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The main objective of this article is to present the formulation of a Capital Asset Pricing Model ordered weighted average CAPMOWAand its extensions, called CAPM-induced OWA (CAPMIOWA), CAPM Bonferroni OWA (CAPMBon-OWA), and CAPM Bonferroni-induced OWA CAPMBon-IOWA. A step-by-step process for applying this new proposal in a real case of formulating investment portfolios is generated. These methods show several scenarios, considering the attitude, preferences, and relationship of each argument, when underestimation or overestimation of the information by the decision maker may influence the decision-making process regarding portfolio investments. Finally, the complexity of the method and the incorporation of soft information into the modeling process lead to generating a greater number of scenarios and reflect the attitudes and preferences of decision makers.

The success on forecasting the performance of PV systems, it lies in depicting the non-linear behavior dynamics of its I–V curves, as a direct consequence of the variations in the operational conditions, where the photovoltaic system is set up. Throughout this work, authors address the physical–mathematical basics, and the assumptions made, so as to propose a theoretical approach, on purpose of describing the dynamics concerning to these systems. Findings, as well as the manuscript novelty, they comprise a full model deduced by subsections dealing with the phenomena under analysis; all them derived as function of the irradiance and module temperature.

Dealing with the sun’s rays reflections behavior, the manuscript shed light about its impact in the PV modules energy yield; where starting from the physical–mathematical basics and through a three empirical parameter model improvement, it sketches the performance of these devices. In turn, an extra term has been considered for the better process tracking, which comprises sun’s rays reflections on PV modules surfaces. The approach takes into account the empirical parameters fitting, leaned on the datasheets information and environmental conditions. Thus, in addition to the thermal losses, the post-module losses caused by the resistance of the semiconductor layers and electrical contacts, as well as the internal losses resulting from recombination at defects and impurities present in the modules, here the pre-module losses are considered in the modeling focused on the sun’s rays reflections. Even though, others factors additional to irradiance and operating temperature, like soiling and partial shading conditions, have influence on PV module performance; the manuscript main purpose lies in deductions and implications demonstrating the expecting concordance between theory and proposed extra term, for sunrays reflections scenario, as one manuscript novelties. Approach is applied to 21 PV modules with cells made of crystalline silicon (mono & poly- Si), passivated emitter and rear cell (PERC), thin films (CdTe) assessing its reliability (> 70%; ∼76%), as other of main targets.

Agricultural product prices are subject to various uncertainties, including unpredictable weather conditions, pest infestations, and market fluctuations, which can significantly impact agricultural yields and productivity. Accurately assessing and understanding price is crucial for farmers, policymakers, and stakeholders in the agricultural sector to make informed decisions and implement appropriate risk management strategies. This study used the ordered weighted average (OWA) operator and its extensions as mathematical aggregation techniques incorporating ordered weights to capture and evaluate the factors influencing price variation. By generating different vectors related to different inputs to the traditional formulation, it is possible to aggregate information to calculate and provide a new view of the outcomes. The results of this research can help enhance risk management practices in agriculture and support decision-making processes to mitigate the adverse effects of price.

A brain tumor occurs in humans when a normal cell turns into an aberrant cell inside the brain. Primarily, there are two types of brain tumors in Homo sapiens: benign tumors and malignant tumors. In brain tumor diagnosis, magnetic resonance imaging (MRI) plays a vital role that requires high precision and accuracy for diagnosis, otherwise, a minor error can result in severe consequences. In this study, we implemented various configured convolutional neural network (CNN) paradigms on brain tumor MRI scans that depict whether a person is a brain tumor patient or not. This paper emphasizes objective function values (OFV) achieved by various CNN paradigms with the least validation cross-entropy loss (LVCEL), maximum validation accuracy (MVA), and training time (TT) in seconds, which can be used as a feasible tool for clinicians and the medical community to recognize tumor patients precisely. Experimentation and evaluation were based on a total of 2189 brain MRI scans, and the best architecture shows the highest accuracy of 0.8275, maximum objective function value of 1.84, and an area under the ROC (AUC-ROC) curve of 0.737 to accurately recognize and classify whether or not a person has a brain tumor.

