The Inverse Relation Between Risks and Benefits: The Role of Affect and Expertise

Preferences for Prevention: People Assume Expensive Problems Have Expensive Solutions

People support inefficient spending on preventing disasters, and these preferences are translated into inefficient policies as elected officials try to appeal to their constituents. Here, we find preferences for prevention spending are biased by the "cost conflation" mechanism, where people assume expensive problems have expensive solutions. In this article, we present a formal model of collective action, and illustrate how cost conflation causes people to deviate from the equilibria. We test for these hypothesized deviations using an incentivized experiment. The experimental subjects engage in cost conflation-they believe the costs of disaster prevention are positively related to the costs of disaster damages, even when explicitly told otherwise. As a result, they fail to prevent smaller disasters and pay too much to prevent large disasters when cheap solutions exist. Furthermore, we provide evidence that overemphasizing disaster damages undermines successful disaster prevention because people view these disasters as too big to solve.

The inverse relation between risks and benefits: The impact of individual differences in information processing style

Existing research shows that evaluations of the risks and benefits of various hazards (i.e., technologies and activities) are inversely related. The affect heuristic explains the negative relation between risks and benefits, as based on the strength of positive or negative affect associated with a hazard. Research on the affect heuristic previously investigated under which conditions people judge risk and benefits independently, focusing on expertise as a factor that might exempt from inversely related judgements of risk and benefits. Measurements within Dual Process Theories have been found to be associated with rational, analytical decision making and accurate judgments. In this paper we investigated the extent to which rational information processing styles can predict the risk-benefit relation of technologies in a medical and food applications and whether the attitudes influence the strength or direction of the relationship. Using the Need for Cognition Scale (NFC), a psychometric-based risk scale and an explicit measure of attitude, in a representative sample of 3228 Swedes, we found that the high NFC group judged the risks and benefits of technologies to be inversely related. In contrast, the low NFC group judged the risks and benefits to be positively related. These results were confirmed across all studied technologies by applying moderation analysis. We discuss the results in light of recent research on cognitive processing and polarization over technologies’ risks.

Is Reliance on the Affect Heuristic associated with Age?

OBJECTIVES

With age, decision makers rely more on heuristic and affect-based processing. However, age differences have not been quantified with respect to the affect heuristic which derives judgments based on positive and negative feelings towards stimuli and concepts. The present study examined whether reliance on the affect heuristic is associated with age, whether these patterns vary by task type, and which covariates account for age effects.

METHOD

In a pre-registered study, an adult lifespan sample (N = 195, 21 - 90 years, Mage = 52.95, 50% female, 71% non-Hispanic White) completed a battery of cognitive, personality, and socioemotional covariates as well as three established affect heuristic tasks: (1) a risk-benefit task, (2) a dread-inference task, and (3) an affect-impact task. Reliance on affect was indexed through (1) a negative relationship between perceived food risks and benefits, (2) a positive relationship between feelings of dread and statistical inferences about mortality risks, and (3) a positive relationship between affective responses and impact judgments when evaluating catastrophes.

RESULTS

For all three tasks, usage of the affect heuristic was documented at the group and the individual level. Contrary to hypotheses, age was not associated with affect heuristic use for any of the tasks. Affect heuristic indices did not correlate across tasks and showed no consistent associations with the covariates.

DISCUSSION

Results suggest that the use of affect-based heuristics is context- or stimulus-dependent rather than a stable, age-associated trait. Further research is needed to validate the present results across additional domains, tasks, and stimulus types.

Consumer acceptance of novel food technologies

Novel food technologies are important for food security, safety and sustainability. Consumers, however, are often hesitant to accept them. In this narrative Review, we organize the research describing how heuristics and individual differences among consumers influence the acceptance of agri-food technologies. Associations evoked by a food technology, its perceived naturalness and trust in the industry using it influence consumer acceptance. Food neophobia, disgust sensitivity and cultural values are crucial personality factors for explaining individual differences. Using gene technology, nanotechnology, cultured meat and food irradiation as cases, we explore factors that may explain consumers' acceptance or lack of acceptance. Climate change, food supply shocks caused by crises such as pandemics and population growth are imminent threats to the food system. Therefore, disruptive food technologies will be needed to progress towards a more resilient food system. Taking into account the factors influencing consumers' perceptions of novel food technologies during the early stage of development and introduction will hopefully result in a higher acceptance of such technologies.

When Evolution Works Against the Future: Disgust's Contributions to the Acceptance of New Food Technologies

New food technologies have a high potential to transform the current resource-consuming food system to a more efficient and sustainable one, but public acceptance of new food technologies is rather low. Such an avoidance might be maintained by a deeply preserved risk avoidance system called disgust. In an online survey, participants (N = 313) received information about a variety of new food technology applications (i.e., genetically modified meat/fish, edible nanotechnology coating film, nanotechnology food box, artificial meat/milk, and a synthetic food additive). Every new food technology application was rated according to the respondent's willingness to eat (WTE) it (i.e., acceptance), risk, benefit, and disgust perceptions. Furthermore, food disgust sensitivity was measured using the Food Disgust Scale. Overall, the WTE both gene-technology applications and meat coated with an edible nanotechnology film were low and disgust responses toward all three applications were high. In full mediation models, food disgust sensitivity predicted the disgust response toward each new food technology application, which in turn influenced WTE them. Effects of disgust responses on the WTE a synthetic food additive were highest for and lowest for the edible nanotechnology coating film compared to the other technologies. Results indicate that direct disgust responses influence acceptance and risk and benefit perceptions of new food technologies. Beyond the discussion of this study, implications for future research and strategies to increase acceptance of new food technologies are discussed.

