Managing risk in process-aware information systems

This research contributes a fully-operational approach for managing business process risk in near real-time. The approach consists of a language for defining risks on top of process models, a technique to detect such risks as they eventuate during the execution of business processes, a recommender system for making risk-informed decisions, and a technique to automatically mitigate the detected risks when they are no longer tolerable. Through the incorporation of risk management elements in all stages of the lifecycle of business processes, this work contributes to the effective integration of the fields of Business Process Management and Risk Management.

Banking sector contingent liabilities and sovereign risk

The global financial crisis has underscored the need to pay attention to contingent government liabilities that could arise from bank failures for sovereign risk management. This paper proposes a simple method to construct a contingent liability index (CLI) for a banking sector that takes into account the size and concentration of the banking system, market expectations of bank defaults, and perceptions of government support to each bank. This method allows us to track potential government liabilities related to bank failures for 32 advanced and emerging economies on a monthly basis from 2006 to 2013. Furthermore, we find that the CLI is a significant determinant of sovereign CDS spreads. Our results suggest that a 1 percentage point increase in the CLI is associated with an increase in sovereign CDS spreads by 24 basis points for advanced economies and 75 basis points for emerging markets on average.

The value of tail risk hedging in defined contribution plans: What does history tell us

Hedging against tail events in equity markets has been forcefully advocated in the aftermath of recent global financial crisis. Whether this is beneficial to long horizon investors like employees enrolled in defined contribution (DC) plans, however, has been subject to criticism. We conduct historical simulation since 1928 to examine the effectiveness of active and passive tail risk hedging using out of money put options for hypothetical equity portfolios of DC plan participants with 20 years to retirement. Our findings show that the cost of tail hedging exceeds the benefits for a majority of the plan participants during the sample period. However, for a significant number of simulations, hedging result in superior outcomes relative to an unhedged position. Active tail hedging is more effective when employees confront several panic-driven periods characterized by short and sharp market swings in the equity markets over the investment horizon. Passive hedging, on the other hand, proves beneficial when they encounter an extremely rare event like the Great Depression as equity markets go into deep and prolonged decline.

Government grants - an abrogation or management of risks?

New public management (NPFM), with its hands-on, private sector-style performance measurement, output control, parsimonious use of resources, disaggreation of public sector units and greater competition in the public sector, has significantly affected charitable and nonprofit organisations delivering community services (Hood, 1991; Dunleavy, 1994; George & Wilding, 2002). The literature indicates that nonprofit organisations under NPM believe they are doing more for less: while administration is increasing, core costs are not being met; their dependence on government funding comes at the expense of other funding strategies; and there are concerns about proportionality and power asymmetries in the relationship (Kerr & Savelsberg, 2001; Powell & Dalton, 2011; Smith, 2002, p. 175; Morris, 1999, 2000a). Government agencies are under increased pressure to do more with less, demonstrate value for money, measure social outcomes, not merely outputs and minimise political risk (Grant, 2008; McGreogor-Lowndes, 2008). Government-community service organisation relationships are often viewed as 'uneasy alliances' characterised by the pressures that come with the parties' differing roles and expectations and the pressures that come with the parties' differing roles and expectations and the pressurs of funding and security (Productivity Commission, 2010, p. 308; McGregor-Lowndes, 2008, p. 45; Morris, 200a). Significant community services are now delivered to citizens through such relationships, often to the most disadvantaged in the community, and it is important for this to be achieved with equity, efficiently and effectively. On one level, the welfare state was seen as a 'risk management system' for the poor, with the state mitigating the risks of sickness, job loss and old age (Giddens, 1999) with the subsequent neoliberalist outlook shifting this risk back to households (Hacker, 2006). At the core of this risk shift are written contracts. Vincent-Jones (1999,2006) has mapped how NPM is characterised by the use of written contracts for all manner of relations; e.g., relgulation of dealings between government agencies, between individual citizens and the state, and the creation of quais-markets of service providers and infrastructure partners. We take this lens of contracts to examine where risk falls in relation to the outsourcing of community services. First we examine the concept of risk. We consider how risk might be managed and apportioned between governments and community serivce organisations (CSOs) in grant agreements, which are quasiy-market transactions at best. This is informed by insights from the law and economics literature. Then, standard grant agreements covering several years in two jurisdictions - Australia and the United Kingdom - are analysed, to establish the risk allocation between government and CSOs. This is placed in the context of the reform agenda in both jurisdictions. In Australia this context is th enonprofit reforms built around the creation of a national charities regulator, and red tape reduction. In the United Kingdom, the backdrop is the THird Way agenda with its compacts, succeed by Big Society in a climate of austerity. These 'case studies' inform a discussion about who is best placed to bear and manage the risks of community service provision on behalf of government. We conclude by identifying the lessons to be learned from our analysis and possible pathways for further scholarship.

