ALBERT

Notes: Quantitative risk assessment (QRA) models are used to estimate the risks of transporting dangerous goods and to assess the merits of introducing alternative risk reduction measures for different transportation scenarios and assumptions. A comprehensive QRA model recently was developed in Europe for application to road tunnels. This model can assess the merits of a limited number of “native safety measures.” In this article, we introduce a procedure for extending its scope to include the treatment of a number of important “nonnative safety measures” of interest to tunnel operators and decisionmakers. Nonnative safety measures were not included in the original model specification. The suggested procedure makes use of expert judgment and Monte Carlo simulation methods to model uncertainty in the revised risk estimates. The results of a case study application are presented that involve the risks of transporting a given volume of flammable liquid through a 10-km road tunnel.

Notes: This article investigates how accurately experts (underwriters) and lay persons (university students) judge the risks posed by life-threatening events. Only one prior study (Slovic, Fischhoff, & Lichtenstein, 1985) has previously investigated the veracity of expert versus lay judgments of the magnitude of risk. In that study, a heterogeneous grouping of 15 experts was found to judge, using marginal estimations, a variety of risks as closer to the true annual frequencies of death than convenience samples of the lay population. In this study, we use a larger, homogenous sample of experts performing an ecologically valid task. We also ask our respondents to assess frequencies and relative frequencies directly, rather than ask for a “risk” estimate—a response mode subject to possible qualitative attributions—as was done in the Slovic et al. study. Although we find that the experts outperformed lay persons on a number of measures, the differences are small, and both groups showed similar global biases in terms of: (1) overestimating the likelihood of dying from a condition (marginal probability) and of dying from a condition given that it happens to you (conditional probability), and (2) underestimating the ratios of marginal and conditional likelihoods between pairs of potentially lethal events. In spite of these scaling problems, both groups showed quite good performance in ordering the lethal events in terms of marginal and conditional likelihoods. We discuss the nature of expertise using a framework developed by Bolger and Wright (1994), and consider whether the commonsense assumption of the superiority of expert risk assessors in making magnitude judgments of risk is, in fact, sensible.

Notes: Probability models incorporating a deterministic versus stochastic infectious dose are described for estimating infection risk due to airborne pathogens that infect at low doses. Such pathogens can be occupational hazards or candidate agents for bioterrorism. Inputs include parameters for the infectious dose model, distribution parameters for ambient pathogen concentrations, the breathing rate, the duration of an exposure period, the anticipated number of exposure periods, and, if a respirator device is used, distribution parameters for respirator penetration values. Application of the models is illustrated with a hypothetical scenario involving exposure to Coccidioides immitis, a fungus present in soil in areas of the southwestern United States. Inhaling C. immitis spores causes a respiratory tract infection and is a recognized occupational hazard in jobs involving soil dust exposure in endemic areas. An uncertainty analysis is applied to risk estimation in the context of selecting respiratory protection with a desired degree of efficacy.

Notes: Linear, no-threshold relationships are typically reported for time series studies of air pollution and mortality. Since regulatory standards and economic valuations typically assume some threshold level, we evaluated the fundamental question of the impact of exposure misclassification on the persistence of underlying personal-level thresholds when personal data are aggregated to the population level in the assessment of exposure-response relationships. As an example, we measured personal exposures to two particle metrics, PM2.5 and sulfate (SO42−), for a sample of lung disease patients and compared these with exposures estimated from ambient measurements. Previous work has shown that ambient:personal correlations for PM2.5 are much lower than for SO42−, suggesting that ambient PM2.5 measurements misclassify exposures to PM2.5. We then developed a method by which the measured:estimated exposure relationships for these patients were used to simulate personal exposures for a larger population and then to estimate individual-level mortality risks under different threshold assumptions. These individual risks were combined to obtain the population risk of death, thereby exhibiting the prominence (and the value) of the threshold in the relationship between risk and estimated exposure. Our results indicated that for poorly classified exposures (PM2.5 in this example) population-level thresholds were apparent at lower ambient concentrations than specified common personal thresholds, while for well-classified exposures (e.g., SO42−), the apparent thresholds were similar to these underlying personal thresholds. These results demonstrate that surrogate metrics that are not highly correlated with personal exposures obscure the presence of thresholds in epidemiological studies of larger populations, while exposure indicators that are highly correlated with personal exposures can accurately reflect underlying personal thresholds.

Notes: To quantify the health benefits of environmental policies, economists generally require estimates of the reduced probability of illness or death. For policies that reduce exposure to carcinogenic substances, these estimates traditionally have been obtained through the linear extrapolation of experimental dose-response data to low-exposure scenarios as described in the U.S. Environmental Protection Agency's Guidelines for Carcinogen Risk Assessment (1986). In response to evolving scientific knowledge, EPA proposed revisions to the guidelines in 1996. Under the proposed revisions, dose-response relationships would not be estimated for carcinogens thought to exhibit nonlinear modes of action. Such a change in cancer-risk assessment methods and outputs will likely have serious consequences for how benefit-cost analyses of policies aimed at reducing cancer risks are conducted. Any tendency for reduced quantification of effects in environmental risk assessments, such as those contemplated in the revisions to EPA's cancer-risk assessment guidelines, impedes the ability of economic analysts to respond to increasing calls for benefit-cost analysis. This article examines the implications for benefit-cost analysis of carcinogenic exposures of the proposed changes to the 1986 Guidelines and proposes an approach for bounding dose-response relationships when no biologically based models are available. In spite of the more limited quantitative information provided in a carcinogen risk assessment under the proposed revisions to the guidelines, we argue that reasonable bounds on dose-response relationships can be estimated for low-level exposures to nonlinear carcinogens. This approach yields estimates of reduced illness for use in a benefit-cost analysis while incorporating evidence of nonlinearities in the dose-response relationship. As an illustration, the bounding approach is applied to the case of chloroform exposure.

Notes: The increased use of stakeholder processes in environmental decision making has raised concerns about the quality of decisions these processes produce. Some claim that stakeholders make inadequate use of scientific information and analysis and are all too ready to sacrifice technical quality for political expediency. This article looks to the case study record to examine the quality of the decisions from stakeholder-based processes. The data for the analysis come from a “case survey,” in which researchers coded information from 239 published case studies of stakeholder involvement in environmental decision making. These cases reflect a diversity of planning, management, and implementation activities carried out by environmental and natural resource agencies at many levels of government. Overall, the case-study record suggests that there should be little concern that stakeholder processes are resulting in low-quality decisions. The majority of cases contain evidence of stakeholders improving decisions over the status quo; adding new information, ideas, and analysis; and having adequate access to technical and scientific resources. Indeed, data suggest that it is the more intensive stakeholder processes—precisely those that have aroused recent concern—that are more likely to result in higher-quality decisions.

Notes: Research on risk perception aims to explain how people perceive risks in order to better communicate about them. Most of this research has tended to view people as passive risk perceivers. However, if confronted with an unknown risk, people can also actively seek information. The main purpose of this study was to investigate what kind of risk information people desire when confronted with an unknown risk and how this desire for information relates to the main dimensions underlying risk perception. Nine focus-group interviews were conducted. The main results of the focus groups were backed up by a paper-and-pencil questionnaire that was distributed among a random sample of 500 households in the Netherlands. Overall, people desire information with which they can determine the personal relevance of the risk confronting them. This pattern is similar to appraisal steps described by health behavior models. The focus-group results provide a dynamic picture of the way risk aspects might interact to create a final risk judgment.

Notes: Probabilistic risk analysis (PRA) can be an effective tool to assess risks and uncertainties and to set priorities among safety policy options. Based on systems analysis and Bayesian probability, PRA has been applied to a wide range of cases, three of which are briefly presented here: the maintenance of the tiles of the space shuttle, the management of patient risk in anesthesia, and the choice of seismic provisions of building codes for the San Francisco Bay Area. In the quantification of a risk, a number of problems arise in the public sector where multiple stakeholders are involved. In this article, I describe different approaches to the treatments of uncertainties in risk analysis, their implications for risk ranking, and the role of risk analysis results in the context of a safety decision process. I also discuss the implications of adopting conservative hypotheses before proceeding to what is, in essence, a conditional uncertainty analysis, and I explore some implications of different levels of ``conservatism'' for the ranking of risk mitigation measures.

Notes: Universal need for, or reactions to, risk communications should not be assumed; potential differences across demographic groups in environmental risk beliefs, attitudes, and behaviors could affect risk levels or opportunities for risk reduction. This article reports relevant findings from a survey experiment involving 1,100 potential jurors in Philadelphia concerning public responses to outdoor air pollution and air quality information. Flynn et al. (1994) and Finucane et al. (2000) found significant differences in risk ratings for multiple hazards, and in generic risk beliefs, between white men (or a subset) and all others (white women, nonwhite men, and nonwhite women). This study examined whether white men had significantly different responses to air pollution and air pollution information. An opportunity sample of volunteers from those awaiting potential jury duty in city courts (matching census estimates for white versus nonwhite proportions, but more female than the city's adult population and more likely to have children) filled out questionnaires distributed quasi-randomly. On most measures there were no statistically significant differences among white men (N = 192), white women (N = 269), nonwhite men (N = 165), and nonwhite women (N = 272). Nonwhites overall (particularly women) reported more concern about and sensitivity to air pollution than whites, and were more concerned by (even overly sensitive to) air pollution information provided as part of the experiment. Nonwhites also were more likely (within-gender comparisons) to report being active outdoors for at least four hours a day, a measure of potential exposure to air pollution, and to report intentions to reduce such outdoor activity after reading air pollution information. Differences between men and women were less frequent than between whites and nonwhites; the most distinctive group was nonwhite women, followed by white men. Flynn et al. (1994) and Finucane et al. (2000) found a far larger proportion of significant differences, with white men as most distinctive, probably due to use of different measures, study design, and population samples. However, all three studies broadly confirm the existence of gender and race interactions in risk beliefs and attitudes (particularly for white men and nonwhite women) that deserve more attention from researchers.

