The self-discovery of a suspicious symptom often brings about an emotional turbulence: while recognizing the importance of having the symptom diagnosed promptly, individuals frequently delay diagnosis, seeking to avoid the pain or discomfort associated with the diagnostic process and fearing to hear that they are developing a serious illness. The present paper proposes a rational, economic-oriented approach to explaining individuals' delay behavior, weighing the fear of the diagnostic procedure and of being told the suspected truth against the fear of consequence of further procrastination. Assuming that the money costs of diagnosis and medical treatment are borne by health insurance, a multi-period expected-utility maximization model is constructed to inquire into the individual's decision of whether and to what extent to delay diagnosis. The results rationalize a variety of observed behavior concerning individuals' reaction to suspicious symptoms that differ in their psychic cost of diagnosis, the likelihood of indicating severe illness and the potential damage to health incurred by delayed diagnosis. The desirability of delayed diagnosis to the health insurer and the socially desired solution are finally discussed.

In 1999 a research program was started with the goal of finding the main reasons that influence people's decisions to insure themselves against losses caused by flood. In a field study a questionnaire that measured perception of the flood risk and motives for insuring or not insuring against the consequences of this disaster was used. The data were collected on a group of 66 households that were hit by flood in 1997. As expected, the results showed that the insurance decisions were related to a few basic psychological factors of flood-risk perception. The most important finding was that people who reported greater fear while thinking about flood bought insurance more often after the flood had occurred than people who did not report fear. Another factor of flood-risk perception, knowledge about flood, was not related to any aspect of insurance decisions. The practical implications of these findings are discussed.

Utility theory as developed by Von Neuman and Morgenstern provides an elegant way to make consistent choices among risky alternatives by maximizing the expected value of a personal utility function over known probability distributions of outcomes. The theory is usually presented in the context of a single (possibly complex) decision, where it gives little guidance on the choice of a utility function. This paper provides a tutorial on the consequences of applying expected utility theory to repeated decisions, using theory and simulation to reveal the statistical regularity arising cumulatively from repeatedly applying the same utility. If decisions are repeated and consequences accumulate, two utility functions stand out as maximizing cumulative incremental growth and cumulative compound growth, namely the linear utility and the logarithmic utility, respectively. Repeatedly basing decisions on the linear utility when compound growth applies and severe losses are possible can be disastrous in the long term. Relevance to financial investment and population catastrophes is considered.

We re-examine the subjects’ behavior in the ultimatum bargaining experiments studied by Roth et al. (1991, American Economic Review). In our model, un-modeled factors including rationality determine players’ initial aspirations, and a modified version of the case-based learning process governs subsequent adaptations. The calibration results of this paper show that ‘satisficing’ can explain the actual subjects’ behavior surprisingly well. More precisely, it is shown that 77.7% to 96.7% of the observed behavior is consistent with our model prediction. We also argue that the closer the initial aspiration levels are to the perfect equilibrium payoff, the lower the mean or modal offer tends to be in the actual experiments.

Genetic algorithm search techniques provide an innovative and robust means of optimization in complex, multivariate real-scale problems. In this paper we present an application of genetic algorithms to the optimization of airport operation and development for an increasing traffic situation. The approach is proven successful and much less time consuming compared to traditional what-if analysis. In addition to the base case optimization results, sensitivity analyses both with respect to the economic parameters of the fitness function, subject to the optimization, and with respect to some important genetic algorithm settings have been performed and yield consistent results.

This paper develops a behavioral model of farmer decision making to analyze the incentives for adoption of a technology that provides information about spatial variability in nutrient availability and enables variable rate application of fertilizers. It examines the implications of uncertainty about the accuracy of the technology on input application and adoption decisions. Risk aversion and uncertainty can lead to the imposition of a risk premium on input use, which create incentives to over or under apply fertilizers. This influences not only the incentives to adopt the technology but also the impact of adoption on pollution. High spatial variability mitigates the disincentives for adoption even if fixed costs are high and farm size is small but the extent to which this occurs depends on the degree of risk aversion and uncertainty. These results have implications for the design and effectiveness of cost–share subsidies to induce adoption and reduce over application of fertilizers.