Institutional investors, risk/performance and corporate governance

Modern portfolio theory suggests that investors minimize risk for a given level of expected return by carefully choosing the proportions of various assets. This study sets out to determine the role of the institutional investor in monitoring risk and firm performance. Using a sample of Australian firms from 2006 to 2008, our empirical study shows a positive association between firm-specific risk, risk-management policy, and performance for firms with increasing institutional shareholdings. The study also finds that the significance of this association depends on the institutional investor's ability to influence management, which in turn depends on the size of ownership and whether the investee firm does not have potential business dealings with the investor. We also find that when firms are financially distressed, institutional investors engage in promoting short-term performance or exit rather than support long-term value creation. The results are robust while controlling the potential for endogeneity and using sensitivity tests to control for variants of performance and risk. These findings add to the growing body of literature examining institutional ownership and the importance of understanding the role of risk-management in the risk and return relation.

‘Only a pawn in their game’ : crime, risk and politics in the case of Robert Fardon

In 2003 Robert Fardon was the first prisoner to be detained under the Dangerous Prisoners (Sexual Offenders) Act 2003 (Qld), the first of the new generation preventive detention laws enacted in Australia and directed at keeping sex offenders in prison or under supervision beyond the expiry of their sentences where a court decides, on the basis of psychiatric assessments, that unconditional release would create an unacceptable risk to the community. A careful examination of Fardon’s case shows the extent to which the administration of the regime was from the outset governed by politics and political calculation rather than the logic of risk management and community protection. In 2003 Robert Fardon was the first person detained under the Dangerous Prisoners (Sexual Offenders) Act 2003 (Qld) (hereafter DPSOA), a newly enacted Queensland law aimed at the preventive detention of sex offenders. It was the first of a new generation of such laws introduced in Australia, now also in force in NSW, Western Australia and Victoria. The laws have been widely criticized by lawyers, academics and others (Keyzer and McSherry 2009; Edgely 2007). In this article I want to focus on the details of how the Queensland law was administered in Fardon’s case, he being perhaps the most well-known prisoner detained under such laws and certainly the longest held. It will show, I hope, that seemingly abstract rule of law principles invoked by other critics are not simply abstract: they afford a crucial practical safeguard against the corruption of criminal justice in which the ends both of community protection and of justice give way to opportunistic exploitation of ‘the mythic resonance of crime and punishment for electoral purposes’ (Scheingold 1998: 888).

The challenge of developing a fleet driving risk assessment tool: What can be learned from the process?

One of the riskiest activities in the course of a person's work is driving. By developing and testing a new work driving risk assessment measurement tool for use by organisations this research will contribute to the safety of those who drive for work purposes. The research results highlighted limitations associated with current self-report measures and provided evidence that the work driving environment is extremely complex and involves constant interactions between humans, vehicles, the road environment, and the organisational context.

Critical risk factors affecting the implementation of PPP waste-to-energy projects in China

Since 2003, Mainland China has been promoting the public–private partnership (PPP) procurement model in the waste-to-energy incineration sector to reduce the waste burying rate and improve environmental quality. Five critical risk factors (CRFs) that affect the construction and operation of waste-to-energy incineration projects have been identified from real-life risk events of 14 PPP waste-to-energy incineration plants through content analysis. These risk factors are insufficient waste supply, disposal of non-licensed waste, environmental risk, payment risk, and lack of supporting infrastructure. A recently completed PPP waste-to-energy incineration plant, the Shanghai Tianma project, was investigated to learn from the effective management of CRFs. First-hand data about the Shanghai Tianma project was collected, with a focus on project negotiation and concession agreement. Lessons learned about risk management were acquired. This paper presents a detailed study of the contractual structure, risk sharing scheme, risk response measures to CRFs, and project transfer of a PPP project. The study results will provide governments with management implications to prepare equitable concession agreements and benefit private investors by effectively mitigating and managing risks in future PPP waste-to-energy incineration projects.

