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A prescriptive framework for recommending decision attributes of infrastructure disaster recovery problems

Zamanifar, Milad; Hartmann, Timo

This paper proposes a framework to systematically evaluate and select attributes of decision models used in disaster risk management. In doing so, we formalized the attribute selection process as a sequential screening-utility problem by formulating a prescriptive decision model. The aim is to assist decision-makers in producing a ranked list of attributes and selecting a set among them. We developed an evaluation process consisting of ten criteria in three sequential stages. We used a combination of three decision rules for the evaluation process, alongside mathematically integrated compensatory and non-compensatory techniques as the aggregation methods. We implemented the framework in the context of disaster resilient transportation network to investigate its performance and outcomes. Results show that the framework acted as an inclusive systematic decision aiding mechanism and promoted creative and collaborative decision-making. Preliminary investigations suggest the successful application of the framework in evaluating and selecting a tenable set of attributes. Further analyses are required to discuss the performance of the produced attributes. The properties of the resulting attributes and feedback of the users suggest the quality of outcomes compared to the retrospective attributes that were selected in an unaided selection process. Research and practice can use the framework to conduct a systematic problem-structuring phase of decision analysis and select an equitable set of decision attributes.
Published in: Environment Systems and Decisions, 10.1007/s10669-021-09824-0, Springer Nature