Belonging relationship of leaders’ multilevel skills for digital transformation

Purpose: The research objective is to identify the alignment and interdependence between the leaders’ skill levels for digital transformation (DT) in the metal-mechanical industrial sector. Design/methodology/approach: This research adopted an exploratory and quantitative approach, carried out based on a survey with the leaders of twenty-two industries associated with Sindimetal RS, totaling 201 respondents. The technique of Exploratory Factor Analysis (EFA) and multinominal logistic regression was applied to identify the relationship between skills at the individual, team, and organizational levels. Findings: The data obtained with the application of multinominal logistic regression demonstrate sufficient validity for the acceptance of the results considering the percentage of correctly classified cases and the relations of belonging of the leaders’ skills to the organizations’ DT. It is worth noting that the correlations between the organizational, team, and individual levels were evaluated and evidenced by the Spearman test, and the relationships between skills belonging to the lower/higher levels were analyzed by logistic regression demonstrating the existence of cyclical movement between the levels as a fundamental dynamic process in multilevel theory. Originality/value: For academic, organizational, and societal purposes, the multilevel study of skills can be reapplied in research aimed at other industries. As managerial contributions, the multilevel model of leaders’ skills for the industry’s DT will serve as a basis for analyses regarding self-assessments of skills already existing in industry leaders and will assist in identifying multilevel development needs.