Unlocking innovation empowerment: how can industrial robots accelerate total factor productivity?

Abstract

Purpose Embodied intelligent robots are the iconic productivity of the Industry 4.0 era, and their potential to bring about a productivity surge mainly comes from the driving force of robots on innovation rather than efficiency. However, the dynamic impact of robots on the innovation capability of enterprises has not been empirically tested. Design/methodology/approach This study integrates panel vector autoregression and threshold effects to investigate this dynamic relationship by a multi-level analysis based on data of Chinese A-share manufacturing listed enterprises. Findings (1) The short-term momentum of industrial robot applications (IRA) on exploitative innovation (EII) is significant and the long-term momentum on exploratory innovation (ERI) is stronger. (2) EII affected by IRA is the main source of short-term total factor productivity (TFP) growth, while ERI is the driving factor for long-term TFP growth. (3) The impact of IRA on TFP exhibits a double-threshold effect based on ERI and follows a “stepped” incremental pattern. The promoting effect of IRA on TFP will significantly increase only when ERI surpasses certain thresholds. Originality/value Industrial robots accelerate the potential productivity growth in the long term, mainly coming from the augmented contribution of ERI, providing reference and inspiration for enterprises to fully utilize the endogenous growth potential of robots and implement innovation strategies. It also provides forward-looking guidance for organisations to undertake adaptive changes for the forthcoming AI economic revolution.