http://ijba.sciedupress.com International Journal of Business Administration Vol. 8, No. 1; 2017 Published by Sciedu Press 50 ISSN 1923-4007 E-ISSN 1923-4015 Study of Behavior of Human Capital from a Fractal Perspective Leydi Z. Guzmán-Aguilar 1 , Ángel Machorro-Rodríguez 2 , Tomás Morales-Acoltzi 3 , Miguel Montaño-Alvarez 1 , Marcos Salazar-Medina 2 & Edna A. Romero-Flores 2 1 Maestría en Ingeniería Administrativa, Tecnológico Nacional de México, Instituto Tecnológico de Orizaba, Colonia Emiliano Zapata, México 2 División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México, Instituto Tecnológico de Orizaba, Colonia Emiliano Zapata, México 3 Centro de Ciencias de la Atmósfera, UNAM, Circuito exterior, CU, CDMX, México Correspondence: Leydi Z. Guzmán-Aguilar, Maestría en Ingeniería Administrativa, Tecnológico Nacional de México, Instituto Tecnológico de Orizaba, Ver. Oriente 9 No. 852 Colonia Emiliano Zapata, C.P. 94320, México. Tel: 1-272-725-7518. Received: November 11, 2016 Accepted: November 27, 2016 Online Published: January 4, 2017 doi:10.5430/ijba.v8n1p50 URL: http://dx.doi.org/10.5430/ijba.v8n1p50 Abstract In the last decade, the application of fractal geometry has surged in all disciplines. In the area of human capital management, obtaining a relatively long time series (TS) is difficult, and likewise nonlinear methods require at least 512 observations. In this research, we therefore suggest the application of a fractal interpolation scheme to generate ad hoc TS. When we inhibit the vertical scale factor, the proposed interpolation scheme has the effect of simulating the original TS. Keywords: human capital, wage, fractal interpolation, vertical scale factor 1. Introduction In nature, irregular processes exist that by using Euclidean models as their basis for analysis, do not capture the variety and complexity of the dynamics of their environment. Owing to the need to develop methods more aligned to this behavior, Mandelbrot used a different approach to understand these irregularities in nature, consisting of fragments known as fractals (Mandelbrot, 1997). Use of the fractal geometric approach has grown exponentially over the past two decades. Its application ranges from economics (Mandelbrot, 1997), music (Perez, 2000), medicine (De la Rosa-Orea, 2014), topology (Vivas, 1999), physics (Aguirre 2004), astronomy (Martinez, 1999), meteorology (Morales-Acoltzi, 2015) and geology (Esper, 2005); recently, it has also been successfully introduced to the social sciences, for example psychology (Pestana, 1999), and more so, in everyday life it can be effectively applied to describe nature which surrounds us. In in the last decade, fractal geometry has been explicitly included in sciences of economic administration, as well as in areas of organization and business management, illustrating to entrepreneurs how company behavior is similar to that of a living entity which adapts to its environment (Iturriaga & Jovanovich, 2014). The human factor is the main element in management decisions. Because human capital is analyzed qualitatively, quantitative models have been proposed, such as that put forward by Iwamoto & Takahashi (2015) with data from their own company. In the second section of the study, the theoretical foundations of fractal geometry are presented. In the third section, we describe the database and methodology. The fourth section includes numerical experiments, results and conclusions. 2. Theoretical Basis The fractal approach comprises a modern mathematical area that improves on Euclidean geometry, describing irregularities in nature in terms of fragments that give rise to fractals. Auto-similarity and the fractal dimension are the main features (Williams, 1997). The first indicates that each entity retains the same format as its global characteristics. Fractals manifest an incomplete dimension which surpasses the topology of the figure under study (Braña, 2003), enabling a better description of the processes of nature. Two methods can be used to describe these; repeating a linear fractal process, and applying complex nonlinear fractal numbers, (Mandelbrot, 1997).