The main aim is to propose a new method for estimating the Human Development Index using ordered weighted average. To develop this method, ordered weighted geometric average (OWGA), induced OWGA prioritized OWA (POWA) operator are studied. Using Human Development Index formulation in combination to aggregations operators presented above is proposed the prioritized induced ordered weighted geometric average (PIOWGA) operator. A mathematical application is carried out to estimate the Human Development Index and compare it with the traditional method and other existing methods. Finally, it is noted that decision makers have an influence on the order given in the ranking by its attitude and criterion, and method can capture the subjective information prioritized by them.

The main aim of this article was, using subjective information, to analyze the forgotten factors that influence the motivation of Boyacenses to become entrepreneurs. The study was carried out with entrepreneurs enrolled in the Boyacá Region Brand Program (BRBP). For the treatment of the collected data, the method of the experts and the theory of forgotten effects were used to identify second-generation incidences involving motivational factors in Boyacense entrepreneurs. The research questions that guided the study were as follows: What are the forgotten effects among the motivational factors of entrepreneurship? What are the intermediate factors that generate the second-order effects? What are the economic, psychological, cultural, and environmental factors that have second-order effects among them? Among the main findings, it was possible to visualize second-degree relationships between economic, cultural, and psychological factors. Additionally, in the case of entrepreneurs from Boyacá, the primary motivation for most of them to develop their business idea was economic independence, while the least motivating was the improvement of social status. Likewise, the need for achievement was highlighted. Finally, the country’s economic situation was found to work against the development of entrepreneurship.

This article applies the Bonferroni prioritized induced heavy ordered weighted average (OWA) to analyze a series of data and focuses on the Bonferroni average and heavy induced prioritized aggregation operators. The objective of the present work is to present a new aggregation operator that combines the heavy induced prioritized Bonferroni and its formulations and represents the Bonferroni mean with variables that induce an order with vectors that are greater than one. This work develops some extensions using prioritization. The main advantage is that different types of information provided by a group of decision makers to compare real situations are included in this formulation. Finally, an example using the operators to calculate the transparency of the websites of the 32 states of Mexico was performed. The main idea was to visualize how the ranking can change depending on the importance of the five components of the methodology. The main results show that it is possible to detect some important changes depending on the operator and the experts considered.

Human capital management is a strategic element for companies in a globalized world. Therefore, they must use strategies and methods to recruit and select personnel assertively to focus their training, strengthening, and business growth efforts. Personnel selection can be seen as a decision problem and can be addressed in a multi-criteria decision-making context. This work aims to present the selection process of a barista in a Mexican coffee shop. The baristas could be the face of the company to customers, and they could significantly impact their overall experience. The personnel selection process included eleven candidates and three criteria. This process was performed using the ELECTRE-III to model the preferences of a decision-maker and RP2-NSGA-II+H, a multi-objective evolutionary algorithm that exploits fuzzy outranking relations to derive multi-criteria rankings. The ordering obtained with the algorithm did not have any inconsistency concerning the integral preference model, and it allowed for the selection of a candidate to occupy the barista position. The results show the relevance of combining preference modeling with multi-criteria analysis methods for decision-making and artificial intelligence techniques.