Notes: Promotion or criticism of risk comparisons in risk communication has far exceeded empirical tests of their effects. Slovic et al. (1990) experimented with a hypothetical jury trial in which an asbestos-installing firm was accused of subjecting school occupants to unreasonable risk. A risk comparison sharply reduced subjects' estimates of risk and judgments that the firm was guilty, but a critique of the risk comparison had risk estimates and guilt judgments rebounding to the original (without risk comparison) level. Slovic et al. concluded that risk comparisons' effects were highly unstable, at least in conflict-ridden situations such as a jury trial. The present study replicates and extends this important study, using the same stimuli and questions. The respective effects of the risk comparison and the critique recurred, although much less sharply than in Slovic et al. Moreover, judgments of guilt, risk, and other aspects of the case seemed shaped more by demographics and beliefs about risk generically (e.g., about the likelihood of cancer after exposure to a carcinogen) than by either risk comparison or critique. A variant design, in which the defense's expert witness dismissed potential criticisms of the risk comparison, appeared to “inoculate” people against shifting their views after seeing the critique. Overall, these results show that risk comparisons might change some beliefs about risks in conflict and that “inoculation” can reduce vulnerability to criticism. However, the results also show strong limits on effects of both comparisons and their critiques: they shifted only a minority of judgments and had small effects relative to people's social locations and prior risk beliefs.

Notes: Current events have heightened the importance of understanding the risks from inhalation exposure to small numbers of spores of Bacillus anthracis. Previously reported data sets have not been fully assessed using current understanding of microbial dose response. This article presents an assessment of the reported primate dose-response data. At low doses, the risk to large populations of low doses of inhaled spores (e.g., 〈100) is not insignificant.

Notes: Annual data from the Finnish National Salmonella Control Programme were used to build up a probabilistic transmission model of salmonella in the primary broiler production chain. The data set consisted of information on grandparent, parent, and broiler flock populations. A probabilistic model was developed to describe the unknown true prevalences, vertical and horizontal transmissions, as well as the dynamical model of infections. By combining these with the observed data, the posterior probability distributions of the unknown parameters and variables could be derived. Predictive distributions were derived for the true number of infected broiler flocks under the adopted intervention scheme and these were compared with the predictions under no intervention. With the model, the effect of the intervention used in the programme, i.e., eliminating salmonella positive breeding flocks, could be quantitatively assessed. The 95% probability interval of the posterior predictive distribution for (broiler) flock prevalence under current (1999) situation was [1.3%–17.4%] (no intervention), and [0.9%–5.8%] (with intervention). In the scenario of one infected grandparent flock, these were [2.8%–43.1%] and [1.0%–5.9%], respectively. Computations were performed using WinBUGS and Matlab softwares.

Notes: We set out to explore potential influences on public views about urban air quality in two different, but geographically close, districts in North-East England via a postal survey. The neighborhoods surveyed were chosen to contrast material deprivation, proximity to industry, and two districts (Teesside and Sunderland), and the respondents within them were contrasted by their gender, age, and illness status. The strongest influences on views about local air quality were found to be proximity to industry, residence in Teesside, and, to a lesser extent, age and illness status. This suggests that neighborhood characteristics play an important role in shaping public perceptions of air quality.

Notes: Public perceptions and political debates regarding the risks and benefits of agricultural biotechnology are well documented in industrialized countries. Yet, hardly any surveys have been conducted in developing countries. The following study aims to contribute to a better understanding of stakeholder attitudes toward agricultural biotechnology in developing countries. For this purpose, stakeholder representatives in the public debates in Mexico and the Philippines were asked to complete two nearly identical questionnaires on the risks and benefits of agricultural biotechnology. A comparison of stakeholder attitudes in the Philippines and Mexico is interesting because it shows how the different political systems, cultural and ecological backgrounds, and the regional context of food and agriculture influence perceptions. In general, the results of the surveys indicate that the participants in both countries consider genetic engineering to be an important tool to address agricultural, nutritional, and environmental problems, and they do not regard transgenic foods as risky for consumers. However, they are concerned about the potential impact of such transgenic crops on their countries' rich biological diversity and do not believe that national biosafety guidelines will be implemented properly. Although the surveys show that stakeholder attitudes in the Philippines and Mexico are quite similar, they also highlight significant differences in perception often related to cultural and political aspects.

Notes: Dermal absorption experiments form an important component in the assessment of risk from exposure to pesticides and other substances. Much dermal absorption data is gathered in rat experiments carried out using a certain standard protocol. Uncertainties in these data arise from many sources and can be quite large. For example, measurements of the systemic absorption of hexaconazole differed by more than an order of magnitude within a single experiment. Two diniconazole studies produced quite different results, due to minor differences in protocol and in chemical formulation. Limits of detection can also prevent accurate measurement when the amounts absorbed are small. These examples illustrate the need for measuring and reporting uncertainties in estimates that are based on these data. The most direct way to estimate uncertainty is to compute the sample standard deviations of replicate measurements. By pooling these estimates across dose and duration groups for which they are similar, the number of degrees of freedom is increased, and more precise confidence intervals can be obtained. In particular, the ratio of upper to lower 95% confidence limits was reduced by as much as ten-fold for hexaconazole, seven-fold for uniconazole, and nearly four-fold for propiconazole.

Notes: Recent advances in risk assessment have led to the development of joint dose-response models to describe prenatal death and fetal malformation rates in developmental toxicity experiments. These models can be used to estimate the effective dose corresponding to a 5% excess risk for both these toxicological endpoints, as well as for overall toxicity. In this article, we develop optimal experimental designs for the estimation of the effective dose for developmental toxicity using joint Weibull dose-response models for prenatal death and fetal malformation. Based on an extended series of developmental studies, near-optimal designs for prenatal death, malformation, and overall toxicity were found to involve three dose groups: an unexposed control group, a high dose equal to the maximum tolerated dose, and a low dose above or comparable to the effective dose. The effect on the optimal designs of changing the number of implants and the degree of intra-litter correlation is also investigated. Although the optimal design has only three dose groups in most cases, practical considerations involving model lack of fit and estimation of the shape of the dose-response curve suggest that, in practice, suboptimal designs with more than three doses will often be preferred.

Notes: Life cycle impact assessment (LCIA) and comparative risk assessment (RA) use the same building blocks for analyzing fate and potential effects of toxic substances. It is tacitly assumed that emission-effect calculations can give uniform and decisive answers in debates on toxicity problems. For several decades, mainstream policy sciences have taken a different starting point when analyzing decision making on complex, controversial societal issues. Such controversies in essence are thought to be caused by the fact that different actor coalitions adhere to a different, but in scientific terms equally reasonable, conceptualization or “framing” of the problem. A historical, argumentative analysis of the Dutch chlorine debate and the Swedish PVC debate shows that this is also true in the discussions on toxic substances. Three frames have been identified, which were coined the “risk assessment frame,”“the strict control frame,” and the “precautionary frame.” These frames tacitly disagree about the extent of knowledge/ignorance about the impacts of substances, the robustness/fallibility of emission-reduction schemes, and the robustness/vulnerability of nature. The latter frame, adhered to by environmentalists, seeks to judge substances mainly on their inherent safety. Under the current institutional arrangements and practices, RA and LCIA are executed mainly in line with the philosophy expressed by the risk assessment frame. This article gives various suggestions for dealing with framing in debates on toxic substances. One of the options is elaborated in somewhat more detail, i.e., the development of multiple indicators and calculation schemes for RA and LCIA that reflect the different frames. An outline is given for a possible indicator system reflecting the precautionary principle.

Notes: Quantitative risk assessment (RA) and life cycle assessment (LCA) are both analytical tools used to support decision making in environmental management. They have been developed and used by largely separate groups of specialists, and it is worth considering whether there is a common research agenda that may increase the relevance of these tools in decision-making processes. The validity of drawing comparisons between use of the tools is established through examining key aspects of the two approaches for their similarities and differences, including the nature of each approach and contextual and methodological aspects. Six case studies involving use of each approach in public decision making are described and used to draw out concerns about using RA and LCA in this context. The following categories of concern can be distinguished: philosophical approach of the tools; quantitative versus qualitative assessment; stakeholder participation; the nature of the results; and the usefulness of the results in relation to time and financial resource requirements. These can be distilled into a common policy research agenda focusing on: the legitimacy of using tools built on a particular perspective in decision making; recognition and role of value judgments in RA and LCA; treatment of uncertainty and variability; the influence of analytical tools in focusing attention on particular aspects of a decision-making situation; and understandability of the results for nonspecialists. It is concluded that it is time to bring together the experiences of RA and LCA specialists and benefit from cross-fertilization of ideas.

Notes: Life cycle assessment (LCA) is a framework for comparing products according to their total estimated environmental impact, summed over all chemical emissions and activities associated with a product at all stages in its life cycle (from raw material acquisition, manufacturing, use, to final disposal). For each chemical involved, the exposure associated with the mass released into the environment, integrated over time and space, is multiplied by a toxicological measure to estimate the likelihood of effects and their potential consequences. In this article, we explore the use of quantitative methods drawn from conventional single-chemical regulatory risk assessments to create a procedure for the estimation of the cancer effect measure in the impact phase of LCA. The approach is based on the maximum likelihood estimate of the effect dose inducing a 10% response over background, ED10, and default linear low-dose extrapolation using the slope βED10 (0.1/ED10). The calculated effects may correspond to residual risks below current regulatory compliance requirements that occur over multiple generations and at multiple locations; but at the very least they represent a “using up” of some portion of the human population's ability to accommodate emissions. Preliminary comparisons are performed with existing measures, such as the U.S. Environmental Protection Agency's (U.S. EPA's) slope factor measure q1*. By analyzing bioassay data for 44 chemicals drawn from the EPA's Integrated Risk Information System (IRIS) database, we explore estimating ED10 from more readily available information such as the median tumor dose rate TD50 and the median single lethal dose LD50. Based on the TD50, we then estimate the ED10 for more than 600 chemicals. Differences in potential consequences, or severity, are addressed by combining βED10 with the measure disability adjusted life years per affected person, DALYp. Most of the variation among chemicals for cancer effects is found to be due to differences in the slope factors (βED10) ranging from 10−4 up to 104 (risk of cancer/mg/kg-day).

