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Comparing barriers to digital transformation between small and medium-sized and large enterprises
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-3488-708X
Osnabrück University, Organization and Information Systems, Katharinenstr. 1, 49069 Osnabrück, Germany.
2023 (English)In: Proceedings of the International Conferences on E-society 2023 and Mobile Learning 2023 / [ed] Piet Kommers; Inmaculada Arnedillo Sánchez; Pedro Isaías, IADIS Press, 2023Conference paper, Published paper (Refereed)
Abstract [en]

With the rise of modern digital connectivity technologies, Digital Transformation (DT) is now an issue for most companies across almost all industries. DT is an evolution to digitalizing internal processes, offering digital services and products, and improving the customer experience. Prior studies have explored different barriers that hinder successful DT. Our study follows a quantitative design to explore further how these barriers are perceived by staff at small and medium-sized enterprises (SMEs) compared to larger enterprises (LEs). Our sample comprises participants from 189 SMEs and 221 LEs. In general, results indicate a somewhat similar perception of their DT processes. In detail, setting up new positions to manage DT poses a more intense barrier for SMEs.

Place, publisher, year, edition, pages
IADIS Press, 2023.
Keywords [en]
Digital Transformation, Small and Medium-Sized Enterprises, Large Enterprises
National Category
Information Systems
Identifiers
URN: urn:nbn:se:mau:diva-70133Scopus ID: 2-s2.0-85174436152ISBN: 978-989-8704-47-4 (electronic)OAI: oai:DiVA.org:mau-70133DiVA, id: diva2:1888049
Conference
21st International Conference on e-Society, ES 2023 and 19th International Conference on Mobile Learning, ML 2023; Lisbon, Portugal; 11-1 3March 2023
Available from: 2024-08-12 Created: 2024-08-12 Last updated: 2024-08-18Bibliographically approved

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Packmohr, Sven

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