El objetivo del presente estudio fue presentar un análisis bibliométrico de las investigaciones sobre intención emprendedora relacionado con la educación superior. Para ello, se aplicó una metodología que usó el conjunto de datos de la colección principal de la Web of Science y, mediante una ecuación de búsqueda en la que se utilizan operadores booleanos, se encontraron un total de 1933 documentos, con un rango temporal para ser analizados desde enero de 1998 hasta diciembre de 2022. Se presenta, además, un análisis de cocitaciones, coocurrencias, citaciones y coautorías de artículos, autores, revistas, países y palabras clave, usando como herramienta principal el software VOSviewer. Los resultados mostraron que el campo empieza a crecer desde 2015, que los enfoques más estudiados están relacionados con la autoeficacia, la transculturalidad, la educación en emprendimiento y género, y que las autorías y universidades más destacados están en España. Se identifican los tres ejes de investigación: actitudes personales (enfoque moldeamiento), capacidad de acción (enfoque empresarial) y entorno (enfoque universitario), así como los retos de la educación superior para la formación empresarial. Con ello, se puede tener una perspectiva holística de lo que ocurren en este campo de investigación que ayude a encontrar temas de interés dentro de este para futuras investigaciones.

Este documento presenta un modelo de articulación productivo que sirve de base para desarrollar y mejorar los sistemas regionales de innovación. El objetivo principal es generar un proceso de vinculación entre el sector industrial, la academia y el gobierno dentro del cual se puedan resolver problemas regionales específicos mediante la intervención efectiva de cada uno de los actores. Además del proceso, se presenta una historia de éxito del Estado de Guanajuato, México, que sirve para visualizar como un proceso claro y definido de articulación que permite una transferencia de conocimiento entre los actores.

El objetivo principal de este trabajo es el de evaluar el nivel de competitividad de las regiones de México basado en el desempeño de 10 principales factores provenientes de 100 indicadores. La metodología está basada en el Proceso Jerárquico Multicriterio con la capacidad de analizar el desempeño de un subconjunto de indicadores y el conjunto completo de indicadores, y como impactan en la competitividad de la región. Un aspecto importante de Proceso Jerárquico Multicriterio implementado es que considera la interacción entre criterios (indicadores) y mide el desempeño de un gran número de criterios. La principal contribución de la investigación es la identificación del nivel peor de competitividad de la región, y los factores que requieren más atención por el tomador de decisiones.

Distance measures in ordered weighted averaging (OWA) operators allow the modelling of complex decision making problems where a set of ideal values or characteristics are required to be met. The objective of this paper is to introduce extended distance measures and logarithmic OWA-based decision making operators especially designed for the analysis of financial investment options. Based on the immediate weights, Bonferroni means and logarithmic averaging operators, in this paper we introduce the immediate weights logarithmic distance (IWLD), the immediate weights ordered weighted logarithmic averaging distance (IWOWLAD), the hybrid weighted logarithmic distance (HWLD), the Bonferroni ordered weighted logarithmic averaging distance (B-OWLAD) operator, the Bonferroni immediate weights ordered weighted logarithmic averaging distance (B-IWOWLAD) operator and the Bonferroni hybrid weighted logarithmic distance (HWLD). A financial decision making illustrative example is proposed, and the main benefits of the characteristic design of the introduced operators is shown, which include the analysis of the interrelation between the modelled arguments required from the decision makers and the stakeholders, and the comparison to an ideal set of characteristics that the possible companies in the example must portray. Moreover, some families, particular cases and brief examples of the proposed operators, are studied and presented. Finally, among the main advantages are the modeling of diverse perspectives, attitudinal characteristics and complex scenarios, through the interrelation and comparison between the elements with an ideal set of characteristics given by the decision makers and a set of options.

In this part of a series of two papers, we extend the theorems discussed in Part I for infinite series. We then use these theorems to develop distinct novel results involving the Hurwitz zeta function, Riemann zeta function, polylogarithms and Fibonacci numbers. In continuation, we obtain some zeros of the newly developed zeta functions and explain their behaviour using plots in complex plane. Furthermore, we provide particular cases for the theorems and corollaries that show that our results generalise the currently available functions and series such as the Riemann zeta function and the geometric series. Finally, we provide four miscellaneous examples to showcase the vast scope of the developed theorems and showcase that these two theorems can provide hundreds of new results and thus can potentially create an entirely new field under the realm of number theory and analysis.

