Evidential Reasoning Decision & Risk Analysis, and Performance Optimisation

This theme has three key research focuses: evidential reasoning decision analysis, belief rule based risk analysis, and performance assessment and planning. The first focus will build on our current strengths of research on multiple criteria decision analysis with both quantitative and qualitative information under uncertainty, which has been extensively supported by research councils and industry. This research will be focused on investigating the interrelationships between statistical decision-making and evidence-based decision-making. The ultimate goal is to develop an evidential reasoning decision analysis methodology and theory to support informed and robust decision making in a wide range of areas. The second research focus will be based on our current research projects funded by EPSRC and other bodies to provide generic frameworks, models, methods and tools to facilitate risk, safety and security analysis and decision making. In many social and engineering systems, it is difficult to estimate the likelihood of occurrence of a risk event, its direct impact and potential vulnerability. This is largely due to the need to analyse many factors that are often associated with various types of uncertainty such as subjectivity, incompleteness and even lack of understanding and data. The frameworks, models, methods and tools will be developed to help handle such uncertainties and applied to various areas such as supply chain risk and security assessment, dynamic clinical risk assessment, project risk assessment, financial risk analysis, corporate risk analysis, and early warning systems for social crises.

The third research focus is to investigate models, methods and processes to integrate performance assessment and performance planning. While performance measurement is becoming increasingly more common in many organisations such as NHS hospitals, it has not yet become performance management. This research will be focused on applying analytical methodologies like data envelopment analysis and multiple objective linear programming to help reconcile management control and management planning in a consistent way with the decision makers’ preferences taken into account in an interactive fashion.