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Additional file 1. is a copy of the final version of the questionnaire.

Additional file 2. is a Word file (.docx) and is a table containing the design criteria with median, interquartile range, its interpretation and the number of panellists.

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteriadecision analysis(MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This reviewpaperpresents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches.

Due to conservative design models and safe construction practices, civil-infrastructure elements, such as bridges, usually have unknown amounts of reserve capacity that exceed code requirements. The quantification of this reserve capacity may lead to better asset management by avoiding unnecessary replacement. However, this task is challenging due to high uncertainty levels that are present in structural-behavior models. These uncertainties can be reduced using field measurements associated with structural-identification methodologies. To maximize the information from monitoring, the choice of the measurement system is crucial and can be seen as an optimization task. Although an optimal measurement system must present several characteristics, only the information-gain criterion is usually taken into account. This study presents a framework to design measurement systems using multiple-objective functions. The Exeter Bascule Bridge (UK) is used as case study and the recommended measurement systems are proposed for multiple settings of asset-manager preferences. The framework supports a rational selection of measurement systems between close alternatives.