Tax Revenue Measurement Using OWA Operators

Leon-Castro, E; Blanco-Mesa, F; Hussain, W; Flores-Sosa, M; Perez-Arellano, LA

Tax Revenue Measurement Using OWA Operators

Leon-Castro, E Blanco-Mesa, F Hussain, W

Flores-Sosa, M Perez-Arellano, LA

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Publisher:: TAYLOR & FRANCIS INC
Publication Type:: Journal Article
Citation:: Cybernetics and Systems, 2022
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Leon-Castro, E
dc.contributor.author	Blanco-Mesa, F
dc.contributor.author	Hussain, W https://orcid.org/0000-0003-0610-4006
dc.contributor.author	Flores-Sosa, M
dc.contributor.author	Perez-Arellano, LA
dc.date.accessioned	2023-04-20T03:59:13Z
dc.date.available	2023-04-20T03:59:13Z
dc.date.issued	2022-01-01
dc.identifier.citation	Cybernetics and Systems, 2022
dc.identifier.issn	0196-9722
dc.identifier.issn	1087-6553
dc.identifier.uri	http://hdl.handle.net/10453/170024
dc.description.abstract	The aim of this paper is to present the application of the OWA operator and some of its extensions in the calculation of continent and global tax revenues. The idea is to present how the analysis of an important economic indicator can vary depending on how the information is aggregated. An example was employed based on the Organization for Economic Co-operation and Development (OECD) database using 111 countries that were divided by continent, and then the global tax revenue was calculated using different aggregation operators. Different analyses can be carried out by governments and enterprises to improve decision making and fiscal politics.
dc.language	English
dc.publisher	TAYLOR & FRANCIS INC
dc.relation.ispartof	Cybernetics and Systems
dc.relation.isbasedon	10.1080/01969722.2022.2110687
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Tax Revenue Measurement Using OWA Operators
dc.type	Journal Article
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-04-20T03:59:11Z
pubs.publication-status	Published

Abstract:

The aim of this paper is to present the application of the OWA operator and some of its extensions in the calculation of continent and global tax revenues. The idea is to present how the analysis of an important economic indicator can vary depending on how the information is aggregated. An example was employed based on the Organization for Economic Co-operation and Development (OECD) database using 111 countries that were divided by continent, and then the global tax revenue was calculated using different aggregation operators. Different analyses can be carried out by governments and enterprises to improve decision making and fiscal politics.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/170024