A Study on the relationship between investment in education and training and smart factory level of manufacturing SMEs

Abstract

Smart Factories so far have achieved quantitative growth led by the government, but discussions are insufficient on how to promote the qualitative advancement of the supplied Smart Factory. This paper performs a binomial logistic regression to find the determinants of the level of Smart Factories focused on the investment of education and training by using the 2019 Workplace Panel Survey data of the Korea Labor Institute (KLI). The analysis results of the study show that the existence of a person (department) in charge, the pre-planning establishment, the annual average of training hours per person, the ratio of training participation, and training cost per person were not significant determinants of the level of Smart Factories. The main training contents seem to have a positive effect on the level of Smart Factories.