Using Ordered Weighted Average for Weighted Averages Inflation

Luis F. Espinoza-Audelo (), Ernesto León-Castro, Marycruz Olazabal-Lugo (), José M. Merigó and Anna M. Gil-Lafuente ()
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Luis F. Espinoza-Audelo: #x2020;Universidad of Occidente, Blvd. Lola Beltrán s/n esq. Circuito Vial, Culiacán 80200, México
Ernesto León-Castro: Universidad de la Salle Bajio, Av Universidad 602 Lomas del Campestre, C.P. #37150 León, Guanajuato, Mexico
Marycruz Olazabal-Lugo: #x2020;Universidad of Occidente, Blvd. Lola Beltrán s/n esq. Circuito Vial, Culiacán 80200, México
José M. Merigó: #x2021;School of Systems, Management and Leadership, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, 2007 NSW, Australia§Department of Management Control and Information Systems, School of Economics and Business, University of Chile, Av. Diagonal Paraguay 257, 8330015 Santiago, Chile
Anna M. Gil-Lafuente: #xB6;Department of Business Administration, University of Barcelona Av. Diagonal 690, 08034 Barcelona, Spain

International Journal of Information Technology & Decision Making (IJITDM), 2020, vol. 19, issue 02, 601-628

Abstract: This paper presents the ordered weighted average weighted average inflation (OWAWAI) and some extensions using induced and heavy aggregation operators and presents the generalized operators and some of their families. The main advantage of these new formulations is that they can use two different sets of weighting vectors and generate new scenarios based on the reordering of the arguments with the weights. With this idea, it is possible to generate new approaches that under- or overestimate the results according to the knowledge and expertise of the decision-maker. The work presents an application of these new approaches in the analysis of the inflation in Chile, Colombia, and Argentina during 2017.

Keywords: OWA operator; inflation; decision making (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0219622020500066

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