The Use of Mental Models in Chemical Risk Protection: Developing a Generic Workplace Methodology

We adopted a comparative approach to evaluate and extend a generic methodology to analyze the different sets of beliefs held about chemical hazards in the workplace. Our study mapped existing knowledge structures about the risks associated with the use of perchloroethylene and rosin-based solder flux in differing workplaces. "Influence diagrams" were used to represent beliefs held by chemical experts; "user models" were developed from data elicited from open-ended interviews with the workplace users of the chemicals. The juxtaposition of expert and user understandings of chemical risks enabled us to identify knowledge gaps and misunderstandings and to reinforce appropriate sets of safety beliefs and behavior relevant to chemical risk communications. By designing safety information to be more relevant to the workplace context of users, we believe that employers and employees may gain improved knowledge about chemical hazards in the workplace, such that better chemical risk management, self-protection, and informed decision making develop over time.     

An Enforceable Indoor Air Quality Standard for Environmental Tobacco Smoke in the Workplace1

Environmental tobacco smoke (ETS)has recently been determined by U.S. environmental and occupational health authorities to be a human carcinogen. We develop a model which permits using atmospheric nicotine measurements to estimate nonsmokers’ETS lung cancer risks in individual workplaces for the first time. We estimate that during the 1980s, the U.S. nonsmoking adult population's median nicotine lung exposure (homes and workplaces combined)was 143 micrograms (μg)of nicotine daily, and that most-exposed adult nonsmokers inhaled 1430 μg/day. These exposure estimates are validated by pharmacokinetic modeling which yields the corresponding steady-state dose of the nicotine metabolite, cotinine. For U.S. adult nonsmokers of working age, we estimate median cotinine values of about 1.0 nanogram per milliliter (ng/ml)in plasma, and 6.2 ng/ml in urine; for most-exposed nonsmokers, we estimate cotinine concentrations of about 10 ng/ml in plasma and 62 ng/ml in urine. These values are consistent to within 15% of the cotinine values observed in contemporaneous clinical epidemiological studies. Corresponding median risk from ETS exposure in U.S. nonsmokers during the 1980s is estimated at about two lung cancer deaths (LCDs)per 1000 at risk, and for most-exposed nonsmokers, about two LCDs per 100. Risks abroad appear similar. Modeling of the lung cancer mortality risk from passive smoking suggests that de minimis [i.e., “acceptable” (10^-6)], risk occurs at an 8-hr time-weighted-average exposure concentration of 7.5 nanograms of ETS nicotine per cubic meter of workplace air for a working lifetime of 40 years. This model is based upon a linear exposure-response relationship validated by physical, clinical, and epidemiological data. From available data, it appears that workplaces without effective smoking policies considerably exceed this de minimis risk standard. For a substantial fraction of the 59 million nonsmoking workers in the U.S., current workplace exposure to ETS also appears to pose risks exceeding the de manifestos risk level above which carcinogens are strictly regulated by the federal government.     

Interference Phenomena in Temporal Evolution of Accident Probability in Workplaces

The aim of this article is to investigate some implications of complexity in workplace risk assessment. Workplace is examined as a complex system, and some of its attributes and aspects of its behavior are investigated. Failure probability of various workplace elements is examined as a time variable and interference phenomena of these probabilities are presented. Potential inefficiencies of common perceptions in applying probabilistic risk assessment models are also discussed. This investigation is conducted through mathematical modeling and qualitative examples of workplace situations. A mathematical model for simulation of the evolution of workplace accident probability in time is developed. Its findings are then attempted to be translated in real-world terms and discussed through simple examples of workplace situations. The mathematical model indicates that workplace is more likely to exhibit an unpredictable behavior. Such a behavior raises issues about usual key assumptions for the workplace, such as aggregation. Chaotic phenomena (nonlinear feedback mechanisms) are also investigated for in simple workplace systems cases. The main conclusions are (1) that time is an important variable for risk assessment, since behavior patterns are complex and unpredictable in the long term and (2) that workplace risk identification should take place in a holistic view (not by work post).     