Notes: Environmental decision-support tools often predict a multitude of different human health effects due to environmental stressors. The accounting and aggregating of these morbidity and mortality outcomes is key to support decision making and can be accomplished by different methods that we call human health metrics. This article attempts to answer two questions: Does it matter which metric is chosen? and What are the relevant characteristics of these metrics in environmental applications? Three metrics (quality adjusted life years (QALYs), disability adjusted life years (DALYs), and willingness to pay (WTP)) have been applied to the same diverse set of health effects due to environmental impacts. In this example, the choice of metric mattered for the ranking of these environmental impacts and it was found for this example that WTP was dominated by mortality outcomes. Further, QALYs and DALYs are sensitive to mild illnesses that affect large numbers of people and the severity of these mild illnesses are difficult to assess. Eight guiding questions are provided in order to help select human health metrics for environmental decision-support tools. Since health metrics tend to follow the paradigm of utility maximization, these metrics may be supplemented with a semi-quantitative discussion of distributional and ethical aspects. Finally, the magnitude of age-dependent disutility due to mortality for both monetary and nonmonetary metrics may bear the largest practical relevance for future research.

Notes: The tragic attacks of September 11 and the bioterrorist threats with respect to anthrax that followed have raised a set of issues regarding how we deal with events where there is considerable ambiguity and uncertainty about the likelihood of their occurrence and their potential consequences. This paper discusses how one can link the tools of risk assessment and our knowledge of risk perception to develop risk management options for dealing with extreme events. In particular, it suggests ways that the members of the Society for Risk Analysis can apply their expertise and talent to the risks associated with terrorism and discusses the changing roles of the public and private sectors in dealing with extreme events.

Notes: Beryllium is the strongest of the lightweight metals. Used primarily in military applications prior to the end of the Cold War, beryllium is finding new applications in many commercial products, including computers, telecommunication equipment, and consumer and automotive electronics. The use of beryllium in nondefense consumer applications is of concern because beryllium is toxic. Inhalation of beryllium dust or vapor causes a chronic lung disease in some individuals at concentrations as low as 0.01 μg/m3 in air. As beryllium enters wider commerce, it is prudent to ask what risks this might present to the general public and to workers downstream of the beryllium materials industry. We address this question by evaluating the potential for beryllium exposure from the manufacturing, use, recycle, and disposal of beryllium-containing products. Combining a market study with a qualitative exposure analysis, we determine which beryllium applications and life cycle phases have the largest exposure potential. Our analysis suggests that use and maintenance of the most common types of beryllium-containing products do not result in any obvious exposures of concern, and that maintenance activities result in greater exposures than product use. Product disposal has potential to present significant individual risks, but uncertainties concerning current and future routes of product disposal make it difficult to be definitive. Overall, additional exposure and dose-response data are needed to evaluate both the health significance of many exposure scenarios, and the adequacy of existing regulations to protect workers and the public. Although public exposures to beryllium and public awareness and concern regarding beryllium risks are currently low, beryllium risks have psychometric qualities that may lead to rapidly heightened public concern.

Notes: Preregulation estimates of benefits and costs are rarely validated after regulations are implemented. This article performs such a validation for the mandatory automobile airbag requirement. We found that the original 1984 model used to estimate benefits became invalid when 1997 values were input into that 1984 model. However, using a published 1997 cost-effectiveness model, we demonstrate, by replacing the model inputs with the values from 1984, that the 1997 cost-effectiveness ratios, based on real-world crash data and tear-down cost data, are less attractive than what would have been originally anticipated. The three most important errors in the 1984 input values are identified: the overestimation of airbag effectiveness, the overestimation of baseline fatality/injury rates, and the underestimation of manual safety belt use. This case study, which suggests that airbags are a reasonable investment in safety, shows that the regulatory analysis tools do not always produce findings that are biased against health, safety, and environmental regulation. Future validation studies of health, safety, and environmental regulation should focus on validation of benefit and risk estimates, areas where we found significant error, as well as on cost estimates.

Notes: Biomagnification of organochlorine and other persistent organic contaminants by higher trophic level organisms represents one of the most significant sources of uncertainty and variability in evaluating potential risks associated with disposal of dredged materials. While it is important to distinguish between population variability (e.g., true population heterogeneity in fish weight, and lipid content) and uncertainty (e.g., measurement error), they can be operationally difficult to define separately in probabilistic estimates of human health and ecological risk. We propose a disaggregation of uncertain and variable parameters based on: (1) availability of supporting data; (2) the specific management and regulatory context (in this case, of the U.S. Army Corps of Engineers/U.S. Environmental Protection Agency tiered approach to dredged material management); and (3) professional judgment and experience in conducting probabilistic risk assessments. We describe and quantitatively evaluate several sources of uncertainty and variability in estimating risk to human health from trophic transfer of polychlorinated biphenyls (PCBs) using a case study of sediments obtained from the New York-New Jersey Harbor and being evaluated for disposal at an open water off-shore disposal site within the northeast region. The estimates of PCB concentrations in fish and dietary doses of PCBs to humans ingesting fish are expressed as distributions of values, of which the arithmetic mean or mode represents a particular fractile. The distribution of risk values is obtained using a food chain biomagnification model developed by Gobas(1,2) by specifying distributions for input parameters disaggregated to represent either uncertainty or variability. Only those sources of uncertainty that could be quantified were included in the analysis. Results for several different two-dimensional Latin Hypercube analyses are provided to evaluate the influence of the uncertain versus variable disaggregation of model parameters. The analysis suggests that variability in human exposure parameters is greater than the uncertainty bounds on any particular fractile, given the described assumptions.

Notes: Delays in evoked potential latencies were observed at increased exposures to methylmercury from seafood in two cohorts of children. Because this outcome parameter appeared to be virtually independent of confounders, including cultural differences, a joint analysis of benchmark doses was carried out. Comparable cohort members included 382 Faroese and 113 Madeiran children without middle ear infection or neurological disease at age seven years. Maternal hair-mercury concentrations at parturition in the Faroese cohort ranged from 0.6 to 39.1 μg/g (geometric average, 4.49 μg/g). In Madeira, mothers who had not changed their diet since pregnancy had current hair-mercury concentrations ranging from 1.1 to 54.4 μg/g (geometric average 10.14 μg/g). The mercury-associated delay in peak III latencies at two frequencies (20 and 40 Hz) showed similar regression equations in the two groups of children, and benchmark dose calculations were therefore carried out for the two groups separately and jointly. For a doubling of a 5% prevalence of abnormal results of the peak III latencies at 40 Hz in a linear dose-response model, the benchmark dose for the maternal hair-mercury concentration was 8.79 μg/g for the Faroese children; 8.04 μg/g for the Madeiran children; and 9.46 μg/g for both groups. Results were similar for the 20 Hz condition. Benchmark dose results were substantially lower using a logarithmic or square root curve function, although the difference in fit between the curves was far from statistically significant. The benchmark results using evoked potential latencies are in close agreement with results based on neuropsychological test performance.

Notes: We discuss the management of catastrophe-risks from a theoretical point of view. The concept of a catastrophe is informally and formally defined, and a number of desiderata for catastrophe-averse decision rules are introduced. However, the proposed desiderata turn out to be mutually inconsistent. As a consequence of this result, it is argued that the ``rigid'' form of catastrophe aversion articulated by, for example, the maximin rule, the maximum probable loss rule, (some versions of) the precautionary principle, and the rule proposed in Ekenberg et al. (1997, 2000) should be given up. An alternative form of ``non-rigid'' catastrophe aversion is considered.

Notes: We review briefly some examples that would support an extended role for quantitative sensitivity analysis in the context of model-based analysis (Section 1). We then review what features a quantitative sensitivity analysis needs to have to play such a role (Section 2). The methods that meet these requirements are described in Section 3; an example is provided in Section 4. Some pointers to further research are set out in Section 5.

Notes: Because ethical considerations often preclude directly determining the human health effects of treatments or interventions by experimentation, such effects are estimated by extrapolating reactions predicted from animal experiments. Under such conditions, it must be demonstrated that the reliability of the extrapolated predictions is not excessively affected by inherent data limitations and other components of model specification. This is especially true of high-level models composed of ad hoc algebraic equations whose parameters do not correspond to specific physical properties or processes. Models based on independent experimental data restricting the numerical space of parameters that do represent actual physical properties can be represented at a more detailed level. Sensitivities of the computed trajectories to parameter variations permit more detailed attribution of uncertainties in the predictions to these low-level properties. S-systems, in which parameters are estimated empirically, and physiological models, whose parameters can be estimated accurately from independent data, are used to illustrate the applicability of trajectory sensitivity analysis to lower-level models.

Notes: Exposure scenarios are a critical part of risk assessment; however, representative scenarios are not generally available for tribal communities where a traditional subsistence lifestyle and diet are relevant and actively encouraged. This article presents portions of a multipathway exposure scenario developed by AESE, Inc. in conjunction with the Spokane Tribal Cultural Resources Program. The scenario serves as the basis for a screening-level reasonable maximum exposure (RME) developed for the Midnite Uranium Mine Superfund site. The process used in developing this scenario balances the need to characterize exposures without revealing proprietary information. The scenario and resulting RME reflect the subsistence use of original and existing natural resources by a hypothetical but representative family living on the reservation at or near the mine site. The representative family lives in a house in a sparsely populated conifer forest, tends a home garden, partakes in a high rate of subsistence activities (hunting, gathering, fishing), uses a sweat lodge daily, has a regular schedule of other cultural activities, and has members employed in outdoor monitoring of natural and cultural resources. The scenario includes two largely subsistence diets based on fish or game, both of which include native plants and home-grown produce. Data gaps and sources of uncertainty are identified. Additional information that risk assessors and agencies need to understand before doing any kind of risk assessment or public health assessment in tribal situations is presented.

