Communicating Conservation Status: How Different Statistical Assessment Criteria Affect Perceptions of Extinction Risk

Although alternative forms of statistical and verbal information are routinely used to convey species’ extinction risk to policymakers and the public, little is known about their effects on audience information processing and risk perceptions. To address this gap in literature, we report on an experiment that was designed to explore how perceptions of extinction risk differ as a function of five different assessment benchmarks (Criteria A–E) used by scientists to classify species within IUCN Red List risk levels (e.g., Critically Endangered, Vulnerable), as well as the role of key individual differences in these effects (e.g., rational and experiential thinking styles, environmental concern). Despite their normative equivalence within the IUCN classification system, results revealed divergent effects of specific assessment criteria: on average, describing extinction risk in terms of proportional population decline over time (Criterion A) and number of remaining individuals (Criterion D) evoked the highest level of perceived risk, whereas the single‐event probability of a species becoming extinct (Criterion E) engendered the least perceived risk. Furthermore, participants scoring high in rationality (analytic thinking) were less prone to exhibit these biases compared to those low in rationality. Our findings suggest that despite their equivalence in the eyes of scientific experts, IUCN criteria are indeed capable of engendering different levels of risk perception among lay audiences, effects that carry direct and important implications for those tasked with communicating about conservation status to diverse publics.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

Autocratic leaders and authoritarian followers revisited: A review and agenda for the future

Despite a long history within the field of leadership, the subject of authoritarianism and how it influences leadership and leadership processes has been neglected in recent decades. However, recent global events make it clear that a better understanding of authoritarianism is needed and that leadership researchers would benefit from a renewed interest in studying why followers embrace autocratic leaders. The nature of authoritarian character, how authoritarian values develop, and how it is measured will be discussed. We will also review autocratic leadership, the factors that make it more likely, its consequences for followers, and the moderators of its effects. A future research agenda for the study of authoritarian character and autocratic leadership will be provided.     

The Women’s Empowerment in Livestock Index

Social Indicators Research - The empowerment of women in the livestock sector is fundamental to achieve gender equality. It also is instrumental for increased household productivity and improved...     

The relationship between burnout and risk-taking in workplace decision-making and decision-making style

This study aimed to investigate what decision-making styles might be exhibited by employees who experience burnout. Using a Work Risk Inventory (WRI), developed for this study, which included generic workplace scenarios, it was also explored whether such employees take relatively more risky decisions. Risk was conceptualised as the adoption of decisions that threaten one’s reputation at work, job performance and job security. The mediating effect of the likelihood and seriousness of the consequences of the worst that could happen in each given scenario on the relationships between dimensions of burnout and risk-taking was also tested. A total of 262 employees in various occupations completed an online survey, including measures on burnout, decision-making styles and the WRI. As predicted, dimensions of burnout – exhaustion, cynicism and professional inefficacy – correlated significantly with avoidant decision-making and negatively with rational decision-making. The seriousness of the consequences of the worst-case scenario occurring mediated the relationship between professional inefficacy and risk-taking. In the context of identifying mechanisms by which burnout leads to risky decision-making, the findings suggest that employees’ sense of professional inefficacy determines their risky decision-making. The contribution to theory and implications for practice are discussed.     

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life‐Cycle Assessment and Decision Analysis

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi‐criteria decision analysis (MCDA) and life‐cycle assessment (LCA) results (LCA‐MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi‐attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary.     

Assessing Risk‐Based Upper Limits of Melamine Migration from Food Containers

Melamine contamination of food has become a major food safety issue because of incidents of infant disease caused by exposure to this chemical. This study was aimed at establishing a safety limit in Taiwan for the degree of melamine migration from food containers. Health risk assessment was performed for three exposure groups (preschool children, individuals who dine out, and elderly residents of nursing homes). Selected values of tolerable daily intake (TDI) for melamine were used to calculate the reference migration concentration limit (RMCL) or reference specific migration limit (RSML) for melamine food containers. The only existing values of these limits for international standards today are 1.2 mg/L (0.2 mg/dm²) in China and 30 mg/L (5 mg/dm²) in the European Union. The factors used in the calculations included the specific surface area of food containers, daily food consumption rate, body weight, TDI, and the percentile of the population protected at a given migration concentration limit (MCL). The results indicate that children are indeed at higher risk of melamine exposure at toxic levels than are other groups and that the 95th percentile of MCL (specific surface area = 5) for children aged 1–6 years should be the RMCL (0.07 mg/dm²) for protecting the sensitive and general population.     

Analysing critical success factors to implement sustainable supply chain practices in Indian automobile industry: a case study

The aim of this article is to analyse the critical success factors (CSFs) behind the successful implementation of sustainable supply chain practices in Indian automobile industry. Supply chain sustainability is a critical and timely topic for the developing country like India that captures increasing concerns over sustainability, whether driven by current legislation, public interest or competitive opportunity. Identification of CSFs responsible for sustainable supply chain practices and evaluating their contextual relationships has the potential to affect future government policy, current production operations and identify new business models. In response to this, this paper intends to identify CSFs based on organisational theory and model them to implement sustainable supply chain practices in Indian automobile industry. Twenty-five CSFs to implement sustainable supply chain practices based on organisational theory are recognised by means of the literature review and in discussions with experts in one case study organisation. A solution methodology based on the interpretive structural modelling (ISM) technique is used to propose a structural model, which not only helps in understanding the contextual relationship among these CSFs, but also in determining their interdependence to implement sustainable supply chain practices. Further, the importance of CSFs has been determined based on their driving and dependence power using MICMAC analysis. Our overarching thesis is that the insights gained are useful for Indian automobile industry and would help practitioners, regulators and academicians to focus their efforts towards implementation of sustainable supply chain practices.