Determination through neural networks of the standard performance of management indicators in the construction industry
DOI:
https://doi.org/10.21678/jb.2020.1414Palabras clave:
Management indicators, standardization, artificial neural networks, decision-makingResumen
Business management requires information for decision-making, and, therefore, tools that aid in the analysis of that information, with support systems whose purpose is to help managers to identify trends, signal problems, and make intelligent decisions.
For several decades, different economic models and statistical techniques have been used to analyze past performance or to forecast the future of business management indicators. To analyze results, businesses make comparisons with past periods, with other organizations, or with the mean for the industry to which they pertains but there is still uncertainty as to whether business management results are optimal or not given the lack of comparative analysis by way of target parameters.
The purpose of this study is to determine the standardized performance of management indicators, so as to enable comparative evaluation of business results and guide future performance under certain specific conditions, grounding management decision-making.
Artificial neural networks (ANNs) are used as tools for standardization and comparison of the results.
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Journal of Business publica todos sus artículos y reseñas bajo la licencia Creative Commons Attribution (CC BY 4.0) con el objetivo de fomentar el intercambio académico a nivel mundial. Por ello, la obra en cuestión puede ser distribuida, remezclada, retocada, etc., como el autor y los lectores de la misma lo estimen conveniente. La única condición es que se cite a la revista Apuntes, revista de Ciencias Sociales como entidad editora del texto.

