The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
How does the development of digital financial inclusion affect the total factor productivity of listed companies? Evidence from China
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“According to Chen et al. (2022), the development of digital financial inclusion requires a solid foundation of the traditional financial system to fully play its role [86].”
From Digital financial inclusion and quality of economic growth (2023) · cites this paper as [86]
Citations
Cites
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Cited by
Sorted by citations
Digital financial inclusion and quality of economic growth
Xi, W., & Wang, Y. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e19731 · Cited by 76
Metadata
- Authors
- Chen, Y., Yang, S., & Li, Q.
- Affiliations
- Nankai University (CN)
- Corresponding author
- Li, Quan
- ORCID
- Li, Quan
- Venue
- Finance Research Letters
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 47
- Pages
- 102956
- ISSN
- 1544-6123 (ISSN-L)
- OpenAlex
- W4229459429
- Cited by
- 149
- References
- 1
- Citations by year
- 2026: 15 · 2025: 47 · 2024: 42 · 2023: 41 · 2022: 4
- FWCI
- 32.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Finance research letters (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › FinTech, Crowdfunding, Digital Finance
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Digital Transformation in Financial Services
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Microfinance and Financial Inclusion
- Keywords
- digital financial inclusion, total factor productivity, listed companies, state-owned enterprises, financial constraints, micro and small enterprises, digital finance
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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.
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