Metodología de Análisis Envolvente de Datos (DEA) - GLMNET para la Evaluación y Pronóstico de Eficiencia Financiera en una Zona Franca Industrial - Colombia.

Fontalvo, Tomás J.; Delahoz-Domínguez, Enrique; Olivos, S A Inversiones Monte de los

doi:10.4067/s0718-07642019000500263

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…Step 4. End more studies about the forecasting models, see Lim, 33 Fontalvo et al, 34 An and Zhai, 35 and Kafi et al 36 The concept of anchor point was used in DEA for the generation of unobserved DMUs in order to extend the DEA efficient frontier and so, this concept plays a critical role in the DEA theory and its applications. Hence, this study focuses on finding the anchor points in the different production possibility sets.…”

Section: Algorithmmentioning

confidence: 99%

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A new method based on finding the weak and strong defining supporting hyperplanes to recognize the anchor points

Khazaeyan

Sohraiee

Mostafaee

et al. 2022

Measurement and Control

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One of the main important issues in Data Envelopment Analysis (DEA) is to recognize the set of anchor points which is the subset of the extreme efficient points of the production possibility set (PPS). An anchor point is an extreme efficient point which is located on the intersection of the strong efficient frontier and the weak efficient frontier. In the other word, each anchor point delineate the strong efficient frontier from the weak efficient frontier. So, if a decision making unit (DMU) is an anchor point, then there is at least one supporting hyperplane whose the gradient vector has some of zero components, and so some input\output factor does not play any role in the performance of the unit under evaluation. The concept of anchor point was used in DEA for the generation of unobserved DMUs in order to extend the DEA efficient frontier and so, this concept plays a critical role in the DEA theory and its applications. Given the importance of the anchor pints in the DEA literature, this study focuses on finding the anchor points and presents a new method to search the anchor points of the PPS under the variable returns to scale (VRS) assumption. For this purpose, we use the definition of the anchor points and present an approach to find the anchor points of the PPS. The proposed method is based on finding the weak and strong defining supporting hyperplanes passing through the unit under evaluation. The main advantage of the proposed method is that it exactly uses the definition of the anchor points to provide the approach and it is very simple to use and the anchor points can be easily identified by solving two simple models. In addition, the proposed approach is such that in addition to determining the anchor points, it also finds two important defining supporting hyperplanes on the PPS, which can be used in many problems in DEA. The potentially of the proposed method is illustrated by some numerical examples, reported in the literature to compare the proposed method with the existing methods.

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Section: Algorithmmentioning

confidence: 99%

“…Their proposed model can capture non-linear features of the wind speed time series. For more studies about the forecasting models, see Lim, 33 Fontalvo et al, 34 An and Zhai, 35 and Kafi et al 36…”

Section: Introductionmentioning

confidence: 99%

A new method based on finding the weak and strong defining supporting hyperplanes to recognize the anchor points

Khazaeyan

Sohraiee

Mostafaee

et al. 2022

Measurement and Control

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“…En inves� gaciones similares otros autores han mostrado la per� nencia del análisis Evolvente de Datos con el machine learnig. (Fontalvo, et al, 2019) Table 4. Es� mación de los parámetros del modelo de regresión logís� ca En esta inves� gación se analizó la efi ciencia del sector inmobiliario de la ciudad de Cartagena, Colombia, ar� culando las técnicas de Análisis de Componentes Principales, Análisis Envolvente de Datos y Regresión Logís� ca.…”

Section: Modelo De Regresión Logís� Caunclassified

Real Estate Sector Efficiency Analysis

Herrera

Hoz

Granadillo³

2020

Dempresarial

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This research an analysis of the efficiency of the real estate sector of the city of Cartagena - Colombia is developed. For the 46 companies registered as real estate agencies in the city, the techniques of principal components, data envelopment analysis and logistic regression were articulated. The results show an average efficiency of the sector of 42.33%, considering 8 companies as efficient. Five hypotheses were raised about the incidence of each financial item in the efficiency result, evidenced through the logistic regression model how the variable Operational Income is the only significant one (Value-p = 0.028). It was evidenced as an efficient real estate company should not have high values in the items of heritage and plants, property and equipment.

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Analysis of the Financial Efficiency of Companies in the Industrial Sector during COVID-19: Case Study in Peru

Rivera

Origuela

Santivañez

2022

2022 IEEE World AI IoT Congress (AIIoT)

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Metodología de Análisis Envolvente de Datos (DEA) - GLMNET para la Evaluación y Pronóstico de Eficiencia Financiera en una Zona Franca Industrial - Colombia.

Cited by 5 publications

References 13 publications

A new method based on finding the weak and strong defining supporting hyperplanes to recognize the anchor points

A new method based on finding the weak and strong defining supporting hyperplanes to recognize the anchor points

Real Estate Sector Efficiency Analysis

Analysis of the Financial Efficiency of Companies in the Industrial Sector during COVID-19: Case Study in Peru

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