Abstract
This work describes the decision-making solution provided by the CONSENSUS project. Such solution is based on contextualising, applying and experimenting both Fuzzy Consensus Model and Average Rating Values algorithm to the Consensus Conference, i.e., a decision-making method widely used to achieve an agreement among different opinions on controversial and complex medical issues. The Consensus Conference has been applied so far without the use of technological enablers but the need for automatically executing some of its steps, tracing all the phases of the process, improving the transparency of the whole procedure, eliminating some biases due to the physical presence of the decision-makers, allowing the remote interaction of all the involved actors has fed the idea to create a tool based on the above computational models.
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References
Al-Samarraie, H., Hurmuzan, S.: A review of brainstorming techniques in higher education. Thinking Skills Creativity 27, 78–91 (2018). https://doi.org/10.1016/j.tsc.2017.12.002. https://www.sciencedirect.com/science/article/pii/S1871187117302729
Candiani, G., Colombo, C., Daghini, R., Magrini, N., Mosconi, P., Nonino, F., Satolli, R.: Come organizzare una conferenza di consenso. Manuale metodologico Sistema nazionale per le Linee Guida. In: Sistema Nazionale per le Linee Guida, 10 October 2019
Das, S., Ghosh, P.K., Kar, S.: Ranking of alternatives in multiple attribute group decision making: a fuzzy preference relation based approach. In: 2013 International Symposium on Computational and Business Intelligence, pp. 127–130 (2013)
Dong, Y., Zhao, S., Zhang, H., Chiclana, F., Herrera-Viedma, E.: A self-management mechanism for noncooperative behaviors in large-scale group consensus reaching processes. IEEE Trans. Fuzzy Syst. 26(6), 3276–3288 (2018)
Liao, H.: From conventional group decision making to large-scale group decision making: what are the challenges and how to meet them in big data era? A state-of-the-art survey. Omega 102141, 10 (2019). https://doi.org/10.1016/j.omega.2019.102141
Morente-Molinera, J., Pérez, I., Ureña, M., Herrera-Viedma, E.: On multi-granular fuzzy linguistic modeling in group decision making problems: a systematic review and future trends. Knowl.-Based Syst. 74, 49–60 (2015). https://doi.org/10.1016/j.knosys.2014.11.001. https://www.sciencedirect.com/science/article/pii/S095070511400392X
Pérez, I., Wikström, R., Mezei, J., Carlsson, C., Herrera-Viedma, E.: A new consensus model for group decision making using fuzzy ontology. Soft Comput. 7, 1617–1627 (2013). https://doi.org/10.1007/s00500-012-0975-5
Pérez, I.J., Cabrerizo, F.J., Alonso, S., Herrera-Viedma, E.: A new consensus model for group decision making problems with non-homogeneous experts. IEEE Trans. Syst. Man Cybern. Syst. 44(4), 494–498 (2014)
Acknowledgements
This paper is partially supported by MISE (Italian Government) in the context of the research initiative CONSENSUS. Moreover, the authors thank the company Momento Medico (https://www.momentomedico.it/) to have supported this work with its knowledge on Consensus Conference practice. Finally, we thank Lucia Pascarella for her contribution in the early study phases of the CONSENSUS project, and Luca Rizzuti for this precious support to the Web App implementation phase.
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Avino, I., Fenza, G., Fuccio, G., Genovese, A., Loia, V., Orciuoli, F. (2021). Applying a Consensus Building Approach to Communication Projects in the Health Sector: The Momento Medico Case Study. In: Barolli, L., Li, K., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2020. Advances in Intelligent Systems and Computing, vol 1263. Springer, Cham. https://doi.org/10.1007/978-3-030-57796-4_5
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