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Even though most people have an intuitive understanding of what is meant by risk, risk is a concept that deﬁes precise deﬁnition. Ordinary citizens as well as scientiﬁc experts diﬀerentiate between choice options or courses of actions in terms of their riskiness, and such explicit or implicit judgments of perceived riskiness often aﬀect their decisions. Some uncertainty about the outcome of a decision or action seems to be necessary to make it appear risky. This research paper describes three paradigms that deﬁne risk in diﬀerent ways and that identify diﬀerent types of variables that have been shown to aﬀect people’s perception of risk.
1. Risk Perception
The democratization of decision making and increased availability of information provide people with more choices than ever before. Economic globalization and faster social and technological change have, at the same time, introduced more uncertainty and unpredictability. Decisions under risk and uncertainty are abundant, and perceptions of risk aﬀect those decisions. People pull their money out of ﬁnancial ventures when they judge the risks to be too high or start a lawsuit when the risks of inaction outweigh the risks of litigation. The risk perceptions of individuals as citizens and consumers also aﬀect decisions made by government agencies and corporations. Public perception that silicone breast implants put users at risk of autoimmune disease, for example, resulted in bankruptcy for the manufacturer, despite clear scientiﬁc evidence of no silicone-related illnesses. Controversies about the licensing of technologies such as genetic engineering or the siting of facilities such as landﬁlls or nuclear power stations tend to be fueled primarily by disagreements about posed levels of risk, rather than by disagreements about the acceptability of speciﬁc risk levels. While business or government experts have clear quantitative evaluations and deﬁnitions of the risks that products or technologies pose, based on objective data or models, members of the general public often seem to evaluate the same options very diﬀerently. Much of the early research on psychological risk dimensions (described in Sect. 2.2) was funded by the Nuclear Regulatory Commission to understand why and how public perception of the riskiness of nuclear technology could diﬀer so dramatically from the estimates provided by nuclear engineers.
2. Measures Of Perceived Risk
Risk perception has been studied empirically within three theoretical paradigms. Studies within the axiomatic measurement paradigm have focused on the way in which people combine objective risk information, that is, possible consequences of risky choice options such as mortality rates or ﬁnancial losses and their likelihood of occurrence. Research within the psychometric paradigm has identiﬁed people’s emotional reactions to risky situations that aﬀect judgments of the riskiness of physical, environmental, and material risks in ways that go beyond their objective consequences. Studies within the sociocultural paradigm have examined the eﬀect of group- and culture- level variables on risk perception.
Risk as an explicit or implicit variable in theories of risk preference is discussed elsewhere (see Weber 1997).
2.1 Axiomatic Measurement Studies
The axiomatic measurement approach models perceived risk as a function of attributes of risky options that are described as probability distributions over possible outcomes. Much of this work derives from the deﬁnition of risk as variance in traditional models of risky choice. Under this deﬁnition sure options carry no risk, since there is no variance around the guaranteed, single, known outcome. The wider the distribution of possible outcomes, the greater an option’s riskiness becomes. Yet, studies that assessed people’s judgments of the riskiness of ﬁnancial gambles have shown that downside variability of outcomes aﬀects the perception of an option’s riskiness much more than upside variability, an asymmetry that is not captured by variance measures.
As a result, other axiomatic measures of perceived risk were developed that diﬀer in the assumptions they impose on judgments of riskiness. These models capture both similarities in people’s risk judgments (with a common functional form by which probability and outcome information about risky options are combined) and individual and group diﬀerences (with the help of model parameters that capture diﬀerences in the relative weight given to diﬀerent model components).
Weber and Bottom (1989, 1990) submitted the behavioral axioms on which these models are based to empirical tests and found support for the assumption that risk judgments are transitive (if option B is judged more risky than option A, and C more risky than B, then C will also be judged more risky than A) and monotonic (if option B is judged more risky than A, then any combination of obtaining B with probability p and X otherwise should also be more risky than the combination of obtaining A with probability p and X otherwise). Some violations of the expectation principle for risk judgments in the gain domain (Keller et al. 1986) were shown to be the result of nonnormative probability accounting, similar to that observed for preferences. People, for example, do not think that a two-stage lottery carries the same risk as a mathematically equivalent single-stage lottery, even if the ﬁnal outcomes of the two lotteries and their probabilities are identical. Weber and Bottom’s (1989) results supported the additive combination of gain and loss components hypothesized by the conjoint expected risk (CER) model (Luce and Weber 1986; see Risk: Theories of Decision and Choice) and ruled out, at least as descriptive models of perceived risk, other risk functions that assume that losses and gains impact risk judgments multiplicatively. The CER model has been described as the most viable model to describe single dimensional risk appraisal (Yates and Stone 1992) and is probably the most widely applied axiomatic model of risk, but other, similar models exist.
