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Going digital: Disruption and transformation in software-intensive embedded systems ecosystems
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-7700-1816
Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.
2020 (English)In: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 32, no 6, article id e2249Article in journal (Refereed) Published
Abstract [en]

Digitalization is transforming industry to an extent that we have only seen the beginnings of. Across domains, companies experience rapid changes to their existing practices due to new technologies and new entrants that current businesses. While digitalization brings endless opportunities, it comes with challenges that require companies to strategically engage with partners in their surrounding ecosystems. In this paper, we study how companies in the embedded systems domain experience the process of transitioning from product-based companies to businesses where software, data, and artificial intelligence (AI) play an increasingly important role. To manage this, these companies need to evolve their existing ecosystems while at the same time create new ecosystems around new technologies. This involves maintaining existing technologies such as mechanics and electronics while at the same time expanding these with software, data, and AI. We provide a strategic decision framework that helps software-intensive embedded systems companies to successfully navigate the digital transformation. We do this in two steps. First, we present three models that provide the technical content of the strategic decision framework. Second, we provide an overview of the strategic alternatives that incumbents and new entrants have available when existing technologies are commoditizing and new technologies are introduced.

Place, publisher, year, edition, pages
John Wiley & Sons, 2020. Vol. 32, no 6, article id e2249
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:mau:diva-13832DOI: 10.1002/smr.2249ISI: 000506127200001Scopus ID: 2-s2.0-85078594530OAI: oai:DiVA.org:mau-13832DiVA, id: diva2:1416302
Available from: 2020-03-23 Created: 2020-03-23 Last updated: 2024-06-17Bibliographically approved

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Olsson, Helena Holmström

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