The design, implementation and use of adequate performance measurement and management frameworks can play an important role if organisations are to succeed in an increasingly complex, interdependent and changing world. Yet, despite widespread recognition of the importance of performance assessment, there are some issues that require further study if measurement systems are to be effective in the process of management through monitoring and decision making. This article proposes and seeks to illustrate that the use of system dynamics and multicriteria decision analysis, as part of a broader framework for performance measurement, can address some of the issues identified. The use of these approaches, independently and in an integrated manner, provides a means of exploring the dynamic complexity of organisations, making explicit trade-offs between performance measures, and assessing the impacts of initiatives to improve performance, thereby enhancing understanding and ultimately contributing to the improvement of organisational performance
The complex structure of construction project risks arises from their internal and external interactions with their dynamic nature throughout the life cycle of the project. A system dynamics (SD) approach to construction project risk management is presented, including risk analysis and response process. Owing to the imprecise and uncertain nature of risks, fuzzy logic is integrated into system dynamics modelling structure. Risk magnitudes are defined by a fuzzy logic based risk magnitude prediction system. Zadeh's extension principle and interval arithmetic is employed in the SD simulation model to present the system outcomes considering uncertainties in the magnitude of risks resulting from the risk magnitude prediction system. The performance of the proposed method is assessed by employing the method in the risk management plan of a sample project. The impact of a sample risk is quantified and efficiency of different alternative response scenarios is assessed. The proposed approach supports different stages of the risk management process considering both the systemic and uncertain nature of risks
In recent years there has been significant interest in multimethodology and the mixing of OR/MS methods, including Discrete Event Simulation (DES) with System Dynamics (SD). Several examples of mixing DES and SD are described in the literature but there is no overarching framework which characterises the spectrum of options available to modellers. This paper draws on a sample of published case studies, in conjunction with the theoretical literature on mixing methods, to propose a toolkit of designs for mixing DES and SD which can be implemented as a set of questions which a modeller should ask in order to guide the choice of design and inform the associated project methodology. The impetus for this work was the perceived need to transfer insight from reported practice in order to formalise how the two methods can be and have been mixed
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