The use of risk registers by project managers

The construction industry is widely recognised as being inherent with risk and uncertainty. This necessitates the need for effective project risk management to achieve the project objectives of time, cost and quality. A popular tool employed in projects to aid in the management of risk is a risk register. This tool documents the project risks and is often employed by the Project Manager (PM) to manage the associated risks on a project. This research aims to ascertain how widely risk registers are used by Project Managers as part of their risk management practices. To achieve this aim entailed interviewing ten PMs, to discuss their use of the risk register as a risk management tool. The results from these interviews indicated the prevalent use of this document and recognised its effectiveness in the management of project risks. The findings identified the front end and feasibility phases of a project as crucial stages for using risk registers, noting it as a vital ingredient in the risk response planning of the decision making process. Moreover, the composition of the risk register was also understood, with an insight into how PMs produce and develop this tool also ascertained. In conclusion, this research signifies the extensive use of the risk register by PMs. A majority of PMs were of the view that risk registers constitute an essential component of their project risk management practices. This suggests a need for further research on the extent to which risk registers actually help PMs to control the risks in a construction project, particularly residual risks, and how this can be improved to minimize deviations from expected outcomes.

Revenue-neutral tax policy under price uncertainty

The firm's response to revenue-neutral taxation is investigated under price uncertainty. Revenue-neutral policies adjust simultaneously the marginal tax rate and the level of exemptions while keeping expected tax receipts constant. Nonincreasing absolute risk aversion is sufficient to sign the firm's response: a reduction in the marginal rate causes the firm to contract output. Implications are established for the equilibrium level of treasury receipts.

Revenue-neutral tax policies under price uncertainty: reply

In their comment on my 1990 article, Yeh, Suwanakul, and Mai extend my analysis-which focused attention exclusively on firm output-to allow for simultaneous endogeneity of price, aggregate output, and numbers of firms. They show that, with downward- sloping demand, industry output adjusts positively to revenue-neutral changes in the marginal rate of taxation. This result is significant for two reasons. First, we are more often interested in predictions about aggregate phenomena than we are in predictions about individual firms. Indeed, firm-level predictions are frequently irrefutable since firm data are often unavailable. Second, the authors derive their result under a set of conditions that appear to be more general than those invoked in my 1990 article. In particular, they circumvent the need to invoke specific assumptions about the nature of firms' aversions toward risk. I consider this a useful extension and I appreciate the careful scrutiny of my paper.

Developing consensus on hospital prescribing indicators of potential harms amenable to decision support

Aim: To develop a list of prescribing indicators specific for the hospital setting that would facilitate the prospective collection of high severity and/or high frequency prescribing errors, which are also amenable to electronic clinical decision support (CDS). Method: A three-stage consensus technique (electronic Delphi) was carried out with 20 expert pharmacists and physicians across England. Participants were asked to score prescribing errors using a 5-point Likert scale for their likelihood of occurrence and the severity of the most likely outcome. These were combined to produce risk scores, from which median scores were calculated for each indicator across the participants in the study. The degree of consensus between the participants was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or more was achieved. Results: A total of 80 prescribing errors were identified by consensus as being high or extreme risk. The most common drug classes named within the indicators were antibiotics (n=13), antidepressants (n=8), nonsteroidal anti-inflammatory drugs (n=6), and opioid analgesics (n=6).The most frequent error type identified as high or extreme risk were those classified as clinical contraindications (n=29/80). Conclusion: 80 high risk prescribing errors in the hospital setting have been identified by an expert panel. These indicators can serve as the basis for a standardised, validated tool for the collection of data in both paperbased and electronic prescribing processes, as well as to assess the impact of electronic decision support implementation or development.

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

Farmers’ attitudes to disease risk management in England: a comparative analysis of sheep and pig farmers

The UK Department for Environment, Food and Rural Affairs (Defra) identified practices to reduce the risk of animal disease outbreaks. We report on the response of sheep and pig farmers in England to promotion of these practices. A conceptual framework was established from research on factors influencing adoption of animal health practices, linking knowledge, attitudes, social influences and perceived constraints to the implementation of specific practices. Qualitative data were collected from nine sheep and six pig enterprises in 2011. Thematic analysis explored attitudes and responses to the proposed practices, and factors influencing the likelihood of implementation. Most feel they are doing all they can reasonably do to minimise disease risk and that practices not being implemented are either not relevant or ineffective. There is little awareness and concern about risk from unseen threats. Pig farmers place more emphasis than sheep farmers on controlling wildlife, staff and visitor management and staff training. The main factors that influence livestock farmers’ decision on whether or not to implement a specific disease risk measure are: attitudes to, and perceptions of, disease risk; attitudes towards the specific measure and its efficacy; characteristics of the enterprise which they perceive as making a measure impractical; previous experience of a disease or of the measure; and the credibility of information and advice. Great importance is placed on access to authoritative information with most seeing vets as the prime source to interpret generic advice from national bodies in the local context. Uptake of disease risk measures could be increased by: improved risk communication through the farming press and vets to encourage farmers to recognise hidden threats; dissemination of credible early warning information to sharpen farmers’ assessment of risk; and targeted information through training events, farming press, vets and other advisers, and farmer groups, tailored to the different categories of livestock farmer.

