Bicycle commuting and exposure to air pollution: A questionnaire-based investigation of perceptions, symptoms and risk management strategies

Background An increase in bicycle commuting participation may improve public health and traffic congestion in cities. Information on air pollution exposure (such as perception, symptoms and risk management) contributes to the responsible promotion of bicycle commuting participation. Methods To determine perceptions, symptoms and willingness for specific exposure risk management strategies of exposure to air pollution, a questionnaire-based cross-sectional investigation was conducted with adult bicycle commuters (n = 153; age = 41 ± 11 yr; 28% female). Results Frequency of acute respiratory signs and symptoms are positively-associated with in- and post-commute compared to pre-commute time periods (p < 0.05); greater positive-association is with respiratory disorder compared to healthy, and female compared to male, participants. The perception (although not signs or symptoms) of in-commute exposure to air pollution is positive-associated with the estimated level of in-commute proximity to motorised traffic. The majority of participants indicated a willingness (which varied with health status and gender) to adopt risk management strategies (with certain practical features) if shown to be appropriate and effective. Conclusions While acute signs and symptoms of air pollution exposure are indicated with bicycle commuting, and more so in susceptible individuals, there is willingness to manage exposure risk by adopting effective strategies with desirable features.

Spontaneous and episodic volunteers: The legislative, insurance and risk management framework

Baby Boomers are a generation of life long association joiners, but following generations prefer spontaneous and episodic volunteering. This trend is apparent not only during natural disasters, but in most other spheres of volunteering. Legal liability for such volunteers is a growing concern, which unresolved, may dampen civic participation. We critically examine the current treatment of these liabilities through legislation, insurance and risk management.

Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance.

Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

Risk management for mycotoxin contamination of Australian maize

Recent incidents of mycotoxin contamination (particularly aflatoxins and fumonisins) have demonstrated a need for an industry-wide management system to ensure Australian maize meets the requirements of all domestic users and export markets. Results of recent surveys are presented, demonstrating overall good conformity with nationally accepted industry marketing standards but with occasional samples exceeding these levels. This paper describes mycotoxin-related hazards inherent in the Australian maize production system and a methodology combining good agricultural practices and the hazard analysis critical control point framework to manage risk.

An analysis of risk management disclosures: Australian evidence

- Purpose Communication of risk management practices are a critical component of good corporate governance. Research to date has been of little benefit in informing regulators internationally. This paper seeks to contribute to the literature by investigating how listed Australian companies in a setting where disclosures are explicitly required by the ASX corporate governance framework, disclose risk management (RM) information in the corporate governance statements within annual reports. - Design/methodology/approach To address our study’s research questions and related hypotheses, we examine the top 300 ASX-listed companies by market capitalisation at 30 June 2010. For these firms, we identify, code and categorise RM disclosures made in the annual reports according to the disclosure categories specified in Australian Stock Exchange Corporate Governance Principles and Recommendations (ASX CGPR). The derived data is then examined using a comprehensive approach comprising thematic content analysis and regression analysis. - Findings The results indicate widespread divergence in disclosure practices and low conformance with the Principle 7 of the ASX CGPR. This result suggests that companies are not disclosing all ‘material business risks’ possibly due to ignorance at the board level, or due to the intentional withholding of sensitive information from financial statement users. The findings also show mixed results across the factors expected to influence disclosure behaviour. Notably, the presence of a risk committee (RC) (in particular, a standalone RC) and technology committee (TC) are found to be associated with improved levels of disclosure. we do not find evidence that company risk measures (as proxied by equity beta and the market-to-book ratio) are significantly associated with greater levels of RM disclosure. Also, contrary to common findings in the disclosure literature, factors such as board independence and expertise, audit committee independence, and the usage of a Big-4 auditor do not seem to impact the level of RM disclosure in the Australian context. - Research limitation/implications The study is limited by the sample and study period selection as the RM disclosures of only the largest (top 300) ASX firms are examined for the fiscal year 2010. Thus, the finding may not be generalisable to smaller firms, or earlier/later years. Also, the findings may have limited applicability in other jurisdictions with different regulatory environments. - Practical implications The study’s findings suggest that insufficient attention has been applied to RM disclosures by listed companies in Australia. These results suggest that the RM disclosures practices observed in the Australian setting may not be meeting the objectives of regulators and the needs of stakeholders. - Originality/value Despite the importance of risk management communication, it is unclear whether disclosures in annual financial reports achieve this communication. The Australian setting provides an ideal environment to examine the nature and extent of risk management communication as the Australian Securities Exchange (ASX) has recommended risk management disclosures follow Principle 7 of its principle-based governance rules since 2007.

