless, a strong relationship exists between the two approaches and both have their limitations.     

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food–pathogen pairs to provide insights for foodborne outbreak investigations.     

An Empirical Investigation of the Effects of Decision Aids on Problem-Solving Processes*

Despite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem-solving processes in a semi-structured problem. Results indicate that decision aids influence the problem-solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem-solving processes into future examinations are proposed.     

Action collective,action de mouvement social: la contribution du syndicalisme à la liberté au travail dans un exemple néo-zélandais

Les syndicats peuvent contribuer à la liberté au travail par une action collective axée sur l'intérêt des membres, mais aussi en nouant des partenariats avec d'autres acteurs de la société civile, dans le cadre d'un mouvement social. Pour traiter ce dernier aspect, encore peu documenté, les auteurs s'appuient sur les définitions de la liberté de Berlin (1988) et MacCallum (1967) puis sur la théorie de la démocratie radicale de Laclau et Mouffe (2019). Ils illustrent leur propos par une étude de cas portant sur les stratégies déployées par des syndicats néozélandais en vue d'accompagner l'action officielle pour une transition juste face au défi climatique.     

Quantitative risk assessment-epidemic curve prediction model for leafy green outbreak investigation

The objective of this study was to leverage quantitative risk assessment to investigate possible root cause(s) of foodborne illness outbreaks related to Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) infections in leafy greens in the United States. To this end, we developed the FDA leafy green quantitative risk assessment epidemic curve prediction model (FDA-LG QRA-EC) that simulated the lettuce supply chain. The model was used to predict the number of reported illnesses and the epidemic curve associated with lettuce contaminated with STEC O157 for a wide range of scenarios representing various contamination conditions and facility processing/sanitation practices. Model predictions were generated for fresh-cut and whole lettuce, quantifying the differing impacts of facility processing and home preparation on predicted illnesses. Our model revealed that the timespan (i.e., number of days with at least one reported illness) and the peak (i.e., day with the most predicted number of reported illnesses) of the epidemic curve of a STEC O157-lettuce outbreak were not strongly influenced by facility processing/sanitation practices and were indications of contamination pattern among incoming lettuce batches received by the facility or distribution center. Through comparisons with observed number of illnesses from recent STEC O157-lettuce outbreaks, the model identified contamination conditions on incoming lettuce heads that could result in an outbreak of similar size, which can be used to narrow down potential root cause hypotheses.     

CEO Narcissism and Global Performance Variance in Multinational Enterprises: The Roles of Foreign Direct Investment Risk-Taking and Business Group Affiliation

This study examines key mechanisms through which CEO narcissism influences global performance variance in the context of Asian emerging market multinational enterprises. Building on the contextual reinforcement model of narcissism and the cushion hypothesis, we focus on the role of foreign direct investment (FDI) risk-taking and business group affiliation (BGA). We test our moderated mediation model on data from 149 South Korean multinational enterprises from 2006 to 2016. The results show that CEO narcissism is positively associated with FDI risk-taking. The effect of CEO narcissism on global performance variance is mediated by FDI risk-taking. Furthermore, BGA moderates the above-mentioned relationships. Our findings offer important contributions to the international business and CEO narcissism literatures.