The simulation of industrial robot systems

This paper describes the GRASP computer aided design system for modelling and evaluating industrial robot workplaces. GRASP satisfies a range of simulation needs within the context of designing, implementing and operating industrial robotic systems. The GRASP software may be used to investigate robots operating by themselves or, more likely, as part of an integrated cell. Facilities within GRASP assist workplace layout, position and velocity evaluations, clash detection and co-ordination between items. A robot library exists and is being extended, and an embryo off-line programming facility has been used under restricted conditions. GRASP has been used to help solve a wide range of practical industrial robot problems and has proved itself technically, and also as an educational tool, by showing how a proposed system would operate. The paper describes the facilities within GRASP.     

Exposure to Environmental Tobacco Smoke in the Workplace and the Impact of Away-From-Work Exposure

Concentrating on exposure in workplaces where smoking occurs, we examined environmental tobacco smoke (ETS)-related concentration data from the 16-City Study.^(1,2) This study involved a large population of nonsmokers, used personal monitors, and encompassed a wide selection of ETS-related constituents. This first article in a series of three describes the 16-City Study, considers the impact of demographic variables, and concludes that these variables did not explain differences in exposure to ETS. We compared 16-City Study concentrations obtained in the workplace to previously reported workplace concentrations and determined that data from this study were representative of current ETS exposure in nonmanufacturing workplaces where smoking occurs. Considering factors other than demographic factors, we found that, not surprisingly, the number of cigarettes observed in the workplace had an impact on exposure concentrations. Finally, we compared people from homes where smoking occurs with people from nonsmoking homes and found that people from smoking homes observed more smoking in the workplace and experienced higher concentrations of ETS-related compounds in the workplace, even when they observed the same number of cigarettes being smoked in the workplace. In two subsequent articles in this series, we discuss relationships between various ETS markers and provide estimates of distributions of doses to nonsmoking workers employed in workplaces where smoking occurs.     

Workplace Job Satisfaction in Britain: Evidence from Linked Employer–Employee Data

The paper examines the nature of workplace job satisfaction in Britain using an ‘overall’ and domain‐specific job satisfaction outcomes from linked employer–employee data. A measure of aggregate job satisfaction alone might mask domain‐specific differences in satisfaction, something the combined approach in this paper addresses. As well as controlling for a rich set of correlates on employees and their workplaces, the paper deploys alternative empirical models that account for employee‐ and workplace‐level unobserved heterogeneity. The paper reports interesting results on the link between job satisfaction and observed as well as unobserved characteristics of employees and their workplaces.     

Use of Advances in Technology for Maritime Risk Assessment

The maritime industry is moving toward a "goal-setting" risk-based regime. This opens the way to safety engineers to explore and exploit flexible and advanced risk modeling and decision-making approaches in the design and operation processes. In this article, following a brief review of the current status of maritime risk assessment, a design/operation selection framework and a design/operation optimization framework are outlined. A general discussion of control engineering techniques and their application to risk modeling and decision making is given. Four novel risk modeling and decision-making approaches are then outlined with illustrative examples to demonstrate their use. Such approaches may be used as alternatives to facilitate risk modeling and decision making in situations where conventional techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in general engineering and technology are suggested with respect to risk modeling and decision making.     

Industrial Machine Systems Risk Assessment: A Critical Review of Concepts and Methods

