Influence of Soft Skills on Employability in Large Companies in the Processing Industry, from a Management Perspective
Authors: Solís Blanca Angélica de la Concha , Mohedano Gisela Yamín Gómez , Torres Daniel Fragoso 
Published: January 2024

Purpose: The purpose of this research was to identify the relationship between soft skills and employability in large companies in the transformation sector in the state of Hidalgo. It was a quantitative, correlational, cross-sectional research. Owners or managers of 117 large companies in the transformation sector from 27 municipalities in the state of Hidalgo were interviewed. The results showed that managers perceive two types of soft skills related to employability: 1) analytical ability and reasoning and 2) intuition and experience. The factors that influence the first are the same reasonable and innovative thinking, however, it was also found that knowing one's own emotions is significant.
 
Theoretical Framework: Soft skills must be understood as the ability to carry out processes and be able to use knowledge in a responsible way to achieve an objective. Skills are part of a holistic concept of competence, which involves the mobilization of knowledge, skills, attitudes and values to meet complex demands (OECD, 2018). There are different types of skills, such as; cognitive and metacognitive skills, including critical thinking, creative thinking, learning to learn, and self-regulation. Social and emotional skills are defined, which include empathy, self-efficacy, responsibility and collaboration, as well as practical and physical skills, among others (OECD, 2018). The study references various authors who have addressed the relationship between these and employability. The literature review delves into the various studies on the matter.
 
Design/Methodology/Approach: A quantitative, correlational, cross-sectional research was carried out. The object of the study were large companies in the transformation sector of 27 municipalities in the state of Hidalgo.
 
Findings: A factor analysis was carried out to determine the soft skills with the highest factor loading, as well as those of employability. Through multiple regression analysis, it was identified that soft skills showed a significant relationship with each of the two factors found in employability (Anderson et al., 2012; Hair et al., 2019; Lind et al., 2012). The factors “Understanding the feelings of others and towards others and reasonable and innovative thinking” and “Knowing one's own emotions and feelings of others” obtained a positive coefficient, that is, both the understanding of the feelings of others, Reasonable and innovative thinking, as well as knowing one's own emotions and feelings of others, have a direct positive relationship with employability. Given that the coefficient of factor 2 is greater than that of factor 3 (0.388 > 0.133), superiors perceive that understanding the feelings of others and having reasonable and innovative thinking contributes more to employability, analytical capacity, reasoning and socialization, more than knowing one's own emotions and feelings of others. Also the “recognition, control and consequences of one's own emotions and creative thinking” was significant. The soft skills summarized in the factor defined as “creating assertive relationships and understanding the needs of others” were not significant for employability in either of the two multiple regression models.
Research, Practical & Social Implications: This research allows us to confirm, through inferential analysis, the influence of soft skills on employability, understood as transferable skills and qualifications that reinforce people's ability to take advantage of the education and training opportunities presented to them with a view to to find and keep decent work (International Labor Organization, 2019).
 
Originality/Value: The study provides a statistical model that confirms the relationship between soft skills and employability. Which benefits both employers and professionals in search of professional development.