Notes: The destruction by terrorists of the twin towers of the World Trade Center and major damage wrought to the Pentagon on September 11, 2001, followed closely by the bioterrorist anthrax attacks via the mails raised the question of whether risk analysis might have a place in defending the United States against terrorist attacks. After first reviewing the multifaceted nature of terrorism and the reasons it is likely to become endemic in world society in the long term, just as other areas of crime are endemic, this article surveys several fields of risk analysis, finding possible short- and long-term uses of risk analysis. The areas chiefly considered are: risk communication and chemical, biological, and technological risk analysis. Broad policy and other uses are also considered. The author finds that risk analysis has already played some role, perhaps informally, but he sees the possibility for a much larger, formal one, a role that is centrally important for the present and future of the United States and the world.

Notes: Incidents can be defined as low-probability, high-consequence events and lesser events of the same type. Lack of data on extremely large incidents makes it difficult to determine distributions of incident size that reflect such disasters, even though they represent the great majority of total losses. If the form of the incident size distribution can be determined, then predictive Bayesian methods can be used to assess incident risks from limited available information. Moreover, incident size distributions have generally been observed to have scale invariant, or power law, distributions over broad ranges. Scale invariance in the distributions of sizes of outcomes of complex dynamical systems has been explained based on mechanistic models of natural and built systems, such as models of self-organized criticality. In this article, scale invariance is shown to result also as the maximum Shannon entropy distribution of incident sizes arising as the product of arbitrary functions of cause sizes. Entropy is shown by simulation and derivation to be maximized as a result of dependence, diversity, abundance, and entropy of multiplicative cause sizes. The result represents an information-theoretic explanation of invariance, parallel to those of mechanistic models. For example, distributions of incident size resulting from 30 partially dependent causes are shown to be scale invariant over several orders of magnitude. Empirical validation of power law distributions of incident size is reviewed, and the Pareto (power law) distribution is validated against oil spill, hurricane, and insurance data. The applicability of the Pareto distribution, in particular, for assessment of total losses over a planning period is discussed. Results justify the use of an analytical, predictive Bayesian version of the Pareto distribution, derived previously, to assess incident risk from available data.

Notes: The fugacity model for evaluating DDTs dynamic performances in the environment was combined with the dietary exposure evaluation model, including the contribution of imported food, to develop the macroscopic mathematical model relating DDTs in the environment with the health risks of the reference Japanese. The model validity was examined by comparing the simulated DDTs concentrations in environmental media, various kinds of food, and dietary intake with those observed. Numerical simulations were done for the past half and future of one century to evaluate the effect of the DDTs usage prohibition in 1970 in Japan. The major results obtained under the limits considered are as follows. The DDTs concentrations in environmental media, various kinds of foods, and the dietary intake showed the steady exponential decrease after the DDTs usage prohibition in 1970. The DDE/DDTs ratio is larger in the higher position in an ecological system, and increased steadily with time. The critical exposure of DDTs occurred through animal product intake until 1960; after 1990 marine product intake caused the most exposure. The estimated DDTs intake was evaluated to be less than the PTDI and RfD. The annual excess cancer induction risk due to the annual dietary intake of DDTs was the largest at the level of (0.5−2.0)×10−6 (1/yr) in the early 1970s. The effect of the DDT usage prohibition on dietary exposure reduction was expected to appear after about 20 years. The life-span excess cancer induction risk was conservatively estimated to be larger than 10−5 (1/lifespan) for the reference Japanese who were born before 1970. The DDTs usage prohibition in 1970 was effective to reduce the life-span cancer risk under the 10−5 level.

Notes: In the event of a terrorist attack or catastrophic release involving potential chemical and/or biological warfare agents, decisionmakers will need to make timely and informed choices about whether, or how, to respond. The objective of this article is to provide a decision framework to specify initial and follow-up actions, including possible decontamination, and to address long-term health and environmental issues. This decision framework consists of four phases, beginning with the identification of an incident and ending with verification that cleanup and remediation criteria have been met. The flowchart takes into account both differences and similarities among potential agents or toxins at key points in the decision-making process. Risk evaluation and communication of information to the public must be done throughout the process to ensure a successful effort.

Notes: Probabilistic risk analyses often construct multistage chance trees to estimate the joint probability of compound events. If random measurement error is associated with some or all of the estimates, we show that resulting estimates of joint probability may be highly skewed. Joint probability estimates based on the analysis of multistage chance trees are more likely than not to be below the true probability of adverse events, but will sometimes substantially overestimate them. In contexts such as insurance markets for environmental risks, skewed distributions of risk estimates amplify the ``winner's curse'' so that the estimated risk premium for low-probability events is likely to be lower than the normative value. Skewness may result even in unbiased estimators of expected value from simple lotteries, if measurement error is associated with both the probability and pay-off terms. Further, skewness may occur even if the error associated with these two estimates is symmetrically distributed. Under certain circumstances, skewed estimates of expected value may result in risk-neutral decisionmakers exhibiting a tendency to choose a certainty equivalent over a lottery of equal expected value, or vice versa. We show that when distributions of estimates of expected value are positively skewed, under certain circumstances it will be optimal to choose lotteries with nominal values lower than the value of apparently superior certainty equivalents. Extending the previous work of Goodman (1960), we provide an exact formula for the skewness of products.

Notes: The practice of chlorine disinfection of drinking water to reduce microbial risks provides substantial benefits to public health. However, increasing concern around potential risks of cancer associated with exposure to chlorinated disinfection byproducts confuses this issue. This article examines the science agenda regarding chlorinated disinfection byproducts (CDBP) and cancer in Canada and the United States, focusing on the social construction of scientific knowledge claims and evidence. Data for this analysis were obtained from published documents as well as from in-depth interviews with epidemiologists and toxicologists centrally involved with the issue in both countries. Results of the analysis suggest that toxicological scientists want to close the door on the “chloroform issue” due to increasing evidence that chloroform is safe at low doses, because epidemiological scientists can no longer move forward the cancer science until significant improvements can be made in assessing human exposures, and because the scientific foci of research on DBP have shifted accordingly. Further, a distinction emerges in terms of how scientific uncertainties are interpreted when they cross-cut disciplines in the context of human health risk assessment. We suggest this tension reflects a balance of how uncertainty and authorities are managed in a mandated science-policy domain. Sufficient evidence was provided to keep the DBP issue on the regulatory agenda and to generate additional research, yet authorities and concomitant interpretations of uncertainty were contested. Such science generation and contestation inevitably influences complex risk assessment processes with respect to what water-related health risks are addressed and how.

Notes: This guest editorial is a summary of the NCSU/USDA Workshop on Sensitivity Analysis held June 11–12, 2001 at North Carolina State University and sponsored by the U.S. Department of Agriculture's Office of Risk Assessment and Cost Benefit Analysis. The objective of the workshop was to learn across disciplines in identifying, evaluating, and recommending sensitivity analysis methods and practices for application to food-safety process risk models. The workshop included presentations regarding the Hazard Assessment and Critical Control Points (HACCP) framework used in food-safety risk assessment, a survey of sensitivity analysis methods, invited white papers on sensitivity analysis, and invited case studies regarding risk assessment of microbial pathogens in food. Based on the sharing of interdisciplinary information represented by the presentations, the workshop participants, divided into breakout sessions, responded to three trigger questions: What are the key criteria for sensitivity analysis methods applied to food-safety risk assessment? What sensitivity analysis methods are most promising for application to food safety and risk assessment? and What are the key needs for implementation and demonstration of such methods? The workshop produced agreement regarding key criteria for sensitivity analysis methods and the need to use two or more methods to try to obtain robust insights. Recommendations were made regarding a guideline document to assist practitioners in selecting, applying, interpreting, and reporting the results of sensitivity analysis.

Notes: The concept of Hazard Analysis and Critical Control Point (HACCP) is a system that enables the production of safe meat and poultry products through the thorough analysis of production processes, identification of all hazards that are likely to occur in the production establishment, the identification of critical points in the process at which these hazards may be introduced into product and therefore should be controlled, the establishment of critical limits for control at those points, the verification of these prescribed steps, and the methods by which the processing establishment and the regulatory authority can monitor how well process control through the HACCP plan is working. The history of the development of HACCP is reviewed, and examples of practical applications of HACCP are described.

Notes: A sequence of linear, monotonic, and nonmonotonic test problems is used to illustrate sampling-based uncertainty and sensitivity analysis procedures. Uncertainty results obtained with replicated random and Latin hypercube samples are compared, with the Latin hypercube samples tending to produce more stable results than the random samples. Sensitivity results obtained with the following procedures and/or measures are illustrated and compared: correlation coefficients (CCs), rank correlation coefficients (RCCs), common means (CMNs), common locations (CLs), common medians (CMDs), statistical independence (SI), standardized regression coefficients (SRCs), partial correlation coefficients (PCCs), standardized rank regression coefficients (SRRCs), partial rank correlation coefficients (PRCCs), stepwise regression analysis with raw and rank-transformed data, and examination of scatter plots. The effectiveness of a given procedure and/or measure depends on the characteristics of the individual test problems, with (1) linear measures (i.e., CCs, PCCs, SRCs) performing well on the linear test problems, (2) measures based on rank transforms (i.e., RCCs, PRCCs, SRRCs) performing well on the monotonic test problems, and (3) measures predicated on searches for nonrandom patterns (i.e., CMNs, CLs, CMDs, SI) performing well on the nonmonotonic test problems.

Notes: The issue of variation is highly important in dose-response analysis: variation among genetically related pathogens infecting the same host, but also variation among hosts, in susceptibility to infection by the same pathogen. This latter issue is addressed here for the protozoan parasite Cryptosporidium parvum, the causative agent for many outbreaks of water-borne gastrointestinal illness. In human feeding studies, infectivity has been shown to be low in subjects with high preexisting anti-Cryptosporidium IgG-levels. Here we adapt the hit theory model of microbial infection to incorporate covariables, characterizing the immune status of the susceptible host. The probability of any single oocyst in the inoculum to cause infection appears to depend on preexisting IgG-levels. This does not necessarily imply direct protection by the humoral immune system; high IgG-levels may reflect a recent episode of infection/illness, and be an epi-phenomenon associated with other protective responses. The IgG-dependence of the dose-response relation can be easily applied in quantitative risk analysis. The distribution of anti-Cryptosporidium IgG levels in the general population is accessible by analyzing serum banks, which are maintained in many Western countries. Using such an approach provides first insights into the variation of susceptibility to infection in the general population.