Bontempo et al. (1997) ﬁt the CER model to judgments of the riskiness of monetary lotteries made by business students and security analysts in Hong Kong, Taiwan, the Netherlands, and the US. Cross-national diﬀerences in risk judgments followed a Chinese–Western division, with respondents from the two culturally Chinese countries having model parameters that were similar to each other but diﬀerent from those of the two Western countries. The probability of a loss had a larger eﬀect on perceived risk for Western respondents, while the magnitude of losses had a larger eﬀect on the risk perceptions of Chinese respondents. Cross-cultural diﬀerences in risk perception were greater than diﬀerences due to occupation (students vs. security analysts), suggesting that cultural upbringing and environment seem to play a larger role in shaping the perception of ﬁnancial risks than professional training or expertise.
2.2 Psychometric Studies
The psychometric measurement approach treats risk perception as a multidimensional construct and uses multidimensional scaling, clustering, and factor analysis to identify its underlying psychological dimensions (Slovic et al. 1986). Research within this paradigm has found that the perceptions of the risks of hazardous technologies or activities by members of the lay public have often little to do with possible outcomes and their probabilities. Compared to technical experts, ordinary citizens overweight risk associated with infrequent, catastrophic, and involuntary events, and underweight the risk associated with frequent, familiar, and voluntary events. The psychological risk dimensions identiﬁed by the psychometric paradigm fall into two categories. The ﬁrst one, dread, is deﬁned by a perceived lack of control, feelings of dread, and perceived catastrophic potential. The second one, risk of the unknown, is deﬁned as the extent to which the hazard is judged to be unobservable, unknown, new, or delayed in producing harmful impacts. Cross-national comparisons show that risk perceptions in a wide range of countries are aﬀected by the dread and the risk of the unknown factor. Risk perceptions between countries diﬀer in where respondents place particular hazards (e.g., nuclear power) within this factor space, usually in ways consistent with national diﬀerences in exposures and socioeconomic development.
2.3 Sociocultural Studies
In Douglas and Wildavsky’s (1982) cultural theory, risk perception is viewed as a collective phenomenon by which members of diﬀerent cultures selectively attend to diﬀerent categories of danger. Each culture selects some risks for attention and chooses to ignore others. Cultural diﬀerences in risk perceptions are explained in terms of their contribution to maintaining a particular way of life. The theory identiﬁes ﬁve distinct cultures (labeled hierarchical, individualist, egalitarian, fatalist, and hermitic, respectively) that diﬀer in their patterns of interpersonal relationships and argues that members of these cultures therefore diﬀer in their perceptions of risk. Hierarchically arranged groups, for example, tend to perceive industrial and technological risks as opportunities, whereas more egalitarian groups tend to perceive them as threats to their social structure. The signiﬁcance of this approach to understanding risk perception is that it provides a way of accounting for the eﬀect of group- and culture-level variables on the behavior of individuals. It suggests that culture teaches individuals where their interests lie and what variables and events pose risks to those interests and ways of life.
Implicit in this cultural theory of risk perception is the hypothesis that cultural diﬀerences in trust in institutions drive diﬀerences in perceived risk. Slovic (1997) summarizes empirical evidence for this hypothesis, for example, the fact that minority status (e.g., due to race) is associated with reduced trust in social institutions. The relationship between trust and risk perception seems to be mediated by an emotional pathway, with reduced trust resulting in stronger negative aﬀective responses to potential hazards and increased perceptions of risk.
Weber and Hsee (1999) provide another culture level explanation of cross-national diﬀerences in risk perception, based on diﬀerences in collectivism– individualism. Comparison of the perception of ﬁnancial and other material risks by Chinese vs. American respondents supports their assumption (coined the cushion hypothesis) that social collectivism serves as mutual insurance against catastrophic losses, making the risks faced by members of the collective, in fact, smaller.