In this paper, we develop two new theorems relating to the series of floor and ceiling functions. We then use these two theorems to develop more than forty distinct novel results. Furthermore, we provide specific cases for the theorems and corollaries which show that our results constitute a generalisation of the currently available results such as the summation of first n Fibonacci numbers and Pascal’s identity. Finally, we provide three miscellaneous examples to showcase the vast scope of our developed theorems.

Este artículo utiliza diferentes operadores de media móvil para innovar en la medición de la administración de portafolio. Entre los operadores que han utilizado se encuentran los operadores Heavy Ordered Weighted Moving Average (HOWMA) y el operador Induced HOWMA (IHOWMA). La principal ventaja de estos operadores es que pueden incluir en la misma formulación los datos históricos a través de las medias móviles y la experiencia y el conocimiento del responsable de la toma de decisiones con el vector de ponderación e inducido. Se desarrolló una aplicación para seleccionar en qué tipo de producto invertir, teniendo en cuenta las ventas históricas y el margen de utilidad, presentando una metodología original para incluir en el proceso de toma de decisiones.

This paper presents the Pythagorean membership grade induced ordered weighted moving average (PMGIOWMA) operator with some particular cases and theorems. The main advantage of this new operator is that can include the knowledge, expectation, and aptitude of the decision maker into the Pythagorean membership function by using a weighting vector and induced variables. An application in financial knowledge based on a survey conducted in 13 provinces in Boyacá, Colombia, is presented.

En la actualidad el desarrollo de las pequeñas y medianas empresas (Pymes) en el mundo es un tema vital derivado del impacto económica y social que crean. Por ejemplo, estas aportan del 55% al 65% del total del Producto Interno Bruto (PIB) y generan del 60% al 70% del empleo (Keskġn et al., 2010; Zafar y Mustafa, 2017). Particularmente, en el caso de las economías en vías de desarrollo, situación de la mayoría de los países de Latinoamérica, las Pymes conforman alrededor del 99% de las empresas existentes en el mercado (Fjose y Grünfeld, 2010; Chege y Wang, 2020). Esta situación demuestra la importancia que tienen estas empresas dentro de los diferentes países, por lo que la formación de capacidades, habilidades y competencias para el manejo eficiente y efectivo de las mismas (St-Jean y Audet, 2012; Dobina et al., 2019).

Modelling and Simulation in Business, Economics and Management. Technological and Economic Development of Economy, 25(4), pp. 571-575.

The volatility is a dispersion technique widely used in statistics and economics. This paper presents a new way to calculate volatility by using different extensions of the ordered weighted average (OWA) operator. This approach is called the induced heavy ordered weighted moving average (IHOWMA) volatility. The main advantage of this operator is that the classical volatility formula only takes into account the standard deviation and the average, while with this formulation it is possible to aggregate information according to the decision maker knowledge, expectations and attitude about the future. Some particular cases are also presented when the aggregation information process is applied only on the standard deviation or on the average. An example in three different exchange rates for 2016 are presented, these are for: USD/MXN, EUR/MXN and EUR/USD.

Financial markets have been characterized in recent years by their uncertainty and volatility. The price of assets is always changing so that the decisions made by consumers, producers, and governments about different products is not still accurate. In this situation, it is necessary to generate models that allow the incorporation of the knowledge and expectations of the markets and thus include in the results obtained not only the historical information, but also the present and future information. The present article introduces a new extension of the ordered weighted averaging (OWA) operator called the Bonferroni probabilistic ordered weighted average (B-POWA) operator. This operator is designed to unify in a single formulation the interrelation of the values given in a data set by the Bonferroni means and a weighted and probabilistic vector that models the attitudinal character, expectations, and knowledge of the decision-maker of a problem. The paper also studies the main characteristics and some families of the B-POWA operator. An illustrative example is also proposed to analyze the mathematical process of the operator. Finally, an application to corn price estimation designed to calculate the error between the price of an agricultural commodity using the B-POWA operator and a leading global market company is presented. The results show that the proposed operator exhibits a better general performance than the traditional methods.