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

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.     

How People Perceive and Will Cope with Risks from the Diffusion of Ubiquitous Information and Communication Technologies

Information and communication technologies (ICTs) are increasingly pervasive and continue to reshape our environment. This trend carries different risks. Therefore, the early sensitization of people to these risks, as well as improving their capacity for protective coping behavior, is essential. Based on the protection motivation theory (PMT), we examined with structural equation modeling the relationships between different components of threat and coping appraisal to explain protective and nonprotective responses. Calculations were performed with data from a representative survey on perception and use of ICT among German residents (N= 5,030). Our findings largely supported the proposed model: an increased perceived threat was positively related to the intentions to react protectively and nonprotectively. Perceived coping efficacy increased the protective and decreased the nonprotective responses. Negative affect enhanced the perceived threat and the nonprotective response, but inhibited protective intentions. The implications of these findings on how to sensitize people to the risks of these new technologies are outlined.     

Methodology for the Calculation of Annualized Incremental Risks in Systems of Dams

In the past few years, the field of dam safety has approached risk informed methodologies throughout the world and several methodologies and programs are appearing to aid in the systematization of the calculations. The most common way of implementing these calculations is through the use of event trees, computing event probabilities, and incremental consequences. This methodology is flexible enough for several situations, but its generalization to the case of systems of several dams is complex and its implementation in a completely general calculation methodology presents some problems. Retaining the event tree framework, a new methodology is proposed to calculate incremental risks. The main advantage of this proposed methodology is the ease with which it can be applied to systems of several dams: with a single risk model that describes the complete system and with a single calculation the incremental risks of the system can be obtained, being able to allocate the risk of each dam and of each failure mode. The article shows how both methodologies are equivalent and also applies them to a case study.     

A Bayesian Evidence Synthesis for Estimating Campylobacteriosis Prevalence

Stakeholders making decisions in public health and world trade need improved estimations of the burden‐of‐illness of foodborne infectious diseases. In this article, we propose a Bayesian meta‐analysis or more precisely a Bayesian evidence synthesis to assess the burden‐of‐illness of campylobacteriosis in France. Using this case study, we investigate campylobacteriosis prevalence, as well as the probabilities of different events that guide the disease pathway, by (i) employing a Bayesian approach on French and foreign human studies (from active surveillance systems, laboratory surveys, physician surveys, epidemiological surveys, and so on) through the chain of events that occur during an episode of illness and (ii) including expert knowledge about this chain of events. We split the target population using an exhaustive and exclusive partition based on health status and the level of disease investigation. We assume an approximate multinomial model over this population partition. Thereby, each observed data set related to the partition brings information on the parameters of the multinomial model, improving burden‐of‐illness parameter estimates that can be deduced from the parameters of the basic multinomial model. This multinomial model serves as a core model to perform a Bayesian evidence synthesis. Expert knowledge is introduced by way of pseudo‐data. The result is a global estimation of the burden‐of‐illness parameters with their accompanying uncertainty.     

Pool‐Point Distribution of Zero‐Inventory Products

We study zero‐inventory production‐distribution systems under pool‐point delivery. The zero‐inventory production and distribution paradigm is supported in a variety of industries in which a product cannot be inventoried because of its short shelf life. The advantages of pool‐point (or hub‐and‐spoke) distribution, explored extensively in the literature, include the efficient use of transportation resources and effective day‐to‐day management of operations. The setting of our analysis is as follows: A production facility (plant) with a finite production rate distributes its single product, which cannot be inventoried, to several pool points. Each pool point may require multiple truckloads to satisfy its customers' demand. A third‐party logistics provider then transports the product to individual customers surrounding each pool point. The production rate can be increased up to a certain limit by incurring additional cost. The delivery of the product is done by identical trucks, each having limited capacity and non‐negligible traveling time between the plant and the pool points. Our objective is to coordinate the production and transportation operations so that the total cost of production and distribution is minimized, while respecting the product lifetime and the delivery capacity constraints. This study attempts to develop intuition into zero‐inventory production‐distribution systems under pool‐point delivery by considering several variants of the above setting. These include multiple trucks, a modifiable production rate, and alternative objectives. Using a combination of theoretical analysis and computational experiments, we gain insights into optimizing the total cost of a production‐delivery plan by understanding the trade‐off between production and transportation.     

The Surgical Scheduling Problem: Current Research and Future Opportunities

This paper reviews the general problem of surgical scheduling. We organize the literature based on the time frame or planning horizon of the schedule into six categories: capacity planning, process reengineering/redesign, the surgical services portfolio, procedure duration estimation, schedule construction, and schedule execution, monitoring, and control. We survey past work and suggest topics for potential future research in each of those areas.     

An effective tool for the optimization of distribution systems

During the past few years an increasing number of firms have begun to analyze and re-organize their traditional, organically grown distribution systems. The reasons for this development have been rising costs on the one hand and changing marketing constellations on the other. Existing distribution systems very often do not reach the level of productivity that could be realized by means of advanced methods of Physical Distribution. The author suggests that the latest methodological developments in this field for analysis, planning and control are frequently under-estimated as to their applicability and efficiency. The availability of computers makes it possible to apply such methods very efficiently and at fairly low cost.     

Bargaining With Time: An Interview With Helen Pavlin

Helen Pavlin is an accredited mental health social worker and family therapist and accredited family dispute resolution practitioner in private practice in Darwin. She has been involved in social work and family therapy since the early 1970s in Australia and internationally. In 1996 she received the 50th Anniversary Commemorative Medal from the Australian Association of Social Workers. She is one of the assessors and associate editors for the Australian and New Zealand Journal of Family Therapy. In 2007 Helen received the Journal Award for her outstanding contribution to the family therapy field in Australia. She is an accomplished writer and a member of the Australian Society of Authors. Her poems and book reviews have been published frequently in ANZJFT.     

Extreme Copulas and the Comparison of Ordered Lists

We introduce two extreme methods to pairwisely compare ordered lists of the same length, viz. the comonotonic and the countermonotonic comparison method, and show that these methods are, respectively, related to the copula T _M (the minimum operator) and the Ł ukasiewicz copula T _L used to join marginal cumulative distribution functions into bivariate cumulative distribution functions. Given a collection of ordered lists of the same length, we generate by means of T _M and T _L two probabilistic relations Q ^M and Q ^L and identify their type of transitivity. Finally, it is shown that any probabilistic relation with rational elements on a 3-dimensional space of alternatives which possesses one of these types of transitivity, can be generated by three ordered lists and at least one of the two extreme comparison methods.