3. Relationships Between Measures Of Risk Perception And Applications
The axiomatic risk measures of Sect. 2.1 were developed to describe the perception of ﬁnancial risks, whereas the psychometric risk measures of Sect. 2.2 were developed to describe the perception of health and safety risks. Holtgrave and Weber (1993) investigated how well either type of measure (a simpliﬁed version of the CER model and the psychometric model) would predict risk judgments for both types of risk. Respondents, who were MBA students, provided holistic risk judgments for a range of ﬁnancial and health and safety risks. They also evaluated each risk on the variables used as predictors by the two types of models (probability of a loss or gain, and expected loss or gain for the CER model; dread, control, catastrophic potential, voluntariness, novelty, and equity for the psychometric model).
Regression results showed the CER model to be a better predictor of perceived risk than the psychometric model for both ﬁnancial risks and health/safety risks. The predictor variables of the CER model seem to come closer to the way people evaluate risk in both domains. The psychometric model may need a dimension reﬂecting the probability of harm to provide a better ﬁt, since this dimension is highly correlated with risk ratings. Another reason might be that people consider both the pros and cons of activities when judging their risks. The CER model assumes that the impact of positive outcomes can oﬀset the impact of negative outcomes. The psychometric model, on the other hand, focuses exclusively on the impact of the downside of activities.
The best predictor of risk perceptions for both ﬁnancial and health/safety risks, however, was a hybrid model that added the dread variable of the psychometric model to the probability and outcome-based variables of the CER model. This suggests that the perception of both ﬁnancial and health/safety risks has an emotional component that is not completely described by the ‘objective’ components of axiomatic models (see Loewenstein et al. 2000 for a summary of the role of aﬀect in risk perception and risk taking).
Palmer and Sainfort (1993) applied the CER model in the context of genetic counseling to model the judgments made by members of a clinical population of dwarfs about the riskiness of diﬀerent procreative alternatives available to them. Faulting the genetic counseling literature for equating the perceived riskiness of an adverse event (e.g., the birth of a child with a genetic disorder) with the perceived probability of the event’s occurrence, Palmer showed that the perceived risk of diﬀerent reproductive alternatives also reﬂects the severity of consequences. Therefore, measures of risk that combine both probability and outcome information (such as the CER model) are a better predictor of risk perception.
The CER model has also been used to test the prediction of Douglas and Wildavsky’s (1982) sociocultural theory that individuals with diﬀerent worldviews diﬀer in predictable ways in their perceptions of risk. Palmer (1996) elicited risk judgments for ﬁnancial and health/safety risks from respondents who came from either a hierarchical, individualist, or egalitarian subculture in Southern California. Hierarchists who are comfortable with determining acceptable levels of risk for technologies (Thompson et al. 1990), a process that explicitly considers and weighs gains and losses, provided risk judgments that reﬂected all predictor variables of the CER model (gains as well as losses, outcome levels as well as probabilities). Egalitarians, on the other hand, who are suspicious of technologies and view nature as fragile and in need of protection, suggesting that they should see risk in terms of possible harm, provided risk judgments that reﬂected only the loss predictor variables of the CER model. Individualists, who view risk as opportunity, given their tendency to see beneﬁts from most activities as long as they do not interfere with market mechanisms (Thompson et al. 1990), were the group that provided the lowest risk judgments for almost all of the risky investments and activities.
4. Conclusions And Future Directions
The empirical studies of risk perception reviewed in this research paper show that risk perceptions are shaped by three classes of variables: the negative and positive outcomes of choice options and their likelihood; aﬀective reactions such as dread or fear of the unknown; and social and cultural variables that inﬂuence the perception and interpretation of the consequences of risky choice options. These variables have mostly been studied in isolation. Future research should examine possible interactions. There is also need for further examination of the accuracy or appropriateness of people’s perception of risk.
The fact that ordinary citizens perceive the risk of many activities and technologies in ways that fundamentally diverge from the way they are perceived by scientists moves the choice of a measure of risk onto which to base policy decisions into the political arena. Fischhoﬀ et al. (1984) argue that such choice should not be the exclusive province of scientists, who have no special insight into what society should value.
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