Mitigating undesirable impacts in the marine environment: A review of market-based management measures

Internationally, marine biodiversity conservation objectives are having an increasing influence on the management of commercial fisheries. While this is largely being implemented through Marine Protected Areas (MPAs) other management measures, such as market based instruments (MBIs), have proved to be effective at managing target species catch in fisheries and reducing environmental impacts in industries such as mining and tourism. Market-based management measures aim to mitigate the impacts of activities by better aligning the incentives their participants face with the objectives of management, changing their behavior as a consequence. In this paper, we review the potential of MBIs as management tools to mitigate undesirable environmental impacts associated with commercial fishing. Where they exist, examples of previous applications are described and the factors that influence their applicability and effectiveness are discussed. Several fishing methods and impacts are considered and suggest that whilst no single approach is most appropriate in all circumstances either replacing or complementing existing management arrangements with MBIs has the potential to improve environmental performance. This has a number of implications. From the environmental perspective they should enable levels of undesirable impacts such as damage to sensitive habitat or the bycatch of protected species of turtles, marine mammals, and seabirds to be reduced. The increased flexibility MBIs allow industry when developing solutions also has the potential to reduce costs to both the industry and managers, improving the cost-effectiveness of regulation as a result. Further, in the increasingly relevant case of MPAs the need for publicly funded compensation, often paid to industry when vessels are excluded from grounds, may also be significantly reduced if improved environmental performance makes it possible for some industry members to continue operating.

Evaluating the risk of mixtures in the indoor air of primary school classrooms

In school environments, children are constantly exposed to mixtures of airborne substances, derived from a variety of sources, both in the classroom and in the school surroundings. It is important to evaluate the hazardous properties of these mixtures, in order to conduct risk assessments of their impact on chil¬dren’s health. Within this context, through the application of a Maximum Cumulative Ratio approach, this study aimed to explore whether health risks due to indoor air mixtures are driven by a single substance or are due to cumulative exposure to various substances. This methodology requires knowledge of the concentration of substances in the air mixture, together with a health related weighting factor (i.e. reference concentration or lowest concentration of interest), which is necessary to calculate the Hazard Index. Maximum cumulative ratio and Hazard Index values were then used to categorise the mixtures into four groups, based on their hazard potential and therefore, appropriate risk management strategies. Air samples were collected from classrooms in 25 primary schools in Brisbane, Australia. Analysis was conducted based on the measured concentration of these substances in about 300 air samples. The results showed that in 92% of the schools, indoor air mixtures belonged to the ‘low concern’ group and therefore, they did not require any further assessment. In the remaining schools, toxicity was mainly governed by a single substance, with a very small number of schools having a multiple substance mix which required a combined risk assessment. The proposed approach enables the identification of such schools and thus, aides in the efficient health risk management of pollution emissions and air quality in the school environment.

Human health risk assessment of heavy metals in urban stormwater

Toxic chemical pollutants such as heavy metals (HMs) are commonly present in urban stormwater. These pollutants can pose a significant risk to human health and hence a significant barrier for urban stormwater reuse. The primary aim of this study was to develop an approach for quantitatively assessing the risk to human health due to the presence of HMs in stormwater. This approach will lead to informed decision making in relation to risk management of urban stormwater reuse, enabling efficient implementation of appropriate treatment strategies. In this study, risks to human health from heavy metals were assessed as hazard index (HI) and quantified as a function of traffic and land use related parameters. Traffic and land use are the primary factors influencing heavy metal loads in the urban environment. The risks posed by heavy metals associated with total solids and fine solids (<150µm) were considered to represent the maximum and minimum risk levels, respectively. The study outcomes confirmed that Cr, Mn and Pb pose the highest risks, although these elements are generally present in low concentrations. The study also found that even though the presence of a single heavy metal does not pose a significant risk, the presence of multiple heavy metals could be detrimental to human health. These findings suggest that stormwater guidelines should consider the combined risk from multiple heavy metals rather than the threshold concentration of an individual species. Furthermore, it was found that risk to human health from heavy metals in stormwater is significantly influenced by traffic volume and the risk associated with stormwater from industrial areas is generally higher than that from commercial and residential areas.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

How to progress forward in improving safety outcomes in the work-related driving field : a review of work-related driving research and development of an intervention framework [Extended abstract]

Road crashes are now the most common cause of work-related injury, death and absence in a number of countries. Given the impact of workrelated driving crashes on social and economic aspects of business and the community, workrelated road safety and risk management has received increasing attention in recent years. However, limited academic research has progressed on improving safety within the work-related driving sector. The aim of this paper is to present a review of work-related driving safety research to date, and provide an intervention framework for the future development and implementation of workrelated driving safety intervention strategies.