Suchergebnisse

Intro; Preface; Contents; Editors and Contributors; Theoretical Aspects of Perceived Safety; 1 What Is "Safety" and Is There "Optimal Safety" in Engineering?; Abstract; 1.1 Introduction; 1.1.1 Current Developments; 1.1.2 Limitation of the Current Developments; 1.2 Terms; 1.2.1 The Term "Safety"; 1.2.2 Solution; References; 2 Categorization of Safety and Risk; Abstract; 2.1 Introduction; 2.2 Theory of Categorizations; 2.3 Types of Safety and Risks; 2.4 Conclusions; References; 3 Philosophical Perspectives on Safety and Risk; Abstract; 3.1 Introduction; 3.2 Risk: Some Basic Uses of the Term

Recent findings on construal level theory (CLT) suggest that abstract thinking leads to a lower estimated probability of an event occurring compared to concrete thinking. We applied this idea to the risk context and explored the influence of construal level (CL) on the overestimation of small and underestimation of large probabilities for risk estimates concerning a vague target person (Study 1 and Study 3) and personal risk estimates (Study 2). We were specifically interested in whether the often‐found overestimation of small probabilities could be reduced with abstract thinking, and the often‐found underestimation of large probabilities was reduced with concrete thinking. The results showed that CL influenced risk estimates. In particular, a concrete mindset led to higher risk estimates compared to an abstract mindset for several adverse events, including events with small and large probabilities. This suggests that CL manipulation can indeed be used for improving the accuracy of lay people's estimates of small and large probabilities. Moreover, the results suggest that professional risk managers' risk estimates of common events (thus with a relatively high probability) could be improved by adopting a concrete mindset. However, the abstract manipulation did not lead managers to estimate extremely unlikely events more accurately. Potential reasons for different CL manipulation effects on risk estimates' accuracy between lay people and risk managers are discussed.

AbstractSelf‐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.