1,720,972 research outputs found
Assessment of quality and compositional attributes of Colombian Arabica coffees through a profile regression based analysis
No full textClassification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios
No full textThis paper proposes a method for generating robust ranks of Delphi projections, which are particularly suitable
as input for clustering algorithms. The resulting clusters can be used for the construction of Delphi-based scenarios.
The method is very flexible and can be applied to the classification of any variable derived from subjective
judgments. In the analysis and interpretation of the results of a Delphi, a series of problems emerge related
to the use of the concept of distance. The use of robust ranks allows us to overcome these problems.
The proposed method is also robust with respect to the expertise of panel members, which is a feature that
creates many problems both at the moment of measurement and in the subsequent use of those measurements.
This opens up important reflections on a crucial aspect of any Delphi study: the dependence of the results on the
expertise of the panelists. One of the outputs of the method proposed here is constituted by the uncertainty
intervals, which can be used as a monitoring system for the quality of the Delphi projections.
By applying the method to the future of families in the north-east of Italy, we will show its validity, reproducibility,
and practicality
Identifying students at risk for academic failure within a construct validation framework
No full textScenari e simulazioni per lo studio delle aree urbane . Applicazioni dell’UrbanSim all’area metropolitana di Roma
No full textResilience, trust in science, and future outlooks: Perspectives of Italian youth in the post-pandemic era
No full text
Robust weighted aggregation of expert opinions in futures studies
Full text linkExpert judgments are widespread in many fields, and the way in which they are collected and the procedure by which they are aggregated are considered crucial steps. From a statistical perspective, expert judgments are subjective data and must be gathered and treated as carefully and scientifically as possible. In the elicitation phase, a multitude of experts is preferable to a single expert, and techniques based on anonymity and iterations, such as Delphi, offer many advantages in terms of reducing distortions, which are mainly related to cognitive biases. There are two approaches to the aggregation of the judgments given by a panel of experts, referred to as behavioural (implying an interaction between the experts) and mathematical (involving non-interacting participants and the aggregation of the judgments using a mathematical formula). Both have advantages and disadvantages, and with the mathematical approach, the main problem concerns the subjective choice of an appropriate formula for both normalization and aggregation. We propose a new method for aggregating and processing subjective data collected using the Delphi method, with the aim of obtaining robust rankings of the outputs. This method makes it possible to normalize and aggregate the opinions of a panel of experts, while modelling different sources of uncertainty. We use an uncertainty analysis approach that allows the contemporaneous use of different aggregation and normalization functions, so that the result does not depend on the choice of a specific mathematical formula, thereby solving the problem of choice. Furthermore, we can also model the uncertainty related to the weighting system, which reflects the different expertise of the participants as well as expert opinion accuracy. By combining the Delphi method with the robust ranking procedure, we offer a new protocol covering the elicitation, the aggregation and the processing of subjective data used in the construction of Delphi-based future scenarios. The method is very flexible and can be applied to the aggregation and processing of any subjective judgments, i.e. also those outside the context of futures studies. Finally, we show the validity, reproducibility and potential of the method through its application with regard to the future of Italian families
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