Notes: I have assembled traditional ways to think about human needs and power along with empirical data to support a mental model of human values. The hierarchy of needs from the world of psychology and the hierarchy of power from the world of diplomacy provide a structure for the model. The empirical data collected from several nations over the last three decades support the structure. Furthermore, an examination of specific trends in this data for specific values indicates that it is not impossible to achieve a sustainable world driven by sustainable values. A world that will be defined by its successful movement toward the ``triple bottom line,'' a term articulated by John Elkington, is a world in which economic prosperity, environmental protection, and social equity are aligned. To say that the model allows one to address terrorism is based on the assumption that the lack of social equity or the perception of that lack determines the likelihood of terrorism.

Notes: Concerns about stigmatization are an important influence on the development of risk management and communication policies for a wide range of technologies and products such as those associated with hazardous waste storage, nuclear power, and genetic engineering of plants or foods. Although much attention has been placed on the adverse economic effects of stigma, we believe that the social, psychological, and cultural impacts are often at least as significant and merit greater attention from policymakers and researchers. Evidence for these impacts of stigma is found in recent studies of resource-based communities, whose residents may be shunned by local and nonlocal publics and whose products may suffer a loss of markets, which in turn creates social and economic hardship for community residents. We examine these aspects of stigma and link descriptions of the problem and prescriptions of recommended policies to five underlying characteristics of stigma, focusing on the possible insights and contributions from trade-off analysis and narrative approaches.

Notes: A third generation of environmental policy making and risk management will increasingly impose environmental measures, which may give rise to analyzing countervailing risks. Therefore, a comprehensive analysis of all risks associated with the decision alternatives will aid decisionmakers in prioritizing alternatives that effectively reduce both target and countervailing risks. Starting with the metaphor of the ripples caused by a stone that is thrown into a pond, we identify 10 types of ripples that symbolize, in our case, risks that deserve closer examination: direct, upstream, downstream, accidental risks, occupational risks, risks due to offsetting behavior, change in disposable income, macro-economic changes, depletion of natural resources, and risks to the manmade environment. Tools to analyze these risks were developed independently and recently have been applied to overlapping fields of application. This suggests that either the tools should be linked in a unified framework for comparative analysis or that the appropriate field of application for single tools should be better understood. The goals of this article are to create a better foundation for the understanding of the nature and coverage of available tools and to identify the remaining gaps. None of the tools is designed to deal with all 10 types of risk. Provided data suggest that, of the 10 types of identified risks, those associated with changes in disposable income may be particularly significant when decision alternatives differ with respect to their effects on disposable income. Finally, the present analysis was limited to analytical questions and did not capture the important role of the decision-making process itself.

Notes: Modern technology, together with an advanced economy, can provide a good or service in myriad ways, giving us choices on what to produce and how to produce it. To make those choices more intelligently, society needs to know not only the market price of each alternative, but the associated health and environmental consequences. A fair comparison requires evaluating the consequences across the whole “life cycle”—from the extraction of raw materials and processing to manufacture/construction, use, and end-of-life—of each alternative. Focusing on only one stage (e.g., manufacture) of the life cycle is often misleading. Unfortunately, analysts and researchers still have only rudimentary tools to quantify the materials and energy inputs and the resulting damage to health and the environment. Life cycle assessment (LCA) provides an overall framework for identifying and evaluating these implications. Since the 1960s, considerable progress has been made in developing methods for LCA, especially in characterizing, qualitatively and quantitatively, environmental discharges. However, few of these analyses have attempted to assess the quantitative impact on the environment and health of material inputs and environmental discharges. Risk analysis and LCA are connected closely. While risk analysis has characterized and quantified the health risks of exposure to a toxicant, the policy implications have not been clear. Inferring that an occupational or public health exposure carries a nontrivial risk is only the first step in formulating a policy response. A broader framework, including LCA, is needed to see which response is likely to lower the risk without creating high risks elsewhere. Even more important, LCA has floundered at the stage of translating an inventory of environmental discharges into estimates of impact on health and the environment. Without the impact analysis, policymakers must revert to some simple rule, such as that all discharges, regardless of which chemical, which medium, and where they are discharged, are equally toxic. Thus, risk analysts should seek LCA guidance in translating a risk analysis into policy conclusions or even advice to those at risk. LCA needs the help of RA to go beyond simplistic assumptions about the implications of a discharge inventory. We demonstrate the need and rationale for LCA, present a brief history of LCA, present examples of the application of this tool, note the limitations of LCA models, and present several methods for incorporating risk assessment into LCA. However, we warn the reader not to expect too much. A comprehensive comparison of the health and environmental implications of alternatives is beyond the state of the art. LCA is currently not able to provide risk analysts with detailed information on the chemical form and location of the environmental discharges that would allow detailed estimation of the risks to individuals due to toxicants. For example, a challenge for risk analysts is to estimate health and other risks where the location and chemical speciation are not characterized precisely. Providing valuable information to decisionmakers requires advances in both LCA and risk analysis. These two disciplines should be closely linked, since each has much to contribute to the other.

Notes: We employ the intake fraction (iF) as an effective tool for expressing the source-to-intake relationship for pollutant emissions in life cycle analysis (LCA) or comparative risk assessment. Intake fraction is the fraction of chemical mass emitted into the environment that eventually passes into a member of the population through inhalation, ingestion, or dermal exposure. To date, this concept has been primarily applied to pollutants whose primary route of exposure is inhalation. Here we extend the use of iF to multimedia pollutants with multiple exposure pathways. We use a level III multimedia model to calculate iF for TCDD and compare the result to one calculated from measured levels of dioxin toxic equivalents in the environment. We calculate iF for emissions to air and surface water for 308 chemicals. We correlate the primary exposure route with the magnitudes of the octanol-water partition coefficient, Kow, and of the air-water partitioning coefficient (dimensionless Henry constant), Kaw. This results in value ranges of Kow and Kaw where the chemical exposure route can be classified with limited input data requirements as primarily inhalation, primarily ingestion, or multipathway. For the inhalation and ingestion dominant pollutants, we also define empirical relationships based on chemical properties for quantifying the intake fraction. The empirical relationships facilitate rapid evaluation of many chemicals in terms of the intake. By defining a theoretical upper limit for iF in a multimedia environment we find that iF calculations provide insight into the multimedia model algorithms and help identify unusual patterns of exposure and questionable exposure model results.

Notes: In Part 1 of this article we developed an approach for the calculation of cancer effect measures for life cycle assessment (LCA). In this article, we propose and evaluate the method for the screening of noncancer toxicological health effects. This approach draws on the noncancer health risk assessment concept of benchmark dose, while noting important differences with regulatory applications in the objectives of an LCA study. We adopt the central tendency estimate of the toxicological effect dose inducing a 10% response over background, ED10, to provide a consistent point of departure for default linear low-dose response estimates (βED10). This explicit estimation of low-dose risks, while necessary in LCA, is in marked contrast to many traditional procedures for noncancer assessments. For pragmatic reasons, mechanistic thresholds and nonlinear low-dose response curves were not implemented in the presented framework. In essence, for the comparative needs of LCA, we propose that one initially screens alternative activities or products on the degree to which the associated chemical emissions erode their margins of exposure, which may or may not be manifested as increases in disease incidence. We illustrate the method here by deriving the βED10) slope factors from bioassay data for 12 chemicals and outline some of the possibilities for extrapolation from other more readily available measures, such as the no observable adverse effect levels (NOAEL), avoiding uncertainty factors that lead to inconsistent degrees of conservatism from chemical to chemical. These extrapolations facilitated the initial calculation of slope factors for an additional 403 compounds; ranging from 10−6 to 103 (risk per mg/kg-day dose). The potential consequences of the effects are taken into account in a preliminary approach by combining the βED10) with the severity measure disability adjusted life years (DALY), providing a screening-level estimate of the potential consequences associated with exposures, integrated over time and space, to a given mass of chemical released into the environment for use in LCA.

Notes: Empirical examinations of the “social amplification of risk” framework are rare, partly because of the difficulties in predicting when conditions likely to result in amplification effects will occur. This means that it is difficult to examine changes in risk perception that are contemporaneous with increases and/or decreases in social or media discussion of the risks associated with a particular risk event. However, the collection of attitude data before, during, and after the increased reporting of the risks of genetically modified food in the United Kingdom (spring 1999) has demonstrated that people's risk perceptions do increase and decrease in line with what might be expected upon examination of the amplification and attenuation mechanisms integral to the framework. Perceptions of benefit, however, appeared to be permanently depressed by negative reporting about genetically modified food. Trust in regulatory institutions with responsibility for protecting the public was not affected. It was concluded that the social amplification of risk framework is a useful framework for beginning to explain the potential impact on risk perceptions of a risk event, particularly if that risk event is presented to the public as a new hazard occurring in a crisis context.

