Decising

DECISING – DECISion science and management engineerING

About

Driven by real world challenges on the frontiers of engineering and management, and grounded on the principles of decision-making and decision-aiding theory, the Decision Science and Management Engineering (DECISING) branch of CEGIST is a multimethodological area that develops methods, models, decision-support tools and knowledge to assist engineering management practice in complex contexts that involve diverse stakeholders, multiple objectives and several sources of uncertainty. At DECISING we follow a collaborative-learning constructivist paradigm integrating socio-technical processes to design sustainable solutions to problems of performance appraisal and value measurement, evaluation and prioritization, resource allocation and budgeting, risk analysis, project management, policy design and strategic choice. Our mission is driven by industry innovation, multidisciplinary research and spin-off partnerships, and is currently focused on (although not limited to) health, energy, and environmental settings, always exploring cross-fertilization with the other areas of CEGIST and international collaboration.

Group Leader

Selected Publications

Desirability–doability group judgment framework for the collaborative multicriteria evaluation of public policies

International Transactions in Operational Research | 2023

Carlos Costa

Mónica Oliveira

Teresa Rodrigues

Collaborative development of composite indices from qualitative value judgements: The EURO-HEALTHY Population Health Index model

European Journal of Operational Research | 2023

Carlos Costa

Teresa Rodrigues

João Costa

Ângela Freitas

Paula Santana

Towards A Framework for Implementing Remote Patient Monitoring From an Integrated Care Perspective: A Scoping Review

International Journal of Health Policy and Management | 2023

Rafael Miranda

Paulo Nicola

Filipa Baptista

Isabel Albuquerque

ANIPHI: An innovative pedagogical platform based on the Delphi method to support animal welfare teaching

PLOS ONE | 2022

M. Vidal

J.-B. Menassol

T.L. Mateus

A.S. Santos

J.-P. Durieux

M.D. Oliveira

Enhancing optimization planning models for health human resources management with foresight

Omega | 2021

M. Amorim-Lopes

M. Raposo

T. Cardoso-Grilo

M. Barbas

M. Alves