The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Connection issues: a study on the limitations of knowledge transfer in Huawei’s African training centres
Abstract
Huawei has built several training centres across Africa. This study establishes the purpose of these centres in Kenya and Nigeria and presents original data on their success based on their objectives. Fieldwork was conducted in 2018 and follow-up interviews continued by phone until 2021. I find that Huawe’s investments offer no significant opportunities for knowledge transfers that could foster technological or industrial upgrading in Kenya or Nigeria’s telecommunications sectors. In part, this is due to domestic obstacles in the host countries. But, like other international equipment vendors operating in the region, knowledge transfers are also hindered by the limited scope of Huawei’s investments and the boundaries on the knowledge it is willing to share with domestic employees. I conclude that Kenya and Nigeria’s governments may underestimate the leverage they have over international equipment vendors to induce more meaningful opportunities for knowledge transfer.
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In the citing paper
“This finding corroborates Tugendhat (2021), who finds that Huawei's training centers in Kenya and Nigeria serve to establish a network of trained technicians, distributors, and salespeople qualified in Huawei technologies.”
From Learning along the Digital Silk Road? Technology transfer, power, and Chinese ICT corporations in North Africa (2024) · cites this paper as Tugendhat 2021
In the citing paper
“In Algeria and Egypt, both Chinese and non-Chinese firms are found to limit knowledge transfer by design to protect their technological edge (Tugendhat 2021).”
From Learning along the Digital Silk Road? Technology transfer, power, and Chinese ICT corporations in North Africa (2024) · cites this paper as Tugendhat 2021
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Cited by
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“In Algeria and Egypt, both Chinese and non-Chinese firms are found to limit knowledge transfer by design to protect their technological edge (Tugendhat 2021).”
BackgroundResultInfluential
Metadata
- Authors
- Tugendhat, H.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Tugendhat, Henry
- ORCID
- Tugendhat, Henry
- Venue
- Journal of Chinese Economic and Business Studies
- Publisher
- Informa UK Limited
- Published
- 2021-07-01
- Volume
- 19
- Issue
- 4
- Pages
- 359-385
- ISSN
- 1476-5284 (ISSN-L)
- 1476-5292
- OpenAlex
- W3174175083
- Cited by
- 13
- References
- 53
- Citations by year
- 2025: 3 · 2024: 4 · 2023: 2 · 2022: 3 · 2021: 1
- FWCI
- 2.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Chinese Economic and Business Studies (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Department for International Development, UK Government
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › International Business and FDI
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Business, Management and Accounting › Strategy and Management › Global trade, sustainability, and social impact
- Keywords
- knowledge transfer, Huawei, training center, telecommunications industry, industrial upgrading, technological upgrading, Kenya, Nigeria, Africa
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- CoChat. (2026). Citation check: Connection issues: a study on the limitations of knowledge transfer in Huawei’s African training centres. https://app.cochat.ai/papers/10.1080/14765284.2021.1943194
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- Tugendhat, H. (2021). Connection issues: a study on the limitations of knowledge transfer in Huawei’s African training centres. Journal of Chinese Economic and Business Studies. https://doi.org/10.1080/14765284.2021.1943194
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
