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Unraveling perceptions of barriers to digital transformation: contrasting small and medium-sized with large enterprises
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Data Society.ORCID iD: 0000-0002-3488-708X
Osnabruck Univ, Org & Informat Syst, Osnabruck, Germany..
Osnabruck Univ, Org & Informat Syst, Osnabruck, Germany..
2023 (English)In: IADIS International Journal on Computer Science and Information Systems, E-ISSN 1646-3692, Vol. 18, no 1, p. 102-119Article in journal (Refereed) Published
Abstract [en]

With the proliferation of contemporary digital technologies, Digital Transformation (DT) has become a significant theme for companies across almost all industries. DT encompasses the digitalization of internal processes, the provision of digital services and products, and the enhancement of the customer experience. Previous research has delved into different barriers that impede successful DT. In our study, we investigate further how these barriers are perceived by employees at small and medium-sized enterprises (SMEs) in contrast to larger enterprises (LEs). We employ a mixed-methods approach by performing a quantitative analysis using the Means, Mann-Whitney U test with effect size and integrating it with qualitative results converted into frequencies. Our empirical data consist of two samples consisting of participants from 189 SMEs and 221 LEs for quantitative analysis and participants from 238 SMEs and 281 LEs for qualitative analysis. Overall, the results suggest a relatively similar perception of DT processes, indicating culture and structure as major barriers. However, the establishment of resources dedicated to managing DT emerges as a vaster barrier for SMEs than for LEs. At the same time, SMEs face fewer barriers regarding general personnel resources.

Place, publisher, year, edition, pages
IADIS Press, 2023. Vol. 18, no 1, p. 102-119
Keywords [en]
Digital Transformation, Barriers, Small and Medium-Sized Enterprise (SME), Large Enterprise (LE), Mixed-Methods
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mau:diva-65624ISI: 001128423200001OAI: oai:DiVA.org:mau-65624DiVA, id: diva2:1833715
Available from: 2024-02-01 Created: 2024-02-01 Last updated: 2024-03-04Bibliographically approved

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Packmohr, Sven

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Citation style
  • apa
  • ieee
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