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MCDM approach for weighted ranking of candidates in e-voting
- Source :
- Informacijos Mokslai, Vol 86 (2019)
- Publication Year :
- 2019
- Publisher :
- Vilnius University Press, 2019.
-
Abstract
- The aim of the study is the application of multi-criteria evaluation methods for ranking of candidates in e-voting. Due to the potential to enhance the electoral efficiency in e-voting multiple criteria, such as personality traits, activity and reputation in social media, opinion followers on election area and so on for the selection of qualified personnel can be considered. In this case, the number of criteria excesses in the decision-making stage directed us to the use of a multi-criteria decision making model (MCDM). This paper proposes MCDM for weighted ranking of candidates in e-voting. Criteria for the candidates’ ranking and selection are determined and each voter uses the linguistic scales for the ranking of each candidate. Candidates’ ranking is evaluated according to all criteria. In a numerical study, it is provided the candidates’ evaluation on the base of selected criteria and ranked according to the importance of criteria. To assess the importance of the criteria and to evaluate the suitability of the candidates for each of the criteria, the voters use linguistic variables. In practice, the proposed model can use different evaluation scales for the selection of candidates in e-voting. The proposed model allows selecting a candidate with the competencies based on the criteria set out in the e-voting process and making more effective decisions.
- Subjects :
- Sociology and Political Science
Process (engineering)
Computer science
media_common.quotation_subject
02 engineering and technology
Machine learning
computer.software_genre
Multi-criteria decision making model
lcsh:Communication. Mass media
Set (abstract data type)
Management of Technology and Innovation
Voting
050602 political science & public administration
0202 electrical engineering, electronic engineering, information engineering
Media Technology
MCDM
Selection (genetic algorithm)
media_common
business.industry
Communication
05 social sciences
Multiple-criteria decision analysis
lcsh:P87-96
0506 political science
E-voting
Weighted rank
Ranking
Political Science and International Relations
020201 artificial intelligence & image processing
E-democracy
Artificial intelligence
Candidate selection
business
computer
Decision-making models
Reputation
Subjects
Details
- ISSN :
- 13921487 and 13920561
- Volume :
- 86
- Database :
- OpenAIRE
- Journal :
- Informacijos mokslai
- Accession number :
- edsair.doi.dedup.....9793757fd70f7e89bc79694956090e33
- Full Text :
- https://doi.org/10.15388/im.2019.86.23