Feelings About Fracking: Using the Affect Heuristic to Understand Opposition to Coal Seam Gas Production

The rapid expansion of coal seam gas (CSG) extraction across Australia has polarized public opinion about the risks, benefits, and the future of the industry. We conducted a randomized controlled experiment to assess the impact of CSG messaging on opposition to the CSG industry. Residents of a major Australian city (N = 549), aged between 21 and 87 years, were randomly assigned to view one of three brief video messages (pro-CSG, anti-CSG, or a neutral control) sourced from the Internet. They then completed measures assessing CSG affective associations, perceived risks and benefits of CSG, and degree of opposition to the CSG industry. A subsample of 317 participants also completed the measures of affect, risks, benefits, and opposition two weeks following the initial message presentation. Message type significantly predicted message effects in a pattern consistent with the affect heuristic model, although overall, the message effects were modest in magnitude. Respondents who viewed the anti-CSG video (relative to the control) reported more negative affective responses to CSG, perceived higher risks, fewer benefits, and greater opposition to the CSG industry. Those who viewed the pro-CSG video (relative to the control) reported stronger positive affective responses to CSG, perceived more CSG benefits and fewer risks, and expressed less opposition to the industry. The effects persisted over a two-week interval for the anti-CSG message, but not for the pro-CSG message. Our findings suggest that people's risk perceptions and views about the acceptability of CSG are malleable by messaging that targets affective pathways.

The Influence of Feelings While Driving Regular Cars on the Perception and Acceptance of Self-Driving Cars

Self-driving vehicles will affect the future of transportation, but factors that underlie perception and acceptance of self-driving cars are yet unclear. Research on feelings as information and the affect heuristic has suggested that feelings are an important source of information, especially in situations of complexity and uncertainty. In this study (N = 1,484), we investigated how feelings related to traditional driving affect risk perception, benefit perception, and trust related to self-driving cars as well as people's acceptance of the technology. Due to limited experiences with and knowledge of self-driving cars, we expected that feelings related to a similar experience, namely, driving regular cars, would influence judgments of self-driving cars. Our results support this assumption. While positive feelings of enjoyment predicted higher benefit perception and trust, negative affect predicted higher risk and higher benefit perception of self-driving cars. Feelings of control were inversely related to risk and benefit perception, which is in line with research on the affect heuristic. Furthermore, negative affect was an important source of information for judgments of use and acceptance. Interest in using a self-driving car was also predicted by lower risk perception, higher benefit perception, and higher levels of trust in the technology. Although people's individual experiences with advanced vehicle technologies and knowledge were associated with perceptions and acceptance, many simply have never been exposed to the technology and know little about it. In the absence of this experience or knowledge, all that is left is the knowledge, experience, and feelings they have related to regular driving.

Reviewing cognitive distortions in managerial decision making

Purpose

Why and how do cognitive distortions in managerial decision making occur? All organizations are imperfect systems (Katz and Kahn, 1966), with wrong decisions often just round the corner. As a consequence, addressing these important questions continues to be particularly lively in the management development area, especially in terms of its intended contribution to the de-biasing activity. Thus, the purpose of this paper is to provide the current scientific dialogue on the topic with updated lenses, which can also be innovative from some aspects.

Design/methodology/approach

The review framework is based on the recent, impactful article on biases in managerial decision making by Kahneman et al. (2011), and on Bazerman and Moore’s (2013) perspective on emanating heuristics, considered as the causes of biases. Accordingly, the authors derive four intertwined thematic clusters of heuristics, through which the authors systematically group and critically analyze the management literature mostly published on the topic since 2011.

Findings

From the analyzed clusters the authors propose an integrative framework of emanating heuristics, which focuses on the co-evolving relationships and potentially self-reinforcing processes in and between them.

Originality/value

The value of the contribution is threefold: from a methodological perspective, to the authors’ knowledge, the studies adopted as the basis of the analysis have not yet been simultaneously used as a comprehensive ground for updated reviews on this topic; from a conceptual perspective, the emerging integrative co-evolutionary framework can help explain the dangerous connections among cognitive traps and emanating heuristics; and from a practical perspective, the resulting framework can also be helpful for future de-biasing attempts in the business arena.

Engaging with residents' perceived risks and benefits about technologies as a way of resolving remediation dilemmas

In recent decades the diversity of remediation technologies has increased significantly, with the breadth of technologies ranging from dig and dump to emergent technologies like phytoremediation and nanoremediation. The benefits of these technologies to the environment and human health are believed to be substantial. However, they also potentially constitute risks. Whilst there is a growing body of knowledge about the risks and benefits of these technologies from the perspective of experts, little is known about how residents perceive the risks and benefits of the application of these technologies to address contaminants in their local environment. This absence of knowledge poses a challenge to remediation practitioners and policy makers who are increasingly seeking to engage these affected local residents in choosing technology applications. Building on broader research into the perceived benefits and risks of technologies, and data from a telephone survey of 2009 residents living near 13 contaminated sites in Australia, regression analysis of closed-ended survey questions and coding of open-ended questions are combined to identify the main predictors of resident's perceived levels of risk and benefit to resident's health and to their local environment from remediation technologies. This research identifies a range of factors associated with the residents' physical context, their engagement with institutions during remediation processes, and the technologies which are associated with residents' level of perceived risk and benefit for human health and the local environment. The analysis found that bioremediation technologies were perceived as less risky and more beneficial than chemical, thermal and physical technologies. The paper also supports broader technology research that reports an inverse correlation between levels of perceived risks and benefits. In addition, the paper reveals the types of risks and benefits to human health and the local environment that residents most commonly associate with remediation technologies.

An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks.