Policy on the Efficient use of Robotics in the Automobile Parts Industry

Abstract

Globally, automobile companies are converting labor-intensive processes to automated processes to secure competitiveness and reduce costs. In 2020, Korea was the fifth largest automobile producer; however, it faced a population decline and rising labor costs. Korean auto parts companies are in a dilemma-whether to adopt manufacturing robots and have trouble due to financial burden or suffer the lack of technology. Hence, Korean auto parts companies often receive national policy funding to adopt manufacturing robots. Therefore, for sustainable policy support, the efficiency and productivity of manufacturing robot adoption must be analyzed considering government policy support. We divided the activities of automobile parts companies into operating activity and financing activity consisting of production and sales. Moreover, we used the Dynamic Network Slacks-Based Measure (DNSBM) model. This study used KIS-VALUE data from Korea. The analysis results revealed that the overall efficiency (0.3822) was low because of the low efficiency of operating activity productivity (0.4342) and the gap between operating activity productivity and financing activity efficiency (0.7702). Moreover, the total factor productivity (0.9534) decreased because of decreases in operating activity productivity (0.9507) and financing activity productivity (0.9841). From 2016 to 2020, when the manufacturing robot adoption policy was implemented, the difference in corporate efficiency according to policy support was significant. Korea’s manufacturing robot adoption policy contributes to the improvement of corporate competitiveness. This study presents the objective evidence necessary for future policy establishment to direct resource readjustment of Korean auto parts companies and analyze past policy.