The Experts below are selected from a list of 234 Experts worldwide ranked by ideXlab platform
Paavo Ritala - One of the best experts on this subject based on the ideXlab platform.
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Service Supply Chain Risk Management
Operations and Supply Chain Management: An International Journal, 2014Co-Authors: Jyri Vilko, Paavo RitalaAbstract:Services are increasing in importance in international business and understanding the characteristics of services in the supply chain Context can provide crucial information for enabling efficient and effective implementation of Risk Management. Service literature has in general suggested that the distinctive nature of services—in contrast to products—can be connected to the so-called IHIP attributes (intangibility, heterogeneity, inseparability of production and consumption, and perishability). In this study, we utilize these attributes in the task of identifying the distinctive features and dynamics of service supply chains in a Risk Management Context. The study provides an important, yet sparsely addressed, viewpoint of the supply chain Risk Management literature by illustrating the special characteristics of services in this Context. We develop a conceptual framework and a set of propositions to highlight our arguments. The findings of the study suggest that service supply chain Risk Management requires special attention in terms of the IHIP attributes, which include issues the traditional supply chain Risk Management tools can easily miss. The presented viewpoint is a novel one and provides a new perspective to supply chain Risk Management theory by linking the service theories to supply chain Risk Management.
Hugh Outhred - One of the best experts on this subject based on the ideXlab platform.
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managing availability quality and security in a restructured electricity industry with reference to the australian national electricity market
Hawaii International Conference on System Sciences, 2006Co-Authors: Hugh OuthredAbstract:An AC electricity industry operates by establishing and maintaining near-sinusoidal voltage waveforms at end-user premises. Electricity markets in a restructured electricity industry should replicate this behavior as far as possible. In particular, they should allow end-users to specify the values they place on quality of electrical energy and allow them to manage their future Risk levels associated with availability and quality of supply. This property is needed to allocate resources to support a cost-effective flow of end-use energy services in a Risk-Management Context. Our research and experience with the Australian National Electricity Market suggest that the use of a forward-looking but short-term (eg 30 minutes) nodal spot market with associated ancillary service and derivative markets (aggregated to balance nodal precision and liquidity) would support an evolution of this kind subject to greater end-user participation in an enhanced electricity nodal spot market design employing voltage-value functions.
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HICSS - Managing Availability, Quality and Security in a Restructured Electricity Industry with Reference to the Australian National Electricity Market
Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06), 2006Co-Authors: Hugh OuthredAbstract:An AC electricity industry operates by establishing and maintaining near-sinusoidal voltage waveforms at end-user premises. Electricity markets in a restructured electricity industry should replicate this behavior as far as possible. In particular, they should allow end-users to specify the values they place on quality of electrical energy and allow them to manage their future Risk levels associated with availability and quality of supply. This property is needed to allocate resources to support a cost-effective flow of end-use energy services in a Risk-Management Context. Our research and experience with the Australian National Electricity Market suggest that the use of a forward-looking but short-term (eg 30 minutes) nodal spot market with associated ancillary service and derivative markets (aggregated to balance nodal precision and liquidity) would support an evolution of this kind subject to greater end-user participation in an enhanced electricity nodal spot market design employing voltage-value functions.
Jyri Vilko - One of the best experts on this subject based on the ideXlab platform.
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Service Supply Chain Risk Management
Operations and Supply Chain Management: An International Journal, 2014Co-Authors: Jyri Vilko, Paavo RitalaAbstract:Services are increasing in importance in international business and understanding the characteristics of services in the supply chain Context can provide crucial information for enabling efficient and effective implementation of Risk Management. Service literature has in general suggested that the distinctive nature of services—in contrast to products—can be connected to the so-called IHIP attributes (intangibility, heterogeneity, inseparability of production and consumption, and perishability). In this study, we utilize these attributes in the task of identifying the distinctive features and dynamics of service supply chains in a Risk Management Context. The study provides an important, yet sparsely addressed, viewpoint of the supply chain Risk Management literature by illustrating the special characteristics of services in this Context. We develop a conceptual framework and a set of propositions to highlight our arguments. The findings of the study suggest that service supply chain Risk Management requires special attention in terms of the IHIP attributes, which include issues the traditional supply chain Risk Management tools can easily miss. The presented viewpoint is a novel one and provides a new perspective to supply chain Risk Management theory by linking the service theories to supply chain Risk Management.
Timothy C Earle - One of the best experts on this subject based on the ideXlab platform.
