Prof. HU Yao Su2019-06-172019-06-172020Prometheus, Mar 2020, vol. 36(1), pp. 10-29.1470-1030http://hdl.handle.net/20.500.11861/5707https://www.jstor.org/stable/pdf/10.13169/prometheus.36.1.0010.pdf?refreqid=excelsior%3A9a8aa93f1c37d913eddb9379f49bb627Open AccessAllyn Young’s concept of increasing returns, not to be confounded with static, equilibrium constructs of economies of scale and increasing returns to scale, is applied in this article to analyze how and why increasing returns arise in the production (generation) and use (application) of knowledge and of big data, thereby driving economic growth and progress. Knowledge is chosen as our focus because it is ‘our most powerful engine of production’ and big data is included to make the analysis more complete and up-to-date. We analyze four mechanisms or sources of increasing returns in the production of knowledge, and four in the use of knowledge. Turning to big data, we analyze increasing returns in the functioning of digital platforms and increasing returns in machine learning from gigantic amounts of training data. Concluding remarks concern some key differences between big data and knowledge, some policy implications, and some of the social negative impacts from the ways in which big data is being used.enPeer Reviewed Journal Article