Neoclassical economic growth model theory identifies technology as a key promotor of productivity and long-run economic growth. Theory and literature on the subject has grown significantly since Robert Solow's seminal work in 1956. Notwithstanding the substantial literature, gaps remain in several aspects, including the establishment of suitable metrics that can be applied to assess the impact and influence of certain technologies, and in particular industrial robots, on the modern economy.
Given these gaps in knowledge, the aim of this study was to support exploratory research that has found industrial robot density, as a proxy for technology and automation, to be a relevant metric that correlates with productivity and economic growth. Decision and policy makers aiming to improve manufacturing productivity and economic development should find this metric and the associated analysis beneficial in achieving a better understanding of forces that influence economic performance. This research was quantitative by design, and used inferential analysis of data from diverse countries. The suitability of industrial robot density as an econometric measure was tested with statistical methods.
Strong statistical correlations were found between industrial robot density, productivity and economic growth in the manufacturing sector. These findings supported existing growth theory quantitatively, while addressing limitations in previous research by using a larger sample that included developing countries for the first time.
Mini Dissertation (MBA)--University of Pretoria, 2017.