Cited by 56

Retaining talent in knowledge-intensive services: enhancing employee engagement through human resource, knowledge and change management

Kossyva, Dorothea, Theriou, Georgios, Aggelidis, Vassilis, Sarigiannidis, Lazaros·2024·Journal of Knowledge Management

Abstract

Purpose: This study aims to explore talent retention in knowledge-intensive industries by investigating the mediating processes between the existence and application of human resource management (HRM) and employee turnover. Toward this end, drawing on the conservation of resources and job demands–resources theories, a three-dimensional model is examined, which includes the relationship between HRM, knowledge management (KM) and change management (CM), as well as their relationship with employee engagement and employee turnover intention. Design/methodology/approach: The proposed research model has been studied with a sample of 168 talented employees in over six European countries, using a quantitative approach, involving the structural equation modeling method. All data were gathered by a multidimensional questionnaire via prolific, an academic crowdsourcing platform. Findings: Results indicated that knowledge-intensive services firms may achieve higher talent retention through the interaction of HRM with KM and CM practices, which may lead to enhanced employee engagement. Research limitations/implications: Possible limitations of the study include the relatively small sample size, the self-rate questions for the collection of data and the use of cross-sectional data. Practical implications: To retain their talented employees, organizations should identify ways to improve their HRM, CM and KM practices. In addition, HR practitioners ought to include their talented employees in all organizational change and KM processes and create mechanisms that successfully support knowledge acquisition, creation, sharing, retention and codification. Originality/value: To the best of the authors’ knowledge, this is the first study to examine various factors of retaining talented employees in knowledge-intensive services. Furthermore, the study took place in six European countries, i.e. UK, Poland, Italy, Germany, Portugal and Greece, where the research on talent retention is very limited.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1108/jkm-03-2022-0174

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Authors
Kossyva, D., Theriou, G., Aggelidis, V., & Sarigiannidis, L.
Venue
Journal of Knowledge Management
Publisher
Emerald
Published
2023-05-25
Volume
28
Issue
2
Pages
409-439
ISSN
1367-3270
Cited by
56
References
4
Language
en

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 ›

Are you an author, or do you see a problem with this page? Request a review