Notes: An exposure model was developed to relate seafood consumption to levels of methylmercury (reported as mercury) in blood and hair in the U.S. population, and two subpopulations defined as children aged 2–5 and women aged 18–45. Seafood consumption was initially modeled using short-term (three-day) U.S.-consumption surveys that recorded the amount of fish eaten per meal. Since longer exposure periods include more eaters with a lower daily mean intake, the consumption distribution was adjusted by broadening the distribution to include more eaters and reducing the distribution mean to keep total population intake constant. The estimate for the total number of eaters was based on long-term purchase diaries. Levels of mercury in canned tuna, swordfish, and shark were based on FDA survey data. The distribution of mercury levels in other species was based on reported mean levels, with the frequency of consumption of each species based on market share. The shape distribution for the given mean was based on the range of variation encountered among shark, tuna, and swordfish. These distributions were integrated with a simulation that estimated average daily intake over a 360-day period, with 10,000 simulated individuals and 1,000 uncertainty iterations. The results of this simulation were then used as an input to a second simulation that modeled levels of mercury in blood and hair. The relationship between dietary intake and blood mercury in a population was modeled from data obtained from a 90-day study with controlled seafood intake. The relationship between blood and hair mercury in a population was modeled from data obtained from several sources. The biomarker simulation employed 2,000 simulated individuals and 1,000 uncertainty iterations. These results were then compared to the recent National Health and Nutrition Examination Survey (NHANES) that tabulated blood and hair mercury levels in a cross-section of the U.S. population. The output of the model and NHANES results were similar for both children and adult women, with predicted mercury biomarker concentrations within a factor of two or less of NHANES biomarker results. However, the model tended to underpredict blood levels for women and overpredict blood and hair levels for children.

Notes: In the past decade, the use of probabilistic risk analysis techniques to quantitatively address variability and uncertainty in risks increased in popularity as recommended by the 1994 National Research Council that wrote Science and Judgment in Risk Assessment. Under the 1996 Food Quality Protection Act, for example, the U.S. EPA supported the development of tools that produce distributions of risk demonstrating the variability and/or uncertainty in the results. This paradigm shift away from the use of point estimates creates new challenges for risk managers, who now struggle with decisions about how to use distributions in decision making. The challenges for risk communication, however, have only been minimally explored. This presentation uses the case studies of variability in the risks of dying on the ground from a crashing airplane and from the deployment of motor vehicle airbags to demonstrate how better characterization of variability and uncertainty in the risk assessment lead to better risk communication. Analogies to food safety and environmental risks are also discussed. This presentation demonstrates that probabilistic risk assessment has an impact on both risk management and risk communication, and highlights remaining research issues associated with using improved sensitivity and uncertainty analyses in risk assessment.

Notes: This article explores two problems analysts face in determining how to estimate values for children's health and safety risk reductions. The first addresses the question: Do willingness-to-pay estimates for health risk changes differ across children and adults and, if so, how? To answer this question, the article first examines the potential effects of age and risk preferences on willingness to pay. A summary of the literature reporting empirical evidence of differences between willingness to pay for adult health and safety risk reductions and willingness to pay for health and safety risk reductions in children is also provided. The second dimension of the problem is a more fundamental issue: Whose perspective is relevant when valuing children's health effects—society's, children's, adults-as-children, or parents'? Each perspective is considered, followed ultimately by the conclusion that adopting a parental perspective through an intrahousehold allocation model seems closest to meeting the needs of the estimation problem at hand. A policy example in which the choice of perspective affects the outcome of a regulatory benefit-cost analysis rounds out the article and emphasizes the importance of perspective.

Notes: This paper contributes a methodological framework to identify, prioritize, assess, and manage risk scenarios of a large-scale system. Qualitative screening of scenarios and classes of scenarios is appropriate initially, while quantitative assessments may be applied once the set of all scenarios (hundreds) has been prioritized in several phases. The eight-phase methodology is described in detail and is applied to operations other than war. The eight phases are as follows: Phase I, Scenario Identification—A hierarchical holographic model (HHM) is developed to describe the system's ``as planned'' or ``success'' scenario. Phase II, Scenario Filtering—The risk scenarios identified in Phase I are filtered according to the responsibilities and interests of the current system user. Phase III, Bi-Criteria Filtering and Ranking. Phase IV, Multi-Criteria Evaluation. Phase V, Quantitative Ranking—We continue to filter and rank scenarios based on quantitative and qualitative matrix scales of likelihood and consequence; and ordinal response to system resiliency, robustness, redundancy. Phase VI, RiskManagement is performed, involving identification of management options for dealing with the filtered scenarios, and estimating the cost, performance benefits, and risk reduction of each. Phase VII, Safeguarding Against Missing Critical Items—We examine the performance of the options selected in Phase VI against the scenarios previously filtered out during Phases II to V. Phase VIII, OperationalFeedback—We use the experience and information gained during application to refine the scenario filtering and decision processes in earlier phases. These eight phases reflect a philosophical approach rather than a mechanical methodology. In this philosophy, the filtering and ranking of discrete scenarios is viewed as a precursor to, rather than a substitute for, consideration of the totality of all risk scenarios.

Notes: Methods of engineering risk analysis are based on a functional analysis of systems and on the probabilities (generally Bayesian) of the events and random variables that affect their performances. These methods allow identification of a system's failure modes, computation of its probability of failure or performance deterioration per time unit or operation, and of the contribution of each component to the probabilities and consequences of failures. The model has been extended to include the human decisions and actions that affect components' performances, and the management factors that affect behaviors and can thus be root causes of system failures. By computing the risk with and without proposed measures, one can then set priorities among different risk management options under resource constraints. In this article, I present briefly the engineering risk analysis method, then several illustrations of risk computations that can be used to identify a system's weaknesses and the most cost-effective way to fix them. The first example concerns the heat shield of the space shuttle orbiter and shows the relative risk contribution of the tiles in different areas of the orbiter's surface. The second application is to patient risk in anesthesia and demonstrates how the engineering risk analysis method can be used in the medical domain to rank the benefits of risk mitigation measures, in that case, mostly organizational. The third application is a model of seismic risk analysis and mitigation, with application to the San Francisco Bay area for the assessment of the costs and benefits of different seismic provisions of building codes. In all three cases, some aspects of the results were not intuitively obvious. The probabilistic risk analysis (PRA) method allowed identifying system weaknesses and the most cost-effective way to fix them.

Notes: Life cycle assessment (LCA) and risk assessment are operationally different but share the common purpose of supporting decisions about reducing threats to human welfare. Both analysis methods also involve a complex mixture of science and value judgments reflecting epistemological as well as moral and esthetic values. The inability of risk assessment and LCA to be “value free” has been a source of considerable controversy in both communities. Recognition of the contingent and social nature of human interpretation of the risks and environmental impacts created by public and private decisions has led to an increased appreciation of the importance of involving interested and affected parties in risk characterization. Comparison of the value-based nature of LCA and risk assessment demonstrates the need for participation in LCA. Although the need for participation by affected parties in decision-making processes is gaining acceptance, there is little agreement as to how participation should be structured. Risk assessment and LCA have a shared need for research examining the design and analysis of participation processes appropriate to a given decision context. A proposed framework recommends participation strategies designed to enhance the effectiveness of policy-driven analyses such as risk assessment and LCA based on the level of trust that interested and affected parties have for other policy participants.

Notes: One of the common challenges for life cycle impact assessment and risk assessment is the need to estimate the population exposures associated with emissions. The concept of intake fraction (a unitless term representing the fraction of material or its precursor released from a source that is eventually inhaled or ingested) can be used when limited site data are available or the number of sources to model is large. Although studies have estimated intake fractions for some pollutant-source combinations, there is a need to quickly and accurately estimate intake fractions for sources and settings not previously evaluated. It would be expected that limited source or site information could be used to yield intake fraction estimates with reasonable accuracy. To test this theory, we developed regression models to predict intake fractions previously estimated for primary fine particles (PM2.5) and secondary sulfate and nitrate particles from power plants and mobile sources in the United States. Our regression models were able to predict pollutant-specific intake fractions with R2 between 0.53 and 0.86 and equations that reflected expected relationships (e.g., intake fraction increased with population density, stack height influenced the intake fraction of primary but not secondary particles). Further analysis would be needed to generalize beyond this case study and construct models applicable across source categories and settings, but our analysis demonstrates that inclusion of a limited number of parameters can significantly reduce the uncertainty in population-average exposure estimates.a

Notes: Refinements of methods for life cycle impact assessment (LCIA) are directed at removing unjustified simplifications and quantifying and reducing uncertainties in results. The amount of uncertainty reduction that is actually achieved through LCIA method refinement depends on the structure of the life cycle inventory model. We investigate the general structure of inventory models using an economic input/output (I/O) life cycle assessment model of the U.S. economy. In particular, we study the results of applying a streamlining algorithm to the I/O LCA model. The streamlining algorithm retains only those “branches” of the process tree that are jointly required to account for a specified fraction of the total impacts upstream of each point in the tree. We examine the implications of these “tree pruning” results for site-informed LCIA. Percentiles are presented for U.S. commodities and several important pollutants, for the share of total upstream emissions contributed by the set of processes in each supply tier, that is, each set of processes that directly supply inputs to another set of processes. Capturing at least 90% of the total direct plus upstream emissions for criteria air pollutants and toxic releases for at least 75% of the commodities in the U.S. economy requires full modeling of direct emissions plus the first five supply tiers. The requirements for capturing a high percentage (e.g., 〉 80%) of total emissions vary widely across products or commodities. To capture more than 60% of total emissions for more than half of all commodities requires models with more than 4,000 process instances. To well characterize the total impacts of products, life cycle impact assessment methods must characterize foreground process impacts in a site-informed way and mean impacts of far-removed processes in an unbiased way.

Notes: Quality adjusted life years (QALYs) and willingness to pay (WTP) are alternative measures of the value of reductions in health risk that are often used in evaluating environmental, health, and safety practices. Although both methods are based on individual preferences, the underlying assumptions differ. The different bases yield systematically different conclusions about the relative value of reducing health and mortality risks to individuals that differ in age, preexisting health conditions, income, and other factors. The choice of which method to use depends on judgments about what constraints should be placed on individual preferences and what factors should be considered in aggregating preferences across people.