The European Flood Alert System and the communication, perception, and use of ensemble predictions for operational flood risk management

Although ensemble prediction systems (EPS) are increasingly promoted as the scientific state-of-the-art for operational flood forecasting, the communication, perception, and use of the resulting alerts have received much less attention. Using a variety of qualitative research methods, including direct user feedback at training workshops, participant observation during site visits to 25 forecasting centres across Europe, and in-depth interviews with 69 forecasters, civil protection officials, and policy makers involved in operational flood risk management in 17 European countries, this article discusses the perception, communication, and use of European Flood Alert System (EFAS) alerts in operational flood management. In particular, this article describes how the design of EFAS alerts has evolved in response to user feedback and desires for a hydrographic-like way of visualizing EFAS outputs. It also documents a variety of forecaster perceptions about the value and skill of EFAS forecasts and the best way of using them to inform operational decision making. EFAS flood alerts were generally welcomed by flood forecasters as a sort of ‘pre-alert’ to spur greater internal vigilance. In most cases, however, they did not lead, by themselves, to further preparatory action or to earlier warnings to the public or emergency services. Their hesitancy to act in response to medium-term, probabilistic alerts highlights some wider institutional obstacles to the hopes in the research community that EPS will be readily embraced by operational forecasters and lead to immediate improvements in flood incident management. The EFAS experience offers lessons for other hydrological services seeking to implement EPS operationally for flood forecasting and warning. Copyright © 2012 John Wiley & Sons, Ltd.

Assessing continental-scale risks for generalist and specialist pollinating bee species under climate change

Increased risks of extinction to populations of animals and plants under changing climate have now been demonstrated for many taxa. This study assesses the extinction risks to species within an important genus of pollinating bees (Colletes: Apidae) by estimating the expected changes in the area and isolation of suitable habitat under predicted climatic condition for 2050. Suitable habitat was defined on the basis of the presence of known forage plants as well as climatic suitability. To investigate whether ecological specialisation was linked to extinction risk we compared three species which were generalist pollen foragers on several plant families with three species which specialised on pollen from a single plant species. Both specialist and generalist species showed an increased risk of extinction with shifting climate, and this was particularly high for the most specialised species (Colletes anchusae and C. wolfi). The forage generalist C. impunctatus, which is associated with Boreo-Alpine environments, is potentially threatened through significant reduction in available climatic niche space. Including the distribution of the principal or sole pollen forage plant, when modelling the distribution of monolectic or narrowly oligolectic species, did not improve the predictive accuracy of our models as the plant species were considerably more widespread than the specialised bees associated with them.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.

Loss potentials associated with European windstorms under future climate conditions

Possible changes in the frequency and intensity of windstorms under future climate conditions during the 21st century are investigated based on an ECHAM5 GCM multi-scenario ensemble. The intensity of a storm is quantified by the associated estimated loss derived with using an empirical model. The geographical focus is ‘Core Europe’, which comprises countries of Western Europe. Possible changes of losses are analysed by comparing ECHAM5 GCM data for recent (20C, 1960 to 2000) and future climate conditions (B1, A1B, A2; 2060 to 2100), each with 3 ensemble members. Changes are quantified using both rank statistics and return periods (RP) estimated by fitting an extreme value distribution using the peak over threshold method to potential storm losses. The estimated losses for ECHAM5 20C and reanalysis events show similar statistical features in terms of return periods. Under future climate conditions, all climate scenarios show an increase in both frequency and magnitude of potential losses caused by windstorms for Core Europe. Future losses that are double the highest ECHAM5 20C loss are identified for some countries. While positive changes of ranking are significant for many countries and multiple scenarios, significantly shorter RPs are mostly found under the A2 scenario for return levels correspondent to 20 yr losses or less. The emergence time of the statistically significant changes in loss varies from 2027 to 2100. These results imply an increased risk of occurrence of windstorm-associated losses, which can be largely attributed to changes in the meteorological severity of the events. Additionally, factors such as changes in the cyclone paths and in the location of the wind signatures relative to highly populated areas are also important to explain the changes in estimated losses.