Reducing the risk of work-related death and injury to machine operators and maintenance personnel poses a continuing occupational safety challenge. The risk of injury from machinery in U.S. workplaces is high. Between 1992 and 2001, there were, on average, 520 fatalities per year involving machines and, on average, 3.8 cases per 10,000 workers of nonfatal caught-in-running-machine injuries involving lost workdays. A U.S. task group recently developed a technical reference guideline, ANSI B11 TR3, "A Guide to Estimate, Evaluate, & Reduce Risks Associated with Machine Tools," that is intended to bring machine tool risk assessment practice in the United States up to or above the level now required by the international standard, ISO 14121. The ANSI guideline emphasizes identifying tasks and hazards not previously considered, particularly those associated with maintenance; and it further emphasizes teamwork among line workers, engineers, and safety professionals. The value of this critical review of concepts and methods resides in (1) its linking current risk theory to machine system risk assessment and (2) its exploration of how various risk estimation tools translate into risk-informed decisions on industrial machine system design and use. The review was undertaken to set the stage for a field evaluation study on machine risk assessment among users of the ANSI B11 TR3 method.     

AbSRiM: An Agent‐Based Security Risk Management Approach for Airport Operations

Security risk management is essential for ensuring effective airport operations. This article introduces AbSRiM, a novel agent‐based modeling and simulation approach to perform security risk management for airport operations that uses formal sociotechnical models that include temporal and spatial aspects. The approach contains four main steps: scope selection, agent‐based model definition, risk assessment, and risk mitigation. The approach is based on traditional security risk management methodologies, but uses agent‐based modeling and Monte Carlo simulation at its core. Agent‐based modeling is used to model threat scenarios, and Monte Carlo simulations are then performed with this model to estimate security risks. The use of the AbSRiM approach is demonstrated with an illustrative case study. This case study includes a threat scenario in which an adversary attacks an airport terminal with an improvised explosive device. The approach provides a promising way to include important elements, such as human aspects and spatiotemporal aspects, in the assessment of risk. More research is still needed to better identify the strengths and weaknesses of the AbSRiM approach in different case studies, but results demonstrate the feasibility of the approach and its potential.     

A Spatio‐Temporal Exposure‐Hazard Model for Assessing Biological Risk and Impact

We developed a simulation model for quantifying the spatio‐temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio‐temporal exposure‐hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (b iological risk a ssessment with R ) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.     

Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams

Probabilistic risk assessment (PRA) is a useful tool to assess complex interconnected systems. This article leverages the capabilities of PRA tools developed for industrial and nuclear risk analysis in community resilience evaluations by modeling the food security of a community in terms of its built environment as an integrated system. To this end, we model the performance of Gilroy, CA, a moderate‐size town, with regard to disruptions in its food supply caused by a severe earthquake. The food retailers of Gilroy, along with the electrical power network, water network elements, and bridges are considered as components of a system. Fault and event trees are constructed to model the requirements for continuous food supply to community residents and are analyzed efficiently using binary decision diagrams (BDDs). The study also identifies shortcomings in approximate classical system analysis methods in assessing community resilience. Importance factors are utilized to rank the importance of various factors to the overall risk of food insecurity. Finally, the study considers the impact of various sources of uncertainties in the hazard modeling and performance of infrastructure on food security measures. The methodology can be applicable for any existing critical infrastructure system and has potential extensions to other hazards.     

Application of data mining to minimize fire-induced domino effect risks

Data mining (DM) has been applied in many advanced science and technology fields, but it has still not been used for domino effect risk management to explore minimum risk scenarios. This work investigates the feasibility of DM in minimizing the risk of fire-induced domino effects in chemical processing facilities. Based on DM, an evidential failure mode and effects analysis (E-FMEA), which could bridge chemical facilities’ operational reliability and domino effect risk, is combined with fault tree analysis (FTA) for the occurrence risk modeling of loss of containment (LOC) event of chemical facilities, which is often the triggering point of fire-induced domino effects. Industry specific data such as reliability data, inspection records, and maintenance records are of great value to model the potential occurrence criticality of LOC. The data are used to characterize the LOC risk priority number (RPN) of chemical facilities through FTA and E-FMEA, search and statistics rules are proposed to mine inspection records to assess LOC risk factors. According to the RPN scores of facilities, inherent safety strategies to minimize risk via inventory control are proposed, and their effectiveness is tested using a well-known probit model. In this way, the approach proposes a unit-specific evidence-based risk minimization strategy for fire-induced domino effects. A case study demonstrates the capability of DM in the risk minimization of fire-induced domino effects.     

