Measuring dynamic inefficiency through machine learning techniques

Aparicio, Juan; Esteve, Miriam; Kapelko, Magdalena

doi:10.1016/j.eswa.2023.120417

Cited by 2 publications

(1 citation statement)

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“…The corrective action is used in the form of an ensemble, and expert knowledge or the multi-stage method is used to achieve better results. Currently, the most modern approach is the discovery of knowledge from data using machine learning (ML)-based methods [8][9][10][11]. One well-known method is the classification of different types of algorithms, which enables feature selection (i.e., significant factors) and, due to the dimensionality reduction, allows for the optimization of a selected procedure, thus providing better results [12].…”

Section: Introductionmentioning

confidence: 99%

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

Kemiveš,

Barjaktarović,

Ranđelović

et al. 2024

Mathematics

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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.

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