Impact of robotics on manufacturing: A longitudinal machine learning perspective

Abstract

The evaluation of the impact of the adoption of industrial robotics on business is increasingly relevant in the current context of digital transformation. Although many companies are eager to adopt these technologies as a means to increase productivity, some concerns have been raised about the cost impact of the transformation, and its effect on the workforce.

A growing body of literature is studying these phenomena but according to our review of it, there is no longitudinal perspective over 25 years illustrating the relationship between the attitude of companies to robotics and principal business indicators.

This investigation uses an innovative machine learning model comprising an automated nested longitudinal clustering performed in two stages, and it is applied over a large sample of 4,578 companies from the Business Strategy Survey conducted by the Spanish Ministry of Finance and Public Administration.

The findings of this research are novel in this field not only because of the longitudinal modelling applied in two stages but also because of the understanding of how companies’ characteristics and performance evolve over time depending on their degree of adoption of robotics. This knowledge is relevant for companies to understand the impact of their transformation to robotics. It also allows for the development of strategies that boost the efficiency of the companies, provides them with tools to protect them from negative financial events, and leads to an optimal sizing of their workforce.