The Sound of Silence. Lesbian,Gay, Bisexual and Transgender Discrimination in ‘Inclusive Organizations’

Most studies on diversity and discrimination in the workplace have focused on ‘visible’ minorities such as gender or race, often neglecting the experiences of invisible minorities such as lesbian, gay, bisexual and transgender (LGBT) workers. In this paper we explore the practices of inclusion/exclusion of LGBTs in the workplace in Italian social cooperatives, which are specifically founded to create employment for people who are disadvantaged in the labour market. The study examines how organizations, which have an ethos focused on inclusion and mainly employ workers from specific social minority groups, manage the inclusion of LGBT workers. We also explore the experience of LGBT workers within these organizations. The paper reports that the culture of silence existing in the five organizations studied prevents LGBT employees from constructing a work identity which encompasses their sexual identity and prevents the organizations from achieving their aim of being fully inclusive workplaces.     

Assessments of Direct Human Exposure—The Approach of EU Risk Assessments Compared to Scenario-Based Risk Assessment

The awareness of potential risks emerging from the use of chemicals in all parts of daily life has increased the need for risk assessments that are able to cover a high number of exposure situations and thereby ensure the safety of workers and consumers. In the European Union (EU), the practice of risk assessments for chemicals is laid down in a Technical Guidance Document; it is designed to consider environmental and human occupational and residential exposure. Almost 70 EU risk assessment reports (RARs) have been finalized for high-production-volume chemicals during the last decade. In the present study, we analyze the assessment of occupational and consumer exposure to trichloroethylene and phthalates presented in six EU RARs. Exposure scenarios in these six RARs were compared to scenarios used in applications of the scenario-based risk assessment approach to the same set of chemicals. We find that scenarios used in the selected EU RARs to represent typical exposure situations in occupational or private use of chemicals and products do not necessarily represent worst-case conditions. This can be due to the use of outdated information on technical equipment and conditions in workplaces or omission of pathways that can cause consumer exposure. Considering the need for exposure and risk assessments under the new chemicals legislation of the EU, we suggest that a transparent process of collecting data on exposure situations and of generating representative exposure scenarios is implemented to improve the accuracy of risk assessments. Also, the data sets used to assess human exposure should be harmonized, summarized in a transparent fashion, and made accessible for all risk assessors and the public.     

Using Real‐Time Decision Tools to Improve Distributed Decision‐Making Capabilities in High‐Magnitude Crisis Situations*

Multi‐organizational collaborative decision making in high‐magnitude crisis situations requires real‐time information sharing and dynamic modeling for effective response. Information technology (IT) based decision support tools can play a key role in facilitating such effective response. We explore one promising class of decision support tools based on machine learning, known as support vector machines (SVM), which have the capability to dynamically model and analyze decision processes. To examine this capability, we use a case study with a design science approach to evaluate improved decision‐making effectiveness of an SVM algorithm in an agent‐based simulation experimental environment. Testing and evaluation of real‐time decision support tools in simulated environments provides an opportunity to assess their value under various dynamic conditions. Decision making in high‐magnitude crisis situations involves multiple different patterns of behavior, requiring the development, application, and evaluation of different models. Therefore, we employ a multistage linear support vector machine (MLSVM) algorithm that permits partitioning decision maker response into behavioral subsets, which can then individually model and examine their diverse patterns of response behavior. The results of our case study indicate that our MLSVM is clearly superior to both single stage SVMs and traditional approaches such as linear and quadratic discriminant analysis for understanding and predicting behavior. We conclude that machine learning algorithms show promise for quickly assessing response strategy behavior and for providing the capability to share information with decision makers in multi‐organizational collaborative environments, thus supporting more effective decision making in such contexts.     

