![]() This conceptualisation brings to the forefront the power relations and multifaceted economic and social interactions within data governance models emerging in an environment mainly dominated by corporate actors. Addressing the politics of data, we considered the actors’ competitive struggles for governing data. Drawing from the notion of data infrastructure we identify the models as a function of the stakeholders’ roles, their interrelationships, articulations of value, and governance principles. We propose a social science-informed conceptualisation of data governance. The article sheds light on four models emerging from the practices of these actors: data sharing pools, data cooperatives, public data trusts and personal data sovereignty. While major attention is currently given to the dominant model of corporate platforms collecting and economically exploiting massive amounts of personal data, other actors, such as small businesses, public bodies and civic society, take also part in data governance. The article examines four models of data governance emerging in the current platform society. We conceptualize this strategy as a form of "techcraft" to center attention on the means and mechanisms that Big Tech firms deploy to make users and user data measurable and legible as future revenue streams. However, our findings show that Big Tech firms turn "users" and "user engagement" into assets through the performative measurement, governance, and valuation of user metrics (e.g., user numbers, user engagement), rather than extending ownership and control rights over personal data per se. We analyse the transformation of personal data into an asset in order to explore how personal data is accounted for, governed, and valued by Big Tech firms and other political-economic actors (e.g., investors). These US-based firms are some of the largest in the world by market capitalization, a position that they retain despite growing policy and public condemnation-or "techlash"-of their market power based on their monopolistic control of personal data. ![]() Control over these data assets seems to explain the emergence and dominance of so-called "Big Tech" firms, consisting of Apple, Microsoft, Amazon, Google/Alphabet, and Facebook. The article can be seen as a novel attempt as it empirically proves that FAANG has grown faster due to the power of surveillance capitalism.ĭigital personal data is increasingly framed as the basis of contemporary economies, representing an important new asset class. ![]() This paper also illuminates the nudging effect created by behaviour-centric advertisements, which results in the brand value appreciation of FAANG. Our undertaking shows that FAANG earns substantial revenue through data-driven business models catalysing the present companies' growth. ![]() Financial indicators like the EPS, ROE, Market Capitalization and ROA were used to capture the growth of FAANG. The relative valuation models were used to substantiate the exponential growth of FAANG companies from 2006 to 2020. A triangulation approach was used to observe the world of surveillance capitalism through multiple lenses. The fundamental research question is how the data-driven models trigger these companies’ future financial performance and ensure sustainable growth. This paper maps the idea of surveillance capitalism of FAANG (Facebook, Apple, Amazon, Netflix, and Google), which have capitalised on the behavioural surplus accumulated in their databases and how they utilise this data for future business models. ![]()
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