The paper addresses basic issues associated with incorporating human and organizational factors in risk analysis of hazardous systems. A conceptual framework has been developed for systematic incorporating these factors in probabilistic models and the risk assessment to be used for the safety management. The methodology outlined in the paper is a synthesis or generalization of techniques and procedures used for performing HRA in the context of PSA, applying both the quantitative and qualitative methods. The similarities and differences of hierarchical influence diagrams (HIDs) compared with hierarchical structures of the AHP method and the influence diagrams used in the FSA methodology developed by IMO are examined. Illustrative examples are included. Finally a fuzzy extension of the proposed approach is introduced.

The standard account of the ‘reflection effect’ (Kahneman and Tversky, 1979) is that attitude toward risk changes across gain or loss framings of outcomes. Weber and Bottom (1989) proposed an alternative account in which decision makers have stable risk attitudes, but changing risk perceptions. Undergraduates were randomly assigned to read one of three hypothetical informed consent documents from a trial of a cholesterol-lowering drug. Documents used gain, loss or both framings to describe expected benefits. Respondents rated riskiness of participation and non-participation in the trial and made a choice about whether they would participate in the trial.

The reflection effect was replicated. In addition, as predicted by the Weber and Bottom account, respondents in the gain condition were more likely to rate participation as riskier than non-participation compared to respondents in the loss condition, and in each condition more than 70 per cent of respondents chose to avoid the option they judged as riskier. Implications for informed consent are discussed.

This paper describes the HARIA-2 methodology for external emergency planning and analysis. The main aim of the HARIA-2 research project is to investigate the possibility of taking into account not only the physical phenomena, but also sociological aspects in technological emergencies. The methodology has been implemented in two software packages.

1. DEMONSTRATOR, which allows to efficiently simulate various accident scenarios; it can also be used for training rescue services and as a support tool for decision making during real emergencies;

2. PROTOTYPE system, addressing emergency planning issues, developed on a commercial GIS platform (Arc-View 3.2©); it integrates all data bases and models developed, including those simulating population behaviour and the evacuation plan, even though in a simplified mode.

The paper describes the main aspects of the HARIA-2 methodology and two examples of application, namely the Mexico City disaster (1984) and a simulation exercise of evacuation for the Milazzo industrial area.

This study examined the relations between risk cognitions and risk behavior. Adolescents’ perceptions of the risks associated with driving after drinking (DAD) and their perceptions of the prevalence of this behavior among their peers were assessed, and these perceptions were used to predict their DAD behavior. Results provided evidence of a type of cognitive social influence: the more common adolescents thought the behavior was, the less risk, both personal and general, they attributed to it. As expected, however, this relation was significant only for those who were high in a tendency to engage in social comparison. Perceptions of risk, in turn, were prospectively related to risk behavior for all participants. Specifically, low perceived risk, especially personal risk, was associated with an increase in DAD behavior. Implications of the results for DAD interventions are discussed.

Modern transportation systems are complex and therefore require effective risk management decision tools. These help to help rank alternatives, allocate resources, and certify critical transportation operations. Existing methods may not accommodate the dynamics of changing environments and personnel threats. They may not handle hard-to-quantify, disparate data, and they may be unable to realistically estimate uncertainty. In this paper we discuss a coordinated set of ongoing model-development efforts to overcome such difficulties.

The opportunity of switching from road to rail or to a combination of road and rail (intermodal) transport is being considered in many countries with the objective of risk reduction in the transport of dangerous goods. This work presents a quantitative approach based on risk analysis for comparing the hazards of road, rail, and intermodal transport, aimed at defining criteria for selecting the safest transport modality. When comparing road and rail transport, the risk mainly depends on the hazardous characteristics of the product. The size of the containers is generally larger for rail transport than for road transport, and consequently the amount of product potentially released, giving rise to impact areas slightly or significantly larger for rail than for road transport. When comparing road and intermodal transport, route length plays the most significant role: the longer the distance, the safer the intermodal transport.

When people attempt to evaluate their personal standing on a variety of dimensions, they often compare themselves with others. This assertion was central to the development of social comparison theory (Festinger, 1954), and has stimulated nearly 50 years of research – primarily in the areas of social psychology, clinical psychology, organizational behavior, and sociology. Social comparison processes have been explored in a broad range of domains including coping, negotiation, academic and work performance, happiness, emotion, and motivation. Numerous volumes have appeared on extensions and applications of the theory, including a recent handbook edited by Suls and Wheeler (2000).

