Programs are demarcated as administrative structures established to realize planned organizational strategies through multi-project activities. Programs occupy a distinct locus in organizational hierarchy, so therefore necessitate specialized management approaches. Risks in programs tend to widen the gap between the organizational plans and the actual program realizations. However, effective risk management can minimize these gaps. This research frames a structured approach for program risk management, called Risk Leveling in Program Environments (RLPE), which suggests (a) a deliberate shift of risks to the right organizational level where they can be addressed most effectively; and (b) a unique procedure for risk management, which attempts to stabilize the risky contexts in programs. RLPE tracks the standard risk management process, preserves distinct program locus, and employs certain qualitative and quantitative measures to achieve risk leveled environments for program success. It has been demonstrated how certain tools and concepts, such as Analytical Hierarchy Process (AHP), As Low As Reasonably Practicable (ALARP), standard deviation, etc. can be employed for risk oriented decision making in programs. RLPE is an instrumental approach, which can help the policy makers in controlling the risky contexts thereby providing sustainable growth for development programs. The offered approach can be particularly advantageous for risk management in large-scale (development) programs.
OPEN ACCESSSustainability 2015, 7 5897
When assessing undiscovered oil resources, an important step is the assessment of geological risk, which is usually defined as the probability that there will be no accumulation of hydrocarbons. Some important authors have traditional ways of obtaining this probability, but these classic models are not developed on a rigorous basis. Therefore, they may present conflicting results, which are not always compatible with reality and are not able to take into account historical data from similar situations already studied. This article aims to propose a Bayesian approach to the determination of geological risk with advantages over classical approaches. The positive aspects and limitations of the Bayesian approach are discussed and an illustrative application using fictitious data is presented.
Aplicação de modelo das p-medianas para a localização de unidades estratégicas de saúde da família ribeirinhas: um estudo de caso em uma localidade amazônica Application of a p-median model for the location of strategic riparian families health units: a case study in an amazon place
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