Artikel
Efficient election campaign optimization using integer programming
Purpose: Political parties spend significant amounts of resources during their election campaigns, which are usually designed in a sub-optimal and informal way. This study aims to provide a mathematical framework for political parties to optimize their election campaigns, so that they can maximize their performance in the elections. Design/methodology/approach: In this work, we provide certain mathematical relations to determine the minimum necessary number of votes to gain additional seats in an election region under the D'hondt election rule. Also we develop a convenient mathematical model that optimizes the resource allocation scheme of a political party to maximize the potential seats won. We test our models on Turkish Parliamentary elections data Findings: Our results show that with various basic assumptions, which are suitable for real life cases, one can obtain significant gains in the election outcomes even with small budgets. We also provide the relations among swing vote rates, unit vote costs and budget with the number seats won in a parliament. Originality/value: This study provides useful insights for both political party management teams as well as researchers. Political parties need to conduct more market research to collect and work on election data to increase their performances. From the research perspective, to the best of our knowledge, this is one of first studies that approaches to the election campaigns for the D'hondt system with mathematical optimization tools.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 11 ; Year: 2018 ; Issue: 2 ; Pages: 341-348 ; Barcelona: OmniaScience
- Classification
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Management
- Subject
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election campaign optimization
D'hondt rule
integer programming
- Event
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Geistige Schöpfung
- (who)
-
Güney, Evren
- Event
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Veröffentlichung
- (who)
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OmniaScience
- (where)
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Barcelona
- (when)
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2018
- DOI
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doi:10.3926/jiem.2496
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Güney, Evren
- OmniaScience
Time of origin
- 2018
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