Notes: Increasing residential insulation can decrease energy consumption and provide public health benefits, given changes in emissions from fuel combustion, but also has cost implications and ancillary risks and benefits. Risk assessment or life cycle assessment can be used to calculate the net impacts and determine whether more stringent energy codes or other conservation policies would be warranted, but few analyses have combined the critical elements of both methodologies. In this article, we present the first portion of a combined analysis, with the goal of estimating the net public health impacts of increasing residential insulation for new housing from current practice to the latest International Energy Conservation Code (IECC 2000). We model state-by-state residential energy savings and evaluate particulate matter less than 2.5 μm in diameter (PM2.5, NOx, and SO2 emission reductions. We use past dispersion modeling results to estimate reductions in exposure, and we apply concentration-response functions for premature mortality and selected morbidity outcomes using current epidemiological knowledge of effects of PM2.5 (primary and secondary). We find that an insulation policy shift would save 3 × 1014 British thermal units or BTU (3 × 1017 J) over a 10-year period, resulting in reduced emissions of 1,000 tons of PM2.5, 30,000 tons of NOx, and 40,000 tons of SO2. These emission reductions yield an estimated 60 fewer fatalities during this period, with the geographic distribution of health benefits differing from the distribution of energy savings because of differences in energy sources, population patterns, and meteorology. We discuss the methodology to be used to integrate life cycle calculations, which can ultimately yield estimates that can be compared with costs to determine the influence of external costs on benefit-cost calculations.

Notes: Two recent papers on risk perception models are discussed. In these papers, quantitative analyses are presented of risk perception in relation to risk characteristics as specified in the Psychometric Model, and to cultural biases according to Cultural Theory. This comment points out that the data quality of these two studies is doubtful, with a very small convenience sample and a very low response rate. More importantly, the analyses show the same low levels of explained variance of risk perception as other researchers have found previously, but the authors still draw optimistic conclusions from their data. Such conclusions are unjustified.

Notes: Studies using open-ended response modes to elicit probabilistic beliefs have sometimes found an elevated frequency (or blip) at 50 in their response distributions. Our previous research(1–3) suggests that this is caused by intrusion of the phrase “fifty-fifty,” which represents epistemic uncertainty, rather than a true numeric probability of 50%. Such inappropriate responses pose a problem for decision analysts and others relying on probabilistic judgments. Using an explicit numeric probability scale (ranging from 0–100%) reduces thinking about uncertain events in verbal terms like “fifty-fifty,” and, with it, exaggerated use of the 50 response.(1,2) Here, we present two procedures for adjusting response distributions for data already collected with open-ended response modes and hence vulnerable to an exaggerated presence of 50%. Each procedure infers the prevalence of 50s had a numeric probability scale been used, then redistributes the excess. The two procedures are validated on some of our own existing data and then applied to judgments elicited from experts in groundwater pollution and bioremediation.

Notes: This is a study of risk perception in relation to New Age (NA) beliefs, including traditional folk superstition and belief in paranormal phenomena, as well as use of alternative healing practices. Data were also obtained on trust dimensions and on personality and psychopathology variables, as well as religious involvement. It was found that four factors accounted for the investigated NA beliefs, which were termed higher consciousness beliefs, denial of analytic knowledge, traditional superstition, and belief in the physical reality of the soul. NA beliefs were strongly and positively related to religious involvement, and negatively to educational level. These beliefs were also positively related to maladjustment and to concerns over tampering with nature. In regression analyses, it was found that NA beliefs explained about 15% of the variance of perceived risk, and that the most powerful explanatory factors were higher consciousness beliefs and beliefs in paranormal phenomena. Traditional superstition and use of healing practices did not contribute to explaining perceived risk.

Notes: A new mathematical model for permeability of chemicals in aqueous vehicle through skin is presented. The rationale for this model is to represent diffusion by its fundamental molecular mechanism, i.e., random thermal motion. Diffusion is modeled as a two-dimensional random walk through the biphasic (lipid and corneocyte) stratum corneum (SC). This approach permits calculations of diffusion phenomena in a morphologically realistic SC structure. Two concepts are key in the application of the model to the prediction of steady-state skin permeability coefficients: ``effective diffusivity'' and ``effective path length,'' meaning the diffusivity and thickness of a homogeneous membrane having identical permeation properties as the stratum corneum. Algebraic expressions for these two variables are developed as functions of the molecular weight and octanol-water partition coefficient of the diffusing substance. Combining these with expressions for membrane-vehicle partition coefficient and permeability of the aqueous epidermis enables the calculation of steady-state skin permeability coefficients. The resulting four-parameter algebraic model was regressed against the ``Flynn data base'' with excellent results (R2=0.84;SE=0.0076; F=154;N=94). The model provides insight into the contributions of stratum corneum diffusivity and effective path lengths to overall skin permeability and may prove useful in the prediction of non-steady-state diffusion phenomena.

Notes: Identification and qualitative comparison of sensitivity analysis methods that have been used across various disciplines, and that merit consideration for application to food-safety risk assessment models, are presented in this article. Sensitivity analysis can help in identifying critical control points, prioritizing additional data collection or research, and verifying and validating a model. Ten sensitivity analysis methods, including four mathematical methods, five statistical methods, and one graphical method, are identified. The selected methods are compared on the basis of their applicability to different types of models, computational issues such as initial data requirement and complexity of their application, representation of the sensitivity, and the specific uses of these methods. Applications of these methods are illustrated with examples from various fields. No one method is clearly best for food-safety risk models. In general, use of two or more methods, preferably with dissimilar theoretical foundations, may be needed to increase confidence in the ranking of key inputs.

Notes: Three topics are addressed: (1) measurement issues (e.g., the reliability and validity of neurobehavioral test scores), (2) general principles of assessment, including test selection, and (3) interpretation of scores. Psychological tests generally perform as well as medical tests in terms of reliability and validity. Test manuals, assessment textbooks, and psychologists are useful resources to the risk assessor. The variety of different tests employed in neurobehavioral studies complicates interstudy comparisons. In addition, tests that ostensibly assess the same general domain of function might assess somewhat different abilities within that domain. Although a uniform battery for use in all studies seems desirable, the battery appropriate for a specific study depends on study goals, knowledge about the mechanism(s) of neurotoxicity, nature of the study population, and pattern of exposure. Exposure-related neurobehavioral deficits are generally indicators of ``altered function'' rather than of ``clinical disease.'' Limiting concern to end points corresponding to clinical disease might not be appropriate. Many neurobehavioral diagnoses are phenomenological and a neurotoxicant might cause a unique pattern of deficits for which no label has been created. The concern that a small shift in the central tendency of a distribution of test scores has no significance for the individual should be reexamined in light of the prevention paradox, formulated on the basis of epidemiologic studies of chronic disease. Poor performance on a neurobehavioral test does not necessarily map clearly onto underlying behavioral or neural substrate. The absence of such linkages, given current knowledge about brain-behavior relationships, should not reduce confidence in neurobehavioral end points. Use of neurobehavioral test scores involves considerations that differ little from those that the risk assessor routinely addresses in using end points commonly used in research on other topics in environmental epidemiology.

Notes: The attack that occurred on September 11, 2001 was, in the end, the result of a failure to detect and prevent the terrorist operations that hit the United States. The U.S. government thus faces at this time the daunting tasks of first, drastically increasing its ability to obtain and interpret different types of signals of impending terrorist attacks with sufficient lead time and accuracy, and second, improving its ability to react effectively. One of the main challenges is the fusion of information, from different sources (U.S. or foreign), and of different types (electronic signals, human intelligence, etc.). Fusion thus involves two very distinct and separate issues: communications, i.e., ensuring that the different U.S. and foreign intelligence agencies communicate all relevant and accurate information in a timely fashion and, perhaps more difficult, merging the content of signals, some ``sharp'' and some ``fuzzy,'' some dependent and some independent into useful information. The focus of this article is on the latter issue, and on the use of the results. In this article, I present a classic probabilistic Bayesian model sometimes used in engineering risk analysis, which can be helpful in the fusion of information because it allows computation of the posterior probability of an event given its prior probability (before the signal is observed) and the quality of the signal characterized by the probabilities of false positive and false negative. Experience suggests that the nature of these errors has been sometimes misunderstood; therefore, I discuss the validity of several possible definitions.

Notes: This article presents the methodology and the simulation results concerning the quantitative assessment of exposure to the fungus toxin named Ochratoxin A (OA) in food, in humans in France. We show that is possible to provide reliable calculations of exposure to OA with the conjugate means of a nonparametric-type method of simulation, a parametric-type method of simulation, and the use of bootstrap confidence intervals. In the context of the Monte Carlo simulation, the nonparametric method takes into account the consumptions and the contaminations in the simulations only via the raw data whereas the parametric method depends on the random samplings from distribution functions fitted to consumption and contamination data. Our conclusions are based on eight types of food only. Nevertheless, they are meaningful due to the major importance of these foodstuffs in human nourishment in France. This methodology can be applied whatever the food contaminant (pesticides, other mycotoxins, Cadmium, etc.) when data are available.

Notes: This article summarizes a quantitative microbial risk assessment designed to characterize the public health impact of consumption of shell eggs and egg products contaminated with Salmonella Enteritidis (SE). This risk assessment's objectives were to: (1) establish the baseline risk of foodborne illness from SE, (2) identify and evaluate potential risk mitigation strategies, and (3) identify data gaps related to future research efforts. The risk assessment model has five modules. The Egg Production module estimates the number of eggs produced that are SE-contaminated. Shell Egg Processing, Egg Products Processing, and Preparation & Consumption modules estimate the increase or decrease in the numbers of SE organisms in eggs or egg products as they pass through storage, transportation, processing, and preparation. A Public Health Outcomes module then calculates the incidence of illnesses and four clinical outcomes, as well as the cases of reactive arthritis associated with SE infection following consumption. The baseline model estimates an average production of 2.3 million SE-contaminated shell eggs/year of the estimated 69 billion produced annually and predicts an average of 661,633, human illnesses per year from consumption of these eggs. The model estimates ≈ 94% of these cases recover without medical care, 5% visit a physician, an additional 0.5% are hospitalized, and 0.05% result in death. The contribution of SE from commercially pasteurized egg products was estimated to be negligible. Five mitigation scenarios were selected for comparison of their individual and combined effects on the number of human illnesses. Results suggest that mitigation in only one segment of the farm-to-table continuum will be less effective than several applied in different segments. Key data gaps and areas for future research include the epidemiology of SE on farms, the bacteriology of SE in eggs, human behavior in food handling and preparation, and human responses to SE exposure.

