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Cited by 365

The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.

Talent management: context matters

Open access
Gallardo-Gallardo, Eva, Thunnissen, Marian, Scullion, Hugh·2020·The International Journal of Human Resource Management

Abstract

There is little doubt that the attraction, development, and retention of talent are nowadays one of the most critical challenges faced by companies worldwide. Despite the increasing scholarly attention during the last years many questions remain, particularly, those related to how (and why) talent management (TM) is conceived, implemented and developed within organizations, not to mention about its outcomes or effectiveness. We argue that organizational context has been underappreciated in TM research, which is an omission since context affects the occurrence, meaning and implementation of TM. Therefore, we edited a special issue which seeks to contribute to advance our knowledge of how contextual factors affect the conceptualization, implementation and effectiveness of TM. In this opening article, we offer a brief overview of how context is integrated in previous TM research. We then introduce the four articles in this special issue and their contributions which addresses gap in TM research and, finally, we offer some suggestions on how to improve contextualized TM research.

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Metadata

Authors
Gallardo-Gallardo, E., Thunnissen, M., & Scullion, H.
Venue
The International Journal of Human Resource Management
Published
2019-07-19
Volume
31
Issue
4
Pages
457-473
ISSN
  • 0958-5192 (ISSN-L)
  • 1466-4399
OpenAlex
W2963497020
Cited by
365
References
66
FWCI
36.68
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Talent management: context matters. https://app.cochat.ai/papers/10.1080/09585192.2019.1642645
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Gallardo-Gallardo, E., Thunnissen, M., & Scullion, H. (2020). Talent management: context matters. The International Journal of Human Resource Management. https://doi.org/10.1080/09585192.2019.1642645

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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.