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thinking aloud about trust a protocol analysis of trust in Risk Management
Risk Analysis, 2004Co-Authors: Timothy C EarleAbstract:There are two general theories of trust in Risk Management. One, derived from normative considerations, claims that trust is based on universally applicable factors such as fairness and objectivity. According to the second, social-psychological theory, trust is based on agreement or similarity and is Context specific. Although the first theory is normative, it also claims, along with the second, to be a descriptive account of how trust judgments are made. The present study was designed to test the adequacy of these two theories by using a think-aloud procedure to examine the thinking associated with trust judgments in an experimental simulation of a typical Risk Management Context. Contrary to the universalist theory, results supported two hypotheses derived from the social-psychological theory. First, study participants--who read brief policy statements designed to address global climate change--based their trust judgments on specific forms of agreement, ranging from agreement on the importance of the issue to agreement on values inferred from the policy statement. Second, the extent and depth of participants' conscious information processing was negatively related to the level of trust. Disagreement and distrust generated more conscious consideration than agreement and trust. These results provide a more detailed understanding than previously available of how trust in Risk Management is based on local forms of agreement that vary across people, Contexts, and time.
Lasse B Andersen - One of the best experts on this subject based on the ideXlab platform.
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the financial crisis in an operational Risk Management Context a review of causes and influencing factors
Reliability Engineering & System Safety, 2012Co-Authors: Lasse B Andersen, David Hager, S Maberg, M B Naess, M TunglandAbstract:Global macroeconomic imbalance combined with deregulation of US banks and increasing US real estate prices formed the basis for aggressive growth in worldwide trading of so called Collateralized Debt Obligations (CDO), i.e. similar loans pooled to create a financial derivative that can be bought or sold. The CDOs consisted mainly of prime and subprime housing loans, where the latter type is characterized by a high probability for default. Due to the growing market demand for this derivative and the subsequent shortage of prime loans, the subprime share in the CDOs increased from 43% to 71% from 2003 to 2007. Surprisingly the credit rating agencies did not change the top level (AAA) credit rating of the CDOs in the same period of time. How was this possible? And how could the tremendously resourceful firms that insured the derivatives by selling so called Credit Default Swaps to CDO owners avoid understanding the enormous Risk they took on? What later was to be called the financial crisis emerges in the spring of 2008 in line with the fall in US real estate prices and subsequent evaporation of the CDO market. The chain of events that led to numerous bankruptcies and threw the world into a recession not seen since the early 1930s has been labeled a system crisis, liquidity crisis, and a crisis of confidence (in the financial markets) among others. In this paper we survey how, and to what extent, operational Risk exposure in the organizations of mortgage brokers and banks, insurance companies, credit rating agencies, and investment banks contributed to the financial crisis. Bayesian Network analysis of causes and influencing factors in these four types of organizations indicates that operational Risk exposure played a crucial role in triggering the financial crisis. Our findings suggest that the financial crisis for a large part was the result of an industry wide failure to manage Risk in general, and operational Risk in particular.
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The financial crisis in an operational Risk Management Context—A review of causes and influencing factors
Reliability Engineering & System Safety, 2012Co-Authors: Lasse B Andersen, David Hager, S Maberg, M B Naess, M TunglandAbstract:Abstract Global macroeconomic imbalance combined with deregulation of US banks and increasing US real estate prices formed the basis for aggressive growth in worldwide trading of so called Collateralized Debt Obligations (CDO), i.e. similar loans pooled to create a financial derivative that can be bought or sold. The CDOs consisted mainly of prime and subprime housing loans, where the latter type is characterized by a high probability for default. Due to the growing market demand for this derivative and the subsequent shortage of prime loans, the subprime share in the CDOs increased from 43% to 71% from 2003 to 2007. Surprisingly the credit rating agencies did not change the top level (AAA) credit rating of the CDOs in the same period of time. How was this possible? And how could the tremendously resourceful firms that insured the derivatives by selling so called Credit Default Swaps to CDO owners avoid understanding the enormous Risk they took on? What later was to be called the financial crisis emerges in the spring of 2008 in line with the fall in US real estate prices and subsequent evaporation of the CDO market. The chain of events that led to numerous bankruptcies and threw the world into a recession not seen since the early 1930s has been labeled a system crisis, liquidity crisis, and a crisis of confidence (in the financial markets) among others. In this paper we survey how, and to what extent, operational Risk exposure in the organizations of mortgage brokers and banks, insurance companies, credit rating agencies, and investment banks contributed to the financial crisis. Bayesian Network analysis of causes and influencing factors in these four types of organizations indicates that operational Risk exposure played a crucial role in triggering the financial crisis. Our findings suggest that the financial crisis for a large part was the result of an industry wide failure to manage Risk in general, and operational Risk in particular.
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Stochastic modelling for the analysis of blowout Risk in exploration drilling.
Reliability Engineering & System Safety, 1998Co-Authors: Lasse B AndersenAbstract:Abstract This article discusses the theoretical basis and the general framework related to stochastic blowout modelling in an offshore Risk Management Context. The general scope is put forward by the Norwegian Petroleum Directorate (NPD) and the operating companies' need for an adequate decision making tool that permits studies of the effects of implemented Risk reducing measures based on local conditions. Previous work and today's practices regarding stochastic modelling for the analysis of blowout Risk are reviewed and discussed. Moreover, a different and perhaps more thorough approach to blowout Risk modelling in exploration drilling is suggested that is based upon physical causal mechanisms and expert judgements combined with hard data rather than world wide blowout statistics.