Notes: The behavioral dimension matters in Probabilistic Risk Analysis (PRA) since players throughout a system incur costs to increase system reliability interpreted as a public good. Individual strategies at the subsystem level generally conflict with collective desires at the system level. Game theory, the natural tool to analyze individual-collective conflicts that affect risk, is integrated into PRA. Conflicts arise in series, parallel, and summation systems over which player(s) prefer(s) to incur the cost of risk reduction. Frequently, the series, parallel, and summation systems correspond to the four most common games in game theory, i.e., the coordination game, the battle of the sexes and the chicken game, and prisoner's dilemma, respectively.

Notes: This article tackles the problem of controversies expressed by experts in the field of estimating and managing ionizing radiation risks. We analyze the paradigms that were conceived on this subject, in particular the studies carried out by the International Commission on Radiological Protection (ICRP), as well as the papers stating either that the effect of low doses is relatively weak or, on the contrary, relatively serious. Uncertainties, which taint the risk estimations, assume a particular importance because they are at the origin of the request for expert and value judgments and represent the critical point of the discussions on the ionizing radiation risks. Our study allows us to look further into the problem of the paradigm's formation, uncertainties, and expert and value judgments, and provides areas for consideration that may contribute to a better understanding of certain gridlocks in the decision-making process, as regards to environmental, health, and energy policies.

Notes: The U.S. Department of Energy's Columbia River Comprehensive Impact Assessment (CRCIA) was an ambitious attempt to direct its cleanup of the Hanford Nuclear Reservation toward the most significant risks to the Columbia River resulting from past plutonium production. DOE's approach was uncommonly open, including tribal, regulatory agency, and other Hanford interest group representatives on the board that was to develop the assessment approach. The CRCIA process had attributes of the “analytic-deliberative” process for risk assessment recommended by the National Research Council. Nevertheless, differences between the DOE and other participants over what was meant by the term “comprehensive” in the group's charge, coupled with differing perceptions of the likely effectiveness of remediation efforts in reducing risks, were never resolved. The CRCIA effort became increasingly fragmented and the role its products were to play in influencing future clean-up decisions increasingly ambiguous. A procedural evaluation of the CRCIA process, based on Thomas Webler's procedural normative model of public participation, reveals numerous instances in which theoretical-normative discourse disconnects occurred. These had negative implications for both the basic procedural dimensions of Webler's model—fairness and competence. Tribal and other interest group representatives lacked the technical resources necessary to make or challenge what philosopher Jurgens Habermas terms cognitive validity claims, while DOE and its contractors did not challenge normative claims made by tribal representatives. The results are cautionary for implementation of the analytic-deliberative process. They highlight the importance of bringing rigor to the evaluation of the quality of the deliberation component of risk characterization via the analytic-deliberative process, as well as to the analytic component.

Notes: A mechanistic model is presented describing the clearance of a compound in a precision-cut liver slice that is incubated in a culture medium. The problem of estimating metabolic rate constants in PBPK models from liver slice experiments is discussed using identifiability analysis. From the identifiability problem analysis, it appears that in addition to the clearance, the compound's free fraction in the slice and the diffusion rate of the exchange of the compound between culture medium and liver slice should be identified. In addition, knowledge of the culture medium volume, the slice volume, the compound's free fraction, and octanol-water-based partition between medium and slice is presupposed. The formal solution for identification is discussed from the perspective of experimental practice. A formally necessary condition for identification is the sampling of parent compound in liver slice or culture medium. However, due to experimental limitations and errors, sampling the parent compound in the slice together with additional sampling of metabolite pooled from the medium and the slice is required for identification in practice. Moreover, it appears that identification results are unreliable when the value of the intrinsic clearance exceeds the value of the diffusion coefficient, a condition to be verified a posteriori.

Notes: I investigate how different sources of information influence the diffusion of pharmaceutical innovations. In prescription-drug markets, both advertising and scientific information stemming from clinical trials can affect physicians' prescription choices. Using novel indices of clinical-research output, I find that both marketing and scientific evidence directly influence the diffusion process in the antiulcer-drug market, with marketing having a more pronounced influence. I also find evidence that clinical outputs are important drivers of firms' marketing efforts, affecting sales indirectly. Taken together, the direct and indirect effects of science on demand imply strong private incentives for clinical research. I conclude that product-market competition in the pharmaceutical industry is shaped by both advertising rivalries and scientific rivalries. Moreover, drug advertising may perform an important informative function.

Notes: The paper studies the effects of bundling on the bidding strategies and seller revenues in auctions when the bidders have common values for the objects. Bundling of objects before the auction reduces the problem of the winner's curse, and the bidders bid more aggressively. This does not mean that a bundled auction is always better for the seller's revenue. Indeed, there is another effect that makes the bundled auction preferable (from the seller's standpoint) if and only if the number of bidders is small. While this is the only effect present in an independent-private-values model, it does not vanish when bidders have pure common values for the objects. The paper concludes that a bundled auction is unambiguously better for the seller than separate auctions when the number of bidders is small.

Notes: There are a growing body of theoretical work, wide anecdotal evidence, and a few large-scale empirical studies supporting the view that business firms quite rarely change their organizational structure, a phenomenon usually referred to in the literature as structural inertia. The present paper aims to analyze empirically the determinants of structural inertia and organizational change. As far as we know, this work constitutes the first attempt to directly address such issues through econometric estimates based on a large, longitudinal dataset at plant level. For this purpose, we consider changes of the organizational structure within a sample composed of 438 Italian manufacturing plants observed from 1975 to 1996. More precisely, we specify and test a duration model of the likelihood of an individual plant changing the number of hierarchical tiers after a spell r, provided that no change has occurred up to T. We also analyze the direction of change, distinguishing increases from decreases of the number of managerial layers. We consider a set of plant- and industry-specific explanatory variables that are expected to induce or oppose organizational change. The findings show that the adoption of advanced manufacturing technologies and new human-resources management practices favors organizational change. On the contrary, the presence of sunk costs and the extent of influence activities figure prominently in explaining structural inertia of business organizations.

Notes: A simple model of open source software (as typified by the GNU-Linux operating system) is presented. Individual user-programmers decide whether to invest their own effort to develop a software enhancement that will become a public good if so developed. The effect of changing the population size of user-programmers is considered; finite and asymptotic results are given. Welfare results are presented. It is shown that whether development will increase when applications have a modular structure depends on whether the developer base exceeds a critical size. Potential explanations of several stylized facts are given, including why certain useful programs don't get written.

Notes: This paper examines the effect of memory loss on the continuity of behavior. We consider a player (individual or firm) who remembers previous actions but not underlying rationales. In a stable environment, relative to a full-recall scenario, memory loss increases the probability of following old policies (inertia). In a volatile environment, memory loss can decrease this probability (impulsiveness). The model provides a memory-loss explanation for some documented psychological biases, implies that inertia and organizational routines should be more important in stable environments than in volatile ones, and provides empirical implications relating memory and environmental variables to economic decisions.

Notes: Syndication arises when venture capitalists jointly invest in projects. We model and test two possible reasons for syndication: project selection, as an additional venture capitalist provides an informative second opinion; and complementary management skills of additional venture capitalists. The central question is whether venture capitalists are engaged primarily in selection or in managerial value added. These alternatives imply contrasting predictions about comparative returns to syndicated and standalone investments. Our empirical analysis, using Canadian data, finds that syndicated investments have higher returns, favoring the value-added interpretation. We also discuss risk sharing and project scale as possible reasons for syndication.

Notes: In the context of an employment relationship, I present an argument suggesting that it is more efficient for the boss to own the productive assets. The idea is that a conflict between productivity and depreciation is internalized if the player deciding what an asset is used for also has residual claims. An empirical test finds evidence consistent with this. By asking whether the boss should own the assets, the paper reverses the reasoning from the literature in which it is argued that the owner has power and thus is the boss.

Notes: Cooperative equilibria can be supported in a repeated game when players use trigger strategies. This paper tests how well trigger strategies explain behavior in two-person experimental games. Reducing payoffs for choices larger than the Cournot level induces smaller average outputs, behavior generally consistent with trigger strategy models. Reducing payoffs for choices well above the Cournot level will not affect behavior if actions are consistent with a trigger strategy involving longer-lived, less intense punishment phases (the grim-reaper strategy), but would matter for trigger strategies with short-lived but intense punishment phases. Results show that behavior is most consistent with the former.

Notes: Knickerbocker (1973) introduced the notion of oligopolistic reaction to explain why firms follow rivals into foreign markets. We develop a model that incorporates central features of Knickerbocker's story—oligopoly, uncertainty, and risk aversion—to establish the conditions required to generate follow-the-leader behavior. We find that rival foreign investment will make risk-neutral firms less inclined to move abroad once its rivals have done so. We show that Knickerbocker's prediction relies on risk aversion and derive an expression for the minimum amount of risk aversion needed to generate oligopolistic reaction.

Notes: Horizontal mergers between firms that have different costs are examined. Owners can transfer technology to an acquired firm and decide whether to consolidate or operate their firms as separate entities in the product market. Thus mergers can exhibit both efficiencies and a market-power effect. The prices of target firms are determined via a bargaining game. An equilibrium sequence of mergers entails the largest firm targeting the next largest rival firm. Initially, this sequence of mergers with technology transfers involves no consolidations and improves welfare. Ultimately, the acquisitions lead to consolidation and may decrease total welfare.

Notes: This note corrects Proposition 3 of Chang (1998).

Notes: It is often claimed that (i) managers work too hard on operational issues and do not spend enough effort on strategic activities, and (ii) something can be done about this by introducing nonfinancial performance measures, as for instance with a balanced scorecard. We give an explanation for both claims in a formal model. The distortion toward operational effort arises because with financial performance measures strategic effort can only be rewarded in the future. But renegotiation-proof long-term compensation plans entail too weak variable components in the future. This problem can be reduced by introducing performance measures that help to disentangle strategic and operational effects.