Assessing the Efficiency of Foreign Investment in a Certification Procedure Using an Ensemble Machine Learning Model

Aleksandar Kemiveš, Lidija Barjaktarović, Milan Ranđelović, Milan Čabarkapa and Dragan Ranđelović ()
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Aleksandar Kemiveš: Department for Postgraduate Studies, Singidunum University, 11000 Belgrade, Serbia
Lidija Barjaktarović: Singidunum University, 11000 Belgrade, Serbia
Milan Ranđelović: Science Technology Park Niš, 18104 Niš, Serbia
Milan Čabarkapa: Faculty of Engineering, University of Kragujevac, 34000 Kragujevac, Serbia
Dragan Ranđelović: Faculty of Diplomacy and Security, University Union-Nikola Tesla Belgrade, 11000 Beograd, Serbia

Mathematics, 2024, vol. 12, issue 7, 1-26

Abstract: Many methods exist for solving the problem of evaluating efficiency in different processes. They are divided into two basic groups, parametric and non-parametric methods, which can have significant differences in the results. In this study, the authors consider the process of assessing the business climate depending on realized foreign investments. Due to the expected difference in efficiency assessment using different approaches, the goal of this paper is to create an optimization model of an ensemble for efficiency assessment that uses both types of methods with the aim of creating a symmetrical approach that achieves better results than each type of method individually. The proposed solution simultaneously analyzes the impact of different factors on foreign investments in order to determine the most important factors and thus enable each local government to ensure the best possible efficiency in this process. The innovative idea of this study is in the inclusion of classification and feature selection methods of machine learning to fulfill the set goal. Our research, focused on a specific case study in various cities across the Republic of Serbia, evaluated the effectiveness of that process. This study extends previous research and confirms the published results, highlighting the advantages of the newly proposed model.

Keywords: foreign investments; DEA; SFA; ensemble model; data classification; efficiency analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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