Managerial challenges of Industry 4.0: an empirically backed research agenda for a nascent field
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Development of innovative digitalization solutions requires significant investment, appropriate staff, and time, which may be difficult for SMEs to overcome.
“It is obvious that the development of innovative solutions in the field of digitalization requires significant investment, appropriate staff, and time, which may prove to be difficult to overcome for SMEs [75,76].”
From Digitalization of Small and Medium-Sized Enterprises and Economic Growth: Evidence for the EU-27 Countries (2022) · cites this paper as [75]
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Industry 4.0 and Knowledge Management: A Review of Empirical Studies
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Desafíos de la Transformación Digital en las PYMES
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Towards Smart Specialisation 2.0. Main Challenges When Updating Strategies
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- Authors
- Schneider, P.
- Affiliations
- University of Cologne (DE)
- Corresponding author
- Schneider, Paul
- ORCID
- Schneider, Paul
- Venue
- Review of Managerial Science
- Published
- 2018-04-20
- Volume
- 12
- Issue
- 3
- Pages
- 803-848
- ISSN
- 1863-6683 (ISSN-L)
- 1863-6691
- OpenAlex
- W2802944856
- Cited by
- 345
- References
- 139
- Citations by year
- 2026: 8 · 2025: 27 · 2024: 47 · 2023: 55 · 2022: 51 · 2021: 78 · 2020: 46 · 2019: 26 · 2018: 7
- FWCI
- 32.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Review of Managerial Science (publishedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Digital Innovation in Industries
- Keywords
- Industry 4.0, management problems, research agenda, planning and implementation, business models, human resources, value creation networks, expert survey, management research
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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