In a multistage investment task the decision maker attempts to increase the capital by committing some part of it over several trials in a risky investment. Despite the richness of experimental results from this task, no decision strategy exists which is able to predict investment behavior. In this paper we formulate three strategies for predicting decisions in the investment task. In the success-expectation strategy (SES), the main factor determining the choice is the expected subjective probability of a success in the coming trial. In the win–loss ratio strategy (WLRS), the main factor is the relation between the possible win and the possible loss in a specific investment situation. In the linear function of capital strategy (LFCS), the available capital is the principal determinant of choice. We tested these strategies with the help of computer simulation, using data from previous experiments. With each strategy we predicted each subject's choices and compared these predictions with the observed decisions. The predictions of WLRS correlated significantly and positively with the observed data for 24 of the 39 subjects (62%), those of LFCS correlated with 14 subjects (36%), and those of SES correlated with nine subjects (23%). The findings reveal previously unsuspected patterns in deploying capital, as well as individual differences in investment behavior. Additional factors influencing strategy use and choices are discussed.

Decisions based on risk analysis require some form of risk acceptance criteria. Presently the International Maritime Organisation (IMO) has initiated an activity on developing a risk-based approach to safety and environmental protection regulations. Explicit risk estimates are new to the organisation. A limited number of FSA trial apllications have been presented so far. Whilst giving increased general knowledge of the risk level in the industry, the debate about risk acceptance has just started.

The objective of this paper is to outline an approach by which societal risk acceptance criteria may be established. The idea is to discriminate between activities representing different risks and importance to society. The societal risk acceptance criteria are calibrated against occupational fatality rates, and transportation fatality rate for scheduled air traffic worldwide. Examples are given for some different ship types. For the sake of discussion a societal risk acceptance for Near Earth objects colliding with the Earth is also derived. It should be noted that many other criteria would be needed in the decision process, like for example individual risks, criteria based on cost effectiveness, and criteria for environmental consequences. Normally a decision would have to be based on acceptance by all these criteria. Only one specific method to arrive at societal risk criteria is dealt with herein. The examples given for some ship types show that when the importance to the society is accounted for, the established FN acceptance curves vary within 1 to 2 orders of magnitude.

The outlined method may be considered for any type of activity above a certain size. An obvious limitation for the method is represented by activities of high economic value with low labour intensity in remote places, for example exploitation of offshore oil and gas resources.

Two views of game theory are discussed: (1) game theory as a description of the behavior of rational individuals who recognize each other's reationality and reasoning abilities, and (2) game theory as an internally consistent recommendation to individuals on how to act in interactive situations. It is shown that the same mathematical tool, namely modal logic, can be used to explicitly model both views.

Klein (1997) found that participants were more influenced by information about their comparative risk standing than information about their absolute risk standing. If reliable, these findings have important implications for understanding and improving risk communication. In this paper we report the findings of several unsuccessful attempts by us to replicate Klein's findings in the UK, using one of his experimental paradigms, and discuss the findings of other recent attempts to replicate his work. Findings are inconsistent from study to study but, overall, provide some evidence that people respond to comparative and not just to absolute risk information. Issues that need to be addressed systematically in future research include: the ambiguity of absolute information, proportional differences in risk magnitude, cross-cultural and individual differences in preferences for social comparison information, and the systematic exploration of responses to absolute and comparative risk information in real choice situations.

In a nuclear processing plant, four departments were compared using a 60-item questionnaire measuring safety attitudes and beliefs including the perception of managers' attitudes and behaviour, communication and risk-taking, and attitudes to taking personal responsibility for safety. Results suggest some differences at the conceptual level in addition to departmental differences and large grade differences. It is proposed that there are certainly two and possibly more differing safety cultures within this organization. The implications of this are discussed in terms of policy.

In processing expert judgements, it is common to assign experts’ opinions different degrees of plausibility or probability. This results in the necessity of constructing some kind of hierarchical model. Hierarchical models are widely used in Bayesian inference. Several models have been proposed by the adherents of imprecise statistical reasoning. This paper describes a new hierarchical uncertainty model of a more general form: first- and second-order uncertainty models are both imprecise. We demonstrate that depending on what kind of evidence the modeller has at hand and the reliability quantifying the quality of expert judgement one comes to different rules of combination. It is shown that the rules of combination known in imprecise statistical reasoning can be inferred from the approach proposed in the paper. We describe how the model can be used to generate first-order coherent interval-valued previsions. The paper is concluded by addressing the issue of computing the probability of an event ‘one imprecise value is greater than another’. This case is prominent in light of decision making based on imprecise previsions.