The climate change risk management matrix for the grazing industry of northern Australia

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

Economic aspects of post-border weed risk management

Aim: Decision-making in weed management involves consideration of limited budgets, long time horizons, conflicting priorities, and as a result, trade-offs. Economics provides tools that allow these issues to be addressed and is thus integral to management of the risks posed by weeds. One of the critical issues in weed risk management during the early stages of an invasion concerns feasibility of eradication. We briefly review how economics may be used in weed risk management, concentrating on this management strategy. Location: Australia. Methods: A range of innovative studies that investigate aspects of weed risk management are reviewed. We show how these could be applied to newly invading weeds, focussing on methods for investigating eradication feasibility. In particular, eradication feasibility is analysed in terms of cost and duration of an eradication programme, using a simulation model based on field-derived parameter values for chromolaena, Chromolaena odorata. Results: The duration of an eradication programme can be reduced by investing in progressively higher amounts of search effort per hectare, but increasing search area will become relatively more expensive as search effort increases. When variation in survey and control success is taken into account, increasing search effort also reduces uncertainty around the required duration of the eradication programme. Main conclusions: Economics is integral to the management of the risks posed by weeds. Decision analysis, based on economic principles, is now commonly used to tackle key issues that confront weed managers. For eradication feasibility, duration and cost of a weed eradication programme are critical components; the dimensions of both factors can usefully be estimated through simulation. © 2013 John Wiley & Sons Ltd.

Human error risk management methodology for rail crack incidents

The paper presents an innovative approach to modelling the causal relationships of human errors in rail crack incidents (RCI) from a managerial perspective. A Bayesian belief network is developed to model RCI by considering the human errors of designers, manufactures, operators and maintainers (DMOM) and the causal relationships involved. A set of dependent variables whose combinations express the relevant functions performed by each DMOM participant is used to model the causal relationships. A total of 14 RCI on Hong Kong’s mass transit railway (MTR) from 2008 to 2011 are used to illustrate the application of the model. Bayesian inference is used to conduct an importance analysis to assess the impact of the participants’ errors. Sensitivity analysis is then employed to gauge the effect the increased probability of occurrence of human errors on RCI. Finally, strategies for human error identification and mitigation of RCI are proposed. The identification of ability of maintainer in the case study as the most important factor influencing the probability of RCI implies the priority need to strengthen the maintenance management of the MTR system and that improving the inspection ability of the maintainer is likely to be an effective strategy for RCI risk mitigation.

Corporate philanthropy, reputation risk management and shareholder value: A study of Australian corporate giving

This study examines the role of corporate philanthropy in the management of reputation risk and shareholder value of the top 100 ASX listed Australian firms for the three years 2011-2013. The results of this study demonstrate the business case for corporate philanthropy and hence encourage corporate philanthropy by showing increasing firms’ investment in corporate giving as a percentage of profit before tax, increases the likelihood of an increase in shareholder value. However, the proviso is that firms must also manage their reputation risk at the same time. There is a negative association between corporate giving and shareholder value (Tobin’s Q) which is mitigated by firms’ management of reputation. The economic significance of this result is that for every cent in the dollar the firm spends on corporate giving, Tobin’s Q will decrease by 0.413%. In contrast, if the firm increase their reputation by 1 point then Tobin’s Q will increase by 0.267%. Consequently, the interaction of corporate giving and reputation risk management is positively associated with shareholder value. These results are robust while controlling for potential endogeneity and reverse causality. This paper assists both academics and practitioners by demonstrating that the benefits of corporate philanthropy extend beyond a gesture to improve reputation or an attempt to increase financial performance, to a direct collaboration between all the factors where the benefits far outweigh the costs.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Risk management plan and pharmacovigilance system - biopharmaceuticals: biosimilars.

Editor literario del libro, Giancarlo Nota - All chapters are Open Access articles distributed under the Creative Commons Non Commercial-Share Alike-Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited.