Marco Falagario

TL;DR: In this paper, a decision-making tool for supplier selection in public procurement is proposed to help the awarding committee in this difficult task and, at the same time, maintaining a transparent procedure in accordance with governmental procurement regulations and requirements as well as guaranteeing fair and equal evaluation of all bids.

TL;DR: The obtained results show that the design method provides managers with key answers to issues related to the supply chain strategic configuration and agility, e.g., choosing the right location for distributors and retailers for enhanced MSC flexibility and performance.

TL;DR: A novel cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique for evaluating different elements (Decision Making Units or DMUs) under uncertainty is presented, demonstrating the model ease of application, its discriminative power among DMUs when compared to a more classical fuzzy DEA approach, and the usefulness in planning and validating targeted reforms in the case of healthcare systems.

TL;DR: By applying the presented methodology to the warehouse of an Italian interior design producer, it is shown that it represents a useful tool to systematically and dynamically improve the warehouse management, and leads to an innovative proposal for the warehouse analysis and optimization.

TL;DR: A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach, that is able to manage the supplier selection problem considering nondeterministic input and output data.