Working Paper No. 355: The artificial intelligence (AI) data access regime: what are the factors affecting the access and sharing of industrial AI data?

PublicationWorking paper
Artificial Intelligence, Data trade, Governance structure, Intellectual Property Rights (IPRs), Per-Olof Bjuggren, Vicky Long
Ratio Working Paper 355


This paper decomposes the factors that govern the access and sharing of machine-generated industrial data in the artificial intelligence era. Through a mapping of the key technological, institutional, and firm-level factors that affect the choice of governance structures, this study provides a synthesised view of AI data-sharing and coordination mechanisms. The question to be asked here is whether the hitherto de facto control—bilateral contracts and technical solution-dominating industrial practices in data sharing—can handle the long-run exchange needs or not.

Bjuggren, P.O. & Long, V. The artificial intelligence (AI) data access regime: what are the factors affecting the access and sharing of industrial AI data?. Ratio Working Paper No. 355. Stockholm: Ratio.

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Smaller is smarter: A case for small to medium-sized smart cities
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Profiting from Innovation in the Digital Era: Evidence from the Swedish Videogames Industry
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We know that firms use multiple appropriability means: intellectual property rights (IPRs), trade secrecy, market lead-time, and this varies significantly between industry sectors. We, however, do not know how and to what extent the appropriability regime are modified in response to digitalization and open innovation. This study aims to fill in that gap, through a study of the Swedish games industry. Applying a well-established framework — Profiting from Innovation — to the digital context, this study collects primary data from semi-structured (firm) interviews, a survey and combining the statistical data from the branch organization and from EUIPO trademark database. It has been identified that: (a) this is an industry re-entering into a fluid phase of innovation with a rapid growth of products and (small) firms; (b) the value chains are transforming into value networks and the complementary assets are to be reassessed; and (c) trademarks are gaining importance and a Demsetz-ian path of internalization of IPs is pursued. Digitalization re-defines the key pillars of the PFI framework in many respects.

Long, V. (2020). Profiting from innovation in the digital era: Evidence from the Swedish videogames industry. In Managing Digital Open Innovation (pp. 141-175).

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Industrial transformation is a research and teaching field with a focus on the phenomenon and mechanisms of industrial development and renewal. It concerns changes in economic activities caused by innovation, competition and collaboration, and has a rich heritage of evolutionary economics, institutional economics, industrial dynamics, technology history and innovation studies. It borrows concepts and models from the social sciences (sociology, history, political sciences, business/management, economics, behavioural sciences) and also from technology and engineering studies.
In this book, the authors present the key theories, frameworks and concepts of industrial transformation and use empirical cases to describe and explain the causes, processes and outcomes of transformation in the context of digitalization and sustainability. They stress that industrial transformation consists both of Darwinian “survival of the fittest” selection, and of intentional pursuits of innovation, and of industrial capabilities creation. The work argues that managing the global trends of transformation is not only about new technology and innovation: existing institutional settings and dynamic interactions between technological change, organizational adaptation and economic activities also have a profound impact on future trajectories.
The areas under investigation are of great relevance for strategic management decisions and industrial and technology policies, and understanding the mechanisms underlying transformation and sustainable growth.

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