Action research to explore perceptions of risk in project management

Uses research in a major UK company on the introduction of an electronic document management system to explore perceptions of, and attitudes to, risk. Phenomenological methods were used; with subsequent dialogue transcripts evaluated with Winmax dialogue software, using an adapted theoretical framework based upon an analysis of the literature. The paper identifies a number of factors, and builds a framework, that should support a greater understanding of risk assessment and project management by the academic community and practitioners.

Precautionary principles: a jurisdiction-free framework for decision-making under risk

Fundamental principles of precaution are legal maxims that ask for preventive actions, perhaps as contingent interim measures while relevant information about causality and harm remains unavailable, to minimize the societal impact of potentially severe or irreversible outcomes. Such principles do not explain how to make choices or how to identify what is protective when incomplete and inconsistent scientific evidence of causation characterizes the potential hazards. Rather, they entrust lower jurisdictions, such as agencies or authorities, to make current decisions while recognizing that future information can contradict the scientific basis that supported the initial decision. After reviewing and synthesizing national and international legal aspects of precautionary principles, this paper addresses the key question: How can society manage potentially severe, irreversible or serious environmental outcomes when variability, uncertainty, and limited causal knowledge characterize their decision-making? A decision-analytic solution is outlined that focuses on risky decisions and accounts for prior states of information and scientific beliefs that can be updated as subsequent information becomes available. As a practical and established approach to causal reasoning and decision-making under risk, inherent to precautionary decision-making, these (Bayesian) methods help decision-makers and stakeholders because they formally account for probabilistic outcomes, new information, and are consistent and replicable. Rational choice of an action from among various alternatives-defined as a choice that makes preferred consequences more likely-requires accounting for costs, benefits and the change in risks associated with each candidate action. Decisions under any form of the precautionary principle reviewed must account for the contingent nature of scientific information, creating a link to the decision-analytic principle of expected value of information (VOI), to show the relevance of new information, relative to the initial ( and smaller) set of data on which the decision was based. We exemplify this seemingly simple situation using risk management of BSE. As an integral aspect of causal analysis under risk, the methods developed in this paper permit the addition of non-linear, hormetic dose-response models to the current set of regulatory defaults such as the linear, non-threshold models. This increase in the number of defaults is an important improvement because most of the variants of the precautionary principle require cost-benefit balancing. Specifically, increasing the set of causal defaults accounts for beneficial effects at very low doses. We also show and conclude that quantitative risk assessment dominates qualitative risk assessment, supporting the extension of the set of default causal models.

Multidimensional analysis of perceived risk in commercial air travel

This study attempts to assess the role of perceived risk in air passenger behaviour. A survey of 889 respondents is used to investigate a multidimensional concept of perceived risk and to analyse the differences between socio-demographic characteristics regarding passengers' risk assessment. The results indicate that financial risk and temporal risk are the most important in the context of commercial air travel. All perceived risk dimensions differ according gender, age, cultural background, income, previous experience, and reason for travelling. (C) 2006 Elsevier Ltd. All rights reserved.

A new instrument for targeting falls prevention interventions was accurate and clinically applicable in a hospital setting

Background and Objective: To describe the diagnostic accuracy and practical application of the Peter James Centre Falls Risk Assessment Tool (PJC-FRAT), a multidisciplinary falls risk screening and intervention deployment instrument. Methods: In phase 1, the accuracy of the PJC-FRAT was prospectively compared to a gold standard (the STRATIFY) on a cohort of subacute hospital patients (n = 122). In phase 2, the PJC-FRAT was temporally reassessed using a subsequent cohort (n = 316), with results compared to those of phase 1. Primary outcomes were falls (events), fallers (patients who fell), and hospital completion rates of the PJC-FRAT. Results: In phase 1, PJC-FRAT accuracy of identifying falters showed sensitivity of 73% (bootstrap 95% confidence interval CI = 55, 90) and specificity of 75% (95% CI = 66, 83), compared with the STRATIFY (cutoff >= 2/5) sensitivity of 77% (95% CI = 59, 92) and specificity of 51% (95% CI = 41, 61). This difference was not significant. In phase 2, accuracy of nursing staff using the PJC-FRAT was lower. PJC-FRAT completion rates varied among disciplines over both phases: nurses and physiotherapists, >= 90%; occupational therapists, >= 82%; and medical officers, >= 57%. Conclusion: The PJC-FRAT was practical and relatively accurate as a predictor of falls and a deployment instrument for falls prevention interventions, although continued staff education may be necessary to maintain its accuracy. (c) 2006 Elsevier Inc. All rights reserved.

Quantification of geological uncertainty and risk using stochastic simulation and applications in the coal mining industry

Stochastic simulation is a recognised tool for quantifying the spatial distribution of geological uncertainty and risk in earth science and engineering. Metals mining is an area where simulation technologies are extensively used; however, applications in the coal mining industry have been limited. This is particularly due to the lack of a systematic demonstration illustrating the capabilities these techniques have in problem solving in coal mining. This paper presents two broad and technically distinct areas of applications in coal mining. The first deals with the use of simulation in the quantification of uncertainty in coal seam attributes and risk assessment to assist coal resource classification, and drillhole spacing optimisation to meet pre-specified risk levels at a required confidence. The second application presents the use of stochastic simulation in the quantification of fault risk, an area of particular interest to underground coal mining, and documents the performance of the approach. The examples presented demonstrate the advantages and positive contribution stochastic simulation approaches bring to the coal mining industry