Evolution of multivariate analysis methods in the field of management sciences

Abstract

Purpose: The evolution of multivariate analysis methods in the field of management sciences is presented, identifying both the current state and future trends that enable further development in business and administration studies.

Methodology: A systematic literature review was conducted on the topic, and the key aspects of the predominant analysis methods are discussed.

Results: the predominant methods are Regression Analysis, Structural Equation Modeling and Artificial Intelligence (AI). The results validate previous studies and highlight future trends.

Implications: The study explores future trends within AI such as the use of random forests, neural networks and the elastic network.

Originality: The evolution of multivariate analysis methods is presented, specifically for the field of management sciences and incorporates the trends of the last 25 years.