People,Pipelines, and Probabilities: Clarifying Significance and Uncertainty in Environmental Impact Assessments

Determinations of significance play a pivotal role in environmental impact assessments because they point decision makers to the predicted effects of an action most deserving of attention and further study. Impact predictions are always subject to uncertainty because they rely on estimates of future consequences. Yet uncertainty is often neglected or treated in a perfunctory manner as part of the characterization, evaluation, and communication of anticipated consequences and their significance. Proposals to construct fossil fuel pipelines in North America provide a highly visible example; casual treatment of how uncertainty affects significance determinations has resulted in poorly informed stakeholders, frustrated industry proponents, and inconsistent choices on the part of public decision makers. Using environmental assessments for recent pipeline proposals as examples, we highlight five ways in which uncertainty is often neglected when determining impact significance and suggest that a mix of known methods, new guidelines, and appropriate oversight could greatly improve current practices.     

Farmers’ Risk‐Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent‐based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large‐scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision‐making techniques. These results may inform continued research on such behavioral tendencies in narrower lab‐ and modeling‐based studies.     

Nanotechnology risk perceptions and communication: emerging technologies, emerging challenges

Nanotechnology involves the fabrication, manipulation, and control of materials at the atomic level and may also bring novel uncertainties and risks. Potential parallels with other controversial technologies mean there is a need to develop a comprehensive understanding of processes of public perception of nanotechnology uncertainties, risks, and benefits, alongside related communication issues. Study of perceptions, at so early a stage in the development trajectory of a technology, is probably unique in the risk perception and communication field. As such it also brings new methodological and conceptual challenges. These include: dealing with the inherent diversity of the nanotechnology field itself; the unfamiliar and intangible nature of the concept, with few analogies to anchor mental models or risk perceptions; and the ethical and value questions underlying many nanotechnology debates. Utilizing the lens of social amplification of risk, and drawing upon the various contributions to this special issue of Risk Analysis on Nanotechnology Risk Perceptions and Communication, nanotechnology may at present be an attenuated hazard. The generic idea of "upstream public engagement" for emerging technologies such as nanotechnology is also discussed, alongside its importance for future work with emerging technologies in the risk communication field.     

Capacity constraints and the dynamics of underwriting profits

The presence of an underwriting profit cycle in property/liability insurance has become a stylized fact. Models of this'underwriting cycle'imply that the insurance market is governed by two regimes, as capacity is constrained or not. We apply the smooth transition regression model to insurance industry data for 1934–1993 to test for a regime shift. We find a rapid shift between two distinct regimes with different dynamics. When capacity is not restricted, we find no evidence of a cycle. The cycle is present in periods when capacity is restricted, immediately following World War II and after 1968. The underwriting cycle appears to be a recent phenomenon.     

A first look at the need for enhanced support services for kinship caregivers

This article describes findings from a series of focus groups conducted with formal kinship caregivers in Maryland. The findings reveal that kinship caregivers are committed to providing safety and stability for the children placed with them. The findings also suggest that caregiving can be a significant adjustment for many kinship caregivers and that expanded support services are needed to enhance their relationship with the child welfare agency.     

The effects of smoking laws on seating allocations of restaurants, bars, and taverns

Supporters of smoking laws often argue that they do not harm restaurants, bars, and taverns and may even raise their profits. Opponents argue that owners cater to customer preferences regarding smoking and that laws mandating specific smoking policies will therefore negatively impact profits of some firms. This article tests hypotheses regarding how smoking laws affect seating allocations, using data from a nationwide survey of restaurant and bar owners. The empirical evidence indicates that smoking laws exert no significant effect on seating allocations. Firms are shown to allocate greater shares of seating to nonsmoking use when customers exhibit stronger preferences for such seating.     

自动往返电动小汽车的设计原理与制作方法

本文介绍了采用脉冲主动采集、计数程序控制、虚拟脉冲复位、撞击转向的方式完成自动往返电动小汽车的构思、设计及制作的方法。     

Use of a case study in sequencing/scheduling research

This paper describes a study of an industrial sequencing/scheduling problem. The study contains the definition of the problem, data requirements and examination of solution technique. Definition of the problem is discussed from the aspect of uniqueness of the specific system. Discussion of data requirements includes availability and accuracy, while examination of solution technique considers limitation of time, computer capacity, etc., as well as the possibility of imbedding available algorithms into the solution procedure. Conclusions are presented relative to the use of the case study approach in sequencing/scheduling research.     

Designing Distribution Systems to Support Vendor Strategies in Supply Chain Management*

The interactions among a firm's distribution strategy, market share, and distribution costs are an important consideration in the design of supply chain networks. However, these interactions are largely ignored by existing distribution system design methodologies, which assume demand is constant regardless of the firm's distribution strategy. This paper describes a multidisciplinary framework that considers these interactions in the design of “profit maximizing” distribution networks. The framework employs two major decision support methodologies: (1) binary logit models for estimating market share considering various demand-influencing parameters such as product price and distribution service, and (2) a mixed-integer programming (MIP) model for finding optimal distribution network designs. We applied the framework to an actual design problem facing a national distributor of industrial chemical products. The test results verify the framework's large-scale capability and the potential benefit of the integrated solution methodology.