Risk Analysis

Determinants and Mapping of Collective Perceptions of Technological Risk: The Case of the Second Nuclear Power Plant in Taiwan

Journal Article

Nuclear power is a highly controversial and salient example of environmental risk. The siting or operating of a nuclear power plant often faces widespread public opposition. Although studies of public perceptions of nuclear power date back to 1970s, little research attempts to explain the spatial heterogeneity of risk attitude toward nuclear power among individuals or communities. This article intends to improve the knowledge about the major factors contributing to nuclear power plant risk perceptions by mapping the geographical patterns of local risk perception and examining the determinants in forming the nature and distribution of the perceived risk among potentially affected population. The analysis was conducted by a case study of the Second Nuclear Power Plant (SNPP) in Taiwan by using a novel methodology that incorporates a comprehensive risk perception (CRP) model into an ethnographic approach called risk perception mapping (RPM). First, we examined the determinants of local nuclear power risk perceptions through the CRP model and multivariate regression analysis. Second, the results were integrated with the RPM approach to map and explain the spatial pattern of risk perceptions. The findings demonstrate that the respondents regard the nuclear power plant as an extremely high‐risk facility, causing them to oppose the SNPP and reject the compensation payment to accept its continuing operation. Results also indicate that perceptions of nuclear power risk were mainly influenced by social trust, psychological and socioeconomic attributes, proximity, and the perceived effects of the SNPP on the quality of everyday life.

Related Topics

Related Publications

Related Content

Site Footer

Address:

This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.