The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios

This paper presents a preliminary assessment of the relative effects of rate of climate change (four Representative Concentration Pathways - RCPs), assumed future population (five Shared Socio-economic Pathways - SSPs), and pattern of climate change (19 CMIP5 climate models) on regional and global exposure to water resources stress and river flooding. Uncertainty in projected future impacts of climate change on exposure to water stress and river flooding is dominated by uncertainty in the projected spatial and seasonal pattern of change in climate. There is little clear difference in impact between RCP2.6, RCP4.5 and RCP6.0 in 2050, and between RCP4.5 and RCP6.0 in 2080. Impacts under RCP8.5 are greater than under the other RCPs in 2050 and 2080. For a given RCP, there is a difference in the absolute numbers of people exposed to increased water resources stress or increased river flood frequency between the five SSPs. With the ‘middle-of-the-road’ SSP2, climate change by 2050 would increase exposure to water resources stress for between approximately 920 and 3400 million people under the highest RCP, and increase exposure to river flood risk for between 100 and 580 million people. Under RCP2.6, exposure to increased water scarcity would be reduced in 2050 by 22-24%, compared to impacts under the RCP8.5, and exposure to increased flood frequency would be reduced by around 16%. The implications of climate change for actual future losses and adaptation depend not only on the numbers of people exposed to changes in risk, but also on the qualitative characteristics of future worlds as described in the different SSPs. The difference in ‘actual’ impact between SSPs will therefore be greater than the differences in numbers of people exposed to impact.

Gender differences in ultimatum games: despite rather than due to risk attitudes

We analyze experimental data obtained from an ultimatum game framed as a situation of employee-employer negotiation over salaries. Parallel to this, we elicit subjects' risk attitudes. In the existing literature, it has often been conjectured that gender differences in strategic environments are partly due to differences in risky decision making. Our evidence suggests that both gender and risk-related effects co-exist in ultimatum bargaining. However, differences in risk attitudes cannot explain gender effects in ultimatum bargaining.

Flood inundation dynamics and socioeconomic vulnerability under environmental change

Floods are a major threat to human existence and historically have both caused the collapse of civilizations and forced the emergence of new cultures. The physical processes of flooding are complex. Increased population, climate variability, change in catchment and channel management, modified landuse and land cover, and natural change of floodplains and river channels all lead to changes in flood dynamics, and as a direct or indirect consequence, social welfare of humans. Section 5.16.1 explores the risks and benefits brought about by floods and reviews the responses of floods and floodplains to climate and landuse change. Section 5.08.2 reviews the existing modeling tools, and the top–down and bottom–up modeling frameworks that are used to assess impacts on future floods. Section 5.08.3 discusses changing flood risk and socioeconomic vulnerability based on current trends in emerging or developing countries and presents an alternative paradigm as a pathway to resilience. Section 5.08.4 concludes the chapter by stating a portfolio of integrated concepts, measures, and avant-garde thinking that would be required to sustainably manage future flood risk.

Serial clustering of extratropical cyclones over the North Atlantic and Europe under recent and future climate conditions

Under particular large-scale atmospheric conditions, several windstorms may affect Europe within a short time period. The occurrence of such cyclone families leads to large socioeconomic impacts and cumulative losses. The serial clustering of windstorms is analyzed for the North Atlantic/western Europe. Clustering is quantified as the dispersion (ratio variance/mean) of cyclone passages over a certain area. Dispersion statistics are derived for three reanalysis data sets and a 20-run European Centre Hamburg Version 5 /Max Planck Institute Version–Ocean Model Version 1 global climate model (ECHAM5/MPI-OM1 GCM) ensemble. The dependence of the seriality on cyclone intensity is analyzed. Confirming previous studies, serial clustering is identified in reanalysis data sets primarily on both flanks and downstream regions of the North Atlantic storm track. This pattern is a robust feature in the reanalysis data sets. For the whole area, extreme cyclones cluster more than nonextreme cyclones. The ECHAM5/MPI-OM1 GCM is generally able to reproduce the spatial patterns of clustering under recent climate conditions, but some biases are identified. Under future climate conditions (A1B scenario), the GCM ensemble indicates that serial clustering may decrease over the North Atlantic storm track area and parts of western Europe. This decrease is associated with an extension of the polar jet toward Europe, which implies a tendency to a more regular occurrence of cyclones over parts of the North Atlantic Basin poleward of 50°N and western Europe. An increase of clustering of cyclones is projected south of Newfoundland. The detected shifts imply a change in the risk of occurrence of cumulative events over Europe under future climate conditions.

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.