Cited by 289E-Government and Public ServicesPublic Policy and Administration ResearchSmart Cities and Technologies

Know-how to lead digital transformation: The case of local governments

Open access
Pittaway, Jeffrey J., Montazemi, Ali Reza·2020·Government Information Quarterly

Integrity signals

Registry

Crossref · 10.1016/j.giq.2020.101474

Cites

89 of 89 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

4 of the 93 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Pittaway, J. J., & Montazemi, A. R.
Affiliations
McMaster University (CA)
Venue
Government Information Quarterly
Publisher
Elsevier BV
Published
2020-10
Volume
37
Issue
4
Pages
101474
ISSN
0740-624X (ISSN-L)
OpenAlex
W3022446025
Cited by
289
References
93
Citations by year
2026: 66 · 2025: 72 · 2024: 67 · 2023: 40 · 2022: 29 · 2021: 13 · 2020: 2
FWCI
67.51
Type
journal article
Language
en
Open access
Locations
  • Government Information Quarterly (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion, other-oa)
Funders
Engineering and Physical Sciences Research Council
Topics
  • Social Sciences › Political Science and International Relations › E-Government and Public Services
  • Social Sciences › Public Administration › Public Policy and Administration Research
  • Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
Keywords
digital transformation, local government, public service delivery, public-private partnerships, knowledge transfer, digital public services, barriers to digitalization

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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