Expanding the Content Domain of Workplace Aggression: A Three‐level Aggressor–target Taxonomy

Workplace aggression (WPA) has been largely considered to be a phenomenon involving individuals. However, higher‐level entities, such as groups and organizations, can also be aggressors (and targets). This aspect of WPA has not been given much scholarly attention and, even in cases where it has been studied, it has not been considered to be part of the WPA stream. By considering aggressors and targets at all three levels of analysis, the author attempts simultaneously to expand and integrate the WPA stream, draw attention to WPA involving higher‐level entities, and provide a more organization‐oriented (rather than individual‐oriented) perspective on WPA. This novel comprehensive perspective is provided through a taxonomy of nine aggressor–target combinations of WPA which can be grouped into three multilevel categories of WPA, i.e. lateral level WPA, upward level WPA, and downward level WPA. Implications for theory, research and practice of these conceptualizations are discussed.     

The Effects of Revealed Information on Catastrophe Loss Projection Models’ Characterization of Risk: Damage Vulnerability Evidence from Florida

We examine whether the risk characterization estimated by catastrophic loss projection models is sensitive to the revelation of new information regarding risk type. We use commercial loss projection models from two widely employed modeling firms to estimate the expected hurricane losses of Florida Atlantic University's building stock, both including and excluding secondary information regarding hurricane mitigation features that influence damage vulnerability. We then compare the results of the models without and with this revealed information and find that the revelation of additional, secondary information influences modeled losses for the windstorm‐exposed university building stock, primarily evidenced by meaningful percent differences in the loss exceedance output indicated after secondary modifiers are incorporated in the analysis. Secondary risk characteristics for the data set studied appear to have substantially greater impact on probable maximum loss estimates than on average annual loss estimates. While it may be intuitively expected for catastrophe models to indicate that secondary risk characteristics hold value for reducing modeled losses, the finding that the primary value of secondary risk characteristics is in reduction of losses in the “tail” (low probability, high severity) events is less intuitive, and therefore especially interesting. Further, we address the benefit‐cost tradeoffs that commercial entities must consider when deciding whether to undergo the data collection necessary to include secondary information in modeling. Although we assert the long‐term benefit‐cost tradeoff is positive for virtually every entity, we acknowledge short‐term disincentives to such an effort.     

Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple topologically‐oriented models to advanced physical‐flow‐based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this article is to compare performance estimates achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combinations of models to use when analyzing large‐scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed.     

Chance Constrained Programming Approach to Empirical Analyses of Mutual Fund Investment Strategies*

Chance constrained programming concepts are used to formalize risk and return relations which are then modeled for use in an empirical study of mutual fund behavior during the period 1984 through 1988. The publicly announced strategies of individual funds are used to form ex ante risk classifications which are employed in examining ex post performance. Negative relations between risk and return held in every year of the period studied. The bearing of these negative risk-return findings for the Bowman paradox, as studied in the strategic management literature, are thus extended from the industrial firms studied by Bowman (and others) and shown to be present even in these investment oriented mutual funds in each of the years of the great bull market from 1984 through 1988. Finally, our use of chance constrained programming enables us to separate risk from return behavior and evaluate their relative strengths as sources of these negative relations, which are found to be more in the returns than the risks.     

Evaluating the Effectiveness of Education,Feedback, & Task Clarification to Increase Workplace Physical Activity

ABSTRACT

Modern office workers spend the majority of their work days in sedentary positions. The risk of preventable diseases such as cardiovascular disease and various cancers increase with increased sedentary time. Thus, targeting office worker health by increasing physical activity is imperative to improve long-term risk factors. This study measured physical activity in the workplace using a commercially-available accelerometer and evaluated the extent to which feedback, and feedback and task clarification increased workplace physical activity relative to a recommended guideline to move every 30-minutes. Results indicated that feedback increased workplace physical activity to varying degrees for 4/8 participants. A social validity questionnaire indicated that workplace variables (e.g., type of task, meetings, deadlines) prevented physical activity. These variables will need to be addressed in future studies.