Options
Dr. León-Castro, Ernesto
Nombre de publicación
Dr. León-Castro, Ernesto
Nombre completo
León Castro, Ernesto
ORCID
3 results
Research Outputs
Now showing 1 - 3 of 3
- PublicationTax revenue measurement using OWA operators(Taylor & Francis, 2024)
; ;Blanco-Mesa, Fabio ;Hussain, Walayat ;Flores-Sosa, MarthaPerez-Arellano, LuisThe 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. - PublicationPrioritized induced heavy operators applied to political modelling(World Scientific Publishing, 2021)
; ;Perez-Arellano, Luis ;Olazabal-Lugo, MaricruzMerigó, JoseThis paper presents the prioritized induced heavy ordered weighted average (PIHOWA) operator. This operator combines an unbounded weighting vector, an induced vector and a prioritized vector and can be applied to the group decision-making process where the information provided by each decision maker does not have the same importance. An application of this operator is done in governmental transparency in Mexico based on the Open Government Metric (OGM). Among the main results it is possible to visualize how the relative importance of each component can generate important change in the top 10 ranking. - PublicationHeavy moving average distances in sales forecasting(Industrial Research Institute for Automation and Measurements, 2023)
;Olazabal-Lugo, Maricruz ;Espinoza-Audelo, Luis; ;Perez-Arellano, LuisBlanco-Mesa, FabioThis paper presents a new aggregation operator technique that uses the ordered weighted average (OWA), heavy aggregation operators, Hamming distance, and moving averages. This approach is called heavy ordered weighted moving average distance (HOWMAD). The main advantage of this operator is that it can use the characteristics of the HOWMA operator to under-or overestimate the results according to the expectations and the knowledge of the future scenarios, analyze the historical data of the moving average, and compare the different alternatives with the ideal results of the distance measures. Some of the main families and specific cases using generalized and quasi-arithmetic means are presented, such as the generalized heavy moving average distance and a generalized HOWMAD. This study develops an application of this operator in forecasting the sales growth rate for a commercial company. We find that it is possible to determine whether the company's objectives can be achieved or must be reevaluated in response to the actual situation and future expectations of the enterprise.