Abstract
AbstractValuable information for decision-making can be obtained by collecting and analyzing opinions from diverse stakeholder or respondent groups, which usually have different backgrounds and are variously affected by the topics under survey. For this to succeed, it is necessary to manage the uncertainty of respondents’ opinions, different number of filled questionnaires among groups, different number of questions for each stakeholder group, and relevance of subsets of respondent groups. This work proposes handling the hesitance of respondents’ opinions for the rating scale questions. To evaluate the collected opinions, a three-level aggregation model is developed. In the first level, the overall opinion of each respondent is computed as a mean of fuzzy numbers covering uncertain answers and their respective hesitance. In the second level, stakeholder groups are considered as a whole. Aggregation by a relative quantifier is applied to calculate the validity of a proposition the majority of respondents have a positive or negative opinion. At the third level, the consensus among diverse subsets of stakeholder groups is calculated considering the relevance of each group independently as well as their so-called coalitions by Choquet integral. Finally, the proposed model is illustrated by a real-life case study.
Funder
Ministerstvo Školství, Mládeže a Telovýchovy
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Reference52 articles.
1. Albert W, Tullis T (2013) Measuring the user experience, collecting, analyzing, and presenting usability metrics (interactive technologies), 2nd edn. Elsevier, Dodrecht
2. Beliakov G, James S, Wu J-Z (2020) Discrete fuzzy measures. Springer, Cham
3. Beliakov G, Sola HB, Calvo T (2016) Practical guide to averaging functions. Springer, Cham
4. Bueno I, Carrasco RA, Ureña R, Herrera-Viedma E (2019) Application of an opinion consensus aggregation model based on owa operators to the recommendation of tourist sites. Procedia Computer Science, 162:539–546. 7th International Conference on Information Technology and Quantitative Management (ITQM 2019): Information technology and quantitative management based on Artificial Intelligence
5. Chen J-F, Hsieh H-N, Do QH (2015) Evaluating teaching performance based on fuzzy ahp and comprehensive evaluation approach. Appl Soft Comput 28:100–108
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