Assessing and forecasting method of financial efficiency in a free industrial economic zone

Tomás José Fontalvo-Herrera, Enrique Delahoz-Dominguez and Orianna Fontalvo-Echavez

International Journal of Productivity and Quality Management, 2021, vol. 33, issue 2, 253-270

Abstract: Industrial free zones are key to the economic progress of developing countries, making the evaluation and forecast of efficiency in these organisations relevant. This research proposes a three-phase method to evaluate and forecast the financial efficiency of the business profiles of companies belonging to the free economic zone of Cartagena - Colombia. The first phase consisted of a cluster analysis to determine representative groups among the companies analysed. In the second phase, financial efficiency is measured for each of the clusters found in phase 1. Finally, in phase 3 a machine learning model is trained and validated to predict the belonging of a company to a category of financial efficiency - cluster. The results show the creation of two business clusters, with an average efficiency of 49.8% and 14.6% respectively. The random forest model has an accuracy of 95% in the validation phase.

Keywords: data envelope analysis; DEA; clustering; machine learning; random forest; efficiency. (search for similar items in EconPapers)
Date: 2021
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