Working Paper No. 208. Institutional Ownership and Returns on Investment

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

Working paperPublication

Bjuggren, P.O. & Long, V.

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Publication year

2022

Published in

Bjuggren, P.O. & Long, V.

Abstract

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.

The openness of open innovation in ecosystems

Article (with peer review)Publication

Öberg, C., & Alexander, A.

Publication year

2019

Published in

Journal of Innovation & Knowledge

Abstract

Open innovation has rendered increased interest both in practice and research, and has expanded from dyadic transfers of ideas, to ecosystem levels. Knowledge is at the heart of open innovation, and this paper describes and discusses knowledge-transfer linkages for open innovation. It does so based on a literature review. The paper links together open innovation research with general management research to categorise and discuss linkages among parties in terms of their openness and how they relate to knowledge management. Conclusions indicate that openness needs to be considered in different dimensions that also links to different knowledge management outcomes. The paper’s contribution consists of how it connects open innovation research to the general management literature, and how it builds a practical understanding of how linkages between firms can be categorised to aid firms to consider which mechanisms they may choose and why.

The role of innovation metrics in innovation systems

Article (with peer review)Publication

Öberg, C.

Publication year

2020

Published in

International Journal of Innovation

Abstract

In innovation systems, venture firms, incubators and science parks may interact with universities to achieve commercialisable output. These various parties are connected to different guiding performance metrics — measures on each party’s performance — that influence their behaviours. This paper illustrates and discusses the role of performance metrics among various parties in innovation systems connected with early research ideas from universities. The empirical part of the paper is based on interviews with 20 researchers and 10 representatives of various innovation system organisations in an EU-based research project. The paper points out how parties in the innovation process saw different reasons to participate which were strongly connected with how each party was evaluated and which caused sub-optimisation in behaviours. Previous research on innovation systems has not focused on the rationales and behaviours of parties. The focus on metrics targets an important point for understanding innovation processes involving several parties and specifically doing so for support organisations that cannot be measured on revenues or profits.

Working Paper No. 208. Institutional Ownership and Returns on Investment

pob_je_dw_institutional_ownership_wp208

Abstract

Working Paper No. 208. Institutional Ownership and Returns on Investment

pob_je_dw_institutional_ownership_wp208

Abstract

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