Enabling digital technologies adoption in industrial districts: The key role of trust and knowledge sharing
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In organizational contexts, trust mediates the relationship between system characteristics and user acceptance.
“In organizational contexts, trust becomes particularly salient as it mediates the relationship between system characteristics and user acceptance [31].”
From From Perception to Practice: Artificial Intelligence as a Pathway to Enhancing Digital Literacy in Higher Education Teaching (2025) · cites this paper as [31]
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- Authors
- Capestro, M., Rizzo, C., Kliestik, T., Peluso, A. M., & Pino, G.
- Affiliations
- University of Pavia (IT)
- University of Turin (IT)
- University of Salento (IT)
- University of Chieti-Pescara (IT)
- Corresponding author
- Rizzo, Cristian
- Venue
- Technological Forecasting and Social Change
- Publisher
- Elsevier BV
- Published
- 2024-01
- Volume
- 198
- Pages
- 123003
- ISSN
- 0040-1625 (ISSN-L)
- OpenAlex
- W4388745759
- Cited by
- 105
- References
- 120
- Citations by year
- 2026: 30 · 2025: 51 · 2024: 23 · 2023: 1
- FWCI
- 26.91
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Technological Forecasting and Social Change (publishedVersion)
- Institutional Research Information System University of Turin (University of Turin) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Ministry of Education Science Research and Sport of the Slovak Republic (NFP313010BWN6)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Communication › Knowledge Management and Sharing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Keywords
- digital technology adoption, industrial districts, cognitive trust, affective trust, tacit knowledge sharing, footwear industry, competitive advantage, organizational factors, technological factors
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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