Data envelopment analysis method and neural networks in the evaluation and prediction of the technical efficiency of small exporting companies

In this research, a method was developed to evaluate and predict the efficiency of small exporting companies taking as input or asset variables the total assets, equity, total liabilities, operating expenses, sales costs and as output or result variables. net sales, net income and operating income. For this, the envelopment data analysis was used in the evaluation of the efficiency, the discriminant analysis in the evaluation of the classification of efficient and inefficient companies and the artificial neural networks to evaluate its capacity of classification prediction in 90 companies of the sector of the city of Barranquilla-Colombia. The results allowed to classify the companies according to level of efficiency showing an average technical efficiency of 41.38% of the sector with 11 representative companies of efficiency. The results show the relevance of the proposed methodology to correctly classify and forecast technical efficiency in small exporting companies. © Centro de Informacion Tecnologica. All rights reserved.

• Fecha de publicación: 2018
• Institución: Universidad Tecnológica de Bolívar
• Repositorio: Repositorio Institucional UTB
• Idioma: eng
• OAI Identifier: oai:repositorio.utb.edu.co:20.500.12585/8727
• Acceso en línea: https://hdl.handle.net/20.500.12585/8727
• Palabra clave: Artificial neural networks; Data envelopment analysis; Technical efficiency; Data envelopment analysis; Discriminant analysis; Forecasting; Neural networks; Classification prediction; Evaluation and predictions; Exporting companies; Net incomes; Net sales; Operating expense; Operating Income; Technical efficiency; Efficiency
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/