Amazon: A story of accumulation through intellectual rentiership and predation

This article elaborates on intellectual monopoly theory as a form of predation and rentiership using Amazon as a case study. By analysing Amazon's financial statements, scientific publications and patents, we show that Amazon's economic power heavily relies on its systematic innovations and capacity to centralize and analyse customized data that orients its business and innovations. We demonstrate how Amazon's innovation activities have evolved over time with growing importance of technologies related to data and machine learning. We also map Amazon's innovation networks with academic institutions and companies. We show how Amazon appropriates intellectual rents from these networks and from technological cooperation with other intellectual monopolies. We argue that Amazon, as other data-driven monopolies, predates value from suppliers and third-party companies participating in its platform. One striking characteristic of Amazon is the low rate of reported profits. The centrality of innovations leads us to suggest an alternative calculation that shows that Amazon's profits are not as low as they appear in Annual Reports. We also argue that lower profits are coherent with Amazon's rentiership and predatory strategy since they contribute to the avoidance of accusations of excessive market power. Finally, the paper offers preliminary observations on: (i) the complementarities between financial and intellectual rentierism and (ii) how data-driven intellectual monopoly expands big corporations' political power. Going beyond the specific case of Amazon, we thus contribute to a better understanding of the role of lead firms and power dynamics within innovation networks.

Automated summary

This article explores the concept of intellectual monopoly theory as a form of predation and rentiership through a case study of Amazon. By examining Amazon's financial statements, scientific publications, and patents, the study highlights the company's economic power derived from systematic innovations and its capacity to centralize and analyze customized data. The article also discusses Amazon's evolving innovation activities, particularly in the field of data and machine learning, and examines how the company appropriates intellectual rents from its innovation networks and collaborations with other intellectual monopolies. It argues that Amazon, like other data-driven monopolies, exploits value from suppliers and third-party companies participating in its platform. The article also raises the issue of Amazon's reported low profits and suggests an alternative calculation to demonstrate that the company's profits may not be as low as they appear. It proposes that lower profits align with Amazon's rentiership and predatory strategy as a means to avoid accusations of excessive market power. Additionally, the paper provides preliminary insights into the link between financial and intellectual rentierism, as well as the expansion of big corporations' political power through data-driven intellectual monopolies. Overall, the article contributes to a better understanding of lead firms and power dynamics within innovation networks.