Evaluating the Efficiency of Human Capital at Small and Medium Enterprises in the Manufacturing Sector Using the DEA-Weight Russell Directional Distance Model

Abstract

The present research aims to analyze the efficiency of human capital in relation to sales in each of the subsectors of economic activity within Mexican small- and medium-sized enterprises in the manufacturing industry. To accomplish this, a panel data set covering the years 2009–2020 is utilized. The inputs used are investment in training, salary, and days worked, with sales as the output. Initially, due to the high variability (cv > 1) of both the inputs and the output, the information is divided into three groups by quartiles: Group 1 < 25%, Group 2 = 25–75%, and Group 3 > 75%. As a first step in the analysis, a hypothesis test identifies a significant increase in sales for those subsectors that reported investing in training compared with those that did not. As a result, for the efficiency analysis, SMEs that report not investing in training are removed from the sample. Subsequently, to confirm the statistical explanation of the inputs for the output, a regression analysis is performed. With an input-oriented DEA model, it is found that most subsectors exhibit high overall and pure efficiency (≥0.75) as well as increasing returns to scale. Interestingly, the research introduces a novel approach by proposing subgroups within SMEs, providing a more precise analysis. The findings of this study emphasize the fundamental role of human capital as a key driver of economic growth and innovation within the manufacturing sector. This research also highlights variations in efficiency among different subsectors, underscoring the need for tailored strategies for each. These results offer practical guidance for companies seeking to optimize their operations and contribute to the economic development of a developing country. In conclusion, this paper contributes both theoretically and practically to understanding the interaction between human capital and financial indicators. The results underscore the importance of investing in workforce development, ultimately promoting economic growth, improving productivity, and advancing social progress.